Sample records for detect polypharmacological targets
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Durrant, Jacob D; Amaro, Rommie E; Xie, Lei; Urbaniak, Michael D; Ferguson, Michael A J; Haapalainen, Antti; Chen, Zhijun; Di Guilmi, Anne Marie; Wunder, Frank; Bourne, Philip E; McCammon, J Andrew
2010-01-22
Conventional drug design embraces the "one gene, one drug, one disease" philosophy. Polypharmacology, which focuses on multi-target drugs, has emerged as a new paradigm in drug discovery. The rational design of drugs that act via polypharmacological mechanisms can produce compounds that exhibit increased therapeutic potency and against which resistance is less likely to develop. Additionally, identifying multiple protein targets is also critical for side-effect prediction. One third of potential therapeutic compounds fail in clinical trials or are later removed from the market due to unacceptable side effects often caused by off-target binding. In the current work, we introduce a multidimensional strategy for the identification of secondary targets of known small-molecule inhibitors in the absence of global structural and sequence homology with the primary target protein. To demonstrate the utility of the strategy, we identify several targets of 4,5-dihydroxy-3-(1-naphthyldiazenyl)-2,7-naphthalenedisulfonic acid, a known micromolar inhibitor of Trypanosoma brucei RNA editing ligase 1. As it is capable of identifying potential secondary targets, the strategy described here may play a useful role in future efforts to reduce drug side effects and/or to increase polypharmacology.
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Chiu, Yi-Yuan; Lin, Chun-Yu; Lin, Chih-Ta; Hsu, Kai-Cheng; Chang, Li-Zen; Yang, Jinn-Moon
2012-01-01
To discover a compound inhibiting multiple proteins (i.e. polypharmacological targets) is a new paradigm for the complex diseases (e.g. cancers and diabetes). In general, the polypharmacological proteins often share similar local binding environments and motifs. As the exponential growth of the number of protein structures, to find the similar structural binding motifs (pharma-motifs) is an emergency task for drug discovery (e.g. side effects and new uses for old drugs) and protein functions. We have developed a Space-Related Pharmamotifs (called SRPmotif) method to recognize the binding motifs by searching against protein structure database. SRPmotif is able to recognize conserved binding environments containing spatially discontinuous pharma-motifs which are often short conserved peptides with specific physico-chemical properties for protein functions. Among 356 pharma-motifs, 56.5% interacting residues are highly conserved. Experimental results indicate that 81.1% and 92.7% polypharmacological targets of each protein-ligand complex are annotated with same biological process (BP) and molecular function (MF) terms, respectively, based on Gene Ontology (GO). Our experimental results show that the identified pharma-motifs often consist of key residues in functional (active) sites and play the key roles for protein functions. The SRPmotif is available at http://gemdock.life.nctu.edu.tw/SRP/. SRPmotif is able to identify similar pharma-interfaces and pharma-motifs sharing similar binding environments for polypharmacological targets by rapidly searching against the protein structure database. Pharma-motifs describe the conservations of binding environments for drug discovery and protein functions. Additionally, these pharma-motifs provide the clues for discovering new sequence-based motifs to predict protein functions from protein sequence databases. We believe that SRPmotif is useful for elucidating protein functions and drug discovery.
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DEFF Research Database (Denmark)
Narayanan, Dilip; Gani, Osman ABSM; Gruber, Franz XE
2017-01-01
encoded into molecular mechanics force fields. Cheminformatics analyses of binding data show EGFR to be dissimilar to ALK and MET, but its structure shows how it may be co-targeted with the addition of a covalent trap. This suggests a strategy for the design of a focussed chemical library based on a pan......Drug design of protein kinase inhibitors is now greatly enabled by thousands of publicly available X-ray structures, extensive ligand binding data, and optimized scaffolds coming off patent. The extensive data begin to enable design against a spectrum of targets (polypharmacology); however...... consider polypharmacological targeting of protein kinases ALK, MET, and EGFR (and its drug resistant mutant T790M) in non small cell lung cancer as an example. Both EGFR and ALK represent sources of primary oncogenic lesions, while drug resistance arises from MET amplification and EGFR mutation. A drug...
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Al-Ali, Hassan; Lee, Do-Hun; Danzi, Matt C.; Nassif, Houssam; Gautam, Prson; Wennerberg, Krister; Zuercher, Bill; Drewry, David H.; Lee, Jae K.; Lemmon, Vance P.; Bixby, John L.
2016-01-01
Mammalian Central Nervous System (CNS) neurons regrow their axons poorly following injury, resulting in irreversible functional losses. Identifying therapeutics that encourage CNS axon repair has been difficult, in part because multiple etiologies underlie this regenerative failure. This suggests a particular need for drugs that engage multiple molecular targets. Although multi-target drugs are generally more effective than highly selective alternatives, we lack systematic methods for discovering such drugs. Target-based screening is an efficient technique for identifying potent modulators of individual targets. In contrast, phenotypic screening can identify drugs with multiple targets; however, these targets remain unknown. To address this gap, we combined the two drug discovery approaches using machine learning and information theory. We screened compounds in a phenotypic assay with primary CNS neurons and also in a panel of kinase enzyme assays. We used learning algorithms to relate the compounds’ kinase inhibition profiles to their influence on neurite outgrowth. This allowed us to identify kinases that may serve as targets for promoting neurite outgrowth, as well as others whose targeting should be avoided. We found that compounds that inhibit multiple targets (polypharmacology) promote robust neurite outgrowth in vitro. One compound with exemplary polypharmacology, was found to promote axon growth in a rodent spinal cord injury model. A more general applicability of our approach is suggested by its ability to deconvolve known targets for a breast cancer cell line, as well as targets recently shown to mediate drug resistance. PMID:26056718
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Directory of Open Access Journals (Sweden)
Stefania Monteleone
2017-08-01
Full Text Available Dark chemical matter compounds are small molecules that have been recently identified as highly potent and selective hits. For this reason, they constitute a promising class of possible candidates in the process of drug discovery and raise the interest of the scientific community. To this purpose, Wassermann et al. (2015 have described the application of 2D descriptors to characterize dark chemical matter. However, their definition was based on the number of reported positive assays rather than the number of known targets. As there might be multiple assays for one single target, the number of assays does not fully describe target selectivity. Here, we propose an alternative classification of active molecules that is based on the number of known targets. We cluster molecules in four classes: black, gray, and white compounds are active on one, two to four, and more than four targets respectively, whilst inactive compounds are found to be inactive in the considered assays. In this study, black and inactive compounds are found to have not only higher solubility, but also a higher number of chiral centers, sp3 carbon atoms and aliphatic rings. On the contrary, white compounds contain a higher number of double bonds and fused aromatic rings. Therefore, the design of a screening compound library should consider these molecular properties in order to achieve target selectivity or polypharmacology. Furthermore, analysis of four main target classes (GPCRs, kinases, proteases, and ion channels shows that GPCR ligands are more selective than the other classes, as the number of black compounds is higher in this target superfamily. On the other side, ligands that hit kinases, proteases, and ion channels bind to GPCRs more likely than to other target classes. Consequently, depending on the target protein family, appropriate screening libraries can be designed in order to minimize the likelihood of unwanted side effects early in the drug discovery process
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Polypharmacology of Approved Anticancer Drugs.
Amelio, Ivano; Lisitsa, Andrey; Knight, Richard A; Melino, Gerry; Antonov, Alexey V
2017-01-01
The major drug discovery efforts in oncology have been concentrated on the development of selective molecules that are supposed to act specifically on one anticancer mechanism by modulating a single or several closely related drug targets. However, a bird's eye view on data from multiple available bioassays implies that most approved anticancer agents do, in fact, target many more proteins with different functions. Here we will review and systematize currently available information on the targets of several anticancer drugs along with revision of their potential mechanisms of action. Polypharmacology of the current antineoplastic agents suggests that drug clinical efficacy in oncology can be achieved only via modulation of multiple cellular mechanisms. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
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Ma, Xiaodong; Lv, Xiaoqing; Zhang, Jiankang
2018-01-01
Polypharmacology has been increasingly advocated for the therapeutic intervention in complex pathological conditions, exemplified by cancer. Although kinase inhibitors (KIs) have revolutionized the treatment for certain types of malignancies, some major medical needs remain unmet due to the relentless advance of drug resistance and insufficient efficacy of mono-target KIs. Hence, "multiple targets, multi-dimensional activities" represents an emerging paradigm for innovative anti-cancer drug discovery. Over recent years, considerable leaps have been made in pursuit of kinase-centric polypharmacological anti-cancer therapeutics, providing avenues to tackling the limitation of mono-target KIs. In the review, we summarize the clinically important mechanisms inducing KI resistance and depict a landscape of recent medicinal chemistry efforts on exploring kinase-centric polypharmacological anti-cancer agents that targeting multiple cancer-related processes. In parallel, some inevitable challenges are emphasized for the sake of more accurate and efficient drug discovery in the field. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
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Li, Peng; Chen, Jianxin; Zhang, Wuxia; Fu, Bangze; Wang, Wei
2017-01-04
Herbal medicine is a concoction of numerous chemical ingredients, and it exhibits polypharmacological effects to act on multiple pharmacological targets, regulating different biological mechanisms and treating a variety of diseases. Thus, this complexity is impossible to deconvolute by the reductionist method of extracting one active ingredient acting on one biological target. To dissect the polypharmacological effects of herbal medicines and their underling pharmacological targets as well as their corresponding active ingredients. We propose a system-biology strategy that combines omics and bioinformatical methodologies for exploring the polypharmacology of herbal mixtures. The myocardial ischemia model was induced by Ameroid constriction of the left anterior descending coronary in Ba-Ma miniature pigs. RNA-seq analysis was utilized to find the differential genes induced by myocardial ischemia in pigs treated with formula QSKL. A transcriptome-based inference method was used to find the landmark drugs with similar mechanisms to QSKL. Gene-level analysis of RNA-seq data in QSKL-treated cases versus control animals yields 279 differential genes. Transcriptome-based inference methods identified 80 landmark drugs that covered nearly all drug classes. Then, based on the landmark drugs, 155 potential pharmacological targets and 57 indications were identified for QSKL. Our results demonstrate the power of a combined approach for exploring the pharmacological target and chemical space of herbal medicines. We hope that our method could enhance our understanding of the molecular mechanisms of herbal systems and further accelerate the exploration of the value of traditional herbal medicine systems. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
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Structural and Functional View of Polypharmacology.
Moya-García, Aurelio; Adeyelu, Tolulope; Kruger, Felix A; Dawson, Natalie L; Lees, Jon G; Overington, John P; Orengo, Christine; Ranea, Juan A G
2017-08-31
Protein domains mediate drug-protein interactions and this principle can guide the design of multi-target drugs i.e. polypharmacology. In this study, we associate multi-target drugs with CATH functional families through the overrepresentation of targets of those drugs in CATH functional families. Thus, we identify CATH functional families that are currently enriched in drugs (druggable CATH functional families) and we use the network properties of these druggable protein families to analyse their association with drug side effects. Analysis of selected druggable CATH functional families, enriched in drug targets, show that relatives exhibit highly conserved drug binding sites. Furthermore, relatives within druggable CATH functional families occupy central positions in a human protein functional network, cluster together forming network neighbourhoods and are less likely to be within proteins associated with drug side effects. Our results demonstrate that CATH functional families can be used to identify drug-target interactions, opening a new research direction in target identification.
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Barneh, Farnaz; Jafari, Mohieddin; Mirzaie, Mehdi
2016-11-01
Network pharmacology elucidates the relationship between drugs and targets. As the identified targets for each drug increases, the corresponding drug-target network (DTN) evolves from solely reflection of the pharmaceutical industry trend to a portrait of polypharmacology. The aim of this study was to evaluate the potentials of DrugBank database in advancing systems pharmacology. We constructed and analyzed DTN from drugs and targets associations in the DrugBank 4.0 database. Our results showed that in bipartite DTN, increased ratio of identified targets for drugs augmented density and connectivity of drugs and targets and decreased modular structure. To clear up the details in the network structure, the DTNs were projected into two networks namely, drug similarity network (DSN) and target similarity network (TSN). In DSN, various classes of Food and Drug Administration-approved drugs with distinct therapeutic categories were linked together based on shared targets. Projected TSN also showed complexity because of promiscuity of the drugs. By including investigational drugs that are currently being tested in clinical trials, the networks manifested more connectivity and pictured the upcoming pharmacological space in the future years. Diverse biological processes and protein-protein interactions were manipulated by new drugs, which can extend possible target combinations. We conclude that network-based organization of DrugBank 4.0 data not only reveals the potential for repurposing of existing drugs, also allows generating novel predictions about drugs off-targets, drug-drug interactions and their side effects. Our results also encourage further effort for high-throughput identification of targets to build networks that can be integrated into disease networks. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
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5-HT2C Receptor Structures Reveal the Structural Basis of GPCR Polypharmacology
DEFF Research Database (Denmark)
Peng, Yao; Mccorvy, John D.; Harpsøe, Kasper
2018-01-01
Drugs frequently require interactions with multiple targets—via a process known as polypharmacology—to achieve their therapeutic actions. Currently, drugs targeting several serotonin receptors, including the 5-HT2C receptor, are useful for treating obesity, drug abuse, and schizophrenia. The comp...... the structural basis of polypharmacology at canonical GPCRs and illustrates how understanding characteristic patterns of ligand-receptor interaction and activation may ultimately facilitate drug design at multiple GPCRs....
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Sidorov, Pavel; Gaspar, Helena; Marcou, Gilles; Varnek, Alexandre; Horvath, Dragos
2015-12-01
Intuitive, visual rendering—mapping—of high-dimensional chemical spaces (CS), is an important topic in chemoinformatics. Such maps were so far dedicated to specific compound collections—either limited series of known activities, or large, even exhaustive enumerations of molecules, but without associated property data. Typically, they were challenged to answer some classification problem with respect to those same molecules, admired for their aesthetical virtues and then forgotten—because they were set-specific constructs. This work wishes to address the question whether a general, compound set-independent map can be generated, and the claim of "universality" quantitatively justified, with respect to all the structure-activity information available so far—or, more realistically, an exploitable but significant fraction thereof. The "universal" CS map is expected to project molecules from the initial CS into a lower-dimensional space that is neighborhood behavior-compliant with respect to a large panel of ligand properties. Such map should be able to discriminate actives from inactives, or even support quantitative neighborhood-based, parameter-free property prediction (regression) models, for a wide panel of targets and target families. It should be polypharmacologically competent, without requiring any target-specific parameter fitting. This work describes an evolutionary growth procedure of such maps, based on generative topographic mapping, followed by the validation of their polypharmacological competence. Validation was achieved with respect to a maximum of exploitable structure-activity information, covering all of Homo sapiens proteins of the ChEMBL database, antiparasitic and antiviral data, etc. Five evolved maps satisfactorily solved hundreds of activity-based ligand classification challenges for targets, and even in vivo properties independent from training data. They also stood chemogenomics-related challenges, as cumulated responsibility
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Epigenetic polypharmacology: from combination therapy to multitargeted drugs.
de Lera, Angel R; Ganesan, A
The modern drug discovery process has largely focused its attention in the so-called magic bullets, single chemical entities that exhibit high selectivity and potency for a particular target. This approach was based on the assumption that the deregulation of a protein was causally linked to a disease state, and the pharmacological intervention through inhibition of the deregulated target was able to restore normal cell function. However, the use of cocktails or multicomponent drugs to address several targets simultaneously is also popular to treat multifactorial diseases such as cancer and neurological disorders. We review the state of the art with such combinations that have an epigenetic target as one of their mechanisms of action. Epigenetic drug discovery is a rapidly advancing field, and drugs targeting epigenetic enzymes are in the clinic for the treatment of hematological cancers. Approved and experimental epigenetic drugs are undergoing clinical trials in combination with other therapeutic agents via fused or linked pharmacophores in order to benefit from synergistic effects of polypharmacology. In addition, ligands are being discovered which, as single chemical entities, are able to modulate multiple epigenetic targets simultaneously (multitarget epigenetic drugs). These multiple ligands should in principle have a lower risk of drug-drug interactions and drug resistance compared to cocktails or multicomponent drugs. This new generation may rival the so-called magic bullets in the treatment of diseases that arise as a consequence of the deregulation of multiple signaling pathways provided the challenge of optimization of the activities shown by the pharmacophores with the different targets is addressed.
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Janga, Sarath Chandra; Tzakos, Andreas
2009-12-01
Recent years have seen an explosion in the amount of "omics" data and the integration of several disciplines, which has influenced all areas of life sciences including that of drug discovery. Several lines of evidence now suggest that the traditional notion of "one drug-one protein" for one disease does not hold any more and that treatment for most complex diseases can best be attempted using polypharmacological approaches. In this review, we formalize the definition of a drug-target network by decomposing it into drug, target and disease spaces and provide an overview of our understanding in recent years about its structure and organizational principles. We discuss advances made in developing promiscuous drugs following the paradigm of polypharmacology and reveal their advantages over traditional drugs for targeting diseases such as cancer. We suggest that drug-target networks can be decomposed to be studied at a variety of levels and argue that such network-based approaches have important implications in understanding disease phenotypes and in accelerating drug discovery. We also discuss the potential and scope network pharmacology promises in harnessing the vast amount of data from high-throughput approaches for therapeutic advantage.
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Exploring Polypharmacology Using a ROCS-Based Target Fishing Approach
2012-01-01
Daylight topological fingerprints were used as the descriptors for the similarity search.17 Nettles et al. have used feature point pharmacophores...conforma- tions (nconfs) = 400, root -mean-square distance (RMS) = 0.5 Å, and Ewindow = 10 kcal/mol. Ewindow is the value used to discard high-energy...Edwards, D. D.; Shoichet, B. K.; Roth, B. L. Predicting new molecular targets for known drugs. Nature 2009, 462 (7270), 175−81. (18) Nettles , J. H
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Lim, Hansaim; Gray, Paul; Xie, Lei; Poleksic, Aleksandar
2016-12-13
Conventional one-drug-one-gene approach has been of limited success in modern drug discovery. Polypharmacology, which focuses on searching for multi-targeted drugs to perturb disease-causing networks instead of designing selective ligands to target individual proteins, has emerged as a new drug discovery paradigm. Although many methods for single-target virtual screening have been developed to improve the efficiency of drug discovery, few of these algorithms are designed for polypharmacology. Here, we present a novel theoretical framework and a corresponding algorithm for genome-scale multi-target virtual screening based on the one-class collaborative filtering technique. Our method overcomes the sparseness of the protein-chemical interaction data by means of interaction matrix weighting and dual regularization from both chemicals and proteins. While the statistical foundation behind our method is general enough to encompass genome-wide drug off-target prediction, the program is specifically tailored to find protein targets for new chemicals with little to no available interaction data. We extensively evaluate our method using a number of the most widely accepted gene-specific and cross-gene family benchmarks and demonstrate that our method outperforms other state-of-the-art algorithms for predicting the interaction of new chemicals with multiple proteins. Thus, the proposed algorithm may provide a powerful tool for multi-target drug design.
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Gu, Jiangyong; Li, Li; Wang, Dongmei; Zhu, Wei; Han, Ling; Zhao, Ruizhi; Xu, Xiaojie; Lu, Chuanjian
2018-06-01
Psoriasis vulgaris is a chronic inflammatory and immune-mediated skin disease. 44 metabonomics biomarkers were identified by high-throughput liquid chromatography coupled to mass spectrometry in our previous work, but the roles of metabonomics biomarkers in the pathogenesis of psoriasis is unclear. The metabonomics biomarker-enzyme network was constructed. The key metabonomics biomarkers and enzymes were screened out by network analysis. The binding affinity between each metabonomics biomarker and target was calculated by molecular docking. A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways. Long-chain fatty acids, phospholipids, Estradiol and NADH were the most important metabonomics biomarkers. Most key enzymes belonged hydrolase, thioesterase and acyltransferase. Six proteins (TNF-alpha, MAPK3, iNOS, eNOS, COX2 and mTOR) were extensively involved in inflammatory reaction, immune response and cell proliferation, and might be drug targets for psoriasis. PI3K-Akt signaling pathway and five other pathways had close correlation with the pathogenesis of psoriasis and could deserve further research. The inflammatory reaction, immune response and cell proliferation are mainly involved in psoriasis. Network pharmacology provide a new insight into the relationships between metabonomics biomarkers and the pathogenesis of psoriasis. KEY MESSAGES • Network pharmacology was adopted to identify key metabonomics biomarkers and enzymes. • Six proteins were screened out as important drug targets for psoriasis. • A binding energy-weighted polypharmacological index was introduced to evaluate the importance of target-related pathways.
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Ligand cluster-based protein network and ePlatton, a multi-target ligand finder.
Du, Yu; Shi, Tieliu
2016-01-01
Small molecules are information carriers that make cells aware of external changes and couple internal metabolic and signalling pathway systems with each other. In some specific physiological status, natural or artificial molecules are used to interact with selective biological targets to activate or inhibit their functions to achieve expected biological and physiological output. Millions of years of evolution have optimized biological processes and pathways and now the endocrine and immune system cannot work properly without some key small molecules. In the past thousands of years, the human race has managed to find many medicines against diseases by trail-and-error experience. In the recent decades, with the deepening understanding of life and the progress of molecular biology, researchers spare no effort to design molecules targeting one or two key enzymes and receptors related to corresponding diseases. But recent studies in pharmacogenomics have shown that polypharmacology may be necessary for the effects of drugs, which challenge the paradigm, 'one drug, one target, one disease'. Nowadays, cheminformatics and structural biology can help us reasonably take advantage of the polypharmacology to design next-generation promiscuous drugs and drug combination therapies. 234,591 protein-ligand interactions were extracted from ChEMBL. By the 2D structure similarity, 13,769 ligand emerged from 156,151 distinct ligands which were recognized by 1477 proteins. Ligand cluster- and sequence-based protein networks (LCBN, SBN) were constructed, compared and analysed. For assisting compound designing, exploring polypharmacology and finding possible drug combination, we integrated the pathway, disease, drug adverse reaction and the relationship of targets and ligand clusters into the web platform, ePlatton, which is available at http://www.megabionet.org/eplatton. Although there were some disagreements between the LCBN and SBN, communities in both networks were largely the same
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A Novel Drug-Mouse Phenotypic Similarity Method Detects Molecular Determinants of Drug Effects.
Directory of Open Access Journals (Sweden)
Jeanette Prinz
2016-09-01
Full Text Available The molecular mechanisms that translate drug treatment into beneficial and unwanted effects are largely unknown. We present here a novel approach to detect gene-drug and gene-side effect associations based on the phenotypic similarity of drugs and single gene perturbations in mice that account for the polypharmacological property of drugs. We scored the phenotypic similarity of human side effect profiles of 1,667 small molecules and biologicals to profiles of phenotypic traits of 5,384 mouse genes. The benchmarking with known relationships revealed a strong enrichment of physical and indirect drug-target connections, causative drug target-side effect links as well as gene-drug links involved in pharmacogenetic associations among phenotypically similar gene-drug pairs. The validation by in vitro assays and the experimental verification of an unknown connection between oxandrolone and prokineticin receptor 2 reinforces the ability of this method to provide new molecular insights underlying drug treatment. Thus, this approach may aid in the proposal of novel and personalized treatments.
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DEFF Research Database (Denmark)
Jensen, Kasper; Plichta, Damian Rafal; Panagiotou, Gianni
2012-01-01
, in order to uncover the weak links in the proteome of the parasite. We predicted 293 proteins of P. falciparum, including the six out of the seven verified targets for P. falciparum malaria treatment, as targets of 4645 GSK active compounds. Furthermore, we prioritized druggable targets, based on a number...... of factors, such as essentiality for growth, lack of homology with human proteins, and availability of experimental data on ligand activity with a non-human homologue of a parasite protein. We have additionally prioritized predicted ligands based on their polypharmacology profile, with focus on validated...
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Space moving target detection using time domain feature
Wang, Min; Chen, Jin-yong; Gao, Feng; Zhao, Jin-yu
2018-01-01
The traditional space target detection methods mainly use the spatial characteristics of the star map to detect the targets, which can not make full use of the time domain information. This paper presents a new space moving target detection method based on time domain features. We firstly construct the time spectral data of star map, then analyze the time domain features of the main objects (target, stars and the background) in star maps, finally detect the moving targets using single pulse feature of the time domain signal. The real star map target detection experimental results show that the proposed method can effectively detect the trajectory of moving targets in the star map sequence, and the detection probability achieves 99% when the false alarm rate is about 8×10-5, which outperforms those of compared algorithms.
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Covariance descriptor fusion for target detection
Cukur, Huseyin; Binol, Hamidullah; Bal, Abdullah; Yavuz, Fatih
2016-05-01
Target detection is one of the most important topics for military or civilian applications. In order to address such detection tasks, hyperspectral imaging sensors provide useful images data containing both spatial and spectral information. Target detection has various challenging scenarios for hyperspectral images. To overcome these challenges, covariance descriptor presents many advantages. Detection capability of the conventional covariance descriptor technique can be improved by fusion methods. In this paper, hyperspectral bands are clustered according to inter-bands correlation. Target detection is then realized by fusion of covariance descriptor results based on the band clusters. The proposed combination technique is denoted Covariance Descriptor Fusion (CDF). The efficiency of the CDF is evaluated by applying to hyperspectral imagery to detect man-made objects. The obtained results show that the CDF presents better performance than the conventional covariance descriptor.
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Detection technique of targets for missile defense system
Guo, Hua-ling; Deng, Jia-hao; Cai, Ke-rong
2009-11-01
Ballistic missile defense system (BMDS) is a weapon system for intercepting enemy ballistic missiles. It includes ballistic-missile warning system, target discrimination system, anti-ballistic-missile guidance systems, and command-control communication system. Infrared imaging detection and laser imaging detection are widely used in BMDS for surveillance, target detection, target tracking, and target discrimination. Based on a comprehensive review of the application of target-detection techniques in the missile defense system, including infrared focal plane arrays (IRFPA), ground-based radar detection technology, 3-dimensional imaging laser radar with a photon counting avalanche photodiode (APD) arrays and microchip laser, this paper focuses on the infrared and laser imaging detection techniques in missile defense system, as well as the trends for their future development.
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The target landscape of clinical kinase drugs.
Klaeger, Susan; Heinzlmeir, Stephanie; Wilhelm, Mathias; Polzer, Harald; Vick, Binje; Koenig, Paul-Albert; Reinecke, Maria; Ruprecht, Benjamin; Petzoldt, Svenja; Meng, Chen; Zecha, Jana; Reiter, Katrin; Qiao, Huichao; Helm, Dominic; Koch, Heiner; Schoof, Melanie; Canevari, Giulia; Casale, Elena; Depaolini, Stefania Re; Feuchtinger, Annette; Wu, Zhixiang; Schmidt, Tobias; Rueckert, Lars; Becker, Wilhelm; Huenges, Jan; Garz, Anne-Kathrin; Gohlke, Bjoern-Oliver; Zolg, Daniel Paul; Kayser, Gian; Vooder, Tonu; Preissner, Robert; Hahne, Hannes; Tõnisson, Neeme; Kramer, Karl; Götze, Katharina; Bassermann, Florian; Schlegl, Judith; Ehrlich, Hans-Christian; Aiche, Stephan; Walch, Axel; Greif, Philipp A; Schneider, Sabine; Felder, Eduard Rudolf; Ruland, Juergen; Médard, Guillaume; Jeremias, Irmela; Spiekermann, Karsten; Kuster, Bernhard
2017-12-01
Kinase inhibitors are important cancer therapeutics. Polypharmacology is commonly observed, requiring thorough target deconvolution to understand drug mechanism of action. Using chemical proteomics, we analyzed the target spectrum of 243 clinically evaluated kinase drugs. The data revealed previously unknown targets for established drugs, offered a perspective on the "druggable" kinome, highlighted (non)kinase off-targets, and suggested potential therapeutic applications. Integration of phosphoproteomic data refined drug-affected pathways, identified response markers, and strengthened rationale for combination treatments. We exemplify translational value by discovering SIK2 (salt-inducible kinase 2) inhibitors that modulate cytokine production in primary cells, by identifying drugs against the lung cancer survival marker MELK (maternal embryonic leucine zipper kinase), and by repurposing cabozantinib to treat FLT3-ITD-positive acute myeloid leukemia. This resource, available via the ProteomicsDB database, should facilitate basic, clinical, and drug discovery research and aid clinical decision-making. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
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Dim point target detection against bright background
Zhang, Yao; Zhang, Qiheng; Xu, Zhiyong; Xu, Junping
2010-05-01
For target detection within a large-field cluttered background from a long distance, several difficulties, involving low contrast between target and background, little occupancy, illumination ununiformity caused by vignetting of lens, and system noise, make it a challenging problem. The existing approaches to dim target detection can be roughly divided into two categories: detection before tracking (DBT) and tracking before detection (TBD). The DBT-based scheme has been widely used in practical applications due to its simplicity, but it often requires working in the situation with a higher signal-to-noise ratio (SNR). In contrast, the TBD-based methods can provide impressive detection results even in the cases of very low SNR; unfortunately, the large memory requirement and high computational load prevents these methods from real-time tasks. In this paper, we propose a new method for dim target detection. We address this problem by combining the advantages of the DBT-based scheme in computational efficiency and of the TBD-based in detection capability. Our method first predicts the local background, and then employs the energy accumulation and median filter to remove background clutter. The dim target is finally located by double window filtering together with an improved high order correlation which speeds up the convergence. The proposed method is implemented on a hardware platform and performs suitably in outside experiments.
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Grossman, S.
2015-05-01
Since the events of September 11, 2001, the intelligence focus has moved from large order-of-battle targets to small targets of opportunity. Additionally, the business community has discovered the use of remotely sensed data to anticipate demand and derive data on their competition. This requires the finer spectral and spatial fidelity now available to recognize those targets. This work hypothesizes that directed searches using calibrated data perform at least as well as inscene manually intensive target detection searches. It uses calibrated Worldview-2 multispectral images with NEF generated signatures and standard detection algorithms to compare bespoke directed search capabilities against ENVI™ in-scene search capabilities. Multiple execution runs are performed at increasing thresholds to generate detection rates. These rates are plotted and statistically analyzed. While individual head-to-head comparison results vary, 88% of the directed searches performed at least as well as in-scene searches with 50% clearly outperforming in-scene methods. The results strongly support the premise that directed searches perform at least as well as comparable in-scene searches.
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The Bering Autonomous Target Detection
DEFF Research Database (Denmark)
Jørgensen, John Leif; Denver, Troelz; Betto, Maurizio
2003-01-01
An autonomous asteroid target detection and tracking method has been developed. The method features near omnidirectionality and focus on high speed operations and completeness of search of the near space rather than the traditional faint object search methods, employed presently at the larger...... telescopes. The method has proven robust in operation and is well suited for use onboard spacecraft. As development target for the method and the associated instrumentation the asteroid research mission Bering has been used. Onboard a spacecraft, the autonomous detection is centered around the fully...... autonomous star tracker the Advanced Stellar Compass (ASC). One feature of this instrument is that potential targets are registered directly in terms of date, right ascension, declination, and intensity, which greatly facilitates both tracking search and registering. Results from ground and inflight tests...
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Spectral Target Detection using Schroedinger Eigenmaps
Dorado-Munoz, Leidy P.
Applications of optical remote sensing processes include environmental monitoring, military monitoring, meteorology, mapping, surveillance, etc. Many of these tasks include the detection of specific objects or materials, usually few or small, which are surrounded by other materials that clutter the scene and hide the relevant information. This target detection process has been boosted lately by the use of hyperspectral imagery (HSI) since its high spectral dimension provides more detailed spectral information that is desirable in data exploitation. Typical spectral target detectors rely on statistical or geometric models to characterize the spectral variability of the data. However, in many cases these parametric models do not fit well HSI data that impacts the detection performance. On the other hand, non-linear transformation methods, mainly based on manifold learning algorithms, have shown a potential use in HSI transformation, dimensionality reduction and classification. In target detection, non-linear transformation algorithms are used as preprocessing techniques that transform the data to a more suitable lower dimensional space, where the statistical or geometric detectors are applied. One of these non-linear manifold methods is the Schroedinger Eigenmaps (SE) algorithm that has been introduced as a technique for semi-supervised classification. The core tool of the SE algorithm is the Schroedinger operator that includes a potential term that encodes prior information about the materials present in a scene, and enables the embedding to be steered in some convenient directions in order to cluster similar pixels together. A completely novel target detection methodology based on SE algorithm is proposed for the first time in this thesis. The proposed methodology does not just include the transformation of the data to a lower dimensional space but also includes the definition of a detector that capitalizes on the theory behind SE. The fact that target pixels and
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Small target pre-detection with an attention mechanism
Wang, Yuehuan; Zhang, Tianxu; Wang, Guoyou
2002-04-01
We introduce the concept of predetection based on an attention mechanism to improve the efficiency of small-target detection by limiting the image region of detection. According to the characteristics of small-target detection, local contrast is taken as the only feature in predetection and a nonlinear sampling model is adopted to make the predetection adaptive to detect small targets with different area sizes. To simplify the predetection itself and decrease the false alarm probability, neighboring nodes in the sampling grid are used to generate a saliency map, and a short-term memory is adopted to accelerate the `pop-out' of targets. We discuss the fact that the proposed approach is simple enough in computational complexity. In addition, even in a cluttered background, attention can be led to targets in a satisfying few iterations, which ensures that the detection efficiency will not be decreased due to false alarms. Experimental results are presented to demonstrate the applicability of the approach.
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Target Detection Based on EBPSK Satellite Passive Radar
Directory of Open Access Journals (Sweden)
Lu Zeyuan
2015-05-01
Full Text Available Passive radar is a topic anti stealth technology with simple structure, and low cost. Radiation source model, signal transmission model, and target detection are the key points of passive radar technology research. The paper analyzes the characteristics of EBPSK signal modulation and target detection method aspect of spaceborne radiant source. By comparison with other satellite navigation and positioning system, the characteristics of EBPSK satellite passive radar system are analyzed. It is proved that the maximum detection range of EBPSK satellite signal can satisfy the needs of the proposed model. In the passive radar model, sparse representation is used to achieve high resolution DOA detection. The comparison with the real target track by simulation demonstrates that effective detection of airborne target using EBPSK satellite passive radar system based on sparse representation is efficient.
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Detection and identification of human targets in radar data
Gürbüz, Sevgi Z.; Melvin, William L.; Williams, Douglas B.
2007-04-01
Radar offers unique advantages over other sensors, such as visual or seismic sensors, for human target detection. Many situations, especially military applications, prevent the placement of video cameras or implantment seismic sensors in the area being observed, because of security or other threats. However, radar can operate far away from potential targets, and functions during daytime as well as nighttime, in virtually all weather conditions. In this paper, we examine the problem of human target detection and identification using single-channel, airborne, synthetic aperture radar (SAR). Human targets are differentiated from other detected slow-moving targets by analyzing the spectrogram of each potential target. Human spectrograms are unique, and can be used not just to identify targets as human, but also to determine features about the human target being observed, such as size, gender, action, and speed. A 12-point human model, together with kinematic equations of motion for each body part, is used to calculate the expected target return and spectrogram. A MATLAB simulation environment is developed including ground clutter, human and non-human targets for the testing of spectrogram-based detection and identification algorithms. Simulations show that spectrograms have some ability to detect and identify human targets in low noise. An example gender discrimination system correctly detected 83.97% of males and 91.11% of females. The problems and limitations of spectrogram-based methods in high clutter environments are discussed. The SNR loss inherent to spectrogram-based methods is quantified. An alternate detection and identification method that will be used as a basis for future work is proposed.
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Manifold structure preservative for hyperspectral target detection
Imani, Maryam
2018-05-01
A nonparametric method termed as manifold structure preservative (MSP) is proposed in this paper for hyperspectral target detection. MSP transforms the feature space of data to maximize the separation between target and background signals. Moreover, it minimizes the reconstruction error of targets and preserves the topological structure of data in the projected feature space. MSP does not need to consider any distribution for target and background data. So, it can achieve accurate results in real scenarios due to avoiding unreliable assumptions. The proposed MSP detector is compared to several popular detectors and the experiments on a synthetic data and two real hyperspectral images indicate the superior ability of it in target detection.
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Detection of Moving Targets Using Soliton Resonance Effect
Kulikov, Igor K.; Zak, Michail
2013-01-01
The objective of this research was to develop a fundamentally new method for detecting hidden moving targets within noisy and cluttered data-streams using a novel "soliton resonance" effect in nonlinear dynamical systems. The technique uses an inhomogeneous Korteweg de Vries (KdV) equation containing moving-target information. Solution of the KdV equation will describe a soliton propagating with the same kinematic characteristics as the target. The approach uses the time-dependent data stream obtained with a sensor in form of the "forcing function," which is incorporated in an inhomogeneous KdV equation. When a hidden moving target (which in many ways resembles a soliton) encounters the natural "probe" soliton solution of the KdV equation, a strong resonance phenomenon results that makes the location and motion of the target apparent. Soliton resonance method will amplify the moving target signal, suppressing the noise. The method will be a very effective tool for locating and identifying diverse, highly dynamic targets with ill-defined characteristics in a noisy environment. The soliton resonance method for the detection of moving targets was developed in one and two dimensions. Computer simulations proved that the method could be used for detection of singe point-like targets moving with constant velocities and accelerations in 1D and along straight lines or curved trajectories in 2D. The method also allows estimation of the kinematic characteristics of moving targets, and reconstruction of target trajectories in 2D. The method could be very effective for target detection in the presence of clutter and for the case of target obscurations.
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Dim target detection method based on salient graph fusion
Hu, Ruo-lan; Shen, Yi-yan; Jiang, Jun
2018-02-01
Dim target detection is one key problem in digital image processing field. With development of multi-spectrum imaging sensor, it becomes a trend to improve the performance of dim target detection by fusing the information from different spectral images. In this paper, one dim target detection method based on salient graph fusion was proposed. In the method, Gabor filter with multi-direction and contrast filter with multi-scale were combined to construct salient graph from digital image. And then, the maximum salience fusion strategy was designed to fuse the salient graph from different spectral images. Top-hat filter was used to detect dim target from the fusion salient graph. Experimental results show that proposal method improved the probability of target detection and reduced the probability of false alarm on clutter background images.
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Quantum Illumination-Based Target Detection and Discrimination
2014-06-30
photodiode with an estimated quantum efficiency of 85% and an ultralow-noise transimpedance amplifier . Compared with to our initial QI measurements...demonstrated high signal-to-noise ratio (SNR) quantum-illumination target detection in a lossy, noisy environment using an optical parametric amplifier ...Research Triangle Park, NC 27709-2211 quantum communication, target detection, entanglement, parametric downconversion, optical parametric amplifiers
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Heterogeneous CPU-GPU moving targets detection for UAV video
Li, Maowen; Tang, Linbo; Han, Yuqi; Yu, Chunlei; Zhang, Chao; Fu, Huiquan
2017-07-01
Moving targets detection is gaining popularity in civilian and military applications. On some monitoring platform of motion detection, some low-resolution stationary cameras are replaced by moving HD camera based on UAVs. The pixels of moving targets in the HD Video taken by UAV are always in a minority, and the background of the frame is usually moving because of the motion of UAVs. The high computational cost of the algorithm prevents running it at higher resolutions the pixels of frame. Hence, to solve the problem of moving targets detection based UAVs video, we propose a heterogeneous CPU-GPU moving target detection algorithm for UAV video. More specifically, we use background registration to eliminate the impact of the moving background and frame difference to detect small moving targets. In order to achieve the effect of real-time processing, we design the solution of heterogeneous CPU-GPU framework for our method. The experimental results show that our method can detect the main moving targets from the HD video taken by UAV, and the average process time is 52.16ms per frame which is fast enough to solve the problem.
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Camouflage target detection via hyperspectral imaging plus information divergence measurement
Chen, Yuheng; Chen, Xinhua; Zhou, Jiankang; Ji, Yiqun; Shen, Weimin
2016-01-01
Target detection is one of most important applications in remote sensing. Nowadays accurate camouflage target distinction is often resorted to spectral imaging technique due to its high-resolution spectral/spatial information acquisition ability as well as plenty of data processing methods. In this paper, hyper-spectral imaging technique together with spectral information divergence measure method is used to solve camouflage target detection problem. A self-developed visual-band hyper-spectral imaging device is adopted to collect data cubes of certain experimental scene before spectral information divergences are worked out so as to discriminate target camouflage and anomaly. Full-band information divergences are measured to evaluate target detection effect visually and quantitatively. Information divergence measurement is proved to be a low-cost and effective tool for target detection task and can be further developed to other target detection applications beyond spectral imaging technique.
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Chamrád, Ivo; Rix, Uwe; Stukalov, Alexey; Gridling, Manuela; Parapatics, Katja; Müller, André C.; Altiok, Soner; Colinge, Jacques; Superti-Furga, Giulio; Haura, Eric B.; Bennett, Keiryn L.
2014-01-01
While targeted therapy based on the idea of attenuating the activity of a preselected, therapeutically relevant protein has become one of the major trends in modern cancer therapy, no truly specific targeted drug has been developed and most clinical agents have displayed a degree of polypharmacology. Therefore, the specificity of anticancer therapeutics has emerged as a highly important but severely underestimated issue. Chemical proteomics is a powerful technique combining postgenomic drug-affinity chromatography with high-end mass spectrometry analysis and bioinformatic data processing to assemble a target profile of a desired therapeutic molecule. Due to high demands on the starting material, however, chemical proteomic studies have been mostly limited to cancer cell lines. Herein, we report a down-scaling of the technique to enable the analysis of very low abundance samples, as those obtained from needle biopsies. By a systematic investigation of several important parameters in pull-downs with the multikinase inhibitor bosutinib, the standard experimental protocol was optimized to 100 µg protein input. At this level, more than 30 well-known targets were detected per single pull-down replicate with high reproducibility. Moreover, as presented by the comprehensive target profile obtained from miniaturized pull-downs with another clinical drug, dasatinib, the optimized protocol seems to be extendable to other drugs of interest. Sixty distinct human and murine targets were finally identified for bosutinib and dasatinib in chemical proteomic experiments utilizing core needle biopsy samples from xenotransplants derived from patient tumor tissue. Altogether, the developed methodology proves robust and generic and holds many promises for the field of personalized health care. PMID:23901793
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Detection algorithm of infrared small target based on improved SUSAN operator
Liu, Xingmiao; Wang, Shicheng; Zhao, Jing
2010-10-01
The methods of detecting small moving targets in infrared image sequences that contain moving nuisance objects and background noise is analyzed in this paper. A novel infrared small target detection algorithm based on improved SUSAN operator is put forward. The algorithm selects double templates for the infrared small target detection: one size is greater than the small target point size and another size is equal to the small target point size. First, the algorithm uses the big template to calculate the USAN of each pixel in the image and detect the small target, the edge of the image and isolated noise pixels; Then the algorithm uses the another template to calculate the USAN of pixels detected in the first step and improves the principles of SUSAN algorithm based on the characteristics of the small target so that the algorithm can only detect small targets and don't sensitive to the edge pixels of the image and isolated noise pixels. So the interference of the edge of the image and isolate noise points are removed and the candidate target points can be identified; At last, the target is detected by utilizing the continuity and consistency of target movement. The experimental results indicate that the improved SUSAN detection algorithm can quickly and effectively detect the infrared small targets.
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Chemical Proteomics Reveals Ferrochelatase as a Common Off-target of Kinase Inhibitors.
Klaeger, Susan; Gohlke, Bjoern; Perrin, Jessica; Gupta, Vipul; Heinzlmeir, Stephanie; Helm, Dominic; Qiao, Huichao; Bergamini, Giovanna; Handa, Hiroshi; Savitski, Mikhail M; Bantscheff, Marcus; Médard, Guillaume; Preissner, Robert; Kuster, Bernhard
2016-05-20
Many protein kinases are valid drug targets in oncology because they are key components of signal transduction pathways. The number of clinical kinase inhibitors is on the rise, but these molecules often exhibit polypharmacology, potentially eliciting desired and toxic effects. Therefore, a comprehensive assessment of a compound's target space is desirable for a better understanding of its biological effects. The enzyme ferrochelatase (FECH) catalyzes the conversion of protoporphyrin IX into heme and was recently found to be an off-target of the BRAF inhibitor Vemurafenib, likely explaining the phototoxicity associated with this drug in melanoma patients. This raises the question of whether FECH binding is a more general feature of kinase inhibitors. To address this, we applied a chemical proteomics approach using kinobeads to evaluate 226 clinical kinase inhibitors for their ability to bind FECH. Surprisingly, low or submicromolar FECH binding was detected for 29 of all compounds tested and isothermal dose response measurements confirmed target engagement in cells. We also show that Vemurafenib, Linsitinib, Neratinib, and MK-2461 reduce heme levels in K562 cells, verifying that drug binding leads to a loss of FECH activity. Further biochemical and docking experiments identified the protoporphyrin pocket in FECH as one major drug binding site. Since the genetic loss of FECH activity leads to photosensitivity in humans, our data strongly suggest that FECH inhibition by kinase inhibitors is the molecular mechanism triggering photosensitivity in patients. We therefore suggest that a FECH assay should generally be part of the preclinical molecular toxicology package for the development of kinase inhibitors.
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Small Surface Target Detection with EO/IR Sensors
Jong, A.N. de; Kemp, R.A.W.
1998-01-01
The detection of small surface targets at sea is an increasing requirement for warships. The present sensors on board do not provide the required detection probabilities for these low observable targets like small rubber boats, floating mines, periscopes, people etc. The reason for the low
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Passive Sonar Target Detection Using Statistical Classifier and Adaptive Threshold
Directory of Open Access Journals (Sweden)
Hamed Komari Alaie
2018-01-01
Full Text Available This paper presents the results of an experimental investigation about target detecting with passive sonar in Persian Gulf. Detecting propagated sounds in the water is one of the basic challenges of the researchers in sonar field. This challenge will be complex in shallow water (like Persian Gulf and noise less vessels. Generally, in passive sonar, the targets are detected by sonar equation (with constant threshold that increases the detection error in shallow water. The purpose of this study is proposed a new method for detecting targets in passive sonars using adaptive threshold. In this method, target signal (sound is processed in time and frequency domain. For classifying, Bayesian classification is used and posterior distribution is estimated by Maximum Likelihood Estimation algorithm. Finally, target was detected by combining the detection points in both domains using Least Mean Square (LMS adaptive filter. Results of this paper has showed that the proposed method has improved true detection rate by about 24% when compared other the best detection method.
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Texture orientation-based algorithm for detecting infrared maritime targets.
Wang, Bin; Dong, Lili; Zhao, Ming; Wu, Houde; Xu, Wenhai
2015-05-20
Infrared maritime target detection is a key technology for maritime target searching systems. However, in infrared maritime images (IMIs) taken under complicated sea conditions, background clutters, such as ocean waves, clouds or sea fog, usually have high intensity that can easily overwhelm the brightness of real targets, which is difficult for traditional target detection algorithms to deal with. To mitigate this problem, this paper proposes a novel target detection algorithm based on texture orientation. This algorithm first extracts suspected targets by analyzing the intersubband correlation between horizontal and vertical wavelet subbands of the original IMI on the first scale. Then the self-adaptive wavelet threshold denoising and local singularity analysis of the original IMI is combined to remove false alarms further. Experiments show that compared with traditional algorithms, this algorithm can suppress background clutter much better and realize better single-frame detection for infrared maritime targets. Besides, in order to guarantee accurate target extraction further, the pipeline-filtering algorithm is adopted to eliminate residual false alarms. The high practical value and applicability of this proposed strategy is backed strongly by experimental data acquired under different environmental conditions.
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Automatic target detection using binary template matching
Jun, Dong-San; Sun, Sun-Gu; Park, HyunWook
2005-03-01
This paper presents a new automatic target detection (ATD) algorithm to detect targets such as battle tanks and armored personal carriers in ground-to-ground scenarios. Whereas most ATD algorithms were developed for forward-looking infrared (FLIR) images, we have developed an ATD algorithm for charge-coupled device (CCD) images, which have superior quality to FLIR images in daylight. The proposed algorithm uses fast binary template matching with an adaptive binarization, which is robust to various light conditions in CCD images and saves computation time. Experimental results show that the proposed method has good detection performance.
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A new method of small target detection based on neural network
Hu, Jing; Hu, Yongli; Lu, Xinxin
2018-02-01
The detection and tracking of moving dim target in infrared image have been an research hotspot for many years. The target in each frame of images only occupies several pixels without any shape and structure information. Moreover, infrared small target is often submerged in complicated background with low signal-to-clutter ratio, making the detection very difficult. Different backgrounds exhibit different statistical properties, making it becomes extremely complex to detect the target. If the threshold segmentation is not reasonable, there may be more noise points in the final detection, which is unfavorable for the detection of the trajectory of the target. Single-frame target detection may not be able to obtain the desired target and cause high false alarm rate. We believe the combination of suspicious target detection spatially in each frame and temporal association for target tracking will increase reliability of tracking dim target. The detection of dim target is mainly divided into two parts, In the first part, we adopt bilateral filtering method in background suppression, after the threshold segmentation, the suspicious target in each frame are extracted, then we use LSTM(long short term memory) neural network to predict coordinates of target of the next frame. It is a brand-new method base on the movement characteristic of the target in sequence images which could respond to the changes in the relationship between past and future values of the values. Simulation results demonstrate proposed algorithm can effectively predict the trajectory of the moving small target and work efficiently and robustly with low false alarm.
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Infrared small target detection technology based on OpenCV
Liu, Lei; Huang, Zhijian
2013-09-01
Accurate and fast detection of infrared (IR) dim target has very important meaning for infrared precise guidance, early warning, video surveillance, etc. In this paper, some basic principles and the implementing flow charts of a series of algorithms for target detection are described. These algorithms are traditional two-frame difference method, improved three-frame difference method, background estimate and frame difference fusion method, and building background with neighborhood mean method. On the foundation of above works, an infrared target detection software platform which is developed by OpenCV and MFC is introduced. Three kinds of tracking algorithms are integrated in this software. In order to explain the software clearly, the framework and the function are described in this paper. At last, the experiments are performed for some real-life IR images. The whole algorithm implementing processes and results are analyzed, and those algorithms for detection targets are evaluated from the two aspects of subjective and objective. The results prove that the proposed method has satisfying detection effectiveness and robustness. Meanwhile, it has high detection efficiency and can be used for real-time detection.
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Infrared small target detection with kernel Fukunaga Koontz transform
Liu, Rui-ming; Liu, Er-qi; Yang, Jie; Zhang, Tian-hao; Wang, Fang-lin
2007-09-01
The Fukunaga-Koontz transform (FKT) has been proposed for many years. It can be used to solve two-pattern classification problems successfully. However, there are few researchers who have definitely extended FKT to kernel FKT (KFKT). In this paper, we first complete this task. Then a method based on KFKT is developed to detect infrared small targets. KFKT is a supervised learning algorithm. How to construct training sets is very important. For automatically detecting targets, the synthetic target images and real background images are used to train KFKT. Because KFKT can represent the higher order statistical properties of images, we expect better detection performance of KFKT than that of FKT. The well-devised experiments verify that KFKT outperforms FKT in detecting infrared small targets.
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Magnetic biosensor system to detect biological targets
Li, Fuquan
2012-09-01
Magneto-resistive sensors in combination with magnetic beads provide sensing platforms, which are small in size and highly sensitive. These platforms can be fully integrated with microchannels and electronics to enable devices capable of performing complex tasks. Commonly, a sandwich method is used that requires a specific coating of the sensor\\'s surface to immobilize magnetic beads and biological targets on top of the sensor. This paper concerns a micro device to detect biological targets using magnetic concentration, magnetic as well as mechanical trapping and magnetic sensing. Target detection is based on the size difference between bare magnetic beads and magnetic beads with targets attached. This method remedies the need for a coating layer and reduces the number of steps required to run an experiment. © 2012 IEEE.
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An Overview of Radar Waveform Optimization for Target Detection
Directory of Open Access Journals (Sweden)
Wang Lulu
2016-10-01
Full Text Available An optimal waveform design method that fully employs the knowledge of the target and the environment can further improve target detection performance, thus is of vital importance to research. In this paper, methods of radar waveform optimization for target detection are reviewed and summarized and provide the basis for the research.
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Magnetic biosensor system to detect biological targets
Li, Fuquan; Gooneratne, Chinthaka Pasan; Kosel, Jü rgen
2012-01-01
magnetic concentration, magnetic as well as mechanical trapping and magnetic sensing. Target detection is based on the size difference between bare magnetic beads and magnetic beads with targets attached. This method remedies the need for a coating layer
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National Research Council Canada - National Science Library
Smetek, Timothy E
2007-01-01
This research extends the field of hyperspectral target detection by developing autonomous anomaly detection and signature matching methodologies that reduce false alarms relative to existing benchmark detectors...
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Kepler Planet Detection Metrics: Per-Target Detection Contours for Data Release 25
Burke, Christopher J.; Catanzarite, Joseph
2017-01-01
A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).
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Robust Small Target Co-Detection from Airborne Infrared Image Sequences.
Gao, Jingli; Wen, Chenglin; Liu, Meiqin
2017-09-29
In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.
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Small target detection using objectness and saliency
Zhang, Naiwen; Xiao, Yang; Fang, Zhiwen; Yang, Jian; Wang, Li; Li, Tao
2017-10-01
We are motived by the need for generic object detection algorithm which achieves high recall for small targets in complex scenes with acceptable computational efficiency. We propose a novel object detection algorithm, which has high localization quality with acceptable computational cost. Firstly, we obtain the objectness map as in BING[1] and use NMS to get the top N points. Then, k-means algorithm is used to cluster them into K classes according to their location. We set the center points of the K classes as seed points. For each seed point, an object potential region is extracted. Finally, a fast salient object detection algorithm[2] is applied to the object potential regions to highlight objectlike pixels, and a series of efficient post-processing operations are proposed to locate the targets. Our method runs at 5 FPS on 1000*1000 images, and significantly outperforms previous methods on small targets in cluttered background.
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Camouflage, detection and identification of moving targets.
Hall, Joanna R; Cuthill, Innes C; Baddeley, Roland; Shohet, Adam J; Scott-Samuel, Nicholas E
2013-05-07
Nearly all research on camouflage has investigated its effectiveness for concealing stationary objects. However, animals have to move, and patterns that only work when the subject is static will heavily constrain behaviour. We investigated the effects of different camouflages on the three stages of predation-detection, identification and capture-in a computer-based task with humans. An initial experiment tested seven camouflage strategies on static stimuli. In line with previous literature, background-matching and disruptive patterns were found to be most successful. Experiment 2 showed that if stimuli move, an isolated moving object on a stationary background cannot avoid detection or capture regardless of the type of camouflage. Experiment 3 used an identification task and showed that while camouflage is unable to slow detection or capture, camouflaged targets are harder to identify than uncamouflaged targets when similar background objects are present. The specific details of the camouflage patterns have little impact on this effect. If one has to move, camouflage cannot impede detection; but if one is surrounded by similar targets (e.g. other animals in a herd, or moving background distractors), then camouflage can slow identification. Despite previous assumptions, motion does not entirely 'break' camouflage.
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Moving Target Detection and Active Tracking with a Multicamera Network
Directory of Open Access Journals (Sweden)
Long Zhao
2014-01-01
Full Text Available We propose a systematic framework for Intelligence Video Surveillance System (IVSS with a multicamera network. The proposed framework consists of low-cost static and PTZ cameras, target detection and tracking algorithms, and a low-cost PTZ camera feedback control algorithm based on target information. The target detection and tracking is realized by fixed cameras using a moving target detection and tracking algorithm; the PTZ camera is manoeuvred to actively track the target from the tracking results of the static camera. The experiments are carried out using practical surveillance system data, and the experimental results show that the systematic framework and algorithms presented in this paper are efficient.
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Bal, A.; Alam, M. S.; Aslan, M. S.
2006-05-01
Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.
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Supervised target detection in hyperspectral images using one-class Fukunaga-Koontz Transform
Binol, Hamidullah; Bal, Abdullah
2016-05-01
A novel hyperspectral target detection technique based on Fukunaga-Koontz transform (FKT) is presented. FKT offers significant properties for feature selection and ordering. However, it can only be used to solve multi-pattern classification problems. Target detection may be considered as a two-class classification problem, i.e., target versus background clutter. Nevertheless, background clutter typically contains different types of materials. That's why; target detection techniques are different than classification methods by way of modeling clutter. To avoid the modeling of the background clutter, we have improved one-class FKT (OC-FKT) for target detection. The statistical properties of target training samples are used to define tunnel-like boundary of the target class. Non-target samples are then created synthetically as to be outside of the boundary. Thus, only limited target samples become adequate for training of FKT. The hyperspectral image experiments confirm that the proposed OC-FKT technique provides an effective means for target detection.
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Multirapid Serial Visual Presentation Framework for EEG-Based Target Detection
Directory of Open Access Journals (Sweden)
Zhimin Lin
2017-01-01
Full Text Available Target image detection based on a rapid serial visual presentation (RSVP paradigm is a typical brain-computer interface system with various applications, such as image retrieval. In an RSVP paradigm, a P300 component is detected to determine target images. This strategy requires high-precision single-trial P300 detection methods. However, the performance of single-trial detection methods is relatively lower than that of multitrial P300 detection methods. Image retrieval based on multitrial P300 is a new research direction. In this paper, we propose a triple-RSVP paradigm with three images being presented simultaneously and a target image appearing three times. Thus, multitrial P300 classification methods can be used to improve detection accuracy. In this study, these mechanisms were extended and validated, and the characteristics of the multi-RSVP framework were further explored. Two different P300 detection algorithms were also utilized in multi-RSVP to demonstrate that the scheme is universally applicable. Results revealed that the detection accuracy of the multi-RSVP paradigm was higher than that of the standard RSVP paradigm. The results validate the effectiveness of the proposed method, and this method can provide a whole new idea in the field of EEG-based target detection.
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Lee, Kyoungyeul; Lee, Minho; Kim, Dongsup
2017-12-28
The identification of target molecules is important for understanding the mechanism of "target deconvolution" in phenotypic screening and "polypharmacology" of drugs. Because conventional methods of identifying targets require time and cost, in-silico target identification has been considered an alternative solution. One of the well-known in-silico methods of identifying targets involves structure activity relationships (SARs). SARs have advantages such as low computational cost and high feasibility; however, the data dependency in the SAR approach causes imbalance of active data and ambiguity of inactive data throughout targets. We developed a ligand-based virtual screening model comprising 1121 target SAR models built using a random forest algorithm. The performance of each target model was tested by employing the ROC curve and the mean score using an internal five-fold cross validation. Moreover, recall rates for top-k targets were calculated to assess the performance of target ranking. A benchmark model using an optimized sampling method and parameters was examined via external validation set. The result shows recall rates of 67.6% and 73.9% for top-11 (1% of the total targets) and top-33, respectively. We provide a website for users to search the top-k targets for query ligands available publicly at http://rfqsar.kaist.ac.kr . The target models that we built can be used for both predicting the activity of ligands toward each target and ranking candidate targets for a query ligand using a unified scoring scheme. The scores are additionally fitted to the probability so that users can estimate how likely a ligand-target interaction is active. The user interface of our web site is user friendly and intuitive, offering useful information and cross references.
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Improved OAM-Based Radar Targets Detection Using Uniform Concentric Circular Arrays
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Mingtuan Lin
2016-01-01
Full Text Available Without any relative moves or beam scanning, the novel Orbital-Angular-Momentum- (OAM- based radar targets detection technique using uniform concentric circular arrays (UCCAs shows the azimuthal estimation ability, which provides new perspective for radar system design. However, the main estimation method, that is, Fast Fourier Transform (FFT, under this scheme suffers from low resolution. As a solution, this paper rebuilds the OAM-based radar targets detection model and introduces the multiple signal classification (MUSIC algorithm to improve the resolution for detecting targets within the main lobes. The spatial smoothing technique is proposed to tackle the coherent problem brought by the proposed model. Analytical study and simulation demonstrate the superresolution estimation capacity the MUSIC algorithm can achieve for detecting targets within the main lobes. The performance of the MUSIC algorithm to detect targets not illuminated by the main lobes is further evaluated. Despite the fact that MUSIC algorithm loses the resolution advantage under this case, its estimation is more robust than that of the FFT method. Overall, the proposed MUSIC algorithm for the OAM-based radar system demonstrates the superresolution ability for detecting targets within the main lobes and good robustness for targets out of the main lobes.
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An infrared small target detection method based on multiscale local homogeneity measure
Nie, Jinyan; Qu, Shaocheng; Wei, Yantao; Zhang, Liming; Deng, Lizhen
2018-05-01
Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.
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Detection of target phonemes in spontaneous and read speech.
Mehta, G; Cutler, A
1988-01-01
Although spontaneous speech occurs more frequently in most listeners' experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalise to the recognition of spontaneous speech. In the present study listeners were presented with both spontaneous and read speech materials, and their response time to detect word-initial target phonemes was measured. Responses were, overall, equally fast in each speech mode. However, analysis of effects previously reported in phoneme detection studies revealed significant differences between speech modes. In read speech but not in spontaneous speech, later targets were detected more rapidly than targets preceded by short words. In contrast, in spontaneous speech but not in read speech, targets were detected more rapidly in accented than in unaccented words and in strong than in weak syllables. An explanation for this pattern is offered in terms of characteristic prosodic differences between spontaneous and read speech. The results support claims from previous work that listeners pay great attention to prosodic information in the process of recognising speech.
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Penalty dynamic programming algorithm for dim targets detection in sensor systems.
Huang, Dayu; Xue, Anke; Guo, Yunfei
2012-01-01
In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD) called penalty DP-TBD (PDP-TBD) is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.
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Penalty Dynamic Programming Algorithm for Dim Targets Detection in Sensor Systems
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Yunfei Guo
2012-04-01
Full Text Available In order to detect and track multiple maneuvering dim targets in sensor systems, an improved dynamic programming track-before-detect algorithm (DP-TBD called penalty DP-TBD (PDP-TBD is proposed. The performances of tracking techniques are used as a feedback to the detection part. The feedback is constructed by a penalty term in the merit function, and the penalty term is a function of the possible target state estimation, which can be obtained by the tracking methods. With this feedback, the algorithm combines traditional tracking techniques with DP-TBD and it can be applied to simultaneously detect and track maneuvering dim targets. Meanwhile, a reasonable constraint that a sensor measurement can originate from one target or clutter is proposed to minimize track separation. Thus, the algorithm can be used in the multi-target situation with unknown target numbers. The efficiency and advantages of PDP-TBD compared with two existing methods are demonstrated by several simulations.
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Target Detection Using an AOTF Hyperspectral Imager
Cheng, L-J.; Mahoney, J.; Reyes, F.; Suiter, H.
1994-01-01
This paper reports results of a recent field experiment using a prototype system to evaluate the acousto-optic tunable filter polarimetric hyperspectral imaging technology for target detection applications.
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Dim small targets detection based on self-adaptive caliber temporal-spatial filtering
Fan, Xiangsuo; Xu, Zhiyong; Zhang, Jianlin; Huang, Yongmei; Peng, Zhenming
2017-09-01
To boost the detect ability of dim small targets, this paper began by using improved anisotropy for background prediction (IABP), followed by target enhancement by improved high-order cumulates (HQS). Finally, on the basis of image pre-processing, to address the problem of missed and wrong detection caused by fixed caliber of traditional pipeline filtering, this paper used targets' multi-frame movement correlation in the time-space domain, combined with the scale-space theory, to propose a temporal-spatial filtering algorithm which allows the caliber to make self-adaptive changes according to the changes of the targets' scale, effectively solving the detection-related issues brought by unchanged caliber and decreased/increased size of the targets. Experiments showed that the improved anisotropic background predication could be loyal to the true background of the original image to the maximum extent, presenting a superior overall performance to other background prediction methods; the improved HQS significantly increased the signal-noise ratio of images; when the signal-noise ratio was lower than 2.6 dB, this detection algorithm could effectively eliminate noise and detect targets. For the algorithm, the lowest signal-to-noise ratio of the detectable target is 0.37.
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Detectability counts when assessing populations for biodiversity targets.
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Silviu O Petrovan
Full Text Available Efficient, practical and accurate estimates of population parameters are a necessary basis for effective conservation action to meet biodiversity targets. The brown hare is representative of many European farmland species: historically widespread and abundant but having undergone rapid declines as a result of agricultural intensification. As a priority species in the UK Biodiversity Action Plan, it has national targets for population increase that are part of wider national environmental indicators. Previous research has indicated that brown hare declines have been greatest in pastural landscapes and that gains might be made by focussing conservation effort there. We therefore used hares in pastural landscapes to examine how basic changes in survey methodology can affect the precision of population density estimates and related these to national targets for biodiversity conservation in the UK. Line transects for hares carried out at night resulted in higher numbers of detections, had better-fitting detection functions and provided more robust density estimates with lower effort than those during the day, due primarily to the increased probability of detection of hares at night and the nature of hare responses to the observer. Hare spring densities varied widely within a single region, with a pooled mean of 20.6 hares km(-2, significantly higher than the reported national average of hares in pastures of 3.3 hares km(-2. The high number of encounters allowed us to resolve hare densities at site, season and year scales. We demonstrate how survey conduct can impact on data quantity and quality with implications for setting and monitoring biodiversity targets. Our case study of the brown hare provides evidence that for wildlife species with low detectability, large scale volunteer-based monitoring programmes, either species specific or generalist, might be more successfully and efficiently carried out by a small number of trained personnel able to
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Contrast, size, and orientation-invariant target detection in infrared imagery
Zhou, Yi-Tong; Crawshaw, Richard D.
1991-08-01
Automatic target detection in IR imagery is a very difficult task due to variations in target brightness, shape, size, and orientation. In this paper, the authors present a contrast, size, and orientation invariant algorithm based on Gabor functions for detecting targets from a single IR image frame. The algorithms consists of three steps. First, it locates potential targets by using low-resolution Gabor functions which resist noise and background clutter effects, then, it removes false targets and eliminates redundant target points based on a similarity measure. These two steps mimic human vision processing but are different from Zeevi's Foveating Vision System. Finally, it uses both low- and high-resolution Gabor functions to verify target existence. This algorithm has been successfully tested on several IR images that contain multiple examples of military vehicles with different size and brightness in various background scenes and orientations.
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Directional detection of dark matter with two-dimensional targets
Hochberg, Yonit; Kahn, Yonatan; Lisanti, Mariangela; Tully, Christopher G.; Zurek, Kathryn M.
2017-09-01
We propose two-dimensional materials as targets for direct detection of dark matter. Using graphene as an example, we focus on the case where dark matter scattering deposits sufficient energy on a valence-band electron to eject it from the target. We show that the sensitivity of graphene to dark matter of MeV to GeV mass can be comparable, for similar exposure and background levels, to that of semiconductor targets such as silicon and germanium. Moreover, a two-dimensional target is an excellent directional detector, as the ejected electron retains information about the angular dependence of the incident dark matter particle. This proposal can be implemented by the PTOLEMY experiment, presenting for the first time an opportunity for directional detection of sub-GeV dark matter.
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Drone Detection with Chirp‐Pulse Radar Based on Target Fluctuation Models
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Byung‐Kwan Kim
2018-04-01
Full Text Available This paper presents a pulse radar system to detect drones based on a target fluctuation model, specifically the Swerling target model. Because drones are small atypical objects and are mainly composed of non‐conducting materials, their radar cross‐section value is low and fluctuating. Therefore, determining the target fluctuation model and applying a proper integration method are important. The proposed system is herein experimentally verified and the results are discussed. A prototype design of the pulse radar system is based on radar equations. It adopts three different pulse modes and a coherent pulse integration to ensure a high signal‐to‐noise ratio. Outdoor measurements are performed with a prototype radar system to detect Doppler frequencies from both the drone frame and blades. The results indicate that the drone frame and blades are detected within an instrumental maximum range. Additionally, the results show that the drone's frame and blades are close to the Swerling 3 and 4 target models, respectively. By the analysis of the Swerling target models, proper integration methods for detecting drones are verified and can thus contribute to increasing in detectability.
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Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection
Kim, Sungho; Song, Woo-Jin; Kim, So-Hyun
2016-01-01
Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR) images or infrared (IR) images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT) and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter) and an asymmetric morphological closing filter (AMCF, post-filter) into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC)-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic database generated
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Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection
Directory of Open Access Journals (Sweden)
Sungho Kim
2016-07-01
Full Text Available Long-range ground targets are difficult to detect in a noisy cluttered environment using either synthetic aperture radar (SAR images or infrared (IR images. SAR-based detectors can provide a high detection rate with a high false alarm rate to background scatter noise. IR-based approaches can detect hot targets but are affected strongly by the weather conditions. This paper proposes a novel target detection method by decision-level SAR and IR fusion using an Adaboost-based machine learning scheme to achieve a high detection rate and low false alarm rate. The proposed method consists of individual detection, registration, and fusion architecture. This paper presents a single framework of a SAR and IR target detection method using modified Boolean map visual theory (modBMVT and feature-selection based fusion. Previous methods applied different algorithms to detect SAR and IR targets because of the different physical image characteristics. One method that is optimized for IR target detection produces unsuccessful results in SAR target detection. This study examined the image characteristics and proposed a unified SAR and IR target detection method by inserting a median local average filter (MLAF, pre-filter and an asymmetric morphological closing filter (AMCF, post-filter into the BMVT. The original BMVT was optimized to detect small infrared targets. The proposed modBMVT can remove the thermal and scatter noise by the MLAF and detect extended targets by attaching the AMCF after the BMVT. Heterogeneous SAR and IR images were registered automatically using the proposed RANdom SAmple Region Consensus (RANSARC-based homography optimization after a brute-force correspondence search using the detected target centers and regions. The final targets were detected by feature-selection based sensor fusion using Adaboost. The proposed method showed good SAR and IR target detection performance through feature selection-based decision fusion on a synthetic
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Polarization Calculation and Underwater Target Detection Inspired by Biological Visual Imaging
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Jie Shen
2014-04-01
Full Text Available In challenging underwater environments, the polarization parameter maps calculated by the Stokes model are characterized by the high noise and error, harassing the underwater target detection tasks. In order to solve this problem, this paper proposes a novel bionic polarization calculation and underwater target detection method by modeling the visual system of mantis shrimps. This system includes many operators including a polarization-opposition calculation, a factor optimization and a visual neural network model. A calibration learning method is proposed to search the optimal value of the factors in the linear subtraction model. Finally, a six-channel visual neural network model is proposed to detect the underwater targets. Experimental results proved that the maps produced by the polarization-opposition parameter is more accurate and have lower noise than that produced by the Stokes parameter, achieving better performance in underwater target detection tasks.
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Shuxin, Li; Zhilong, Zhang; Biao, Li
2018-01-01
Plane is an important target category in remote sensing targets and it is of great value to detect the plane targets automatically. As remote imaging technology developing continuously, the resolution of the remote sensing image has been very high and we can get more detailed information for detecting the remote sensing targets automatically. Deep learning network technology is the most advanced technology in image target detection and recognition, which provided great performance improvement in the field of target detection and recognition in the everyday scenes. We combined the technology with the application in the remote sensing target detection and proposed an algorithm with end to end deep network, which can learn from the remote sensing images to detect the targets in the new images automatically and robustly. Our experiments shows that the algorithm can capture the feature information of the plane target and has better performance in target detection with the old methods.
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Remote sensing image ship target detection method based on visual attention model
Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong
2017-11-01
The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.
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Visual performance on detection tasks with double-targets of the same and different difficulty.
Chan, Alan H S; Courtney, Alan J; Ma, C W
2002-10-20
This paper reports a study of measurement of horizontal visual sensitivity limits for 16 subjects in single-target and double-targets detection tasks. Two phases of tests were conducted in the double-targets task; targets of the same difficulty were tested in phase one while targets of different difficulty were tested in phase two. The range of sensitivity for the double-targets test was found to be smaller than that for single-target in both the same and different target difficulty cases. The presence of another target was found to affect performance to a marked degree. Interference effect of the difficult target on detection of the easy one was greater than that of the easy one on the detection of the difficult one. Performance decrement was noted when correct percentage detection was plotted against eccentricity of target in both the single-target and double-targets tests. Nevertheless, the non-significant correlation found between the performance for the two tasks demonstrated that it was impossible to predict quantitatively ability for detection of double targets from the data for single targets. This indicated probable problems in generalizing data for single target visual lobes to those for multiple targets. Also lobe area values obtained from measurements using a single-target task cannot be applied in a mathematical model for situations with multiple occurrences of targets.
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Combining orthogonal polarization for elongated target detection with GPR
International Nuclear Information System (INIS)
Lualdi, Maurizio; Lombardi, Federico
2014-01-01
For an accurate imaging of ground penetrating radar data the polarization characteristics of the propagating electromagnetic (EM) wavefield and wave amplitude variations with antenna pattern orientation must be taken into account. For objects that show some directionality feature and cylindrical shape any misalignment between transmitter and target can strongly modify the polarization state of the backscattered wavefield, thus conditioning the detection capability of the system. Hints on the depolarization can be used to design the optimal GPR antenna survey to avoid omissions and pitfalls during data processing. This research addresses the issue of elongated target detection through a multi azimuth (or multi polarization) approach based on the combination of mutually orthogonal GPR data. Results from the analysis of the formal scattering problem demonstrate how this strategy can reach a scalar formulation of the scattering matrix and achieve a rotational invariant quantity. The effectiveness of the algorithm is then evaluated with a detailed field example showing results closely proximal to those obtained under the optimal alignment condition: detection is significantly improved and the risk of target missing is reduced. (paper)
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Detection of range migrating targets in compound-Gaussian clutter
Petrov, N.; le Chevalier, F.; Yarovyi, O.
2018-01-01
This paper deals with the problem of coherent radar detection of fast moving targets in a high range resolution mode. In particular, we are focusing on the spiky clutter modeled as a compound Gaussian process with rapidly varying power along range. Additionally, a fast moving target of interest has
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Tensor Fukunaga-Koontz transform for small target detection in infrared images
Liu, Ruiming; Wang, Jingzhuo; Yang, Huizhen; Gong, Chenglong; Zhou, Yuanshen; Liu, Lipeng; Zhang, Zhen; Shen, Shuli
2016-09-01
Infrared small targets detection plays a crucial role in warning and tracking systems. Some novel methods based on pattern recognition technology catch much attention from researchers. However, those classic methods must reshape images into vectors with the high dimensionality. Moreover, vectorizing breaks the natural structure and correlations in the image data. Image representation based on tensor treats images as matrices and can hold the natural structure and correlation information. So tensor algorithms have better classification performance than vector algorithms. Fukunaga-Koontz transform is one of classification algorithms and it is a vector version method with the disadvantage of all vector algorithms. In this paper, we first extended the Fukunaga-Koontz transform into its tensor version, tensor Fukunaga-Koontz transform. Then we designed a method based on tensor Fukunaga-Koontz transform for detecting targets and used it to detect small targets in infrared images. The experimental results, comparison through signal-to-clutter, signal-to-clutter gain and background suppression factor, have validated the advantage of the target detection based on the tensor Fukunaga-Koontz transform over that based on the Fukunaga-Koontz transform.
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Tiwari, K. C.; Arora, M. K.; Singh, D.
2011-10-01
Hyperspectral data acquired over hundreds of narrow contiguous wavelength bands are extremely suitable for target detection due to their high spectral resolution. Though spectral response of every material is expected to be unique, but in practice, it exhibits variations, which is known as spectral variability. Most target detection algorithms depend on spectral modelling using a priori available target spectra In practice, target spectra is, however, seldom available a priori. Independent component analysis (ICA) is a new evolving technique that aims at finding out components which are statistically independent or as independent as possible. The technique therefore has the potential of being used for target detection applications. A assessment of target detection from hyperspectral images using ICA and other algorithms based on spectral modelling may be of immense interest, since ICA does not require a priori target information. The aim of this paper is, thus, to assess the potential of ICA based algorithm vis a vis other prevailing algorithms for military target detection. Four spectral matching algorithms namely Orthogonal Subspace Projection (OSP), Constrained Energy Minimisation (CEM), Spectral Angle Mapper (SAM) and Spectral Correlation Mapper (SCM), and four anomaly detection algorithms namely OSP anomaly detector (OSPAD), Reed-Xiaoli anomaly detector (RXD), Uniform Target Detector (UTD) and a combination of Reed-Xiaoli anomaly detector and Uniform Target Detector (RXD-UTD) were considered. The experiments were conducted using a set of synthetic and AVIRIS hyperspectral images containing aircrafts as military targets. A comparison of true positive and false positive rates of target detections obtained from ICA and other algorithms plotted on a receiver operating curves (ROC) space indicates the superior performance of the ICA over other algorithms.
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Detection of Target ssDNA Using a Microfabricated Hall Magnetometer with Correlated Optical Readout
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Steven M. Hira
2012-01-01
Full Text Available Sensing biological agents at the genomic level, while enhancing the response time for biodetection over commonly used, optics-based techniques such as nucleic acid microarrays or enzyme-linked immunosorbent assays (ELISAs, is an important criterion for new biosensors. Here, we describe the successful detection of a 35-base, single-strand nucleic acid target by Hall-based magnetic transduction as a mimic for pathogenic DNA target detection. The detection platform has low background, large signal amplification following target binding and can discriminate a single, 350 nm superparamagnetic bead labeled with DNA. Detection of the target sequence was demonstrated at 364 pM (<2 target DNA strands per bead target DNA in the presence of 36 μM nontarget (noncomplementary DNA (<10 ppm target DNA using optical microscopy detection on a GaAs Hall mimic. The use of Hall magnetometers as magnetic transduction biosensors holds promise for multiplexing applications that can greatly improve point-of-care (POC diagnostics and subsequent medical care.
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High-Resolution Remotely Sensed Small Target Detection by Imitating Fly Visual Perception Mechanism
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Fengchen Huang
2012-01-01
Full Text Available The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.
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High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.
Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min
2012-01-01
The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.
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Moving target detection based on temporal-spatial information fusion for infrared image sequences
Toing, Wu-qin; Xiong, Jin-yu; Zeng, An-jun; Wu, Xiao-ping; Xu, Hao-peng
2009-07-01
Moving target detection and localization is one of the most fundamental tasks in visual surveillance. In this paper, through analyzing the advantages and disadvantages of the traditional approaches about moving target detection, a novel approach based on temporal-spatial information fusion is proposed for moving target detection. The proposed method combines the spatial feature in single frame and the temporal properties within multiple frames of an image sequence of moving target. First, the method uses the spatial image segmentation for target separation from background and uses the local temporal variance for extracting targets and wiping off the trail artifact. Second, the logical "and" operator is used to fuse the temporal and spatial information. In the end, to the fusion image sequence, the morphological filtering and blob analysis are used to acquire exact moving target. The algorithm not only requires minimal computation and memory but also quickly adapts to the change of background and environment. Comparing with other methods, such as the KDE, the Mixture of K Gaussians, etc., the simulation results show the proposed method has better validity and higher adaptive for moving target detection, especially in infrared image sequences with complex illumination change, noise change, and so on.
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Indoor detection of passive targets recast as an inverse scattering problem
Gottardi, G.; Moriyama, T.
2017-10-01
The wireless local area networks represent an alternative to custom sensors and dedicated surveillance systems for target indoor detection. The availability of the channel state information has opened the exploitation of the spatial and frequency diversity given by the orthogonal frequency division multiplexing. Such a fine-grained information can be used to solve the detection problem as an inverse scattering problem. The goal of the detection is to reconstruct the properties of the investigation domain, namely to estimate if the domain is empty or occupied by targets, starting from the measurement of the electromagnetic perturbation of the wireless channel. An innovative inversion strategy exploiting both the frequency and the spatial diversity of the channel state information is proposed. The target-dependent features are identified combining the Kruskal-Wallis test and the principal component analysis. The experimental validation points out the detection performance of the proposed method when applied to an existing wireless link of a WiFi architecture deployed in a real indoor scenario. False detection rates lower than 2 [%] have been obtained.
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Exploring drug-target interaction networks of illicit drugs
Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming
2013-01-01
Background Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit dru...
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Hierarchical effects on target detection and conflict monitoring
Cao, Bihua; Gao, Feng; Ren, Maofang; Li, Fuhong
2016-01-01
Previous neuroimaging studies have demonstrated a hierarchical functional structure of the frontal cortices of the human brain, but the temporal course and the electrophysiological signature of the hierarchical representation remains unaddressed. In the present study, twenty-one volunteers were asked to perform a nested cue-target task, while their scalp potentials were recorded. The results showed that: (1) in comparison with the lower-level hierarchical targets, the higher-level targets elicited a larger N2 component (220–350 ms) at the frontal sites, and a smaller P3 component (350–500 ms) across the frontal and parietal sites; (2) conflict-related negativity (non-target minus target) was greater for the lower-level hierarchy than the higher-level, reflecting a more intensive process of conflict monitoring at the final step of target detection. These results imply that decision making, context updating, and conflict monitoring differ among different hierarchical levels of abstraction. PMID:27561989
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Targets Mask U-Net for Wind Turbines Detection in Remote Sensing Images
Han, M.; Wang, H.; Wang, G.; Liu, Y.
2018-04-01
To detect wind turbines precisely and quickly in very high resolution remote sensing images (VHRRSI) we propose target mask U-Net. This convolution neural network (CNN), which is carefully designed to be a wide-field detector, models the pixel class assignment to wind turbines and their context information. The shadow, which is the context information of the target in this study, has been regarded as part of a wind turbine instance. We have trained the target mask U-Net on training dataset, which is composed of down sampled image blocks and instance mask blocks. Some post-processes have been integrated to eliminate wrong spots and produce bounding boxes of wind turbine instances. The evaluation metrics prove the reliability and effectiveness of our method for the average F1-score of our detection method is up to 0.97. The comparison of detection accuracy and time consuming with the weakly supervised targets detection method based on CNN illustrates the superiority of our method.
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Camouflaged target detection based on polarized spectral features
Tan, Jian; Zhang, Junping; Zou, Bin
2016-05-01
The polarized hyperspectral images (PHSI) include polarization, spectral, spatial and radiant features, which provide more information about objects and scenes than traditional intensity or spectrum ones. And polarization can suppress the background and highlight the object, leading to the high potential to improve camouflaged target detection. So polarized hyperspectral imaging technique has aroused extensive concern in the last few years. Nowadays, the detection methods are still not very mature, most of which are rooted in the detection of hyperspectral image. And before using these algorithms, Stokes vector is used to process the original four-dimensional polarized hyperspectral data firstly. However, when the data is large and complex, the amount of calculation and error will increase. In this paper, tensor is applied to reconstruct the original four-dimensional data into new three-dimensional data, then, the constraint energy minimization (CEM) is used to process the new data, which adds the polarization information to construct the polarized spectral filter operator and takes full advantages of spectral and polarized information. This way deals with the original data without extracting the Stokes vector, so as to reduce the computation and error greatly. The experimental results also show that the proposed method in this paper is more suitable for the target detection of the PHSI.
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Neuromorphic Modeling of Moving Target Detection in Insects
2007-12-31
Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39, 18 Grants FA9550-04-1-0283 and FA9550-04-1-0294 Neuromorphic Modeling of Moving Target Detection...natural for neuromorphic sensory processing. We developed visual motion detection circuitry, including photodetectors, early vision, and models for both...Lincoln Labs 3DM2 run, Tanner Research reserved and utilized space corresponding to two MOSIS ’tiny chips ’ (2mm square each), each with three interconnected
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MutScan: fast detection and visualization of target mutations by scanning FASTQ data.
Chen, Shifu; Huang, Tanxiao; Wen, Tiexiang; Li, Hong; Xu, Mingyan; Gu, Jia
2018-01-22
Some types of clinical genetic tests, such as cancer testing using circulating tumor DNA (ctDNA), require sensitive detection of known target mutations. However, conventional next-generation sequencing (NGS) data analysis pipelines typically involve different steps of filtering, which may cause miss-detection of key mutations with low frequencies. Variant validation is also indicated for key mutations detected by bioinformatics pipelines. Typically, this process can be executed using alignment visualization tools such as IGV or GenomeBrowse. However, these tools are too heavy and therefore unsuitable for validating mutations in ultra-deep sequencing data. We developed MutScan to address problems of sensitive detection and efficient validation for target mutations. MutScan involves highly optimized string-searching algorithms, which can scan input FASTQ files to grab all reads that support target mutations. The collected supporting reads for each target mutation will be piled up and visualized using web technologies such as HTML and JavaScript. Algorithms such as rolling hash and bloom filter are applied to accelerate scanning and make MutScan applicable to detect or visualize target mutations in a very fast way. MutScan is a tool for the detection and visualization of target mutations by only scanning FASTQ raw data directly. Compared to conventional pipelines, this offers a very high performance, executing about 20 times faster, and offering maximal sensitivity since it can grab mutations with even one single supporting read. MutScan visualizes detected mutations by generating interactive pile-ups using web technologies. These can serve to validate target mutations, thus avoiding false positives. Furthermore, MutScan can visualize all mutation records in a VCF file to HTML pages for cloud-friendly VCF validation. MutScan is an open source tool available at GitHub: https://github.com/OpenGene/MutScan.
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Infrared Small Moving Target Detection via Saliency Histogram and Geometrical Invariability
Directory of Open Access Journals (Sweden)
Minjie Wan
2017-06-01
Full Text Available In order to detect both bright and dark small moving targets effectively in infrared (IR video sequences, a saliency histogram and geometrical invariability based method is presented in this paper. First, a saliency map that roughly highlights the salient regions of the original image is obtained by tuning its amplitude spectrum in the frequency domain. Then, a saliency histogram is constructed by means of averaging the accumulated saliency value of each gray level in the map, through which bins corresponding to bright target and dark target are assigned with large values in the histogram. Next, single-frame detection of candidate targets is accomplished by a binarized segmentation using an adaptive threshold, and their centroid coordinates with sub-pixel accuracy are calculated through a connected components labeling method as well as a gray-weighted criterion. Finally, considering the motion characteristics in consecutive frames, an inter-frame false alarm suppression method based on geometrical invariability is developed to improve the precision rate further. Quantitative analyses demonstrate the detecting precision of this proposed approach can be up to 97% and Receiver Operating Characteristic (ROC curves further verify our method outperforms other state-of-the-arts methods in both detection rate and false alarm rate.
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Detection and characterization of ship targets using CryoSat-2 altimeter waveforms
G?mez-Enri, Jesus; Scozzari, Andrea; Soldovieri, Francesco; Coca, Josep; Vignudelli, Stefano
2016-01-01
This article describes an investigation of the new possibilities offered by SAR altimetry compared with conventional altimetry in the detection and characterization of non-ocean targets. We explore the capabilities of the first SAR altimeter installed on the European Space Agency satellite CryoSat-2 for the detection and characterization of ships. We propose a methodology for the detection of anomalous targets in the radar signals, based on the advantages of SAR/Doppler processing over conven...
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Directional support value of Gaussian transformation for infrared small target detection.
Yang, Changcai; Ma, Jiayi; Qi, Shengxiang; Tian, Jinwen; Zheng, Sheng; Tian, Xin
2015-03-20
Robust small target detection is one of the key techniques in IR search and tracking systems for self-defense or attacks. In this paper we present a robust solution for small target detection in a single IR image. The key ideas of the proposed method are to use the directional support value of Gaussian transform (DSVoGT) to enhance the targets, and use the multiscale representation provided by DSVoGT to reduce the false alarm rate. The original image is decomposed into sub-bands in different orientations by convolving the image with the directional support value filters, which are deduced from the weighted mapped least-squares-support vector machines (LS-SVMs). Based on the sub-band images, a support value of Gaussian matrix is constructed, and the trace of this matrix is then defined as the target measure. The corresponding multiscale correlations of the target measures are computed for enhancing target signal while suppressing the background clutter. We demonstrate the advantages of the proposed method on real IR images and compare the results against those obtained from standard detection approaches, including the top-hat filter, max-mean filter, max-median filter, min-local-Laplacian of Gaussian (LoG) filter, as well as LS-SVM. The experimental results on various cluttered background images show that the proposed method outperforms other detectors.
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Performance evaluation of sea surface simulation methods for target detection
Xia, Renjie; Wu, Xin; Yang, Chen; Han, Yiping; Zhang, Jianqi
2017-11-01
With the fast development of sea surface target detection by optoelectronic sensors, machine learning has been adopted to improve the detection performance. Many features can be learned from training images by machines automatically. However, field images of sea surface target are not sufficient as training data. 3D scene simulation is a promising method to address this problem. For ocean scene simulation, sea surface height field generation is the key point to achieve high fidelity. In this paper, two spectra-based height field generation methods are evaluated. Comparison between the linear superposition and linear filter method is made quantitatively with a statistical model. 3D ocean scene simulating results show the different features between the methods, which can give reference for synthesizing sea surface target images with different ocean conditions.
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Directory of Open Access Journals (Sweden)
Jiang Tie-zhen
2015-01-01
Full Text Available Space target surveillance generally uses active radars. To take full advantage of passive radars, the idea of using spaceborne illuminators of opportunity for space target detection is presented in this paper. Analysis of the detectable time and direct wave suppression shows that passive radar using spaceborne illuminators of opportunity can effectively detect a Low-Earth-Orbit (LEO target. Meanwhile, Ku and L band bi-static radar cross section of passive radars that use spaceborne illuminators of opportunity are presented by simulation, providing the basis of choosing space target forward scatter. Finally the key parameters, mainly system gain, accumulation time and radiation source selection are studied. Results show that system size using satellite TV signals as illuminators of opportunity is relatively small. These encouraging results should stimulate the development of passive radar detection of space targets using spaceborne illuminators of opportunity.
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International Nuclear Information System (INIS)
Osman, Abdalla; El-Sheimy, Naser; Nourledin, Aboelamgd; Theriault, Jim; Campbell, Scott
2009-01-01
The problem of target detection and tracking in the ocean environment has attracted considerable attention due to its importance in military and civilian applications. Sonobuoys are one of the capable passive sonar systems used in underwater target detection. Target detection and bearing estimation are mainly obtained through spectral analysis of received signals. The frequency resolution introduced by current techniques is limited which affects the accuracy of target detection and bearing estimation at a relatively low signal-to-noise ratio (SNR). This research investigates the development of a bearing estimation method using fast orthogonal search (FOS) for enhanced spectral estimation. FOS is employed in this research in order to improve both target detection and bearing estimation in the case of low SNR inputs. The proposed methods were tested using simulated data developed for two different scenarios under different underwater environmental conditions. The results show that the proposed method is capable of enhancing the accuracy for target detection as well as bearing estimation especially in cases of a very low SNR
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Search-Lidar Demonstrator for Detection of Small Sea-Surface Targets
Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M. van; Cohen, L.H.; Schleijpen, H.M.A.
2008-01-01
Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC’s, and speedboats. Lidar
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Detection of Small Sea-Surface Targets with a Search Lidar
Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M.; Cohen, L.A.
2007-01-01
Naval operations in the littoral have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and low velocity, which makes them hard to detect by radar in the presence of sea clutter. Typical threats include periscopes, jet skies, FIAC’s, and speedboats.
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Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images
Directory of Open Access Journals (Sweden)
Antonio Plaza
2010-01-01
Full Text Available Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS system over theWorld Trade Center (WTC in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.
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Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images
Directory of Open Access Journals (Sweden)
Paz Abel
2010-01-01
Full Text Available Abstract Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS system over theWorld Trade Center (WTC in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.
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Diagnostic imaging strategy for MDCT- or MRI-detected breast lesions: use of targeted sonography
International Nuclear Information System (INIS)
Nakano, Satoko; Ohtsuka, Masahiko; Mibu, Akemi; Karikomi, Masato; Sakata, Hitomi; Yamamoto, Masahiro
2012-01-01
Leading-edge technology such as magnetic resonance imaging (MRI) or computed tomography (CT) often reveals mammographically and ultrasonographically occult lesions. MRI is a well-documented, effective tool to evaluate these lesions; however, the detection rate of targeted sonography varies for MRI detected lesions, and its significance is not well established in diagnostic strategy of MRI detected lesions. We assessed the utility of targeted sonography for multidetector-row CT (MDCT)- or MRI-detected lesions in practice. We retrospectively reviewed 695 patients with newly diagnosed breast cancer who were candidates for breast conserving surgery and underwent MDCT or MRI in our hospital between January 2004 and March 2011. Targeted sonography was performed in all MDCT- or MRI-detected lesions followed by imaging-guided biopsy. Patient background, histopathology features and the sizes of the lesions were compared among benign, malignant and follow-up groups. Of the 695 patients, 61 lesions in 56 patients were detected by MDCT or MRI. The MDCT- or MRI-detected lesions were identified by targeted sonography in 58 out of 61 lesions (95.1%). Patients with pathological diagnoses were significantly older and more likely to be postmenopausal than the follow-up patients. Pathological diagnosis proved to be benign in 20 cases and malignant in 25. The remaining 16 lesions have been followed up. Lesion size and shape were not significantly different among the benign, malignant and follow-up groups. Approximately 95% of MDCT- or MRI-detected lesions were identified by targeted sonography, and nearly half of these lesions were pathologically proven malignancies in this study. Targeted sonography is a useful modality for MDCT- or MRI-detected breast lesions
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Detecting ship targets in spaceborne infrared image based on modeling radiation anomalies
Wang, Haibo; Zou, Zhengxia; Shi, Zhenwei; Li, Bo
2017-09-01
Using infrared imaging sensors to detect ship target in the ocean environment has many advantages compared to other sensor modalities, such as better thermal sensitivity and all-weather detection capability. We propose a new ship detection method by modeling radiation anomalies for spaceborne infrared image. The proposed method can be decomposed into two stages, where in the first stage, a test infrared image is densely divided into a set of image patches and the radiation anomaly of each patch is estimated by a Gaussian Mixture Model (GMM), and thereby target candidates are obtained from anomaly image patches. In the second stage, target candidates are further checked by a more discriminative criterion to obtain the final detection result. The main innovation of the proposed method is inspired by the biological mechanism that human eyes are sensitive to the unusual and anomalous patches among complex background. The experimental result on short wavelength infrared band (1.560 - 2.300 μm) and long wavelength infrared band (10.30 - 12.50 μm) of Landsat-8 satellite shows the proposed method achieves a desired ship detection accuracy with higher recall than other classical ship detection methods.
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NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.
Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina
2008-10-01
We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.
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Assessment of Schrodinger Eigenmaps for target detection
Dorado Munoz, Leidy P.; Messinger, David W.; Czaja, Wojtek
2014-06-01
Non-linear dimensionality reduction methods have been widely applied to hyperspectral imagery due to its structure as the information can be represented in a lower dimension without losing information, and because the non-linear methods preserve the local geometry of the data while the dimension is reduced. One of these methods is Laplacian Eigenmaps (LE), which assumes that the data lies on a low dimensional manifold embedded in a high dimensional space. LE builds a nearest neighbor graph, computes its Laplacian and performs the eigendecomposition of the Laplacian. These eigenfunctions constitute a basis for the lower dimensional space in which the geometry of the manifold is preserved. In addition to the reduction problem, LE has been widely used in tasks such as segmentation, clustering, and classification. In this regard, a new Schrodinger Eigenmaps (SE) method was developed and presented as a semi-supervised classification scheme in order to improve the classification performance and take advantage of the labeled data. SE is an algorithm built upon LE, where the former Laplacian operator is replaced by the Schrodinger operator. The Schrodinger operator includes a potential term V, that, taking advantage of the additional information such as labeled data, allows clustering of similar points. In this paper, we explore the idea of using SE in target detection. In this way, we present a framework where the potential term V is defined as a barrier potential: a diagonal matrix encoding the spatial position of the target, and the detection performance is evaluated by using different targets and different hyperspectral scenes.
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A Review of Ground Target Detection and Classification Techniques in Forward Scattering Radars
Directory of Open Access Journals (Sweden)
M. E. A. Kanona
2018-06-01
Full Text Available This paper presents a review of target detection and classification in forward scattering radar (FSR which is a special state of bistatic radars, designed to detect and track moving targets in the narrow region along the transmitter-receiver base line. FSR has advantages and incredible features over other types of radar configurations. All previous studies proved that FSR can be used as an alternative system for ground target detection and classification. The radar and FSR fundamentals were addressed and classification algorithms and techniques were debated. On the other hand, the current and future applications and the limitations of FSR were discussed.
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Aerial surveillance based on hierarchical object classification for ground target detection
Vázquez-Cervantes, Alberto; García-Huerta, Juan-Manuel; Hernández-Díaz, Teresa; Soto-Cajiga, J. A.; Jiménez-Hernández, Hugo
2015-03-01
Unmanned aerial vehicles have turned important in surveillance application due to the flexibility and ability to inspect and displace in different regions of interest. The instrumentation and autonomy of these vehicles have been increased; i.e. the camera sensor is now integrated. Mounted cameras allow flexibility to monitor several regions of interest, displacing and changing the camera view. A well common task performed by this kind of vehicles correspond to object localization and tracking. This work presents a hierarchical novel algorithm to detect and locate objects. The algorithm is based on a detection-by-example approach; this is, the target evidence is provided at the beginning of the vehicle's route. Afterwards, the vehicle inspects the scenario, detecting all similar objects through UTM-GPS coordinate references. Detection process consists on a sampling information process of the target object. Sampling process encode in a hierarchical tree with different sampling's densities. Coding space correspond to a huge binary space dimension. Properties such as independence and associative operators are defined in this space to construct a relation between the target object and a set of selected features. Different densities of sampling are used to discriminate from general to particular features that correspond to the target. The hierarchy is used as a way to adapt the complexity of the algorithm due to optimized battery duty cycle of the aerial device. Finally, this approach is tested in several outdoors scenarios, proving that the hierarchical algorithm works efficiently under several conditions.
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Gedalin, Daniel; Oiknine, Yaniv; August, Isaac; Blumberg, Dan G.; Rotman, Stanley R.; Stern, Adrian
2017-04-01
Compressive sensing theory was proposed to deal with the high quantity of measurements demanded by traditional hyperspectral systems. Recently, a compressive spectral imaging technique dubbed compressive sensing miniature ultraspectral imaging (CS-MUSI) was presented. This system uses a voltage controlled liquid crystal device to create multiplexed hyperspectral cubes. We evaluate the utility of the data captured using the CS-MUSI system for the task of target detection. Specifically, we compare the performance of the matched filter target detection algorithm in traditional hyperspectral systems and in CS-MUSI multiplexed hyperspectral cubes. We found that the target detection algorithm performs similarly in both cases, despite the fact that the CS-MUSI data is up to an order of magnitude less than that in conventional hyperspectral cubes. Moreover, the target detection is approximately an order of magnitude faster in CS-MUSI data.
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He, Michael W; Lee, Patrick S; Sweeney, Zachary K
2015-02-01
Selectivity is a central aspect of lead optimization in the drug discovery process. Medicinal chemists often try to decrease molecular flexibility to improve selectivity, given the common belief that the two are interdependent. To investigate the relationship between polypharmacology and conformational flexibility, we mined the Protein Data Bank and constructed a dataset of pharmaceutically relevant ligands that crystallized in more than one protein target while binding to each co-crystallized receptor with similar in vitro affinities. After analyzing the molecular conformations of these 100 ligands, we found that 59 ligands bound to different protein targets without significantly changing conformation, suggesting that there is no distinct correlation between conformational flexibility and polypharmacology within our dataset. Ligands crystallized in similar proteins and highly ligand-efficient compounds with five or fewer rotatable bonds were less likely to adjust conformation when binding. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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A speeded-up saliency region-based contrast detection method for small targets
Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang
2018-04-01
To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.
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Liu, Xian; Xu, Yuan; Li, Shanshan; Wang, Yulan; Peng, Jianlong; Luo, Cheng; Luo, Xiaomin; Zheng, Mingyue; Chen, Kaixian; Jiang, Hualiang
2014-01-01
Ligand-based in silico target fishing can be used to identify the potential interacting target of bioactive ligands, which is useful for understanding the polypharmacology and safety profile of existing drugs. The underlying principle of the approach is that known bioactive ligands can be used as reference to predict the targets for a new compound. We tested a pipeline enabling large-scale target fishing and drug repositioning, based on simple fingerprint similarity rankings with data fusion. A large library containing 533 drug relevant targets with 179,807 active ligands was compiled, where each target was defined by its ligand set. For a given query molecule, its target profile is generated by similarity searching against the ligand sets assigned to each target, for which individual searches utilizing multiple reference structures are then fused into a single ranking list representing the potential target interaction profile of the query compound. The proposed approach was validated by 10-fold cross validation and two external tests using data from DrugBank and Therapeutic Target Database (TTD). The use of the approach was further demonstrated with some examples concerning the drug repositioning and drug side-effects prediction. The promising results suggest that the proposed method is useful for not only finding promiscuous drugs for their new usages, but also predicting some important toxic liabilities. With the rapid increasing volume and diversity of data concerning drug related targets and their ligands, the simple ligand-based target fishing approach would play an important role in assisting future drug design and discovery.
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Defending a single object against an attacker trying to detect a subset of false targets
International Nuclear Information System (INIS)
Peng, R.; Zhai, Q.Q.; Levitin, G.
2016-01-01
Deployment of false targets can be a very important and effective measure for enhancing the survivability of an object subjected to intentional attacks. Existing papers have assumed that false targets are either perfect or can be detected with a constant probability. In practice, the attacker may allocate part of its budget into intelligence actions trying to detect a subset of false targets. Analogously, the defender can allocate part of its budget into disinformation actions to prevent the false targets from being detected. In this paper, the detection probability of each false target is assumed to be a function of the intelligence and disinformation efforts allocated on the false target. The optimal resource distribution between target identification/disinformation and attack/protection efforts is studied as solutions of a non-cooperative two period min–max game between the two competitors for the case of constrained defense and attack resources. - Highlights: • A defense-attack problem is studied as a two-period min–max game. • Both intelligence contest over false targets and impact contest are considered. • Optimal defense and attack strategies are investigated with different parameters.
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Detection and localization of multiple short range targets using FMCW radar signal
Jardak, Seifallah
2016-07-26
In this paper, a 24 GHz frequency-modulated continuous wave radar is used to detect and localize both stationary and moving targets. Depending on the application, the implemented software offers different modes of operation. For example, it can simply output raw data samples for advanced offline processing or directly carry out a two dimensional fast Fourier transform to estimate the location and velocity of multiple targets. To suppress clutter and detect only moving targets, two methods based on the background reduction and the slow time processing techniques are implemented. A trade-off between the two methods is presented based on their performance and the required processing time. © 2016 IEEE.
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Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar
Directory of Open Access Journals (Sweden)
Raja Syamsul Azmir Raja Abdullah
2016-09-01
Full Text Available The passive bistatic radar (PBR system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR. The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system’s capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.
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Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar.
Raja Abdullah, Raja Syamsul Azmir; Abdul Aziz, Noor Hafizah; Abdul Rashid, Nur Emileen; Ahmad Salah, Asem; Hashim, Fazirulhisyam
2016-09-29
The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of this paper is to show the feasibility of passive FSR for moving target detection and classification by experimental analysis and results. The signal source is coming from the latest technology of 4G Long-Term Evolution (LTE) base station. A detailed explanation on the passive FSR receiver circuit, the detection scheme and the classification algorithm are given. In addition, the proposed passive FSR circuit employs the self-mixing technique at the receiver; hence the synchronization signal from the transmitter is not required. The experimental results confirm the passive FSR system's capability for ground target detection and classification. Furthermore, this paper illustrates the first classification result in the passive FSR system. The great potential in the passive FSR system provides a new research area in passive radar that can be used for diverse remote monitoring applications.
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Energy Technology Data Exchange (ETDEWEB)
Hao, Ming; Wang, Yanli, E-mail: ywang@ncbi.nlm.nih.gov; Bryant, Stephen H., E-mail: bryant@ncbi.nlm.nih.gov
2016-02-25
Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.
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International Nuclear Information System (INIS)
Hao, Ming; Wang, Yanli; Bryant, Stephen H.
2016-01-01
Identification of drug-target interactions (DTI) is a central task in drug discovery processes. In this work, a simple but effective regularized least squares integrating with nonlinear kernel fusion (RLS-KF) algorithm is proposed to perform DTI predictions. Using benchmark DTI datasets, our proposed algorithm achieves the state-of-the-art results with area under precision–recall curve (AUPR) of 0.915, 0.925, 0.853 and 0.909 for enzymes, ion channels (IC), G protein-coupled receptors (GPCR) and nuclear receptors (NR) based on 10 fold cross-validation. The performance can further be improved by using a recalculated kernel matrix, especially for the small set of nuclear receptors with AUPR of 0.945. Importantly, most of the top ranked interaction predictions can be validated by experimental data reported in the literature, bioassay results in the PubChem BioAssay database, as well as other previous studies. Our analysis suggests that the proposed RLS-KF is helpful for studying DTI, drug repositioning as well as polypharmacology, and may help to accelerate drug discovery by identifying novel drug targets. - Graphical abstract: Flowchart of the proposed RLS-KF algorithm for drug-target interaction predictions. - Highlights: • A nonlinear kernel fusion algorithm is proposed to perform drug-target interaction predictions. • Performance can further be improved by using the recalculated kernel. • Top predictions can be validated by experimental data.
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Low-Altitude and Slow-Speed Small Target Detection Based on Spectrum Zoom Processing
Directory of Open Access Journals (Sweden)
Xuwang Zhang
2018-01-01
Full Text Available This paper proposes a spectrum zoom processing based target detection algorithm for detecting the weak echo of low-altitude and slow-speed small (LSS targets in heavy ground clutter environments, which can be used to retrofit the existing radar systems. With the existing range-Doppler frequency images, the proposed method firstly concatenates the data from the same Doppler frequency slot of different images and then applies the spectrum zoom processing. After performing the clutter suppression, the target detection can be finally implemented. Through the theoretical analysis and real data verification, it is shown that the proposed algorithm can obtain a preferable spectrum zoom result and improve the signal-to-clutter ratio (SCR with a very low computational load.
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Gastric cancer target detection using near-infrared hyperspectral imaging with chemometrics
Yi, Weisong; Zhang, Jian; Jiang, Houmin; Zhang, Niya
2014-09-01
Gastric cancer is one of the leading causes of cancer death in the world due to its high morbidity and mortality. Hyperspectral imaging (HSI) is an emerging, non-destructive, cutting edge analytical technology that combines conventional imaging and spectroscopy in one single system. The manuscript has investigated the application of near-infrared hyperspectral imaging (900-1700 nm) (NIR-HSI) for gastric cancer detection with algorithms. Major spectral differences were observed in three regions (950-1050, 1150-1250, and 1400-1500 nm). By inspecting cancerous mean spectrum three major absorption bands were observed around 975, 1215 and 1450 nm. Furthermore, the cancer target detection results are consistent and conformed with histopathological examination results. These results suggest that NIR-HSI is a simple, feasible and sensitive optical diagnostic technology for gastric cancer target detection with chemometrics.
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Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong
2017-06-01
The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.
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Study on moving target detection to passive radar based on FM broadcast transmitter
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Target detection by a noncooperative illuminator is a topic of general interest in the electronic warfare field.First of all,direct-path interference(DPI)suppression which is the technique of bottleneck of moving target detection by a noncooperative frequency modulation(FM) broadcast transmitter is analyzed in this article;Secondly,a space-time-frequency domain synthetic solution to this problem is introduced:Adaptive nulling array processing is considered in the space domain,DPI cancellation based on adaptive fractional delay interpolation(AFDI)technique is used in planned time domain,and long-time coherent integration is utilized in the frequency domain;Finally,an experimental system is planned by considering FM broadcast transmitter as a noncooperative illuminator,Simulation results by real collected data show that the proposed method has a better performance of moving target detection.
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Aircraft target detection algorithm based on high resolution spaceborne SAR imagery
Zhang, Hui; Hao, Mengxi; Zhang, Cong; Su, Xiaojing
2018-03-01
In this paper, an image classification algorithm for airport area is proposed, which based on the statistical features of synthetic aperture radar (SAR) images and the spatial information of pixels. The algorithm combines Gamma mixture model and MRF. The algorithm using Gamma mixture model to obtain the initial classification result. Pixel space correlation based on the classification results are optimized by the MRF technique. Additionally, morphology methods are employed to extract airport (ROI) region where the suspected aircraft target samples are clarified to reduce the false alarm and increase the detection performance. Finally, this paper presents the plane target detection, which have been verified by simulation test.
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Exploring drug-target interaction networks of illicit drugs.
Atreya, Ravi V; Sun, Jingchun; Zhao, Zhongming
2013-01-01
Drug addiction is a complex and chronic mental disease, which places a large burden on the American healthcare system due to its negative effects on patients and their families. Recently, network pharmacology is emerging as a promising approach to drug discovery by integrating network biology and polypharmacology, allowing for a deeper understanding of molecular mechanisms of drug actions at the systems level. This study seeks to apply this approach for investigation of illicit drugs and their targets in order to elucidate their interaction patterns and potential secondary drugs that can aid future research and clinical care. In this study, we extracted 188 illicit substances and their related information from the DrugBank database. The data process revealed 86 illicit drugs targeting a total of 73 unique human genes, which forms an illicit drug-target network. Compared to the full drug-target network from DrugBank, illicit drugs and their target genes tend to cluster together and form four subnetworks, corresponding to four major medication categories: depressants, stimulants, analgesics, and steroids. External analysis of Anatomical Therapeutic Chemical (ATC) second sublevel classifications confirmed that the illicit drugs have neurological functions or act via mechanisms of stimulants, opioids, and steroids. To further explore other drugs potentially having associations with illicit drugs, we constructed an illicit-extended drug-target network by adding the drugs that have the same target(s) as illicit drugs to the illicit drug-target network. After analyzing the degree and betweenness of the network, we identified hubs and bridge nodes, which might play important roles in the development and treatment of drug addiction. Among them, 49 non-illicit drugs might have potential to be used to treat addiction or have addictive effects, including some results that are supported by previous studies. This study presents the first systematic review of the network
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Location detection and tracking of moving targets by a 2D IR-UWB radar system.
Nguyen, Van-Han; Pyun, Jae-Young
2015-03-19
In indoor environments, the Global Positioning System (GPS) and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB) technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB) radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF) is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.
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Transductive and matched-pair machine learning for difficult target detection problems
Theiler, James
2014-06-01
This paper will describe the application of two non-traditional kinds of machine learning (transductive machine learning and the more recently proposed matched-pair machine learning) to the target detection problem. The approach combines explicit domain knowledge to model the target signal with a more agnostic machine-learning approach to characterize the background. The concept is illustrated with simulated data from an elliptically-contoured background distribution, on which a subpixel target of known spectral signature but unknown spatial extent has been implanted.
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Vision models for target detection and recognition in memory of Arthur Menendez
Peli, Eli
1995-01-01
This book is an international collection of contributions from academia, industry and the armed forces. It addresses current and emerging Spatial Vision Models and their application to the understanding, prediction and evaluation of the tasks of target detection and recognition. The discussion in many of the chapters is framed in terms of military targets and military vision aids. However, the techniques analyses and problems are by no means limited to this area of application. The detection and recognition of an armored vehicle from a reconnaissance image are performed by the same visual syst
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Targeted Ultrasound for MR-Detected Lesions in Breast Cancer Patients
International Nuclear Information System (INIS)
Shin, Jung Hee; Han, Boo Kyung; Choe, Yeon Hyeon; Ko, Kyung Ran; Choi, Nami
2007-01-01
To investigate the usefulness of targeted ultrasound (US) in the identification of additional suspicious lesions found by magnetic resonance (MR) imaging in breast cancer patients and the changes in treatment based on the identification of the lesions by the use of targeted US. One-hundred forty nine patients who underwent breast MR imaging for a preoperative evaluation of breast cancer between January 2002 and July 2004 were included in the study. We searched all cases for any additional lesions that were found initially by MR imaging and investigated the performance of targeted US in identifying the lesions. We also investigated their pathological outcomes and changes in treatment as a result of lesion identification. Of the 149 patients with breast cancer, additional suspicious lesions were detected with MR imaging in 62 patients (42%). Of the 69 additional lesions found in those 62 patients, 26 (38%) were confirmed as cancers by histology. Thirty-eight lesions in 31 patients were examined with targeted US and were histologically revealed as cancers in 18 (47%), high risk lesions in two (5%), benign lesions in 15 (39%), and unidentified lesions in three (8%). The cancer rate was statistically higher in lesions with a US correlate than in lesions without a US correlate (p = 0.028). Of 31 patients, the surgical plan was altered in 27 (87%). The use of targeted US justified a change in treatment for 22 patients (81%) and misled five patients (19%) into having an unnecessary surgical excision. Targeted US can play a useful role in the evaluation of additional suspicious lesions detected by MR imaging in breast cancer patients, but is limited in lesions without a US correlate
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Zhou, Anran; Xie, Weixin; Pei, Jihong
2018-06-01
Accurate detection of maritime targets in infrared imagery under various sea clutter conditions is always a challenging task. The fractional Fourier transform (FRFT) is the extension of the Fourier transform in the fractional order, and has richer spatial-frequency information. By combining it with the high order statistic filtering, a new ship detection method is proposed. First, the proper range of angle parameter is determined to make it easier for the ship components and background to be separated. Second, a new high order statistic curve (HOSC) at each fractional frequency point is designed. It is proved that maximal peak interval in HOSC reflects the target information, while the points outside the interval reflect the background. And the value of HOSC relative to the ship is much bigger than that to the sea clutter. Then, search the curve's maximal target peak interval and extract the interval by bandpass filtering in fractional Fourier domain. The value outside the peak interval of HOSC decreases rapidly to 0, so the background is effectively suppressed. Finally, the detection result is obtained by the double threshold segmenting and the target region selection method. The results show the proposed method is excellent for maritime targets detection with high clutters.
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Zou, Zhengxia; Shi, Zhenwei
2018-03-01
We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.
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Low velocity target detection based on time-frequency image for high frequency ground wave radar
Institute of Scientific and Technical Information of China (English)
YAN Songhua; WU Shicai; WEN Biyang
2007-01-01
The Doppler spectral broadening resulted from non-stationary movement of target and radio-frequency interference will decrease the veracity of target detection by high frequency ground wave(HEGW)radar.By displaying the change of signal energy on two dimensional time-frequency images based on time-frequency analysis,a new mathematical morphology method to distinguish target from nonlinear time-frequency curves is presented.The analyzed results from the measured data verify that with this new method the target can be detected correctly from wide Doppler spectrum.
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Sun, Lihui; Wang, Yongzhong; He, Yongqiang
2007-01-01
The detection for motive small target in infrared image sequence has become a hot topic nowadays. Background suppress algorithm based on minim gradient median filter and temporal recursion target detection algorithm are introduced. On the basis of contents previously mentioned, a four stages pipeline structure infrared small target detection process system, which aims at characters of algorithm complexity, large amounts of data to process, high frame frequency and exigent real-time character in this kind of application, is designed and implemented. The logical structure of the system was introduced and the function and signals flows are programmed. The system is composed of two FPGA chips and two DSP chips of TI. According to the function of each part, the system is divided into image preprocess stage, target detection stage, track relation stage and image output stage. The experiment of running algorithms on the system presented in this paper proved that the system could meet acquisition and process of 50Hz 240x320 digital image and the system could real time detect small target with a signal-noise ratio more than 3 reliably. The system achieves the characters of large amount of memory, high real-time processing, excellent extension and favorable interactive interface.
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Location Detection and Tracking of Moving Targets by a 2D IR-UWB Radar System
Directory of Open Access Journals (Sweden)
Van-Han Nguyen
2015-03-01
Full Text Available In indoor environments, the Global Positioning System (GPS and long-range tracking radar systems are not optimal, because of signal propagation limitations in the indoor environment. In recent years, the use of ultra-wide band (UWB technology has become a possible solution for object detection, localization and tracking in indoor environments, because of its high range resolution, compact size and low cost. This paper presents improved target detection and tracking techniques for moving objects with impulse-radio UWB (IR-UWB radar in a short-range indoor area. This is achieved through signal-processing steps, such as clutter reduction, target detection, target localization and tracking. In this paper, we introduce a new combination consisting of our proposed signal-processing procedures. In the clutter-reduction step, a filtering method that uses a Kalman filter (KF is proposed. Then, in the target detection step, a modification of the conventional CLEAN algorithm which is used to estimate the impulse response from observation region is applied for the advanced elimination of false alarms. Then, the output is fed into the target localization and tracking step, in which the target location and trajectory are determined and tracked by using unscented KF in two-dimensional coordinates. In each step, the proposed methods are compared to conventional methods to demonstrate the differences in performance. The experiments are carried out using actual IR-UWB radar under different scenarios. The results verify that the proposed methods can improve the probability and efficiency of target detection and tracking.
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Liu, Ruiming; Liu, Erqi; Yang, Jie; Zeng, Yong; Wang, Fanglin; Cao, Yuan
2007-11-01
Fukunaga-Koontz transform (FKT), stemming from principal component analysis (PCA), is used in many pattern recognition and image-processing fields. It cannot capture the higher-order statistical property of natural images, so its detection performance is not satisfying. PCA has been extended into kernel PCA in order to capture the higher-order statistics. However, thus far there have been no researchers who have definitely proposed kernel FKT (KFKT) and researched its detection performance. For accurately detecting potential small targets from infrared images, we first extend FKT into KFKT to capture the higher-order statistical properties of images. Then a framework based on Kalman prediction and KFKT, which can automatically detect and track small targets, is developed. Results of experiments show that KFKT outperforms FKT and the proposed framework is competent to automatically detect and track infrared point targets.
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Directory of Open Access Journals (Sweden)
Yum S
2015-08-01
Full Text Available Soohwan Yum, Seongkeun Jeong, Sunyoung Lee, Joon Nam, Wooseong Kim, Jin-Wook Yoo, Min-Soo Kim, Bok Luel Lee, Yunjin Jung College of Pharmacy, Pusan National University, Busan, Republic of Korea Abstract: Piceatannol (PCT, an anti-colitic natural product, undergoes extensive Phase II hepatic metabolism, resulting in very low bioavailability. We investigated whether colon-targeted delivery of PCT could enhance anti-colitic effects and how therapeutic enhancement occurred at the molecular level. Molecular effects of PCT were examined in human colon carcinoma cells and inflamed colons. The anti-colitic effects of PCT in a colon-targeted capsule (colon-targeted PCT were compared with PCT in a gelatin capsule (conventional PCT in a trinitrobenzene sulfonic acid-induced rat colitis model. Colon-targeted PCT elicited greatly enhanced recovery of the colonic inflammation. In HCT116 cells, PCT inhibited nuclear factor kappaB while activating anti-colitic transcription factors, nuclear factor-erythroid 2 (NF-E2 p45-related factor 2, and hypoxia-inducible factor-1. Colon-targeted PCT, but not conventional PCT, modulated production of the target gene products of the transcription factors in the inflamed colonic tissues. Rectal administration of PCT, which simulates the therapeutic action of colon-targeted PCT, also ameliorated rat colitis and reproduced the molecular effects in the inflamed colonic tissues. Colon-targeted delivery increased therapeutic efficacy of PCT against colitis, likely resulting from multitargeted effects exerted by colon-targeted PCT. The drug delivery technique may be useful for therapeutic optimization of anti-colitic lead compounds including natural products. Keywords: piceatannol, colitis, colon-targeted delivery, multitarget, polypharmacology
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Analysis on Target Detection and Classification in LTE Based Passive Forward Scattering Radar
Raja Syamsul Azmir Raja Abdullah; Noor Hafizah Abdul Aziz; Nur Emileen Abdul Rashid; Asem Ahmad Salah; Fazirulhisyam Hashim
2016-01-01
The passive bistatic radar (PBR) system can utilize the illuminator of opportunity to enhance radar capability. By utilizing the forward scattering technique and procedure into the specific mode of PBR can provide an improvement in target detection and classification. The system is known as passive Forward Scattering Radar (FSR). The passive FSR system can exploit the peculiar advantage of the enhancement in forward scatter radar cross section (FSRCS) for target detection. Thus, the aim of th...
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Liu, Yun; Zhao, Yuejin; Liu, Ming; Dong, Liquan; Hui, Mei; Liu, Xiaohua; Wu, Yijian
2015-09-01
As an important branch of infrared imaging technology, infrared target tracking and detection has a very important scientific value and a wide range of applications in both military and civilian areas. For the infrared image which is characterized by low SNR and serious disturbance of background noise, an innovative and effective target detection algorithm is proposed in this paper, according to the correlation of moving target frame-to-frame and the irrelevance of noise in sequential images based on OpenCV. Firstly, since the temporal differencing and background subtraction are very complementary, we use a combined detection method of frame difference and background subtraction which is based on adaptive background updating. Results indicate that it is simple and can extract the foreground moving target from the video sequence stably. For the background updating mechanism continuously updating each pixel, we can detect the infrared moving target more accurately. It paves the way for eventually realizing real-time infrared target detection and tracking, when transplanting the algorithms on OpenCV to the DSP platform. Afterwards, we use the optimal thresholding arithmetic to segment image. It transforms the gray images to black-white images in order to provide a better condition for the image sequences detection. Finally, according to the relevance of moving objects between different frames and mathematical morphology processing, we can eliminate noise, decrease the area, and smooth region boundaries. Experimental results proves that our algorithm precisely achieve the purpose of rapid detection of small infrared target.
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Signal Detection, Target Tracking and Differential Geometry Applications to Statistical Inference
National Research Council Canada - National Science Library
Rao, C
1997-01-01
Signal detection and target tracking. A novel method known as polynomial rooting approach is proposed to obtain estimates of frequencies, amplitudes and noise variance of two-dimensional exponential signals...
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Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao
2018-01-01
Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.
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Directory of Open Access Journals (Sweden)
S. Sharifi hashjin
2016-06-01
Full Text Available In recent years, developing target detection algorithms has received growing interest in hyperspectral images. In comparison to the classification field, few studies have been done on dimension reduction or band selection for target detection in hyperspectral images. This study presents a simple method to remove bad bands from the images in a supervised manner for sub-pixel target detection. The proposed method is based on comparing field and laboratory spectra of the target of interest for detecting bad bands. For evaluation, the target detection blind test dataset is used in this study. Experimental results show that the proposed method can improve efficiency of the two well-known target detection methods, ACE and CEM.
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Switchable DNA interfaces for the highly sensitive detection of label-free DNA targets.
Rant, Ulrich; Arinaga, Kenji; Scherer, Simon; Pringsheim, Erika; Fujita, Shozo; Yokoyama, Naoki; Tornow, Marc; Abstreiter, Gerhard
2007-10-30
We report a method to detect label-free oligonucleotide targets. The conformation of surface-tethered probe nucleic acids is modulated by alternating electric fields, which cause the molecules to extend away from or fold onto the biased surface. Binding (hybridization) of targets to the single-stranded probes results in a pronounced enhancement of the layer-height modulation amplitude, monitored optically in real time. The method features an exceptional detection limit of <3 x 10(8) bound targets per cm(2) sensor area. Single base-pair mismatches in the sequences of DNA complements may readily be identified; moreover, binding kinetics and binding affinities can be determined with high accuracy. When driving the DNA to oscillate at frequencies in the kHz regime, distinct switching kinetics are revealed for single- and double-stranded DNA. Molecular dynamics are used to identify the binding state of molecules according to their characteristic kinetic fingerprints by using a chip-compatible detection format.
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Target Detection, Identification, and Marksmanship Under Various Types of Physiological Strain
National Research Council Canada - National Science Library
Tikuisis, Peter
2006-01-01
.... Using a small arms trainer (SAT), target detection, identification, and engagement were tested under a variety of conditions including heat and cold exposure, fatiguing exercise, and sleep deprivation, with caffeine intervention...
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Xu, Huo; Jiang, Yifan; Liu, Dengyou; Liu, Kai; Zhang, Yafeng; Yu, Suhong; Shen, Zhifa; Wu, Zai-Sheng
2018-06-29
The sensitive detection of cancer-related genes is of great significance for early diagnosis and treatment of human cancers, and previous isothermal amplification sensing systems were often based on the reuse of target DNA, the amplification of enzymatic products and the accumulation of reporting probes. However, no reporting probes are able to be transformed into target species and in turn initiate the signal of other probes. Herein we reported a simple, isothermal and highly sensitive homogeneous assay system for tumor suppressor p53 gene detection based on a new autonomous DNA machine, where the signaling probe, molecular beacon (MB), was able to execute the function similar to target DNA besides providing the common signal. In the presence of target p53 gene, the operation of DNA machine can be initiated, and cyclical nucleic acid strand-displacement polymerization (CNDP) and nicking/polymerization cyclical amplification (NPCA) occur, during which the MB was opened by target species and cleaved by restriction endonuclease. In turn, the cleaved fragments could activate the next signaling process as target DNA did. According to the functional similarity, the cleaved fragment was called twin target, and the corresponding fashion to amplify the signal was named twin target self-amplification. Utilizing this newly-proposed DNA machine, the target DNA could be detected down to 0.1 pM with a wide dynamic range (6 orders of magnitude) and single-base mismatched targets were discriminated, indicating a very high assay sensitivity and good specificity. In addition, the DNA machine was not only used to screen the p53 gene in complex biological matrix but also was capable of practically detecting genomic DNA p53 extracted from A549 cell line. This indicates that the proposed DNA machine holds the potential application in biomedical research and early clinical diagnosis. Copyright © 2018 Elsevier B.V. All rights reserved.
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Effect of Various Environmental Stressors on Target Detection, Identification, and Marksmanship
National Research Council Canada - National Science Library
Tikuisis, Peter; Keefe, Allan A
2007-01-01
.... Using a small arms trainer (SAT), the detection, identification, and engagement of targets were tested under a variety of environmentally stressful conditions including heat and cold exposure, noise, fatiguing exercise, and sleep...
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Detection of ferromagnetic target based on mobile magnetic gradient tensor system
Energy Technology Data Exchange (ETDEWEB)
Gang, Y.I.N., E-mail: gang.gang88@163.com; Yingtang, Zhang; Zhining, Li; Hongbo, Fan; Guoquan, Ren
2016-03-15
Attitude change of mobile magnetic gradient tensor system critically affects the precision of gradient measurements, thereby increasing ambiguity in target detection. This paper presents a rotational invariant-based method for locating and identifying ferromagnetic targets. Firstly, unit magnetic moment vector was derived based on the geometrical invariant, such that the intermediate eigenvector of the magnetic gradient tensor is perpendicular to the magnetic moment vector and the source–sensor displacement vector. Secondly, unit source–sensor displacement vector was derived based on the characteristic that the angle between magnetic moment vector and source–sensor displacement is a rotational invariant. By introducing a displacement vector between two measurement points, the magnetic moment vector and the source–sensor displacement vector were theoretically derived. To resolve the problem of measurement noises existing in the realistic detection applications, linear equations were formulated using invariants corresponding to several distinct measurement points and least square solution of magnetic moment vector and source–sensor displacement vector were obtained. Results of simulation and principal verification experiment showed the correctness of the analytical method, along with the practicability of the least square method. - Highlights: • Ferromagnetic target detection method is proposed based on rotational invariants • Intermediate eigenvector is perpendicular to magnetic moment and displacement vector • Angle between magnetic moment and displacement vector is a rotational invariant • Magnetic moment and displacement vector are derived based on invariants of two points.
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Infrared images target detection based on background modeling in the discrete cosine domain
Ye, Han; Pei, Jihong
2018-02-01
Background modeling is the critical technology to detect the moving target for video surveillance. Most background modeling techniques are aimed at land monitoring and operated in the spatial domain. A background establishment becomes difficult when the scene is a complex fluctuating sea surface. In this paper, the background stability and separability between target are analyzed deeply in the discrete cosine transform (DCT) domain, on this basis, we propose a background modeling method. The proposed method models each frequency point as a single Gaussian model to represent background, and the target is extracted by suppressing the background coefficients. Experimental results show that our approach can establish an accurate background model for seawater, and the detection results outperform other background modeling methods in the spatial domain.
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A new frozen-spin target for 4π particle detection
International Nuclear Information System (INIS)
Bradtke, Ch.; Dutz, H.; Peschel, H.; Goertz, S.; Harmsen, J.; Hasegawa, S.; Horikawa, N.; Iwata, T.; Kageya, T.; Matsuda, T.; Meier, A.; Meyer, W.; Radtke, E.; Reicherz, G.; Rohlof, Ch.; Thomas, A.; Wakai, A.
1999-01-01
A new frozen-spin target has been developed, that allows the detection of emitted particles in an angular acceptance of almost 4π in the laboratory frame. The central part of this new target represents a 3 He/ 4 He dilution refrigerator that is installed horizontally along the beam axis. The refrigerator includes an internal superconducting holding coil to maintain the nucleon polarization in the frozen-spin mode longitudinally to the beam. The design of the dilution refrigerator and the use of an internal holding coil enabled for the first time the measurement of a spin-dependent total cross section in combination with a polarized solid state target. This new frozen-spin target was used successfully to measure the helicity asymmetry of the total photoabsorption cross-section at the Mainz accelerator facility MAMI. This experiment has been performed in order to verify for the first time the GDH sum rule
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Robust Detection of Moving Human Target in Foliage-Penetration Environment Based on Hough Transform
Directory of Open Access Journals (Sweden)
P. Lei
2014-04-01
Full Text Available Attention has been focused on the robust moving human target detection in foliage-penetration environment, which presents a formidable task in a radar system because foliage is a rich scattering environment with complex multipath propagation and time-varying clutter. Generally, multiple-bounce returns and clutter are additionally superposed to direct-scatter echoes. They obscure true target echo and lead to poor visual quality time-range image, making target detection particular difficult. Consequently, an innovative approach is proposed to suppress clutter and mitigate multipath effects. In particular, a clutter suppression technique based on range alignment is firstly applied to suppress the time-varying clutter and the instable antenna coupling. Then entropy weighted coherent integration (EWCI algorithm is adopted to mitigate the multipath effects. In consequence, the proposed method effectively reduces the clutter and ghosting artifacts considerably. Based on the high visual quality image, the target trajectory is detected robustly and the radial velocity is estimated accurately with the Hough transform (HT. Real data used in the experimental results are provided to verify the proposed method.
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de Castro, Sonia; Camarasa, María-José
2018-04-25
HIV infection still has a serious health and socio-economical impact and is one of the primary causes of morbidity and mortality all over the world. HIV infection and the AIDS pandemic are still matters of great concern, especially in less developed countries where the access to highly active antiretroviral therapy (HAART) is limited. Patient compliance is another serious drawback. Nowadays, HAART is the treatment of choice although it is not the panacea. Despite the fact that it suppresses viral replication at undetectable viral loads and prevents progression of HIV infection into AIDS HAART has several pitfalls, namely, long-term side-effects, drug resistance development, emergence of drug-resistant viruses, low compliance and the intolerance of some patients to these drugs. Moreover, another serious health concern is the event of co-infection with more than one pathogen at the same time (e.g. HIV and HCV, HBV, herpes viruses, etc). Currently, the multi-target drug approach has become an exciting strategy to address complex diseases and overcome drug resistance development. Such multifunctional molecules combine in their structure pharmacophores that may simultaneously interfere with multiple targets and their use may eventually be more safe and efficacious than that involving a mixture of separate molecules because of avoidance or delay of drug resistance, lower incidence of unwanted drug-drug interactions and improved compliance. In this review we focus on multifunctional molecules with dual activity against different targets of the HIV life cycle or able to block replication, not only of HIV but also of other viruses that are often co-pathogens of HIV. The different approaches are documented by selected examples. Copyright © 2018 The Authors. Published by Elsevier Masson SAS.. All rights reserved.
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Park, Yeonkyung; Lee, Chang Yeol; Kang, Shinyoung; Kim, Hansol; Park, Ki Soo; Park, Hyun Gyu
2018-02-01
In this work, we developed a novel, label-free, and enzyme-free strategy for the colorimetric detection of microRNA (miRNA), which relies on a target-catalyzed toehold-mediated strand displacement (TMSD) reaction. The system employs a detection probe that specifically binds to the target miRNA and sequentially releases a catalyst strand (CS) intended to trigger the subsequent TMSD reaction. Thus, the presence of target miRNA releases the CS that mediates the formation of an active G-quadruplex DNAzyme which is initially caged and inactivated by a blocker strand. In addition, a fuel strand that is supplemented for the recycling of the CS promotes another TMSD reaction, consequently generating a large number of active G-quadruplex DNAzymes. As a result, a distinct colorimetric signal is produced by the ABTS oxidation promoted by the peroxidase mimicking activity of the released G-quadruplex DNAzymes. Based on this novel strategy, we successfully detected miR-141, a promising biomarker for human prostate cancer, with high selectivity. The diagnostic capability of this system was also demonstrated by reliably determining target miR-141 in human serum, showing its great potential towards real clinical applications. Importantly, the proposed approach is composed of separate target recognition and signal transduction modules. Thus, it could be extended to analyze different target miRNAs by simply redesigning the detection probe while keeping the same signal transduction module as a universal signal amplification unit, which was successfully demonstrated by analyzing another target miRNA, let-7d.
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International Nuclear Information System (INIS)
Yue, Ning J.; Kim, Sung; Jabbour, Salma; Narra, Venkat; Haffty, Bruce G.
2007-01-01
Image guided radiotherapy technologies are being increasingly utilized in the treatment of various cancers. These technologies have enhanced the ability to detect temporal and spatial deviations of the target volume relative to planned radiation beams. Correcting these detected deviations may, in principle, improve the accuracy of dose delivery to the target. However, in many situations, a clinical decision has to be made as to whether it is necessary to correct some of the deviations since the relevant dosimetric impact may or may not be significant, and the corresponding corrective action may be either impractical or time consuming. Ideally this decision should be based on objective and reproducible criteria rather than subjective judgment. In this study, a strategy is proposed for the objective evaluation of the necessity of deviation correction during the treatment verification process. At the treatment stage, without any alteration from the planned beams, the treatment beams should provide the desired dose coverage to the geometric volume identical to the planning target volume (PTV). Given this fact, the planned dose distribution and PTV geometry were used to compute the dose coverage and PTV enclosure of the clinical target volume (CTV) that was detected from imaging during the treatment setup verification. The spatial differences between the detected CTV and the planning CTV are essentially the target deviations. The extent of the PTV enclosure of the detected CTV as well as its dose coverage were used as criteria to evaluate the necessity of correcting any of the target deviations. This strategy, in principle, should be applicable to any type of target deviations, including both target deformable and positional changes and should be independent of how the deviations are detected. The proposed strategy was used on two clinical prostate cancer cases. In both cases, gold markers were implanted inside the prostate for the purpose of treatment setup
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Implementation Of Vision-Based Landing Target Detection For VTOL UAV Using Raspberry Pi
Directory of Open Access Journals (Sweden)
Ei Ei Nyein
2017-04-01
Full Text Available This paper presents development and implementation of a real-time vision-based landing system for VTOL UAV. We use vision for precise target detection and recognition. A UAV is equipped with the onboard raspberry pi camera to take images and raspberry pi platform to operate the image processing techniques. Today image processing is used for various applications in this paper it is used for landing target extraction. And vision system is also used for take-off and landing function in VTOL UAV. Our landing target design is used as the helipad H shape. Firstly the image is captured to detect the target by the onboard camera. Next the capture image is operated in the onboard processor. Finally the alert sound signal is sent to the remote control RC for landing VTOL UAV. The information obtained from vision system is used to navigate a safe landing. The experimental results from real tests are presented.
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Botanical drugs, synergy, and network pharmacology: forth and back to intelligent mixtures.
Gertsch, Jürg
2011-07-01
For centuries the science of pharmacognosy has dominated rational drug development until it was gradually substituted by target-based drug discovery in the last fifty years. Pharmacognosy stems from the different systems of traditional herbal medicine and its "reverse pharmacology" approach has led to the discovery of numerous pharmacologically active molecules and drug leads for humankind. But do botanical drugs also provide effective mixtures? Nature has evolved distinct strategies to modulate biological processes, either by selectively targeting biological macromolecules or by creating molecular promiscuity or polypharmacology (one molecule binds to different targets). Widely claimed to be superior over monosubstances, mixtures of bioactive compounds in botanical drugs allegedly exert synergistic therapeutic effects. Despite evolutionary clues to molecular synergism in nature, sound experimental data are still widely lacking to support this assumption. In this short review, the emerging concept of network pharmacology is highlighted, and the importance of studying ligand-target networks for botanical drugs is emphasized. Furthermore, problems associated with studying mixtures of molecules with distinctly different pharmacodynamic properties are addressed. It is concluded that a better understanding of the polypharmacology and potential network pharmacology of botanical drugs is fundamental in the ongoing rationalization of phytotherapy. © Georg Thieme Verlag KG Stuttgart · New York.
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A new frozen-spin target for 4 pi particle detection
Bradtke, C; Peschel, H; Görtz, S; Harmsen, J; Hasegawa, S; Horikawa, N; Iwata, T; Kageya, T; Matsuda, T; Meier, A; Meyer, Werner T; Radtke, E; Reicherz, G; Rohlof, C; Thomas, A; Wakai, A
1999-01-01
A new frozen-spin target has been developed, that allows the detection of emitted particles in an angular acceptance of almost 4 pi in the laboratory frame. The central part of this new target represents a sup 3 He/ sup 4 He dilution refrigerator that is installed horizontally along the beam axis. The refrigerator includes an internal superconducting holding coil to maintain the nucleon polarization in the frozen-spin mode longitudinally to the beam. The design of the dilution refrigerator and the use of an internal holding coil enabled for the first time the measurement of a spin-dependent total cross section in combination with a polarized solid state target. This new frozen-spin target was used successfully to measure the helicity asymmetry of the total photoabsorption cross-section at the Mainz accelerator facility MAMI. This experiment has been performed in order to verify for the first time the GDH sum rule.
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Ship detection for high resolution optical imagery with adaptive target filter
Ju, Hongbin
2015-10-01
Ship detection is important due to both its civil and military use. In this paper, we propose a novel ship detection method, Adaptive Target Filter (ATF), for high resolution optical imagery. The proposed framework can be grouped into two stages, where in the first stage, a test image is densely divided into different detection windows and each window is transformed to a feature vector in its feature space. The Histograms of Oriented Gradients (HOG) is accumulated as a basic feature descriptor. In the second stage, the proposed ATF highlights all the ship regions and suppresses the undesired backgrounds adaptively. Each detection window is assigned a score, which represents the degree of the window belonging to a certain ship category. The ATF can be adaptively obtained by the weighted Logistic Regression (WLR) according to the distribution of backgrounds and targets of the input image. The main innovation of our method is that we only need to collect positive training samples to build the filter, while the negative training samples are adaptively generated by the input image. This is different to other classification method such as Support Vector Machine (SVM) and Logistic Regression (LR), which need to collect both positive and negative training samples. The experimental result on 1-m high resolution optical images shows the proposed method achieves a desired ship detection performance with higher quality and robustness than other methods, e.g., SVM and LR.
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Elbakary, M. I.; Alam, M. S.; Aslan, M. S.
2008-03-01
In a FLIR image sequence, a target may disappear permanently or may reappear after some frames and crucial information such as direction, position and size related to the target are lost. If the target reappears at a later frame, it may not be tracked again because the 3D orientation, size and location of the target might be changed. To obtain information about the target before disappearing and to detect the target after reappearing, distance classifier correlation filter (DCCF) is trained manualy by selecting a number of chips randomly. This paper introduces a novel idea to eliminates the manual intervention in training phase of DCCF. Instead of selecting the training chips manually and selecting the number of the training chips randomly, we adopted the K-means algorithm to cluster the training frames and based on the number of clusters we select the training chips such that a training chip for each cluster. To detect and track the target after reappearing in the field-ofview ,TBF and DCCF are employed. The contduced experiemnts using real FLIR sequences show results similar to the traditional agorithm but eleminating the manual intervention is the advantage of the proposed algorithm.
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In situ targeted MRI detection of Helicobacter pylori with stable magnetic graphitic nanocapsules
Li, Yunjie; Hu, Xiaoxiao; Ding, Ding; Zou, Yuxiu; Xu, Yiting; Wang, Xuewei; Zhang, Yin; Chen, Long; Chen, Zhuo; Tan, Weihong
2017-06-01
Helicobacter pylori infection is implicated in the aetiology of many diseases. Despite numerous studies, a painless, fast and direct method for the in situ detection of H. pylori remains a challenge, mainly due to the strong acidic/enzymatic environment of the gastric mucosa. Herein, we report the use of stable magnetic graphitic nanocapsules (MGNs), for in situ targeted magnetic resonance imaging (MRI) detection of H. pylori. Several layers of graphene as the shell effectively protect the magnetic core from corrosion while retaining the superior contrast effect for MRI in the gastric environment. Boronic-polyethylene glycol molecules were synthesized and modified on the MGN surface for targeted MRI detection. In a mouse model of H. pylori-induced infection, H. pylori was specifically detected through both T2-weighted MR imaging and Raman gastric mucosa imaging using functionalized MGNs. These results indicated that enhancement of MRI using MGNs may be a promising diagnostic and bioimaging platform for very harsh conditions.
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Detection of target phonemes in spontaneous and read speech
Mehta, G.; Cutler, A.
1988-01-01
Although spontaneous speech occurs more frequently in most listeners’ experience than read speech, laboratory studies of human speech recognition typically use carefully controlled materials read from a script. The phonological and prosodic characteristics of spontaneous and read speech differ considerably, however, which suggests that laboratory results may not generalize to the recognition of spontaneous and read speech materials, and their response time to detect word-initial target phonem...
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Wang, Xuezhi; Huang, Xiaotao; Suvorova, Sofia; Moran, Bill
2018-01-01
Golay complementary waveforms can, in theory, yield radar returns of high range resolution with essentially zero sidelobes. In practice, when deployed conventionally, while high signal-to-noise ratios can be achieved for static target detection, significant range sidelobes are generated by target returns of nonzero Doppler causing unreliable detection. We consider signal processing techniques using Golay complementary waveforms to improve radar detection performance in scenarios involving multiple nonzero Doppler targets. A signal processing procedure based on an existing, so called, Binomial Design algorithm that alters the transmission order of Golay complementary waveforms and weights the returns is proposed in an attempt to achieve an enhanced illumination performance. The procedure applies one of three proposed waveform transmission ordering algorithms, followed by a pointwise nonlinear processor combining the outputs of the Binomial Design algorithm and one of the ordering algorithms. The computational complexity of the Binomial Design algorithm and the three ordering algorithms are compared, and a statistical analysis of the performance of the pointwise nonlinear processing is given. Estimation of the areas in the Delay–Doppler map occupied by significant range sidelobes for given targets are also discussed. Numerical simulations for the comparison of the performances of the Binomial Design algorithm and the three ordering algorithms are presented for both fixed and randomized target locations. The simulation results demonstrate that the proposed signal processing procedure has a better detection performance in terms of lower sidelobes and higher Doppler resolution in the presence of multiple nonzero Doppler targets compared to existing methods. PMID:29324708
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Added value of second biopsy target in screen-detected widespread suspicious breast calcifications.
Falkner, Nathalie M; Hince, Dana; Porter, Gareth; Dessauvagie, Ben; Jeganathan, Sanjay; Bulsara, Max; Lo, Glen
2018-06-01
There is controversy on the optimal work-up of screen-detected widespread breast calcifications: whether to biopsy a single target or multiple targets. This study evaluates agreement between multiple biopsy targets within the same screen-detected widespread (≥25 mm) breast calcification to determine if the second biopsy adds value. Retrospective observational study of women screened in a statewide general population risk breast cancer mammographic screening program from 2009 to 2016. Screening episodes recalled for widespread calcifications where further views indicated biopsy, and two or more separate target areas were sampled within the same lesion were included. Percentage agreement and Cohen's Kappa were calculated. A total of 293317 women were screened during 761124 separate episodes with recalls for widespread calcifications in 2355 episodes. In 171 women, a second target was biopsied within the same lesion. In 149 (86%) cases, the second target biopsy result agreed with the first biopsy (κ = 0.6768). Agreement increased with increasing mammography score (85%, 86% and 92% for score 3, 4 and 5 lesions). Same day multiple biopsied lesions were three times more likely to yield concordant results compared to post-hoc second target biopsy cases. While a single target biopsy is sufficient to discriminate a benign vs. malignant diagnosis in most cases, in 14% there is added value in performing a second target biopsy. Biopsies performed prospectively are more likely to yield concordant results compared to post-hoc second target biopsy cases, suggesting a single prospective biopsy may be sufficient when results are radiological-pathological concordant; discordance still requires repeat sampling. © 2018 The Royal Australian and New Zealand College of Radiologists.
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Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks
Directory of Open Access Journals (Sweden)
Tengyue Zou
2017-05-01
Full Text Available Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k-means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.
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Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks.
Zou, Tengyue; Li, Zhenjia; Li, Shuyuan; Lin, Shouying
2017-05-04
Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k -means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones.
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Hassan, Syed S.; Jamal, Syed B.; Radusky, Leandro G.; Tiwari, Sandeep; Ullah, Asad; Ali, Javed; Behramand; de Carvalho, Paulo V. S. D.; Shams, Rida; Khan, Sabir; Figueiredo, Henrique C. P.; Barh, Debmalya; Ghosh, Preetam; Silva, Artur; Baumbach, Jan; Röttger, Richard; Turjanski, Adrián G.; Azevedo, Vasco A. C.
2018-01-01
Diphtheria is an acute and highly infectious disease, previously regarded as endemic in nature but vaccine-preventable, is caused by Corynebacterium diphtheriae (Cd). In this work, we used an in silico approach along the 13 complete genome sequences of C. diphtheriae followed by a computational assessment of structural information of the binding sites to characterize the “pocketome druggability.” To this end, we first computed the “modelome” (3D structures of a complete genome) of a randomly selected reference strain Cd NCTC13129; that had 13,763 open reading frames (ORFs) and resulted in 1,253 (∼9%) structure models. The amino acid sequences of these modeled structures were compared with the remaining 12 genomes and consequently, 438 conserved protein sequences were obtained. The RCSB-PDB database was consulted to check the template structures for these conserved proteins and as a result, 401 adequate 3D models were obtained. We subsequently predicted the protein pockets for the obtained set of models and kept only the conserved pockets that had highly druggable (HD) values (137 across all strains). Later, an off-target host homology analyses was performed considering the human proteome using NCBI database. Furthermore, the gene essentiality analysis was carried out that gave a final set of 10-conserved targets possessing highly druggable protein pockets. To check the target identification robustness of the pipeline used in this work, we crosschecked the final target list with another in-house target identification approach for C. diphtheriae thereby obtaining three common targets, these were; hisE-phosphoribosyl-ATP pyrophosphatase, glpX-fructose 1,6-bisphosphatase II, and rpsH-30S ribosomal protein S8. Our predicted results suggest that the in silico approach used could potentially aid in experimental polypharmacological target determination in C. diphtheriae and other pathogens, thereby, might complement the existing and new drug-discovery pipelines
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Analysis of the Chirplet Transform-Based Algorithm for Radar Detection of Accelerated Targets
Galushko, V. G.; Vavriv, D. M.
2017-06-01
Purpose: Efficiency analysis of an optimal algorithm of chirp signal processing based on the chirplet transform as applied to detection of radar targets in uniformly accelerated motion. Design/methodology/approach: Standard methods of the optimal filtration theory are used to investigate the ambiguity function of chirp signals. Findings: An analytical expression has been derived for the ambiguity function of chirp signals that is analyzed with respect to detection of radar targets moving at a constant acceleration. Sidelobe level and characteristic width of the ambiguity function with respect to the coordinates frequency and rate of its change have been estimated. The gain in the signal-to-noise ratio has been assessed that is provided by the algorithm under consideration as compared with application of the standard Fourier transform to detection of chirp signals against a “white” noise background. It is shown that already with a comparatively small (processing channels (elementary filters with respect to the frequency change rate) the gain in the signal-tonoise ratio exceeds 10 dB. A block diagram of implementation of the algorithm under consideration is suggested on the basis of a multichannel weighted Fourier transform. Recommendations as for selection of the detection algorithm parameters have been developed. Conclusions: The obtained results testify to efficiency of application of the algorithm under consideration to detection of radar targets moving at a constant acceleration. Nevertheless, it seems expedient to perform computer simulations of its operability with account for the noise impact along with trial measurements in real conditions.
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Fluorescence turn-on detection of target sequence DNA based on silicon nanodot-mediated quenching.
Zhang, Yanan; Ning, Xinping; Mao, Guobin; Ji, Xinghu; He, Zhike
2018-05-01
We have developed a new enzyme-free method for target sequence DNA detection based on the dynamic quenching of fluorescent silicon nanodots (SiNDs) toward Cy5-tagged DNA probe. Fascinatingly, the water-soluble SiNDs can quench the fluorescence of cyanine (Cy5) in Cy5-tagged DNA probe in homogeneous solution, and the fluorescence of Cy5-tagged DNA probe can be restored in the presence of target sequence DNA (the synthetic target miRNA-27a). Based on this phenomenon, a SiND-featured fluorescent sensor has been constructed for "turn-on" detection of the synthetic target miRNA-27a for the first time. This newly developed approach possesses the merits of low cost, simple design, and convenient operation since no enzymatic reaction, toxic reagents, or separation procedures are involved. The established method achieves a detection limit of 0.16 nM, and the relative standard deviation of this method is 9% (1 nM, n = 5). The linear range is 0.5-20 nM, and the recoveries in spiked human fluids are in the range of 90-122%. This protocol provides a new tactic in the development of the nonenzymic miRNA biosensors and opens a promising avenue for early diagnosis of miRNA-associated disease. Graphical abstract The SiND-based fluorescent sensor for detection of S-miR-27a.
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Risk maps for targeting exotic plant pest detection programs in the United States
R.D. Magarey; D.M. Borchert; J.S. Engle; M Garcia-Colunga; Frank H. Koch; et al
2011-01-01
In the United States, pest risk maps are used by the Cooperative Agricultural Pest Survey for spatial and temporal targeting of exotic plant pest detection programs. Methods are described to create standardized host distribution, climate and pathway risk maps for the top nationally ranked exotic pest targets. Two examples are provided to illustrate the risk mapping...
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Wu, Binlin
New near-infrared (NIR) diffuse optical tomography (DOT) approaches were developed to detect, locate, and image small targets embedded in highly scattering turbid media. The first approach, referred to as time reversal optical tomography (TROT), is based on time reversal (TR) imaging and multiple signal classification (MUSIC). The second approach uses decomposition methods of non-negative matrix factorization (NMF) and principal component analysis (PCA) commonly used in blind source separation (BSS) problems, and compare the outcomes with that of optical imaging using independent component analysis (OPTICA). The goal is to develop a safe, affordable, noninvasive imaging modality for detection and characterization of breast tumors in early growth stages when those are more amenable to treatment. The efficacy of the approaches was tested using simulated data, and experiments involving model media and absorptive, scattering, and fluorescent targets, as well as, "realistic human breast model" composed of ex vivo breast tissues with embedded tumors. The experimental arrangements realized continuous wave (CW) multi-source probing of samples and multi-detector acquisition of diffusely transmitted signal in rectangular slab geometry. A data matrix was generated using the perturbation in the transmitted light intensity distribution due to the presence of absorptive or scattering targets. For fluorescent targets the data matrix was generated using the diffusely transmitted fluorescence signal distribution from the targets. The data matrix was analyzed using different approaches to detect and characterize the targets. The salient features of the approaches include ability to: (a) detect small targets; (b) provide three-dimensional location of the targets with high accuracy (~within a millimeter or 2); and (c) assess optical strength of the targets. The approaches are less computation intensive and consequently are faster than other inverse image reconstruction methods that
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Limitations and Strengths of the Fourier Transform Method to Detect Accelerating Targets
National Research Council Canada - National Science Library
Thayaparan, Thayananthan
2000-01-01
.... In using a Pulse Doppler Radar to detect a non-accelerating target in additive white Gaussian noise and to estimate its radial velocity, the Fourier method provides an output signal-to-noise ratio (SNR...
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Directory of Open Access Journals (Sweden)
Julie Lao
2017-03-01
Full Text Available The pathogenicity of the different flu species is a real public health problem worldwide. To combat this scourge, we established a method to detect drug targets, reducing the possibility of escape. Besides being able to attach a drug candidate, these targets should have the main characteristic of being part of an essential viral function. The invariance groups that are sets of residues bearing an essential function can be detected genetically. They consist of invariant and synthetic lethal residues (interdependent residues not varying or slightly varying when together. We analyzed an alignment of more than 10,000 hemagglutinin sequences of influenza to detect six invariance groups, close in space, and on the protein surface. In parallel we identified five potential pockets on the surface of hemagglutinin. By combining these results, three potential binding sites were determined that are composed of invariance groups located respectively in the vestigial esterase domain, in the bottom of the stem and in the fusion area. The latter target is constituted of residues involved in the spring-loaded mechanism, an essential step in the fusion process. We propose a model describing how this potential target could block the reorganization of the hemagglutinin HA2 secondary structure and prevent viral entry into the host cell.
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Huber, Samuel; Dunau, Patrick; Wellig, Peter; Stein, Karin
2017-10-01
Background: In target detection, the success rates depend strongly on human observer performances. Two prior studies tested the contributions of target detection algorithms and prior training sessions. The aim of this Swiss-German cooperation study was to evaluate the dependency of human observer performance on the quality of supporting image analysis algorithms. Methods: The participants were presented 15 different video sequences. Their task was to detect all targets in the shortest possible time. Each video sequence showed a heavily cluttered simulated public area from a different viewing angle. In each video sequence, the number of avatars in the area was altered to 100, 150 and 200 subjects. The number of targets appearing was kept at 10%. The number of marked targets varied from 0, 5, 10, 20 up to 40 marked subjects while keeping the positive predictive value of the detection algorithm at 20%. During the task, workload level was assessed by applying an acoustic secondary task. Detection rates and detection times for the targets were analyzed using inferential statistics. Results: The study found Target Detection Time to increase and Target Detection Rates to decrease with increasing numbers of avatars. The same is true for the Secondary Task Reaction Time while there was no effect on Secondary Task Hit Rate. Furthermore, we found a trend for a u-shaped correlation between the numbers of markings and RTST indicating increased workload. Conclusion: The trial results may indicate useful criteria for the design of training and support of observers in observational tasks.
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Multiple Targeting Approaches on Histamine H3 Receptor Antagonists
Directory of Open Access Journals (Sweden)
Mohammad eKhanfar
2016-05-01
Full Text Available With the very recent market approval of pitolisant (Wakix®, the interest in clinical applications of novel multifunctional histamine H3 receptor antagonists has clearly increased. Since histamine H3 receptor antagonists in clinical development have been tested for a variety of different indications, the combination of pharmacological properties in one molecule for improved pharmacological effects and reduced unwanted side-effects is rationally based on the increasing knowledge on the complex neurotransmitter regulations. The polypharmacological approaches on histamine H3 receptor antagonists on different G-protein coupled receptors, transporters, enzymes as well as on NO-signaling mechanism are described, supported with some lead structures.
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Detection of small targets in a marine environment using laser radar
Kunz, G.J.; Bekman, H.H.P.T.; Benoist, K.W.; Cohen, L.H.; Heuvel, J.C. van den; Putten, F.J.M.
2005-01-01
Small maritime targets, e.g., periscope tubes, jet skies, swimmers and small boats, are potential threats for naval ships under many conditions, but are difficult to detect with current radar systems due to their limited radar cross section and the presence of sea clutter. On the other hand,
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A Review on Hot-IP Finding Methods and Its Application in Early DDoS Target Detection
Directory of Open Access Journals (Sweden)
Xuan Dau Hoang
2016-10-01
Full Text Available On the high-speed connections of the Internet or computer networks, the IP (Internet Protocol packet traffic passing through the network is extremely high, and that makes it difficult for network monitoring and attack detection applications. This paper reviews methods to find the high-occurrence-frequency elements in the data stream and applies the most efficient methods to find Hot-IPs that are high-frequency IP addresses of IP packets passing through the network. Fast finding of Hot-IPs in the IP packet stream can be effectively used in early detection of DDoS (Distributed Denial of Service attack targets and spreading sources of network worms. Research results show that the Count-Min method gives the best overall performance for Hot-IP detection thanks to its low computational complexity, low space requirement and fast processing speed. We also propose an early detection model of DDoS attack targets based on Hot-IP finding, which can be deployed on the target network routers.
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Fast and sensitive detection of indels induced by precise gene targeting
DEFF Research Database (Denmark)
Yang, Zhang; Steentoft, Catharina; Hauge, Camilla
2015-01-01
The nuclease-based gene editing tools are rapidly transforming capabilities for altering the genome of cells and organisms with great precision and in high throughput studies. A major limitation in application of precise gene editing lies in lack of sensitive and fast methods to detect...... and characterize the induced DNA changes. Precise gene editing induces double-stranded DNA breaks that are repaired by error-prone non-homologous end joining leading to introduction of insertions and deletions (indels) at the target site. These indels are often small and difficult and laborious to detect...
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Directory of Open Access Journals (Sweden)
Amy M. Jimenez
2016-03-01
Full Text Available Early visual perception and attention are impaired in schizophrenia, and these deficits can be observed on target detection tasks. These tasks activate distinct ventral and dorsal brain networks which support stimulus-driven and goal-directed attention, respectively. We used single and dual target rapid serial visual presentation (RSVP tasks during fMRI with an ROI approach to examine regions within these networks associated with target detection and the attentional blink (AB in 21 schizophrenia outpatients and 25 healthy controls. In both tasks, letters were targets and numbers were distractors. For the dual target task, the second target (T2 was presented at 3 different lags after the first target (T1 (lag1=100ms, lag3=300ms, lag7=700ms. For both single and dual target tasks, patients identified fewer targets than controls. For the dual target task, both groups showed the expected AB effect with poorer performance at lag 3 than at lags 1 or 7, and there was no group by lag interaction. During the single target task, patients showed abnormally increased deactivation of the temporo-parietal junction (TPJ, a key region of the ventral network. When attention demands were increased during the dual target task, patients showed overactivation of the posterior intraparietal cortex, a key dorsal network region, along with failure to deactivate TPJ. Results suggest inefficient and faulty suppression of salience-oriented processing regions, resulting in increased sensitivity to stimuli in general, and difficulty distinguishing targets from non-targets.
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Results from the search-lidar demonstrator project for detection of small Sea-Surface targets
Heuvel, J.C. van den; Putten, F.J.M. van; Cohen, L.H.; Kemp, R.A.W.; Franssen, G.C.
2009-01-01
Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC's, and speedboats. Previous lidar
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Detection and localization of multiple short range targets using FMCW radar signal
Jardak, Seifallah; Kiuru, Tero; Metso, Mikko; Pursula, Pekka; Hakli, Janne; Hirvonen, Mervi; Ahmed, Sajid; Alouini, Mohamed-Slim
2016-01-01
In this paper, a 24 GHz frequency-modulated continuous wave radar is used to detect and localize both stationary and moving targets. Depending on the application, the implemented software offers different modes of operation. For example, it can
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NMR parallel Q-meter with double-balanced-mixer detection for polarized target experiments
International Nuclear Information System (INIS)
Boissevain, J.; Tippens, W.B.
1983-01-01
A constant-voltage, parallel-tuned nuclear magnetic resonance (NMR) circuit, patterned after a Liverpool design, has been developed for polarized target experiments. Measuring the admittance of the resonance circuit allows advantageous use of double-balanced mixer detection. The resonant circuit is tolerant of stray capacitance between the NMR coil and the target cavity, thus easing target-cell-design constraints. The reference leg of the circuit includes a voltage-controlled attenuator and phase shifter for ease of tuning. The NMR output features a flat background and has good linearity and stability
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Millikan, Brian; Dutta, Aritra; Sun, Qiyu; Foroosh, Hassan
2017-01-01
Target detection of potential threats at night can be deployed on a costly infrared focal plane array with high resolution. Due to the compressibility of infrared image patches, the high resolution requirement could be reduced with target detection capability preserved. For this reason, a compressive midwave infrared imager (MWIR) with a low-resolution focal plane array has been developed. As the most probable coefficient indices of the support set of the infrared image patches could be learned from the training data, we develop stochastically trained least squares (STLS) for MWIR image reconstruction. Quadratic correlation filters (QCF) have been shown to be effective for target detection and there are several methods for designing a filter. Using the same measurement matrix as in STLS, we construct a compressed quadratic correlation filter (CQCF) employing filter designs for compressed infrared target detection. We apply CQCF to the U.S. Army Night Vision and Electronic Sensors Directorate dataset. Numerical simulations show that the recognition performance of our algorithm matches that of the standard full reconstruction methods, but at a fraction of the execution time.
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Millikan, Brian
2017-05-02
Target detection of potential threats at night can be deployed on a costly infrared focal plane array with high resolution. Due to the compressibility of infrared image patches, the high resolution requirement could be reduced with target detection capability preserved. For this reason, a compressive midwave infrared imager (MWIR) with a low-resolution focal plane array has been developed. As the most probable coefficient indices of the support set of the infrared image patches could be learned from the training data, we develop stochastically trained least squares (STLS) for MWIR image reconstruction. Quadratic correlation filters (QCF) have been shown to be effective for target detection and there are several methods for designing a filter. Using the same measurement matrix as in STLS, we construct a compressed quadratic correlation filter (CQCF) employing filter designs for compressed infrared target detection. We apply CQCF to the U.S. Army Night Vision and Electronic Sensors Directorate dataset. Numerical simulations show that the recognition performance of our algorithm matches that of the standard full reconstruction methods, but at a fraction of the execution time.
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Moradi, Saed; Moallem, Payman; Sabahi, Mohamad Farzan
2018-03-01
False alarm rate and detection rate are still two contradictory metrics for infrared small target detection in an infrared search and track system (IRST), despite the development of new detection algorithms. In certain circumstances, not detecting true targets is more tolerable than detecting false items as true targets. Hence, considering background clutter and detector noise as the sources of the false alarm in an IRST system, in this paper, a false alarm aware methodology is presented to reduce false alarm rate while the detection rate remains undegraded. To this end, advantages and disadvantages of each detection algorithm are investigated and the sources of the false alarms are determined. Two target detection algorithms having independent false alarm sources are chosen in a way that the disadvantages of the one algorithm can be compensated by the advantages of the other one. In this work, multi-scale average absolute gray difference (AAGD) and Laplacian of point spread function (LoPSF) are utilized as the cornerstones of the desired algorithm of the proposed methodology. After presenting a conceptual model for the desired algorithm, it is implemented through the most straightforward mechanism. The desired algorithm effectively suppresses background clutter and eliminates detector noise. Also, since the input images are processed through just four different scales, the desired algorithm has good capability for real-time implementation. Simulation results in term of signal to clutter ratio and background suppression factor on real and simulated images prove the effectiveness and the performance of the proposed methodology. Since the desired algorithm was developed based on independent false alarm sources, our proposed methodology is expandable to any pair of detection algorithms which have different false alarm sources.
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Detection of Moving Targets Based on Doppler Spectrum Analysis Technique for Passive Coherent Radar
Directory of Open Access Journals (Sweden)
Zhao Yao-dong
2013-06-01
Full Text Available A novel method of moving targets detection taking Doppler spectrum analysis technique for Passive Coherent Radar (PCR is provided. After dividing the receiving signals into segments as pulse series, it utilizes the technique of pulse compress and Doppler processing to detect and locate the targets. Based on the algorithm for Pulse-Doppler (PD radar, the equipollence between continuous and pulsed wave in match filtering is proved and details of this method are introduced. To compare it with the traditional method of Cross-Ambiguity Function (CAF calculation, the relationship and mathematical modes of them are analyzed, with some suggestions on parameters choosing. With little influence to the gain of targets, the method can greatly promote the processing efficiency. The validity of the proposed method is demonstrated by offline processing real collected data sets and simulation results.
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Directory of Open Access Journals (Sweden)
Yang Zhang
2016-10-01
Full Text Available Ultra-wideband (UWB radar has been widely used for detecting human physiological signals (respiration, movement, etc. in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc., the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.
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Zhang, Yang; Chen, Fuming; Xue, Huijun; Li, Zhao; An, Qiang; Wang, Jianqi; Zhang, Yang
2016-10-27
Ultra-wideband (UWB) radar has been widely used for detecting human physiological signals (respiration, movement, etc.) in the fields of rescue, security, and medicine owing to its high penetrability and range resolution. In these applications, especially in rescue after disaster (earthquake, collapse, mine accident, etc.), the presence, number, and location of the trapped victims to be detected and rescued are the key issues of concern. Ample research has been done on the first issue, whereas the identification and localization of multi-targets remains a challenge. False positive and negative identification results are two common problems associated with the detection of multiple stationary human targets. This is mainly because the energy of the signal reflected from the target close to the receiving antenna is considerably stronger than those of the targets at further range, often leading to missing or false recognition if the identification method is based on the energy of the respiratory signal. Therefore, a novel method based on cross-correlation is proposed in this paper that is based on the relativity and periodicity of the signals, rather than on the energy. The validity of this method is confirmed through experiments using different scenarios; the results indicate a discernible improvement in the detection precision and identification of the multiple stationary targets.
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Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis.
Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq
2015-01-01
Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim' based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks.
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Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis
Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq
2015-01-01
Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim’ based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks. PMID:26222882
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Directory of Open Access Journals (Sweden)
Lianpeng Li
2018-04-01
Full Text Available In recent years, the robots, especially heavy-duty robots, have become the hardest-hit areas for targeted attacks. These attacks come from both the cyber-domain and the physical-domain. In order to improve the security of heavy-duty robots, this paper proposes a detection and mitigation mechanism which based on improved deep belief networks (IDBN and dynamic model. The detection mechanism consists of two parts: (1 IDBN security checks, which can detect targeted attacks from the cyber-domain; (2 Dynamic model and security detection, used to detect the targeted attacks which can possibly lead to a physical-domain damage. The mitigation mechanism was established on the base of the detection mechanism and could mitigate transient and discontinuous attacks. Moreover, a test platform was established to carry out the performance evaluation test for the proposed mechanism. The results show that, the detection accuracy for the attack of the cyber-domain of IDBN reaches 96.2%, and the detection accuracy for the attack of physical-domain control commands reaches 94%. The performance evaluation test has verified the reliability and high efficiency of the proposed detection and mitigation mechanism for heavy-duty robots.
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Directory of Open Access Journals (Sweden)
Stougaard Magnus
2007-11-01
Full Text Available Abstract Background In situ detection of short sequence elements in genomic DNA requires short probes with high molecular resolution and powerful specific signal amplification. Padlock probes can differentiate single base variations. Ligated padlock probes can be amplified in situ by rolling circle DNA synthesis and detected by fluorescence microscopy, thus enhancing PRINS type reactions, where localized DNA synthesis reports on the position of hybridization targets, to potentially reveal the binding of single oligonucleotide-size probe molecules. Such a system has been presented for the detection of mitochondrial DNA in fixed cells, whereas attempts to apply rolling circle detection to metaphase chromosomes have previously failed, according to the literature. Methods Synchronized cultured cells were fixed with methanol/acetic acid to prepare chromosome spreads in teflon-coated diagnostic well-slides. Apart from the slide format and the chromosome spreading everything was done essentially according to standard protocols. Hybridization targets were detected in situ with padlock probes, which were ligated and amplified using target primed rolling circle DNA synthesis, and detected by fluorescence labeling. Results An optimized protocol for the spreading of condensed metaphase chromosomes in teflon-coated diagnostic well-slides was developed. Applying this protocol we generated specimens for target primed rolling circle DNA synthesis of padlock probes recognizing a 40 nucleotide sequence in the male specific repetitive satellite I sequence (DYZ1 on the Y-chromosome and a 32 nucleotide sequence in the repetitive kringle IV domain in the apolipoprotein(a gene positioned on the long arm of chromosome 6. These targets were detected with good efficiency, but the efficiency on other target sites was unsatisfactory. Conclusion Our aim was to test the applicability of the method used on mitochondrial DNA to the analysis of nuclear genomes, in particular as
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Moens, Lotte N J; Falk-Sörqvist, Elin; Ljungström, Viktor; Mattsson, Johanna; Sundström, Magnus; La Fleur, Linnéa; Mathot, Lucy; Micke, Patrick; Nilsson, Mats; Botling, Johan
2015-11-01
In recent years, the advent of massively parallel next-generation sequencing technologies has enabled substantial advances in the study of human diseases. Combined with targeted DNA enrichment methods, high sequence coverage can be obtained for different genes simultaneously at a reduced cost per sample, creating unique opportunities for clinical cancer diagnostics. However, the formalin-fixed, paraffin-embedded (FFPE) process of tissue samples, routinely used in pathology departments, results in DNA fragmentation and nucleotide modifications that introduce a number of technical challenges for downstream biomolecular analyses. We evaluated the HaloPlex target enrichment system for somatic mutation detection in 80 tissue fractions derived from 20 clinical cancer cases with paired tumor and normal tissue available in both FFPE and fresh-frozen format. Several modifications to the standard method were introduced, including a reduced target fragment length and two strand capturing. We found that FFPE material can be used for HaloPlex-based target enrichment and next-generation sequencing, even when starting from small amounts of DNA. By specifically capturing both strands for each target fragment, we were able to reduce the number of false-positive errors caused by FFPE-induced artifacts and lower the detection limit for somatic mutations. We believe that the HaloPlex method presented here will be broadly applicable as a tool for somatic mutation detection in clinical cancer settings. Copyright © 2015 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.
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Computational optimisation of targeted DNA sequencing for cancer detection
DEFF Research Database (Denmark)
Martinez, Pierre; McGranahan, Nicholas; Birkbak, Nicolai Juul
2013-01-01
Despite recent progress thanks to next-generation sequencing technologies, personalised cancer medicine is still hampered by intra-tumour heterogeneity and drug resistance. As most patients with advanced metastatic disease face poor survival, there is need to improve early diagnosis. Analysing...... detection. Dividing 4,467 samples into one discovery and two independent validation cohorts, we show that up to 76% of 10 cancer types harbour at least one mutation in a panel of only 25 genes, with high sensitivity across most tumour types. Our analyses demonstrate that targeting "hotspot" regions would...
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A Targeted Swallow Screen for the Detection of Postoperative Dysphagia.
Gee, Erica; Lancaster, Elizabeth; Meltzer, Jospeh; Mendelsohn, Abie H; Benharash, Peyman
2015-10-01
Postoperative dysphagia leads to aspiration pneumonia, prolonged hospital stay, and is associated with increased mortality. A simple and sensitive screening test to identify patients requiring objective dysphagia evaluation is presently lacking. In this study, we evaluated the efficacy of a novel targeted swallow screen evaluation. This was a prospective trial involving all adult patients who underwent elective cardiac surgery with cardiopulmonary bypass at our institution over an 8-week period. Within 24 hours of extubation and before the initiation of oral intake, all postsurgical patients were evaluated using the targeted swallow screen. A fiberoptic endoscopic evaluation of swallowing was requested for failed screenings. During the study, 50 postcardiac surgery patients were screened. Fifteen (30%) failed the targeted swallow screen, and ten of the fifteen (66%) failed the subsequent fiberoptic endoscopic evaluation of swallowing exam and were confirmed to have dysphagia. The screening test had 100 per cent sensitivity for detecting dysphagia in our patient population, and a specificity of 87.5 per cent. The overall incidence of dysphagia was 20 per cent. We have shown that a targeted swallow evaluation can efficiently screen patients during the postcardiac surgery period. Furthermore, we have shown that the true incidence of dysphagia after cardiac surgery is significantly higher than previously recognized in literature.
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Lin, Douglas I; Hecht, Jonathan L
2016-06-01
Endometrial cancer is associated with Lynch syndrome in 2% to 6% of cases. Adequate screening may prevent of a second cancer and incident cancers in family members via risk-reducing strategies. The goal of the study was to evaluate the detection rate of Lynch syndrome via a targeted screening approach. In 2009, we incorporated targeted Lynch syndrome screening via immunohistochemistry for MLH1, PMS2, MSH2, and MSH6, followed by MLH1 promoter hypermethylation, in select cases of endometrial carcinoma. Criteria for patient selection included (1) all patients Lynch syndrome. Therefore, targeted screening with combined age and morphology based criteria enriches detection of Lynch syndrome in endometrial cancer. However, the detection rate is lower than the rates from published series that offer universal screening. © The Author(s) 2016.
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Directory of Open Access Journals (Sweden)
Maria W Smith
Full Text Available PCR multiplexing has proven to be challenging, and thus has provided limited means for pathogen genotyping. We developed a new approach for analysis of PCR amplicons based on restriction endonuclease digestion. The first stage of the restriction enzyme assay is hybridization of a target DNA to immobilized complementary oligonucleotide probes that carry a molecular marker, horseradish peroxidase (HRP. At the second stage, a target-specific restriction enzyme is added, cleaving the target-probe duplex at the corresponding restriction site and releasing the HRP marker into solution, where it is quantified colorimetrically. The assay was tested for detection of the methicillin-resistant Staphylococcus aureus (MRSA pathogen, using the mecA gene as a target. Calibration curves indicated that the limit of detection for both target oligonucleotide and PCR amplicon was approximately 1 nM. Sequences of target oligonucleotides were altered to demonstrate that (i any mutation of the restriction site reduced the signal to zero; (ii double and triple point mutations of sequences flanking the restriction site reduced restriction to 50-80% of the positive control; and (iii a minimum of a 16-bp target-probe dsDNA hybrid was required for significant cleavage. Further experiments showed that the assay could detect the mecA amplicon from an unpurified PCR mixture with detection limits similar to those with standard fluorescence-based qPCR. Furthermore, addition of a large excess of heterologous genomic DNA did not affect amplicon detection. Specificity of the assay is very high because it involves two biorecognition steps. The proposed assay is low-cost and can be completed in less than 1 hour. Thus, we have demonstrated an efficient new approach for pathogen detection and amplicon genotyping in conjunction with various end-point and qPCR applications. The restriction enzyme assay may also be used for parallel analysis of multiple different amplicons from the same
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Li, Yanpeng; Li, Xiang; Wang, Hongqiang; Deng, Bin; Qin, Yuliang
2016-01-06
Radar is a very important sensor in surveillance applications. Near-space vehicle-borne radar (NSVBR) is a novel installation of a radar system, which offers many benefits, like being highly suited to the remote sensing of extremely large areas, having a rapidly deployable capability and having low vulnerability to electronic countermeasures. Unfortunately, a target detection challenge arises because of complicated scenarios, such as nuclear blackout, rain attenuation, etc. In these cases, extra care is needed to evaluate the detection performance in blackout situations, since this a classical problem along with the application of an NSVBR. However, the existing evaluation measures are the probability of detection and the receiver operating curve (ROC), which cannot offer detailed information in such a complicated application. This work focuses on such requirements. We first investigate the effect of blackout on an electromagnetic wave. Performance evaluation indexes are then built: three evaluation indexes on the detection capability and two evaluation indexes on the robustness of the detection process. Simulation results show that the proposed measure will offer information on the detailed performance of detection. These measures are therefore very useful in detecting the target of interest in a remote sensing system and are helpful for both the NSVBR designers and users.
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Usefulness of thin slice target CT scan in detecting mediastinal and hilar lymphadenopathy
International Nuclear Information System (INIS)
Yoshida, Shoji; Maeda, Tomoho; Nishioka, Masatoshi
1986-01-01
Comparative study of target scan with the different slice thickness and scan modes was performed to evaluate the mediastinal and hilar lymphadenopathy. 20 cases in controls and 35 cases in lymphadenopathy were examined. To delineate mediastinal and hilar lymphadenopathy, the scan mode of standard target was most useful in contrast and sharpness. Thin slice thickness with 5 mm was necessary in detecting small lymphnode or contour and internal structure of enlarged lymphnode. Valuable estimation of 5 mm contiguous target scan was obtained in the subaortic node (no. 5), tracheobronchial node (no. 4), precarinal and subcarinal node (no. 7) and right hilar node (no. 12). (author)
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Quétard, Boris; Quinton, Jean-Charles; Colomb, Michèle; Pezzulo, Giovanni; Barca, Laura; Izaute, Marie; Appadoo, Owen Kevin; Mermillod, Martial
2015-09-01
Detecting a pedestrian while driving in the fog is one situation where the prior expectation about the target presence is integrated with the noisy visual input. We focus on how these sources of information influence the oculomotor behavior and are integrated within an underlying decision-making process. The participants had to judge whether high-/low-density fog scenes displayed on a computer screen contained a pedestrian or a deer by executing a mouse movement toward the response button (mouse-tracking). A variable road sign was added on the scene to manipulate expectations about target identity. We then analyzed the timing and amplitude of the deviation of mouse trajectories toward the incorrect response and, using an eye tracker, the detection time (before fixating the target) and the identification time (fixations on the target). Results revealed that expectation of the correct target results in earlier decisions with less deviation toward the alternative response, this effect being partially explained by the facilitation of target identification.
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[Study on spectral detection of green plant target].
Deng, Wei; Zhao, Chun-jiang; He, Xiong-kui; Chen, Li-ping; Zhang, Lu-da; Wu, Guang-wei; Mueller, J; Zhai, Chang-yuan
2010-08-01
Weeds grow scatteredly in fields, where many insentient objects exist, for example, withered grasses, dry twig and barriers. In order to improve the precision level of spraying, it is important to study green plant detecting technology. The present paper discussed detecting method of green plant by using spectral recognizing technology, because of the real-time feature of spectral recognition. By analyzing the reflectivity difference between each of the two sides of the "red edge" of the spectrum from plants and surrounding environment, green plant discriminat index (GPDI) is defined as the value which equals the reflectivity ratio at the wavelength of 850 nm divided by the reflectivity ratio at the wavelength of 650 nm. The original spectral data of green plants and the background were measured by using the handhold FieldSpec 3 Spectroradiometer manufactured by ASD Inc. in USA. The spectral data were processed to get the reflectivity of each measured objects and to work out the GPDI thereof as well. The classification model of green plant and its background was built up using decision tree method in order to obtain the threshold of GPDI to distinguish green plants and the background. The threshold of GPDI was chosen as 5.54. The detected object was recognized as green plant when it is GPDI>GPDITH, and vice versa. Through another test, the accuracy rate was verified which was 100% by using the threshold. The authors designed and developed the green plant detector based on single chip microcomputer (SCM) "AT89S51" and photodiode "OPT101" to realize detecting green plants from the background. After passing through two optical filters, the center wavelengths of which are 650 and 850 nm respectively, the reflected light from measured targets was detected by two photodiodes and converted into electrical signals. These analog signals were then converted to digital signals via an analog-to-digital converter (ADS7813) after being amplified by a signal amplifier (OP400
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Directory of Open Access Journals (Sweden)
Z. W. ZONG
2014-04-01
Full Text Available Multiple repeat false targets (RFTs, created by the digital radio frequency memory (DRFM system of jammer, are widely used in practical to effectively exhaust the limited tracking and discrimination resource of defence radar. In this paper, common characteristic of radar polarization echoes of multiple RFTs is used for target recognition. Based on the echoes from two receiving polarization channels, the instantaneous polarization radio (IPR is defined and its variance is derived by employing Taylor series expansion. A detection-discrimination method is designed based on probability grids. By using the data from microwave anechoic chamber, the detection threshold of the method is confirmed. Theoretical analysis and simulations indicate that the method is valid and feasible. Furthermore, the estimation performance of IPRs of RFTs due to the influence of signal noise ratio (SNR is also covered.
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Li, Zheng-Zhou; Chen, Jing; Hou, Qian; Fu, Hong-Xia; Dai, Zhen; Jin, Gang; Li, Ru-Zhang; Liu, Chang-Ju
2014-05-27
It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD) algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn't be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.
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Directory of Open Access Journals (Sweden)
Zheng-Zhou Li
2014-05-01
Full Text Available It is difficult for structural over-complete dictionaries such as the Gabor function and discriminative over-complete dictionary, which are learned offline and classified manually, to represent natural images with the goal of ideal sparseness and to enhance the difference between background clutter and target signals. This paper proposes an infrared dim target detection approach based on sparse representation on a discriminative over-complete dictionary. An adaptive morphological over-complete dictionary is trained and constructed online according to the content of infrared image by K-singular value decomposition (K-SVD algorithm. Then the adaptive morphological over-complete dictionary is divided automatically into a target over-complete dictionary describing target signals, and a background over-complete dictionary embedding background by the criteria that the atoms in the target over-complete dictionary could be decomposed more sparsely based on a Gaussian over-complete dictionary than the one in the background over-complete dictionary. This discriminative over-complete dictionary can not only capture significant features of background clutter and dim targets better than a structural over-complete dictionary, but also strengthens the sparse feature difference between background and target more efficiently than a discriminative over-complete dictionary learned offline and classified manually. The target and background clutter can be sparsely decomposed over their corresponding over-complete dictionaries, yet couldn’t be sparsely decomposed based on their opposite over-complete dictionary, so their residuals after reconstruction by the prescribed number of target and background atoms differ very visibly. Some experiments are included and the results show that this proposed approach could not only improve the sparsity more efficiently, but also enhance the performance of small target detection more effectively.
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Joint sparsity based heterogeneous data-level fusion for target detection and estimation
Niu, Ruixin; Zulch, Peter; Distasio, Marcello; Blasch, Erik; Shen, Dan; Chen, Genshe
2017-05-01
Typical surveillance systems employ decision- or feature-level fusion approaches to integrate heterogeneous sensor data, which are sub-optimal and incur information loss. In this paper, we investigate data-level heterogeneous sensor fusion. Since the sensors monitor the common targets of interest, whose states can be determined by only a few parameters, it is reasonable to assume that the measurement domain has a low intrinsic dimensionality. For heterogeneous sensor data, we develop a joint-sparse data-level fusion (JSDLF) approach based on the emerging joint sparse signal recovery techniques by discretizing the target state space. This approach is applied to fuse signals from multiple distributed radio frequency (RF) signal sensors and a video camera for joint target detection and state estimation. The JSDLF approach is data-driven and requires minimum prior information, since there is no need to know the time-varying RF signal amplitudes, or the image intensity of the targets. It can handle non-linearity in the sensor data due to state space discretization and the use of frequency/pixel selection matrices. Furthermore, for a multi-target case with J targets, the JSDLF approach only requires discretization in a single-target state space, instead of discretization in a J-target state space, as in the case of the generalized likelihood ratio test (GLRT) or the maximum likelihood estimator (MLE). Numerical examples are provided to demonstrate that the proposed JSDLF approach achieves excellent performance with near real-time accurate target position and velocity estimates.
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Detection of atherosclerotic lesions and intimal macrophages using CD36-targeted nanovesicles.
Nie, Shufang; Zhang, Jia; Martinez-Zaguilan, Raul; Sennoune, Souad; Hossen, Md Nazir; Lichtenstein, Alice H; Cao, Jun; Meyerrose, Gary E; Paone, Ralph; Soontrapa, Suthipong; Fan, Zhaoyang; Wang, Shu
2015-12-28
Current approaches to the diagnosis and therapy of atherosclerosis cannot target lesion-determinant cells in the artery wall. Intimal macrophage infiltration promotes atherosclerotic lesion development by facilitating the accumulation of oxidized low-density lipoproteins (oxLDL) and increasing inflammatory responses. The presence of these cells is positively associated with lesion progression, severity and destabilization. Hence, they are an important diagnostic and therapeutic target. The objective of this study was to noninvasively assess the distribution and accumulation of intimal macrophages using CD36-targeted nanovesicles. Soy phosphatidylcholine was used to synthesize liposome-like nanovesicles. 1-(Palmitoyl)-2-(5-keto-6-octene-dioyl) phosphatidylcholine was incorporated on their surface to target the CD36 receptor. All in vitro data demonstrate that these targeted nanovesicles had a high binding affinity for the oxLDL binding site of the CD36 receptor and participated in CD36-mediated recognition and uptake of nanovesicles by macrophages. Intravenous administration into LDL receptor null mice of targeted compared to non-targeted nanovesicles resulted in higher uptake in aortic lesions. The nanovesicles co-localized with macrophages and their CD36 receptors in aortic lesions. This molecular target approach may facilitate the in vivo noninvasive imaging of atherosclerotic lesions in terms of intimal macrophage accumulation and distribution and disclose lesion features related to inflammation and possibly vulnerability thereby facilitate early lesion detection and targeted delivery of therapeutic compounds to intimal macrophages. Copyright © 2015 Elsevier B.V. All rights reserved.
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Drug target ontology to classify and integrate drug discovery data.
Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C
2017-11-09
model for druggable targets including various related information such as protein, gene, protein domain, protein structure, binding site, small molecule drug, mechanism of action, protein tissue localization, disease association, and many other types of information. DTO will further facilitate the otherwise challenging integration and formal linking to biological assays, phenotypes, disease models, drug poly-pharmacology, binding kinetics and many other processes, functions and qualities that are at the core of drug discovery. The first version of DTO is publically available via the website http://drugtargetontology.org/ , Github ( http://github.com/DrugTargetOntology/DTO ), and the NCBO Bioportal ( http://bioportal.bioontology.org/ontologies/DTO ). The long-term goal of DTO is to provide such an integrative framework and to populate the ontology with this information as a community resource.
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Rapid Target Detection in High Resolution Remote Sensing Images Using Yolo Model
Wu, Z.; Chen, X.; Gao, Y.; Li, Y.
2018-04-01
Object detection in high resolution remote sensing images is a fundamental and challenging problem in the field of remote sensing imagery analysis for civil and military application due to the complex neighboring environments, which can cause the recognition algorithms to mistake irrelevant ground objects for target objects. Deep Convolution Neural Network(DCNN) is the hotspot in object detection for its powerful ability of feature extraction and has achieved state-of-the-art results in Computer Vision. Common pipeline of object detection based on DCNN consists of region proposal, CNN feature extraction, region classification and post processing. YOLO model frames object detection as a regression problem, using a single CNN predicts bounding boxes and class probabilities in an end-to-end way and make the predict faster. In this paper, a YOLO based model is used for object detection in high resolution sensing images. The experiments on NWPU VHR-10 dataset and our airport/airplane dataset gain from GoogleEarth show that, compare with the common pipeline, the proposed model speeds up the detection process and have good accuracy.
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International Nuclear Information System (INIS)
Mariscotti, Giovanna; Durando, Manuela; Regini, Elisa; Fornari, Alberto; Fonio, Paolo; Gandini, Giovanni; Houssami, Nehmat; Campanino, Pier Paolo; Bussone, Riccardo; Castellano, Isabella; Sapino, Anna
2015-01-01
Preoperative breast magnetic resonance (MR) often generates additional suspicious findings needing further investigations. Targeted breast ultrasound (US) is the standard tool to characterize MR additional lesions. The purpose of this study is to evaluate the potential role of digital breast tomosynthesis (DBT) to characterize MR detected additional findings, unidentified at targeted breast US. This prospective study included women who a) had biopsy-proven, newly diagnosed breast cancers detected at conventional 2D mammography and/or US, referred to breast MR for tumour staging; and b) had DBT if additional MR findings were not detected at targeted ('second look') US. In 520 patients, MR identified 164 (in 114 women, 22 %) additional enhancing lesions. Targeted US identified 114/164 (69.5 %) of these, whereas 50/164 (30.5 %) remained unidentified. DBT identified 32/50 of these cases, increasing the overall characterization of MR detected additional findings to 89.0 % (146/164). Using DBT the identified lesions were significantly more likely to be malignant than benign MR-detected additional lesions (p = 0.04). DBT improves the characterization of additional MR findings not identified at targeted breast US in preoperative breast cancer staging. (orig.)
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Energy Technology Data Exchange (ETDEWEB)
Mariscotti, Giovanna; Durando, Manuela; Regini, Elisa; Fornari, Alberto; Fonio, Paolo; Gandini, Giovanni [Breast Imaging Service, Radiology - University of Turin, Department of Diagnostic Imaging and Radiotherapy, A.O.U. Citta della Salute e della Scienza, Torino (Italy); Houssami, Nehmat [University of Sydney, Screening and Test Evaluation Program, School of Public Health, Sydney Medical School, Sydney, NSW (Australia); Campanino, Pier Paolo [Ospedale Koelliker, Breast Imaging Service, Torino (Italy); Bussone, Riccardo [A.O.U. Citta della Salute e della Scienza of Turin, SSCVD Breast Surgery. Department of Surgery, Torino (Italy); Castellano, Isabella; Sapino, Anna [University of Turin, Department of Biomedical Sciences and Human Oncology, A.O.U. Citta della Salute e della Scienza, Torino (Italy)
2015-09-15
Preoperative breast magnetic resonance (MR) often generates additional suspicious findings needing further investigations. Targeted breast ultrasound (US) is the standard tool to characterize MR additional lesions. The purpose of this study is to evaluate the potential role of digital breast tomosynthesis (DBT) to characterize MR detected additional findings, unidentified at targeted breast US. This prospective study included women who a) had biopsy-proven, newly diagnosed breast cancers detected at conventional 2D mammography and/or US, referred to breast MR for tumour staging; and b) had DBT if additional MR findings were not detected at targeted ('second look') US. In 520 patients, MR identified 164 (in 114 women, 22 %) additional enhancing lesions. Targeted US identified 114/164 (69.5 %) of these, whereas 50/164 (30.5 %) remained unidentified. DBT identified 32/50 of these cases, increasing the overall characterization of MR detected additional findings to 89.0 % (146/164). Using DBT the identified lesions were significantly more likely to be malignant than benign MR-detected additional lesions (p = 0.04). DBT improves the characterization of additional MR findings not identified at targeted breast US in preoperative breast cancer staging. (orig.)
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Silvestre, Daphné; Cavanagh, Patrick; Arleo, Angelo; Allard, Rémy
2017-02-01
External noise paradigms are widely used to characterize sensitivity by comparing the effect of a variable on contrast threshold when it is limited by internal versus external noise. A basic assumption of external noise paradigms is that the processing properties are the same in low and high noise. However, recent studies (e.g., Allard & Cavanagh, 2011; Allard & Faubert, 2014b) suggest that this assumption could be violated when using spatiotemporally localized noise (i.e., appearing simultaneously and at the same location as the target) but not when using spatiotemporally extended noise (i.e., continuously displayed, full-screen, dynamic noise). These previous findings may have been specific to the crowding and 0D noise paradigms that were used, so the purpose of the current study is to test if this violation of noise-invariant processing also occurs in a standard contrast detection task in white noise. The rationale of the current study is that local external noise triggers the use of recognition rather than detection and that a recognition process should be more affected by uncertainty about the shape of the target than one involving detection. To investigate the contribution of target knowledge on contrast detection, the effect of orientation uncertainty was evaluated for a contrast detection task in the absence of noise and in the presence of spatiotemporally localized or extended noise. A larger orientation uncertainty effect was observed with temporally localized noise than with temporally extended noise or with no external noise, indicating a change in the nature of the processing for temporally localized noise. We conclude that the use of temporally localized noise in external noise paradigms risks triggering a shift in process, invalidating the noise-invariant processing required for the paradigm. If, instead, temporally extended external noise is used to match the properties of internal noise, no such processing change occurs.
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Mustafa, Mohammad Razif Bin; Dhahi, Th S.; Ehfaed, Nuri. A. K. H.; Adam, Tijjani; Hashim, U.; Azizah, N.; Mohammed, Mohammed; Noriman, N. Z.
2017-09-01
The nano structure based on silicon can be surface modified to be used as label-free biosensors that allow real-time measurements. The silicon nanowire surface was functionalized using 3-aminopropyltrimethoxysilane (APTES), which functions as a facilitator to immobilize biomolecules on the silicon nanowire surface. The process is simple, economical; this will pave the way for point-of-care applications. However, the surface modification and subsequent detection mechanism still not clear. Thus, study proposed step by step process of silicon nano surface modification and its possible in specific and selective target detection of Supra-genome 21 Mers Salmonella. The device captured the molecule with precisely; the approach took the advantages of strong binding chemistry created between APTES and biomolecule. The results indicated how modifications of the nanowires provide sensing capability with strong surface chemistries that can lead to specific and selective target detection.
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Wang, Yunhua; Li, Huimin; Zhang, Yanmin; Guo, Lixin
2015-01-01
A focus on marine target detection in noise corrupted fully polarimetric synthetic aperture radar (SAR) is presented. The property of the relative phase between two cross-polarized channels reveals that the relative phases evaluated within sea surface area or noise corrupted area are widely spread phase angle region [-π,π] due to decorrelation effect; however, the relative phases are concentrated to zero and ±π for real target and its first-order azimuth ambiguities (FOAAs), respectively. Exploiting this physical behavior, the reciprocal of the mean square value of the relative phase (RMSRP) is defined as a new parameter for target detection, and the experiments based on fully polarimetric Radarsat-2 SAR images show that the strong noise and the FOAAs can be effectively suppressed in RMSRP image. Meanwhile, validity of the new parameter for target detection is also verified by two typical Radarsat-2 SAR images, in which targets' ambiguities and strong noise are present.
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panelcn.MOPS: Copy-number detection in targeted NGS panel data for clinical diagnostics.
Povysil, Gundula; Tzika, Antigoni; Vogt, Julia; Haunschmid, Verena; Messiaen, Ludwine; Zschocke, Johannes; Klambauer, Günter; Hochreiter, Sepp; Wimmer, Katharina
2017-07-01
Targeted next-generation-sequencing (NGS) panels have largely replaced Sanger sequencing in clinical diagnostics. They allow for the detection of copy-number variations (CNVs) in addition to single-nucleotide variants and small insertions/deletions. However, existing computational CNV detection methods have shortcomings regarding accuracy, quality control (QC), incidental findings, and user-friendliness. We developed panelcn.MOPS, a novel pipeline for detecting CNVs in targeted NGS panel data. Using data from 180 samples, we compared panelcn.MOPS with five state-of-the-art methods. With panelcn.MOPS leading the field, most methods achieved comparably high accuracy. panelcn.MOPS reliably detected CNVs ranging in size from part of a region of interest (ROI), to whole genes, which may comprise all ROIs investigated in a given sample. The latter is enabled by analyzing reads from all ROIs of the panel, but presenting results exclusively for user-selected genes, thus avoiding incidental findings. Additionally, panelcn.MOPS offers QC criteria not only for samples, but also for individual ROIs within a sample, which increases the confidence in called CNVs. panelcn.MOPS is freely available both as R package and standalone software with graphical user interface that is easy to use for clinical geneticists without any programming experience. panelcn.MOPS combines high sensitivity and specificity with user-friendliness rendering it highly suitable for routine clinical diagnostics. © 2017 The Authors. Human Mutation published by Wiley Periodicals, Inc.
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TRUSTWORTHY OPTIMIZED CLUSTERING BASED TARGET DETECTION AND TRACKING FOR WIRELESS SENSOR NETWORK
Directory of Open Access Journals (Sweden)
C. Jehan
2016-06-01
Full Text Available In this paper, an efficient approach is proposed to address the problem of target tracking in wireless sensor network (WSN. The problem being tackled here uses adaptive dynamic clustering scheme for tracking the target. It is a specific problem in object tracking. The proposed adaptive dynamic clustering target tracking scheme uses three steps for target tracking. The first step deals with the identification of clusters and cluster heads using OGSAFCM. Here, kernel fuzzy c-means (KFCM and gravitational search algorithm (GSA are combined to create clusters. At first, oppositional gravitational search algorithm (OGSA is used to optimize the initial clustering center and then the KFCM algorithm is availed to guide the classification and the cluster formation process. In the OGSA, the concept of the opposition based population initialization in the basic GSA to improve the convergence profile. The identified clusters are changed dynamically. The second step deals with the data transmission to the cluster heads. The third step deals with the transmission of aggregated data to the base station as well as the detection of target. From the experimental results, the proposed scheme efficiently and efficiently identifies the target. As a result the tracking error is minimized.
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Target vessel detection by epicardial ultrasound in off-pump coronary bypass surgery.
Hayakawa, Masato; Asai, Tohru; Kinoshita, Takeshi; Suzuki, Tomoaki; Shiraishi, Shoichiro
2013-01-01
The detection of embedded coronary arteries is difficult especially in off-pump coronary bypass surgery. From June 2010, we introduced high-frequency epicardial ultrasound (ECUS) to assess and evaluate embedded arteries during off-pump coronary bypass surgery. Between June 2010 and June 2011, a total of 89 consecutive patients underwent isolated coronary bypass surgery at our institution. The patients consisted of 72 men and 17 women with a mean age of 67.9 years. We routinely use the VeriQC system (MediStim, Oslo, Norway) to detect the target vessels in the operation. The patients were assigned to one of two groups, depending on whether ECUS was used in the operation (n = 10, ECUS group) or not (n = 79, non-ECUS group). We analyzed the impact of introducing the ECUS in terms of operative outcome. All patients underwent revascularization using the off-pump technique without emergent conversion to cardiopulmonary bypass during surgery. The total number of distal anastomoses was 299, and 12 target vessels could not be identified either visually or on palpation. Thus, the frequency of the embedded coronary arteries was 4.01% (12/299 cases). The preoperative profiles of the two groups were not significantly different. Operation time was significantly longer in the ECUS group (P = 0.02). There were no significant differences in postoperative outcome between the two groups. In the present study, in which the target coronary arteries could not be detected either visually or on palpation in 12 (4.01%) of 299 cases, the use of high-frequency ECUS allowed all patients to undergo off-pump coronary bypass surgery without conversion to cardiopulmonary bypass during the operation. High-frequency ECUS is therefore useful in off-pump coronary bypass surgery.
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A Plant Immune Receptor Detects Pathogen Effectors that Target WRKY Transcription Factors.
Sarris, Panagiotis F; Duxbury, Zane; Huh, Sung Un; Ma, Yan; Segonzac, Cécile; Sklenar, Jan; Derbyshire, Paul; Cevik, Volkan; Rallapalli, Ghanasyam; Saucet, Simon B; Wirthmueller, Lennart; Menke, Frank L H; Sohn, Kee Hoon; Jones, Jonathan D G
2015-05-21
Defense against pathogens in multicellular eukaryotes depends on intracellular immune receptors, yet surveillance by these receptors is poorly understood. Several plant nucleotide-binding, leucine-rich repeat (NB-LRR) immune receptors carry fusions with other protein domains. The Arabidopsis RRS1-R NB-LRR protein carries a C-terminal WRKY DNA binding domain and forms a receptor complex with RPS4, another NB-LRR protein. This complex detects the bacterial effectors AvrRps4 or PopP2 and then activates defense. Both bacterial proteins interact with the RRS1 WRKY domain, and PopP2 acetylates lysines to block DNA binding. PopP2 and AvrRps4 interact with other WRKY domain-containing proteins, suggesting these effectors interfere with WRKY transcription factor-dependent defense, and RPS4/RRS1 has integrated a "decoy" domain that enables detection of effectors that target WRKY proteins. We propose that NB-LRR receptor pairs, one member of which carries an additional protein domain, enable perception of pathogen effectors whose function is to target that domain. Copyright © 2015 Elsevier Inc. All rights reserved.
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A comparison of machine learning techniques for detection of drug target articles.
Danger, Roxana; Segura-Bedmar, Isabel; Martínez, Paloma; Rosso, Paolo
2010-12-01
Important progress in treating diseases has been possible thanks to the identification of drug targets. Drug targets are the molecular structures whose abnormal activity, associated to a disease, can be modified by drugs, improving the health of patients. Pharmaceutical industry needs to give priority to their identification and validation in order to reduce the long and costly drug development times. In the last two decades, our knowledge about drugs, their mechanisms of action and drug targets has rapidly increased. Nevertheless, most of this knowledge is hidden in millions of medical articles and textbooks. Extracting knowledge from this large amount of unstructured information is a laborious job, even for human experts. Drug target articles identification, a crucial first step toward the automatic extraction of information from texts, constitutes the aim of this paper. A comparison of several machine learning techniques has been performed in order to obtain a satisfactory classifier for detecting drug target articles using semantic information from biomedical resources such as the Unified Medical Language System. The best result has been achieved by a Fuzzy Lattice Reasoning classifier, which reaches 98% of ROC area measure. Copyright © 2010 Elsevier Inc. All rights reserved.
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Chan, George Ho Man; Ho, Emmie Ngai Man; Leung, David Kwan Kon; Wong, Kin Sing; Wan, Terence See Ming
2016-01-05
The use of anabolic androgenic steroids (AAS) is prohibited in both human and equine sports. The conventional approach in doping control testing for AAS (as well as other prohibited substances) is accomplished by the direct detection of target AAS or their characteristic metabolites in biological samples using hyphenated techniques such as gas chromatography or liquid chromatography coupled with mass spectrometry. Such an approach, however, falls short when dealing with unknown designer steroids where reference materials and their pharmacokinetics are not available. In addition, AASs with fast elimination times render the direct detection approach ineffective as the detection window is short. A targeted metabolomics approach is a plausible alternative to the conventional direct detection approach for controlling the misuse of AAS in sports. Because the administration of AAS of the same class may trigger similar physiological responses or effects in the body, it may be possible to detect such administrations by monitoring changes in the endogenous steroidal expression profile. This study attempts to evaluate the viability of using the targeted metabolomics approach to detect the administration of steroidal aromatase inhibitors, namely androst-4-ene-3,6,17-trione (6-OXO) and androsta-1,4,6-triene-3,17-dione (ATD), in horses. Total (free and conjugated) urinary concentrations of 31 endogenous steroids were determined by gas chromatography-tandem mass spectrometry for a group of 2 resting and 2 in-training thoroughbred geldings treated with either 6-OXO or ATD. Similar data were also obtained from a control (untreated) group of in-training thoroughbred geldings (n = 28). Statistical processing and chemometric procedures using principle component analysis and orthogonal projection to latent structures-discriminant analysis (OPLS-DA) have highlighted 7 potential biomarkers that could be used to differentiate urine samples obtained from the control and the treated groups
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Valerio, Massimo; McCartan, Neil; Freeman, Alex; Punwani, Shonit; Emberton, Mark; Ahmed, Hashim U
2015-10-01
Targeted biopsy based on cognitive or software magnetic resonance imaging (MRI) to transrectal ultrasound registration seems to increase the detection rate of clinically significant prostate cancer as compared with standard biopsy. However, these strategies have not been directly compared against an accurate test yet. The aim of this study was to obtain pilot data on the diagnostic ability of visually directed targeted biopsy vs. software-based targeted biopsy, considering transperineal template mapping (TPM) biopsy as the reference test. Prospective paired cohort study included 50 consecutive men undergoing TPM with one or more visible targets detected on preoperative multiparametric MRI. Targets were contoured on the Biojet software. Patients initially underwent software-based targeted biopsies, then visually directed targeted biopsies, and finally systematic TPM. The detection rate of clinically significant disease (Gleason score ≥3+4 and/or maximum cancer core length ≥4mm) of one strategy against another was compared by 3×3 contingency tables. Secondary analyses were performed using a less stringent threshold of significance (Gleason score ≥4+3 and/or maximum cancer core length ≥6mm). Median age was 68 (interquartile range: 63-73); median prostate-specific antigen level was 7.9ng/mL (6.4-10.2). A total of 79 targets were detected with a mean of 1.6 targets per patient. Of these, 27 (34%), 28 (35%), and 24 (31%) were scored 3, 4, and 5, respectively. At a patient level, the detection rate was 32 (64%), 34 (68%), and 38 (76%) for visually directed targeted, software-based biopsy, and TPM, respectively. Combining the 2 targeted strategies would have led to detection rate of 39 (78%). At a patient level and at a target level, software-based targeted biopsy found more clinically significant diseases than did visually directed targeted biopsy, although this was not statistically significant (22% vs. 14%, P = 0.48; 51.9% vs. 44.3%, P = 0.24). Secondary
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Directory of Open Access Journals (Sweden)
La Mura Maurizio
2009-02-01
Full Text Available Abstract Background The most common method of GMO detection is based upon the amplification of GMO-specific DNA amplicons using the polymerase chain reaction (PCR. Here we have applied the loop-mediated isothermal amplification (LAMP method to amplify GMO-related DNA sequences, 'internal' commonly-used motifs for controlling transgene expression and event-specific (plant-transgene junctions. Results We have tested the specificity and sensitivity of the technique for use in GMO studies. Results show that detection of 0.01% GMO in equivalent background DNA was possible and dilutions of template suggest that detection from single copies of the template may be possible using LAMP. Conclusion This work shows that GMO detection can be carried out using LAMP for routine screening as well as for specific events detection. Moreover, the sensitivity and ability to amplify targets, even with a high background of DNA, here demonstrated, highlights the advantages of this isothermal amplification when applied for GMO detection.
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Lee, David; La Mura, Maurizio; Allnutt, Theo R; Powell, Wayne
2009-02-02
The most common method of GMO detection is based upon the amplification of GMO-specific DNA amplicons using the polymerase chain reaction (PCR). Here we have applied the loop-mediated isothermal amplification (LAMP) method to amplify GMO-related DNA sequences, 'internal' commonly-used motifs for controlling transgene expression and event-specific (plant-transgene) junctions. We have tested the specificity and sensitivity of the technique for use in GMO studies. Results show that detection of 0.01% GMO in equivalent background DNA was possible and dilutions of template suggest that detection from single copies of the template may be possible using LAMP. This work shows that GMO detection can be carried out using LAMP for routine screening as well as for specific events detection. Moreover, the sensitivity and ability to amplify targets, even with a high background of DNA, here demonstrated, highlights the advantages of this isothermal amplification when applied for GMO detection.
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Magneto-mechanical trapping systems for biological target detection
Li, Fuquan
2014-03-29
We demonstrate a magnetic microsystem capable of detecting nucleic acids via the size difference between bare magnetic beads and bead compounds. The bead compounds are formed through linking nonmagnetic beads and magnetic beads by the target nucleic acids. The system comprises a tunnel magneto-resistive (TMR) sensor, a trapping well, and a bead-concentrator. The TMR sensor detects the stray field of magnetic beads inside the trapping well, while the sensor output depends on the number of beads. The size of the bead compounds is larger than that of bare magnetic beads, and fewer magnetic beads are required to fill the trapping well. The bead-concentrator, in turn, is capable of filling the trap in a controlled fashion and so to shorten the assay time. The bead-concentrator includes conducting loops surrounding the trapping well and a conducting line underneath. The central conducting line serves to attract magnetic beads in the trapping well and provides a magnetic field to magnetize them so to make them detectable by the TMR sensor. This system excels by its simplicity in that the DNA is incubated with magnetic and nonmagnetic beads, and the solution is then applied to the chip and analyzed in a single step. In current experiments, a signal-to-noise ratio of 40.3 dB was obtained for a solution containing 20.8 nM of DNA. The sensitivity and applicability of this method can be controlled by the size or concentration of the nonmagnetic bead, or by the dimension of the trapping well.
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Magneto-mechanical trapping systems for biological target detection
International Nuclear Information System (INIS)
Li, Fuquan; Kodzius, Rimantas; Gooneratne, Chinthaka P.; Foulds, Ian G.; Kosel, Jürgen
2014-01-01
We demonstrate a magnetic microsystem capable of detecting nucleic acids via the size difference between bare magnetic beads and bead compounds. The bead compounds are formed through linking nonmagnetic beads and magnetic beads by the target nucleic acids. The system comprises a tunnel magneto-resistive (TMR) sensor, a trapping well, and a bead-concentrator. The TMR sensor detects the stray field of magnetic beads inside the trapping well, while the sensor output depends on the number of beads. The size of the bead compounds is larger than that of bare magnetic beads, and fewer magnetic beads are required to fill the trapping well. The bead-concentrator, in turn, is capable of filling the trap in a controlled fashion and so to shorten the assay time. The bead-concentrator includes conducting loops surrounding the trapping well and a conducting line underneath. The central conducting line serves to attract magnetic beads in the trapping well and provides a magnetic field to magnetize them so to make them detectable by the TMR sensor. This system excels by its simplicity in that the DNA is incubated with magnetic and nonmagnetic beads, and the solution is then applied to the chip and analyzed in a single step. In current experiments, a signal-to-noise ratio of 40.3 dB was obtained for a solution containing 20.8 nM of DNA. The sensitivity and applicability of this method can be controlled by the size or concentration of the nonmagnetic bead, or by the dimension of the trapping well. (author)
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Energy Technology Data Exchange (ETDEWEB)
Hetényi, Anasztázia [University of Szeged, Department of Medical Chemistry (Hungary); Hegedűs, Zsófia [University of Szeged, SZTE-MTA Lendület Foldamer Research Group, Institute of Pharmaceutical Analysis Department (Hungary); Fajka-Boja, Roberta; Monostori, Éva [Biological Research Center of the Hungarian Academy of Sciences, Lymphocyte Signal Transduction Laboratory, Institute of Genetics (Hungary); Kövér, Katalin E. [University of Debrecen, Department of Inorganic and Analytical Chemistry (Hungary); Martinek, Tamás A., E-mail: martinek@pharm.u-szeged.hu [University of Szeged, SZTE-MTA Lendület Foldamer Research Group, Institute of Pharmaceutical Analysis Department (Hungary)
2016-12-15
Fragment-based drug design has been successfully applied to challenging targets where the detection of the weak protein–ligand interactions is a key element. {sup 1}H saturation transfer difference (STD) NMR spectroscopy is a powerful technique for this work but it requires pure homogeneous proteins as targets. Monoclonal antibody (mAb)-relayed {sup 15}N-GS STD spectroscopy has been developed to resolve the problem of protein mixtures and impure proteins. A {sup 15}N-labelled target-specific mAb is selectively irradiated and the saturation is relayed through the target to the ligand. Tests on the anti-Gal-1 mAb/Gal-1/lactose system showed that the approach is experimentally feasible in a reasonable time frame. This method allows detection and identification of binding molecules directly from a protein mixture in a multicomponent system.
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Directory of Open Access Journals (Sweden)
Jinhong Wang
2017-07-01
Full Text Available In this article, we propose a novel detection method for underwater moving targets by detecting their extremely low frequency (ELF emissions with inductive sensors. The ELF field source of the targets is modeled by a horizontal electric dipole at distances more than several times of the targets’ length. The formulas for the fields produced in air are derived with a three-layer model (air, seawater and seafloor and are evaluated with a complementary numerical integration technique. A proof of concept measurement is presented. The ELF emissions from a surface ship were detected by inductive electronic and magnetic sensors as the ship was leaving a harbor. ELF signals are of substantial strength and have typical characteristic of harmonic line spectrum, and the fundamental frequency has a direct relationship with the ship’s speed. Due to the high sensitivity and low noise level of our sensors, it is capable of resolving weak ELF signals at long distance. In our experiment, a detection distance of 1300 m from the surface ship above the sea surface was realized, which shows that this method would be an appealing complement to the usual acoustic detection and magnetic anomaly detection capability.
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Detection of attack-targeted scans from the Apache HTTP Server access logs
Directory of Open Access Journals (Sweden)
Merve Baş Seyyar
2018-01-01
Full Text Available A web application could be visited for different purposes. It is possible for a web site to be visited by a regular user as a normal (natural visit, to be viewed by crawlers, bots, spiders, etc. for indexing purposes, lastly to be exploratory scanned by malicious users prior to an attack. An attack targeted web scan can be viewed as a phase of a potential attack and can lead to more attack detection as compared to traditional detection methods. In this work, we propose a method to detect attack-oriented scans and to distinguish them from other types of visits. In this context, we use access log files of Apache (or ISS web servers and try to determine attack situations through examination of the past data. In addition to web scan detections, we insert a rule set to detect SQL Injection and XSS attacks. Our approach has been applied on sample data sets and results have been analyzed in terms of performance measures to compare our method and other commonly used detection techniques. Furthermore, various tests have been made on log samples from real systems. Lastly, several suggestions about further development have been also discussed.
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Goldman, Johnathan M; Zhang, Li Ang; Manna, Arunava; Armitage, Bruce A; Ly, Danith H; Schneider, James W
2013-07-08
Hybridization analysis of short DNA and RNA targets presents many challenges for detection. The commonly employed sandwich hybridization approach cannot be implemented for these short targets due to insufficient probe-target binding strengths for unmodified DNA probes. Here, we present a method capable of rapid and stable sandwich hybridization detection for 22 nucleotide DNA and RNA targets. Stable hybridization is achieved using an n-alkylated, polyethylene glycol γ-carbon modified peptide nucleic acid (γPNA) amphiphile. The γPNA's exceptionally high affinity enables stable hybridization of a second DNA-based probe to the remaining bases of the short target. Upon hybridization of both probes, an electrophoretic mobility shift is measured via interaction of the n-alkane modification on the γPNA with capillary electrophoresis running buffer containing nonionic surfactant micelles. We find that sandwich hybridization of both probes is stable under multiple binding configurations and demonstrate single base mismatch discrimination. The binding strength of both probes is also stabilized via coaxial stacking on adjacent hybridization to targets. We conclude with a discussion on the implementation of the proposed sandwich hybridization assay as a high-throughput microRNA detection method.
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Oldenburg, Cor; Schoon, Adee; Heitkönig, I.M.A.
2016-01-01
Wildlife detection dogs are required to correctly discriminate target wildlife species odor from nontarget
species odors (specificity), while enabling some degree of target odor variation (generality). Because
there is no standardized training protocol, and little knowledge on training -
Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS
Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar E.; Baker, Erin S.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco
2017-09-01
In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150-250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMS-CID-TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10-200 nM range, while simultaneously achieving discovery measurements of not initially targeted peptides as markers from the same proteins and, eventually, other proteins. [Figure not available: see fulltext.
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Ma, Qi; Yang, Dong-Rong; Xue, Bo-Xin; Wang, Cheng; Chen, Han-Bin; Dong, Yun; Wang, Cai-Shan; Shan, Yu-Xi
2017-07-01
The focus of the present study was to evaluate transrectal real-time tissue elastography (RTE)-targeted two-core biopsy coupled with peak strain index for the detection of prostate cancer (PCa) and to compare this method with 10-core systematic biopsy. A total of 141 patients were enrolled for evaluation. The diagnostic value of peak strain index was assessed using a receiver operating characteristic curve. The cancer detection rates of the two approaches and corresponding positive cores and Gleason score were compared. The cancer detection rate per core in the RTE-targeted biopsy (44%) was higher compared with that in systematic biopsy (30%). The peak strain index value of PCa was higher compared with that of the benign lesion. PCa was detected with the highest sensitivity (87.5%) and specificity (85.5%) using the threshold value of a peak strain index of ≥5.97 with an area under the curve value of 0.95. When the Gleason score was ≥7, RTE-targeted biopsy coupled with peak strain index detected 95.6% of PCa cases, but 84.4% were detected using systematic biopsy. Peak strain index as a quantitative parameter may improve the differentiation of PCa from benign lesions in the prostate peripheral zone. Transrectal RTE-targeted biopsy coupled with peak strain index may enhance the detection of clinically significant PCa, particularly when combined with systematic biopsy.
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Shulman, Gordon L.; Pope, Daniel L. W.; Astafiev, Serguei V.; McAvoy, Mark P.; Snyder, Abraham Z.; Corbetta, Maurizio
2010-01-01
Spatial selective attention is widely considered to be right hemisphere dominant. Previous functional magnetic resonance imaging (fMRI) studies, however, have reported bilateral blood-oxygenation-level-dependent (BOLD) responses in dorsal fronto-parietal regions during anticipatory shifts of attention to a location (Kastner et al., 1999; Corbetta et al., 2000; Hopfinger et al., 2000). Right-lateralized activity has mainly been reported in ventral fronto-parietal regions for shifts of attention to an unattended target stimulus (Arrington et al., 2000; Corbetta et al., 2000). However, clear conclusions cannot be drawn from these studies because hemispheric asymmetries were not assessed using direct voxel-wise comparisons of activity in left and right hemispheres. Here, we used this technique to measure hemispheric asymmetries during shifts of spatial attention evoked by a peripheral cue stimulus and during target detection at the cued location. Stimulus-driven shifts of spatial attention in both visual fields evoked right-hemisphere dominant activity in temporo-parietal junction (TPJ). Target detection at the attended location produced a more widespread right hemisphere dominance in frontal, parietal, and temporal cortex, including the TPJ region asymmetrically activated during shifts of spatial attention. However, hemispheric asymmetries were not observed during either shifts of attention or target detection in the dorsal fronto-parietal regions (anterior precuneus, medial intraparietal sulcus, frontal eye fields) that showed the most robust activations for shifts of attention. Therefore, right hemisphere dominance during stimulus-driven shifts of spatial attention and target detection reflects asymmetries in cortical regions that are largely distinct from the dorsal fronto-parietal network involved in the control of selective attention. PMID:20219998
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Detection of Subpixel Submerged Mine-Like Targets in WorldView-2 Multispectral Imagery
2012-09-01
exploit the capabilities of the technology already in use, such as the WorldView-2. This is a complicated issue, as any capability has to be able to...Applied Science and Analysis Inc. 91 Mayer, R., & Bucholtz, F. (2003). Object detection by using “ whitening / dewhitening” to transform target
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Antagonism pattern detection between microRNA and target expression in Ewing's sarcoma.
Directory of Open Access Journals (Sweden)
Loredana Martignetti
Full Text Available MicroRNAs (miRNAs have emerged as fundamental regulators that silence gene expression at the post-transcriptional and translational levels. The identification of their targets is a major challenge to elucidate the regulated biological processes. The overall effect of miRNA is reflected on target mRNA expression, suggesting the design of new investigative methods based on high-throughput experimental data such as miRNA and transcriptome profiles. We propose a novel statistical measure of non-linear dependence between miRNA and mRNA expression, in order to infer miRNA-target interactions. This approach, which we name antagonism pattern detection, is based on the statistical recognition of a triangular-shaped pattern in miRNA-target expression profiles. This pattern is observed in miRNA-target expression measurements since their simultaneously elevated expression is statistically under-represented in the case of miRNA silencing effect. The proposed method enables miRNA target prediction to strongly rely on cellular context and physiological conditions reflected by expression data. The procedure has been assessed on synthetic datasets and tested on a set of real positive controls. Then it has been applied to analyze expression data from Ewing's sarcoma patients. The antagonism relationship is evaluated as a good indicator of real miRNA-target biological interaction. The predicted targets are consistently enriched for miRNA binding site motifs in their 3'UTR. Moreover, we reveal sets of predicted targets for each miRNA sharing important biological function. The procedure allows us to infer crucial miRNA regulators and their potential targets in Ewing's sarcoma disease. It can be considered as a valid statistical approach to discover new insights in the miRNA regulatory mechanisms.
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Directory of Open Access Journals (Sweden)
Yung Hsiang eKao
2014-02-01
Full Text Available High-resolution yttrium-90 (90Y imaging of post-radioembolization microsphere biodistribution may be achieved by conventional positron emission tomography with integrated computed tomography (PET/CT scanners that have time-of-flight capability. However, reconstructed 90Y PET/CT images have high background noise, making non-target activity detection technically challenging. This educational article describes our image assessment technique for non-target activity detection by 90Y PET/CT which qualitatively overcomes the problem of background noise. We present selected case examples of non-target activity in untargeted liver, stomach, gallbladder, chest wall and kidney, supported by angiography and 90Y bremsstrahlung single photon emission computed tomography with integrated computed tomography (SPECT/CT or technetium-99m macroaggregated albumin SPECT/CT.
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Directory of Open Access Journals (Sweden)
Mabruka H. Tarhoni
2011-10-01
Full Text Available Organophosphorus (OP compounds are a diverse chemical group that includes nerve agents and pesticides. They share a common chemical signature that facilitates their binding and adduction of acetylcholinesterase (AChE within nerve synapses to induce cholinergic toxicity. However, this group diversity results in non-uniform binding and inactivation of other secondary protein targets, some of which may be adducted and protein activity influenced, even when only a relatively minor portion of tissue AChE is inhibited. The determination of individual OP protein binding targets has been hampered by the sensitivity of methods of detection and quantification of protein-pesticide adducts. We have overcome this limitation by the employment of a microchannel plate (MCP autoradiographic detector to monitor a radiolabelled OP tracer compound. We preincubated rat thymus tissue in vitro with the OP pesticides, azamethiphos-oxon, chlorfenvinphos-oxon, chlorpyrifos-oxon, diazinon-oxon, and malaoxon, and then subsequently radiolabelled the free OP binding sites remaining with 3H-diisopropylfluorophosphate (3H-DFP. Proteins adducted by OP pesticides were detected as a reduction in 3H-DFP radiolabelling after protein separation by one dimensional polyacrylamide gel electrophoresis and quantitative digital autoradiography using the MCP imager. Thymus tissue proteins of molecular weights ~28 kDa, 59 kDa, 66 kDa, and 82 kDa displayed responsiveness to adduction by this panel of pesticides. The 59 kDa protein target (previously putatively identified as carboxylesterase I was only significantly adducted by chlorfenvinphos-oxon (p < 0.001, chlorpyrifos-oxon (p < 0.0001, and diazinon-oxon (p < 0.01, the 66 kDa protein target (previously identified as serum albumin similarly only adducted by the same three pesticides (p < 0.0001, (p < 0.001, and (p < 0.01, and the 82 kDa protein target (previously identified as acyl peptide hydrolase only adducted by chlorpyrifos-oxon (p
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Duong, Tuan A.; Duong, Nghi; Le, Duong
2017-01-01
In this paper, we present an integration technique using a bio-inspired, control-based visual and olfactory receptor system to search for elusive targets in practical environments where the targets cannot be seen obviously by either sensory data. Bio-inspired Visual System is based on a modeling of extended visual pathway which consists of saccadic eye movements and visual pathway (vertebrate retina, lateral geniculate nucleus and visual cortex) to enable powerful target detections of noisy, partial, incomplete visual data. Olfactory receptor algorithm, namely spatial invariant independent component analysis, that was developed based on data of old factory receptor-electronic nose (enose) of Caltech, is adopted to enable the odorant target detection in an unknown environment. The integration of two systems is a vital approach and sets up a cornerstone for effective and low-cost of miniaturized UAVs or fly robots for future DOD and NASA missions, as well as for security systems in Internet of Things environments.
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Detection method of elastic scattering in the Coulomb interference region: scintillation target
International Nuclear Information System (INIS)
Azaiez, Hamza.
1981-01-01
Measurement of polarization in (p-p) elastic scattering in the Coulomb interference region is considered as a valid method for calibrating high energy polarized proton beams. Possibility of using a scintillation target to detect low energy recoil protons in this /t/ region has been studied by using a 4 GeV/c π - beam from CERN PS. The results obtained with a steack of thin plastic scintillators, each 1 mm thick, showed the feasibility of detecting recoil protons in a /t/ range as low a 5.10 -3 (GeV/c) 2 . This method thus confirmed experimentally can be used also to measure, using a polarized beam, polarization in Coulomb interference region [fr
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Harmonic pulsed excitation and motion detection of a vibrating reflective target.
Urban, Matthew W; Greenleaf, James F
2008-01-01
Elasticity imaging is an emerging medical imaging modality. Methods involving acoustic radiation force excitation and pulse-echo ultrasound motion detection have been investigated to assess the mechanical response of tissue. In this work new methods for dynamic radiation force excitation and motion detection are presented. The theory and model for harmonic motion detection of a vibrating reflective target are presented. The model incorporates processing of radio frequency data acquired using pulse-echo ultrasound to measure harmonic motion with amplitudes ranging from 100 to 10,000 nm. A numerical study was performed to assess the effects of different parameters on the accuracy and precision of displacement amplitude and phase estimation and showed how estimation errors could be minimized. Harmonic pulsed excitation is introduced as a multifrequency radiation force excitation method that utilizes ultrasound tonebursts repeated at a rate f(r). The radiation force, consisting of frequency components at multiples of f(r), is generated using 3.0 MHz ultrasound, and motion detection is performed simultaneously with 9.0 MHz pulse-echo ultrasound. A parameterized experimental analysis showed that displacement can be measured with small errors for motion with amplitudes as low as 100 nm. The parameterized numerical and experimental analyses provide insight into how to optimize acquisition parameters to minimize measurement errors.
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1995-06-01
applied to analyze numerous experimental tasks (Macmillan and Creelman , 1991). One of these tasks, target detection, is the subject research. In...between each associated pair of false alarm rate and hit rate z-scores is d’ for the bias level associated with the pairing (Macmillan and Creelman , 1991...unequal variance in normal distributions (Macmillan and Creelman , 1991). 61 1966). It is described in detail for the interested reader by Green and
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Automatic detection of the unknown number point targets in FMICW radar signals
Czech Academy of Sciences Publication Activity Database
Rejfek, L.; Mošna, Zbyšek; Beran, L.; Fišer, O.; Dobrovolný, M.
2017-01-01
Roč. 4, č. 11 (2017), s. 116-120 ISSN 2313-626X R&D Projects: GA ČR(CZ) GA15-24688S Institutional support: RVO:68378289 Keywords : FMICW radar * 2D FFT * signal filtration * taraget detection * target parameter estimation Subject RIV: DG - Athmosphere Sciences, Meteorology OBOR OECD: Meteorology and atmospheric sciences http://science-gate.com/IJAAS/Articles/2017-4-11/18%202017-4-11-pp.116-120.pdf
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Generic detection of poleroviruses using an RT-PCR assay targeting the RdRp coding sequence.
Lotos, Leonidas; Efthimiou, Konstantinos; Maliogka, Varvara I; Katis, Nikolaos I
2014-03-01
In this study a two-step RT-PCR assay was developed for the generic detection of poleroviruses. The RdRp coding region was selected as the primers' target, since it differs significantly from that of other members in the family Luteoviridae and its sequence can be more informative than other regions in the viral genome. Species specific RT-PCR assays targeting the same region were also developed for the detection of the six most widespread poleroviral species (Beet mild yellowing virus, Beet western yellows virus, Cucurbit aphid-borne virus, Carrot red leaf virus, Potato leafroll virus and Turnip yellows virus) in Greece and the collection of isolates. These isolates along with other characterized ones were used for the evaluation of the generic PCR's detection range. The developed assay efficiently amplified a 593bp RdRp fragment from 46 isolates of 10 different Polerovirus species. Phylogenetic analysis using the generic PCR's amplicon sequence showed that although it cannot accurately infer evolutionary relationships within the genus it can differentiate poleroviruses at the species level. Overall, the described generic assay could be applied for the reliable detection of Polerovirus infections and, in combination with the specific PCRs, for the identification of new and uncharacterized species in the genus. Copyright © 2013 Elsevier B.V. All rights reserved.
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Qian, Zhaosheng; Shan, Xiaoyue; Chai, Lujing; Chen, Jianrong; Feng, Hui
2014-12-01
Simultaneous detection of multiple DNA targets was achieved based on a biocompatible graphene quantum dots (GQDs) and carbon nanotubes (CNTs) platform through spontaneous assembly between dual-color GQD-based probes and CNTs and subsequently self-recognition between DNA probes and targets. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Detection of Accelerating Targets in Clutter Using a De-Chirping Technique
2014-06-01
Cubic Phase Functions By definition the Wigner -Ville distribution, W , of a signal x(n) can be written generally as W (n, ω) = ∑ m x(n+m/2)x∗(n−m/2)e−jωm...which is known as the Radon- Wigner transform (RWT), as discussed by Wood [3] and Lohmann [16]. Similarly, the Ambiguity Function , AF, for the signal...the integrated cubic phase functions , at least in the case of single target detection with the linear fre- quency modulated (LFM) waveform. This is
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Target detection and driving behaviour measurements in a driving simulator at mesopic light levels
Alferdinck, J.W.A.M.
2006-01-01
During night-time driving hazardous objects often appear at mesopic light levels, which are typically measured using light meters with a spectral sensitivity that is only valid for photopic light levels. In order to develop suitable mesopic models a target detection experiment was performed in a
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Design, Synthesis and in Combo Antidiabetic Bioevaluation of Multitarget Phenylpropanoic Acids
Directory of Open Access Journals (Sweden)
Blanca Colín-Lozano
2018-02-01
Full Text Available We have synthesized a small series of five 3-[4-arylmethoxyphenyl]propanoic acids employing an easy and short synthetic pathway. The compounds were tested in vitro against a set of four protein targets identified as key elements in diabetes: G protein-coupled receptor 40 (GPR40, aldose reductase (AKR1B1, peroxisome proliferator-activated receptor gama (PPARγ and solute carrier family 2 (facilitated glucose transporter, member 4 (GLUT-4. Compound 1 displayed an EC50 value of 0.075 μM against GPR40 and was an AKR1B1 inhibitor, showing IC50 = 7.4 μM. Compounds 2 and 3 act as slightly AKR1B1 inhibitors, potent GPR40 agonists and showed an increase of 2 to 4-times in the mRNA expression of PPARγ, as well as the GLUT-4 levels. Docking studies were conducted in order to explain the polypharmacological mode of action and the interaction binding mode of the most active molecules on these targets, showing several coincidences with co-crystal ligands. Compounds 1–3 were tested in vivo at an explorative 100 mg/kg dose, being 2 and 3 orally actives, reducing glucose levels in a non-insulin-dependent diabetes mice model. Compounds 2 and 3 displayed robust in vitro potency and in vivo efficacy, and could be considered as promising multitarget antidiabetic candidates. This is the first report of a single molecule with these four polypharmacological target action.
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Hotspots ampersand other hidden targets: Probability of detection, number, frequency and area
International Nuclear Information System (INIS)
Vita, C.L.
1994-01-01
Concepts and equations are presented for making probability-based estimates of the detection probability, and the number, frequency, and area of hidden targets, including hotspots, at a given site. Targets include hotspots, which are areas of extreme or particular contamination, and any object or feature that is hidden from direct visual observation--including buried objects and geologic or hydrologic details or anomalies. Being Bayesian, results are fundamentally consistent with observational methods. Results are tools for planning or interpreting exploration programs used in site investigation or characterization, remedial design, construction, or compliance monitoring, including site closure. Used skillfully and creatively, these tools can help streamline and expedite environmental restoration, reducing time and cost, making site exploration cost-effective, and providing acceptable risk at minimum cost. 14 refs., 4 figs
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Kalash, Leen; Val, Cristina; Azuaje, Jhonny; Loza, María I; Svensson, Fredrik; Zoufir, Azedine; Mervin, Lewis; Ladds, Graham; Brea, José; Glen, Robert; Sotelo, Eddy; Bender, Andreas
2017-12-30
Compounds designed to display polypharmacology may have utility in treating complex diseases, where activity at multiple targets is required to produce a clinical effect. In particular, suitable compounds may be useful in treating neurodegenerative diseases by promoting neuronal survival in a synergistic manner via their multi-target activity at the adenosine A 1 and A 2A receptors (A 1 R and A 2A R) and phosphodiesterase 10A (PDE10A), which modulate intracellular cAMP levels. Hence, in this work we describe a computational method for the design of synthetically feasible ligands that bind to A 1 and A 2A receptors and inhibit phosphodiesterase 10A (PDE10A), involving a retrosynthetic approach employing in silico target prediction and docking, which may be generally applicable to multi-target compound design at several target classes. This approach has identified 2-aminopyridine-3-carbonitriles as the first multi-target ligands at A 1 R, A 2A R and PDE10A, by showing agreement between the ligand and structure based predictions at these targets. The series were synthesized via an efficient one-pot scheme and validated pharmacologically as A 1 R/A 2A R-PDE10A ligands, with IC 50 values of 2.4-10.0 μM at PDE10A and K i values of 34-294 nM at A 1 R and/or A 2A R. Furthermore, selectivity profiling of the synthesized 2-amino-pyridin-3-carbonitriles against other subtypes of both protein families showed that the multi-target ligand 8 exhibited a minimum of twofold selectivity over all tested off-targets. In addition, both compounds 8 and 16 exhibited the desired multi-target profile, which could be considered for further functional efficacy assessment, analog modification for the improvement of selectivity towards A 1 R, A 2A R and PDE10A collectively, and evaluation of their potential synergy in modulating cAMP levels.
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Directory of Open Access Journals (Sweden)
A. V. Karman
2017-01-01
Full Text Available Оbjective: to define the approach to the management of patients with the detected ASAP area.Materials and methods. In the time period from 2012 through 2015, 494 patients with previously negative biopsy and remaining suspicion of prostate cancer (PCa were examined. The patients underwent repeat 24-core multifocal prostate biopsy with taking additional tissue samples from suspicious areas detected by multiparametric magnetic resonance imaging and transrectal ultrasound. An isolated ASAP area was found in 127 (25. 7 % of the 494 examined men. All of them were offered to perform repeat target transrectal biopsy of this area. Targeted transrectal ultrasound guided biopsy of the ASAP area was performed in 56 (44.1 % of the 127 patients, 53 of them being included in the final analysis.Results. PCa was diagnosed in 14 (26.4 % of the 53 patients, their mean age being 64.4 ± 6.9 years. The average level of prostate-specific antigen (PSA in PCa patients was 6.8 ± 3.0 ng/ml, in those with benign lesions – 9.3 ± 6.5 ng/ml; the percentage ratio of free/total PSA with PCa was 16.2 ± 7,8 %, with benign lesions – 23.3 ± 7.7 %; PSA density in PCa patients was 0.14 ± 0.07 ng/ml/cm3, in those with benign lesions – 0.15 ± 0.12 ng/ml/cm3. Therefore, with ASAP area being detected in repeat prostate biopsy samples, it is advisable that targeted extended biopsy of this area be performed.
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Pu, Yang
Optical spectroscopy and imaging using near-infrared (NIR) light provides powerful tools for non-invasive detection of cancer in tissue. Optical techniques are capable of quantitative reconstructions maps of tissue absorption and scattering properties, thus can map in vivo the differences in the content of certain marker chromophores and/or fluorophores in normal and cancerous tissues (for example: water, tryptophan, collagen and NADH contents). Potential clinical applications of optical spectroscopy and imaging include functional tumor detection and photothermal therapeutics. Optical spectroscopy and imaging apply contrasts from intrinsic tissue chromophores such as water, collagen and NADH, and extrinsic optical contrast agents such as Indocyanine Green (ICG) to distinguish disease tissue from the normal one. Fluorescence spectroscopy and imaging also gives high sensitivity and specificity for biomedical diagnosis. Recent developments on specific-targeting fluorophores such as small receptor-targeted dye-peptide conjugate contrast agent offer high contrast between normal and cancerous tissues hence provide promising future for early tumour detection. This thesis focus on a study to distinguish the cancerous prostate tissue from the normal prostate tissues with enhancement of specific receptor-targeted prostate cancer contrast agents using optical spectroscopy and imaging techniques. The scattering and absorption coefficients, and anisotropy factor of cancerous and normal prostate tissues were investigated first as the basis for the biomedical diagnostic and optical imaging. Understanding the receptors over-expressed prostate cancer cells and molecular target mechanism of ligand, two small ICG-derivative dye-peptides, namely Cypate-Bombesin Peptide Analogue Conjugate (Cybesin) and Cypate-Octreotate Peptide Conjugate (Cytate), were applied to study their clinical potential for human prostate cancer detection. In this work, the steady-state and time
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Zhang, Decai; Wang, Weijia; Dong, Qian; Huang, Yunxiu; Wen, Dongmei; Mu, Yuejing; Yuan, Yong
2017-12-21
An isothermal colorimetric method is described for amplified detection of the CaMV 35S promoter sequence in genetically modified organism (GMO). It is based on (a) target DNA-triggered unlabeled molecular beacon (UMB) termini binding, and (b) exonuclease III (Exo III)-assisted target recycling, and (c) hemin/G-quadruplex (DNAzyme) based signal amplification. The specific binding of target to the G-quadruplex sequence-locked UMB triggers the digestion of Exo III. This, in turn, releases an active G-quadruplex segment and target DNA for successive hybridization and cleavage. The Exo III impellent recycling of targets produces numerous G-quadruplex sequences. These further associate with hemin to form DNAzymes and hence will catalyze H 2 O 2 -mediated oxidation of the chromogenic enzyme substrate ABTS 2- causing the formation of a green colored product. This finding enables a sensitive colorimetric determination of GMO DNA (at an analytical wavelength of 420 nm) at concentrations as low as 0.23 nM. By taking advantage of isothermal incubation, this method does not require sophisticated equipment or complicated syntheses. Analyses can be performed within 90 min. The method also discriminates single base mismatches. In our perception, it has a wide scope in that it may be applied to the detection of many other GMOs. Graphical abstract An isothermal and sensitive colorimetric method is described for amplified detection of CaMV 35S promoter sequence in genetically modified organism (GMO). It is based on target DNA-triggered molecular beacon (UMB) termini-binding and exonuclease III assisted target recycling, and on hemin/G-quadruplex (DNAzyme) signal amplification.
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Integrated detection, estimation, and guidance in pursuit of a maneuvering target
Dionne, Dany
The thesis focuses on efficient solutions of non-cooperative pursuit-evasion games with imperfect information on the state of the system. This problem is important in the context of interception of future maneuverable ballistic missiles. However, the theoretical developments are expected to find application to a broad class of hybrid control and estimation problems in industry. The validity of the results is nevertheless confirmed using a benchmark problem in the area of terminal guidance. A specific interception scenario between an incoming target with no information and a single interceptor missile with noisy measurements is analyzed in the form of a linear hybrid system subject to additive abrupt changes. The general research is aimed to achieve improved homing accuracy by integrating ideas from detection theory, state estimation theory and guidance. The results achieved can be summarized as follows. (i) Two novel maneuver detectors are developed to diagnose abrupt changes in a class of hybrid systems (detection and isolation of evasive maneuvers): a new implementation of the GLR detector and the novel adaptive- H0 GLR detector. (ii) Two novel state estimators for target tracking are derived using the novel maneuver detectors. The state estimators employ parameterized family of functions to described possible evasive maneuvers. (iii) A novel adaptive Bayesian multiple model predictor of the ballistic miss is developed which employs semi-Markov models and ideas from detection theory. (iv) A novel integrated estimation and guidance scheme that significantly improves the homing accuracy is also presented. The integrated scheme employs banks of estimators and guidance laws, a maneuver detector, and an on-line governor; the scheme is adaptive with respect to the uncertainty affecting the probability density function of the filtered state. (v) A novel discretization technique for the family of continuous-time, game theoretic, bang-bang guidance laws is introduced. The
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Detection of Pathogenic Biofilms with Bacterial Amyloid Targeting Fluorescent Probe, CDy11
DEFF Research Database (Denmark)
Kim, Jun Young; Sahu, Srikanta; Yau, Yin Hoe
2016-01-01
Bacterial biofilms are responsible for a wide range of persistent infections. In the clinic, diagnosis of biofilm-associated infections relies heavily on culturing methods, which fail to detect nonculturable bacteria. Identification of novel fluorescent probes for biofilm imaging will greatly...... facilitate diagnosis of pathogenic bacterial infection. Herein, we report a novel fluorescent probe, CDy11 (compound of designation yellow 11), which targets amyloid in the Pseudomonas aeruginosa biofilm matrix through a diversity oriented fluorescent library approach (DOFLA). CDy11 was further demonstrated...
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Directory of Open Access Journals (Sweden)
Melissa R Beck
Full Text Available Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1 different time intervals between a response and the next target; and 2 possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1 and target discrimination (Experiment 2 were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations.
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2016-09-07
sequences of the target mRNA, and a double stranded stem at the 5′ end that forms a stem -loop to function as a forceps to stabilize the secondary...E-mjournal homepage: www.elsevier.com/locate/bbrepDetection of siRNA-mediated target mRNA cleavage activities in human cells by a novel stem -loop...challenges for the accurate and efficient detection and verification of cleavage sites on target mRNAs. Here we used a sensitive stem -loop array reverse
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DEFF Research Database (Denmark)
Tian, Bo; Ma, Jing; Qiu, Zhen
2017-01-01
-efficiency, and potential for bioresponsive multiplexing. Herein, we demonstrate a sensitive and rapid miRNA detection method based on optomagnetic read-out, duplex-specific nuclease (DSN)-assisted target recycling, and the use of multilayer core-satellite magnetic superstructures. Triggered by the presence of target mi...
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Yin, Gang; Zhang, Yingtang; Fan, Hongbo; Ren, Guoquan; Li, Zhining
2017-12-01
We have developed a method for automatically detecting UXO-like targets based on magnetic anomaly inversion and self-adaptive fuzzy c-means clustering. Magnetic anomaly inversion methods are used to estimate the initial locations of multiple UXO-like sources. Although these initial locations have some errors with respect to the real positions, they form dense clouds around the actual positions of the magnetic sources. Then we use the self-adaptive fuzzy c-means clustering algorithm to cluster these initial locations. The estimated number of cluster centroids represents the number of targets and the cluster centroids are regarded as the locations of magnetic targets. Effectiveness of the method has been demonstrated using synthetic datasets. Computational results show that the proposed method can be applied to the case of several UXO-like targets that are randomly scattered within in a confined, shallow subsurface, volume. A field test was carried out to test the validity of the proposed method and the experimental results show that the prearranged magnets can be detected unambiguously and located precisely.
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Marandet, Christian; Roux, Philippe; Nicolas, Barbara; Mars, Jérôme
2011-01-01
This study demonstrates experimentally at the laboratory scale the detection and localization of a wavelength-sized target in a shallow ultrasonic waveguide between two source-receiver arrays at 3 MHz. In the framework of the acoustic barrier problem, at the 1/1000 scale, the waveguide represents a 1.1-km-long, 52-m-deep ocean acoustic channel in the kilohertz frequency range. The two coplanar arrays record in the time-domain the transfer matrix of the waveguide between each pair of source-receiver transducers. Invoking the reciprocity principle, a time-domain double-beamforming algorithm is simultaneously performed on the source and receiver arrays. This array processing projects the multireverberated acoustic echoes into an equivalent set of eigenrays, which are defined by their launch and arrival angles. Comparison is made between the intensity of each eigenray without and with a target for detection in the waveguide. Localization is performed through tomography inversion of the acoustic impedance of the target, using all of the eigenrays extracted from double beamforming. The use of the diffraction-based sensitivity kernel for each eigenray provides both the localization and the signature of the target. Experimental results are shown in the presence of surface waves, and methodological issues are discussed for detection and localization.
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Alteration mineral mapping in inaccessible regions using target detection algorithms to ASTER data
International Nuclear Information System (INIS)
Pour, A B; Hashim, M; Park, Y
2017-01-01
In this study, the applications of target detection algorithms such as Constrained Energy Minimization (CEM), Orthogonal Subspace Projection (OSP) and Adaptive Coherence Estimator (ACE) to shortwave infrared bands of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data was investigated to extract geological information for alteration mineral mapping in poorly exposed lithologies in inaccessible domains. The Oscar II coast area north-eastern Graham Land, Antarctic Peninsula (AP) was selected in this study to conduct a satellite-based remote sensing mapping technique. It is an inaccessible region due to the remoteness of many rock exposures and the necessity to travel over sever mountainous and glacier-cover terrains for geological field mapping and sample collection. Fractional abundance of alteration minerals such as muscovite, kaolinite, illite, montmorillonite, epidote, chlorite and biotite were identified in alteration zones using CEM, OSP and ACE algorithms in poorly mapped and unmapped zones at district scale for the Oscar II coast area. The results of this investigation demonstrated the applicability of ASTER shortwave infrared spectral data for lithological and alteration mineral mapping in poorly exposed lithologies and inaccessible regions, particularly using the image processing algorithms that are capable to detect sub-pixel targets in the remotely sensed images, where no prior information is available. (paper)
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Gong, Xue; Li, Jinfu; Zhou, Wenjiao; Xiang, Yun; Yuan, Ruo; Chai, Yaqin
2014-05-30
Based on target recycling amplification, the development of a new label-free, simple and sensitive colorimetric detection method for ATP by using un-modified aptamers and DNAzymes is described. The association of the model target molecules (ATP) with the corresponding aptamers of the dsDNA probes leads to the release of the G-quadruplex sequences. The ATP-bound aptamers can be further degraded by Exonuclease III to release ATP, which can again bind the aptamers of the dsDNA probes to initiate the target recycling amplification process. Due to this target recycling amplification, the amount of the released G-quadruplex sequences is significantly enhanced. Subsequently, these G-quadruplex sequences bind hemin to form numerous peroxidase mimicking DNAzymes, which cause substantially intensified color change of the probe solution for highly sensitive colorimetric detection of ATP down to the sub-nanomolar (0.33nM) level. Our method is highly selective toward ATP against other control molecules and can be performed in one single homogeneous solution, which makes our sensing approach hold great potential for sensitive colorimetric detection of other small molecules and proteins. Copyright © 2014 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
R. P. Perry
2008-03-01
Full Text Available SAR images experience significant range walk and, without some form of motion compensation, can be quite blurred. The MITRE-developed Keystone formatting simultaneously and automatically compensates for range walk due to the radial velocity component of each moving target, independent of the number of targets or the value of each target's radial velocity with respect to the ground. Target radial motion also causes moving targets in synthetic aperture radar images to appear at locations offset from their true instantaneous locations on the ground. In a multichannel radar, the interferometric phase values associated with all nonmoving points on the ground appear as a continuum of phase differences while the moving targets appear as interferometric phase discontinuities. By multiple threshold comparisons and grouping of pixels within the intensity and the phase images, we show that it is possible to reliably detect and accurately georegister moving targets within short-duration SAR (QuickSAR images.
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Energy Technology Data Exchange (ETDEWEB)
Lee, C; Han, M; Baek, J [Yonsei University, Incheon (Korea, Republic of)
2015-06-15
Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR{sup 2} ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201
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International Nuclear Information System (INIS)
Lee, C; Han, M; Baek, J
2015-01-01
Purpose: To investigate the detectability of a small target for different slice direction of a volumetric cone beam CT image and its impact on dose reduction. Methods: Analytic projection data of a sphere object (1 mm diameter, 0.2/cm attenuation coefficient) were generated and reconstructed by FDK algorithm. In this work, we compared the detectability of the small target from four different backprojection Methods: hanning weighted ramp filter with linear interpolation (RECON 1), hanning weighted ramp filter with Fourier interpolation (RECON2), ramp filter with linear interpolation (RECON 3), and ramp filter with Fourier interpolation (RECON4), respectively. For noise simulation, 200 photons per measurement were used, and the noise only data were reconstructed using FDK algorithm. For each reconstructed volume, axial and coronal slice were extracted and detection-SNR was calculated using channelized Hotelling observer (CHO) with dense difference-of-Gaussian (D-DOG) channels. Results: Detection-SNR of coronal images varies for different backprojection methods, while axial images have a similar detection-SNR. Detection-SNR 2 ratios of coronal and axial images in RECON1 and RECON2 are 1.33 and 1.15, implying that the coronal image has a better detectability than axial image. In other words, using coronal slices for the small target detection can reduce the patient dose about 33% and 15% compared to using axial slices in RECON 1 and RECON 2. Conclusion: In this work, we investigated slice direction dependent detectability of a volumetric cone beam CT image. RECON 1 and RECON 2 produced the highest detection-SNR, with better detectability in coronal slices. These results indicate that it is more beneficial to use coronal slice to improve detectability of a small target in a volumetric cone beam CT image. This research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea, under the IT Consilience Creative Program (NIPA-2014-H0201
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Shokri, Ehsan; Hosseini, Morteza; Davari, Mehdi D.; Ganjali, Mohammad R.; Peppelenbosch, Maikel P.; Rezaee, Farhad
2017-04-01
A modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol- modified probes, each of which specifically binds at one half of the target introduced SH groups at both ends of dsDNA. Continuous disulfide bond formation at 3‧ and 5‧ terminals of targets leads to the self-assembly of dsDNAs into the sulfur- rich and flexible products with different lengths. These products have a high affinity for the surface of Au-NPs and efficiently protect the surface from salt induced aggregation. To evaluate the assay efficacy, a small part of the citrus tristeza virus (CTV) genome was targeted, leading to a detection limit of about 5 × 10-9 mol.L-1 over a linear ranged from 20 × 10-9 to 10 × 10-7 mol.L-1. This approach also exhibits good reproducibility and recovery levels in the presence of plant total RNA or human plasma total circulating RNA extracts. Self-assembled targets can be then sensitively distinguished from non-assembled or mismatched targets after gel electrophoresis. The disulfide reaction method and integrating self-assembled DNAs/RNAs targets with bare AuNPs as a sensitive indicator provide us a powerful and simple visual detection tool for a wide range of applications.
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Meitzler, Thomas J.
The field of computer vision interacts with fields such as psychology, vision research, machine vision, psychophysics, mathematics, physics, and computer science. The focus of this thesis is new algorithms and methods for the computation of the probability of detection (Pd) of a target in a cluttered scene. The scene can be either a natural visual scene such as one sees with the naked eye (visual), or, a scene displayed on a monitor with the help of infrared sensors. The relative clutter and the temperature difference between the target and background (DeltaT) are defined and then used to calculate a relative signal -to-clutter ratio (SCR) from which the Pd is calculated for a target in a cluttered scene. It is shown how this definition can include many previous definitions of clutter and (DeltaT). Next, fuzzy and neural -fuzzy techniques are used to calculate the Pd and it is shown how these methods can give results that have a good correlation with experiment. The experimental design for actually measuring the Pd of a target by observers is described. Finally, wavelets are applied to the calculation of clutter and it is shown how this new definition of clutter based on wavelets can be used to compute the Pd of a target.
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DEFF Research Database (Denmark)
Nåbo, Lina J.; Madsen, Charlotte S.; Jensen, Knud J.
2015-01-01
Functionalized synthetic oligonucleotides are finding growing applications in research, clinical studies, and therapy. However, it is not easy to prepare them in a biocompatible and highly efficient manner. We report a new strategy to synthesize oligonucleotides with promising nucleic acid...... targeting and detection properties. We focus in particular on the pH sensitivity of these new probes and their high target specificity. For the first time, human copper(I)-binding chaperon Cox17 was applied to effectively catalyze click labeling of oligonucleotides. This was performed under ultramild...... conditions with fluorophore, peptide, and carbohydrate azide derivatives. In thermal denaturation studies, the modified probes showed specific binding to complementary DNA and RNA targets. Finally, we demonstrated the pH sensitivity of the new rhodamine-based fluorescent probes in vitro and rationalize our...
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Peng, Cheng; Wang, Pengfei; Xu, Xiaoli; Wang, Xiaofu; Wei, Wei; Chen, Xiaoyun; Xu, Junfeng
2016-01-01
As the amount of commercially available genetically modified organisms (GMOs) grows recent years, the diversity of target sequences for molecular detection techniques are eagerly needed. Considered as the gold standard for GMO analysis, the real-time PCR technology was optimized to produce a high-throughput GMO screening method. With this method we can detect 19 transgenic targets. The specificity of the assays was demonstrated to be 100 % by the specific amplification of DNA derived from reference material from 20 genetically modified crops and 4 non modified crops. Furthermore, most assays showed a very sensitive detection, reaching the limit of ten copies. The 19 assays are the most frequently used genetic elements present in GM crops and theoretically enable the screening of the known GMO described in Chinese markets. Easy to use, fast and cost efficient, this method approach fits the purpose of GMO testing laboratories.
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Directory of Open Access Journals (Sweden)
Benetode Konziase
2015-12-01
Full Text Available Here we describe the isolation and purity determination of Trypanosoma brucei (T. b. brucei candidate target proteins of artemisinin. The candidate target proteins were detected and purified from their biological source (T. b. brucei lysate using the diazirine-free biotinylated probe 5 for an affinity binding to a streptavidin-tagged resin and, subsequently, the labeled target proteins were purified by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE. We herein showed the electrophoresis gel and the immunoblotting film containing the 60-kDa trypanosomal candidate target protein of artemisinin as a single band, which was visualized on-gel by the reverse-staining method and on a Western blotting film by enhanced chemiluminescence. The data provided in this article are related to the original research article “Biotinylated probes of artemisinin with labeling affinity toward Trypanosoma brucei brucei target proteins”, by Konziase (Anal. Biochem., vol. 482, 2015, pp. 25–31. http://dx.doi.org/10.1016/j.ab.2015.04.020.
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Detection of Balamuthia mandrillaris DNA by real-time PCR targeting the RNase P gene
Directory of Open Access Journals (Sweden)
Lewin Astrid
2008-12-01
Full Text Available Abstract Background The free-living amoeba Balamuthia mandrillaris may cause fatal encephalitis both in immunocompromised and in – apparently – immunocompetent humans and other mammalian species. Rapid, specific, sensitive, and reliable detection requiring little pathogen-specific expertise is an absolute prerequisite for a successful therapy and a welcome tool for both experimental and epidemiological research. Results A real-time polymerase chain reaction assay using TaqMan® probes (real-time PCR was established specifically targeting the RNase P gene of B. mandrillaris amoebae. The assay detected at least 2 (down to 0.5 genomes of B. mandrillaris grown in axenic culture. It did not react with DNA from closely related Acanthamoeba (3 species, nor with DNA from Toxoplasma gondii, Leishmania major, Pneumocystis murina, Mycobacterium bovis (BCG, human brain, various mouse organs, or from human and murine cell lines. The assay efficiently detected B. mandrillaris DNA in spiked cell cultures, spiked murine organ homogenates, B. mandrillaris-infected mice, and CNS tissue-DNA preparations from 2 patients with proven cerebral balamuthiasis. This novel primer set was successfully combined with a published set that targets the B. mandrillaris 18S rRNA gene in a duplex real-time PCR assay to ensure maximum specificity and as a precaution against false negative results. Conclusion A real-time PCR assay for B. mandrillaris amoebae is presented, that is highly specific, sensitive, and reliable and thus suited both for diagnosis and for research.
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Directory of Open Access Journals (Sweden)
Jing Yuan
2015-12-01
Full Text Available Ebola virus (EBOV can lead to severe hemorrhagic fever with a high risk of death in humans and other primates. To guide treatment and prevent spread of the viral infection, a rapid and sensitive detection method is required for clinical samples. Here, we described and evaluated a reverse transcription loop-mediated isothermal amplification (RT-LAMP method to detect Zaire ebolavirus using the nucleoprotein gene (NP as a target sequence. Two different techniques were used, a calcein/Mn2+ complex chromogenic method and real-time turbidity monitoring. The RT-LAMP assay detected the NP target sequence with a limit of 4.56 copies/μL within 45 min under 61°C, a similar even or increase in sensitivity than that of real-time reverse transcription-polymerase chain reaction (RT-PCR. Additionally, all pseudoviral particles or non- Zaire EBOV genomes were negative for LAMP detection, indicating that the assay was highly specific for EBOV. To appraise the availability of the RT-LAMP method for use in clinical diagnosis of EBOV, of 417 blood or swab samples collected from patients with clinically suspected infections in Sierra Leone, 307 were identified for RT-LAMP-based surveillance of EBOV. Therefore, the highly specific and sensitive RT-LAMP method allows the rapid detection of EBOV, and is a suitable tool for clinical screening, diagnosis, and primary quarantine purposes.
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Przybyla, Jay; Taylor, Jeffrey; Zhou, Xuesong
2010-01-01
In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM) smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.
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Directory of Open Access Journals (Sweden)
Xuesong Zhou
2010-08-01
Full Text Available In this paper, a spatial information-theoretic model is proposed to locate sensors for detecting source-to-target patterns of special nuclear material (SNM smuggling. In order to ship the nuclear materials from a source location with SNM production to a target city, the smugglers must employ global and domestic logistics systems. This paper focuses on locating a limited set of fixed and mobile radiation sensors in a transportation network, with the intent to maximize the expected information gain and minimize the estimation error for the subsequent nuclear material detection stage. A Kalman filtering-based framework is adapted to assist the decision-maker in quantifying the network-wide information gain and SNM flow estimation accuracy.
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2016-04-25
ElectroMagnetic, Multipath propagation, Reflection-diffraction, SAR signal processing 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT SAR 18...protection, and traffic surveillance, etc. With these above reasons, we are motivated to introduce a new approach to the target detection and...coherent integrating the backscattering signal , we propose a 3D propagation model that is useful not only in explaining the mechanisms of wave
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SPIDERS: selection of spectroscopic targets using AGN candidates detected in all-sky X-ray surveys
Dwelly, T.; Salvato, M.; Merloni, A.; Brusa, M.; Buchner, J.; Anderson, S. F.; Boller, Th.; Brandt, W. N.; Budavári, T.; Clerc, N.; Coffey, D.; Del Moro, A.; Georgakakis, A.; Green, P. J.; Jin, C.; Menzel, M.-L.; Myers, A. D.; Nandra, K.; Nichol, R. C.; Ridl, J.; Schwope, A. D.; Simm, T.
2017-07-01
SPIDERS (SPectroscopic IDentification of eROSITA Sources) is a Sloan Digital Sky Survey IV (SDSS-IV) survey running in parallel to the Extended Baryon Oscillation Spectroscopic Survey (eBOSS) cosmology project. SPIDERS will obtain optical spectroscopy for large numbers of X-ray-selected active galactic nuclei (AGN) and galaxy cluster members detected in wide-area eROSITA, XMM-Newton and ROSAT surveys. We describe the methods used to choose spectroscopic targets for two sub-programmes of SPIDERS X-ray selected AGN candidates detected in the ROSAT All Sky and the XMM-Newton Slew surveys. We have exploited a Bayesian cross-matching algorithm, guided by priors based on mid-IR colour-magnitude information from the Wide-field Infrared Survey Explorer survey, to select the most probable optical counterpart to each X-ray detection. We empirically demonstrate the high fidelity of our counterpart selection method using a reference sample of bright well-localized X-ray sources collated from XMM-Newton, Chandra and Swift-XRT serendipitous catalogues, and also by examining blank-sky locations. We describe the down-selection steps which resulted in the final set of SPIDERS-AGN targets put forward for spectroscopy within the eBOSS/TDSS/SPIDERS survey, and present catalogues of these targets. We also present catalogues of ˜12 000 ROSAT and ˜1500 XMM-Newton Slew survey sources that have existing optical spectroscopy from SDSS-DR12, including the results of our visual inspections. On completion of the SPIDERS programme, we expect to have collected homogeneous spectroscopic redshift information over a footprint of ˜7500 deg2 for >85 per cent of the ROSAT and XMM-Newton Slew survey sources having optical counterparts in the magnitude range 17 < r < 22.5, producing a large and highly complete sample of bright X-ray-selected AGN suitable for statistical studies of AGN evolution and clustering.
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Rapid amplification/detection of nucleic acid targets utilizing a HDA/thin film biosensor.
Jenison, Robert; Jaeckel, Heidi; Klonoski, Joshua; Latorra, David; Wiens, Jacinta
2014-08-07
Thin film biosensors exploit a flat, optically coated silicon-based surface whereupon formation of nucleic acid hybrids are enzymatically transduced in a molecular thin film that can be detected by the unaided human eye under white light. While the limit of sensitivity for detection of nucleic acid targets is at sub-attomole levels (60 000 copies) many clinical specimens containing bacterial pathogens have much lower levels of analyte present. Herein, we describe a platform, termed HDA/thin film biosensor, which performs helicase-dependant nucleic acid amplification on a thin film biosensor surface to improve the limit of sensitivity to 10 copies of the mecA gene present in methicillin-resistant strains of Staphylococcus. As double-stranded DNA is unwound by helicase it was either bound by solution-phase DNA primers to be copied by DNA polymerase or hybridized to surface immobilized probe on the thin film biosensor surface to be detected. Herein, we show that amplification reactions on the thin film biosensor are equivalent to in standard thin wall tubes, with detection at the limit of sensitivity of the assay occurring after 30 minutes of incubation time. Further we validate the approach by detecting the presence of the mecA gene in methicillin-resistant Staphylococcus aureus (MRSA) from positive blood culture aliquots with high specificity (signal/noise ratio of 105).
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REVISED STELLAR PROPERTIES OF KEPLER TARGETS FOR THE QUARTER 1-16 TRANSIT DETECTION RUN
Energy Technology Data Exchange (ETDEWEB)
Huber, Daniel [NASA Ames Research Center, Moffett Field, CA 94035 (United States); Aguirre, Victor Silva [Stellar Astrophysics Centre, Department of Physics and Astronomy, Aarhus University, Ny Munkegade 120, DK-8000 Aarhus C (Denmark); Matthews, Jaymie M. [Department of Physics and Astronomy, University of British Columbia, Vancouver (Canada); Pinsonneault, Marc H. [Department of Astronomy, Ohio State University, OH 43210 (United States); Gaidos, Eric [Department of Geology and Geophysics, University of Hawaii at Manoa, Honolulu, HI 96822 (United States); García, Rafael A. [Laboratoire AIM, CEA/DSM-CNRS, Université Paris 7 Diderot, IRFU/SAp, Centre de Saclay, F-91191 Gif-sur-Yvette (France); Hekker, Saskia [Max-Planck-Institut für Sonnensystemforschung, Justus-von-Liebig-Weg 3, D-37077 Göttingen (Germany); Mathur, Savita [Space Science Institute, 4750 Walnut Street, Suite 205, Boulder, CO 80301 (United States); Mosser, Benoit [LESIA, CNRS, Université Pierre et Marie Curie, Université Denis, Diderot, Observatoire de Paris, F-92195 Meudon cedex (France); Torres, Guillermo [Harvard-Smithsonian Center for Astrophysics, Cambridge, MA 02138 (United States); Bastien, Fabienne A. [Department of Physics and Astronomy, Vanderbilt University, 1807 Station B, Nashville, TN 37235 (United States); Basu, Sarbani [Department of Astronomy, Yale University, New Haven, CT 06511 (United States); Bedding, Timothy R. [Sydney Institute for Astronomy (SIfA), School of Physics, University of Sydney, NSW 2006 (Australia); Chaplin, William J. [School of Physics and Astronomy, University of Birmingham, Birmingham B15 2TT (United Kingdom); Demory, Brice-Olivier [Department of Physics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Fleming, Scott W., E-mail: daniel.huber@nasa.gov [Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218 (United States); and others
2014-03-01
We present revised properties for 196,468 stars observed by the NASA Kepler mission and used in the analysis of Quarter 1-16 (Q1-Q16) data to detect and characterize transiting planets. The catalog is based on a compilation of literature values for atmospheric properties (temperature, surface gravity, and metallicity) derived from different observational techniques (photometry, spectroscopy, asteroseismology, and exoplanet transits), which were then homogeneously fitted to a grid of Dartmouth stellar isochrones. We use broadband photometry and asteroseismology to characterize 11,532 Kepler targets which were previously unclassified in the Kepler Input Catalog (KIC). We report the detection of oscillations in 2762 of these targets, classifying them as giant stars and increasing the number of known oscillating giant stars observed by Kepler by ∼20% to a total of ∼15,500 stars. Typical uncertainties in derived radii and masses are ∼40% and ∼20%, respectively, for stars with photometric constraints only, and 5%-15% and ∼10% for stars based on spectroscopy and/or asteroseismology, although these uncertainties vary strongly with spectral type and luminosity class. A comparison with the Q1-Q12 catalog shows a systematic decrease in radii of M dwarfs, while radii for K dwarfs decrease or increase depending on the Q1-Q12 provenance (KIC or Yonsei-Yale isochrones). Radii of F-G dwarfs are on average unchanged, with the exception of newly identified giants. The Q1-Q16 star properties catalog is a first step toward an improved characterization of all Kepler targets to support planet-occurrence studies.
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Rong, Weining; Chen, Xuejuan; Li, Huiping; Liu, Yani; Sheng, Xunlun
2014-06-01
To detect the disease-causing genes of 10 retinitis pigmentosa pedigrees by using exon combined target region capture sequencing chip. Pedigree investigation study. From October 2010 to December 2013, 10 RP pedigrees were recruited for this study in Ningxia Eye Hospital. All the patients and family members received complete ophthalmic examinations. DNA was abstracted from patients, family members and controls. Using exon combined target region capture sequencing chip to screen the candidate disease-causing mutations. Polymerase chain reaction (PCR) and direct sequencing were used to confirm the disease-causing mutations. Seventy patients and 23 normal family members were recruited from 10 pedigrees. Among 10 RP pedigrees, 1 was autosomal dominant pedigrees and 9 were autosomal recessive pedigrees. 7 mutations related to 5 genes of 5 pedigrees were detected. A frameshift mutation on BBS7 gene was detected in No.2 pedigree, the patients of this pedigree combined with central obesity, polydactyly and mental handicap. No.2 pedigree was diagnosed as Bardet-Biedl syndrome finally. A missense mutation was detected in No.7 and No.10 pedigrees respectively. Because the patients suffered deafness meanwhile, the final diagnosis was Usher syndrome. A missense mutation on C3 gene related to age-related macular degeneration was also detected in No. 7 pedigrees. A nonsense mutation and a missense mutation on CRB1 gene were detected in No. 1 pedigree and a splicesite mutation on PROM1 gene was detected in No. 5 pedigree. Retinitis pigmentosa is a kind of genetic eye disease with diversity clinical phenotypes. Rapid and effective genetic diagnosis technology combined with clinical characteristics analysis is helpful to improve the level of clinical diagnosis of RP.
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Li, Zhuqing; Li, Xiang; Wang, Canhua; Song, Guiwen; Pi, Liqun; Zheng, Lan; Zhang, Dabing; Yang, Litao
2017-09-27
Multiple-target plasmid DNA reference materials have been generated and utilized as good substitutes of matrix-based reference materials in the analysis of genetically modified organisms (GMOs). Herein, we report the construction of one multiple-target plasmid reference molecule, pCAN, which harbors eight GM canola event-specific sequences (RF1, RF2, MS1, MS8, Topas 19/2, Oxy235, RT73, and T45) and a partial sequence of the canola endogenous reference gene PEP. The applicability of this plasmid reference material in qualitative and quantitative PCR assays of the eight GM canola events was evaluated, including the analysis of specificity, limit of detection (LOD), limit of quantification (LOQ), and performance of pCAN in the analysis of various canola samples, etc. The LODs are 15 copies for RF2, MS1, and RT73 assays using pCAN as the calibrator and 10 genome copies for the other events. The LOQ in each event-specific real-time PCR assay is 20 copies. In quantitative real-time PCR analysis, the PCR efficiencies of all event-specific and PEP assays are between 91% and 97%, and the squared regression coefficients (R 2 ) are all higher than 0.99. The quantification bias values varied from 0.47% to 20.68% with relative standard deviation (RSD) from 1.06% to 24.61% in the quantification of simulated samples. Furthermore, 10 practical canola samples sampled from imported shipments in the port of Shanghai, China, were analyzed employing pCAN as the calibrator, and the results were comparable with those assays using commercial certified materials as the calibrator. Concluding from these results, we believe that this newly developed pCAN plasmid is one good candidate for being a plasmid DNA reference material in the detection and quantification of the eight GM canola events in routine analysis.
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Canuto, Holly C; McLachlan, Charles; Kettunen, Mikko I; Velic, Marko; Krishnan, Anant S; Neves, Andre' A; de Backer, Maaike; Hu, D-E; Hobson, Michael P; Brindle, Kevin M
2009-05-01
A targeted Gd(3+)-based contrast agent has been developed that detects tumor cell death by binding to the phosphatidylserine (PS) exposed on the plasma membrane of dying cells. Although this agent has been used to detect tumor cell death in vivo, the differences in signal intensity between treated and untreated tumors was relatively small. As cell death is often spatially heterogeneous within tumors, we investigated whether an image analysis technique that parameterizes heterogeneity could be used to increase the sensitivity of detection of this targeted contrast agent. Two-dimensional (2D) Minkowski functionals (MFs) provided an automated and reliable method for parameterization of image heterogeneity, which does not require prior assumptions about the number of regions or features in the image, and were shown to increase the sensitivity of detection of the contrast agent as compared to simple signal intensity analysis. (c) 2009 Wiley-Liss, Inc.
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A Fast Algorithm of Generalized Radon-Fourier Transform for Weak Maneuvering Target Detection
Directory of Open Access Journals (Sweden)
Weijie Xia
2016-01-01
Full Text Available The generalized Radon-Fourier transform (GRFT has been proposed to detect radar weak maneuvering targets by realizing coherent integration via jointly searching in motion parameter space. Two main drawbacks of GRFT are the heavy computational burden and the blind speed side lobes (BSSL which will cause serious false alarms. The BSSL learning-based particle swarm optimization (BPSO has been proposed before to reduce the computational burden of GRFT and solve the BSSL problem simultaneously. However, the BPSO suffers from an apparent loss in detection performance compared with GRFT. In this paper, a fast implementation algorithm of GRFT using the BSSL learning-based modified wind-driven optimization (BMWDO is proposed. In the BMWDO, the BSSL learning procedure is also used to deal with the BSSL phenomenon. Besides, the MWDO adjusts the coefficients in WDO with Levy distribution and uniform distribution, and it outperforms PSO in a noisy environment. Compared with BPSO, the proposed method can achieve better detection performance with a similar computational cost. Several numerical experiments are also provided to demonstrate the effectiveness of the proposed method.
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Towards Discovery and Targeted Peptide Biomarker Detection Using nanoESI-TIMS-TOF MS
Energy Technology Data Exchange (ETDEWEB)
Garabedian, Alyssa; Benigni, Paolo; Ramirez, Cesar; Baker, Erin M.; Liu, Tao; Smith, Richard D.; Fernandez-Lima, Francisco
2018-05-01
Abstract. In the present work, the potential of trapped ion mobility spectrometry coupled to TOF mass spectrometry (TIMS-TOF MS) for discovery and targeted monitoring of peptide biomarkers from human-in-mouse xenograft tumor tissue was evaluated. In particular, a TIMS-MS workflow was developed for the detection and quantification of peptide biomarkers using internal heavy analogs, taking advantage of the high mobility resolution (R = 150–250) prior to mass analysis. Five peptide biomarkers were separated, identified, and quantified using offline nanoESI-TIMSCID- TOF MS; the results were in good agreement with measurements using a traditional LC-ESI-MS/MS proteomics workflow. The TIMS-TOF MS analysis permitted peptide biomarker detection based on accurate mobility, mass measurements, and high sequence coverage for concentrations in the 10–200 nM range, while simultaneously achieving discovery measurements
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Hu, Yuhua; Xu, Xueqin; Liu, Qionghua; Wang, Ling; Lin, Zhenyu; Chen, Guonan
2014-09-02
A simple, ultrasensitive, and specific electrochemical biosensor was designed to determine the given DNA sequence of Bacillus subtilis by coupling target-induced strand displacement and nicking endonuclease signal amplification. The target DNA (TD, the DNA sequence from the hypervarient region of 16S rDNA of Bacillus subtilis) could be detected by the differential pulse voltammetry (DPV) in a range from 0.1 fM to 20 fM with the detection limit down to 0.08 fM at the 3s(blank) level. This electrochemical biosensor exhibits high distinction ability to single-base mismatch, double-bases mismatch, and noncomplementary DNA sequence, which may be expected to detect single-base mismatch and single nucleotide polymorphisms (SNPs). Moreover, the applicability of the designed biosensor for detecting the given DNA sequence from Bacillus subtilis was investigated. The result obtained by electrochemical method is approximately consistent with that by a real-time quantitative polymerase chain reaction detecting system (QPCR) with SYBR Green.
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Burke, Christopher J.; Catanzarite, Joseph
2017-01-01
the recovered signals can be further classified as planet candidates or false positives in the exact same manner as detections from the nominal (i.e., observed) pipeline run (Twicken et al., 2016, Thompson et al., in preparation). To date, the PLTI test has been the standard means of measuring pipeline completeness averaged over large samples of targets (Christiansen et al., 2015, 2016; Christiansen, 2017). However, since the PLTI test uses only one injection per target, it does not elucidate individual-target variations in pipeline completeness due to differences in stellar properties or astrophysical variability. Thus, we developed the FLTI test to provide a numerically efficient way to fully map individual targets and explore the performance of the pipeline in greater detail. The FLTI tests thereby allow a thorough validation of the pipeline completeness models (such as window function (Burke and Catanzarite, 2017a), detection efficiency (Burke Catanzarite, 2017b), etc.) across the spectrum of Kepler targets (i.e., various astrophysical phenomena and differences in instrumental noise). Tests during development of the FLTI capability revealed that there are significant target-to-target variations in the detection efficiency.
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International Nuclear Information System (INIS)
Orco, G. Dell; Horiike, H.; Ida, M.; Nakamura, H.
2006-01-01
In the IFMIF (International Fusion Materials Irradiation Facility) testing facility, the required high energy neutrons emission will be produced by reaction of two D + beams with a free surface liquid Lithium jet target flowing along concave back-wall at 20 m/s. The Lithium height in the experimental loop and its relevant static pressure, the high flow velocities and the presence of several devices for the flow control and the pressure reduction increase the risk of cavitation onset in the target system. Special attention has to be taken in the primary pump, in the flow straightener, in the nozzle and their interconnections where the local pressure decreases and/or velocity increases or flow separations could promote the emission of cavitation vapour bubbles. The successive bubble re-implosions, in the higher pressure liquid bulk, could activate material erosion and transportation of activated particulates. These bubbles, if emitted close to the free jet flow, could also procure hydraulic instability and disturbance of the neutron field in the D + beams-Lithium target zone. Therefore, the cavitation risk must be properly foreseen along the whole IFMIF Lithium target circuit and its occurrence at different operating condition should be also monitored by special instrumentation. ENEA, in close cooperation with JAEA, has demonstrated the capability to detect the onset of the cavitation noises in liquid Lithium, by using the ENEA patented accelerometric gauge called CASBA-2000, during hydraulic test campaigns carried-out at Osaka University Lithium facility on a straight mock-up of the IFMIF back plate target. Comparison with the Thoma' cavitation similitude criteria have also determined the critical threshold limit for the estimation of the onset. Theoretical study on the conditions of cavitations generation in the IFMIF Lithium Target Circuit were also launched between ENEA and JAEA aiming at analysing the risk of the cavitation occurrence in the Lithium flow by
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A New Methodology for 3D Target Detection in Automotive Radar Applications
Directory of Open Access Journals (Sweden)
Fabio Baselice
2016-04-01
Full Text Available Today there is a growing interest in automotive sensor monitoring systems. One of the main challenges is to make them an effective and valuable aid in dangerous situations, improving transportation safety. The main limitation of visual aid systems is that they do not produce accurate results in critical visibility conditions, such as in presence of rain, fog or smoke. Radar systems can greatly help in overcoming such limitations. In particular, imaging radar is gaining interest in the framework of Driver Assistance Systems (DAS. In this manuscript, a new methodology able to reconstruct the 3D imaged scene and to detect the presence of multiple targets within each line of sight is proposed. The technique is based on the use of Compressive Sensing (CS theory and produces the estimation of multiple targets for each line of sight, their range distance and their reflectivities. Moreover, a fast approach for 2D focus based on the FFT algorithm is proposed. After the description of the proposed methodology, different simulated case studies are reported in order to evaluate the performances of the proposed approach.
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Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor
2011-07-01
Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with ~ 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of ~ 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in ~ 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of ~ 12 nm retained bright fluorescence over an extended duration of ~ a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of ~ 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of ~ 8.2% in human peripheral blood cells (PBMCs) which are CD33low. The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.
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International Nuclear Information System (INIS)
Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor
2011-01-01
Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with ∼ 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of ∼ 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in ∼ 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of ∼ 12 nm retained bright fluorescence over an extended duration of ∼ a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of ∼ 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of ∼ 8.2% in human peripheral blood cells (PBMCs) which are CD33 low . The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.
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Energy Technology Data Exchange (ETDEWEB)
Retnakumari, Archana; Jayasimhan, Jasusri; Chandran, Parwathy; Menon, Deepthy; Nair, Shantikumar; Mony, Ullas; Koyakutty, Manzoor, E-mail: manzoork@aims.amrita.edu, E-mail: ullasmony@aims.amrita.edu [Amrita Centre for Nanoscience and Molecular Medicine, Amrita Institute of Medical Science, Cochin 682 041 (India)
2011-07-15
Protein stabilized gold nanoclusters (Au-NCs) are biocompatible, near-infrared (NIR) emitting nanosystems having a wide range of biomedical applications. Here, we report the development of a Au-NC based targeted fluorescent nano-bioprobe for the flow-cytometric detection of acute myeloid leukaemia (AML) cells. Au-NCs with {approx} 25-28 atoms showing bright red-NIR fluorescence (600-750 nm) and average size of {approx} 0.8 nm were prepared by bovine serum albumin assisted reduction-cum-stabilization in aqueous phase. The protein protected clusters were conjugated with monoclonal antibody against CD33 myeloid antigen, which is overexpressed in {approx} 99.2% of the primitive population of AML cells, as confirmed by immunophenotyping using flow cytometry. Au-NC-CD33 conjugates having average size of {approx} 12 nm retained bright fluorescence over an extended duration of {approx} a year, as the albumin protein protects Au-NCs against degradation. Nanotoxicity studies revealed excellent biocompatibility of Au-NC conjugates, as they showed no adverse effect on the cell viability and inflammatory response. Target specificity of the conjugates for detecting CD33 expressing AML cells (KG1a) in flow cytometry showed specific staining of {approx} 95.4% of leukaemia cells within 1-2 h compared to a non-specific uptake of {approx} 8.2% in human peripheral blood cells (PBMCs) which are CD33{sup low}. The confocal imaging also demonstrated the targeted uptake of CD33 conjugated Au-NCs by leukaemia cells, thus confirming the flow cytometry results. This study demonstrates that novel nano-bioprobes can be developed using protein protected fluorescent nanoclusters of Au for the molecular receptor targeted flow cytometry based detection and imaging of cancer cells.
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Sensitive targeted multiple protein quantification based on elemental detection of Quantum Dots
Energy Technology Data Exchange (ETDEWEB)
Montoro Bustos, Antonio R.; Garcia-Cortes, Marta [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain); González-Iglesias, Hector [Fundación de Investigación Oftalmológica, Instituto Oftalmológico Fernandez-Vega, Avenida Doctores Fernández-Vega, 34, Oviedo 33012 (Spain); Ruiz Encinar, Jorge, E-mail: ruizjorge@uniovi.es [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain); Costa-Fernández, José M. [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain); Coca-Prados, Miguel [Fundación de Investigación Oftalmológica, Instituto Oftalmológico Fernandez-Vega, Avenida Doctores Fernández-Vega, 34, Oviedo 33012 (Spain); Department of Ophthalmology and Visual Science, Yale University School of Medicine, New Haven, CT 06510 (United States); Sanz-Medel, Alfredo, E-mail: asm@uniovi.es [Department of Physical and Analytical Chemistry, University of Oviedo, Julián Clavería 8, Oviedo 33006 (Spain)
2015-06-16
Highlights: • Novel generic platform for multiparametric quantification of proteins. • QDs labeling and ICP-MS detection allow significant analytical signal amplification. • ICP-MS mass balances information provided an internal validation of the immunoassay. • Multiparametric determination of 5 proteins in human serum samples. • ICP-MS reduced matrix effects as compared to other conventional detection techniques. - Abstract: A generic strategy based on the use of CdSe/ZnS Quantum Dots (QDs) as elemental labels for protein quantification, using immunoassays with elemental mass spectrometry (ICP-MS), detection is presented. In this strategy, streptavidin modified QDs (QDs-SA) are bioconjugated to a biotinylated secondary antibody (b-Ab{sub 2}). After a multi-technique characterization of the synthesized generic platform (QDs-SA-b-Ab{sub 2}) it was applied to the sequential quantification of five proteins (transferrin, complement C3, apolipoprotein A1, transthyretin and apolipoprotein A4) at different concentration levels in human serum samples. It is shown how this generic strategy does only require the appropriate unlabeled primary antibody for each protein to be detected. Therefore, it introduces a way out to the need for the cumbersome and specific bioconjugation of the QDs to the corresponding specific recognition antibody for every target analyte (protein). Results obtained were validated with those obtained using UV–vis spectrophotometry and commercial ELISA Kits. As expected, ICP-MS offered one order of magnitude lower DL (0.23 fmol absolute for transferrin) than the classical spectrophotometric detection (3.2 fmol absolute). ICP-MS precision and detection limits, however turned out to be compromised by procedural blanks. The full analytical performance of the ICP-MS-based immunoassay proposed was assessed for detection of transferrin (Tf), present at the low ng mL{sup −1} range in a complex “model” synthetic matrix, where the total protein
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An N-targeting real-time PCR strategy for the accurate detection of spring viremia of carp virus.
Shao, Ling; Xiao, Yu; He, Zhengkan; Gao, Longying
2016-03-01
Spring viremia of carp virus (SVCV) is a highly pathogenic agent of several economically important Cyprinidae fish species. Currently, there are no effective vaccines or drugs for this virus, and prevention of the disease mostly relies on prompt diagnosis. Previously, nested RT-PCR and RT-qPCR detection methods based on the glycoprotein gene G have been developed. However, the high genetic diversity of the G gene seriously limits the reliability of those methods. Compared with the G gene, phylogenetic analyses indicate that the nucleoprotein gene N is more conserved. Furthermore, studies in other members of the Rhabdoviridae family reveals that their gene transcription level follows the order N>P>M>G>L, indicating that an N gene based RT-PCR should have higher sensitivity. Therefore, two pairs of primers and two corresponding probes targeting the conserved regions of the N gene were designed. RT-qPCR assays demonstrated all primers and probes could detect phylogenetically distant isolates specifically and efficiently. Moreover, in artificially infected fish, the detected copy numbers of the N gene were much higher than those of the G gene in all tissues, and both the N and G gene copy numbers were highest in the kidney and spleen. Testing in 1100 farm-raised fish also showed that the N-targeting strategy was more reliable than the G-targeting methods. The method developed in this study provides a reliable tool for the rapid diagnosis of SVCV. Copyright © 2015 Elsevier B.V. All rights reserved.
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Kaysheva, A. L.; Pleshakova, T. O.; Kopylov, A. T.; Shumov, I. D.; Iourov, I. Y.; Vorsanova, S. G.; Yurov, Y. B.; Ziborov, V. S.; Archakov, A. I.; Ivanov, Y. D.
2017-10-01
Possibility of detection of target proteins associated with development of autistic disorders in children with use of combined atomic force microscopy and mass spectrometry (AFM/MS) method is demonstrated. The proposed method is based on the combination of affine enrichment of proteins from biological samples and visualization of these proteins by AFM and MS analysis with quantitative detection of target proteins.
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Track-before-detect procedures for detection of extended object
Fan, Ling; Zhang, Xiaoling; Shi, Jun
2011-12-01
In this article, we present a particle filter (PF)-based track-before-detect (PF TBD) procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance). Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.
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Permafrost-An alternative target material for ultra-high energy neutrino detection?
International Nuclear Information System (INIS)
Nahnhauer, R.; Rostovtsev, A.A.; Tosi, D.
2008-01-01
The interest in the detection of cosmic neutrinos with energies above 10 17 eV has increased considerably in recent years. Possible target materials for in-matter arrays of ∼100 km 3 size under discussion are water, ice and rock salt. Here we propose to investigate permafrost as an additional alternative, covering ∼20% of Earth land surface and reaching down to more than 1000 m depth at certain locations. If sufficiently large attenuation lengths for radio and acoustic signals can be demonstrated by in-situ measurements, the construction of a large hybrid array within this material may be possible in the Northern Hemisphere. Properties and problems of a possible location in Siberia are discussed below. Some acoustic data are compared with laboratory measurements using 'artificial' permafrost
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Turankar, Ravindra P; Pandey, Shradha; Lavania, Mallika; Singh, Itu; Nigam, Astha; Darlong, Joydeepa; Darlong, Fam; Sengupta, Utpal
2015-03-01
PCR assay is a highly sensitive, specific and reliable diagnostic tool for the identification of pathogens in many infectious diseases. Genome sequencing Mycobacterium leprae revealed several gene targets that could be used for the detection of DNA from clinical and environmental samples. The PCR sensitivity of particular gene targets for specific clinical and environmental isolates has not yet been established. The present study was conducted to compare the sensitivity of RLEP, rpoT, Sod A and 16S rRNA gene targets in the detection of M. leprae in slit skin smear (SSS), blood, soil samples of leprosy patients and their surroundings. Leprosy patients were classified into Paucibacillary (PB) and Multibacillary (MB) types. Ziehl-Neelsen (ZN) staining method for all the SSS samples and Bacteriological Index (BI) was calculated for all patients. Standard laboratory protocol was used for DNA extraction from SSS, blood and soil samples. PCR technique was performed for the detection of M. leprae DNA from all the above-mentioned samples. RLEP gene target was able to detect the presence of M. leprae in 83% of SSS, 100% of blood samples and in 36% of soil samples and was noted to be the best out of all other gene targets (rpoT, Sod A and 16S rRNA). It was noted that the RLEP gene target was able to detect the highest number (53%) of BI-negative leprosy patients amongst all the gene targets used in this study. Amongst all the gene targets used in this study, PCR positivity using RLEP gene target was the highest in all the clinical and environmental samples. Further, the RLEP gene target was able to detect 53% of blood samples as positive in BI-negative leprosy cases indicating its future standardization and use for diagnostic purposes. Copyright © 2015 Asian African Society for Mycobacteriology. Published by Elsevier Ltd. All rights reserved.
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Detection Range of Airborne Magnetometers in Magnetic Anomaly Detection
Directory of Open Access Journals (Sweden)
Chengjing Li
2015-11-01
Full Text Available Airborne magnetometers are utilized for the small-range search, precise positioning, and identification of the ferromagnetic properties of underwater targets. As an important performance parameter of sensors, the detection range of airborne magnetometers is commonly set as a fixed value in references regardless of the influences of environment noise, target magnetic properties, and platform features in a classical model to detect airborne magnetic anomalies. As a consequence, deviation in detection ability analysis is observed. In this study, a novel detection range model is proposed on the basis of classic detection range models of airborne magnetometers. In this model, probability distribution is applied, and the magnetic properties of targets and the environment noise properties of a moving submarine are considered. The detection range model is also constructed by considering the distribution of the moving submarine during detection. A cell-averaging greatest-of-constant false alarm rate test method is also used to calculate the detection range of the model at a desired false alarm rate. The detection range model is then used to establish typical submarine search probabilistic models. Results show that the model can be used to evaluate not only the effects of ambient magnetic noise but also the moving and geomagnetic features of the target and airborne detection platform. The model can also be utilized to display the actual operating range of sensor systems.
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Track-before-detect procedures for detection of extended object
Directory of Open Access Journals (Sweden)
Fan Ling
2011-01-01
Full Text Available Abstract In this article, we present a particle filter (PF-based track-before-detect (PF TBD procedure for detection of extended objects whose shape is modeled by an ellipse. By incorporating of an existence variable and the target shape parameters into the state vector, the proposed algorithm performs joint estimation of the target presence/absence, trajectory and shape parameters under unknown nuisance parameters (target power and noise variance. Simulation results show that the proposed algorithm has good detection and tracking capabilities for extended objects.
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Beanland, Vanessa; Filtness, Ashleigh J; Jeans, Rhiannon
2017-03-01
The ability to detect changes is crucial for safe driving. Previous research has demonstrated that drivers often experience change blindness, which refers to failed or delayed change detection. The current study explored how susceptibility to change blindness varies as a function of the driving environment, type of object changed, and safety relevance of the change. Twenty-six fully-licenced drivers completed a driving-related change detection task. Changes occurred to seven target objects (road signs, cars, motorcycles, traffic lights, pedestrians, animals, or roadside trees) across two environments (urban or rural). The contextual safety relevance of the change was systematically manipulated within each object category, ranging from high safety relevance (i.e., requiring a response by the driver) to low safety relevance (i.e., requiring no response). When viewing rural scenes, compared with urban scenes, participants were significantly faster and more accurate at detecting changes, and were less susceptible to "looked-but-failed-to-see" errors. Interestingly, safety relevance of the change differentially affected performance in urban and rural environments. In urban scenes, participants were more efficient at detecting changes with higher safety relevance, whereas in rural scenes the effect of safety relevance has marginal to no effect on change detection. Finally, even after accounting for safety relevance, change blindness varied significantly between target types. Overall the results suggest that drivers are less susceptible to change blindness for objects that are likely to change or move (e.g., traffic lights vs. road signs), and for moving objects that pose greater danger (e.g., wild animals vs. pedestrians). Copyright © 2017 Elsevier Ltd. All rights reserved.
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DEFF Research Database (Denmark)
de Knegt, Victoria Elizabeth; Kristiansen, Gitte Qvist; Schønning, Kristian
2017-01-01
BACKGROUND: We aimed to evaluate the relevance of dual target real-time polymerase chain (PCR) assays targeting the rtxA and cpn60 genes of the paediatric pathogen Kingella kingae. We also studied for the first time the clinical and epidemiological features of K. kingae infections in a Danish pop......-value: peak in autumn. CONCLUSION: Dual target-specific real-time PCR markedly improved the detection of K. kingae in clinical specimens when compared to culture methods....
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Feature-based RNN target recognition
Bakircioglu, Hakan; Gelenbe, Erol
1998-09-01
Detection and recognition of target signatures in sensory data obtained by synthetic aperture radar (SAR), forward- looking infrared, or laser radar, have received considerable attention in the literature. In this paper, we propose a feature based target classification methodology to detect and classify targets in cluttered SAR images, that makes use of selective signature data from sensory data, together with a neural network technique which uses a set of trained networks based on the Random Neural Network (RNN) model (Gelenbe 89, 90, 91, 93) which is trained to act as a matched filter. We propose and investigate radial features of target shapes that are invariant to rotation, translation, and scale, to characterize target and clutter signatures. These features are then used to train a set of learning RNNs which can be used to detect targets within clutter with high accuracy, and to classify the targets or man-made objects from natural clutter. Experimental data from SAR imagery is used to illustrate and validate the proposed method, and to calculate Receiver Operating Characteristics which illustrate the performance of the proposed algorithm.
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Directory of Open Access Journals (Sweden)
Chantal Robitaille
2015-01-01
Full Text Available BACKGROUND: Targeted spirometry screening for chronic obstructive pulmonary disease (COPD has been studied in primary care and community settings. Limitations regarding availability and quality of testing remain. A targeted spirometry screening program was implemented within a presurgical screening (PSS clinic to detect undiagnosed airways disease and identify patients with COPD/asthma in need of treatment optimization.
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A Tumor-Targeted Nanodelivery System to Improve Early MRI Detection of Cancer
Directory of Open Access Journals (Sweden)
Kathleen F. Pirollo
2006-01-01
Full Text Available The development of improvements in magnetic resonance imaging (MRI that would enhance sensitivity, leading to earlier detection of cancer and visualization of metastatic disease, is an area of intense exploration. We have devised a tumor-targeting, liposomal nanodelivery platform for use in gene medicine. This systemically administered nanocomplex has been shown to specifically and efficiently deliver both genes and oligonucleotides to primary and metastatic tumor cells, resulting in significant tumor growth inhibition and even tumor regression. Here we examine the effect on MRI of incorporating conventional MRI contrast agent Magnevist® into our anti-transferrin receptor single-chain antibody (TfRscFv liposomal complex. Both in vitro and in an in vivo orthotopic mouse model of pancreatic cancer, we show increased resolution and image intensity with the complexed Magnevist®. Using advanced microscopy techniques (scanning electron microscopy and scanning probe microscopy, we also established that the Magnevist® is in fact encapsulated by the liposome in the complex and that the complex still retains its nanodimensional size. These results demonstrate that this TfRscFv-liposome-Magnevist® nanocomplex has the potential to become a useful tool in early cancer detection.
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Ferreira, Ana Sofia; Costa, Pedro; Rocha, Teresa; Amaro, Ana; Vieira, Maria Luísa; Ahmed, Ahmed; Thompson, Gertrude; Hartskeerl, Rudy A.; Inácio, João
2014-01-01
Leptospirosis is a growing public and veterinary health concern caused by pathogenic species of Leptospira. Rapid and reliable laboratory tests for the direct detection of leptospiral infections in animals are in high demand not only to improve diagnosis but also for understanding the epidemiology of the disease. In this work we describe a novel and simple TaqMan-based multi-gene targeted real-time PCR approach able to detect and differentiate Leptospira interrogans, L. kirschneri, L. borgpeteresenii and L. noguchii, which constitute the veterinary most relevant pathogenic species of Leptospira. The method uses sets of species-specific probes, and respective flanking primers, designed from ompL1 and secY gene sequences. To monitor the presence of inhibitors, a duplex amplification assay targeting both the mammal β-actin and the leptospiral lipL32 genes was implemented. The analytical sensitivity of all primer and probe sets was estimated to be <10 genome equivalents (GE) in the reaction mixture. Application of the amplification reactions on genomic DNA from a variety of pathogenic and non-pathogenic Leptospira strains and other non-related bacteria revealed a 100% analytical specificity. Additionally, pathogenic leptospires were successfully detected in five out of 29 tissue samples from animals (Mus spp., Rattus spp., Dolichotis patagonum and Sus domesticus). Two samples were infected with L. borgpetersenii, two with L. interrogans and one with L. kirschneri. The possibility to detect and identify these pathogenic agents to the species level in domestic and wildlife animals reinforces the diagnostic information and will enhance our understanding of the epidemiology of leptopirosis. PMID:25398140
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Tartakovsky, A.; Brown, A.; Brown, J.
The paper describes the development and evaluation of a suite of advanced algorithms which provide significantly-improved capabilities for finding, fixing, and tracking multiple ballistic and flying low observable objects in highly stressing cluttered environments. The algorithms have been developed for use in satellite-based staring and scanning optical surveillance suites for applications including theatre and intercontinental ballistic missile early warning, trajectory prediction, and multi-sensor track handoff for midcourse discrimination and intercept. The functions performed by the algorithms include electronic sensor motion compensation providing sub-pixel stabilization (to 1/100 of a pixel), as well as advanced temporal-spatial clutter estimation and suppression to below sensor noise levels, followed by statistical background modeling and Bayesian multiple-target track-before-detect filtering. The multiple-target tracking is performed in physical world coordinates to allow for multi-sensor fusion, trajectory prediction, and intercept. Output of detected object cues and data visualization are also provided. The algorithms are designed to handle a wide variety of real-world challenges. Imaged scenes may be highly complex and infinitely varied -- the scene background may contain significant celestial, earth limb, or terrestrial clutter. For example, when viewing combined earth limb and terrestrial scenes, a combination of stationary and non-stationary clutter may be present, including cloud formations, varying atmospheric transmittance and reflectance of sunlight and other celestial light sources, aurora, glint off sea surfaces, and varied natural and man-made terrain features. The targets of interest may also appear to be dim, relative to the scene background, rendering much of the existing deployed software useless for optical target detection and tracking. Additionally, it may be necessary to detect and track a large number of objects in the threat cloud
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Detection of dim targets in multiple environments
Mirsky, Grace M.; Woods, Matthew; Grasso, Robert J.
2013-10-01
The proliferation of a wide variety of weapons including Anti-Aircraft Artillery (AAA), rockets, and small arms presents a substantial threat to both military and civilian aircraft. To address this ever-present threat, Northrop Grumman has assessed unguided threat phenomenology to understand the underlying physical principles for detection. These principles, based upon threat transit through the atmosphere, exploit a simple phenomenon universal to all objects moving through an atmosphere comprised of gaseous media to detect and track the threat in the presence of background and clutter. Threat detection has rapidly become a crucial component of aircraft survivability systems that provide situational awareness to the crew. It is particularly important to platforms which may spend a majority of their time at low altitudes and within the effective range of a large variety of weapons. Detection of these threats presents a unique challenge as this class of threat typically has a dim signature coupled with a short duration. Correct identification of each of the threat components (muzzle flash and projectile) is important to determine trajectory and intent while minimizing false alarms and maintaining a high detection probability in all environments.
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Peter, P; Dhillon, R; Bose, S; Bourke, A
2016-10-01
To analyse the value of targeted second-look ultrasound and imaging-guided biopsy in high-risk young women eligible for screening magnetic resonance imaging (MRI) in a tertiary referral centre in Perth, Western Australia. A retrospective analysis of eligible high-risk young women who underwent screening breast MRI and targeted second-look ultrasound between June 2012 and June 2014 was performed with review of data. Over a 2-year period, 139 women underwent high-risk screening MRI. Of these, 30 women (with a total of 45 lesions) were recalled for targeted second-look ultrasound. Thirty-four MRI-detected lesions were identified on targeted ultrasound with 19 of them proceeding to ultrasound-guided biopsy, while the remaining 15 lesions were considered benign on ultrasound, were not biopsied, and were stable on follow-up imaging 12 months later. One lesion proceeded to an MRI-guided biopsy to confirm a benign result. Of the 11 lesions not seen on ultrasound, nine underwent MRI biopsy, one proceeded directly to hook wire localisation and excision, and one did not return for biopsy and was lost to follow-up. The overall biopsy rate was 14.4%. The cancer detection rate was 1.4%. The results of this study indicate that targeted second-look ultrasound and ultrasound-guided biopsy is a cost-effective and time-efficient approach for MRI-detected lesions in young women at high risk of developing breast cancer. MRI-guided biopsy should be considered for ultrasonographically occult suspicious lesions as there is a low, but definite, risk of cancer. Copyright © 2016 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
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Dedysh, Svetlana N; Dunfield, Peter F; Derakshani, Manigee; Stubner, Stephan; Heyer, Jürgen; Liesack, Werner
2003-04-01
Abstract Based on an extensive 16S rRNA sequence database for type II methanotrophic bacteria, a set of 16S rRNA-targeted oligonucleotide probes was developed for differential detection of specific phylogenetic groups of these bacteria by fluorescence in situ hybridisation (FISH). This set of oligonucleotides included a genus-specific probe for Methylocystis (Mcyst-1432) and three species-specific probes for Methylosinus sporium (Msins-647), Methylosinus trichosporium (Msint-1268) and the recently described acidophilic methanotroph Methylocapsa acidiphila (Mcaps-1032). These novel probes were applied to further characterise the type II methanotroph community that was detected in an acidic Sphagnum peat from West Siberia in a previous study (Dedysh et al. (2001) Appl. Environ. Microbiol. 67, 4850-4857). The largest detectable population of indigenous methanotrophs simultaneously hybridised with a group-specific probe targeting all currently known Methylosinus/Methylocystis spp. (M-450), with a genus-specific probe for Methylocystis spp. (Mcyst-1432), and with an additional probe (Mcyst-1261) that had been designed to target a defined phylogenetic subgroup of Methylocystis spp. The same subgroup of Methylocystis was also detected in acidic peat sampled from Sphagnum-dominated wetland in northern Germany. The population size of this peat-inhabiting Methylocystis subgroup was 2.0+/-0.1x10(6) cells g(-1) (wet weight) of peat from Siberia and 5.5+/-0.5x10(6) cells g(-1) of peat from northern Germany. This represented 60 and 95%, respectively, of the total number of methanotroph cells detected by FISH in these two wetland sites. Other major methanotroph populations were M. acidiphila and Methylocella palustris. Type I methanotrophs accounted for not more than 1% of total methanotroph cells. Neither M. trichosporium nor M. sporium were detected in acidic Sphagnum peat.
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National Research Council Canada - National Science Library
Repperger, D. W; Phillips, C. A; Schrider, C. D; Smith, E. A
2004-01-01
In an effort to improve decision-making on the identity of unknown objects appearing in visual images when the surrounding environment may be noisy and cluttered, a highly sensitive target detection...
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Martinez, Jennifer S [Santa Fe, NM; Swanson, Basil I [Los Alamos, NM; Grace, Karen M [Los Alamos, NM; Grace, Wynne K [Los Alamos, NM; Shreve, Andrew P [Santa Fe, NM
2009-06-02
An assay element is described including recognition ligands bound to a film on a single mode planar optical waveguide, the film from the group of a membrane, a polymerized bilayer membrane, and a self-assembled monolayer containing polyethylene glycol or polypropylene glycol groups therein and an assay process for detecting the presence of a biological target is described including injecting a biological target-containing sample into a sensor cell including the assay element, with the recognition ligands adapted for binding to selected biological targets, maintaining the sample within the sensor cell for time sufficient for binding to occur between selected biological targets within the sample and the recognition ligands, injecting a solution including a reporter ligand into the sensor cell; and, interrogating the sample within the sensor cell with excitation light from the waveguide, the excitation light provided by an evanescent field of the single mode penetrating into the biological target-containing sample to a distance of less than about 200 nanometers from the waveguide thereby exciting the fluorescent-label in any bound reporter ligand within a distance of less than about 200 nanometers from the waveguide and resulting in a detectable signal.
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Energy Technology Data Exchange (ETDEWEB)
Shi, Kai; Dou, Baoting; Yang, Jianmei; Yuan, Ruo; Xiang, Yun, E-mail: yunatswu@swu.edu.cn
2016-04-15
The monitoring of microRNA (miRNA) expression levels is of great importance in cancer diagnosis. In the present work, based on two cascaded toehold-mediated strand displacement reactions (TSDRs), we have developed a label- and enzyme-free target recycling signal amplification approach for sensitive electronic detection of miRNA-21 from human breast cancer cells. The junction probes containing the locked G-quadruplex forming sequences are self-assembled on the senor surface. The presence of the target miRNA-21 initiates the first TSDR and results in the disassembly of the junction probes and the release of the active G-quadruplex forming sequences. Subsequently, the DNA fuel strand triggers the second TSDR and leads to cyclic reuse of the target miRNA-21. The cascaded TSDRs thus generate many active G-quadruplex forming sequences on the sensor surface, which associate with hemin to produce significantly amplified current response for sensitive detection of miRNA-21 at 1.15 fM. The sensor is also selective and can be employed to monitor miRNA-21 from human breast cancer cells. - Highlights: • Amplified and sensitive detection of microRNA from tumor cells is achieved. • Signal amplification is realized by two cascaded strand displacement reactions. • The developed sensor is selective and label-free without involving any enzymes.
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Itoh, Toshio; Akamatsu, Takafumi; Tsuruta, Akihiro; Shin, Woosuck
2017-01-01
We investigated selective detection of the target volatile organic compounds (VOCs) nonanal, n-decane, and acetoin for lung cancer-related VOCs, and acetone and methyl i-butyl ketone for diabetes-related VOCs, in humid air with simulated VOC contamination (total concentration: 300 μg/m3). We used six “grain boundary-response type” sensors, including four commercially available sensors (TGS 2600, 2610, 2610, and 2620) and two Pt, Pd, and Au-loaded SnO2 sensors (Pt, Pd, Au/SnO2), and two “bulk-response type” sensors, including Zr-doped CeO2 (CeZr10), i.e., eight sensors in total. We then analyzed their sensor signals using principal component analysis (PCA). Although the six “grain boundary-response type” sensors were found to be insufficient for selective detection of the target gases in humid air, the addition of two “bulk-response type” sensors improved the selectivity, even with simulated VOC contamination. To further improve the discrimination, we selected appropriate sensors from the eight sensors based on the PCA results. The selectivity to each target gas was maintained and was not affected by contamination. PMID:28753948
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2017-12-01
Fig. 2 Simulation method; the process for one iteration of the simulation . It was repeated 250 times per combination of HR and FAR. Analysis was...distribution is unlimited. 8 Fig. 2 Simulation method; the process for one iteration of the simulation . It was repeated 250 times per combination of HR...stimuli. Simulations show that this regression method results in an unbiased and accurate estimate of target detection performance. The regression
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Ge, Lei; Wang, Wenxiao; Sun, Ximei; Hou, Ting; Li, Feng
2016-02-16
As is well-known, graphene shows a remarkable difference in affinity toward nonstructured single-stranded (ss) DNA and double-stranded (ds) DNA. This property makes it popular to prepare DNA-based optical sensors. In this work, taking this unique property of graphene in combination with the sensitive electrochemical transducer, we report a novel affinity-mediated homogeneous electrochemical aptasensor using graphene modified glassy carbon electrode (GCE) as the sensing platform. In this approach, the specific aptamer-target recognition is converted into an ultrasensitive electrochemical signal output with the aid of a novel T7 exonuclease (T7Exo)-assisted target-analog recycling amplification strategy, in which the ingeniously designed methylene blue (MB)-labeled hairpin DNA reporters are digested in the presence of target and, then, converted to numerous MB-labeled long ssDNAs. The distinct difference in differential pulse voltammetry response between the designed hairpin reporters and the generated long ssDNAs on the graphene/GCE allows ultrasensitive detection of target biomolecules. Herein, the design and working principle of this homogeneous electrochemical aptasensor were elucidated, and the working conditions were optimized. The gel electrophoresis results further demonstrate that the designed T7Exo-assisted target-analog recycling amplification strategy can work well. This electrochemical aptasensor realizes the detection of biomolecule in a homogeneous solution without immobilization of any bioprobe on electrode surface. Moreover, this versatile homogeneous electrochemical sensing system was used for the determination of biomolecules in real serum samples with satisfying results.
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Frawley, Thomas; O'Brien, Cathal P; Conneally, Eibhlin; Vandenberghe, Elisabeth; Percy, Melanie; Langabeer, Stephen E; Haslam, Karl
2018-02-01
The classical Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs), consisting of polycythemia vera, essential thrombocythemia, and primary myelofibrosis, are a heterogeneous group of neoplasms that harbor driver mutations in the JAK2, CALR, and MPL genes. The detection of mutations in these genes has been incorporated into the recent World Health Organization (WHO) diagnostic criteria for MPN. Given a pressing clinical need to screen for mutations in these genes in a routine diagnostic setting, a targeted next-generation sequencing (NGS) assay for the detection of MPN-associated mutations located in JAK2 exon 14, JAK2 exon 12, CALR exon 9, and MPL exon 10 was developed to provide a single platform alternative to reflexive, stepwise diagnostic algorithms. Polymerase chain reaction (PCR) primers were designed to target mutation hotspots in JAK2 exon 14, JAK2 exon 12, MPL exon 10, and CALR exon 9. Multiplexed PCR conditions were optimized by using qualitative PCR followed by NGS. Diagnostic genomic DNA from 35 MPN patients, known to harbor driver mutations in one of the target genes, was used to validate the assay. One hundred percent concordance was observed between the previously-identified mutations and those detected by NGS, with no false positives, nor any known mutations missed (specificity = 100%, CI = 0.96, sensitivity = 100%, CI = 0.89). Improved resolution of mutation sequences was also revealed by NGS analysis. Detection of diagnostically relevant driver mutations of MPN is enhanced by employing a targeted multiplex NGS approach. This assay presents a robust solution to classical MPN mutation screening, providing an alternative to time-consuming sequential analyses.
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Xu, Yunying; Xu, Jin; Xiang, Yun; Yuan, Ruo; Chai, Yaqin
2014-01-15
In this work, we described the development of a new label-free, simple and sensitive fluorescent ATP sensing platform based on exonuclease III (Exo III)-catalyzed target recycling (ECTR) amplification and SYBR Green I indicator. The hairpin aptamer probes underwent conformational structure switching and re-configuration in the presence of ATP, which led to catalytic cleavage of the re-configured aptamers by Exo III to release ATP and to initiate the ECTR process. Such ECTR process resulted in the digestion of a significant number of the hairpin aptamer probes, leading to much less intercalation of SYBR Green I to the hairpin stems and drastic suppression of the fluorescence emission for sensitive ATP detection down to the low nanomolar level. Due to the highly specific affinity bindings between aptamers and ATP, the developed method exhibited excellent selectivity toward ATP against other analogous molecules. Besides, our ATP sensing approach used un-modified aptamer probes and could be performed in a "mix-and-detect" fashion in homogenous solutions. All these distinct advantages of the developed method thus made it hold great potential for the development of simple and robust sensing strategies for the detection of other small molecules. © 2013 Elsevier B.V. All rights reserved.
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Zhao, Yang; Tan, Lu; Gao, Xiaoshan; Jie, Guifen; Huang, Tingyu
2018-07-01
Herein, we successfully devised a novel photoelectrochemical (PEC) platform for ultrasensitive detection of adenosine by target-triggering cascade multiple cycle amplification based on the silver nanoparticles-assisted ion-exchange reaction with CdTe quantum dots (QDs). In the presence of target adenosine, DNA s1 is released from the aptamer and then hybridizes with hairpin DNA (HP1), which could initiate the cycling cleavage process under the reaction of nicking endonuclease. Then the product (DNA b) of cycle I could act as the "DNA trigger" of cycle II to further generate a large number of DNA s1, which again go back to cycle I, thus a cascade multiple DNA cycle amplification was carried out to produce abundant DNA c. These DNA c fragments with the cytosine (C)-rich loop were captured by magnetic beads, and numerous silver nanoclusters (Ag NCs) were synthesized by AgNO 3 and sodium borohydride. The dissolved AgNCs released numerous silver ions which could induce ion exchange reaction with the CdTe QDs, thus resulting in greatly amplified change of photocurrent for target detection. The detection linear range for adenosine was 1.0 fM ~10 nM with the detection limit of 0.5 fM. The present PEC strategy combining cascade multiple DNA cycle amplification and AgNCs-induced ion-exchange reaction with QDs provides new insight into rapid, and ultrasensitive PEC detection of different biomolecules, which showed great potential for detecting trace amounts in bioanalysis and clinical biomedicine. Copyright © 2018 Elsevier B.V. All rights reserved.
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Workflow for the Targeted and Untargeted Detection of Small Metabolites in Fish Skin Mucus
Directory of Open Access Journals (Sweden)
Lada Ivanova
2018-06-01
Full Text Available The skin mucus of fish is in permanent contact with the aquatic environment. Data from the analysis of the chemical composition of skin mucus could potentially be used for monitoring the health status of the fish. Knowledge about mucus composition or change in composition over time could also contribute to understanding the aetiology of certain diseases. The objective of the present study was the development of a workflow for non-invasive sampling of skin mucus from farmed salmon (Salmo salar for the targeted and untargeted detection of small metabolites. Skin mucus was either scraped off, wiped off using medical wipes, or the mucus’ water phase was absorbed using the same type of medical wipes that was used for the wiping method. Following a simple filtration step, the obtained mucus samples were subjected to hydrophilic interaction chromatography coupled to high-resolution mass spectrometry. Post-acquisition processing included the targeted analysis of 86 small metabolites, of which up to 60 were detected in absorbed mucus. Untargeted analysis of the mucus samples from equally treated salmon revealed that the total variation of the metabolome was lowest in absorbed mucus and highest in the scraped mucus. Thus, future studies including small-molecule metabolomics of skin mucus in fish would benefit from a sampling regime employing absorption of the water phase in order to minimize the bias related to the sampling step. Furthermore, the absorption method is also a less invasive approach allowing for repetitive sampling within short time intervals.
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Coffman, B. A.; Trumbo, M. C.; Flores, R. A.; Garcia, C. M.; van der Merwe, A. J.; Wassermann, E. M.; Weisend, M. P.; Clark, V. P.
2012-01-01
We have previously found that transcranial direct current stimulation (tDCS) over right inferior frontal cortex (RIFC) enhances performance during learning of a difficult visual target detection task (Clark et al., 2012). In order to examine the cognitive mechanisms of tDCS that lead to enhanced performance, here we analyzed its differential…
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Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)
Blacknell, David
2013-01-01
The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th
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Massad-Ivanir, Naama; Shtenberg, Giorgi; Raz, Nitzan; Gazenbeek, Christel; Budding, Dries; Bos, Martine P; Segal, Ester
2016-11-30
Rapid detection of target bacteria is crucial to provide a safe food supply and to prevent foodborne diseases. Herein, we present an optical biosensor for identification and quantification of Escherichia coli (E. coli, used as a model indicator bacteria species) in complex food industry process water. The biosensor is based on a nanostructured, oxidized porous silicon (PSi) thin film which is functionalized with specific antibodies against E. coli. The biosensors were exposed to water samples collected directly from process lines of fresh-cut produce and their reflectivity spectra were collected in real time. Process water were characterized by complex natural micro-flora (microbial load of >10 7 cell/mL), in addition to soil particles and plant cell debris. We show that process water spiked with culture-grown E. coli, induces robust and predictable changes in the thin-film optical interference spectrum of the biosensor. The latter is ascribed to highly specific capture of the target cells onto the biosensor surface, as confirmed by real-time polymerase chain reaction (PCR). The biosensors were capable of selectively identifying and quantifying the target cells, while the target cell concentration is orders of magnitude lower than that of other bacterial species, without any pre-enrichment or prior processing steps.
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Molenkamp, Richard; van der Ham, Alwin; Schinkel, Janke; Beld, Marcel
2007-01-01
One of the most interesting aspects of real-time PCR based on the detection of fluorophoric labeled oligonucleotides is the possibility of being able to detect conveniently multiple targets in the same PCR reaction. Recently, Roche Diagnostics launched a real-time PCR platform, the LightCycler480
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Directory of Open Access Journals (Sweden)
Idnin Pasya
2014-01-01
Full Text Available This paper presents a joint direction-of-departure (DOD and direction-of-arrival (DOA estimation in a multiple-input multiple-output (MIMO radar utilizing ultra wideband (UWB signals in detecting targets with fluctuating radar cross sections (RCS. The UWB MIMO radar utilized a combination of two-way MUSIC and majority decision based on angle histograms of estimated DODs and DOAs at each frequency of the UWB signal. The proposed angle estimation scheme was demonstrated to be effective in detecting targets with fluctuating RCS, compared to conventional spectra averaging method used in subband angle estimations. It was found that a wider bandwidth resulted in improved estimation performance. Numerical simulations along with experimental evaluations in a radio anechoic chamber are presented.
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Generalised two target localisation using passive monopulse radar
Jardak, Seifallah
2017-04-07
The simultaneous lobing technique, also known as monopulse technique, has been widely used for fast target localisation and tracking purposes. Many works focused on accurately localising one or two targets lying within a narrow beam centred around the monopulse antenna boresight. In this study, a new approach is proposed, which uses the outputs of four antennas to rapidly localise two point targets present in the hemisphere. If both targets have the same elevation angle, the proposed scheme cannot detect them. To detect such targets, a second set of antennas is required. In this study, to detect two targets at generalised locations, the antenna array is divided into multiple overlapping sets each of four antennas. Two algorithms are proposed to combine the outputs from multiple sets and improve the detection performance. Simulation results show that the algorithm is able to localise both targets with <;2° mean square error in azimuth and elevation.
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A Study of Adaptive Detection of Range-Distributed Targets
National Research Council Canada - National Science Library
Gerlach, Karl R
2000-01-01
... to be characterized as complex zero-mean correlated Gaussian random variables. The target's or targets' complex amplitudes are assumed to be distributed across the entire input data block (sensor x range...
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Canine Detection of the Volatilome: A Review of Implications for Pathogen and Disease Detection.
Angle, Craig; Waggoner, Lowell Paul; Ferrando, Arny; Haney, Pamela; Passler, Thomas
2016-01-01
The volatilome is the entire set of volatile organic compounds (VOC) produced by an organism. The accumulation of VOC inside and outside of the body reflects the unique metabolic state of an organism. Scientists are developing technologies to non-invasively detect VOC for the purposes of medical diagnosis, therapeutic monitoring, disease outbreak containment, and disease prevention. Detection dogs are proven to be a valuable real-time mobile detection technology for the detection of VOC related to explosives, narcotics, humans, and many other targets of interests. Little is known about what dogs are detecting when searching for biological targets. It is important to understand where biological VOC originates and how dogs might be able to detect biological targets. This review paper discusses the recent scientific literature involving VOC analysis and postulates potential biological targets for canine detection. Dogs have shown their ability to detect pathogen and disease-specific VOC. Future research will determine if dogs can be employed operationally in hospitals, on borders, in underserved areas, on farms, and in other operational environments to give real-time feedback on the presence of a biological target.
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Directory of Open Access Journals (Sweden)
Huang Tian
2014-10-01
Full Text Available Moving object detection and tracking is the computer vision and image processing is a hot research direction, based on the analysis of the moving target detection and tracking algorithm in common use, focus on the sports video target tracking non rigid body. In sports video, non rigid athletes often have physical deformation in the process of movement, and may be associated with the occurrence of moving target under cover. Media data is surging to fast search and query causes more difficulties in data. However, the majority of users want to be able to quickly from the multimedia data to extract the interested content and implicit knowledge (concepts, rules, rules, models and correlation, retrieval and query quickly to take advantage of them, but also can provide the decision support problem solving hierarchy. Based on the motion in sport video object as the object of study, conducts the system research from the theoretical level and technical framework and so on, from the layer by layer mining between low level motion features to high-level semantic motion video, not only provides support for users to find information quickly, but also can provide decision support for the user to solve the problem.
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SUPERPIXEL BASED FACTOR ANALYSIS AND TARGET TRANSFORMATION METHOD FOR MARTIAN MINERALS DETECTION
Directory of Open Access Journals (Sweden)
X. Wu
2018-04-01
Full Text Available The Factor analysis and target transformation (FATT is an effective method to test for the presence of particular mineral on Martian surface. It has been used both in thermal infrared (Thermal Emission Spectrometer, TES and near-infrared (Compact Reconnaissance Imaging Spectrometer for Mars, CRISM hyperspectral data. FATT derived a set of orthogonal eigenvectors from a mixed system and typically selected first 10 eigenvectors to least square fit the library mineral spectra. However, minerals present only in a limited pixels will be ignored because its weak spectral features compared with full image signatures. Here, we proposed a superpixel based FATT method to detect the mineral distributions on Mars. The simple linear iterative clustering (SLIC algorithm was used to partition the CRISM image into multiple connected image regions with spectral homogeneous to enhance the weak signatures by increasing their proportion in a mixed system. A least square fitting was used in target transformation and performed to each region iteratively. Finally, the distribution of the specific minerals in image was obtained, where fitting residual less than a threshold represent presence and otherwise absence. We validate our method by identifying carbonates in a well analysed CRISM image in Nili Fossae on Mars. Our experimental results indicate that the proposed method work well both in simulated and real data sets.
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Irsch, Kristina; Gramatikov, Boris I.; Wu, Yi-Kai; Guyton, David L.
2014-06-01
Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.
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Irsch, Kristina; Gramatikov, Boris I; Wu, Yi-Kai; Guyton, David L
2014-06-01
Amblyopia ("lazy eye") is a major public health problem, caused by misalignment of the eyes (strabismus) or defocus. If detected early in childhood, there is an excellent response to therapy, yet most children are detected too late to be treated effectively. Commercially available vision screening devices that test for amblyopia's primary causes can detect strabismus only indirectly and inaccurately via assessment of the positions of external light reflections from the cornea, but they cannot detect the anatomical feature of the eyes where fixation actually occurs (the fovea). Our laboratory has been developing technology to detect true foveal fixation, by exploiting the birefringence of the uniquely arranged Henle fibers delineating the fovea using retinal birefringence scanning (RBS), and we recently described a polarization-modulated approach to RBS that enables entirely direct and reliable detection of true foveal fixation, with greatly enhanced signal-to-noise ratio and essentially independent of corneal birefringence (a confounding variable with all polarization-sensitive ophthalmic technology). Here, we describe the design and operation of a new pediatric vision screener that employs polarization-modulated, RBS-based strabismus detection and bull's eye focus detection with an improved target system, and demonstrate the feasibility of this new approach.
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Better target detection in the presence of collinear flankers under high working memory load
Directory of Open Access Journals (Sweden)
Jan W. De Fockert
2014-10-01
Full Text Available There are multiple ways in which working memory can influence selective attention. Aside from the content-specific effects of working memory on selective attention, whereby attention is more likely to be directed towards information that matches the contents of working memory, the mere level of load on working memory has also been shown to have an effect on selective attention. Specifically, high load on working memory is associated with increased processing of irrelevant information. In most demonstrations of the effect to-date, this has led to impaired target performance, leaving open the possibility that the effect partly reflects an increase in general task difficulty under high load. Here we show that working memory load can result in a performance gain when processing of distracting information aids target performance. The facilitation in the detection of a low-contrast Gabor stimulus in the presence of collinear flanking Gabors was greater when load on a concurrent working memory task was high, compared to low. This finding suggests that working memory can interact with selective attention at an early stage in visual processing.
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Krøigård, Anne Bruun; Thomassen, Mads; Lænkholm, Anne-Vibeke; Kruse, Torben A; Larsen, Martin Jakob
2016-01-01
Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.
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International Nuclear Information System (INIS)
Schwenkbier, Lydia; Pollok, Sibyll; Popp, Jürgen; Weber, Karina; König, Stephan; Wagner, Stefan; Werres, Sabine; Weber, Jörg; Hentschel, Martin
2014-01-01
We report on a lab-on-a-chip approach for on-site detection of Phytophthora species that allows visual signal readout. The results demonstrate the significance of single-stranded DNA (ssDNA) generation in terms of improving the intensity of the hybridization signal and to improve the reliability of the method. Conventional PCR with subsequent heat denaturation, sodium hydroxide-based denaturation, lambda exonuclease digestion and two asymmetric PCR methods were investigated for the species P. fragariae, P. kernoviae, and P. ramorum. The positioning of the capture probe within the amplified yeast GTP-binding protein (YPT1) target DNA was also of interest because it significantly influences the intensity of the signal. Statistical tests were used to validate the impact of the ssDNA generation methods and the capture-target probe position. The single-stranded target DNA generated by Linear-After-The-Exponential PCR (LATE-PCR) was found to produce signal intensities comparable to post-PCR exonuclease treatment. The LATE-PCR is the best method for the on-site detection of Phytophthora because the enzymatic digestion after PCR is more laborious and time-consuming. (author)
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High or Low Target Prevalence Increases the Dual-Target Cost in Visual Search
Menneer, Tamaryn; Donnelly, Nick; Godwin, Hayward J.; Cave, Kyle R.
2010-01-01
Previous studies have demonstrated a dual-target cost in visual search. In the current study, the relationship between search for one and search for two targets was investigated to examine the effects of target prevalence and practice. Color-shape conjunction stimuli were used with response time, accuracy and signal detection measures. Performance…
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Stoltenburg, Regina; Kraf?ikov?, Petra; V?glask?, Viktor; Strehlitz, Beate
2016-01-01
Aptamers for whole cell detection are selected mostly by the Cell-SELEX procedure. Alternatively, the use of specific cell surface epitopes as target during aptamer selections allows the development of aptamers with ability to bind whole cells. In this study, we integrated a formerly selected Protein A-binding aptamer PA#2/8 in an assay format called ELONA (Enzyme-Linked OligoNucleotide Assay) and evaluated the ability of the aptamer to recognise and bind to Staphylococcus aureus presenting P...
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Directory of Open Access Journals (Sweden)
Liu Zhen
2012-03-01
Full Text Available Blind zones and ambiguities in range and velocity measurement are two important issues in traditional pulse-Doppler radar. By generating random deviations with respect to a mean Pulse Repetition Interval (PRI, this paper proposes a novel algorithm of Moving Target Detection (MTD based on the Compressed Sensing (CS theory, in which the random deviations of the PRIare converted to the Restricted Isometry Property (RIP of the observing matrix. The ambiguities of range and velocity are eliminated by designing the signal parameters. The simulation results demonstrate that this scheme has high performance of detection, and there is no ambiguity and blind zones as well. It can also shorten the coherent processing interval compared to traditional staggered PRI mode because only one pulse train is needed instead of several trains.
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Packard, Corey D.; Viola, Timothy S.; Klein, Mark D.
2017-10-01
The ability to predict spectral electro-optical (EO) signatures for various targets against realistic, cluttered backgrounds is paramount for rigorous signature evaluation. Knowledge of background and target signatures, including plumes, is essential for a variety of scientific and defense-related applications including contrast analysis, camouflage development, automatic target recognition (ATR) algorithm development and scene material classification. The capability to simulate any desired mission scenario with forecast or historical weather is a tremendous asset for defense agencies, serving as a complement to (or substitute for) target and background signature measurement campaigns. In this paper, a systematic process for the physical temperature and visible-through-infrared radiance prediction of several diverse targets in a cluttered natural environment scene is presented. The ability of a virtual airborne sensor platform to detect and differentiate targets from a cluttered background, from a variety of sensor perspectives and across numerous wavelengths in differing atmospheric conditions, is considered. The process described utilizes the thermal and radiance simulation software MuSES and provides a repeatable, accurate approach for analyzing wavelength-dependent background and target (including plume) signatures in multiple band-integrated wavebands (multispectral) or hyperspectrally. The engineering workflow required to combine 3D geometric descriptions, thermal material properties, natural weather boundary conditions, all modes of heat transfer and spectral surface properties is summarized. This procedure includes geometric scene creation, material and optical property attribution, and transient physical temperature prediction. Radiance renderings, based on ray-tracing and the Sandford-Robertson BRDF model, are coupled with MODTRAN for the inclusion of atmospheric effects. This virtual hyperspectral/multispectral radiance prediction methodology has been
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Cottenet, Geoffrey; Blancpain, Carine; Sonnard, Véronique; Chuah, Poh Fong
2013-08-01
Considering the increase of the total cultivated land area dedicated to genetically modified organisms (GMO), the consumers' perception toward GMO and the need to comply with various local GMO legislations, efficient and accurate analytical methods are needed for their detection and identification. Considered as the gold standard for GMO analysis, the real-time polymerase chain reaction (RTi-PCR) technology was optimised to produce a high-throughput GMO screening method. Based on simultaneous 24 multiplex RTi-PCR running on a ready-to-use 384-well plate, this new procedure allows the detection and identification of 47 targets on seven samples in duplicate. To comply with GMO analytical quality requirements, a negative and a positive control were analysed in parallel. In addition, an internal positive control was also included in each reaction well for the detection of potential PCR inhibition. Tested on non-GM materials, on different GM events and on proficiency test samples, the method offered high specificity and sensitivity with an absolute limit of detection between 1 and 16 copies depending on the target. Easy to use, fast and cost efficient, this multiplex approach fits the purpose of GMO testing laboratories.
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Targeted Nanotechnology for Cancer Imaging
Toy, Randall; Bauer, Lisa; Hoimes, Christopher; Ghaghada, Ketan B.; Karathanasis, Efstathios
2014-01-01
Targeted nanoparticle imaging agents provide many benefits and new opportunities to facilitate accurate diagnosis of cancer and significantly impact patient outcome. Due to the highly engineerable nature of nanotechnology, targeted nanoparticles exhibit significant advantages including increased contrast sensitivity, binding avidity and targeting specificity. Considering the various nanoparticle designs and their adjustable ability to target a specific site and generate detectable signals, nanoparticles can be optimally designed in terms of biophysical interactions (i.e., intravascular and interstitial transport) and biochemical interactions (i.e., targeting avidity towards cancer-related biomarkers) for site-specific detection of very distinct microenvironments. This review seeks to illustrate that the design of a nanoparticle dictates its in vivo journey and targeting of hard-to-reach cancer sites, facilitating early and accurate diagnosis and interrogation of the most aggressive forms of cancer. We will report various targeted nanoparticles for cancer imaging using X-ray computed tomography, ultrasound, magnetic resonance imaging, nuclear imaging and optical imaging. Finally, to realize the full potential of targeted nanotechnology for cancer imaging, we will describe the challenges and opportunities for the clinical translation and widespread adaptation of targeted nanoparticles imaging agents. PMID:25116445
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Zhang, Yuhan; Lu, Dr. Thomas
2010-01-01
The objectives of this project were to develop a ROI (Region of Interest) detector using Haar-like feature similar to the face detection in Intel's OpenCV library, implement it in Matlab code, and test the performance of the new ROI detector against the existing ROI detector that uses Optimal Trade-off Maximum Average Correlation Height filter (OTMACH). The ROI detector included 3 parts: 1, Automated Haar-like feature selection in finding a small set of the most relevant Haar-like features for detecting ROIs that contained a target. 2, Having the small set of Haar-like features from the last step, a neural network needed to be trained to recognize ROIs with targets by taking the Haar-like features as inputs. 3, using the trained neural network from the last step, a filtering method needed to be developed to process the neural network responses into a small set of regions of interests. This needed to be coded in Matlab. All the 3 parts needed to be coded in Matlab. The parameters in the detector needed to be trained by machine learning and tested with specific datasets. Since OpenCV library and Haar-like feature were not available in Matlab, the Haar-like feature calculation needed to be implemented in Matlab. The codes for Adaptive Boosting and max/min filters in Matlab could to be found from the Internet but needed to be integrated to serve the purpose of this project. The performance of the new detector was tested by comparing the accuracy and the speed of the new detector against the existing OTMACH detector. The speed was referred as the average speed to find the regions of interests in an image. The accuracy was measured by the number of false positives (false alarms) at the same detection rate between the two detectors.
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Energy Technology Data Exchange (ETDEWEB)
Charlton, Adrian J. [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)], E-mail: adrian.charlton@csl.gov.uk; Robb, Paul; Donarski, James A.; Godward, John [Department for Environment, Food and Rural Affairs, Central Science Laboratory, Sand Hutton, York YO41 1LZ (United Kingdom)
2008-06-23
An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined {sup 1}H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare {sup 1}H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications.
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International Nuclear Information System (INIS)
Charlton, Adrian J.; Robb, Paul; Donarski, James A.; Godward, John
2008-01-01
An efficient method for detecting malicious and accidental contamination of foods has been developed using a combined 1 H nuclear magnetic resonance (NMR) and chemometrics approach. The method has been demonstrated using a commercially available carbonated soft drink, as being capable of identifying atypical products and to identify contaminant resonances. Soft-independent modelling of class analogy (SIMCA) was used to compare 1 H NMR profiles of genuine products (obtained from the manufacturer) against retail products spiked in the laboratory with impurities. The benefits of using feature selection for extracting contaminant NMR frequencies were also assessed. Using example impurities (paraquat, p-cresol and glyphosate) NMR spectra were analysed using multivariate methods resulting in detection limits of approximately 0.075, 0.2, and 0.06 mM for p-cresol, paraquat and glyphosate, respectively. These detection limits are shown to be approximately 100-fold lower than the minimum lethal dose for paraquat. The methodology presented here is used to assess the composition of complex matrices for the presence of contaminating molecules without a priori knowledge of the nature of potential contaminants. The ability to detect if a sample does not fit into the expected profile without recourse to multiple targeted analyses is a valuable tool for incident detection and forensic applications
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Directory of Open Access Journals (Sweden)
Anne Bruun Krøigård
Full Text Available Next generation sequencing is extensively applied to catalogue somatic mutations in cancer, in research settings and increasingly in clinical settings for molecular diagnostics, guiding therapy decisions. Somatic variant callers perform paired comparisons of sequencing data from cancer tissue and matched normal tissue in order to detect somatic mutations. The advent of many new somatic variant callers creates a need for comparison and validation of the tools, as no de facto standard for detection of somatic mutations exists and only limited comparisons have been reported. We have performed a comprehensive evaluation using exome sequencing and targeted deep sequencing data of paired tumor-normal samples from five breast cancer patients to evaluate the performance of nine publicly available somatic variant callers: EBCall, Mutect, Seurat, Shimmer, Indelocator, Somatic Sniper, Strelka, VarScan 2 and Virmid for the detection of single nucleotide mutations and small deletions and insertions. We report a large variation in the number of calls from the nine somatic variant callers on the same sequencing data and highly variable agreement. Sequencing depth had markedly diverse impact on individual callers, as for some callers, increased sequencing depth highly improved sensitivity. For SNV calling, we report EBCall, Mutect, Virmid and Strelka to be the most reliable somatic variant callers for both exome sequencing and targeted deep sequencing. For indel calling, EBCall is superior due to high sensitivity and robustness to changes in sequencing depths.
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Autonomous Target Ranging Techniques
DEFF Research Database (Denmark)
Jørgensen, Peter Siegbjørn; Jørgensen, John Leif; Denver, Troelz
2003-01-01
of this telescope, a fast determination of the range to and the motion of the detected targets are important. This is needed in order to prepare the future observation strategy for each target, i.e. when is the closest approach where imaging will be optimal. In order to quickly obtain such a determination two...... ranging strategies are presented. One is an improved laser ranger with an effective range with non-cooperative targets of at least 10,000 km, demonstrated in ground tests. The accuracy of the laser ranging will be approximately 1 m. The laser ranger may furthermore be used for trajectory determination...... of nano-gravity probes, which will perform direct mass measurements of selected targets. The other is triangulation from two spacecraft. For this method it is important to distinguish between detection and tracking range, which will be different for Bering since different instruments are used...
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Zhou, Anran; Xie, Weixin; Pei, Jihong; Chen, Yapei
2018-02-01
For ship targets detection in cluttered infrared image sequences, a robust detection method, based on the probabilistic single Gaussian model of sea background in Fourier domain, is put forward. The amplitude spectrum sequences at each frequency point of the pure seawater images in Fourier domain, being more stable than the gray value sequences of each background pixel in the spatial domain, are regarded as a Gaussian model. Next, a probability weighted matrix is built based on the stability of the pure seawater's total energy spectrum in the row direction, to make the Gaussian model more accurate. Then, the foreground frequency points are separated from the background frequency points by the model. Finally, the false-alarm points are removed utilizing ships' shape features. The performance of the proposed method is tested by visual and quantitative comparisons with others.
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International Nuclear Information System (INIS)
Santiago-Felipe, Sara; Tortajada-Genaro, Luis Antonio; Puchades, Rosa; Maquieira, Ángel
2016-01-01
An integrated method for the parallelized detection of multiple DNA target sequences is presented by using microstructures in a digital versatile disc (DVD). Samples and reagents were managed by using both the capillary and centrifugal forces induced by disc rotation. Recombinase polymerase amplification (RPA), in a bridge solid phase format, took place in separate wells, which thereby modified their optical properties. Then the DVD drive reader recorded the modifications of the transmitted laser beam. The strategy allowed tens of genetic determinations to be made simultaneously within <2 h, with small sample volumes (3 μL), low manipulation and at low cost. The method was applied to high-throughput screening of relevant safety threats (allergens, GMOs and pathogenic bacteria) in food samples. Satisfactory results were obtained in terms of sensitivity (48.7 fg of DNA) and reproducibility (below 18 %). This scheme warrants cost-effective multiplex amplification and detection and is perceived to represent a viable tool for screening of nucleic acid targets. (author)
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Yang, Yutao; Zhou, Tingting; Bai, Bozan; Yin, Caixia; Xu, Wenzhi; Li, Wei
2018-05-01
Two mitochondria-targeted colorimetric and ratiometric fluorescent probes for SO2 derivatives were constructed based on the SO2 derivatives-triggered Michael addition reaction. The probes exhibit high specificity toward HSO3-/SO32- by interrupting their conjugation system resulting in a large ratiometric blue shift of 46-121 nm in their emission spectrum. The two well-resolved emission bands can ensure accurate detection of HSO3-. The detection limits were calculated to be 1.09 and 1.35 μM. Importantly, probe 1 and probe 2 were successfully used to fluorescence ratiometric imaging of endogenous HSO3- in BT-474 cells.
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Lin, Jia-Hui; Tseng, Wei-Lung
2015-01-01
Detection of salt- and analyte-induced aggregation of gold nanoparticles (AuNPs) mostly relies on costly and bulky analytical instruments. To response this drawback, a portable, miniaturized, sensitive, and cost-effective detection technique is urgently required for rapid field detection and monitoring of target analyte via the use of AuNP-based sensor. This study combined a miniaturized spectrometer with a 532-nm laser to develop a laser-induced Rayleigh scattering technique, allowing the sensitive and selective detection of Rayleigh scattering from the aggregated AuNPs. Three AuNP-based sensing systems, including salt-, thiol- and metal ion-induced aggregation of the AuNPs, were performed to examine the sensitivity of laser-induced Rayleigh scattering technique. Salt-, thiol-, and metal ion-promoted NP aggregation were exemplified by the use of aptamer-adsorbed, fluorosurfactant-stabilized, and gallic acid-capped AuNPs for probing K(+), S-adenosylhomocysteine hydrolase-induced hydrolysis of S-adenosylhomocysteine, and Pb(2+), in sequence. Compared to the reported methods for monitoring the aggregated AuNPs, the proposed system provided distinct advantages of sensitivity. Laser-induced Rayleigh scattering technique was improved to be convenient, cheap, and portable by replacing a diode laser and a miniaturized spectrometer with a laser pointer and a smart-phone. Using this smart-phone-based detection platform, we can determine whether or not the Pb(2+) concentration exceed the maximum allowable level of Pb(2+) in drinking water. Copyright © 2014 Elsevier B.V. All rights reserved.
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Attending to unrelated targets boosts short-term memory for color arrays.
Makovski, Tal; Swallow, Khena M; Jiang, Yuhong V
2011-05-01
Detecting a target typically impairs performance in a second, unrelated task. It has been recently reported however, that detecting a target in a stream of distractors can enhance long-term memory of faces and scenes that were presented concurrently with the target (the attentional boost effect). In this study we ask whether target detection also enhances performance in a visual short-term memory task, where capacity limits are severe. Participants performed two tasks at once: a one shot, color change detection task and a letter-detection task. In Experiment 1, a central letter appeared at the same time as 3 or 5 color patches (memory display). Participants encoded the colors and pressed the spacebar if the letter was a T (target). After a short retention interval, a probe display of color patches appeared. Performance on the change detection task was enhanced when a target, rather than a distractor, appeared with the memory display. This effect was not modulated by memory load or the frequency of trials in which a target appeared. However, there was no enhancement when the target appeared at the same time as the probe display (Experiment 2a) or during the memory retention interval (Experiment 2b). Together these results suggest that detecting a target facilitates the encoding of unrelated information into visual short-term memory. Copyright © 2010 Elsevier Ltd. All rights reserved.
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Merkiene, Egle; Gaidamaviciute, Edita; Riauba, Laurynas; Janulaitis, Arvydas; Lagunavicius, Arunas
2010-08-01
We improved the target RNA-primed RCA technique for direct detection and analysis of RNA in vitro and in situ. Previously we showed that the 3' --> 5' single-stranded RNA exonucleolytic activity of Phi29 DNA polymerase converts the target RNA into a primer and uses it for RCA initiation. However, in some cases, the single-stranded RNA exoribonucleolytic activity of the polymerase is hindered by strong double-stranded structures at the 3'-end of target RNAs. We demonstrate that in such hampered cases, the double-stranded RNA-specific Escherichia coli RNase III efficiently assists Phi29 DNA polymerase in converting the target RNA into a primer. These observations extend the target RNA-primed RCA possibilities to test RNA sequences distanced far from the 3'-end and customize this technique for the inner RNA sequence analysis.
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Cuadrado, Angeles; Golczyk, Hieronim; Jouve, Nicolás
2009-01-01
We report a new technique-nondenaturing FISH (ND-FISH)-for the rapid detection of plant telomeres without the need for prior denaturation of the chromosomes. In its development, two modified, synthetic oligonucleotides, 21 nt in length, fluorescently labelled at their 5' and 3' ends and complementary to either the cytidine-rich (C(3)TA(3)) or guanosine-rich (T(3)AG(3)) telomeric DNA strands, were used as probes. The high binding affinity of these probes and the short hybridization time required allows the visualization of plant telomeres in less than an hour. In tests, both probes gave strong signals visualized as double spots at both chromosome ends; this was true of both the mitotic and meiotic chromosomes of barley, wheat, rye, maize, Brachypodium distachyon and Rhoeo spathacea. They were also able to detect telomere motifs at certain intercalary sites in the chromosomes of R. spathacea. To investigate the nature of the target structures detected, the chromosomes were treated with RNase A and single strand-specific nuclease S1 before ND-FISH experiments. Signal formation was resistant to standard enzymatic treatment, but sensitive when much higher enzyme concentrations were used. The results are discussed in relation to current knowledge of telomere structure.
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Electromagnetic Induction Spectroscopy for the Detection of Subsurface Targets
2012-12-01
is proportional to the product of the transmitted and received magnetic fields and the magnetic polarizability tensor of the target being measured by...the EMI sensor (Appendix A). The magnetic polarizability tensor of several canonical targets can be calculated analytically, and these formulas show...prescreener. A simple voting mechanism is employed to discourage temporary mislabeling of land- mines by taking advantage of the sequential measurements. As
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Xu, Chang; Nezami Ranjbar, Mohammad R; Wu, Zhong; DiCarlo, John; Wang, Yexun
2017-01-03
Detection of DNA mutations at very low allele fractions with high accuracy will significantly improve the effectiveness of precision medicine for cancer patients. To achieve this goal through next generation sequencing, researchers need a detection method that 1) captures rare mutation-containing DNA fragments efficiently in the mix of abundant wild-type DNA; 2) sequences the DNA library extensively to deep coverage; and 3) distinguishes low level true variants from amplification and sequencing errors with high accuracy. Targeted enrichment using PCR primers provides researchers with a convenient way to achieve deep sequencing for a small, yet most relevant region using benchtop sequencers. Molecular barcoding (or indexing) provides a unique solution for reducing sequencing artifacts analytically. Although different molecular barcoding schemes have been reported in recent literature, most variant calling has been done on limited targets, using simple custom scripts. The analytical performance of barcode-aware variant calling can be significantly improved by incorporating advanced statistical models. We present here a highly efficient, simple and scalable enrichment protocol that integrates molecular barcodes in multiplex PCR amplification. In addition, we developed smCounter, an open source, generic, barcode-aware variant caller based on a Bayesian probabilistic model. smCounter was optimized and benchmarked on two independent read sets with SNVs and indels at 5 and 1% allele fractions. Variants were called with very good sensitivity and specificity within coding regions. We demonstrated that we can accurately detect somatic mutations with allele fractions as low as 1% in coding regions using our enrichment protocol and variant caller.
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Directory of Open Access Journals (Sweden)
Yong Ye
2016-05-01
Full Text Available A novel method for proximity detection of moving targets (with high dielectric constants using a large-scale (the size of each sensor is 31 cm × 19 cm planar capacitive sensor system (PCSS is proposed. The capacitive variation with distance is derived, and a pair of electrodes in a planar capacitive sensor unit (PCSU with a spiral shape is found to have better performance on sensitivity distribution homogeneity and dynamic range than three other shapes (comb shape, rectangular shape, and circular shape. A driving excitation circuit with a Clapp oscillator is proposed, and a capacitance measuring circuit with sensitivity of 0.21 V p − p / pF is designed. The results of static experiments and dynamic experiments demonstrate that the voltage curves of static experiments are similar to those of dynamic experiments; therefore, the static data can be used to simulate the dynamic curves. The dynamic range of proximity detection for three projectiles is up to 60 cm, and the results of the following static experiments show that the PCSU with four neighboring units has the highest sensitivity (the sensitivities of other units are at least 4% lower; when the attack angle decreases, the intensity of sensor signal increases. This proposed method leads to the design of a feasible moving target detector with simple structure and low cost, which can be applied in the interception system.
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Shokri, Ehsan; Hosseini, Morteza; Davari, Mehdi D.; Ganjali, Mohammad R.; Peppelenbosch, Maikel P.; Rezaee, Farhad
2017-01-01
A modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol-modified probes, each of which specifically
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Shokri, E. (Ehsan); M. Hosseini (Morteza); Davari, M.D. (Mehdi D.); Ganjali, M.R. (Mohammad R.); M.P. Peppelenbosch (Maikel); F. Rezaee (Farhad)
2017-01-01
textabstractA modified non-cross-linking gold-nanoparticles (Au-NPs) aggregation strategy has been developed for the label free colorimetric detection of DNAs/RNAs based on self-assembling target species in the presence of thiolated probes. Two complementary thiol- modified probes, each of which
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International Nuclear Information System (INIS)
Krishnan, Kalpagam; Liu, Jeff; Kohli, Kirpal
2014-01-01
Purpose: Fusion of electrical impedance tomography (EIT) with computed tomography (CT) can be useful as a clinical tool for providing additional physiological information about tissues, but requires suitable fusion algorithms and validation procedures. This work explores the feasibility of fusing EIT and CT images using an algorithm for coregistration. The imaging performance is validated through feature space assessment on phantom contrast targets. Methods: EIT data were acquired by scanning a phantom using a circuit, configured for injecting current through 16 electrodes, placed around the phantom. A conductivity image of the phantom was obtained from the data using electrical impedance and diffuse optical tomography reconstruction software (EIDORS). A CT image of the phantom was also acquired. The EIT and CT images were fused using a region of interest (ROI) coregistration fusion algorithm. Phantom imaging experiments were carried out on objects of different contrasts, sizes, and positions. The conductive medium of the phantoms was made of a tissue-mimicking bolus material that is routinely used in clinical radiation therapy settings. To validate the imaging performance in detecting different contrasts, the ROI of the phantom was filled with distilled water and normal saline. Spatially separated cylindrical objects of different sizes were used for validating the imaging performance in multiple target detection. Analyses of the CT, EIT and the EIT/CT phantom images were carried out based on the variations of contrast, correlation, energy, and homogeneity, using a gray level co-occurrence matrix (GLCM). A reference image of the phantom was simulated using EIDORS, and the performances of the CT and EIT imaging systems were evaluated and compared against the performance of the EIT/CT system using various feature metrics, detectability, and structural similarity index measures. Results: In detecting distilled and normal saline water in bolus medium, EIT as a stand
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Amar R Marathe; Anthony J Ries; Vernon J Lawhern; Vernon J Lawhern; Brent J Lance; Jonathan eTouryan; Kaleb eMcDowell; Hubert eCecotti
2015-01-01
Brain computer interaction (BCI) technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in si...
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Marathe, Amar R.; Ries, Anthony J.; Lawhern, Vernon J.; Lance, Brent J.; Touryan, Jonathan; McDowell, Kaleb; Cecotti, Hubert
2015-01-01
Brain computer interaction (BCI) technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in si...
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Developing and evaluating a target-background similarity metric for camouflage detection.
Directory of Open Access Journals (Sweden)
Chiuhsiang Joe Lin
Full Text Available BACKGROUND: Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. METHODOLOGY: In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. SIGNIFICANCE: The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.
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Developing and evaluating a target-background similarity metric for camouflage detection.
Lin, Chiuhsiang Joe; Chang, Chi-Chan; Liu, Bor-Shong
2014-01-01
Measurement of camouflage performance is of fundamental importance for military stealth applications. The goal of camouflage assessment algorithms is to automatically assess the effect of camouflage in agreement with human detection responses. In a previous study, we found that the Universal Image Quality Index (UIQI) correlated well with the psychophysical measures, and it could be a potentially camouflage assessment tool. In this study, we want to quantify the camouflage similarity index and psychophysical results. We compare several image quality indexes for computational evaluation of camouflage effectiveness, and present the results of an extensive human visual experiment conducted to evaluate the performance of several camouflage assessment algorithms and analyze the strengths and weaknesses of these algorithms. The experimental data demonstrates the effectiveness of the approach, and the correlation coefficient result of the UIQI was higher than those of other methods. This approach was highly correlated with the human target-searching results. It also showed that this method is an objective and effective camouflage performance evaluation method because it considers the human visual system and image structure, which makes it consistent with the subjective evaluation results.
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Multi-Stage System for Automatic Target Recognition
Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver
2010-01-01
A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an
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Modeling of Antenna for Deep Target Hydrocarbon Exploration
Directory of Open Access Journals (Sweden)
Nadeem Nasir
2017-11-01
Full Text Available Nowadays control source electromagnetic method is used for offshore hydrocarbon exploration. Hydrocarbon detection in sea bed logging (SBL is a very challenging task for deep target hydrocarbon reservoir. Response of electromagnetic (EM field from marine environment is very low and it is very difficult to predict deep target reservoir below 2km from the sea floor. This work premise deals with modeling of new antenna for deep water deep target hydrocarbon exploration. Conventional and new EM antennas at 0.125Hz frequency are used in modeling for the detection of deep target hydrocarbon reservoir. The proposed area of the seabed model (40km ´ 40km was simulated by using CST (computer simulation technology EM studio based on Finite Integration Method (FIM. Electromagnetic field components were compared at 500m target depth and it was concluded that Ex and Hz components shows better resistivity contrast. Comparison of conventional and new antenna for different target depths was done in our proposed model. From the results, it was observed that conventional antenna at 0.125Hz shows 70% ,86% resistivity contrast at target depth of 1000m where as new antenna showed 329%, 355% resistivity contrast at the same target depth for Ex and Hz field respectively. It was also investigated that at frequency of0.125Hz, new antenna gave 46% better delineation of hydrocarbon at 4000m target depth. This is due to focusing of electromagnetic waves by using new antenna. New antenna design gave 125% more extra depth than straight antenna for deep target hydrocarbon detection. Numerical modeling for straight and new antenna was also done to know general equation for electromagnetic field behavior with target depth. From this numerical model it was speculated that this new antenna can detect up to 4.5 km target depth. This new EM antenna may open new frontiers for oil and gas
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Presenting a New Standard Drug Model for Turmeric and Its Prized Extract, Curcumin
Directory of Open Access Journals (Sweden)
Franco Cavaleri
2018-01-01
Full Text Available Various parts of the turmeric plant have been used as medicinal treatment for various conditions from ulcers and arthritis to cardiovascular disease and neuroinflammation. The rhizome’s curcumin extract is the most studied active constituent, which exhibits an expansive polypharmacology with influence on many key inflammatory markers. Despite the expansive reports of curcucmin’s therapeutic value, clinical reliability and research repeatability with curcumin treatment are still poor. The pharmacology must be better understood and reliably mapped if curcumin is to be accepted and used in modern medical applications. Although the polypharmacology of this extract has been considered, in mainstream medicine, to be a drawback, a perspective change reveals a comprehensive and even synergistic shaping of the NF-kB pathway, including transactivation. Much of the inconsistent research data and unreliable clinical outcomes may be due to a lack of standardization which also pervades research standard samples. The possibility of other well-known curcumin by-products contributing in the polypharmacology is also discussed. A new flowchart of crosstalk in transduction pathways that lead to shaping of nuclear NF-kB transactivation is generated and a new calibration or standardization protocol for the extract is proposed which could lead to more consistent data extraction and improved reliability in therapy.
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Claudin-4-targeted optical imaging detects pancreatic cancer and its precursor lesions.
Neesse, Albrecht; Hahnenkamp, Anke; Griesmann, Heidi; Buchholz, Malte; Hahn, Stefan A; Maghnouj, Abdelouahid; Fendrich, Volker; Ring, Janine; Sipos, Bence; Tuveson, David A; Bremer, Christoph; Gress, Thomas M; Michl, Patrick
2013-07-01
Novel imaging methods based on specific molecular targets to detect both established neoplasms and their precursor lesions are highly desirable in cancer medicine. Previously, we identified claudin-4, an integral constituent of tight junctions, as highly expressed in various gastrointestinal tumours including pancreatic cancer. Here, we investigate the potential of targeting claudin-4 with a naturally occurring ligand to visualise pancreatic cancer and its precursor lesions in vitro and in vivo by near-infrared imaging approaches. A non-toxic C-terminal fragment of the claudin-4 ligand Clostridium perfringens enterotoxin (C-CPE) was labelled with a cyanine dye (Cy5.5). Binding of the optical tracer was analysed on claudin-4 positive and negative cells in vitro, and tumour xenografts in vivo. In addition, two genetically engineered mouse models for pancreatic intraepithelial neoplasia (PanIN) and pancreatic cancer were used for in vivo validation. Optical imaging studies were conducted using 2D planar fluorescence reflectance imaging (FRI) technology and 3D fluorescence-mediated tomography (FMT). In vitro, the peptide-dye conjugate showed high binding affinity to claudin-4 positive CAPAN1 cells, while claudin-4 negative HT1080 cells revealed little or no fluorescence. In vivo, claudin-4 positive tumour xenografts, endogenous pancreatic tumours, hepatic metastases, as well as preinvasive PanIN lesions, were visualised by FRI and FMT up to 48 h after injection showing a significantly higher average of fluorochrome concentration as compared with claudin-4 negative xenografts and normal pancreatic tissue. C-CPE-Cy5.5 combined with novel optical imaging methods enables non-invasive visualisation of claudin-4 positive murine pancreatic tumours and their precursor lesions, representing a promising modality for early diagnostic imaging.
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Directory of Open Access Journals (Sweden)
Hernández-Moneo Jose-Luis
2006-09-01
Full Text Available Abstract Background Conventional cytogenetic and comparative genomic hybridization (CGH studies in brain malignancies have shown that glioblastoma multiforme (GBM is characterized by complex structural and numerical alterations. However, the limited resolution of these techniques has precluded the precise identification of detailed specific gene copy number alterations. Results We performed a genome-wide survey of gene copy number changes in 20 primary GBMs by CGH on cDNA microarrays. A novel amplicon at 4p15, and previously uncharacterized amplicons at 13q32-34 and 1q32 were detected and are analyzed here. These amplicons contained amplified genes not previously reported. Other amplified regions containg well-known oncogenes in GBMs were also detected at 7p12 (EGFR, 7q21 (CDK6, 4q12 (PDGFRA, and 12q13-15 (MDM2 and CDK4. In order to identify the putative target genes of the amplifications, and to determine the changes in gene expression levels associated with copy number change events, we carried out parallel gene expression profiling analyses using the same cDNA microarrays. We detected overexpression of the novel amplified genes SLA/LP and STIM2 (4p15, and TNFSF13B and COL4A2 (13q32-34. Some of the candidate target genes of amplification (EGFR, CDK6, MDM2, CDK4, and TNFSF13B were tested in an independent set of 111 primary GBMs by using FISH and immunohistological assays. The novel candidate 13q-amplification target TNFSF13B was amplified in 8% of the tumors, and showed protein expression in 20% of the GBMs. Conclusion This high-resolution analysis allowed us to propose novel candidate target genes such as STIM2 at 4p15, and TNFSF13B or COL4A2 at 13q32-34 that could potentially contribute to the pathogenesis of these tumors and which would require futher investigations. We showed that overexpression of the amplified genes could be attributable to gene dosage and speculate that deregulation of those genes could be important in the development
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A Magnetic Sensor System for Biological Detection
Li, Fuquan
2015-05-01
Magnetic biosensors detect biological targets through sensing the stray field of magnetic beads which label the targets. Commonly, magnetic biosensors employ the “sandwich” method to immobilize biological targets, i.e., the targets are sandwiched between a bio-functionalized sensor surface and bio-functionalized magnetic beads. This method has been used very successfully in different application, but its execution requires a rather elaborate procedure including several washing and incubation steps. This dissertation investigates a new magnetic biosensor concept, which enables a simple and effective detection of biological targets. The biosensor takes advantage of the size difference between bare magnetic beads and compounds of magnetic beads and biological targets. First, the detection of super-paramagnetic beads via magnetic tunnel junction (MTJ) sensors is implemented. Frequency modulation is used to enhance the signal-to-noise ratio, enabling the detection of a single magnetic bead. Second, the concept of the magnetic biosensor is investigated theoretically. The biosensor consists of an MTJ sensor, which detects the stray field of magnetic beads inside of a trap on top of the MTJ. A microwire between the trap and the MTJ is used to attract magnetic beads to the trapping well by applying a current to it. The MTJ sensor’s output depends on the number of beads inside the trap. If biological targets are in the sample solution, the beads will form bead compounds consisting of beads linked to the biological targets. Since bead compounds are larger than bare beads, the number of beads inside the trapping well will depend on the presence of biological targets. Hence, the output of the MTJ sensor will depend on the biological targets. The dependences of sensor signals on the sizes of the MTJ sensor, magnetic beads and biological targets are studied to find the optimum constellations for the detection of specific biological targets. The optimization is demonstrated
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Identification of Bexarotene as a PPARγ Antagonist with HDX
Directory of Open Access Journals (Sweden)
David P. Marciano
2015-01-01
Full Text Available The retinoid x receptors (RXRs are the pharmacological target of Bexarotene, an antineoplastic agent indicated for the treatment of cutaneous T cell lymphoma (CTCL. The RXRs form heterodimers with several nuclear receptors (NRs, including peroxisome proliferator-activated receptor gamma (PPARγ, to regulate target gene expression through cooperative recruitment of transcriptional machinery. Here we have applied hydrogen/deuterium exchange (HDX mass spectrometry to characterize the effects of Bexarotene on the conformational plasticity of the intact RXRα:PPARγ heterodimer. Interestingly, addition of Bexarotene to PPARγ in the absence of RXRα induced protection from solvent exchange, suggesting direct receptor binding. This observation was confirmed using a competitive binding assay. Furthermore, Bexarotene functioned as a PPARγ antagonist able to alter rosiglitazone induced transactivation in a cell based promoter:reporter transactivation assay. Together these results highlight the complex polypharmacology of lipophilic NR targeted small molecules and the utility of HDX for identifying and characterizing these interactions.
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Adaptive Waveform Design for Cognitive Radar in Multiple Targets Situations
Directory of Open Access Journals (Sweden)
Xiaowen Zhang
2018-02-01
Full Text Available In this paper, the problem of cognitive radar (CR waveform optimization design for target detection and estimation in multiple extended targets situations is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended targets with unknown target impulse response (TIR. To address this problem, an improved algorithm is employed for target detection by maximizing the detection probability of the received echo on the promise of ensuring the TIR estimation precision. In this algorithm, an additional weight vector is introduced to achieve a trade-off among different targets. Both the estimate of TIR and transmit waveform can be updated at each step based on the previous step. Under the same constraint on waveform energy and bandwidth, the information theoretical approach is also considered. In addition, the relationship between the waveforms that are designed based on the two criteria is discussed. Unlike most existing works that only consider single target with temporally correlated characteristics, waveform design for multiple extended targets is considered in this method. Simulation results demonstrate that compared with linear frequency modulated (LFM signal, waveforms designed based on maximum detection probability and maximum mutual information (MI criteria can make radar echoes contain more multiple-target information and improve radar performance as a result.
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Ogawa, Mikako; Kosaka, Nobuyuki; Choyke, Peter L; Kobayashi, Hisataka
2009-01-01
In vivo molecular cancer imaging with monoclonal antibodies has great potential not only for cancer detection but also for cancer characterization. However, the prolonged retention of intravenously injected antibody in the blood causes low target tumor-to-background ratio (TBR). Avidin has been used as a “chase” to clear the unbound, circulating biotinylated antibody and decrease the background signal. Here, we utilize a combined approach of a Fluorescence Resonance Energy Transfer (FRET) quenched antibody with an “avidin chase” to increase TBR. Trastuzumab, a humanized monoclonal antibody against human epidermal growth factor receptor type 2 (HER2), was biotinylated and conjugated with the near-infrared (NIR) fluorophore Alexa680 to synthesize Tra-Alexa680-biotin. Next, the FRET quencher, QSY-21, was conjugated to avidin, neutravidin (nAv) or streptavidin (sAv), thus creating Av-QSY21, nAv-QSY21 or sAv-QSY21 as “chasers”. The fluorescence was quenched in vitro by binding Tra-Alexa680-biotin to Av-QSY21, nAv-QSY21 or sAv-QSY21. To evaluate if the injection of quencher-conjugated avidin-derivatives can improve target TBR by using a dual “quench and chase” strategy, both target (3T3/HER2+) and non-target (Balb3T3/ZsGreen) tumor bearing mice were employed. The “FRET quench” effect induced by all the QSY21 avidin-based conjugates reduced but did not totally eliminate background signal from the blood pool. The addition of nAv-QSY21 administration increased target TBR mainly due to the “chase” effect where unbound conjugated antibody was preferentially cleared to the liver. The relatively slow clearance of unbound nAv-QSY21 leads to further reductions in background signal by leaking out of the vascular space and binding to unbound antibodies in the extravascular space of tumors resulting in decreased non-target tumor-to-background ratios but increased target TBR due to the “FRET quench” effect because target-bound antibodies were internalized
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Directory of Open Access Journals (Sweden)
Ravindra P Turankar
2015-01-01
Conclusion: Amongst all the gene targets used in this study, PCR positivity using RLEP gene target was the highest in all the clinical and environmental samples. Further, the RLEP gene target was able to detect 53% of blood samples as positive in BI-negative leprosy cases indicating its future standardization and use for diagnostic purposes.
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Yan, Genping; Wang, Yonghong; He, Xiaoxiao; Wang, Kemin; Liu, Jinquan; Du, Yudan
2013-06-15
We report here a highly sensitive and label-free electrochemical aptasensing technology for detection of interferon-gamma (IFN-γ) based on graphene controlled assembly and enzyme cleavage-assisted target recycling amplification strategy. In this work, in the absence of IFN-γ, the graphene could not be assembled onto the 16-mercaptohexadecanoic acid (MHA) modified gold electrode because the IFN-γ binding aptamer was strongly adsorbed on the graphene due to the strong π-π interaction. Thus the electronic transmission was blocked (eT OFF). However, the presence of target IFN-γ and DNase I led to desorption of aptamer from the graphene surface and further cleavage of the aptamer, thereby releasing the IFN-γ. The released IFN-γ could then re-attack other aptamers on the graphene, resulting in the successive release of the aptamers from the graphene. At the same time, the "naked" graphene could be assembled onto the MHA modified gold electrode with hydrophobic interaction and π-conjunction, mediating the electron transfer between the electrode and the electroactive indicator. Then, measurable electrochemical signals were generated (eT ON), which was related to the concentration of the IFN-γ. By taking advantages of graphene and enzyme cleavage-assisted target recycling amplification, the developed label-free electrochemical aptasensing technology showed a linear response to concentration of IFN-γ range from 0.1 to 0.7 pM. The detection limit of IFN-γ was determined to be 0.065 pM. Moreover, this aptasensor shows good selectivity toward the target in the presence of other relevant proteins. Our strategy thus opens new opportunities for label-free and amplified detection of other kinds of proteins. Copyright © 2013 Elsevier B.V. All rights reserved.
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Mortezavi, Ashkan; Märzendorfer, Olivia; Donati, Olivio F; Rizzi, Gianluca; Rupp, Niels J; Wettstein, Marian S; Gross, Oliver; Sulser, Tullio; Hermanns, Thomas; Eberli, Daniel
2018-02-21
We evaluated the diagnostic accuracy of multiparametric magnetic resonance imaging and multiparametric magnetic resonance imaging/transrectal ultrasound fusion guided targeted biopsy against that of transperineal template saturation prostate biopsy to detect prostate cancer. We retrospectively analyzed the records of 415 men who consecutively presented for prostate biopsy between November 2014 and September 2016 at our tertiary care center. Multiparametric magnetic resonance imaging was performed using a 3 Tesla device without an endorectal coil, followed by transperineal template saturation prostate biopsy with the BiopSee® fusion system. Additional fusion guided targeted biopsy was done in men with a suspicious lesion on multiparametric magnetic resonance imaging, defined as Likert score 3 to 5. Any Gleason pattern 4 was defined as clinically significant prostate cancer. The detection rates of multiparametric magnetic resonance imaging and fusion guided targeted biopsy were compared with the detection rate of transperineal template saturation prostate biopsy using the McNemar test. We obtained a median of 40 (range 30 to 55) and 3 (range 2 to 4) transperineal template saturation prostate biopsy and fusion guided targeted biopsy cores, respectively. Of the 124 patients (29.9%) without a suspicious lesion on multiparametric magnetic resonance imaging 32 (25.8%) were found to have clinically significant prostate cancer on transperineal template saturation prostate biopsy. Of the 291 patients (70.1%) with a Likert score of 3 to 5 clinically significant prostate cancer was detected in 129 (44.3%) by multiparametric magnetic resonance imaging fusion guided targeted biopsy, in 176 (60.5%) by transperineal template saturation prostate biopsy and in 187 (64.3%) by the combined approach. Overall 58 cases (19.9%) of clinically significant prostate cancer would have been missed if fusion guided targeted biopsy had been performed exclusively. The sensitivity of
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Quirion, Nate
Unmanned Aerial Systems (UASs) today are fulfilling more roles than ever before. There is a general push to have these systems feature more advanced autonomous capabilities in the near future. To achieve autonomous behavior requires some unique approaches to control and decision making. More advanced versions of these approaches are able to adapt their own behavior and examine their past experiences to increase their future mission performance. To achieve adaptive behavior and decision making capabilities this study used Reinforcement Learning algorithms. In this research the effects of sensor performance, as modeled through Signal Detection Theory (SDT), on the ability of RL algorithms to accomplish a target localization task are examined. Three levels of sensor sensitivity are simulated and compared to the results of the same system using a perfect sensor. To accomplish the target localization task, a hierarchical architecture used two distinct agents. A simulated human operator is assumed to be a perfect decision maker, and is used in the system feedback. An evaluation of the system is performed using multiple metrics, including episodic reward curves and the time taken to locate all targets. Statistical analyses are employed to detect significant differences in the comparison of steady-state behavior of different systems.
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Breaking camouflage and detecting targets require optic flow and image structure information.
Pan, Jing Samantha; Bingham, Ned; Chen, Chang; Bingham, Geoffrey P
2017-08-01
Use of motion to break camouflage extends back to the Cambrian [In the Blink of an Eye: How Vision Sparked the Big Bang of Evolution (New York Basic Books, 2003)]. We investigated the ability to break camouflage and continue to see camouflaged targets after motion stops. This is crucial for the survival of hunting predators. With camouflage, visual targets and distracters cannot be distinguished using only static image structure (i.e., appearance). Motion generates another source of optical information, optic flow, which breaks camouflage and specifies target locations. Optic flow calibrates image structure with respect to spatial relations among targets and distracters, and calibrated image structure makes previously camouflaged targets perceptible in a temporally stable fashion after motion stops. We investigated this proposal using laboratory experiments and compared how many camouflaged targets were identified either with optic flow information alone or with combined optic flow and image structure information. Our results show that the combination of motion-generated optic flow and target-projected image structure information yielded efficient and stable perception of camouflaged targets.
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Gangwar, Maulshree
2012-09-23
A SYBR Green™ I-based real-time multiplexed PCR assay was developed targeting invA and spvB for the detection of Salmonella strains in shellfish after both hns and invA genes were identified in all Salmonella strains. Simultaneously, the 16S rRNA gene was used as a PCR internal amplification control (IAC). All 89 Salmonella strains tested in this study exhibited amplification of invA, whereas only 21 (23. 6 %) were PCR positive for spvB. The sensitivity of detection of all three targeted genes was 1 ng, which is equivalent to approximately 105 colony-forming unit (CFU) of Salmonella enterica. The analysis showed specific PCR products that were identified by reproducible melt temperature profiles (invA, 84. 27 ± 1. 7 °C; spvB, 88. 76 ± 1. 0 °C; and 16S rRNA gene, 87. 16 ± 0. 8 °C). The sensitivity of detection was 10 pg purified DNA (invA) or 105 CFU in 1 mL pure culture of S. enterica ATCC 14028. The above molecular detection method for Salmonella strains was successfully applied to the oyster homogenates (food matrix). An initial inoculum of 106 and 102 CFU Salmonella in 1 ml seeded oyster tissue homogenate was detected by multiplexed PCR for all three genes after 5 and 24 h of enrichment, respectively. Natural oysters isolated from Gulf of Mexico during the winter months exhibited negative PCR amplification results suggesting the absence of Salmonella. In contrast to conventional PCR, real-time multiplex PCR assay developed in this study is rapid and sensitive and will help Interstate Shellfish Sanitation Conference undertake appropriate measures to monitor Salmonella in oysters, thereby preventing disease outbreaks and consequently protecting consumer health. © 2012 Springer Science+Business Media, LLC.
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Gangwar, Maulshree; Waters, Alicia M.; Bej, Gautam A.; Bej, Asim K.; Mojib, Nazia
2012-01-01
A SYBR Green™ I-based real-time multiplexed PCR assay was developed targeting invA and spvB for the detection of Salmonella strains in shellfish after both hns and invA genes were identified in all Salmonella strains. Simultaneously, the 16S rRNA gene was used as a PCR internal amplification control (IAC). All 89 Salmonella strains tested in this study exhibited amplification of invA, whereas only 21 (23. 6 %) were PCR positive for spvB. The sensitivity of detection of all three targeted genes was 1 ng, which is equivalent to approximately 105 colony-forming unit (CFU) of Salmonella enterica. The analysis showed specific PCR products that were identified by reproducible melt temperature profiles (invA, 84. 27 ± 1. 7 °C; spvB, 88. 76 ± 1. 0 °C; and 16S rRNA gene, 87. 16 ± 0. 8 °C). The sensitivity of detection was 10 pg purified DNA (invA) or 105 CFU in 1 mL pure culture of S. enterica ATCC 14028. The above molecular detection method for Salmonella strains was successfully applied to the oyster homogenates (food matrix). An initial inoculum of 106 and 102 CFU Salmonella in 1 ml seeded oyster tissue homogenate was detected by multiplexed PCR for all three genes after 5 and 24 h of enrichment, respectively. Natural oysters isolated from Gulf of Mexico during the winter months exhibited negative PCR amplification results suggesting the absence of Salmonella. In contrast to conventional PCR, real-time multiplex PCR assay developed in this study is rapid and sensitive and will help Interstate Shellfish Sanitation Conference undertake appropriate measures to monitor Salmonella in oysters, thereby preventing disease outbreaks and consequently protecting consumer health. © 2012 Springer Science+Business Media, LLC.
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SPMK AND GRABCUT BASED TARGET EXTRACTION FROM HIGH RESOLUTION REMOTE SENSING IMAGES
Directory of Open Access Journals (Sweden)
W. Cui
2016-06-01
Full Text Available Target detection and extraction from high resolution remote sensing images is a basic and wide needed application. In this paper, to improve the efficiency of image interpretation, we propose a detection and segmentation combined method to realize semi-automatic target extraction. We introduce the dense transform color scale invariant feature transform (TC-SIFT descriptor and the histogram of oriented gradients (HOG & HSV descriptor to characterize the spatial structure and color information of the targets. With the k-means cluster method, we get the bag of visual words, and then, we adopt three levels’ spatial pyramid (SP to represent the target patch. After gathering lots of different kinds of target image patches from many high resolution UAV images, and using the TC-SIFT-SP and the multi-scale HOG & HSV feature, we constructed the SVM classifier to detect the target. In this paper, we take buildings as the targets. Experiment results show that the target detection accuracy of buildings can reach to above 90%. Based on the detection results which are a series of rectangle regions of the targets. We select the rectangle regions as candidates for foreground and adopt the GrabCut based and boundary regularized semi-auto interactive segmentation algorithm to get the accurate boundary of the target. Experiment results show its accuracy and efficiency. It can be an effective way for some special targets extraction.
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Spmk and Grabcut Based Target Extraction from High Resolution Remote Sensing Images
Cui, Weihong; Wang, Guofeng; Feng, Chenyi; Zheng, Yiwei; Li, Jonathan; Zhang, Yi
2016-06-01
Target detection and extraction from high resolution remote sensing images is a basic and wide needed application. In this paper, to improve the efficiency of image interpretation, we propose a detection and segmentation combined method to realize semi-automatic target extraction. We introduce the dense transform color scale invariant feature transform (TC-SIFT) descriptor and the histogram of oriented gradients (HOG) & HSV descriptor to characterize the spatial structure and color information of the targets. With the k-means cluster method, we get the bag of visual words, and then, we adopt three levels' spatial pyramid (SP) to represent the target patch. After gathering lots of different kinds of target image patches from many high resolution UAV images, and using the TC-SIFT-SP and the multi-scale HOG & HSV feature, we constructed the SVM classifier to detect the target. In this paper, we take buildings as the targets. Experiment results show that the target detection accuracy of buildings can reach to above 90%. Based on the detection results which are a series of rectangle regions of the targets. We select the rectangle regions as candidates for foreground and adopt the GrabCut based and boundary regularized semi-auto interactive segmentation algorithm to get the accurate boundary of the target. Experiment results show its accuracy and efficiency. It can be an effective way for some special targets extraction.
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Human synthetic lethal inference as potential anti-cancer target gene detection
Directory of Open Access Journals (Sweden)
Solé Ricard V
2009-12-01
Full Text Available Abstract Background Two genes are called synthetic lethal (SL if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism's fitness. The detection of SL gene pairs constitutes a promising alternative for anti-cancer therapy. As cancer cells exhibit a large number of mutations, the identification of these mutated genes' SL partners may provide specific anti-cancer drug candidates, with minor perturbations to the healthy cells. Since existent SL data is mainly restricted to yeast screenings, the road towards human SL candidates is limited to inference methods. Results In the present work, we use phylogenetic analysis and database manipulation (BioGRID for interactions, Ensembl and NCBI for homology, Gene Ontology for GO attributes in order to reconstruct the phylogenetically-inferred SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases as well as on existent approved drugs (DrugBank database supports our selection of cancer-therapy candidates. Conclusions Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology.
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Xu, Ke; Xu, Chen; Zhang, Yanzhenzi; Qi, Feiran; Yu, Bingran; Li, Ping; Jia, Lixin; Li, Yulin; Xu, Fu-jian; Du, Jie
2018-01-01
Thoracic aortic dissection (TAD) is an aggressive and life-threatening vascular disease and there is no effective means of early diagnosis of dissection. Type IV collagen (Col-IV) is a major component of the sub-endothelial basement membrane, which is initially exposed followed by endothelial injury as early-stage event of TAD. So, we want to build a noninvasive diagnostic method to detect early dissection by identifying the exposed Col-IV via MRI. Methods: Col-IV-targeted magnetic resonance/ fluorescence dual probe (Col-IV-DOTA-Gd-rhodamine B; CDR) was synthesized by amide reaction and coordination reaction. Flow cytometry analysis was used to evaluate the cell viability of SMC treated with CDR and fluorescence assays were used to assess the Col-IV targeting ability of CDR in vitro. We then examined the sensitivity and specificity of CDR at different stages of TAD via MRI and bioluminescence imaging in vivo. Results: The localization of Col-IV (under the intima) was observed by histology images. CDR bound specifically to Col-IV-expressing vascular smooth muscle cells and BAPN-induced dissected aorta. The CDR signal was co-detected by magnetic resonance imaging (MRI) and bioluminescence imaging as early as 2 weeks after BAPN administration (pre-dissection stage). The ability to detect rupture of dissected aorta was indicated by a strong normalized signal enhancement (NSE) in vivo. Moreover, NSE was negatively correlated with the time of dissection rupture after BAPN administration (r2 = 0.8482). Conclusion: As confirmed by in vivo studies, the CDR can identify the exposed Col-IV in degenerated aorta to monitor the progress of aortic dissection from the early stage to the rupture via MRI. Thus, CDR-enhanced MRI proposes a potential method for dissection screening, and for monitoring disease progression and therapeutic response. PMID:29290819
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Investigations of internal noise levels for different target sizes, contrasts, and noise structures
Han, Minah; Choi, Shinkook; Baek, Jongduk
2014-03-01
To describe internal noise levels for different target sizes, contrasts, and noise structures, Gaussian targets with four different sizes (i.e., standard deviation of 2,4,6 and 8) and three different noise structures(i.e., white, low-pass, and highpass) were generated. The generated noise images were scaled to have standard deviation of 0.15. For each noise type, target contrasts were adjusted to have the same detectability based on NPW, and the detectability of CHO was calculated accordingly. For human observer study, 3 trained observers performed 2AFC detection tasks, and correction rate, Pc, was calculated for each task. By adding proper internal noise level to numerical observer (i.e., NPW and CHO), detectability of human observer was matched with that of numerical observers. Even though target contrasts were adjusted to have the same detectability of NPW observer, detectability of human observer decreases as the target size increases. The internal noise level varies for different target sizes, contrasts, and noise structures, demonstrating different internal noise levels should be considered in numerical observer to predict the detection performance of human observer.
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Tan, Teck Wei; Png, Keng Siang; Lee, Chau Hung; Yuwono, Arianto; Yeow, Yuyi; Chong, Kian Tai; Lee, Yee Mun; Tan, Cher Heng; Tan, Yung Khan
2017-11-01
To test the hypothesis that targeted biopsy has a higher detection rate for clinically significant prostate cancer (csPCa) than systematic biopsy. We defined csPCa as any Gleason sum ≥7 cancer. In patients with Prostate Imaging Reporting and Data System (PI-RADS) 3 lesions, to determine if factors, such as prostate-specific antigen density (PSAD) and prostate health index (PHI), can predict csPCa and help select patients for biopsy. We report the first series of targeted biopsies in Southeast Asian men, with comparison against systematic biopsy. Consecutive patients were registered into a prospective institutional review board-approved database in our institution. We reviewed patients who underwent biopsy from May 2016 to June 2017. Inclusion criteria for our study were patients with at least one PI-RADS ≥3, and who underwent both targeted and systematic biopsies in the same sitting. There were 115 patients in the study, of whom 74 (64.3%) had a previous negative systematic biopsy. Targeted biopsies detected significantly less Gleason 6 cancers than systematic biopsies (p < 0.01), and demonstrated significantly higher sensitivity, specificity, positive predictive value, and negative predictive value (NPV) for the detection of csPCa. For patients with PI-RADS 3 lesions, PHI and PSAD were found to be the best predictors for csPCa. PSAD <0.10 ng/mL/mL had an NPV of 93% and sensitivity of 92%, while allowing 20% of patients to avoid biopsy. PHI cutoff of <27 would allow 34% of patients to avoid biopsy, with both sensitivity and NPV of 100%. Targeted prostate biopsies were found to be significantly superior to systematic biopsies for the detection of csPCa, while detecting less Gleason 6 cancer. Usage of PSAD and PHI cutoff levels in patients with PI-RADS 3 lesions may enable a number of patients to avoid unnecessary biopsy.
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He, Jincan; Li, Gongke; Hu, Yuling
2015-11-03
Poor selectivity and biocompability remain problems in applying surface-enhanced Raman spectroscopy (SERS) for direct detection of proteins due to similar spectra of most proteins and overlapping Raman bands in complex mixtures. To solve these problems, an aptamer recognition induced target-bridged strategy based on magnetic chitosan (MCS) and silver/chitosan nanoparticles (Ag@CS NPs) using SERS was developed for detection of protein benefiting from specific affinity of aptamers and biocompatibility of chitosan (CS). In this process, one aptamer (or antibody) modified MCS worked as capture probes through the affinity binding site of protein. The other aptamer modified Raman report molecules encapsulated Ag@CS NPs were used as SERS sensing probes based on the other binding site of protein. The sandwich complexes of aptamer (antibody)/protein/aptamer were separated easily with a magnet from biological samples, and the concentration of protein was indirectly reflected by the intensity variation of SERS signal of Raman report molecules. To explore the universality of the strategy, three different kinds of proteins including thrombin, platelet derived growth factor BB (PDGF BB) and immunoglobulin E (lgE) were investigated. The major advantages of this aptamer recognition induced target-bridged strategy are convenient operation with a magnet, stable signal expressing resulting from preventing loss of report molecules with the help of CS shell, and the avoidance of slow diffusion-limited kinetics problems occurring on a solid substrate. To demonstrate the feasibility of the proposed strategy, the method was applied to detection of PDGF BB in clinical samples. The limit of detection (LOD) of PDGF BB was estimated to be 3.2 pg/mL. The results obtained from human serum of healthy persons and cancer patients using the proposed strategy showed good agreement with that of the ELISA method but with wider linear range, more convenient operation, and lower cost. The proposed
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Effects of Resolution, Range, and Image Contrast on Target Acquisition Performance.
Hollands, Justin G; Terhaar, Phil; Pavlovic, Nada J
2018-05-01
We sought to determine the joint influence of resolution, target range, and image contrast on the detection and identification of targets in simulated naturalistic scenes. Resolution requirements for target acquisition have been developed based on threshold values obtained using imaging systems, when target range was fixed, and image characteristics were determined by the system. Subsequent work has examined the influence of factors like target range and image contrast on target acquisition. We varied the resolution and contrast of static images in two experiments. Participants (soldiers) decided whether a human target was located in the scene (detection task) or whether a target was friendly or hostile (identification task). Target range was also varied (50-400 m). In Experiment 1, 30 participants saw color images with a single target exemplar. In Experiment 2, another 30 participants saw monochrome images containing different target exemplars. The effects of target range and image contrast were qualitatively different above and below 6 pixels per meter of target for both tasks in both experiments. Target detection and identification performance were a joint function of image resolution, range, and contrast for both color and monochrome images. The beneficial effects of increasing resolution for target acquisition performance are greater for closer (larger) targets.
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The application of unattended ground sensors to stationary targets
International Nuclear Information System (INIS)
Sleefe, G.E.; Peglow, S.; Hamrick, R.
1997-01-01
The unattended sensing of stationary (i.e. non-mobile) targets is important in applications ranging from counter-proliferation to law enforcement. With stationary targets, sources of seismic, acoustic, and electro-magnetic emissions can potentially be used to detect, identify, and locate the target. Stationary targets have considerably different sensing requirements than the traditional mobile-target unattended ground sensor applications. This paper presents the novel features and requirements of a system for sensing stationary targets. In particular, issues associated with long-listen time signal processing for signal detection, and array processing techniques for signal localization are presented. Example data and signal processing outputs from a stationary target will be used to illustrate these issues. The impact on sensor, electronic signal processing, battery subsystem, and communication requirements will also be discussed. The paper will conclude with a detailed comparison between mobile-target and stationary-target unattended ground sensor architectures
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Marchant, Jennifer L; Ruff, Christian C; Driver, Jon
2012-01-01
The brain seeks to combine related inputs from different senses (e.g., hearing and vision), via multisensory integration. Temporal information can indicate whether stimuli in different senses are related or not. A recent human fMRI study (Noesselt et al. [2007]: J Neurosci 27:11431–11441) used auditory and visual trains of beeps and flashes with erratic timing, manipulating whether auditory and visual trains were synchronous or unrelated in temporal pattern. A region of superior temporal sulcus (STS) showed higher BOLD signal for the synchronous condition. But this could not be related to performance, and it remained unclear if the erratic, unpredictable nature of the stimulus trains was important. Here we compared synchronous audiovisual trains to asynchronous trains, while using a behavioral task requiring detection of higher-intensity target events in either modality. We further varied whether the stimulus trains had predictable temporal pattern or not. Synchrony (versus lag) between auditory and visual trains enhanced behavioral sensitivity (d') to intensity targets in either modality, regardless of predictable versus unpredictable patterning. The analogous contrast in fMRI revealed BOLD increases in several brain areas, including the left STS region reported by Noesselt et al. [2007: J Neurosci 27:11431–11441]. The synchrony effect on BOLD here correlated with the subject-by-subject impact on performance. Predictability of temporal pattern did not affect target detection performance or STS activity, but did lead to an interaction with audiovisual synchrony for BOLD in inferior parietal cortex. PMID:21953980
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Fusion and normalization to enhance anomaly detection
Mayer, R.; Atkinson, G.; Antoniades, J.; Baumback, M.; Chester, D.; Edwards, J.; Goldstein, A.; Haas, D.; Henderson, S.; Liu, L.
2009-05-01
This study examines normalizing the imagery and the optimization metrics to enhance anomaly and change detection, respectively. The RX algorithm, the standard anomaly detector for hyperspectral imagery, more successfully extracts bright rather than dark man-made objects when applied to visible hyperspectral imagery. However, normalizing the imagery prior to applying the anomaly detector can help detect some of the problematic dark objects, but can also miss some bright objects. This study jointly fuses images of RX applied to normalized and unnormalized imagery and has a single decision surface. The technique was tested using imagery of commercial vehicles in urban environment gathered by a hyperspectral visible/near IR sensor mounted in an airborne platform. Combining detections first requires converting the detector output to a target probability. The observed anomaly detections were fitted with a linear combination of chi square distributions and these weights were used to help compute the target probability. Receiver Operator Characteristic (ROC) quantitatively assessed the target detection performance. The target detection performance is highly variable depending on the relative number of candidate bright and dark targets and false alarms and controlled in this study by using vegetation and street line masks. The joint Boolean OR and AND operations also generate variable performance depending on the scene. The joint SUM operation provides a reasonable compromise between OR and AND operations and has good target detection performance. In addition, new transforms based on normalizing correlation coefficient and least squares generate new transforms related to canonical correlation analysis (CCA) and a normalized image regression (NIR). Transforms based on CCA and NIR performed better than the standard approaches. Only RX detection of the unnormalized of the difference imagery in change detection provides adequate change detection performance.
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Masking of Time-Frequency Patterns in Applications of Passive Underwater Target Detection
Directory of Open Access Journals (Sweden)
Jüri Sildam
2010-01-01
Full Text Available Spectrogram analysis of acoustical sounds for underwater target classification is utilized when loud nonstationary interference sources overlap with a signal of interest in time but can be separated in time-frequency (TF domain. We propose a signal masking method which in a TF plane combines local statistical and morphological features of the signal of interest. A dissimilarity measure D of adjacent TF cells is used for local estimation of entropy H, followed by estimation of ΔH=Htc−Hfc entropy difference, where Hfc is calculated along the time axis at a mean frequency fc and Htc is calculated along the frequency axis at a mean time tc of the TF window, respectively. Due to a limited number of points used in ΔH estimation, the number of possible ΔH values, which define a primary mask, is also limited. A secondary mask is defined using morphological operators applied to, for example, H and ΔH. We demonstrate how primary and secondary masks can be used for signal detection and discrimination, respectively. We also show that the proposed approach can be generalized within the framework of Genetic Programming.
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Memory for found targets interferes with subsequent performance in multiple-target visual search.
Cain, Matthew S; Mitroff, Stephen R
2013-10-01
Multiple-target visual searches--when more than 1 target can appear in a given search display--are commonplace in radiology, airport security screening, and the military. Whereas 1 target is often found accurately, additional targets are more likely to be missed in multiple-target searches. To better understand this decrement in 2nd-target detection, here we examined 2 potential forms of interference that can arise from finding a 1st target: interference from the perceptual salience of the 1st target (a now highly relevant distractor in a known location) and interference from a newly created memory representation for the 1st target. Here, we found that removing found targets from the display or making them salient and easily segregated color singletons improved subsequent search accuracy. However, replacing found targets with random distractor items did not improve subsequent search accuracy. Removing and highlighting found targets likely reduced both a target's visual salience and its memory load, whereas replacing a target removed its visual salience but not its representation in memory. Collectively, the current experiments suggest that the working memory load of a found target has a larger effect on subsequent search accuracy than does its perceptual salience. PsycINFO Database Record (c) 2013 APA, all rights reserved.
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International Nuclear Information System (INIS)
Kim, K.; Murphy, M.J.
1982-04-01
Techniques for fabricating cryogenic inertial confinement fusion targets (i.e., spherical shells containing a uniform layer of DT ice) are investigated using target free-fall concept. Detection and characterization of the moving targets are effected by optoelectronic means, of which the principal is an RF ac-interferometer. This interferometer system demonstrates, for the first time, the speed capabilities of the phase-modulation ac-interferometry. New techiques developed for handling, holding, launching, and transporting targets are also described. Results obtained at both room and cryogenic temperatures are presented
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Nucleic acid detection system and method for detecting influenza
Cai, Hong; Song, Jian
2015-03-17
The invention provides a rapid, sensitive and specific nucleic acid detection system which utilizes isothermal nucleic acid amplification in combination with a lateral flow chromatographic device, or DNA dipstick, for DNA-hybridization detection. The system of the invention requires no complex instrumentation or electronic hardware, and provides a low cost nucleic acid detection system suitable for highly sensitive pathogen detection. Hybridization to single-stranded DNA amplification products using the system of the invention provides a sensitive and specific means by which assays can be multiplexed for the detection of multiple target sequences.
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Biologically Inspired Target Recognition in Radar Sensor Networks
Directory of Open Access Journals (Sweden)
Liang Qilian
2010-01-01
Full Text Available One of the great mysteries of the brain is cognitive control. How can the interactions between millions of neurons result in behavior that is coordinated and appears willful and voluntary? There is consensus that it depends on the prefrontal cortex (PFC. Many PFC areas receive converging inputs from at least two sensory modalities. Inspired by human's innate ability to process and integrate information from disparate, network-based sources, we apply human-inspired information integration mechanisms to target detection in cognitive radar sensor network. Humans' information integration mechanisms have been modelled using maximum-likelihood estimation (MLE or soft-max approaches. In this paper, we apply these two algorithms to cognitive radar sensor networks target detection. Discrete-cosine-transform (DCT is used to process the integrated data from MLE or soft-max. We apply fuzzy logic system (FLS to automatic target detection based on the AC power values from DCT. Simulation results show that our MLE-DCT-FLS and soft-max-DCT-FLS approaches perform very well in the radar sensor network target detection, whereas the existing 2D construction algorithm does not work in this study.
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A Study of Adaptive Detection of Range-Distributed Targets
National Research Council Canada - National Science Library
Gerlach, Karl R
2000-01-01
.... The unknown parameters associated with the hypothesis test are the complex amplitudes in range of the desired target and the unknown covariance matrix of the additive interference, which is assumed...
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SeedVicious: Analysis of microRNA target and near-target sites.
Marco, Antonio
2018-01-01
Here I describe seedVicious, a versatile microRNA target site prediction software that can be easily fitted into annotation pipelines and run over custom datasets. SeedVicious finds microRNA canonical sites plus other, less efficient, target sites. Among other novel features, seedVicious can compute evolutionary gains/losses of target sites using maximum parsimony, and also detect near-target sites, which have one nucleotide different from a canonical site. Near-target sites are important to study population variation in microRNA regulation. Some analyses suggest that near-target sites may also be functional sites, although there is no conclusive evidence for that, and they may actually be target alleles segregating in a population. SeedVicious does not aim to outperform but to complement existing microRNA prediction tools. For instance, the precision of TargetScan is almost doubled (from 11% to ~20%) when we filter predictions by the distance between target sites using this program. Interestingly, two adjacent canonical target sites are more likely to be present in bona fide target transcripts than pairs of target sites at slightly longer distances. The software is written in Perl and runs on 64-bit Unix computers (Linux and MacOS X). Users with no computing experience can also run the program in a dedicated web-server by uploading custom data, or browse pre-computed predictions. SeedVicious and its associated web-server and database (SeedBank) are distributed under the GPL/GNU license.
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Nie, Liju; Li, Fulai; Huang, Xiaolin; Aguilar, Zoraida P; Wang, Yongqiang Andrew; Xiong, Yonghua; Fu, Fen; Xu, Hengyi
2018-04-25
Studies regarding circulating tumor cells (CTCs) have great significance for cancer prognosis, treatment monitoring, and metastasis diagnosis. However, due to their extremely low concentration in peripheral blood, isolation and enrichment of CTCs are the key steps for early detection. To this end, targeting the folic acid receptors (FRs) on the CTC surface for capture with folic acid (FA) using bovine serum albumin (BSA)-tether for multibiotin enhancement in combination with streptavidin-coated magnetic nanoparticles (MNPs-SA) was developed for ovarian cancer CTC isolation. The streptavidin-biotin-system-mediated two-step binding strategy was shown to capture CTCs from whole blood efficiently without the need for a pretreatment process. The optimized parameters for this system exhibited an average capture efficiency of 80%, which was 25% higher than that of FA-decorated magnetic nanoparticles based on the one-step CTC separation method. Moreover, the isolated cells remained highly viable and were cultured directly without detachment from the MNPs-SA-biotin-CTC complex. Furthermore, when the system was applied for the isolation and detection of CTCs in ovarian cancer patients' peripheral blood samples, it exhibited an 80% correlation with clinical diagnostic criteria. The results indicated that FA targeting, in combination with BSA-based multibiotin enhancement magnetic nanoparticle separation, is a promising tool for CTC enrichment and detection of early-stage ovarian cancer.
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Knowledge-Base Application to Ground Moving Target Detection
National Research Council Canada - National Science Library
Adve, R
2001-01-01
This report summarizes a multi-year in-house effort to apply knowledge-base control techniques and advanced Space-Time Adaptive Processing algorithms to improve detection performance and false alarm...
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Detection of low-energy antinuclei in space using an active-target particle detector
Energy Technology Data Exchange (ETDEWEB)
Poeschl, Thomas; Greenwald, Daniel; Konorov, Igor; Paul, Stephan [Physics Department E18, Technische Universitaet Muenchen (Germany); Losekamm, Martin [Physics Department E18, Technische Universitaet Muenchen (Germany); Institute of Astronautics, Technische Universitaet Muenchen (Germany)
2015-07-01
Measuring antimatter in space excellently probes various astrophysical processes. The abundances and energy spectra of antiparticles reveal a lot about the creation and propagation of cosmic-ray particles in the universe. Abnormalities in their spectra can reveal exotic sources or inaccuracies in our understanding of the involved processes. The measurement of antiprotons and the search for antideuterons and antihelium are optimal at low kinetic energies since background from high-energy cosmic-ray collisions is low. For this reason, we are developing an active-target particle detector capable of detecting ions and anti-ions in the energy range of 30-100 MeV per nucleon. The detector consists of 900 scintillating fibers coupled to silicon photomultipliers and is designed to operate on nanosatellites. The primary application of the detector will be the Antiproton Flux in Space (AFIS) mission, whose goal is the measurement of geomagnetically trapped antiprotons inside Earth's inner radiation belt. In this talk, we explain our particle identification technique and present results from first in-beam measurements with a prototype.
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Galaj, Ewa; Ewing, Scott; Ranaldi, Robert
2018-06-01
In the search for efficacious pharmacotherapies to treat cocaine addiction much attention has been given to agents targeting dopamine D1 or D3 receptors because of the involvement of these receptors in drug-related behaviors. D1-like and D3 receptor partial agonists and antagonists have been shown to reduce drug reward, reinstatement of drug seeking and conditioned place preference in rodents and non-human primates. However, translation of these encouraging results to clinical settings has been limited due to a number of factors including toxicity, poor pharmacokinetic properties and extrapyramidal and sedative side effects. This review highlights the role of D1 and D3 receptors in drug reward and seeking, the discovery of D1-D3 heteromers and their potential as targets in the treatment of addiction. Copyright © 2018 Elsevier Ltd. All rights reserved.
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Energy Technology Data Exchange (ETDEWEB)
O-Thong, Sompong [Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet Bg 115, DK-2800, Kgs Lyngby (Denmark); Department of Biology, Faculty of Science, Thaksin University, Patthalung 93110 (Thailand); Prasertsan, Poonsuk [Department of Industrial Biotechnology, Faculty of Agro-Industry, Prince of Songkla University, Hat-Yai, Songkhla 90112 (Thailand); Karakashev, Dimitar; Angelidaki, Irini [Department of Environmental Engineering, Technical University of Denmark, Bygningstorvet Bg 115, DK-2800, Kgs Lyngby (Denmark)
2008-11-15
16S rRNA gene targeted oligonucleotide probes for specific detection of genera Thermoanaerobacterium (Tbm1282), Caldicellulosiruptor (Ccs432), and specie Thermoanaerobacterium thermosaccharolyticum (Tbmthsacc184) were designed and used to monitor the spatial distribution of hydrogen producing bacteria in sludge and granules from anaerobic reactors. The designed probes were checked for their specificity and then validated using fluorescence in situ hybridization with target microorganisms and non-target microorganisms. Thermoanaerobacterium spp., T. thermosaccharolyticum and Caldicellulosiruptor spp. were detected with the probes designed with coverage of 75%, 100% and 93%, respectively. Thermophilic (60 C) hydrogen producing reactors, one fed with sucrose and another, fed with palm oil mill effluent comprised of following major groups of hydrogen producers: Thermoanaerobacterium spp. (49% and 36%), T. thermosaccharolyticum (16% and 10%), phylum Firmicutes (low G+C) gram positive bacteria (15% and 27%). Extreme-thermophilic (70 C) hydrogen producing reactors, one fed with xylose and another, fed with lignocellulosic hydrolysate comprised of following major groups of hydrogen producers: Caldicellulosiruptor spp. (40.5% and 20.5%), phylum Firmicutes (low G+C) gram positive bacteria (17% and 20%), Archaea (7% and 8.5%), and Thermoanaerobacterium spp. (0% and 5%). Results obtained, showed good applicability of the probes Tbm1282, Tbmthsacc184 and Ccs432 for specific detection and quantification of thermophilic and extreme-thermophilic hydrogen producers in complex environments. (author)
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Amplification of biological targets via on-chip culture for biosensing
Harper, Jason C.; Edwards, Thayne L.; Carson, Bryan; Finley, Melissa; Arndt, William
2018-01-02
The present invention, in part, relates to methods and apparatuses for on-chip amplification and/or detection of various targets, including biological targets and any amplifiable targets. In some examples, the microculture apparatus includes a single-use, normally-closed fluidic valve that is initially maintained in the closed position by a valve element bonded to an adhesive coating. The valve is opened using a magnetic force. The valve element includes a magnetic material or metal. Such apparatuses and methods are useful for in-field or real-time detection of targets, especially in limited resource settings.
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Enzyme detection by microfluidics
DEFF Research Database (Denmark)
2013-01-01
Microfluidic-implemented methods of detecting an enzyme, in particular a DNA-modifying enzyme, are provided, as well as methods for detecting a cell, or a microorganism expressing said enzyme. The enzyme is detected by providing a nucleic acid substrate, which is specifically targeted...... by that enzyme...
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van der Velden, V. H. J.; Willemse, M. J.; van der Schoot, C. E.; Hählen, K.; van Wering, E. R.; van Dongen, J. J. M.
2002-01-01
Immunoglobulin gene rearrangements are used as PCR targets for detection of minimal residual disease (MRD) in acute lymphoblastic leukemia (ALL). We Investigated the occurrence of monoclonal immunoglobulin kappa-deleting element (IGK-Kde) rearrangements by Southern blotting and PCR/heteroduplex
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Energy Technology Data Exchange (ETDEWEB)
Nakamura, Ikuko, E-mail: nakamuri@riken.jp [RIKEN Center for Molecular Imaging Science, Kobe (Japan); Department of Cardiovascular Medicine, Saga University, Saga (Japan); Hasegawa, Koki [RIKEN Center for Molecular Imaging Science, Kobe (Japan); Department of Pathology and Experimental Medicine, Kumamoto University, Kumamoto (Japan); Wada, Yasuhiro [RIKEN Center for Molecular Imaging Science, Kobe (Japan); Hirase, Tetsuaki; Node, Koichi [Department of Cardiovascular Medicine, Saga University, Saga (Japan); Watanabe, Yasuyoshi, E-mail: yywata@riken.jp [RIKEN Center for Molecular Imaging Science, Kobe (Japan)
2013-03-29
Highlights: ► P-selectin regulates leukocyte recruitment as an early stage event of atherogenesis. ► We developed an antibody-based molecular imaging probe targeting P-selectin for PET. ► This is the first report on successful PET imaging for delineation of P-selectin. ► P-selectin is a candidate target for atherosclerotic plaque imaging by clinical PET. -- Abstract: Background: Sensitive detection and qualitative analysis of atherosclerotic plaques are in high demand in cardiovascular clinical settings. The leukocyte–endothelial interaction mediated by an adhesion molecule P-selectin participates in arterial wall inflammation and atherosclerosis. Methods and results: A {sup 64}Cu-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid conjugated anti-P-selectin monoclonal antibody ({sup 64}Cu-DOTA-anti-P-selectin mAb) probe was prepared by conjugating an anti-P-selectin monoclonal antibody with DOTA followed by {sup 64}Cu labeling. Thirty-six hours prior to PET and CT fusion imaging, 3 MBq of {sup 64}Cu-DOTA-anti-P-selectin mAb was intravenously injected into low density lipoprotein receptor-deficient Ldlr-/- mice. After a 180 min PET scan, autoradiography and biodistribution of {sup 64}Cu-DOTA-anti-P-selectin monoclonal antibody was examined using excised aortas. In Ldlr-/- mice fed with a high cholesterol diet for promotion of atherosclerotic plaque development, PET and CT fusion imaging revealed selective and prominent accumulation of the probe in the aortic root. Autoradiography of aortas that demonstrated probe uptake into atherosclerotic plaques was confirmed by Oil red O staining for lipid droplets. In Ldlr-/- mice fed with a chow diet to develop mild atherosclerotic plaques, probe accumulation was barely detectable in the aortic root on PET and CT fusion imaging. Probe biodistribution in aortas was 6.6-fold higher in Ldlr-/- mice fed with a high cholesterol diet than in those fed with a normal chow diet. {sup 64}Cu-DOTA-anti-P-selectin m
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International Nuclear Information System (INIS)
Wu, Shijia; Duan, Nuo; Ma, Xiaoyuan; Xia, Yu; Wang, Hongxin; Wang, Zhouping
2013-01-01
Graphical abstract: -- Highlights: •An ultrasensitive FRET aptasensor was developed for staphylococcal enterotoxin B determination. •SEB was recognized by SEB aptamer with high affinity and specificity. •The Mn 2+ doped NaYF 4 :Yb/Er UCNPs used as donor to quencher dye (BHQ 3 ) in new FRET. •The fluorescence intensity was prominently amplified using an exonuclease-catalyzed target recycling strategy. -- Abstract: An ultrasensitive fluorescence resonance energy transfer (FRET) bioassay was developed to detect staphylococcal enterotoxin B (SEB), a low molecular exotoxin, using an aptamer-affinity method coupled with upconversion nanoparticles (UCNPs)-sensing, and the fluorescence intensity was prominently enhanced using an exonuclease-catalyzed target recycling strategy. To construct this aptasensor, both fluorescence donor probes (complementary DNA 1 –UCNPs) and fluorescence quencher probes (complementary DNA 2 –Black Hole Quencher 3 (BHQ 3 )) were hybridized to an SEB aptamer, and double-strand oligonucleotides were fabricated, which quenched the fluorescence of the UCNPs via FRET. The formation of an aptamer–SEB complex in the presence of the SEB analyte resulted in not only the dissociation of aptamer from the double-strand DNA but also both the disruption of the FRET system and the restoration of the UCNPs fluorescence. In addition, the SEB was liberated from the aptamer–SEB complex using exonuclease I, an exonuclease specific to single-stranded DNA, for analyte recycling by selectively digesting a particular DNA (SEB aptamer). Based on this exonuclease-catalyzed target recycling strategy, an amplified fluorescence intensity could be produced using different SEB concentrations. Using optimized experimental conditions produced an ultrasensitive aptasensor for the detection of SEB, with a wide linear range of 0.001–1 ng mL −1 and a lower detection limit (LOD) of 0.3 pg mL −1 SEB (at 3σ). The fabricated aptasensor was used to measure SEB in a
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Dresen, S; Ferreirós, N; Gnann, H; Zimmermann, R; Weinmann, W
2010-04-01
The multi-target screening method described in this work allows the simultaneous detection and identification of 700 drugs and metabolites in biological fluids using a hybrid triple-quadrupole linear ion trap mass spectrometer in a single analytical run. After standardization of the method, the retention times of 700 compounds were determined and transitions for each compound were selected by a "scheduled" survey MRM scan, followed by an information-dependent acquisition using the sensitive enhanced product ion scan of a Q TRAP hybrid instrument. The identification of the compounds in the samples analyzed was accomplished by searching the tandem mass spectrometry (MS/MS) spectra against the library we developed, which contains electrospray ionization-MS/MS spectra of over 1,250 compounds. The multi-target screening method together with the library was included in a software program for routine screening and quantitation to achieve automated acquisition and library searching. With the help of this software application, the time for evaluation and interpretation of the results could be drastically reduced. This new multi-target screening method has been successfully applied for the analysis of postmortem and traffic offense samples as well as proficiency testing, and complements screening with immunoassays, gas chromatography-mass spectrometry, and liquid chromatography-diode-array detection. Other possible applications are analysis in clinical toxicology (for intoxication cases), in psychiatry (antidepressants and other psychoactive drugs), and in forensic toxicology (drugs and driving, workplace drug testing, oral fluid analysis, drug-facilitated sexual assault).
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Low level photoneutron detection equipment
International Nuclear Information System (INIS)
Ji Changsong; Zhang Yuqin; Li Yuansui
1991-01-01
A low level photoneutron detection equipment has been developed. The photoneutrons produced by interaction of 226 Ra gamma quanta and deutron (D) target are detected with n-n discrimination detector made up of 3 He proportional counter array. The D-content information in the target can be obtained from the measured photoneutron counts. The equipment developed is mainly used for nondestructive D-content measurement of D-devices
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Detection of proteins using a colorimetric bio-barcode assay.
Nam, Jwa-Min; Jang, Kyung-Jin; Groves, Jay T
2007-01-01
The colorimetric bio-barcode assay is a red-to-blue color change-based protein detection method with ultrahigh sensitivity. This assay is based on both the bio-barcode amplification method that allows for detecting miniscule amount of targets with attomolar sensitivity and gold nanoparticle-based colorimetric DNA detection method that allows for a simple and straightforward detection of biomolecules of interest (here we detect interleukin-2, an important biomarker (cytokine) for many immunodeficiency-related diseases and cancers). The protocol is composed of the following steps: (i) conjugation of target capture molecules and barcode DNA strands onto silica microparticles, (ii) target capture with probes, (iii) separation and release of barcode DNA strands from the separated probes, (iv) detection of released barcode DNA using DNA-modified gold nanoparticle probes and (v) red-to-blue color change analysis with a graphic software. Actual target detection and quantification steps with premade probes take approximately 3 h (whole protocol including probe preparations takes approximately 3 days).
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Entering the 'big data' era in medicinal chemistry: molecular promiscuity analysis revisited.
Hu, Ye; Bajorath, Jürgen
2017-06-01
The 'big data' concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein focusing on medicinal chemistry. This is a scientific discipline where big data is beginning to emerge and provide new opportunities. For example, the ability of many drugs to specifically interact with multiple targets, termed promiscuity, forms the molecular basis of polypharmacology, a hot topic in drug discovery. Compound promiscuity analysis is an area that is much influenced by big data phenomena. Different results are obtained depending on chosen data selection and confidence criteria, as we also demonstrate.
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Entering the ‘big data’ era in medicinal chemistry: molecular promiscuity analysis revisited
Hu, Ye; Bajorath, Jürgen
2017-01-01
The ‘big data’ concept plays an increasingly important role in many scientific fields. Big data involves more than unprecedentedly large volumes of data that become available. Different criteria characterizing big data must be carefully considered in computational data mining, as we discuss herein focusing on medicinal chemistry. This is a scientific discipline where big data is beginning to emerge and provide new opportunities. For example, the ability of many drugs to specifically interact with multiple targets, termed promiscuity, forms the molecular basis of polypharmacology, a hot topic in drug discovery. Compound promiscuity analysis is an area that is much influenced by big data phenomena. Different results are obtained depending on chosen data selection and confidence criteria, as we also demonstrate. PMID:28670471
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Towner, Rheal A; Smith, Nataliya; Tesiram, Yasvir A; Abbott, Andrew; Saunders, Debbie; Blindauer, Rebecca; Herlea, Oana; Silasi-Mansat, Robert; Lupu, Florea
2007-01-01
The multifunctional growth factor scatter factor/hepatocyte growth factor and its tyrosine kinase receptor, c-MET, have been implicated in the genesis and malignant progression of numerous human malignancies, including hepatocellular carcinomas. The incidence of hepatocellular carcinomas in the United States has increased noticeably over the past two decades and is listed as the fifth major cancer in men worldwide. In this study, we used a choline-deficient l-amino acid (CDAA)-defined rat hepatocarcinogenesis model to visualize increased in vivo expression of the c-MET antigen in neoplastic lesion formation with the use of a super paramagnetic iron oxide (SPIO)-anti-c-MET molecularly targeted magnetic resonance imaging (MRI) contrast agent. SPIO-anti-c-MET was used for the first time to detect overexpression of c-MET in neoplastic nodules and tumors within the livers of CDAA-treated rats, as determined by a decrease in MRI signal intensity and a decrease in regional T(2) values. Specificity for the binding of the molecularly targeted anti-c-MET contrast agent was determined using rat hepatoma (H4-II-E-C3) cell cultures and immunofluorescence microscopic imaging of the targeting agents within neoplastic liver tissue 1 to 2 hours following intravenous administration of SPIO-anti-c-MET and MRI investigation. This method has the ability to visualize in vivo the overexpression of c-MET at early developmental stages of tumor formation.
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Huang, Xin; Fan, Chengqi; Zhu, Huanhuan; Le, Wenjun; Cui, Shaobin; Chen, Xin; Li, Wei; Zhang, Fulei; Huang, Yong; Sh, Donglu; Cui, Zheng; Shao, Chengwei; Chen, Bingdi
2018-01-01
Pancreatic cancer (PC) has a poor prognosis with high mortality, due to the lack of effective early diagnostic and prognostic tools. In order to target and diagnose PC, we developed a dual-modal imaging probe using Glypican-1 (GPC-1) antibody conjugated with Gd-Au nanoclusters (NCs; Gd-Au-NC-GPC-1). GPC-1 is a type of cell surface heparan sulfate proteoglycan, which is often highly expressed in PC. The probe was successfully prepared with a hydrodynamic diameter ranging from 13.5 to 24.4 nm. Spectral characteristics showed absorption at 280 nm and prominent emission at 650 nm. Confocal microscopic imaging showed effective detection of GPC-1 highly expressed PC cells by Gd-Au-NC-GPC-1, which was consistent with flow cytometry results. In vitro relaxivity characterization demonstrated that the r1 value of the probe was 17.722 s -1 mM -1 Gd, which was almost 4 times higher compared with that of Gd-diethylenetriaminepentacetate (DTPA; r1 value =4.6 s -1 mM -1 Gd). Gd-Au-NC-GPC-1 exhibited similar magnetic resonance (MR) signals when compared to Gd-DTPA even at lower Gd concentrations. Much higher MR signals were registered in PC cells (COLO-357) compared with normal cells (293T). Furthermore, Gd-Au-NC-GPC-1 could effectively detect PC cells in vivo by dual-modal fluorescence imaging/magnetic resonance imaging (FI/MRI) at 30 minutes postinjection. In addition, Gd-Au-NC-GPC-1 did not show significant biotoxicity to normal cells at tested concentrations both in vitro and in vivo. Gd-Au-NC-GPC-1 has demonstrated to be a promising dual-modal FI/MRI contrast agent for targeted diagnosis of PC.
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Zhu, Huanhuan; Le, Wenjun; Cui, Shaobin; Chen, Xin; Li, Wei; Zhang, Fulei; Huang, Yong; Sh, Donglu; Cui, Zheng; Shao, Chengwei; Chen, Bingdi
2018-01-01
Introduction Pancreatic cancer (PC) has a poor prognosis with high mortality, due to the lack of effective early diagnostic and prognostic tools. Materials and methods In order to target and diagnose PC, we developed a dual-modal imaging probe using Glypican-1 (GPC-1) antibody conjugated with Gd–Au nanoclusters (NCs; Gd-Au-NC-GPC-1). GPC-1 is a type of cell surface heparan sulfate proteoglycan, which is often highly expressed in PC. The probe was successfully prepared with a hydrodynamic diameter ranging from 13.5 to 24.4 nm. Results Spectral characteristics showed absorption at 280 nm and prominent emission at 650 nm. Confocal microscopic imaging showed effective detection of GPC-1 highly expressed PC cells by Gd-Au-NC-GPC-1, which was consistent with flow cytometry results. In vitro relaxivity characterization demonstrated that the r1 value of the probe was 17.722 s−1 mM−1 Gd, which was almost 4 times higher compared with that of Gd-diethylenetriaminepentacetate (DTPA; r1 value =4.6 s−1 mM−1 Gd). Gd-Au-NC-GPC-1 exhibited similar magnetic resonance (MR) signals when compared to Gd-DTPA even at lower Gd concentrations. Much higher MR signals were registered in PC cells (COLO-357) compared with normal cells (293T). Furthermore, Gd-Au-NC-GPC-1 could effectively detect PC cells in vivo by dual-modal fluorescence imaging/magnetic resonance imaging (FI/MRI) at 30 minutes postinjection. In addition, Gd-Au-NC-GPC-1 did not show significant biotoxicity to normal cells at tested concentrations both in vitro and in vivo. Conclusion Gd-Au-NC-GPC-1 has demonstrated to be a promising dual-modal FI/MRI contrast agent for targeted diagnosis of PC. PMID:29750031
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Janvier, Monique; Regnault, Béatrice; Grimont, Patrick
2003-09-01
Methylotrophic bacteria are widespread in nature. They may play an important role in the cycling of carbon and in the metabolism of dimethylsulfide in a marine environment. Bacteria belonging to the genus Methylophaga are a unique group of aerobic, halophilic, non-methane-utilizing methylotrophs. Two 16S rRNA-targeted oligonucleotide probes were developed for the specific detection of Methylophaga species, marine methylobacteria, by fluorescence in situ hybridization. Probe MPH-730 was highly specific for all members of the genus Methylophaga while probe MPHm-994 targeted exclusively M. marina. The application of these probes were demonstrated by the detection of Methylophaga species in enrichment cultures from various marine sediments. All isolates recovered were visualized by using the genus specific probe MPH-730. The results were confirmed by 16S rDNA sequencing which demonstrated that all selected isolates belong to Methylophaga. Five isolates could be detected by the M. marina-specific probe MPHm-994 and were confirmed by rRNA gene restriction pattern (ribotyping). With the development of these specific probes, fluorescence in situ hybridization shows that the genus Methylophaga is widespread in marine samples.
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Cucu, Tatiana; De Meulenaer, Bruno; Devreese, Bart
2012-02-01
Soybean (Glycine max) is extensively used all over the world due to its nutritional qualities. However, soybean is included in the "big eight" list of food allergens. According to the EU directive 2007/68/EC, food products containing soybeans have to be labeled in order to protect the allergic consumers. Nevertheless, soybeans can still inadvertently be present in food products. The development of analytical methods for the detection of traces of allergens is important for the protection of allergic consumers. Mass spectrometry of marker proteolytical fragments of protein allergens is growingly recognized as a detection method in food control. However, quantification of soybean at the peptide level is hindered due to limited information regarding specific stable markers derived after proteolytic digestion. The aim of this study was to use MALDI-TOF/MS and MS/MS as a fast screening tool for the identification of stable soybean derived tryptic markers which were still identifiable even if the proteins were subjected to various changes at the molecular level through a number of reactions typically occurring during food processing (denaturation, the Maillard reaction and oxidation). The peptides (401)Val-Arg(410) from the G1 glycinin (Gly m 6) and the (518)Gln-Arg(528) from the α' chain of the β-conglycinin (Gly m 5) proved to be the most stable. These peptides hold potential to be used as targets for the development of new analytical methods for the detection of soybean protein traces in processed foods. Copyright © 2011 Elsevier Inc. All rights reserved.
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Through-Wall Multiple Targets Vital Signs Tracking Based on VMD Algorithm
Directory of Open Access Journals (Sweden)
Jiaming Yan
2016-08-01
Full Text Available Targets located at the same distance are easily neglected in most through-wall multiple targets detecting applications which use the single-input single-output (SISO ultra-wideband (UWB radar system. In this paper, a novel multiple targets vital signs tracking algorithm for through-wall detection using SISO UWB radar has been proposed. Taking advantage of the high-resolution decomposition of the Variational Mode Decomposition (VMD based algorithm, the respiration signals of different targets can be decomposed into different sub-signals, and then, we can track the time-varying respiration signals accurately when human targets located in the same distance. Intensive evaluation has been conducted to show the effectiveness of our scheme with a 0.15 m thick concrete brick wall. Constant, piecewise-constant and time-varying vital signs could be separated and tracked successfully with the proposed VMD based algorithm for two targets, even up to three targets. For the multiple targets’ vital signs tracking issues like urban search and rescue missions, our algorithm has superior capability in most detection applications.
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Deconinck, E; Djiogo, C A Sokeng; Kamugisha, A; Courselle, P
2017-08-01
The consumption of plant food supplements is increasing steadily and more and more, these products are bought through internet. Often the products sold through internet are not registered or declared with a national authority, meaning that no or minimal quality control is performed and that they could contain herbs or plants that are regulated. Stationary Phase Optimized Selectivity Liquid Chromatography (SOS-LC) was evaluated for the development of specific fingerprints, to be used for the detection of targeted plants in plant food supplements. Three commonly used plants in plant food supplements and two regulated plants were used to develop fingerprints with SOS-LC. It was shown that for all plants specific fingerprints could be obtained, allowing the detection of these targeted plants in triturations with different herbal matrices as well as in real samples of suspicious supplements seized by the authorities. For three of the five plants a more specific fingerprint was obtained, compared to the ones developed on traditional columns described in literature. It could therefore be concluded that the combination of segments of different types of stationary phases, as used in SOS-LC, has the potential of becoming a valuable tool in the quality control and the identification of crude herbal or plant material and in the detection of regulated plants in plant food supplements or other herbal preparations. Copyright © 2017 Elsevier B.V. All rights reserved.
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Target scattering characteristics for OAM-based radar
Directory of Open Access Journals (Sweden)
Kang Liu
2018-02-01
Full Text Available The target scattering characteristics are crucial for radar systems. However, there is very little study conducted for the recently developed orbital angular momentum (OAM based radar system. To illustrate the role of OAM-based radar cross section (ORCS, conventional radar equation is modified by taking characteristics of the OAM waves into account. Subsequently, the ORCS is defined in analogy to classical radar cross section (RCS. The unique features of the incident OAM-carrying field are analyzed. The scattered field is derived, and the analytical expressions of ORCSs for metal plate and cylinder targets are obtained. Furthermore, the ORCS and RCS are compared to illustrate the influences of OAM mode number, target size and signal frequency on the ORCS. Analytical studies demonstrate that the mirror-reflection phenomenon disappears and peak values of ORCS are in the non-specular direction. Finally, the ORCS features are summarized to show its advantages in radar target detection. This work can provide theoretical guidance to the design of OAM-based radar as well as the target detection and identification applications.
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Target scattering characteristics for OAM-based radar
Liu, Kang; Gao, Yue; Li, Xiang; Cheng, Yongqiang
2018-02-01
The target scattering characteristics are crucial for radar systems. However, there is very little study conducted for the recently developed orbital angular momentum (OAM) based radar system. To illustrate the role of OAM-based radar cross section (ORCS), conventional radar equation is modified by taking characteristics of the OAM waves into account. Subsequently, the ORCS is defined in analogy to classical radar cross section (RCS). The unique features of the incident OAM-carrying field are analyzed. The scattered field is derived, and the analytical expressions of ORCSs for metal plate and cylinder targets are obtained. Furthermore, the ORCS and RCS are compared to illustrate the influences of OAM mode number, target size and signal frequency on the ORCS. Analytical studies demonstrate that the mirror-reflection phenomenon disappears and peak values of ORCS are in the non-specular direction. Finally, the ORCS features are summarized to show its advantages in radar target detection. This work can provide theoretical guidance to the design of OAM-based radar as well as the target detection and identification applications.
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Ponce-Robles, L; Oller, I; Agüera, A; Trinidad-Lozano, M J; Yuste, F J; Malato, S; Perez-Estrada, L A
2018-08-15
Cork boiling wastewater is a very complex mixture of naturally occurring compounds leached and partially oxidized during the boiling cycles. The effluent generated is recalcitrant and could cause a significant environmental impact. Moreover, if this untreated industrial wastewater enters a municipal wastewater treatment plant it could hamper or reduce the efficiency of most activated sludge degradation processes. Despite the efforts to treat the cork boiling wastewater for reusing purposes, is still not well-known how safe these compounds (original compounds and oxidation by-products) will be. The purpose of this work was to apply an HPLC-high resolution mass spectrometry method and subsequent non-target screening using a multivariate analysis method (PCA), to explore relationships between samples (treatments) and spectral features (masses or compounds) that could indicate changes in formation, degradation or polarity, during coagulation/flocculation (C/F) and photo-Fenton (PhF). Although, most of the signal intensities were reduced after the treatment line, 16 and 4 new peaks were detected to be formed after C/F and PhF processes respectively. The use of this non-target approach showed to be an effective strategy to explore, classify and detect transformation products during the treatment of an unknown complex mixture. Copyright © 2018 Elsevier B.V. All rights reserved.
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Background suppression of infrared small target image based on inter-frame registration
Ye, Xiubo; Xue, Bindang
2018-04-01
We propose a multi-frame background suppression method for remote infrared small target detection. Inter-frame information is necessary when the heavy background clutters make it difficult to distinguish real targets and false alarms. A registration procedure based on points matching in image patches is used to compensate the local deformation of background. Then the target can be separated by background subtraction. Experiments show our method serves as an effective preliminary of target detection.
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DNA-based species detection capabilities using laser transmission spectroscopy.
Mahon, A R; Barnes, M A; Li, F; Egan, S P; Tanner, C E; Ruggiero, S T; Feder, J L; Lodge, D M
2013-01-06
Early detection of invasive species is critical for effective biocontrol to mitigate potential ecological and economic damage. Laser transmission spectroscopy (LTS) is a powerful solution offering real-time, DNA-based species detection in the field. LTS can measure the size, shape and number of nanoparticles in a solution and was used here to detect size shifts resulting from hybridization of the polymerase chain reaction product to nanoparticles functionalized with species-specific oligonucleotide probes or with the species-specific oligonucleotide probes alone. We carried out a series of DNA detection experiments using the invasive freshwater quagga mussel (Dreissena bugensis) to evaluate the capability of the LTS platform for invasive species detection. Specifically, we tested LTS sensitivity to (i) DNA concentrations of a single target species, (ii) the presence of a target species within a mixed sample of other closely related species, (iii) species-specific functionalized nanoparticles versus species-specific oligonucleotide probes alone, and (iv) amplified DNA fragments versus unamplified genomic DNA. We demonstrate that LTS is a highly sensitive technique for rapid target species detection, with detection limits in the picomolar range, capable of successful identification in multispecies samples containing target and non-target species DNA. These results indicate that the LTS DNA detection platform will be useful for field application of target species. Additionally, we find that LTS detection is effective with species-specific oligonucleotide tags alone or when they are attached to polystyrene nanobeads and with both amplified and unamplified DNA, indicating that the technique may also have versatility for broader applications.
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A Magnetic Sensor System for Biological Detection
Li, Fuquan
2015-01-01
Magnetic biosensors detect biological targets through sensing the stray field of magnetic beads which label the targets. Commonly, magnetic biosensors employ the “sandwich” method to immobilize biological targets, i.e., the targets are sandwiched
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Development Of Signal Detection For Radar Navigation System
Directory of Open Access Journals (Sweden)
Theingi Win Hlaing
2017-09-01
Full Text Available This paper aims to evaluate the performance of target detection in the presence of sea clutter. Radar detection of a background of unwanted clutter due to echoes from sea clutter or land is a problem of interest in the radar field. Radar detector has been developed by assuming the radar clutter is Gaussian distributed. However as technology emerges the radar distribution is seen to deviates from the Gaussian assumption. Thus detectors designs based on Gaussian assumption are no longer optimum for detection in non-Gaussian nature. The theory of target detection in Gaussian distributed clutter has been well established and the closed form of the detection performances can be easily obtained. However that is not the case in non-Gaussian clutter distributions. The operation of radar detection is determined by radar detection theory with different types of Swerling target models such as Swerling I II III IV and V. By using MATLAB these signal detection techniques are developed.
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Receptor-targeted metalloradiopharmaceuticals. Final technical report
International Nuclear Information System (INIS)
Green, Mark A.
2000-01-01
Copper (II) and platinum (II) coordination complexes were prepared and characterized. These complexes were designed to afford structural homology with steroidal and non-steroidal estrogens for possible use as receptor-targeted radiopharmaceuticals. While weak affinity for the estrogen receptor was detectable, none would appear to have sufficient receptor-affinity for estrogen-receptor-targeted imaging or therapy
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Geometric shapes inversion method of space targets by ISAR image segmentation
Huo, Chao-ying; Xing, Xiao-yu; Yin, Hong-cheng; Li, Chen-guang; Zeng, Xiang-yun; Xu, Gao-gui
2017-11-01
The geometric shape of target is an effective characteristic in the process of space targets recognition. This paper proposed a method of shape inversion of space target based on components segmentation from ISAR image. The Radon transformation, Hough transformation, K-means clustering, triangulation will be introduced into ISAR image processing. Firstly, we use Radon transformation and edge detection to extract space target's main body spindle and solar panel spindle from ISAR image. Then the targets' main body, solar panel, rectangular and circular antenna are segmented from ISAR image based on image detection theory. Finally, the sizes of every structural component are computed. The effectiveness of this method is verified using typical targets' simulation data.
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Stoltenburg, Regina; Krafčiková, Petra; Víglaský, Viktor; Strehlitz, Beate
2016-09-21
Aptamers for whole cell detection are selected mostly by the Cell-SELEX procedure. Alternatively, the use of specific cell surface epitopes as target during aptamer selections allows the development of aptamers with ability to bind whole cells. In this study, we integrated a formerly selected Protein A-binding aptamer PA#2/8 in an assay format called ELONA (Enzyme-Linked OligoNucleotide Assay) and evaluated the ability of the aptamer to recognise and bind to Staphylococcus aureus presenting Protein A on the cell surface. The full-length aptamer and one of its truncated variants could be demonstrated to specifically bind to Protein A-expressing intact cells of S. aureus, and thus have the potential to expand the portfolio of aptamers that can act as an analytical agent for the specific recognition and rapid detection of the bacterial pathogen. The functionality of the aptamer was found to be based on a very complex, but also highly variable structure. Two structural key elements were identified. The aptamer sequence contains several G-clusters allowing folding into a G-quadruplex structure with the potential of dimeric and multimeric assembly. An inverted repeat able to form an imperfect stem-loop at the 5'-end also contributes essentially to the aptameric function.
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Liang, Beibei; Wang, Baiyan; Ma, Qiujuan; Xie, Caixia; Li, Xian; Wang, Suiping
2018-03-01
Biological thiols, like cysteine (Cys), homocysteine (Hcy) and glutathione (GSH), play crucial roles in biological systems and in lysosomal processes. Highly selective probes for detecting biological thiols in lysomes of living cells are rare. In this work, a lysosome-targetable turn-on fluorescent probe for the detection of thiols in living cells was designed and synthesized based on a 1,8-naphthalimide derivative. The probe has a 4-(2-aminoethyl)morpholine unit as a lysosome-targetable group and an acrylate group as the thiol recognition unit as well as a fluorescence quencher. In the absence of biothiols, the probe displayed weak fluorescence due to the photoinduced electron transfer (PET) process. Upon the addition of biothiols, the probe exhibited an enhanced fluorescence emission centered at 550 nm due to cleavage of the acrylate moiety. The probe had high selectivity toward biothiols. Moreover, the probe features fast response time, excitation in the visible region and ability of working in a wide pH range. The linear response range covers a concentration range of Cys from 1.5 × 10- 7 to 1.0 × 10- 5 mol·L- 1 and the detection limit is 6.9 × 10- 8 mol·L- 1 for Cys. The probe has been successfully applied to the confocal imaging of biothiols in lysosomes of A549 cells with low cell toxicity. Furthermore, the method was successfully applied to the determination of thiols in a complex multicomponent mixture such as human serum, which suggests our proposed method has great potential for diagnostic purposes. All of such good properties prove it can be used to monitor biothiols in lysosomes of living cells and to be a good fluorescent probe for the selective detection of thiols.
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Bistatic Forward Scattering Radar Detection and Imaging
Directory of Open Access Journals (Sweden)
Hu Cheng
2016-06-01
Full Text Available Forward Scattering Radar (FSR is a special type of bistatic radar that can implement image detection, imaging, and identification using the forward scattering signals provided by the moving targets that cross the baseline between the transmitter and receiver. Because the forward scattering effect has a vital significance in increasing the targets’ Radar Cross Section (RCS, FSR is quite advantageous for use in counter stealth detection. This paper first introduces the front line technology used in forward scattering RCS, FSR detection, and Shadow Inverse Synthetic Aperture Radar (SISAR imaging and key problems such as the statistical characteristics of forward scattering clutter, accurate parameter estimation, and multitarget discrimination are then analyzed. Subsequently, the current research progress in FSR detection and SISAR imaging are described in detail, including the theories and experiments. In addition, with reference to the BeiDou navigation satellite, the results of forward scattering experiments in civil aircraft detection are shown. Finally, this paper considers future developments in FSR target detection and imaging and presents a new, promising technique for stealth target detection.
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Multi-target detection and positioning in crowds using multiple camera surveillance
Huang, Jiahu; Zhu, Qiuyu; Xing, Yufeng
2018-04-01
In this study, we propose a pixel correspondence algorithm for positioning in crowds based on constraints on the distance between lines of sight, grayscale differences, and height in a world coordinates system. First, a Gaussian mixture model is used to obtain the background and foreground from multi-camera videos. Second, the hair and skin regions are extracted as regions of interest. Finally, the correspondences between each pixel in the region of interest are found under multiple constraints and the targets are positioned by pixel clustering. The algorithm can provide appropriate redundancy information for each target, which decreases the risk of losing targets due to a large viewing angle and wide baseline. To address the correspondence problem for multiple pixels, we construct a pixel-based correspondence model based on a similar permutation matrix, which converts the correspondence problem into a linear programming problem where a similar permutation matrix is found by minimizing an objective function. The correct pixel correspondences can be obtained by determining the optimal solution of this linear programming problem and the three-dimensional position of the targets can also be obtained by pixel clustering. Finally, we verified the algorithm with multiple cameras in experiments, which showed that the algorithm has high accuracy and robustness.
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Minefield overwatch using moving target indicator radar
Donadio, Anthony; Ewing, Robert; Kenneally, William J.; Santapietro, John J.
1999-07-01
Traditional antipersonnel land mines are an effective military tool, but they are unable to distinguish friend from foe, or civilian from military personnel. The concept described here uses an advanced moving target indicator (MTI) radar to scan the minefield in order to detect movement towards or within the minefield, coupled with visual identification by a human operator and a communication link for command and control. Selected mines in the minefield can then be activated by means of the command link. In order to demonstrate this concept, a 3D, interactive simulation has been developed. This simulation builds on previous work by integrating a detailed analytical model of an MTI radar. This model has been tailored to the specific application of detection of slowly moving dismounted entities immersed in ground clutter. The model incorporates the effects of internal scatterer motion and antenna scanning modulation in order to provide a realistic representation of the detection problem in this environment. The angle information on the MTI target detection is then passed to a virtual 3D sight which cues a human operator to the target location. In addition, radar propagation effects and an experimental design in which the radar itself is used as a command link are explored.
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Pancreatic cancer cell detection by targeted lipid microbubbles and multiphoton imaging
Cromey, Benjamin; McDaniel, Ashley; Matsunaga, Terry; Vagner, Josef; Kieu, Khanh Quoc; Banerjee, Bhaskar
2018-04-01
Surgical resection of pancreatic cancer represents the only chance of cure and long-term survival in this common disease. Unfortunately, determination of a cancer-free margin at surgery is based on one or two tiny frozen section biopsies, which is far from ideal. Not surprisingly, cancer is usually left behind and is responsible for metastatic disease. We demonstrate a method of receptor-targeted imaging using peptide ligands, lipid microbubbles, and multiphoton microscopy that could lead to a fast and accurate way of examining the entire cut surface during surgery. Using a plectin-targeted microbubble, we performed a blinded in-vitro study to demonstrate avid binding of targeted microbubbles to pancreatic cancer cells but not noncancerous cell lines. Further work should lead to a much-needed point-of-care diagnostic test for determining clean margins in oncologic surgery.
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Effect of Various Environmental Stressors on Target Detection, Identification, and Marksmanship
2007-03-01
diverses conditions environnementales difficiles, dont l’exposition à la chaleur et au froid, le bruit, l’exercice épuisant et la privation de sommeil...urban scenario used for marksmanship testing. The arrow indicates a walking target and the centrepiece depicting a poster of a soldier was a permanent... poster of a soldier was a permanent display that was used to hide targets. The heating and cooling protocols caused significant separations in core
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Detecting proxima b's atmosphere with JWST targeting CO
Snellen, I. A G; Désert, J. M.; Waters, L. B.F.M.; Robinson, T; Meadows, V.; van Dishoeck, E.F.; Brandl, B.R.; Henning, T.; Bouwman, J.; Lahuis, F.; Min, M.; Lovis, C.; Dominik, C.; Van Eylen, V.; Sing, D.; Anglada-Escudé, G.; Birkby, J. L.; Brogi, M.
2017-01-01
Exoplanet Proxima b will be an important laboratory for the search for extraterrestrial life for the decades ahead. Here, we discuss the prospects of detecting carbon dioxide at 15 μm using a spectral filtering technique with the Medium Resolution Spectrograph (MRS) mode of the Mid-Infrared
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Different Neuroplasticity for Task Targets and Distractors
Spingath, Elsie Y.; Kang, Hyun Sug; Plummer, Thane; Blake, David T.
2011-01-01
Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from nonselective
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Different neuroplasticity for task targets and distractors.
Directory of Open Access Journals (Sweden)
Elsie Y Spingath
2011-01-01
Full Text Available Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from
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Zhang, Pu; Wu, Xiaoyan; Yuan, Ruo; Chai, Yaqin
2015-03-17
In this study, an off-on switching of a dual amplified electrochemiluminescence (ECL) biosensor based on Pb(2+)-induced DNAzyme-assisted target recycling and rolling circle amplification (RCA) was constructed for microRNA (miRNA) detection. First, the primer probe with assistant probe and miRNA formed Y junction which was cleaved with the addition of Pb(2+) to release miRNA. Subsequently, the released miRNA could initiate the next recycling process, leading to the generation of numerous intermediate DNA sequences (S2). Afterward, bare glassy carbon electrode (GCE) was immersed into HAuCl4 solution to electrodeposit a Au nanoparticle layer (depAu), followed by the assembly of a hairpin probe (HP). Then, dopamine (DA)-modified DNA sequence (S1) was employed to hybridize with HP, which switching off the sensing system. This is the first work that employs DA to quench luminol ECL signal, possessing the biosensor ultralow background signal. Afterward, S2 produced by the target recycling process was loaded onto the prepared electrode to displace S1 and served as an initiator for RCA. With rational design, numerous repeated DNA sequences coupling with hemin to form hemin/G-quadruplex were generated, which could exhibit strongly catalytic toward H2O2, thus amplified the ECL signal and switched the ON state of the sensing system. The liner range for miRNA detection was from 1.0 fM to 100 pM with a low detection limit down to 0.3 fM. Moreover, with the high sensitivity and specificity induced by the dual signal amplification, the proposed miRNA biosensor holds great potential for analysis of other interesting tumor markers.
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International Nuclear Information System (INIS)
Bains, Lauren J.; Baker, Jennifer; Kyle, Alastair H.; Minchinton, Andrew I.; Reinsberg, Stefan A.
2009-01-01
Purpose: To determine whether vascular-targeting effects can be detected in vivo using magnetic resonance imaging (MRI). Methods and Materials: MR images of HCT-116 xenograft-bearing mice were acquired at 7 Tesla before and 24 hours after intraperitoneal injections of tirapazamine. Quantitative dynamic contrast-enhanced MRI analyses were performed to evaluate changes in tumor perfusion using two biomarkers: the volume transfer constant (K trans ) and the initial area under the concentration-time curve (IAUC). We used novel implanted fiducial markers to obtain cryosections that corresponded to MR image planes from excised tumors; quantitative immunohistochemical mapping of tumor vasculature, perfusion, and necrosis enabled correlative analysis between these and MR images. Results: Conventional histological analysis showed lower vascular perfusion or greater amounts of necrosis in the central regions of five of eight tirapazamine-treated tumors, with three treated tumors showing no vascular dysfunction response. MRI data reflected this result, and a striking decrease in both K trans and IAUC values was seen with the responsive tumors. Retrospective evaluation of pretreatment MRI parameters revealed that those tumors that did not respond to the vascular-targeting effects of tirapazamine had significantly higher pretreatment K trans and IAUC values. Conclusions: MRI-derived parameter maps showed good agreement with histological tumor mapping. MRI was found to be an effective tool for noninvasively monitoring and predicting tirapazamine-mediated central vascular dysfunction.
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Hypertensive target organ damage in Ghanaian civil servants with hypertension.
Directory of Open Access Journals (Sweden)
Juliet Addo
2009-08-01
Full Text Available Low levels of detection, treatment and control of hypertension have repeatedly been reported from sub Saharan Africa, potentially increasing the likelihood of target organ damage.A cross-sectional study was conducted on 1015 urban civil servants aged > or = 25 years from seven central government ministries in Accra, Ghana. Participants diagnosed to have hypertension were examined for target organ involvement. Hypertensive target organ damage was defined as the detection of any of the following: left ventricular hypertrophy diagnosed by electrocardiogram, reduction in glomerular filtration rate, the presence of hypertensive retinopathy or a history of a stroke.Of the 219 hypertensive participants examined, 104 (47.5% had evidence of target organ damage. The presence of target organ damage was associated with higher systolic and diastolic blood pressure levels. The odds of developing hypertensive target organ damage was five to six times higher in participants with blood pressure (BP > or = 180/110 mmHg compared to those with BP < 140/90 mmHg, and there was a trend to higher odds of target organ damage with increasing BP (p = 0.001. Women had about lower odds of developing target organ damage compared to men.The high prevalence of target organ damage in this working population associated with increasing blood pressure, emphasises the need for hypertension control programs aimed at improving the detection of hypertension, and importantly addressing the issues inhibiting the effective treatment and control of people with hypertension in the population.
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Directory of Open Access Journals (Sweden)
Zheng Shi-chao
2013-12-01
Full Text Available As an important mode in airborne radar systems, Wide Area Surveillance Ground Moving Target Indication (WAS-GMTI mode has the ability of monitoring a large area in a short time, and then the detected moving targets can be located quickly. However, in real environment, many factors introduce considerable errors into the location of moving targets. In this paper, a fast location method based on the characteristics of the moving targets in WAS-GMTI mode is utilized. And in order to improve the location performance, those factors that introduce location errors are analyzed and moving targets are relocated. Finally, the analysis of those factors is proved to be reasonable by simulation and real data experiments.
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Directory of Open Access Journals (Sweden)
Rheal A. Towner
2007-01-01
Full Text Available The multifunctional growth factor scatter factor/hepatocyte growth factor and its tyrosine kinase receptor, c-MET, have been implicated in the genesis and malignant progression of numerous human malignancies, including hepatocellular carcinomas. The incidence of hepatocellular carcinomas in the United States has increased noticeably over the past two decades and is listed as the fifth major cancer in men worldwide. In this study, we used a choline-deficient l-amino acid (CDAA-defined rat hepatocarcinogenesis model to visualize increased in vivo expression of the c-MET antigen in neoplastic lesion formation with the use of a super paramagnetic iron oxide (SPIO–anti-c-MET molecularly targeted magnetic resonance imaging (MRI contrast agent. SPIO–anti-c-MET was used for the first time to detect overexpression of c-MET in neoplastic nodules and tumors within the livers of CDAA-treated rats, as determined by a decrease in MRI signal intensity and a decrease in regional T2 values. Specificity for the binding of the molecularly targeted anti-c-MET contrast agent was determined using rat hepatoma (H4-II-E-C3 cell cultures and immunofluorescence microscopic imaging of the targeting agents within neoplastic liver tissue 1 to 2 hours following intravenous administration of SPIO–anti-c-MET and MRI investigation. This method has the ability to visualize in vivo the overexpression of c-MET at early developmental stages of tumor formation.
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Detecting Target Objects by Natural Language Instructions Using an RGB-D Camera
Directory of Open Access Journals (Sweden)
Jiatong Bao
2016-12-01
Full Text Available Controlling robots by natural language (NL is increasingly attracting attention for its versatility, convenience and no need of extensive training for users. Grounding is a crucial challenge of this problem to enable robots to understand NL instructions from humans. This paper mainly explores the object grounding problem and concretely studies how to detect target objects by the NL instructions using an RGB-D camera in robotic manipulation applications. In particular, a simple yet robust vision algorithm is applied to segment objects of interest. With the metric information of all segmented objects, the object attributes and relations between objects are further extracted. The NL instructions that incorporate multiple cues for object specifications are parsed into domain-specific annotations. The annotations from NL and extracted information from the RGB-D camera are matched in a computational state estimation framework to search all possible object grounding states. The final grounding is accomplished by selecting the states which have the maximum probabilities. An RGB-D scene dataset associated with different groups of NL instructions based on different cognition levels of the robot are collected. Quantitative evaluations on the dataset illustrate the advantages of the proposed method. The experiments of NL controlled object manipulation and NL-based task programming using a mobile manipulator show its effectiveness and practicability in robotic applications.
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The search for an alerted moving target; 2005BU2-OA
Vermeulen, J.F.J.; Brink, M. van den
2005-01-01
We investigate a two-sided, multi-stage search problem where a continuous search effort is made by one or more search units to detect a moving target in a continuous target space, under noisy detection conditions. A specific example of this problem is hunting for an enemy submarine by naval forces.
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Expanding applications of gene-based targeting biotechnology in functional genomics and the treatment of plants, animals, and microbes has synergized the need for new methods to measure binding efficiencies of these products to their genetic targets. The adaptation and innovative use of Cell–Penetra...
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Image thresholding in the high resolution target movement monitor
Moss, Randy H.; Watkins, Steve E.; Jones, Tristan H.; Apel, Derek B.; Bairineni, Deepti
2009-03-01
Image thresholding in the High Resolution Target Movement Monitor (HRTMM) is examined. The HRTMM was developed at the Missouri University of Science and Technology to detect and measure wall movements in underground mines to help reduce fatality and injury rates. The system detects the movement of a target with sub-millimeter accuracy based on the images of one or more laser dots projected on the target and viewed by a high-resolution camera. The relative position of the centroid of the laser dot (determined by software using thresholding concepts) in the images is the key factor in detecting the target movement. Prior versions of the HRTMM set the image threshold based on a manual, visual examination of the images. This work systematically examines the effect of varying threshold on the calculated centroid position and describes an algorithm for determining a threshold setting. First, the thresholding effects on the centroid position are determined for a stationary target. Plots of the centroid positions as a function of varying thresholds are obtained to identify clusters of thresholds for which the centroid position does not change for stationary targets. Second, the target is moved away from the camera in sub-millimeter increments and several images are obtained at each position and analyzed as a function of centroid position, target movement and varying threshold values. With this approach, the HRTMM can accommodate images in batch mode without the need for manual intervention. The capability for the HRTMM to provide automated, continuous monitoring of wall movement is enhanced.
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International Nuclear Information System (INIS)
Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing
2016-01-01
during the documentation of patient positioning and localization of the patient. Incidents were most frequently detected during treatment delivery (30%), and incidents identified at this point also had higher severity scores than other workflow areas (NMRI = 1.6). Incidents identified during on-treatment quality management were also more severe (NMRI = 1.7), and the specific process steps of reviewing portal and CBCT images tended to catch highest-severity incidents. On average, safety barriers caught 46% of all incidents, most frequently at physics chart review, therapist’s chart check, and the review of portal images; however, most of the incidents that pass through a particular safety barrier are not designed to be capable of being captured at that barrier. Conclusions: Incident learning systems can be used to assess the most common points of error origination and detection in radiation oncology. This can help tailor safety improvement efforts and target the highest impact portions of the workflow. The most severe near-miss events tend to originate during simulation, with the most severe near-miss events detected at the time of patient treatment. Safety barriers can be improved to allow earlier detection of near-miss events.
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Energy Technology Data Exchange (ETDEWEB)
Novak, Avrey; Nyflot, Matthew J.; Ermoian, Ralph P.; Jordan, Loucille E.; Sponseller, Patricia A.; Kane, Gabrielle M.; Ford, Eric C.; Zeng, Jing, E-mail: jzeng13@uw.edu [Department of Radiation Oncology, University of Washington Medical Center, 1959 NE Pacific Street, Campus Box 356043, Seattle, Washington 98195 (United States)
2016-05-15
during the documentation of patient positioning and localization of the patient. Incidents were most frequently detected during treatment delivery (30%), and incidents identified at this point also had higher severity scores than other workflow areas (NMRI = 1.6). Incidents identified during on-treatment quality management were also more severe (NMRI = 1.7), and the specific process steps of reviewing portal and CBCT images tended to catch highest-severity incidents. On average, safety barriers caught 46% of all incidents, most frequently at physics chart review, therapist’s chart check, and the review of portal images; however, most of the incidents that pass through a particular safety barrier are not designed to be capable of being captured at that barrier. Conclusions: Incident learning systems can be used to assess the most common points of error origination and detection in radiation oncology. This can help tailor safety improvement efforts and target the highest impact portions of the workflow. The most severe near-miss events tend to originate during simulation, with the most severe near-miss events detected at the time of patient treatment. Safety barriers can be improved to allow earlier detection of near-miss events.
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A novel SERRS sandwich-hybridization assay to detect specific DNA target.
Directory of Open Access Journals (Sweden)
Cécile Feuillie
Full Text Available In this study, we have applied Surface Enhanced Resonance Raman Scattering (SERRS technology to the specific detection of DNA. We present an innovative SERRS sandwich-hybridization assay that allows specific DNA detection without any enzymatic amplification, such as is the case with Polymerase Chain Reaction (PCR. In some substrates, such as ancient or processed remains, enzymatic amplification fails due to DNA alteration (degradation, chemical modification or to the presence of inhibitors. Consequently, the development of a non-enzymatic method, allowing specific DNA detection, could avoid long, expensive and inconclusive amplification trials. Here, we report the proof of concept of a SERRS sandwich-hybridization assay that leads to the detection of a specific chamois DNA. This SERRS assay reveals its potential as a non-enzymatic alternative technology to DNA amplification methods (particularly the PCR method with several applications for species detection. As the amount and type of damage highly depend on the preservation conditions, the present SERRS assay would enlarge the range of samples suitable for DNA analysis and ultimately would provide exciting new opportunities for the investigation of ancient DNA in the fields of evolutionary biology and molecular ecology, and of altered DNA in food frauds detection and forensics.
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Efficacy of Exome-Targeted Capture Sequencing to Detect Mutations in Known Cerebellar Ataxia Genes.
Coutelier, Marie; Hammer, Monia B; Stevanin, Giovanni; Monin, Marie-Lorraine; Davoine, Claire-Sophie; Mochel, Fanny; Labauge, Pierre; Ewenczyk, Claire; Ding, Jinhui; Gibbs, J Raphael; Hannequin, Didier; Melki, Judith; Toutain, Annick; Laugel, Vincent; Forlani, Sylvie; Charles, Perrine; Broussolle, Emmanuel; Thobois, Stéphane; Afenjar, Alexandra; Anheim, Mathieu; Calvas, Patrick; Castelnovo, Giovanni; de Broucker, Thomas; Vidailhet, Marie; Moulignier, Antoine; Ghnassia, Robert T; Tallaksen, Chantal; Mignot, Cyril; Goizet, Cyril; Le Ber, Isabelle; Ollagnon-Roman, Elisabeth; Pouget, Jean; Brice, Alexis; Singleton, Andrew; Durr, Alexandra
2018-05-01
Molecular diagnosis is difficult to achieve in disease groups with a highly heterogeneous genetic background, such as cerebellar ataxia (CA). In many patients, candidate gene sequencing or focused resequencing arrays do not allow investigators to reach a genetic conclusion. To assess the efficacy of exome-targeted capture sequencing to detect mutations in genes broadly linked to CA in a large cohort of undiagnosed patients and to investigate their prevalence. Three hundred nineteen index patients with CA and without a history of dominant transmission were included in the this cohort study by the Spastic Paraplegia and Ataxia Network. Centralized storage was in the DNA and cell bank of the Brain and Spine Institute, Salpetriere Hospital, Paris, France. Patients were classified into 6 clinical groups, with the largest being those with spastic ataxia (ie, CA with pyramidal signs [n = 100]). Sequencing was performed from January 1, 2014, through December 31, 2016. Detected variants were classified as very probably or definitely causative, possibly causative, or of unknown significance based on genetic evidence and genotype-phenotype considerations. Identification of variants in genes broadly linked to CA, classified in pathogenicity groups. The 319 included patients had equal sex distribution (160 female [50.2%] and 159 male patients [49.8%]; mean [SD] age at onset, 27.9 [18.6] years). The age at onset was younger than 25 years for 131 of 298 patients (44.0%) with complete clinical information. Consanguinity was present in 101 of 298 (33.9%). Very probable or definite diagnoses were achieved for 72 patients (22.6%), with an additional 19 (6.0%) harboring possibly pathogenic variants. The most frequently mutated genes were SPG7 (n = 14), SACS (n = 8), SETX (n = 7), SYNE1 (n = 6), and CACNA1A (n = 6). The highest diagnostic rate was obtained for patients with an autosomal recessive CA with oculomotor apraxia-like phenotype (6 of 17 [35.3%]) or
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International Nuclear Information System (INIS)
Stupin, D.M.
1986-01-01
We have developed x-ray radiography to measure thickness variations of coatings on laser fusion targets. Our technique is based on measuring the variation in x-ray transmission through the targets. The simplest targets are hollow glass microshells or microballoons 100 to 500 μm in diameter, that have several layers of metals or plastics, 1 to 100 μm thick. Our goal is to examine these opaque coatings for thickness variations as small as 1% or 0.1%, depending on the type of defect. Using contact radiography we have obtained the desired sensitivity for concentric and elliptical defects of 1%. This percentage corresponds to thickness variations as small as 100 A in a 1-μm-thick coating. For warts and dimples, the desired sensitivity is a function of the area of the defect, and we are developing a system to detect 0.1% thickness variations that cover an area 10 μm by 10 μm. We must use computer analysis of contact radiographs to measure 1% thickness variations in either concentricity or ellipticity. Because this analysis takes so long on our minicomputer, we preselect the radiographs by looking for defects at the 10% level on a video image analysis system
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Palomo, Laura; Fuster-Tormo, Francisco; Alvira, Daniel; Ademà, Vera; Armengol, María Pilar; Gómez-Marzo, Paula; de Haro, Nuri; Mallo, Mar; Xicoy, Blanca; Zamora, Lurdes; Solé, Francesc
2017-08-01
Whole genome amplification (WGA) has become an invaluable method for preserving limited samples of precious stock material and has been used during the past years as an alternative tool to increase the amount of DNA before library preparation for next-generation sequencing. Myelodysplastic syndromes (MDS) are a group of clonal hematopoietic stem cell disorders characterized by presenting somatic mutations in several myeloid-related genes. In this work, targeted deep sequencing has been performed on four paired fresh DNA and WGA DNA samples from bone marrow of MDS patients, to assess the feasibility of using WGA DNA for detecting somatic mutations. The results of this study highlighted that, in general, the sequencing and alignment statistics of fresh DNA and WGA DNA samples were similar. However, after variant calling and when considering variants detected at all frequencies, there was a high level of discordance between fresh DNA and WGA DNA (overall, a higher number of variants was detected in WGA DNA). After proper filtering, a total of three somatic mutations were detected in the cohort. All somatic mutations detected in fresh DNA were also identified in WGA DNA and validated by whole exome sequencing.
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The Bering Target Tracking Instrumentation
DEFF Research Database (Denmark)
Denver, Troelz; Jørgensen, John Leif; Betto, Maurizio
2003-01-01
The key science instrument on the Bering satellite mission is a relative small telescope with an entrance aperture of 300 mm and a focal length between 500 and 1000 mm. The detection of potential targets is performed by one of the target scanning advanced stellar compasses (ASCs). This procedure...... results in a simple prioritized list of right ascension, declination, proper motion and intensity of each prospective target. The telescope itself has a dedicated ASC Camera Head Unit (CHU) mounted on the secondary mirror, largely co-aligned with the telescope. This CHU accurately determines the telescope......'s pointing direction. To achieve fast tracking over a large solid angle, the telescope pointing is achieved by means of a folding mirror in the optical pathway. When a prospective target approaches the telescope FOV, the ASC on the secondary will guide the folding mirror into position such that the target...
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Coarse to fine aircraft detection from front-looking infrared images
Lin, Jin; Tan, Yihua; Tian, Jinwen
2018-03-01
Due to the weak feature and wide angle of long-distance aircraft targeting in the parking apron from front-looking infrared images, there are always false alarms in aircraft targeting detection. This leads to relatively poor reliability for detection results. In this paper, we present a scene-driven coarse-to-fine aircraft target detection method. First, we preprocess the image by combining the sharpened and enhanced images. Second, the region of interest (ROI) is segmented by using the local mean variance of the image and a series of subsequent processing. Then, target candidate areas are located by using the feature of local marginal distributions. Lastly, aircrafts can be detected accurately by a novel aircraft shape filter. Experiments on three infrared image sequences have shown that the presented method is effective and robust in detecting long-distance aircraft from front-looking infrared images and can also improve the reliability of the detection results.
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Contraband and threat material detection
International Nuclear Information System (INIS)
Lowrey, J. D.; Dunn, W.L.
2008-01-01
Full text: A pressing threat in modern society is the effective use of improvised explosive devices or IED's. One of the commonly used techniques to detect explosives is radiography. A primary drawback of this method is that humans are required in order to examine the image of each target. This requires trained personnel, who are subject to fatigue if many targets are being examined in rapid succession. Other trace element techniques generally require collection of samples from or near the surface of suspect targets. The signature-based radiation scanning (SBRS) technology has been developed to counter this threat. This technology can result in automated systems, requiring minimal operator involvement, that can rapidly identify IEDs from standoff. Preliminary research indicates that explosive samples of 5-10 kg or greater hidden in various targets can be detected from standoffs of more than a meter, with high sensitivity and high specificity. Many common explosives have similar concentrations of hydrogen, carbon, nitrogen and oxygen (HCNO). As neutrons interact with HCNO materials, unique signatures are created based on the specific composition of the material. We collect signatures from the HCNO prompt and inelastically scattered gamma rays and from scattered neutrons. Two neutron detectors (one bare and one cadmium-covered) are used in order to provide some measure of the back-scattered neutron spectrum. A library of signature templates, based on signatures detected from known targets containing known explosives in various configurations, is created. Similar signatures can be collected for suspect targets. Then a template-matching technique is used to construct two figure-of-merit metrics. The values of these metrics can be used to differentiate between safe targets and IEDs. Laboratory tests have been conducted using a high purity Germanium (HPGe) detector and two europium-doped lithium-iodide neutron detectors (one bare and one covered with cadmium) are used to
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A Novel Fusion-Based Ship Detection Method from Pol-SAR Images
Directory of Open Access Journals (Sweden)
Wenguang Wang
2015-09-01
Full Text Available A novel fusion-based ship detection method from polarimetric Synthetic Aperture Radar (Pol-SAR images is proposed in this paper. After feature extraction and constant false alarm rate (CFAR detection, the detection results of HH channel, diplane scattering by Pauli decomposition and helical factor by Barnes decomposition are fused together. The confirmed targets and potential target pixels can be obtained after the fusion process. Using the difference degree of the target, potential target pixels can be classified. The fusion-based ship detection method works accurately by utilizing three different features comprehensively. The result of applying the technique to measured Airborne Synthetic Radar (AIRSAR data shows that the novel detection method can achieve better performance in both ship’s detection and ship’s shape preservation compared to the result of K-means clustering method and the Notch Filter method.
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A man-made object detection for underwater TV
Cheng, Binbin; Wang, Wenwu; Chen, Yao
2018-03-01
It is a great challenging task to complete an automatic search of objects underwater. Usually the forward looking sonar is used to find the target, and then the initial identification of the target is completed by the side-scan sonar, and finally the confirmation of the target is accomplished by underwater TV. This paper presents an efficient method for automatic extraction of man-made sensitive targets in underwater TV. Firstly, the image of underwater TV is simplified with taking full advantage of the prior knowledge of the target and the background; then template matching technology is used for target detection; finally the target is confirmed by extracting parallel lines on the target contour. The algorithm is formulated for real-time execution on limited-memory commercial-of-the-shelf platforms and is capable of detection objects in underwater TV.
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Directory of Open Access Journals (Sweden)
Amar R Marathe
2015-08-01
Full Text Available Brain computer interaction (BCI technologies have proven effective in utilizing single-trial classification algorithms to detect target images in rapid serial visualization presentation tasks. While many factors contribute to the accuracy of these algorithms, a critical aspect that is often overlooked concerns the feature similarity between target and non-target images. In most real-world environments there are likely to be many shared features between targets and non-targets resulting in similar neural activity between the two classes. It is unknown how current neural-based target classification algorithms perform when qualitatively similar target and non-target images are presented. This study address this question by comparing behavioral and neural classification performance across two conditions: first, when targets were the only infrequent stimulus presented amongst frequent background distracters; and second when targets were presented together with infrequent non-targets containing similar visual features to the targets. The resulting findings show that behavior is slower and less accurate when targets are presented together with similar non-targets; moreover, single-trial classification yielded high levels of misclassification when infrequent non-targets are included. Furthermore, we present an approach to mitigate the image misclassification. We use confidence measures to assess the quality of single-trial classification, and demonstrate that a system in which low confidence trials are reclassified through a secondary process can result in improved performance.
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Detection is unaffected by the deployment of focal attention
Directory of Open Access Journals (Sweden)
Jeff eMoher
2013-05-01
Full Text Available There has been much debate regarding how much information humans can extract from their environment without the use of limited attentional resources. In a recent study, Theeuwes, Van der Burg, and Belopolsky (2008 argued that even detection of simple feature targets is not possible without selection by focal attention. Supporting this claim, they found response time benefits in a simple feature (color detection task when a target letter’s identity was repeated on consecutive trials, suggesting that the letter was selected by focal attention and identified prior to detection. This intertrial repetition benefit remained even when observers were required to simultaneously identify a central digit. However, we found that intertrial repetition benefits disappeared when a simple color target was presented among a heterogeneously (rather than homogeneously colored set of distractors, thus reducing its bottom-up salience. Still, detection performance remained high. Thus, detection performance was unaffected by whether a letter was focally attended and identified prior to detection or not. Intertrial identity repetition benefits also disappeared when observers were required to perform a simultaneous, attention-demanding central task (Experiment 2, or when unfamiliar Chinese characters were used (Experiment 3. Together, these results suggest that while shifts of focal attention can be affected by target salience, by the availability of excess cognitive resources, and by target familiarity, detection performance itself is unaffected by these manipulations and is thus unaffected by the deployment of focal attention.
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Hay, Elizabeth Anne; Khalaf, Abdulla Razak; Marini, Pietro; Brown, Andrew; Heath, Karyn; Sheppard, Darrin; MacKenzie, Alasdair
2017-08-01
We have successfully used comparative genomics to identify putative regulatory elements within the human genome that contribute to the tissue specific expression of neuropeptides such as galanin and receptors such as CB1. However, a previous inability to rapidly delete these elements from the mouse genome has prevented optimal assessment of their function in-vivo. This has been solved using CAS9/CRISPR genome editing technology which uses a bacterial endonuclease called CAS9 that, in combination with specifically designed guide RNA (gRNA) molecules, cuts specific regions of the mouse genome. However, reports of "off target" effects, whereby the CAS9 endonuclease is able to cut sites other than those targeted, limits the appeal of this technology. We used cytoplasmic microinjection of gRNA and CAS9 mRNA into 1-cell mouse embryos to rapidly generate enhancer knockout mouse lines. The current study describes our analysis of the genomes of these enhancer knockout lines to detect possible off-target effects. Bioinformatic analysis was used to identify the most likely putative off-target sites and to design PCR primers that would amplify these sequences from genomic DNA of founder enhancer deletion mouse lines. Amplified DNA was then sequenced and blasted against the mouse genome sequence to detect off-target effects. Using this approach we were unable to detect any evidence of off-target effects in the genomes of three founder lines using any of the four gRNAs used in the analysis. This study suggests that the problem of off-target effects in transgenic mice have been exaggerated and that CAS9/CRISPR represents a highly effective and accurate method of deleting putative neuropeptide gene enhancer sequences from the mouse genome. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.
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SAR Ground Moving Target Indication Based on Relative Residue of DPCA Processing
Directory of Open Access Journals (Sweden)
Jia Xu
2016-10-01
Full Text Available For modern synthetic aperture radar (SAR, it has much more urgent demands on ground moving target indication (GMTI, which includes not only the point moving targets like cars, truck or tanks but also the distributed moving targets like river or ocean surfaces. Among the existing GMTI methods, displaced phase center antenna (DPCA can effectively cancel the strong ground clutter and has been widely used. However, its detection performance is closely related to the target’s signal-to-clutter ratio (SCR as well as radial velocity, and it cannot effectively detect the weak large-sized river surfaces in strong ground clutter due to their low SCR caused by specular scattering. This paper proposes a novel method called relative residue of DPCA (RR-DPCA, which jointly utilizes the DPCA cancellation outputs and the multi-look images to improve the detection performance of weak river surfaces. Furthermore, based on the statistics analysis of the RR-DPCA outputs on the homogenous background, the cell average (CA method can be well applied for subsequent constant false alarm rate (CFAR detection. The proposed RR-DPCA method can well detect the point moving targets and distributed moving targets simultaneously. Finally, the results of both simulated and real data are provided to demonstrate the effectiveness of the proposed SAR/GMTI method.
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Composite Wavelet Filters for Enhanced Automated Target Recognition
Chiang, Jeffrey N.; Zhang, Yuhan; Lu, Thomas T.; Chao, Tien-Hsin
2012-01-01
Automated Target Recognition (ATR) systems aim to automate target detection, recognition, and tracking. The current project applies a JPL ATR system to low-resolution sonar and camera videos taken from unmanned vehicles. These sonar images are inherently noisy and difficult to interpret, and pictures taken underwater are unreliable due to murkiness and inconsistent lighting. The ATR system breaks target recognition into three stages: 1) Videos of both sonar and camera footage are broken into frames and preprocessed to enhance images and detect Regions of Interest (ROIs). 2) Features are extracted from these ROIs in preparation for classification. 3) ROIs are classified as true or false positives using a standard Neural Network based on the extracted features. Several preprocessing, feature extraction, and training methods are tested and discussed in this paper.
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Photonics: From target recognition to lesion detection
Henry, E. Michael
1994-01-01
Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.
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Tumor-targeting peptides from combinatorial libraries*
Liu, Ruiwu; Li, Xiaocen; Xiao, Wenwu; Lam, Kit S.
2018-01-01
Cancer is one of the major and leading causes of death worldwide. Two of the greatest challenges infighting cancer are early detection and effective treatments with no or minimum side effects. Widespread use of targeted therapies and molecular imaging in clinics requires high affinity, tumor-specific agents as effective targeting vehicles to deliver therapeutics and imaging probes to the primary or metastatic tumor sites. Combinatorial libraries such as phage-display and one-bead one-compound (OBOC) peptide libraries are powerful approaches in discovering tumor-targeting peptides. This review gives an overview of different combinatorial library technologies that have been used for the discovery of tumor-targeting peptides. Examples of tumor-targeting peptides identified from each combinatorial library method will be discussed. Published tumor-targeting peptide ligands and their applications will also be summarized by the combinatorial library methods and their corresponding binding receptors. PMID:27210583
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Power spectrum weighted edge analysis for straight edge detection in images
Karvir, Hrishikesh V.; Skipper, Julie A.
2007-04-01
Most man-made objects provide characteristic straight line edges and, therefore, edge extraction is a commonly used target detection tool. However, noisy images often yield broken edges that lead to missed detections, and extraneous edges that may contribute to false target detections. We present a sliding-block approach for target detection using weighted power spectral analysis. In general, straight line edges appearing at a given frequency are represented as a peak in the Fourier domain at a radius corresponding to that frequency, and a direction corresponding to the orientation of the edges in the spatial domain. Knowing the edge width and spacing between the edges, a band-pass filter is designed to extract the Fourier peaks corresponding to the target edges and suppress image noise. These peaks are then detected by amplitude thresholding. The frequency band width and the subsequent spatial filter mask size are variable parameters to facilitate detection of target objects of different sizes under known imaging geometries. Many military objects, such as trucks, tanks and missile launchers, produce definite signatures with parallel lines and the algorithm proves to be ideal for detecting such objects. Moreover, shadow-casting objects generally provide sharp edges and are readily detected. The block operation procedure offers advantages of significant reduction in noise influence, improved edge detection, faster processing speed and versatility to detect diverse objects of different sizes in the image. With Scud missile launcher replicas as target objects, the method has been successfully tested on terrain board test images under different backgrounds, illumination and imaging geometries with cameras of differing spatial resolution and bit-depth.
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International Nuclear Information System (INIS)
Pallwein, Leo; Struve, Peter; Aigner, Friedrich; Gradl, Johann; Schurich, Matthias; Frauscher, Ferdinand; Mitterberger, Michael; Horninger, Wolfgang; Bartsch, Georg; Pedross, Florian
2007-01-01
A prospective study was performed to determine the value of sonoelastography (SE) targeted biopsy for prostate cancer (PCa) detection. A series of 230 male screening volunteers was examined. Two independent examiners evaluated each subject. One single investigator performed ≤5 SE targeted biopsies into suspicious regions in the peripheral zone only. The stiffness of the lesion was displayed by SE and color-coded from red (soft) to blue (hard). Hard lesions were considered as malignant and targeted by biopsy. Subsequently, another examiner performed ten systematic biopsies. Cancer detection rates of the two techniques were compared. Cancer was detected in 81 of the 230 patients (35%), including 68 (30%) by SE targeted biopsy and in 58 (25%) by systematic biopsy. Cancer was detected by targeted biopsy alone in 23 patients (10%) and by systematic biopsy alone in 13 patients (6%). The detection rate for SE targeted biopsy cores (12.7% or 135 of 1,109 cores) was significantly better than for systematic biopsy cores (5.6% or 130 of 2,300 cores, P < 0.001). SE targeted biopsy in a patient with cancer was 2.9-fold more likely to detect PCa than systematic biopsy. SE targeted biopsy detected more cases of PCa than systematic biopsy, with fewer than half the number of biopsy cores in this prostate-specific antigen screening population. (orig.)
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Real-Time Detection of a Virus Using Detection Dogs
Directory of Open Access Journals (Sweden)
Craig eAngle
2016-01-01
Full Text Available Viral infections are ubiquitous in humans, animals, and plants. Real-time methods to identify viral infections are limited and do not exist for use in harsh or resource-constrained environments. Previous research identified that tissues produce unique volatile organic compounds (VOC and demonstrated that VOC concentrations change during pathologic states including infection, neoplasia, or metabolic disease. Patterns of VOC expression may be pathogen-specific and may be associated with an odor that could be used for disease detection.We investigated the ability of two trained dogs to detect cell cultures infected with bovine viral diarrhea virus (BVDV and to discriminate BVDV-infected cell cultures from uninfected cell cultures and from cell cultures infected with bovine herpes virus 1 (BHV 1 and bovine parainfluenza virus 3 (BPIV 3. Dogs were trained to recognize cell cultures infected with two different biotypes of BVDV propagated in MDBK cells using one of three culture media. For detection trials, one target and seven distractors were presented on a scent wheel by a dog handler unaware of the location of targets and distractors.Detection of BVDV- infected cell cultures by Dog 1 had a diagnostic sensitivity of 0.850 (95% CI: 0.701 - 0.942, which was lower than Dog 2 (0.967, 95% CI: 0.837 - 0.994. Both dogs exhibited very high diagnostic specificity (0.981, 95% CI: 0.960 - 0.993 and (0.993, 95% CI: 0.975 - 0.999, respectively.These findings demonstrate that trained dogs can differentiate between cultured cells infected with BVDV, BHV1, and BPIV3 and are a realistic real-time mobile pathogen sensing technology for viral pathogens. The ability to discriminate between target and distractor samples plausibly results from expression of unique VOC patterns virus-infected and uninfected cells.
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Real-Time Detection of a Virus Using Detection Dogs.
Angle, T Craig; Passler, Thomas; Waggoner, Paul L; Fischer, Terrence D; Rogers, Bart; Galik, Patricia K; Maxwell, Herris S
2015-01-01
Viral infections are ubiquitous in humans, animals, and plants. Real-time methods to identify viral infections are limited and do not exist for use in harsh or resource-constrained environments. Previous research identified that tissues produce unique volatile organic compounds (VOC) and demonstrated that VOC concentrations change during pathologic states, including infection, neoplasia, or metabolic disease. Patterns of VOC expression may be pathogen specific and may be associated with an odor that could be used for disease detection. We investigated the ability of two trained dogs to detect cell cultures infected with bovine viral diarrhea virus (BVDV) and to discriminate BVDV-infected cell cultures from uninfected cell cultures and from cell cultures infected with bovine herpes virus 1 (BHV 1) and bovine parainfluenza virus 3 (BPIV 3). Dogs were trained to recognize cell cultures infected with two different biotypes of BVDV propagated in Madin-Darby bovine kidney cells using one of three culture media. For detection trials, one target and seven distractors were presented on a scent wheel by a dog handler unaware of the location of targets and distractors. Detection of BVDV-infected cell cultures by Dog 1 had a diagnostic sensitivity of 0.850 (95% CI: 0.701-0.942), which was lower than Dog 2 (0.967, 95% CI: 0.837-0.994). Both dogs exhibited very high diagnostic specificity (0.981, 95% CI: 0.960-0.993) and (0.993, 95% CI: 0.975-0.999), respectively. These findings demonstrate that trained dogs can differentiate between cultured cells infected with BVDV, BHV1, and BPIV3 and are a realistic real-time mobile pathogen sensing technology for viral pathogens. The ability to discriminate between target and distractor samples plausibly results from expression of unique VOC patterns in virus-infected and -uninfected cells.
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Directory of Open Access Journals (Sweden)
Duy Tien Ta
2016-07-01
Full Text Available Surface bioconjugation of biomolecules has gained enormous attention for developing advanced biomaterials including biosensors. While conventional immobilization (by physisorption or covalent couplings using the functional groups of the endogenous amino acids usually results in surfaces with low activity, reproducibility and reusability, the application of methods that allow for a covalent and uniformly oriented coupling can circumvent these limitations. In this study, the nanobody targeting Vascular Cell Adhesion Molecule-1 (NbVCAM1, an atherosclerotic biomarker, is engineered with a C-terminal alkyne function via Expressed Protein Ligation (EPL. Conjugation of this nanobody to azidified silicon wafers and Biacore™ C1 sensor chips is achieved via Copper(I-catalyzed azide-alkyne cycloaddition (CuAAC “click” chemistry to detect VCAM1 binding via ellipsometry and surface plasmon resonance (SPR, respectively. The resulting surfaces, covered with uniformly oriented nanobodies, clearly show an increased antigen binding affinity, sensitivity, detection limit, quantitation limit and reusability as compared to surfaces prepared by random conjugation. These findings demonstrate the added value of a combined EPL and CuAAC approach as it results in strong control over the surface orientation of the nanobodies and an improved detecting power of their targets—a must for the development of advanced miniaturized, multi-biomarker biosensor platforms.
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Kashida, Hiromu; Yamaguchi, Kyohei; Hara, Yuichi; Asanuma, Hiroyuki
2012-07-15
In this study, we synthesized a simple but efficient quencher-free molecular beacon tethering 7-hydroxycoumarin on D-threoninol based on its pK(a) change. The pK(a) of 7-hydroxycoumarin in a single strand was determined as 8.8, whereas that intercalated in the duplex was over 10. This large pK(a) shift (more than 1.2) upon hybridization could be attributed to the anionic and hydrophobic microenvironment inside the DNA duplex. Because 7-hydroxycoumarin quenches its fluorescence upon protonation, the emission intensity of the duplex at pH 8.5 was 1/15 that of the single strand. We applied this quenching mechanism to the preparation of a quencher-free molecular beacon by introducing the dye into the middle of the stem part. In the absence of the target, the stem region formed a duplex and fluorescence was quenched. However, when the target was added, the molecular beacon opened and the dye was deprotonated. As a result, the emission intensity of the molecular beacon with the target was 10 times higher than that without the target. Accordingly, a quencher-free molecular beacon utilizing the pK(a) change was successfully developed. Copyright © 2012 Elsevier Ltd. All rights reserved.
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Vision-Based Target Finding and Inspection of a Ground Target Using a Multirotor UAV System.
Hinas, Ajmal; Roberts, Jonathan M; Gonzalez, Felipe
2017-12-17
In this paper, a system that uses an algorithm for target detection and navigation and a multirotor Unmanned Aerial Vehicle (UAV) for finding a ground target and inspecting it closely is presented. The system can also be used for accurate and safe delivery of payloads or spot spraying applications in site-specific crop management. A downward-looking camera attached to a multirotor is used to find the target on the ground. The UAV descends to the target and hovers above the target for a few seconds to inspect the target. A high-level decision algorithm based on an OODA (observe, orient, decide, and act) loop was developed as a solution to address the problem. Navigation of the UAV was achieved by continuously sending local position messages to the autopilot via Mavros. The proposed system performed hovering above the target in three different stages: locate, descend, and hover. The system was tested in multiple trials, in simulations and outdoor tests, from heights of 10 m to 40 m. Results show that the system is highly reliable and robust to sensor errors, drift, and external disturbance.
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Dynamical scene analysis with a moving camera: mobile targets detection system
International Nuclear Information System (INIS)
Hennebert, Christine
1996-01-01
This thesis work deals with the detection of moving objects in monocular image sequences acquired with a mobile camera. We propose a method able to detect small moving objects in visible or infrared images of real outdoor scenes. In order to detect objects of very low apparent motion, we consider an analysis on a large temporal interval. We have chosen to compensate for the dominant motion due to the camera displacement for several consecutive images in order to form a sub-sequence of images for which the camera seems virtually static. We have also developed a new approach allowing to extract the different layers of a real scene in order to deal with cases where the 2D motion due to the camera displacement cannot be globally compensated for. To this end, we use a hierarchical model with two levels: the local merging step and the global merging one. Then, an appropriate temporal filtering is applied to registered image sub-sequence to enhance signals corresponding to moving objects. The detection issue is stated as a labeling problem within a statistical regularization based on Markov Random Fields. Our method has been validated on numerous real image sequences depicting complex outdoor scenes. Finally, the feasibility of an integrated circuit for mobile object detection has been proved. This circuit could lead to an ASIC creation. (author) [fr
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Target Detection Routine (TADER). User’s Guide.
1987-09-01
o System range capability subset (one record - omitted for standoff SLAR and penetrating system) o System inherent detection probability subset ( IELT ...records, i.e., one per element type) * System capability modifier subset/A=1, E=1 ( IELT records) o System capability modifier subset/A=1, E=2 ( IELT ...records) s System capability modifier subset/A=2, E=1 ( IELT records) o System capability modifier subset/A=2, E=2 ( IELT records) Unit Data Set (one set
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Peltier, Chad; Becker, Mark W
2017-05-01
Target prevalence influences visual search behavior. At low target prevalence, miss rates are high and false alarms are low, while the opposite is true at high prevalence. Several models of search aim to describe search behavior, one of which has been specifically intended to model search at varying prevalence levels. The multiple decision model (Wolfe & Van Wert, Current Biology, 20(2), 121--124, 2010) posits that all searches that end before the observer detects a target result in a target-absent response. However, researchers have found very high false alarms in high-prevalence searches, suggesting that prevalence rates may be used as a source of information to make "educated guesses" after search termination. Here, we further examine the ability for prevalence level and knowledge gained during visual search to influence guessing rates. We manipulate target prevalence and the amount of information that an observer accumulates about a search display prior to making a response to test if these sources of evidence are used to inform target present guess rates. We find that observers use both information about target prevalence rates and information about the proportion of the array inspected prior to making a response allowing them to make an informed and statistically driven guess about the target's presence.
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Target 5000: Target Capture Sequencing for Inherited Retinal Degenerations
Directory of Open Access Journals (Sweden)
Adrian Dockery
2017-11-01
Full Text Available There are an estimated 5000 people in Ireland who currently have an inherited retinal degeneration (IRD. It is the goal of this study, through genetic diagnosis, to better enable these 5000 individuals to obtain a clearer understanding of their condition and improved access to potentially applicable therapies. Here we show the current findings of a target capture next-generation sequencing study of over 750 patients from over 520 pedigrees currently situated in Ireland. We also demonstrate how processes can be implemented to retrospectively analyse patient datasets for the detection of structural variants in previously obtained sequencing reads. Pathogenic or likely pathogenic mutations were detected in 68% of pedigrees tested. We report nearly 30 novel mutations including three large structural variants. The population statistics related to our findings are presented by condition and credited to their respective candidate gene mutations. Rediagnosis rates of clinical phenotypes after genotyping are discussed. Possible causes of failure to detect a candidate mutation are evaluated. Future elements of this project, with a specific emphasis on structural variants and non-coding pathogenic variants, are expected to increase detection rates further and thereby produce an even more comprehensive representation of the genetic landscape of IRDs in Ireland.
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Space-based infrared sensors of space target imaging effect analysis
Dai, Huayu; Zhang, Yasheng; Zhou, Haijun; Zhao, Shuang
2018-02-01
Target identification problem is one of the core problem of ballistic missile defense system, infrared imaging simulation is an important means of target detection and recognition. This paper first established the space-based infrared sensors ballistic target imaging model of point source on the planet's atmosphere; then from two aspects of space-based sensors camera parameters and target characteristics simulated atmosphere ballistic target of infrared imaging effect, analyzed the camera line of sight jitter, camera system noise and different imaging effects of wave on the target.
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Deng, Yun-Liang; Xu, Dang-Dang; Pang, Dai-Wen; Tang, Hong-Wu
2017-02-01
A three-layer core-shell nanostructure consisting of a silver core, a silica spacer, and a fluorescent dye RuBpy-doped outer silica layer was fabricated, and the optimal metal-enhanced fluorescence (MEF) distance was explored through adjusting the thickness of the silica spacer. The results show that the optimal distance is ˜10.4 nm with the maximum fluorescence enhancement factor 2.12. Then a new target-triggered MEF ‘turn-on’ strategy based on the optimized composite nanoparticles was successfully constructed for quantitative detection of prostate specific antigen (PSA), by using RuBpy as the energy donor and BHQ-2 as the acceptor. The hybridization of the complementary DNA of PSA-aptamer immobilized on the surface of the MEF nanoparticles with PSA-aptamer modified with BHQ-2, brought BHQ-2 in close proximity to RuBpy-doped silica shell and resulted in the decrease of fluorescence. In the presence of target PSA molecules, the BHQ-PSA aptamer is dissociated from the surface of the nanoparticles with the fluorescence switched on. Therefore, the assay of PSA was achieved by measuring the varying fluorescence intensity. The results show that PSA can be detected in the range of 1-100 ng ml-1 with a detection limit of 0.20 ng ml-1 (6.1 pM), which is 6.7-fold increase of that using hollow RuBpy-doped silica nanoparticles. Moreover, satisfactory results were obtained when PSA was detected in 1% serum.
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Directory of Open Access Journals (Sweden)
Xu Yongli
2017-01-01
Full Text Available Ship detection in synthetic aperture radar (SAR remote sensing images, being a fundamental but challenging problem in the field of satellite image analysis, plays an important role for a wide range of applications and is receiving significant attention in recent years. Aiming at the requirements of ship detection in high-resolution SAR images, the accuracy, the intelligent level, a better real-time operation and processing efficiency, The characteristics of ocean background and ship target in high-resolution SAR images were analyzed, we put forward a ship detection algorithm in high-resolution SAR images. The algorithm consists of two detection stages: The first step designs a pre-training classifier based on improved spectral residual visual model to obtain the visual salient regions containing ship targets quickly, then achieve the purpose of probably detection of ships. In the second stage, considering the Bayesian theory of binary hypothesis detection, a local maximum posterior probability (MAP classifier is designed for the classification of pixels. After the parameter estimation and judgment criterion, the classification of pixels are carried out in the target areas to achieve the classification of two types of pixels in the salient regions. In the paper, several types of satellite image data, such as TerraSAR-X (TS-X, Radarsat-2, are used to evaluate the performance of detection methods. Comparing with classical CFAR detection algorithms, experimental results show that the algorithm can achieve a better effect of suppressing false alarms, which caused by the speckle noise and ocean clutter background inhomogeneity. At the same time, the detection speed is increased by 25% to 45%.
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Directory of Open Access Journals (Sweden)
John Cooper
2010-03-01
Full Text Available The CombiMatrix ElectraSense microarray is a highly multiplex, complementary metal oxide semiconductor with 12,544 electrodes that are individually addressable. This platform is commercially available as a custom DNA microarray; and, in this configuration, it has also been used to tether antibodies (Abs specifically on electrodes using complementary DNA sequences conjugated to the Abs.An empirical method is described for developing and optimizing immunoassays on the CombiMatrix ElectraSense microarray based upon targeted deposition of polypyrrole (Ppy and capture Ab. This process was automated using instrumentation that can selectively apply a potential or current to individual electrodes and also measure current generated at the electrodes by an enzyme-enhanced electrochemical (ECD reaction. By designating groups of electrodes on the array for different Ppy deposition conditions, we determined that the sensitivity and specificity of a sandwich immunoassay for staphylococcal enterotoxin B (SEB is influenced by the application of different voltages or currents and the application time. The sandwich immunoassay used a capture Ab adsorbed to the Ppy and a reporter Ab labeled for fluorescence detection or ECD, and results from these methods of detection were different.Using Ppy deposition conditions for optimum results, the lower limit of detection for SEB using the ECD assay was between 0.003 and 0.01 pg/ml, which represents an order of magnitude improvement over a conventional enzyme-linked immunosorbant assay. In the absence of understanding the variables and complexities that affect assay performance, this highly multiplexed electrode array provided a rapid, high throughput, and empirical approach for developing a sensitive immunoassay.
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Target-Specific Assay for Rapid and Quantitative Detection of Mycobacterium chimaera DNA.
Zozaya-Valdés, Enrique; Porter, Jessica L; Coventry, John; Fyfe, Janet A M; Carter, Glen P; Gonçalves da Silva, Anders; Schultz, Mark B; Seemann, Torsten; Johnson, Paul D R; Stewardson, Andrew J; Bastian, Ivan; Roberts, Sally A; Howden, Benjamin P; Williamson, Deborah A; Stinear, Timothy P
2017-06-01
Mycobacterium chimaera is an opportunistic environmental mycobacterium belonging to the Mycobacterium avium - M. intracellulare complex. Although most commonly associated with pulmonary disease, there has been growing awareness of invasive M. chimaera infections following cardiac surgery. Investigations suggest worldwide spread of a specific M. chimaera clone, associated with contaminated hospital heater-cooler units used during the surgery. Given the global dissemination of this clone, its potential to cause invasive disease, and the laboriousness of current culture-based diagnostic methods, there is a pressing need to develop rapid and accurate diagnostic assays specific for M. chimaera Here, we assessed 354 mycobacterial genome sequences and confirmed that M. chimaera is a phylogenetically coherent group. In silico comparisons indicated six DNA regions present only in M. chimaera We targeted one of these regions and developed a TaqMan quantitative PCR (qPCR) assay for M. chimaera with a detection limit of 100 CFU/ml in whole blood spiked with bacteria. In vitro screening against DNA extracted from 40 other mycobacterial species and 22 bacterial species from 21 diverse genera confirmed the in silico -predicted specificity for M. chimaera Screening 33 water samples from heater-cooler units with this assay highlighted the increased sensitivity of PCR compared to culture, with 15 of 23 culture-negative samples positive by M. chimaera qPCR. We have thus developed a robust molecular assay that can be readily and rapidly deployed to screen clinical and environmental specimens for M. chimaera . Copyright © 2017 American Society for Microbiology.
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Nanaware, Padma P; Ramteke, Manoj P; Somavarapu, Arun K; Venkatraman, Prasanna
2014-07-01
Gankyrin, a non-ATPase component of the proteasome and a chaperone of proteasome assembly, is also an oncoprotein. Gankyrin regulates a variety of oncogenic signaling pathways in cancer cells and accelerates degradation of tumor suppressor proteins p53 and Rb. Therefore gankyrin may be a unique hub integrating signaling networks with the degradation pathway. To identify new interactions that may be crucial in consolidating its role as an oncogenic hub, crystal structure of gankyrin-proteasome ATPase complex was used to predict novel interacting partners. EEVD, a four amino acid linear sequence seems a hot spot site at this interface. By searching for EEVD in exposed regions of human proteins in PDB database, we predicted 34 novel interactions. Eight proteins were tested and seven of them were found to interact with gankyrin. Affinity of four interactions is high enough for endogenous detection. Others require gankyrin overexpression in HEK 293 cells or occur endogenously in breast cancer cell line- MDA-MB-435, reflecting lower affinity or presence of a deregulated network. Mutagenesis and peptide inhibition confirm that EEVD is the common hot spot site at these interfaces and therefore a potential polypharmacological drug target. In MDA-MB-231 cells in which the endogenous CLIC1 is silenced, trans-expression of Wt protein (CLIC1_EEVD) and not the hot spot site mutant (CLIC1_AAVA) resulted in significant rescue of the migratory potential. Our approach can be extended to identify novel functionally relevant protein-protein interactions, in expansion of oncogenic networks and in identifying potential therapeutic targets. © 2013 Wiley Periodicals, Inc.
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Dangerous gas detection based on infrared video
Ding, Kang; Hong, Hanyu; Huang, Likun
2018-03-01
As the gas leak infrared imaging detection technology has significant advantages of high efficiency and remote imaging detection, in order to enhance the detail perception of observers and equivalently improve the detection limit, we propose a new type of gas leak infrared image detection method, which combines background difference methods and multi-frame interval difference method. Compared to the traditional frame methods, the multi-frame interval difference method we proposed can extract a more complete target image. By fusing the background difference image and the multi-frame interval difference image, we can accumulate the information of infrared target image of the gas leak in many aspect. The experiment demonstrate that the completeness of the gas leakage trace information is enhanced significantly, and the real-time detection effect can be achieved.
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Low-resolution ship detection from high-altitude aerial images
Qi, Shengxiang; Wu, Jianmin; Zhou, Qing; Kang, Minyang
2018-02-01
Ship detection from optical images taken by high-altitude aircrafts such as unmanned long-endurance airships and unmanned aerial vehicles has broad applications in marine fishery management, ship monitoring and vessel salvage. However, the major challenge is the limited capability of information processing on unmanned high-altitude platforms. Furthermore, in order to guarantee the wide detection range, unmanned aircrafts generally cruise at high altitudes, resulting in imagery with low-resolution targets and strong clutters suffered by heavy clouds. In this paper, we propose a low-resolution ship detection method to extract ships from these high-altitude optical images. Inspired by a recent research on visual saliency detection indicating that small salient signals could be well detected by a gradient enhancement operation combined with Gaussian smoothing, we propose the facet kernel filtering to rapidly suppress cluttered backgrounds and delineate candidate target regions from the sea surface. Then, the principal component analysis (PCA) is used to compute the orientation of the target axis, followed by a simplified histogram of oriented gradient (HOG) descriptor to characterize the ship shape property. Finally, support vector machine (SVM) is applied to discriminate real targets and false alarms. Experimental results show that the proposed method actually has high efficiency in low-resolution ship detection.
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Seeing Objects as Faces Enhances Object Detection.
Takahashi, Kohske; Watanabe, Katsumi
2015-10-01
The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.
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Seeing Objects as Faces Enhances Object Detection
Directory of Open Access Journals (Sweden)
Kohske Takahashi
2015-09-01
Full Text Available The face is a special visual stimulus. Both bottom-up processes for low-level facial features and top-down modulation by face expectations contribute to the advantages of face perception. However, it is hard to dissociate the top-down factors from the bottom-up processes, since facial stimuli mandatorily lead to face awareness. In the present study, using the face pareidolia phenomenon, we demonstrated that face awareness, namely seeing an object as a face, enhances object detection performance. In face pareidolia, some people see a visual stimulus, for example, three dots arranged in V shape, as a face, while others do not. This phenomenon allows us to investigate the effect of face awareness leaving the stimulus per se unchanged. Participants were asked to detect a face target or a triangle target. While target per se was identical between the two tasks, the detection sensitivity was higher when the participants recognized the target as a face. This was the case irrespective of the stimulus eccentricity or the vertical orientation of the stimulus. These results demonstrate that seeing an object as a face facilitates object detection via top-down modulation. The advantages of face perception are, therefore, at least partly, due to face awareness.
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Spatial Release from Masking with a Moving Target
Directory of Open Access Journals (Sweden)
M. Torben Pastore
2017-12-01
Full Text Available In the visual domain, a stationary object that is difficult to detect usually becomes far more salient if it moves while the objects around it do not. This “pop out” effect is important for parsing the visual world into figure/ground relationships that allow creatures to detect food, threats, etc. We tested for an auditory correlate to this visual effect by asking listeners to identify a single word, spoken by a female, embedded with two or four masking words spoken by males. Percentage correct scores were analyzed and compared between conditions where target and maskers were presented from the same position vs. when the target was presented from one position while maskers were presented from different positions. In some trials, the target word was moved across the speaker array using amplitude panning, while in other trials that target was played from a single, static position. Results showed a spatial release from masking for all conditions where the target and maskers were not located at the same position, but there was no statistically significant difference between identification performance when the target was moving vs. when it was stationary. These results suggest that, at least for short stimulus durations (0.75 s for the stimuli in this experiment, there is unlikely to be a “pop out” effect for moving target stimuli in the auditory domain as there is in the visual domain.
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SU-F-J-160: Clinical Evaluation of Targeting Accuracy in Radiosurgery Using Tractography
Energy Technology Data Exchange (ETDEWEB)
Juh, R; Han, J; Kim, C; Oh, C [Seoul National University Bundang Hospital, Seongnamsi, GyeonggiDo (Korea, Republic of); Suh, T [The catholic university of Korea, Seoul (Korea, Republic of)
2016-06-15
Purpose: Focal radiosurgery is a common treatment modality for trigeminal neuralgia (TN), a neuropathic facial pain condition. Assessment of treatment effectiveness is primarily clinical, given the paucity of investigational tools to assess trigeminal nerve changes. The efficiency of radiosurgery is related to its highly precise targeting. We assessed clinically the targeting accuracy of radiosurgery with Gamma knife. We hypothesized that trigeminal tractography provides more information than 2D-MR imaging, allowing detection of unique, focal changes in the target area after radiosurgery. Methods: Sixteen TN patients (2 females, 4 males, average age 65.3 years) treated with Gamma Knife radiosurgery, 40 Gy/50% isodose line underwent 1.5Tesla MR trigeminal nerve. Target accuracy was assessed from deviation of the coordinates of the target compared with the center of enhancement on post MRI. Radiation dose delivered at the borders of contrast enhancement was evaluated. Results: The median deviation of the coordinates between the intended target and the center of contrast enhancement was within 1mm. The radiation doses fitting within the borders of the contrast enhancement the target ranged from 37.5 to 40 Gy. Trigeminal tractography accurately detected the radiosurgical target. Radiosurgery resulted in 47% drop in FA values at the target with no significant change in FA outside the target, suggesting that radiosurgery primarily affects myelin. Tractography was more sensitive, since FA changes were detected regardless of trigeminal nerve enhancement. Conclusion: The median deviation found in clinical assessment of gamma knife treatment for TN Is low and compatible with its high rate of efficiency. DTI parameters accurately detect the effects of focal radiosurgery on the trigeminal nerve, serving as an in vivo imaging tool to study TN. This study is a proof of principle for further assessment of DTI parameters to understand the pathophysiology of TN and treatment
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Ogawa, Mikako; Kosaka, Nobuyuki; Choyke, Peter L; Kobayashi, Hisataka
2009-01-01
In vivo molecular cancer imaging with monoclonal antibodies has great potential not only for cancer detection, but also for cancer characterization. However, the prolonged retention of intravenously injected antibody in the blood causes low target tumor-to-background ratio (TBR). Avidin has been used as a "chase" to clear the unbound, circulating biotinylated antibody and decrease the background signal. Here, we utilize a combined approach of a fluorescence resonance energy transfer (FRET) quenched antibody with an "avidin chase" to increase TBR. Trastuzumab, a humanized monoclonal antibody against human epidermal growth factor receptor type 2 (HER2), was biotinylated and conjugated with the near-infrared (NIR) fluorophore Alexa680 to synthesize Tra-Alexa680-biotin. Next, the FRET quencher, QSY-21, was conjugated to avidin, neutravidin (nAv), or streptavidin (sAv), thus creating Av-QSY21, nAv-QSY21, or sAv-QSY21 as "chasers". The fluorescence was quenched in vitro by binding Tra-Alexa680-biotin to Av-QSY21, nAv-QSY21, or sAv-QSY21. To evaluate if the injection of quencher-conjugated avidin derivatives can improve target TBR by using a dual "quench and chase" strategy, both target (3T3/HER2+) and nontarget (Balb3T3/ZsGreen) tumor-bearing mice were employed. The "FRET quench" effect induced by all the QSY21 avidin-based conjugates reduced but did not totally eliminate background signal from the blood pool. The addition of nAv-QSY21 administration increased target TBR mainly because of the "chase" effect where unbound conjugated antibody was preferentially cleared to the liver. The relatively slow clearance of unbound nAv-QSY21 leads to further reductions in background signal by leaking out of the vascular space and binding to unbound antibodies in the extravascular space of tumors, resulting in decreased nontarget tumor-to-background ratios but increased target TBR due to the "FRET quench" effect, because target-bound antibodies were internalized and could not bind
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The Advanced Linked Extended Reconnaissance & Targeting Technology Demonstration project
Edwards, Mark
2008-04-01
The Advanced Linked Extended Reconnaissance & Targeting (ALERT) Technology Demonstration (TD) project is addressing many operational needs of the future Canadian Army's Surveillance and Reconnaissance forces. Using the surveillance system of the Coyote reconnaissance vehicle as an experimental platform, the ALERT TD project aims to significantly enhance situational awareness by fusing multi-sensor and tactical data, developing automated processes, and integrating beyond line-of-sight sensing. The project is exploiting important advances made in computer processing capability, displays technology, digital communications, and sensor technology since the design of the original surveillance system. As the major research area within the project, concepts are discussed for displaying and fusing multi-sensor and tactical data within an Enhanced Operator Control Station (EOCS). The sensor data can originate from the Coyote's own visible-band and IR cameras, laser rangefinder, and ground-surveillance radar, as well as from beyond line-of-sight systems such as mini-UAVs and unattended ground sensors. Video-rate image processing has been developed to assist the operator to detect poorly visible targets. As a second major area of research, automatic target cueing capabilities have been added to the system. These include scene change detection, automatic target detection and aided target recognition algorithms processing both IR and visible-band images to draw the operator's attention to possible targets. The merits of incorporating scene change detection algorithms are also discussed. In the area of multi-sensor data fusion, up to Joint Defence Labs level 2 has been demonstrated. The human factors engineering aspects of the user interface in this complex environment are presented, drawing upon multiple user group sessions with military surveillance system operators. The paper concludes with Lessons Learned from the project. The ALERT system has been used in a number of C4ISR
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Wilson, Kris; Webster, Scott P.; Iredale, John P.; Zheng, Xiaozhong; Homer, Natalie Z.; Pham, Nhan T.; Auer, Manfred; Mole, Damian J.
2018-01-01
The assessment of drug-target engagement for determining the efficacy of a compound inside cells remains challenging, particularly for difficult target proteins. Existing techniques are more suited to soluble protein targets. Difficult target proteins include those with challenging in vitro solubility, stability or purification properties that preclude target isolation. Here, we report a novel technique that measures intracellular compound-target complex formation, as well as cellular permeability, specificity and cytotoxicity-the toxicity-affinity-permeability-selectivity (TAPS) technique. The TAPS assay is exemplified here using human kynurenine 3-monooxygenase (KMO), a challenging intracellular membrane protein target of significant current interest. TAPS confirmed target binding of known KMO inhibitors inside cells. We conclude that the TAPS assay can be used to facilitate intracellular hit validation on most, if not all intracellular drug targets.
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Multi-Agent Cooperative Target Search
Directory of Open Access Journals (Sweden)
Jinwen Hu
2014-05-01
Full Text Available This paper addresses a vision-based cooperative search for multiple mobile ground targets by a group of unmanned aerial vehicles (UAVs with limited sensing and communication capabilities. The airborne camera on each UAV has a limited field of view and its target discriminability varies as a function of altitude. First, by dividing the whole surveillance region into cells, a probability map can be formed for each UAV indicating the probability of target existence within each cell. Then, we propose a distributed probability map updating model which includes the fusion of measurement information, information sharing among neighboring agents, information decay and transmission due to environmental changes such as the target movement. Furthermore, we formulate the target search problem as a multi-agent cooperative coverage control problem by optimizing the collective coverage area and the detection performance. The proposed map updating model and the cooperative control scheme are distributed, i.e., assuming that each agent only communicates with its neighbors within its communication range. Finally, the effectiveness of the proposed algorithms is illustrated by simulation.
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Optimization of OT-MACH Filter Generation for Target Recognition
Johnson, Oliver C.; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin
2009-01-01
An automatic Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter generator for use in a gray-scale optical correlator (GOC) has been developed for improved target detection at JPL. While the OT-MACH filter has been shown to be an optimal filter for target detection, actually solving for the optimum is too computationally intensive for multiple targets. Instead, an adaptive step gradient descent method was tested to iteratively optimize the three OT-MACH parameters, alpha, beta, and gamma. The feedback for the gradient descent method was a composite of the performance measures, correlation peak height and peak to side lobe ratio. The automated method generated and tested multiple filters in order to approach the optimal filter quicker and more reliably than the current manual method. Initial usage and testing has shown preliminary success at finding an approximation of the optimal filter, in terms of alpha, beta, gamma values. This corresponded to a substantial improvement in detection performance where the true positive rate increased for the same average false positives per image.
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Multiple-Targeted Graphene-based Nanocarrier for Intracellular Imaging of mRNAs
Energy Technology Data Exchange (ETDEWEB)
Wang, Ying; Li, Zhaohui; Liu, Misha; Hu, Dehong; Lin, Yuehe; Li, Jinghong
2017-08-29
Simultaneous detection and imaging of multiple intracellular messenger RNA (mRNAs) hold great significant for early cancer diagnostics and preventive medicine development. Herein, we propose a multiple-targeted graphene oxide (GO) nanocarrier that can simultaneously detect and image different type mRNAs in living cells. First of all, in vitro detection of multiple targets have been realized successfully based on the multiple-targeted GO nanocarrier with linear relationship ranging from 3 nM to 200 nM, as well as sensitive detection limit of 1.84 nM for manganese superoxide dismutase (Mn-SOD) mRNA and 2.45 nM for β-actin mRNA. Additionally, this nanosensing platform composed of fluorescent labeled single strand DNA probes and GO nanocarrier can identify Mn-SOD mRNA and endogenous mRNA of β-actin in living cancer cells, showing rapid response, high specificity, nuclease stability, and good biocompatibility during the cell imaging. Thirdly, changes of the expression levels of mRNA in living cells before or after the drug treatment can be monitored successfully. By using multiple ssDNA as probes and GO nanocarrier as the cellular delivery cargo, the proposed simultaneous multiple-targeted sensing platform will be of great potential as a powerful tool for intracellular trafficking process from basic research to clinical diagnosis.
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Drug Target Interference in Immunogenicity Assays: Recommendations and Mitigation Strategies.
Zhong, Zhandong Don; Clements-Egan, Adrienne; Gorovits, Boris; Maia, Mauricio; Sumner, Giane; Theobald, Valerie; Wu, Yuling; Rajadhyaksha, Manoj
2017-11-01
Sensitive and specific methodology is required for the detection and characterization of anti-drug antibodies (ADAs). High-quality ADA data enables the evaluation of potential impact of ADAs on the drug pharmacokinetic profile, patient safety, and efficacious response to the drug. Immunogenicity assessments are typically initiated at early stages in preclinical studies and continue throughout the drug development program. One of the potential bioanalytical challenges encountered with ADA testing is the need to identify and mitigate the interference mediated by the presence of soluble drug target. A drug target, when present at sufficiently high circulating concentrations, can potentially interfere with the performance of ADA and neutralizing antibody (NAb) assays, leading to either false-positive or, in some cases, false-negative ADA and NAb assay results. This publication describes various mechanisms of assay interference by soluble drug target, as well as strategies to recognize and mitigate such target interference. Pertinent examples are presented to illustrate the impact of target interference on ADA and NAb assays as well as several mitigation strategies, including the use of anti-target antibodies, soluble versions of the receptors, target-binding proteins, lectins, and solid-phase removal of targets. Furthermore, recommendations for detection and mitigation of such interference in different formats of ADA and NAb assays are provided.
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Flash trajectory imaging of target 3D motion
Wang, Xinwei; Zhou, Yan; Fan, Songtao; He, Jun; Liu, Yuliang
2011-03-01
We present a flash trajectory imaging technique which can directly obtain target trajectory and realize non-contact measurement of motion parameters by range-gated imaging and time delay integration. Range-gated imaging gives the range of targets and realizes silhouette detection which can directly extract targets from complex background and decrease the complexity of moving target image processing. Time delay integration increases information of one single frame of image so that one can directly gain the moving trajectory. In this paper, we have studied the algorithm about flash trajectory imaging and performed initial experiments which successfully obtained the trajectory of a falling badminton. Our research demonstrates that flash trajectory imaging is an effective approach to imaging target trajectory and can give motion parameters of moving targets.
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Santagata, Sara; Portella, Luigi; Napolitano, Maria; Greco, Adelaide; D'Alterio, Crescenzo; Barone, Maria Vittoria; Luciano, Antonio; Gramanzini, Matteo; Auletta, Luigi; Arra, Claudio; Zannetti, Antonella; Scala, Stefania
2017-05-31
C-X-C chemokine receptor 4 (CXCR4) is over-expressed in multiple human cancers and correlates with tumor aggressiveness, poor prognosis and increased risk for distant metastases. Imaging agents for CXCR4 are thus highly desirable. We developed a novel CXCR4-targeted near-infrared (NIR) fluorescent probe (Peptide R-NIR750) conjugating the new developed CXCR4 peptidic antagonist Peptide R with the NIR fluorescent dye VivoTag-S750. Specific CXCR4 binding was obtained in cells overexpressing human CXCR4 (B16-hCXCR4 and human melanoma cells PES43), but not in CXCR4 low expressing cells (FB-1). Ex vivo evaluation demonstrated that PepR-NIR750 specifically detects B16-hCXCR4-derived subcutaneous tumors and lung metastases. Fluorescence Molecular Tomography (FMT) in vivo imaging was performed on mice carrying subcutaneous CHO and CHO-CXCR4 tumors. PepR-NIR750 accumulates only in CXCR4-positive expressing subcutaneous tumors. Additionally, an intense NIR fluorescence signal was detected in PES43-derived lung metastases of nude mice injected with PepR-NIR750 versus mice injected with VivoTag-S750. With a therapeutic intent, mice bearing PES43-derived lung metastases were treated with Peptide R. A the dramatic reduction in PES43-derived lung metastases was detected through a decrease of the PepR-NIR750 signal. PepR-NIR750 is a specific probe for non-invasive detection of human high CXCR4-expressing tumors and metastatic lesion and thus a valuable tool for cancer molecular imaging.
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A Semiparametric Model for Hyperspectral Anomaly Detection
2012-01-01
treeline ) in the presence of natural background clutter (e.g., trees, dirt roads, grasses). Each target consists of about 7 × 4 pixels, and each pixel...vehicles near the treeline in Cube 1 (Figure 1) constitutes the target set, but, since anomaly detectors are not designed to detect a particular target
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Li, Dong; Wei, Zhen; Song, Dawei; Sun, Wenfeng; Fan, Xiaoyan
2016-11-01
With the development of space technology, the number of spacecrafts and debris are increasing year by year. The demand for detecting and identification of spacecraft is growing strongly, which provides support to the cataloguing, crash warning and protection of aerospace vehicles. The majority of existing approaches for three-dimensional reconstruction is scattering centres correlation, which is based on the radar high resolution range profile (HRRP). This paper proposes a novel method to reconstruct the threedimensional scattering centre structure of target from a sequence of radar ISAR images, which mainly consists of three steps. First is the azimuth scaling of consecutive ISAR images based on fractional Fourier transform (FrFT). The later is the extraction of scattering centres and matching between adjacent ISAR images using grid method. Finally, according to the coordinate matrix of scattering centres, the three-dimensional scattering centre structure is reconstructed using improved factorization method. The three-dimensional structure is featured with stable and intuitive characteristic, which provides a new way to improve the identification probability and reduce the complexity of the model matching library. A satellite model is reconstructed using the proposed method from four consecutive ISAR images. The simulation results prove that the method has gotten a satisfied consistency and accuracy.
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Zhou, Jin; Shi, Wen; Li, Lihong; Gong, Qiuyu; Wu, Xiaofeng; Li, Xiaohua; Ma, Huimin
2016-04-19
Tyrosinase is regarded as an important biomarker of melanoma cancer, and its metabolism is closely related to some severe skin diseases such as vitiligo. Since tyrosinase is mainly located in the melanosomes of melanocytes, a probe that can specifically detect and image tysosinase in melanosomes would be in urgent demand to study the behavior of the enzyme in cells, but unfortunately, no melanosome-targeting tyrosinase fluorescent probe has been reported so far to the best of our knowledge. In this work, we have developed such a new probe, Mela-TYR, which bears morpholine as a melanosome-targeting group and 4-aminophenol as a tyrosinase reaction group. The probe exhibits not only a highly sensitive and selective off-on response to tyrosinase via oxidization cleavage, but also an accurate targeting ability toward the acidic organelles of melanosomes and lyososomes, which is validated by colocalization experiments with mCherry-tagged melanosomes as well as DND-99 (a commercial dye). The probe has been used to image the relative contents of tyrosinase in different cells. Notably, because of the tyrosinase deficiency in normal lysosomes, the probe only fluoresces in melanosomes in principle although it can accumulate in other acidic organelles like lysosomes. By virtue of this property, the misdistribution of tyrosinase from melanosomes to lysosomes in murine melanoma B16 cells under the stimulation of inulavosin is imaged in real time for the first time. Moreover, the upregulation of melanosomal tyrosinase in live B16 cells under the stimulation of psoralen/ultraviolet A is detected with our probe, and this upregulation is further verified by standard colorimetric assay. The probe provides a simple, visual method to study the metabolism of tyrosinase in cells and shows great potential in clinical diagnosis and treatments of tyrosinase-associated diseases.
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Marchetto, Aruna; Gerke, Julia S.; Rubio, Rebeca Alba; Kiran, Merve M.; Musa, Julian; Knott, Maximilian M. L.; Ohmura, Shunya; Li, Jing; Akpolat, Nusret; Akatli, Ayse N.; Özen, Özlem; Dirksen, Uta; Hartmann, Wolfgang; de Alava, Enrique; Baumhoer, Daniel; Sannino, Giuseppina; Kirchner, Thomas; Grünewald, Thomas G. P.
2018-01-01
Ewing sarcoma is an undifferentiated small-round-cell sarcoma. Although molecular detection of pathognomonic EWSR1-ETS fusions such as EWSR1-FLI1 enables definitive diagnosis, substantial confusion can arise if molecular diagnostics are unavailable. Diagnosis based on the conventional immunohistochemical marker CD99 is unreliable due to its abundant expression in morphological mimics. To identify novel diagnostic immunohistochemical markers for Ewing sarcoma, we performed comparative expression analyses in 768 tumors representing 21 entities including Ewing-like sarcomas, which confirmed that CIC-DUX4-, BCOR-CCNB3-, EWSR1-NFATc2-, and EWSR1-ETS-translocated sarcomas are distinct entities, and revealed that ATP1A1, BCL11B, and GLG1 constitute specific markers for Ewing sarcoma. Their high expression was validated by immunohistochemistry and proved to depend on EWSR1-FLI1-binding to highly active proximal super-enhancers. Automated cut-off-finding and combination-testing in a tissue-microarray comprising 174 samples demonstrated that detection of high BCL11B and/or GLG1 expression is sufficient to reach 96% specificity for Ewing sarcoma. While 88% of tested Ewing-like sarcomas displayed strong CD99-immunoreactivity, none displayed combined strong BCL11B- and GLG1-immunoreactivity. Collectively, we show that ATP1A1, BCL11B, and GLG1 are EWSR1-FLI1 targets, of which BCL11B and GLG1 offer a fast, simple, and cost-efficient way to diagnose Ewing sarcoma by immunohistochemistry. These markers may significantly reduce the number of misdiagnosed patients, and thus improve patient care. PMID:29416716
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Ma, Huilian; Jin, Jing; Li, Yun; Chen, Jiping
2017-10-08
A method of comprehensive screening of the target and non-target volatile organic compounds (VOCs) in industrial exhaust gas using thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) has been developed. In this paper, two types of solid phase adsorption column were compared, and the Tenex SS TD Tube was selected. The analytes were enriched into the adsorption tube by constant flow sampling, and detected by TD-GC-MS in full scan mode. Target compounds were quantified by internal standard method, and the quantities of non-target compounds were calculated by response coefficient of toluene. The method detection limits (MDLs) for the 24 VOCs were 1.06 to 5.44 ng, and MDLs could also be expressed as 0.004 to 0.018 mg/m 3 assuming that the sampling volume was 300 mL. The average recoveries were in the range of 78.4% to 89.4% with the relative standard deviations (RSDs) of 3.9% to 14.4% ( n =7). The established analytical method was applied for the comprehensive screening of VOCs in a waste incineration power plant in Dalian city. Twenty-nine VOCs were identified. In these compounds, only five VOCs were the target compounds set in advance, which accounted for 26.7% of the total VOCs identified. Therefore, this study further proved the importance of screening non-target compounds in the analysis of VOCs in industrial exhaust gas, and has certain reference significance for the complete determination of VOCs distribution.
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DETECTION OF POTENTIAL TRANSIT SIGNALS IN 16 QUARTERS OF KEPLER MISSION DATA
International Nuclear Information System (INIS)
Tenenbaum, Peter; Jenkins, Jon M.; Seader, Shawn; Burke, Christopher J.; Christiansen, Jessie L.; Rowe, Jason F.; Caldwell, Douglas A.; Clarke, Bruce D.; Coughlin, Jeffrey L.; Li, Jie; Quintana, Elisa V.; Smith, Jeffrey C.; Thompson, Susan E.; Twicken, Joseph D.; Haas, Michael R.; Henze, Christopher E.; Hunter, Roger C.; Sanderfer, Dwight T.; Campbell, Jennifer R.; Girouard, Forrest R.
2014-01-01
We present the results of a search for potential transit signals in 4 yr of photometry data acquired by the Kepler mission. The targets of the search include 111,800 stars which were observed for the entire interval and 85,522 stars which were observed for a subset of the interval. We found that 9743 targets contained at least one signal consistent with the signature of a transiting or eclipsing object where the criteria for detection are periodicity of the detected transits, adequate signal-to-noise ratio, and acceptance by a number of tests which reject false positive detections. When targets that had produced a signal were searched repeatedly, an additional 6542 signals were detected on 3223 target stars, for a total of 16,285 potential detections. Comparison of the set of detected signals with a set of known and vetted transit events in the Kepler field of view shows that the recovery rate for these signals is 96.9%. The ensemble properties of the detected signals are reviewed
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DETECTION OF POTENTIAL TRANSIT SIGNALS IN 16 QUARTERS OF KEPLER MISSION DATA
Energy Technology Data Exchange (ETDEWEB)
Tenenbaum, Peter; Jenkins, Jon M.; Seader, Shawn; Burke, Christopher J.; Christiansen, Jessie L.; Rowe, Jason F.; Caldwell, Douglas A.; Clarke, Bruce D.; Coughlin, Jeffrey L.; Li, Jie; Quintana, Elisa V.; Smith, Jeffrey C.; Thompson, Susan E.; Twicken, Joseph D. [SETI Institute/NASA Ames Research Center, Moffett Field, CA 94305 (United States); Haas, Michael R.; Henze, Christopher E.; Hunter, Roger C.; Sanderfer, Dwight T. [NASA Ames Research Center, Moffett Field, CA 94305 (United States); Campbell, Jennifer R.; Girouard, Forrest R., E-mail: peter.tenenbaum@nasa.gov [Orbital Sciences Corporation/NASA Ames Research Center, Moffett Field, CA 94305 (United States); and others
2014-03-01
We present the results of a search for potential transit signals in 4 yr of photometry data acquired by the Kepler mission. The targets of the search include 111,800 stars which were observed for the entire interval and 85,522 stars which were observed for a subset of the interval. We found that 9743 targets contained at least one signal consistent with the signature of a transiting or eclipsing object where the criteria for detection are periodicity of the detected transits, adequate signal-to-noise ratio, and acceptance by a number of tests which reject false positive detections. When targets that had produced a signal were searched repeatedly, an additional 6542 signals were detected on 3223 target stars, for a total of 16,285 potential detections. Comparison of the set of detected signals with a set of known and vetted transit events in the Kepler field of view shows that the recovery rate for these signals is 96.9%. The ensemble properties of the detected signals are reviewed.
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Chen, Zongbao; Lu, Minghua
2016-11-01
A novel electrochemical sensing platform based on manganese dioxide (MnO2) nanosheets was developed for sensitive screening of target cocaine with the signal amplification. Ferrocene-labeled cocaine aptamers were initially immobilized onto MnO2 nanosheets-modified screen-printed carbon electrode because of π-stacking interaction between nucleobases and nanosheets. The immobilized ferrocene-aptamer activated the electrical contact with the electrode, thereby resulting in the sensor circuit to switch on. Upon target cocaine introduction, the analyte reacted with the aptamer and caused the dissociation of ferrocene-aptamer from the electrode, thus giving rise to the detection circuit to switch off. The released aptamer was cleaved by DNase I with target recycling. Under optimal conditions, the decreasing percentage of the electronic signal relative to background current increased with the increasing cocaine concentration in the dynamic range of 0.1-20nM, and the detection limit was 32pM. The reproducibility, selectivity and method accuracy were acceptable. Importantly, this concept offers promise for rapid, simple, and cost-effective analysis of cocaine biological samples without the needs of sample separation and multiple washing steps. Copyright © 2016 Elsevier B.V. All rights reserved.
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Directory of Open Access Journals (Sweden)
Koji Hashimoto
2016-05-01
Full Text Available We have developed a novel gene detection method based on the loop-mediated isothermal amplification (LAMP reaction and the DNA dissociation reaction on the same DNA chip surface to achieve a lower detection limit, broader dynamic range and faster detection time than are attainable with a conventional DNA chip. Both FAM- and thiol-labeled DNA probe bound to the complementary sequence accompanying Dabcyl was immobilized on the gold surface via Au/thiol bond. The LAMP reaction was carried out on the DNA probe fixed gold surface. At first, Dabcyl molecules quenched the FAM fluorescence. According to the LAMP reaction, the complementary sequence with Dabcyl was competitively reacted with the amplified targeted sequence. As a result, the FAM fluorescence increased owing to dissociation of the complementary sequence from the DNA probe. The simultaneous reaction of LAMP and DNA chip detection was achieved, and 103 copies of the targeted gene were detected within an hour by measuring fluorescence intensity of the DNA probe. Keywords: Biosensor, DNA chip, Loop-mediated isothermal amplification (LAMP, Fluorescence detection, Gold substrate, Au/thiol bond
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Qurollo, Barbara A; Archer, Nikole R; Schreeg, Megan E; Marr, Henry S; Birkenheuer, Adam J; Haney, Kaitlin N; Thomas, Brittany S; Breitschwerdt, Edward B
2017-03-07
Babesiosis is a protozoal, tick transmitted disease found worldwide in humans, wildlife and domesticated animals. Commonly used approaches to diagnose babesiosis include microscopic examination of peripheral blood smears, detection of circulating antibodies and PCR. To screen and differentiate canine Babesia infections many PCR assays amplify the 18S rRNA gene. These sequences contain hypervariable regions flanked by highly conserved regions allowing for amplification of a broad-range of Babesia spp. However, differences in the 18S rRNA gene sequence of distantly related clades can make it difficult to design assays that will amplify all Babesia species while excluding the amplification of other eukaryotes. By targeting Babesia mitochondrial genome (mtDNA), we designed a novel three primer qPCR with greater sensitivity and broader screening capabilities to diagnose and differentiate Babesia spp. Using 13 Babesia mtDNA sequences, a region spanning two large subunit rRNA gene fragments (lsu5-lsu4) was aligned to design three primers for use in a qPCR assay (LSU qPCR) capable of amplifying a wide range of Babesia spp. Plasmid clones were generated and used as standards to determine efficiency, linear dynamic range and analytical sensitivity. Animals naturally infected with vector-borne pathogens were tested retrospectively and prospectively to determine relative clinical sensitivity and specificity by comparing the LSU qPCR to an established 18S rDNA qPCR. The LSU qPCR efficiencies ranged between 92 and 100% with the limit of detection at five copies/reaction. The assay did not amplify mammalian host or other vector-borne pathogen gDNA except Cytauxzoon felis (a feline protozoal pathogen). The LSU qPCR assay amplified 12 different Babesia. sp. and C. felis from 31/31 (100%) archived samples, whereas the 18S qPCR amplified only 26/31 (83.9%). By prospective analysis, 19/394 diagnostic accessions (4.8%) were LSU qPCR positive, compared to 11/394 (2.8%) 18S rDNA q
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TargetSpy: a supervised machine learning approach for microRNA target prediction.
Sturm, Martin; Hackenberg, Michael; Langenberger, David; Frishman, Dmitrij
2010-05-28
Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences.In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila