Strategic project selection based on evidential reasoning approach for high-end equipment manufacturing industry

Directory of Open Access Journals (Sweden)

Lu Guangyan

2017-01-01

Full Text Available With the rapid development of science and technology, emerging information technologies have significantly changed the daily life of people. In such context, strategic project selection for high-end equipment manufacturing industries faces more and more complexities and uncertainties with the consideration of several complex criteria. For example, a group of experts rather than a single expert should be invited to select strategic project for high-end equipment manufacturing industries and the experts may feel difficulty to express their preferences towards different strategic projects due to their limited cognitive capabilities. In order to handle these complexities and uncertainties, the criteria framework of strategic project selection is firstly constructed based on the characteristics of high-end equipment manufacturing industries and then evidential reasoning (ER approach is introduced in this paper to help experts express their uncertain preferences and aggregate these preferences to generate an appropriate strategic project. A real case of strategic project selection in a high-speed train manufacturing enterprise is investigated to demonstrate the validity of the ER approach in solving strategic project selection problem.

Frequency-Wavenumber (FK)-Based Data Selection in High-Frequency Passive Surface Wave Survey

Science.gov (United States)

Cheng, Feng; Xia, Jianghai; Xu, Zongbo; Hu, Yue; Mi, Binbin

2018-04-01

Passive surface wave methods have gained much attention from geophysical and civil engineering communities because of the limited application of traditional seismic surveys in highly populated urban areas. Considering that they can provide high-frequency phase velocity information up to several tens of Hz, the active surface wave survey would be omitted and the amount of field work could be dramatically reduced. However, the measured dispersion energy image in the passive surface wave survey would usually be polluted by a type of "crossed" artifacts at high frequencies. It is common in the bidirectional noise distribution case with a linear receiver array deployed along roads or railways. We review several frequently used passive surface wave methods and derive the underlying physics for the existence of the "crossed" artifacts. We prove that the "crossed" artifacts would cross the true surface wave energy at fixed points in the f-v domain and propose a FK-based data selection technique to attenuate the artifacts in order to retrieve the high-frequency information. Numerical tests further demonstrate the existence of the "crossed" artifacts and indicate that the well-known wave field separation method, FK filter, does not work for the selection of directional noise data. Real-world applications manifest the feasibility of the proposed FK-based technique to improve passive surface wave methods by a priori data selection. Finally, we discuss the applicability of our approach.

Frequency-Wavenumber (FK)-Based Data Selection in High-Frequency Passive Surface Wave Survey

Science.gov (United States)

Cheng, Feng; Xia, Jianghai; Xu, Zongbo; Hu, Yue; Mi, Binbin

2018-07-01

Passive surface wave methods have gained much attention from geophysical and civil engineering communities because of the limited application of traditional seismic surveys in highly populated urban areas. Considering that they can provide high-frequency phase velocity information up to several tens of Hz, the active surface wave survey would be omitted and the amount of field work could be dramatically reduced. However, the measured dispersion energy image in the passive surface wave survey would usually be polluted by a type of "crossed" artifacts at high frequencies. It is common in the bidirectional noise distribution case with a linear receiver array deployed along roads or railways. We review several frequently used passive surface wave methods and derive the underlying physics for the existence of the "crossed" artifacts. We prove that the "crossed" artifacts would cross the true surface wave energy at fixed points in the f- v domain and propose a FK-based data selection technique to attenuate the artifacts in order to retrieve the high-frequency information. Numerical tests further demonstrate the existence of the "crossed" artifacts and indicate that the well-known wave field separation method, FK filter, does not work for the selection of directional noise data. Real-world applications manifest the feasibility of the proposed FK-based technique to improve passive surface wave methods by a priori data selection. Finally, we discuss the applicability of our approach.

Computational design for a wide-angle cermet-based solar selective absorber for high temperature applications

International Nuclear Information System (INIS)

Sakurai, Atsushi; Tanikawa, Hiroya; Yamada, Makoto

2014-01-01

The purpose of this study is to computationally design a wide-angle cermet-based solar selective absorber for high temperature applications by using a characteristic matrix method and a genetic algorithm. The present study investigates a solar selective absorber with tungsten–silica (W–SiO 2 ) cermet. Multilayer structures of 1, 2, 3, and 4 layers and a wide range of metal volume fractions are optimized. The predicted radiative properties show good solar performance, i.e., thermal emittances, especially beyond 2 μm, are quite low, in contrast, solar absorptance levels are successfully high with wide angular range, so that solar photons are effectively absorbed and infrared radiative heat loss can be decreased. -- Highlights: • Electromagnetic simulation of radiative properties by characteristic matrix method. • Optimization for multilayered W–SiO 2 cermet-based absorber by a Genetic Algorithm. • We propose a successfully high solar performance of solar selective absorber

Solvent effects on the excited-state double proton transfer mechanism in the 7-azaindole dimer: a TDDFT study with the polarizable continuum model.

Science.gov (United States)

Yu, Xue-Fang; Yamazaki, Shohei; Taketsugu, Tetsuya

2017-08-30

Solvent effects on the excited-state double proton transfer (ESDPT) mechanism in the 7-azaindole (7AI) dimer were investigated using the time-dependent density functional theory (TDDFT) method. Excited-state potential energy profiles along the reaction paths in a locally excited (LE) state and a charge transfer (CT) state were calculated using the polarizable continuum model (PCM) to include the solvent effect. A series of non-polar and polar solvents with different dielectric constants were used to examine the polarity effect on the ESDPT mechanism. The present results suggest that in a non-polar solvent and a polar solvent with a small dielectric constant, ESDPT follows a concerted mechanism, similar to the case in the gas phase. In a polar solvent with a relatively large dielectric constant, however, ESDPT is likely to follow a stepwise mechanism via a stable zwitterionic intermediate in the LE state on the adiabatic potential energy surface, although inclusion of zero-point vibrational energy (ZPE) corrections again suggests the concerted mechanism. In the meantime, the stepwise reaction path involving the CT state with neutral intermediates is also examined, and is found to be less competitive than the concerted or stepwise path in the LE state in both non-polar and polar solvents. The present study provides a new insight into the experimental controversy of the ESDPT mechanism of the 7AI dimer in a solution.

Origin of high oxide to nitride polishing selectivity of ceria-based slurry in the presence of picolinic acid

Institute of Scientific and Technical Information of China (English)

Wang Liang-Yong; Liu Bo; Song Zhi-Tang; Liu Wei-Li; Feng Song-Lin; David Huang; S.V Babu

2011-01-01

We report on the investigation of the origin of high oxide to nitride polishing selectivity of ceria-based slurry in the presence of picolinic acid. The oxide to nitride removal selectivity of the ceria slurry with picolinic acid is as high as 76.6 in the chemical mechanical polishing. By using zeta potential analyzer, particle size analyzer, horizon profilometer, thermogravimetric analysis and Fourier transform infrared spectroscopy, the pre-and the post-polished wafer surfaces as well as the pre-and the post-used ceria-based slurries are compared. Possible mechanism of high oxide to nitride selectivity with using ceria-based slurry with picolinic acid is discussed.

Highly Selective and Sensitive Self-Powered Glucose Sensor Based on Capacitor Circuit.

Science.gov (United States)

Slaughter, Gymama; Kulkarni, Tanmay

2017-05-03

Enzymatic glucose biosensors are being developed to incorporate nanoscale materials with the biological recognition elements to assist in the rapid and sensitive detection of glucose. Here we present a highly sensitive and selective glucose sensor based on capacitor circuit that is capable of selectively sensing glucose while simultaneously powering a small microelectronic device. Multi-walled carbon nanotubes (MWCNTs) is chemically modified with pyrroloquinoline quinone glucose dehydrogenase (PQQ-GDH) and bilirubin oxidase (BOD) at anode and cathode, respectively, in the biofuel cell arrangement. The input voltage (as low as 0.25 V) from the biofuel cell is converted to a stepped-up power and charged to the capacitor to the voltage of 1.8 V. The frequency of the charge/discharge cycle of the capacitor corresponded to the oxidation of glucose. The biofuel cell structure-based glucose sensor synergizes the advantages of both the glucose biosensor and biofuel cell. In addition, this glucose sensor favored a very high selectivity towards glucose in the presence of competing and non-competing analytes. It exhibited unprecedented sensitivity of 37.66 Hz/mM.cm 2 and a linear range of 1 to 20 mM. This innovative self-powered glucose sensor opens new doors for implementation of biofuel cells and capacitor circuits for medical diagnosis and powering therapeutic devices.

Origin of high oxide to nitride polishing selectivity of ceria-based slurry in the presence of picolinic acid

International Nuclear Information System (INIS)

Wang Liang-Yong; Liu Bo; Song Zhi-Tang; Liu Wei-Li; Feng Song-Lin; David Huang; Babu, S.V

2011-01-01

We report on the investigation of the origin of high oxide to nitride polishing selectivity of ceria-based slurry in the presence of picolinic acid. The oxide to nitride removal selectivity of the ceria slurry with picolinic acid is as high as 76.6 in the chemical mechanical polishing. By using zeta potential analyzer, particle size analyzer, horizon profilometer, thermogravimetric analysis and Fourier transform infrared spectroscopy, the pre- and the post-polished wafer surfaces as well as the pre- and the post-used ceria-based slurries are compared. Possible mechanism of high oxide to nitride selectivity with using ceria-based slurry with picolinic acid is discussed. (interdisciplinary physics and related areas of science and technology)

Highly selective thiocyanate optochemical sensor based on manganese(III)-salophen ionophore

International Nuclear Information System (INIS)

Abdel-Haleem, Fatehy M.; Rizk, Mahmoud S.

2017-01-01

We report on the development of optochemical sensor based on Mn(III)-salophen ionophore. The sensor was prepared by embedding the ionophore in a plasticized poly (vinyl chloride) impregnated with the chromoionophore ETH7075. Optical response to thiocyanate occurred due to thiocyanate extraction into the polymer via formation of strong complex with the ionophore and simultaneous protonation of the indicator dye yielding the optical response at 545 nm. The developed optochemical sensor exhibited high selectivity for thiocyanate over other anions including the most lipophilic species such as salicylate and perchlorate. For instance, the optical selectivity coefficients, logK SCN,anion opt , were as follow: ClO 4 − = − 5.8; Sal − = − 4.0; NO 3 − ˂ − 6. Further, the thiocyanate optical selectivity obtained using the present optochemical sensor was greatly enhanced in comparison with that obtained using an anion-exchanger based sensor. Also, the optimized optochemical sensor exhibited micro-molar detection limit with 2 min response time at pH 4.5 using acetate buffer. The reversibility of the optimized sensor was poor due to strong ligation of the thiocyanate to the central Metal ion, log K = 14.1, which can be overcome by soaking the optode in sodium hydroxide followed by soaking in buffer solution. The developed sensor was utilized successfully for the determination of thiocyanate in human saliva and in spiked saliva samples. - Highlights: • Preparation of different optodes using different compositions • Mechanism depends on co-extraction of thiocyanate and protons to membrane. • Sensor showed excellent selectivity. • Sensor could be applied for thiocyanate determination in real saliva.

Highly selective thiocyanate optochemical sensor based on manganese(III)-salophen ionophore

Energy Technology Data Exchange (ETDEWEB)

Abdel-Haleem, Fatehy M., E-mail: fatehy@sci.cu.edu.eg; Rizk, Mahmoud S.

2017-06-01

We report on the development of optochemical sensor based on Mn(III)-salophen ionophore. The sensor was prepared by embedding the ionophore in a plasticized poly (vinyl chloride) impregnated with the chromoionophore ETH7075. Optical response to thiocyanate occurred due to thiocyanate extraction into the polymer via formation of strong complex with the ionophore and simultaneous protonation of the indicator dye yielding the optical response at 545 nm. The developed optochemical sensor exhibited high selectivity for thiocyanate over other anions including the most lipophilic species such as salicylate and perchlorate. For instance, the optical selectivity coefficients, logK{sub SCN,anion}{sup opt}, were as follow: ClO{sub 4}{sup −} = − 5.8; Sal{sup −} = − 4.0; NO{sub 3}{sup −} ˂ − 6. Further, the thiocyanate optical selectivity obtained using the present optochemical sensor was greatly enhanced in comparison with that obtained using an anion-exchanger based sensor. Also, the optimized optochemical sensor exhibited micro-molar detection limit with 2 min response time at pH 4.5 using acetate buffer. The reversibility of the optimized sensor was poor due to strong ligation of the thiocyanate to the central Metal ion, log K = 14.1, which can be overcome by soaking the optode in sodium hydroxide followed by soaking in buffer solution. The developed sensor was utilized successfully for the determination of thiocyanate in human saliva and in spiked saliva samples. - Highlights: • Preparation of different optodes using different compositions • Mechanism depends on co-extraction of thiocyanate and protons to membrane. • Sensor showed excellent selectivity. • Sensor could be applied for thiocyanate determination in real saliva.

Tuning PIM-PI-Based Membranes for Highly Selective Transport of Propylene/Propane

KAUST Repository

Swaidan, Ramy J.

2016-12-06

To date there exists a great deal of energetic and economic inefficiency in the separation of olefins from paraffins because the principal means of achieving industrial purity requirements is accomplished with very energy intensive cryogenic distillation. Mitigation of the severe energy intensity of the propylene/propane separation has been identified as one of seven chemical separations which can change the landscape of global energy use, and membranes have been targeted as an emerging technology because they offer scalability and lower capital and operating costs. The focus of this work was to evaluate a new direction of material development for the very industrially relevant propylene/propane separation using membranes. The objective was to develop a rational design approach for generating highly selective membranes using a relatively new platform of materials known as polyimides of intrinsic microporosity (PIM-PIs), the prospects of which have never been examined for the propylene/propane separation. Structurally, PIMs comprise relatively inflexible macromolecular architectures integrating contortion sites that help disrupt packing and trap microporous free volume elements (< 20 Å). To date most of the work reported in the literature on this separation is based on conventional low free volume 6FDA-based polyimides which in the best case show moderate C3H6/C3H8 selectivities (<20) with C3H6 permeabilities too low to garner industrial interest. Due to propylene and propane’s relatively large molecular size, we hypothesized that the use of more open structures can provide greater accessibility to the pores necessary to enhance membrane sieving and flux. It has been shown for numerous key gas separations that introduction of microporosity into a polymer structure can defy the notorious permeability/selectivity tradeoff curve and induce simultaneous boosts in both permeability and selectivity. The cornerstone approach to designing state of the art high

Highly Sensitive and Selective Potassium Ion Detection Based on Graphene Hall Effect Biosensors

Directory of Open Access Journals (Sweden)

Xiangqi Liu

2018-03-01

Full Text Available Potassium (K+ ion is an important biological substance in the human body and plays a critical role in the maintenance of transmembrane potential and hormone secretion. Several detection techniques, including fluorescent, electrochemical, and electrical methods, have been extensively investigated to selectively recognize K+ ions. In this work, a highly sensitive and selective biosensor based on single-layer graphene has been developed for K+ ion detection under Van der Pauw measurement configuration. With pre-immobilization of guanine-rich DNA on the graphene surface, the graphene devices exhibit a very low limit of detection (≈1 nM with a dynamic range of 1 nM–10 μM and excellent K+ ion specificity against other alkali cations, such as Na+ ions. The origin of K+ ion selectivity can be attributed to the fact that the formation of guanine-quadruplexes from guanine-rich DNA has a strong affinity for capturing K+ ions. The graphene-based biosensors with improved sensing performance for K+ ion recognition can be applied to health monitoring and early disease diagnosis.

Genetic Particle Swarm Optimization–Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection

Science.gov (United States)

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-01-01

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm. PMID:27483285

Genetic Particle Swarm Optimization-Based Feature Selection for Very-High-Resolution Remotely Sensed Imagery Object Change Detection.

Science.gov (United States)

Chen, Qiang; Chen, Yunhao; Jiang, Weiguo

2016-07-30

In the field of multiple features Object-Based Change Detection (OBCD) for very-high-resolution remotely sensed images, image objects have abundant features and feature selection affects the precision and efficiency of OBCD. Through object-based image analysis, this paper proposes a Genetic Particle Swarm Optimization (GPSO)-based feature selection algorithm to solve the optimization problem of feature selection in multiple features OBCD. We select the Ratio of Mean to Variance (RMV) as the fitness function of GPSO, and apply the proposed algorithm to the object-based hybrid multivariate alternative detection model. Two experiment cases on Worldview-2/3 images confirm that GPSO can significantly improve the speed of convergence, and effectively avoid the problem of premature convergence, relative to other feature selection algorithms. According to the accuracy evaluation of OBCD, GPSO is superior at overall accuracy (84.17% and 83.59%) and Kappa coefficient (0.6771 and 0.6314) than other algorithms. Moreover, the sensitivity analysis results show that the proposed algorithm is not easily influenced by the initial parameters, but the number of features to be selected and the size of the particle swarm would affect the algorithm. The comparison experiment results reveal that RMV is more suitable than other functions as the fitness function of GPSO-based feature selection algorithm.

[18F]fluoromethylated phenyl-pyrroles and 7-azaindole analog as potential dopamine D4 receptor imaging agents

International Nuclear Information System (INIS)

Ji, D. Y.; Oh, S. Z.; Choi, Y. S.; Lee, K. C.; Kim, S. E.; Choi, Y.; Lee, K. H.; Kim, B. T.

1997-01-01

An association between the dopamine D 4 receptor and schizophrenia was recently suggested and the D 4 receptor antagonists may thus have potential in elucidating the role of the receptor in schizophrenic patients. The purpose of this study was to develop some of these antagonists as potential dopamine D 4 receptor imaging agents for PET. We have prepared 1-(3-[ 18 F]fluoromethylphenyl)-3-([4-(pyridin-2-yl)piperazin-1-yl)methyl) pyrrole (1), 1-(3-[ 18 F]fluoromethylphenyl)-3-([4-(pyridin-2-yl)piperazin-1-yl)methyl) pyrrole (2), and 3-([4-(4-[ 18 F]fluoro methylbenzyl)piperazin-1-yl)methyl)-1H-pyrrolo(2,3,-b)pyridine (3) as potential imaging agents for the dopamine D 4 receptor for PET. The compounds [ 18 F]1 and [ 18 F]2 were prepared by coupling of (3-[ 18 F]fluoromethylphenyl)-pyrrol-1- yl-3-aldehyde and the piperazine moiety in the presence of NaBH 3 CN. The [ 18 F]fluorinated aldehyde was obtained in 60-85% yield by the displacement of the corresponding mesylate with F-18-(THF, 90 .deg. C, 5 min). HPLC purification (Alltech Econosil C-18 columm, 250 x 10 mm, 35: 65 = 0.1M NH 4 CI 2 H : CH 3 OH, 4 ml/min, t R =26.6 min) gave the [ 18 F]1 and [ 18 F]2 in 7-12% yield. In the case of azaindole 3, a methlene link was inserted between the piperazinyl and a fluoromethyl phenyl group. Radiochemical synthesis of the [ 18 F]3 was carried out by coupling of the piperazne moiety and [ 18 F]fluoromethylbenzyl mesylate in the presence of NEt 3 (3:1-CH 3 CN: DMF, 120 .deg. C, 30 min). Purification was carried out by HPLC using a C-18 column (Alltech Econosil, 50 x 10 mm, 100% 0.1M NH 4 CO 2 H for 5 min followed by 40:60=0.1 M NH 4 CO 2 H : MeOH, 4 ml/min t R =28.7 min). The time of synthesis including HPLC purification was 100 min. The overall yield of [ 18 F]3 was 10-15% with a radiochemical purity better than 97% and a specific activity greater than 1000 ci/mmol

A highly sensitive and selective aptamer-based colorimetric sensor for the rapid detection of PCB 77.

Science.gov (United States)

Cheng, Ruojie; Liu, Siyao; Shi, Huijie; Zhao, Guohua

2018-01-05

A highly sensitive, specific and simple colorimetric sensor based on aptamer was established for the detection of polychlorinated biphenyls (PCB 77). The use of unmodified gold nanoparticles as a colorimetric probe for aptamer sensors enabled the highly sensitive and selective detection of polychlorinated biphenyls (PCB 77). A linear range of 0.5nM to 900nM was obtained for the colorimetric assay with a minimum detection limit of 0.05nM. In addition, by the methods of circular dichroism, UV and naked eyes, we found that the 35 base fragments retained after cutting 5 bases from the 5 'end of aptamer plays the most significant role in the PCB 77 specific recognition process. We found a novel way to truncated nucleotides to optimize the detection of PCB 77, and the selected nucleotides also could achieve high affinity with PCB 77. At the same time, the efficient detection of the PCB 77 by our colorimetric sensor in the complex environmental water samples was realized, which shows a good application prospect. Copyright © 2017 Elsevier B.V. All rights reserved.

Cooperativity of hydrogen-bonded networks in 7-azaindole(CH3OH)n (n=2,3) clusters evidenced by IR-UV ion-dip spectroscopy and natural bond orbital analysis.

Science.gov (United States)

Sakota, Kenji; Kageura, Yutaka; Sekiya, Hiroshi

2008-08-07

IR-UV ion-dip spectra of the 7-azaindole (7AI)(CH(3)OH)(n) (n=1-3) clusters have been measured in the hydrogen-bonded NH and OH stretching regions to investigate the stable structures of 7AI(CH(3)OH)(n) (n=1-3) in the S(0) state and the cooperativity of the H-bonding interactions in the H-bonded networks. The comparison of the IR-UV ion-dip spectra with IR spectra obtained by quantum chemistry calculations shows that 7AI(CH(3)OH)(n) (n=1-3) have cyclic H-bonded structures, where the NH group and the heteroaromatic N atom of 7AI act as the proton donor and proton acceptor, respectively. The H-bonded OH stretch fundamental of 7AI(CH(3)OH)(2) is remarkably redshifted from the corresponding fundamental of (CH(3)OH)(2) by 286 cm(-1), which is an experimental manifestation of the cooperativity in H-bonding interaction. Similarly, two localized OH fundamentals of 7AI(CH(3)OH)(3) also exhibit large redshifts. The cooperativity of 7AI(CH(3)OH)(n) (n=2,3) is successfully explained by the donor-acceptor electron delocalization interactions between the lone-pair orbital in the proton acceptor and the antibonding orbital in the proton donor in natural bond orbital (NBO) analyses.

A novel dansyl-based fluorescent probe for highly selective detection of ferric ions.

Science.gov (United States)

Yang, Min; Sun, Mingtai; Zhang, Zhongping; Wang, Suhua

2013-02-15

A novel dansyl-based fluorescent probe was synthesized and characterized. It exhibits high selectivity and sensitivity towards Fe(3+) ion. This fluorescent probe is photostable, water soluble and pH insensitive. The limit of detection is found to be 0.62 μM. These properties make it a good fluorescent probe for Fe(3+) ion detection in both chemical and biological systems. Spike recovery test confirms its practical application in tap water samples. Copyright © 2012 Elsevier B.V. All rights reserved.

How High School Students Select a College.

Science.gov (United States)

Gilmour, Joseph E., Jr.; And Others

The college selection process used by high school students was studied and a paradigm that describes the process was developed, based on marketing theory concerning consumer behavior. Primarily college freshmen and high school seniors were interviewed, and a few high school juniors and upper-level college students were surveyed to determine…

Styrene and Azo-Styrene Based Colorimetric Sensors for Highly Selective Detection of Cyanide

OpenAIRE

Prestiani, Agustina Eka; Purwono, Bambang

2017-01-01

A novel styrene (1) and azo-styrene (2) based chemosensor from vanillin has been successfully synthesized. Sensor 1 was obtained by one step Knoevenagel condensation of Ultrasound method and sensor 2 by coupling diazo and Knoevenagel condensation reaction. Both of sensors showed high sensitivity and selectivity to detect CN- in aqueous media, even the presence of other anions, such as F-, Cl-, Br-, I-, CO32-, SO42-, H2PO4-, and AcO-. Colorimetric sensing of sensor 1 is inclined to be deproton...

Is it beneficial to selectively boost high-risk tumor subvolumes? A comparison of selectively boosting high-risk tumor subvolumes versus homogeneous dose escalation of the entire tumor based on equivalent EUD plans

International Nuclear Information System (INIS)

Kim, Yusung; To me, Wolfgang A.

2008-01-01

Purpose. To quantify and compare expected local tumor control and expected normal tissue toxicities between selective boosting IMRT and homogeneous dose escalation IMRT for the case of prostate cancer. Methods. Four different selective boosting scenarios and three different high-risk tumor subvolume geometries were designed to compare selective boosting and homogeneous dose escalation IMRT plans delivering the same equivalent uniform dose (EUD) to the entire PTV. For each scenario, differences in tumor control probability between both boosting strategies were calculated for the high-risk tumor subvolume and remaining low-risk PTV, and were visualized using voxel based iso-TCP maps. Differences in expected rectal and bladder complications were quantified using radiobiological indices (generalized EUD (gEUD) and normal tissue complication probability (NTCP)) as well as %-volumes. Results. For all investigated scenarios and high-risk tumor subvolume geometries, selective boosting IMRT improves expected TCP compared to homogeneous dose escalation IMRT, especially when lack of control of the high-risk tumor subvolume could be the cause for tumor recurrence. Employing, selective boosting IMRT significant increases in expected TCP can be achieved for the high-risk tumor subvolumes. The three conventional selective boosting IMRT strategies, employing physical dose objectives, did not show significant improvement in rectal and bladder sparing as compared to their counterpart homogeneous dose escalation plans. However, risk-adaptive optimization, utilizing radiobiological objective functions, resulted in reduction in NTCP for the rectum when compared to its corresponding homogeneous dose escalation plan. Conclusions. Selective boosting is a more effective method than homogeneous dose escalation for achieving optimal treatment outcomes. Furthermore, risk-adaptive optimization increases the therapeutic ratio as compared to conventional selective boosting IMRT

A highly selective biosensor with nanomolar sensitivity based on cytokinin dehydrogenase.

Directory of Open Access Journals (Sweden)

Faming Tian

Full Text Available We have developed a N6-dimethylallyladenine (cytokinin dehydrogenase-based microbiosensor for real-time determination of the family of hormones known as cytokinins. Cytokinin dehydrogenase from Zea mays (ZmCKX1 was immobilised concurrently with electrodeposition of a silica gel film on the surface of a Pt microelectrode, which was further functionalized by free electron mediator 2,6-dichlorophenolindophenol (DCPIP in supporting electrolyte to give a bioactive film capable of selective oxidative cleavage of the N6- side chain of cytokinins. The rapid electron shuffling between freely diffusible DCPIP and the FAD redox group in ZmCKX1 endowed the microbiosensor with a fast response time of less than 10 s. The immobilised ZmCKX1 retained a high affinity for its preferred substrate N6-(Δ2-isopentenyl adenine (iP, and gave the miniaturized biosensor a large linear dynamic range from 10 nM to 10 µM, a detection limit of 3.9 nM and a high sensitivity to iP of 603.3 µAmM-1cm-2 (n = 4, R2 = 0.9999. Excellent selectivity was displayed for several other aliphatic cytokinins and their ribosides, including N6-(Δ2-isopentenyl adenine, N6-(Δ2-isopentenyl adenosine, cis-zeatin, trans-zeatin and trans-zeatin riboside. Aromatic cytokinins and metabolites such as cytokinin glucosides were generally poor substrates. The microbiosensors exhibited excellent stability in terms of pH and long-term storage and have been used successfully to determine low nanomolar cytokinin concentrations in tomato xylem sap exudates.

Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels (Conference Presentation)

Science.gov (United States)

Zhao, Jianhua; Zeng, Haishan; Kalia, Sunil; Lui, Harvey

2017-02-01

Background: Raman spectroscopy is a non-invasive optical technique which can measure molecular vibrational modes within tissue. A large-scale clinical study (n = 518) has demonstrated that real-time Raman spectroscopy could distinguish malignant from benign skin lesions with good diagnostic accuracy; this was validated by a follow-up independent study (n = 127). Objective: Most of the previous diagnostic algorithms have typically been based on analyzing the full band of the Raman spectra, either in the fingerprint or high wavenumber regions. Our objective in this presentation is to explore wavenumber selection based analysis in Raman spectroscopy for skin cancer diagnosis. Methods: A wavenumber selection algorithm was implemented using variably-sized wavenumber windows, which were determined by the correlation coefficient between wavenumbers. Wavenumber windows were chosen based on accumulated frequency from leave-one-out cross-validated stepwise regression or least and shrinkage selection operator (LASSO). The diagnostic algorithms were then generated from the selected wavenumber windows using multivariate statistical analyses, including principal component and general discriminant analysis (PC-GDA) and partial least squares (PLS). A total cohort of 645 confirmed lesions from 573 patients encompassing skin cancers, precancers and benign skin lesions were included. Lesion measurements were divided into training cohort (n = 518) and testing cohort (n = 127) according to the measurement time. Result: The area under the receiver operating characteristic curve (ROC) improved from 0.861-0.891 to 0.891-0.911 and the diagnostic specificity for sensitivity levels of 0.99-0.90 increased respectively from 0.17-0.65 to 0.20-0.75 by selecting specific wavenumber windows for analysis. Conclusion: Wavenumber selection based analysis in Raman spectroscopy improves skin cancer diagnostic specificity at high sensitivity levels.

High-dimensional orbital angular momentum entanglement concentration based on Laguerre–Gaussian mode selection

International Nuclear Information System (INIS)

Zhang, Wuhong; Su, Ming; Wu, Ziwen; Lu, Meng; Huang, Bingwei; Chen, Lixiang

2013-01-01

Twisted photons enable the definition of a Hilbert space beyond two dimensions by orbital angular momentum (OAM) eigenstates. Here we propose a feasible entanglement concentration experiment, to enhance the quality of high-dimensional entanglement shared by twisted photon pairs. Our approach is started from the full characterization of entangled spiral bandwidth, and is then based on the careful selection of the Laguerre–Gaussian (LG) modes with specific radial and azimuthal indices p and ℓ. In particular, we demonstrate the possibility of high-dimensional entanglement concentration residing in the OAM subspace of up to 21 dimensions. By means of LabVIEW simulations with spatial light modulators, we show that the Shannon dimensionality could be employed to quantify the quality of the present concentration. Our scheme holds promise in quantum information applications defined in high-dimensional Hilbert space. (letter)

High Selectively Catalytic Conversion of Lignin-Based Phenols into para-/m-Xylene over Pt/HZSM-5

Directory of Open Access Journals (Sweden)

Guozhu Liu

2016-01-01

Full Text Available High selectively catalytic conversion of lignin-based phenols (m-cresol, p-cresol, and guaiacol into para-/m-xylene was performed over Pt/HZSM-5 through hydrodeoxygenation and in situ methylation with methanol. It is found that the p-/m-xylene selectivity is uniformly higher than 21%, and even increase up to 33.5% for m-cresol (with phenols/methanol molar ratio of 1/8. The improved p-/m-xylene selectivity in presence of methanol is attributed to the combined reaction pathways: methylation of m-cresol into xylenols followed by HDO into p-/m-xylene, and HDO of m-cresol into toluene followed by methylation into p-/m-xylene. Comparison of the product distribution over a series of catalysts indicates that both metals and supporters have distinct effect on the p-/m-xylene selectivity.

A simple highly sensitive and selective aptamer-based colorimetric sensor for environmental toxins microcystin-LR in water samples.

Science.gov (United States)

Li, Xiuyan; Cheng, Ruojie; Shi, Huijie; Tang, Bo; Xiao, Hanshuang; Zhao, Guohua

2016-03-05

A simple and highly sensitive aptamer-based colorimetric sensor was developed for selective detection of Microcystin-LR (MC-LR). The aptamer (ABA) was employed as recognition element which could bind MC-LR with high-affinity, while gold nanoparticles (AuNPs) worked as sensing materials whose plasma resonance absorption peaks red shifted upon binding of the targets at a high concentration of sodium chloride. With the addition of MC-LR, the random coil aptamer adsorbed on Au NPs altered into regulated structure to form MC-LR-aptamer complexes and broke away from the surface of Au NPs, leading to the aggregation of AuNPs, and the color converted from red to blue due to the interparticle plasmon coupling. Results showed that our aptamer-based colorimetric sensor exhibited rapid and sensitive detection performance for MC-LR with linear range from 0.5 nM to 7.5 μM and the detection limit reached 0.37 nM. Meanwhile, the pollutants usually coexisting with MC-LR in pollutant water samples had not demonstrated disturbance for detecting of MC-LR. The mechanism was also proposed suggesting that high affinity interaction between aptamer and MC-LR significantly enhanced the sensitivity and selectivity for MC-LR detection. Besides, the established method was utilized in analyzing real water samples and splendid sensitivity and selectivity were obtained as well. Copyright © 2015 Elsevier B.V. All rights reserved.

Anionic chromogenic chemosensors highly selective for fluoride or cyanide based on 4-(4-Nitrobenzylideneamine)phenol

Energy Technology Data Exchange (ETDEWEB)

Nicoleti, Celso R; Marini, Vanderleia G; Zimmermann, Lizandra M; Machado, Vanderlei G., E-mail: vanderlei.machado@ufsc.br [Departamento de Quimica, Universidade Federal de Santa Catarina (UFSC), Florianopolis, SC (Brazil)

2012-08-15

4-(4-Nitrobenzylideneamine)phenol was used in two strategies allowing the highly selective detection of F{sup -} and CN{sup -}. Firstly, the compound in acetonitrile acts as a chromogenic chemosensor based on the idea that more basic anions cause its deprotonation (colorless solution), generating a colored solution containing phenolate. The discrimination of CN{sup -} over F{sup -} was obtained by adding 1.4% water to acetonitrile: water preferentially solvates F{sup -}, leaving the CN{sup -} free to deprotonate the compound. Another strategy involved an assay comprised of the competition between phenolate dye and the analyte for calyx[4]pyrrole in acetonitrile, a receptor highly selective for F{sup -}. Phenolate and calyx[4]pyrrole form a hydrogen-bonded complex, which changes the color of the medium. On the addition of various anions, only F{sup -} was able to restore the original color corresponding to phenolate in solution due to the fact that the anion dislodges phenolate from the complexation site. (author)

Anionic chromogenic chemosensors highly selective for fluoride or cyanide based on 4-(4-Nitrobenzylideneamine)phenol

International Nuclear Information System (INIS)

Nicoleti, Celso R.; Marini, Vanderleia G.; Zimmermann, Lizandra M.; Machado, Vanderlei G.

2012-01-01

4-(4-Nitrobenzylideneamine)phenol was used in two strategies allowing the highly selective detection of F - and CN - . Firstly, the compound in acetonitrile acts as a chromogenic chemosensor based on the idea that more basic anions cause its deprotonation (colorless solution), generating a colored solution containing phenolate. The discrimination of CN - over F - was obtained by adding 1.4% water to acetonitrile: water preferentially solvates F - , leaving the CN - free to deprotonate the compound. Another strategy involved an assay comprised of the competition between phenolate dye and the analyte for calyx[4]pyrrole in acetonitrile, a receptor highly selective for F - . Phenolate and calyx[4]pyrrole form a hydrogen-bonded complex, which changes the color of the medium. On the addition of various anions, only F - was able to restore the original color corresponding to phenolate in solution due to the fact that the anion dislodges phenolate from the complexation site. (author)

Anionic chromogenic chemosensors highly selective for fluoride or cyanide based on 4-(4-Nitrobenzylideneamine)phenol

OpenAIRE

Nicoleti,Celso R.; Marini,Vanderléia G.; Zimmermann,Lizandra M.; Machado,Vanderlei G.

2012-01-01

4-(4-Nitrobenzylideneamine)phenol was used in two strategies allowing the highly selective detection of F- and CN-. Firstly, the compound in acetonitrile acts as a chromogenic chemosensor based on the idea that more basic anions cause its deprotonation (colorless solution), generating a colored solution containing phenolate. The discrimination of CN- over F- was obtained by adding 1.4% water to acetonitrile: water preferentially solvates F-, leaving the CN- free to deprotonate the compound. A...

New detection systems of bacteria using highly selective media designed by SMART: selective medium-design algorithm restricted by two constraints.

Directory of Open Access Journals (Sweden)

Takeshi Kawanishi

Full Text Available Culturing is an indispensable technique in microbiological research, and culturing with selective media has played a crucial role in the detection of pathogenic microorganisms and the isolation of commercially useful microorganisms from environmental samples. Although numerous selective media have been developed in empirical studies, unintended microorganisms often grow on such media probably due to the enormous numbers of microorganisms in the environment. Here, we present a novel strategy for designing highly selective media based on two selective agents, a carbon source and antimicrobials. We named our strategy SMART for highly Selective Medium-design Algorithm Restricted by Two constraints. To test whether the SMART method is applicable to a wide range of microorganisms, we developed selective media for Burkholderia glumae, Acidovorax avenae, Pectobacterium carotovorum, Ralstonia solanacearum, and Xanthomonas campestris. The series of media developed by SMART specifically allowed growth of the targeted bacteria. Because these selective media exhibited high specificity for growth of the target bacteria compared to established selective media, we applied three notable detection technologies: paper-based, flow cytometry-based, and color change-based detection systems for target bacteria species. SMART facilitates not only the development of novel techniques for detecting specific bacteria, but also our understanding of the ecology and epidemiology of the targeted bacteria.

NetProt: Complex-based Feature Selection.

Science.gov (United States)

Goh, Wilson Wen Bin; Wong, Limsoon

2017-08-04

Protein complex-based feature selection (PCBFS) provides unparalleled reproducibility with high phenotypic relevance on proteomics data. Currently, there are five PCBFS paradigms, but not all representative methods have been implemented or made readily available. To allow general users to take advantage of these methods, we developed the R-package NetProt, which provides implementations of representative feature-selection methods. NetProt also provides methods for generating simulated differential data and generating pseudocomplexes for complex-based performance benchmarking. The NetProt open source R package is available for download from https://github.com/gohwils/NetProt/releases/ , and online documentation is available at http://rpubs.com/gohwils/204259 .

Optimization of cell line development in the GS-CHO expression system using a high-throughput, single cell-based clone selection system.

Science.gov (United States)

Nakamura, Tsuyoshi; Omasa, Takeshi

2015-09-01

Therapeutic antibodies are commonly produced by high-expressing, clonal and recombinant Chinese hamster ovary (CHO) cell lines. Currently, CHO cells dominate as a commercial production host because of their ease of use, established regulatory track record, and safety profile. CHO-K1SV is a suspension, protein-free-adapted CHO-K1-derived cell line employing the glutamine synthetase (GS) gene expression system (GS-CHO expression system). The selection of high-producing mammalian cell lines is a crucial step in process development for the production of therapeutic antibodies. In general, cloning by the limiting dilution method is used to isolate high-producing monoclonal CHO cells. However, the limiting dilution method is time consuming and has a low probability of monoclonality. To minimize the duration and increase the probability of obtaining high-producing clones with high monoclonality, an automated single cell-based clone selector, the ClonePix FL system, is available. In this study, we applied the high-throughput ClonePix FL system for cell line development using CHO-K1SV cells and investigated efficient conditions for single cell-based clone selection. CHO-K1SV cell growth at the pre-picking stage was improved by optimizing the formulation of semi-solid medium. The efficiency of picking and cell growth at the post-picking stage was improved by optimization of the plating time without decreasing the diversity of clones. The conditions for selection, including the medium formulation, were the most important factors for the single cell-based clone selection system to construct a high-producing CHO cell line. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Rolling cycle amplification based single-color quantum dots–ruthenium complex assembling dyads for homogeneous and highly selective detection of DNA

Energy Technology Data Exchange (ETDEWEB)

Su, Chen; Liu, Yufei; Ye, Tai; Xiang, Xia; Ji, Xinghu; He, Zhike, E-mail: zhkhe@whu.edu.cn

2015-01-01

Graphical abstract: A universal, label-free, homogeneous, highly sensitive, and selective fluorescent biosensor for DNA detection is developed by using rolling-circle amplification (RCA) based single-color quantum dots–ruthenium complex (QDs–Ru) assembling dyads. - Highlights: • The single-color QDs–Ru assembling dyads were applied in homogeneous DNA assay. • This biosensor exhibited high selectivity against base mismatched sequences. • This biosensor could be severed as universal platform for the detection of ssDNA. • This sensor could be used to detect the target in human serum samples. • This DNA sensor had a good selectivity under the interference of other dsDNA. - Abstract: In this work, a new, label-free, homogeneous, highly sensitive, and selective fluorescent biosensor for DNA detection is developed by using rolling-circle amplification (RCA) based single-color quantum dots–ruthenium complex (QDs–Ru) assembling dyads. This strategy includes three steps: (1) the target DNA initiates RCA reaction and generates linear RCA products; (2) the complementary DNA hybridizes with the RCA products to form long double-strand DNA (dsDNA); (3) [Ru(phen){sub 2}(dppx)]{sup 2+} (dppx = 7,8-dimethyldipyrido [3,2-a:2′,3′-c] phenanthroline) intercalates into the long dsDNA with strong fluorescence emission. Due to its strong binding propensity with the long dsDNA, [Ru(phen){sub 2}(dppx)]{sup 2+} is removed from the surface of the QDs, resulting in restoring the fluorescence of the QDs, which has been quenched by [Ru(phen){sub 2}(dppx)]{sup 2+} through a photoinduced electron transfer process and is overlaid with the fluorescence of dsDNA bonded Ru(II) polypyridyl complex (Ru-dsDNA). Thus, high fluorescence intensity is observed, and is related to the concentration of target. This sensor exhibits not only high sensitivity for hepatitis B virus (HBV) ssDNA with a low detection limit (0.5 pM), but also excellent selectivity in the complex matrix. Moreover

A high surface area Zr(IV)-based metal–organic framework showing stepwise gas adsorption and selective dye uptake

Energy Technology Data Exchange (ETDEWEB)

Lv, Xiu-Liang [Beijing Key Laboratory for Green Catalysis and Separation, Department of Chemistry and Chemical Engineering, Beijing University of Technology, Beijing 100124 (China); Tong, Minman; Huang, Hongliang [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China); Wang, Bin; Gan, Lei [Beijing Key Laboratory for Green Catalysis and Separation, Department of Chemistry and Chemical Engineering, Beijing University of Technology, Beijing 100124 (China); Yang, Qingyuan [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China); Zhong, Chongli [College of Chemical Engineering, Beijing University of Chemical Technology, Beijing 100029 (China); State Key Laboratory of Organic–Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029 (China); Li, Jian-Rong, E-mail: jrli@bjut.edu.cn [Beijing Key Laboratory for Green Catalysis and Separation, Department of Chemistry and Chemical Engineering, Beijing University of Technology, Beijing 100124 (China); State Key Laboratory of Organic–Inorganic Composites, Beijing University of Chemical Technology, Beijing 100029 (China)

2015-03-15

Exploitation of new metal–organic framework (MOF) materials with high surface areas has been attracting great attention in related research communities due to their broad potential applications. In this work, a new Zr(IV)-based MOF, [Zr{sub 6}O{sub 4}(OH){sub 4}(eddb){sub 6}] (BUT-30, H{sub 2}eddb=4,4′-(ethyne-1,2-diyl)dibenzoic acid) has been solvothermally synthesized, characterized, and explored for gases and dyes adsorptions. Single-crystal X-ray diffraction analysis demonstrates a three-dimensional cubic framework structure of this MOF, in which each Zr{sub 6}O{sub 4}(OH){sub 4} building unit is linked by 12 linear eddb ligands. BUT-30 has been found stable up to 400 °C and has a Brunauer–Emmett–Teller (BET) surface area as high as 3940.6 m{sup 2} g{sup −1} (based on the N{sub 2} adsorption at 77 K) and total pore volume of 1.55 cm{sup 3} g{sup −1}. It is more interesting that this MOF exhibits stepwise adsorption behaviors for Ar, N{sub 2}, and CO{sub 2} at low temperatures, and selective uptakes towards different ionic dyes. - Graphical abstract: A new Zr(IV)-based MOF with high surface area has been synthesized and structurally characterized, which shows stepwise gas adsorption at low temperature and selective dye uptake from solution. - Highlights: • A new Zr-based MOF was synthesized and structurally characterized. • This MOF shows a higher surface area compared with its analogous UiO-67 and 68. • This MOF shows a rare stepwise adsorption towards light gases at low temperature. • This MOF performs selective uptakes towards cationic dyes over anionic ones. • Using triple-bond spacer is confirmed feasible in enhancing MOF surface areas.

Surface stress sensor based on MEMS Fabry-Perot interferometer with high wavelength selectivity for label-free biosensing

Science.gov (United States)

Takahashi, Toshiaki; Hizawa, Takeshi; Misawa, Nobuo; Taki, Miki; Sawada, Kazuaki; Takahashi, Kazuhiro

2018-05-01

We have developed a surface stress sensor based on a microelectromechanical Fabry-Perot interferometer with high wavelength selectivity by using Au half-mirrors, for highly sensitive label-free biosensing. When the target molecule is adsorbed by the antigen-antibody reaction onto a movable membrane with a thin Au film, which acts as an upper mirror of the optical interferometer, the amount of deflection of the movable membrane deflected by the change in surface stress can be detected with high sensitivity. To improve the signal at the small membrane deflection region of this biosensor resulting in detection of low concentration molecules, by integrating 50 nm-thick Au half-mirrors, the wavelength selectivity of the optical interferometer has been successfully improved 6.6 times. Furthermore, the peak shift in the reflection spectrum due to the adsorption of bovine serum albumin (BSA) antigen with a concentration of 10 ng ml-l by the antigen-antibody reaction was spectroscopically measured on the fabricated optical interferometer, and the deflection amount of the movable membrane after 10 min treatment was 2.4 times larger than that of nonspecific adsorption with the avidin molecules. This result indicated that the proposed sensor can be used for selective detection of low-concentration target antigen molecules.

A highly sensitive and selective dimethyl ether sensor based on cataluminescence.

Science.gov (United States)

Zhang, Runkun; Cao, Xiaoan; Liu, Yonghui; Peng, Yan

2010-07-15

A sensor for detecting dimethyl ether was designed based on the cataluminescence phenomenon when dimethyl ether vapors were passing through the surface of the ceramic heater. The proposed sensor showed high sensitivity and selectivity to dimethyl ether at an optimal temperature of 279 degrees C. Quantitative analysis were performed at a wavelength of 425 nm, the flow rate of carrier air is around 300 mL/min. The linear range of the cataluminescence intensity versus concentration of dimethyl ether is 100-6.0x10(3) ppm with a detection limit of 80 ppm. The sensor response time is 2.5 s. Under the optimized conditions, none or only very low levels of interference were observed while the foreign substances such as benzene, formaldehyde, ammonia, methanol, ethanol, acetaldehyde, acetic acid, acrolein, isopropyl ether, ethyl acetate, glycol ether and 2-methoxyethanol were passing through the sensor. Since the sensor does not need to prepare and fix up the granular catalyst, the simple technology reduces cost, improves stability and extends life span. The method can be applied to facilitate detection of dimethyl ether in the air. The possible mechanism of cataluminescence from the oxidation of dimethyl ether on the surface of ceramic heater was discussed based on the reaction products. Copyright 2010 Elsevier B.V. All rights reserved.

Performance of high-temperature superconducting band-pass filters with high selectivity for base transceiver applications of digital cellular communication systems

Science.gov (United States)

Kwak, J. S.; Lee, J. H.; Kim, C. O.; Hong, J. P.; Han, S. K.; Char, K.

2002-07-01

Highly selective high-temperature superconducting band-pass filters based on spiral meander line structures have been developed for base transceiver station applications of digital cellular communication systems. The filter comprised 12-pole microstrip line resonators with a circuit size of 0.5 × 17 × 41 mm3. The filter was designed to have a bandwidth of 25 MHz at a centre frequency of 834 MHz. Particularly, the physical size of each resonator was chosen not only to reduce far-field radiation, but also to have reasonable tunability in the filter. Device characteristics exhibited a low insertion loss of 0.4 dB with a 0.2 dB ripple and a return loss better than 10 dB in the pass-band at 65 K. The out-of-band signals were attenuated better than 60 dB at about 3.5 MHz from the lower band edge, and 3.8 MHz from the higher band edge.

Performance of high-temperature superconducting band-pass filters with high selectivity for base transceiver applications of digital cellular communication systems

Energy Technology Data Exchange (ETDEWEB)

Kwak, J.S.; Lee, J.H.; Kim, C.O.; Hong, J.P. [Department of Physics, Hanyang University, Seoul (Korea, Republic of); Han, S.K.; Char, K. [RFtron Inc., Seoul (Korea, Republic of)

2002-07-01

Highly selective high-temperature superconducting band-pass filters based on spiral meander line structures have been developed for base transceiver station applications of digital cellular communication systems. The filter comprised 12-pole microstrip line resonators with a circuit size of 0.5x17x41 mm{sup 3}. The filter was designed to have a bandwidth of 25 MHz at a centre frequency of 834 MHz. Particularly, the physical size of each resonator was chosen not only to reduce far-field radiation, but also to have reasonable tunability in the filter. Device characteristics exhibited a low insertion loss of 0.4 dB with a 0.2 dB ripple and a return loss better than 10 dB in the pass-band at 65 K. The out-of-band signals were attenuated better than 60 dB at about 3.5 MHz from the lower band edge, and 3.8 MHz from the higher band edge. (author)

Performance of high-temperature superconducting band-pass filters with high selectivity for base transceiver applications of digital cellular communication systems

International Nuclear Information System (INIS)

Kwak, J.S.; Lee, J.H.; Kim, C.O.; Hong, J.P.; Han, S.K.; Char, K.

2002-01-01

Highly selective high-temperature superconducting band-pass filters based on spiral meander line structures have been developed for base transceiver station applications of digital cellular communication systems. The filter comprised 12-pole microstrip line resonators with a circuit size of 0.5x17x41 mm 3 . The filter was designed to have a bandwidth of 25 MHz at a centre frequency of 834 MHz. Particularly, the physical size of each resonator was chosen not only to reduce far-field radiation, but also to have reasonable tunability in the filter. Device characteristics exhibited a low insertion loss of 0.4 dB with a 0.2 dB ripple and a return loss better than 10 dB in the pass-band at 65 K. The out-of-band signals were attenuated better than 60 dB at about 3.5 MHz from the lower band edge, and 3.8 MHz from the higher band edge. (author)

Metal-organic framework based highly selective fluorescence turn-on probe for hydrogen sulphide

Science.gov (United States)

Nagarkar, Sanjog S.; Saha, Tanmoy; Desai, Aamod V.; Talukdar, Pinaki; Ghosh, Sujit K.

2014-11-01

Hydrogen sulphide (H2S) is known to play a vital role in human physiology and pathology which stimulated interest in understanding complex behaviour of H2S. Discerning the pathways of H2S production and its mode of action is still a challenge owing to its volatile and reactive nature. Herein we report azide functionalized metal-organic framework (MOF) as a selective turn-on fluorescent probe for H2S detection. The MOF shows highly selective and fast response towards H2S even in presence of other relevant biomolecules. Low cytotoxicity and H2S detection in live cells, demonstrate the potential of MOF towards monitoring H2S chemistry in biological system. To the best of our knowledge this is the first example of MOF that exhibit fast and highly selective fluorescence turn-on response towards H2S under physiological conditions.

Prediction-Oriented Marker Selection (PROMISE): With Application to High-Dimensional Regression.

Science.gov (United States)

Kim, Soyeon; Baladandayuthapani, Veerabhadran; Lee, J Jack

2017-06-01

In personalized medicine, biomarkers are used to select therapies with the highest likelihood of success based on an individual patient's biomarker/genomic profile. Two goals are to choose important biomarkers that accurately predict treatment outcomes and to cull unimportant biomarkers to reduce the cost of biological and clinical verifications. These goals are challenging due to the high dimensionality of genomic data. Variable selection methods based on penalized regression (e.g., the lasso and elastic net) have yielded promising results. However, selecting the right amount of penalization is critical to simultaneously achieving these two goals. Standard approaches based on cross-validation (CV) typically provide high prediction accuracy with high true positive rates but at the cost of too many false positives. Alternatively, stability selection (SS) controls the number of false positives, but at the cost of yielding too few true positives. To circumvent these issues, we propose prediction-oriented marker selection (PROMISE), which combines SS with CV to conflate the advantages of both methods. Our application of PROMISE with the lasso and elastic net in data analysis shows that, compared to CV, PROMISE produces sparse solutions, few false positives, and small type I + type II error, and maintains good prediction accuracy, with a marginal decrease in the true positive rates. Compared to SS, PROMISE offers better prediction accuracy and true positive rates. In summary, PROMISE can be applied in many fields to select regularization parameters when the goals are to minimize false positives and maximize prediction accuracy.

Selective Distance-Based K+ Quantification on Paper-Based Microfluidics.

Science.gov (United States)

Gerold, Chase T; Bakker, Eric; Henry, Charles S

2018-04-03

In this study, paper-based microfluidic devices (μPADs) capable of K + quantification in aqueous samples, as well as in human serum, using both colorimetric and distance-based methods are described. A lipophilic phase containing potassium ionophore I (valinomycin) was utilized to achieve highly selective quantification of K + in the presence of Na + , Li + , and Mg 2+ ions. Successful addition of a suspended lipophilic phase to a wax printed paper-based device is described and offers a solution to current approaches that rely on organic solvents, which damage wax barriers. The approach provides an avenue for future alkali/alkaline quantification utilizing μPADs. Colorimetric spot tests allowed for K + quantification from 0.1-5.0 mM using only 3.00 μL of sample solution. Selective distance-based quantification required small sample volumes (6.00 μL) and gave responses sensitive enough to distinguish between 1.0 and 2.5 mM of sample K + . μPADs using distance-based methods were also capable of differentiating between 4.3 and 6.9 mM K + in human serum samples. Distance-based methods required no digital analysis, electronic hardware, or pumps; any steps required for quantification could be carried out using the naked eye.

A highly sensitive and selective fluorescent sensor for detection of sulfide anion based on the steric hindrance effect

Science.gov (United States)

Chen, Guanfan; Tang, Mengzhuo; Fu, Xiufang; Cheng, Fenmin; Zou, Xianghua; Wang, Jingpei; Zeng, Rongjin

2018-01-01

Sulfide anions are not only generated as a byproduct from industrial processes but also as a crucial kind of element in biological systems. Therefore, fluorescent probes for detecting sulfide anion with sensitive and selective characters are highly popular. In this study, we report a highly sensitive and selective fluorescent sensor M1 for detection of sulfide anion based on the steric hindrance effect, where the recognition unit, dinitrobenzenesulfonate ester group is linked to aromatic ortho-position in the porphyrin, and correspondingly the fluorescence of fluorescein is efficiently quenched. Compared with the sensors with recognition unit linked to the other aromatic positions, the fluorescent sensor M1 has a lower fluorescence background. Furthermore, the corresponding fluorescence responses (F/F0) of M1 for mercapto amino-acid GSH, Hcy and Cys, were all far lower than the relative fluorescence ratio F/F0 values for S2-. It means that M1 is sensitive and selective to detection of S2-, and has an anti-disturbance ability to the biologically-relevant thiols, GSH, Hcy and Cys, and has the prospect of application in the exact detection of sulfide anions in living organisms. This approach offers some useful insights for realizing sensitive and selective fluorescent turn-on sensing in the detection assays for other analytes.

Information Gain Based Dimensionality Selection for Classifying Text Documents

Energy Technology Data Exchange (ETDEWEB)

Dumidu Wijayasekara; Milos Manic; Miles McQueen

2013-06-01

Selecting the optimal dimensions for various knowledge extraction applications is an essential component of data mining. Dimensionality selection techniques are utilized in classification applications to increase the classification accuracy and reduce the computational complexity. In text classification, where the dimensionality of the dataset is extremely high, dimensionality selection is even more important. This paper presents a novel, genetic algorithm based methodology, for dimensionality selection in text mining applications that utilizes information gain. The presented methodology uses information gain of each dimension to change the mutation probability of chromosomes dynamically. Since the information gain is calculated a priori, the computational complexity is not affected. The presented method was tested on a specific text classification problem and compared with conventional genetic algorithm based dimensionality selection. The results show an improvement of 3% in the true positives and 1.6% in the true negatives over conventional dimensionality selection methods.

Selection of Highly Expressed Gene Variants in Escherichia coli Using Translationally Coupled Antibiotic Selection Markers

DEFF Research Database (Denmark)

Rennig, Maja; Daley, Daniel O.; Nørholm, Morten H. H.

2018-01-01

Strategies to select highly expressed variants of a protein coding sequence are usually based on trial-and-error approaches, which are time-consuming and expensive. We address this problem using translationally coupled antibiotic resistance markers. The system requires that the target gene can...

A perfluorinated covalent triazine-based framework for highly selective and water-tolerant CO2 capture

KAUST Repository

Zhao, Yunfeng

2013-01-01

We designed and synthesized a perfluorinated covalent triazine-based framework (FCTF-1) for selective CO2 capture. The incorporation of fluorine (F) groups played multiple roles in improving the framework\\'s CO 2 adsorption and separation capabilities. Thermodynamically, the strongly polar C-F bonds promoted CO2 adsorption via electrostatic interactions, especially at low pressures. FCTF-1\\'s CO2 uptake was 1.76 mmol g-1 at 273 K and 0.1 bar through equilibrium adsorption, exceeding the CO2 adsorption capacity of any reported porous organic polymers to date. In addition, incorporating F groups produced a significant amount of ultra-micropores (<0.5 nm), which offered not only high gas adsorption potential but also kinetic selectivity for CO2-N 2 separation. In mixed-gas breakthrough experiments, FCTF-1 exhibited an exceptional CO2-N2 selectivity of 77 under kinetic flow conditions, much higher than the selectivity (31) predicted from single-gas equilibrium adsorption data. Moreover, FCTF-1 proved to be tolerant to water and its CO2 capture performance remained excellent when there was moisture in the gas mixture, due to the hydrophobic nature of the C-F bonds. In addition, the moderate adsorbate-adsorbent interaction allowed it to be fully regenerated by pressure swing adsorption processes. These attributes make FCTF-1 a promising sorbent for CO2 capture from flue gas. © 2013 The Royal Society of Chemistry.

Zirconium-based metal organic frameworks: Highly selective adsorbents for removal of phosphate from water and urine

Energy Technology Data Exchange (ETDEWEB)

Lin, Kun-Yi Andrew, E-mail: linky@nchu.edu.tw [Department of Environmental Engineering, National Chung Hsing University, 250 Kuo-Kuang Road, Taichung, Taiwan (China); Chen, Shen-Yi [Department of Environmental Engineering, National Chung Hsing University, 250 Kuo-Kuang Road, Taichung, Taiwan (China); Jochems, Andrew P. [New Mexico Bureau of Geology & Mineral Resources and New Mexico Institute of Mining & Technology, Socorro, NM (United States)

2015-06-15

Phosphate is one of the most concerning compounds in wastewater streams and a main nutrient that causes eutrophication. To eliminate the phosphate pollution, Metal Organic Frameworks (MOFs) are proposed in this study as adsorbents to remove phosphate from water. The zirconium-based MOF, UiO-66, was selected as representative MOF given its exceptional stability in water. To investigate the effect of an amine functional group, UiO-66-NH2 was also prepared using an amine-substituted ligand. The adsorption kinetics and isotherm reveal that UiO-66-NH2 exhibited higher adsorption capacities than UiO-66 possibly due to the amine group. However, the interaction between phosphate and zirconium sites of UiO MOFs might be the primary factor accounting for the phosphate adsorption to UiO MOFs. UiO MOFs also exhibited a high selectivity towards phosphate over other anions such as bromate, nitrite and nitrate. Furthermore, UiO MOFs were found to adsorb phosphate and to completely remove diluted phosphate in urine. We also found that UiO MOFs could be easily regenerated and re-used for phosphate adsorption. These findings suggest that UiO MOFs can be effective and selective adsorbents to remove phosphate from water as well as urine. - Highlights: • UiO-66 as the first type of MOFs was used to remove phosphate from water and urine. • The amine group in UiO MOFs was found to enhance the phosphate adsorption. • UiO-66 exhibited a high adsorption selectivity towards phosphate over other anions. • UiO-66 could be easily regenerated and re-used with 85% regeneration efficiency.

Microfluidic sensor for ultra high redox cycling amplification for highly selective electrochemical measurements

NARCIS (Netherlands)

Odijk, Mathieu; Straver, Martin; Olthuis, Wouter; van den Berg, Albert

2011-01-01

In this contribution a SU8/glass-based microfluidic sensor is described with two closely spaced parallel electrodes for highly selective measurements using the redox cycling (RC) effect. Using this sensor, a RC amplification of ~2000x is measured using the ferrocyanide redox couple, which is much

Highly selective rhodamine-based fluorescence turn-on chemosensor for Al3+ ion

Science.gov (United States)

Manjunath, Rangasamy; Kannan, Palaninathan

2018-05-01

A new rhodamine-based colorimetric and fluorescent turn-on chemosensor (L) has been designed and synthesized for selective and sensitive detection of Al3+ ion. The sensing behavior toward metal ion was investigated by UV/Vis and fluorescence spectroscopy. Upon addition of Al3+ ion to solution of L provided a visual color change as well as significantly fluorescent enhancement, while other metal ions including Na+, Mg2+, K+, Mn2+, Fe3+, Ni2+, Cu2+, Zn2+, Pb2+, Cd2+ and Hg2+ ions fails to generate a distinct color and spectral changes, the distinct color change and rapid switch-on fluorescence also provide naked eye detection for Al3+ ion. The mechanism involved equilibrium between non-fluorescent spirocyclic form and highly fluorescent ring open form process was utilized and 1:2 stoichiometry for L-Al3+ complex formed with an association constant of 1.42 × 103 M-1. Moreover, chemosensor L was applied for living cell imaging and confirmed that can be used as a fluorescent probe for monitoring Al3+ ion in living cells.

A rhodamine B-based fluorescent sensor toward highly selective mercury (II) ions detection.

Science.gov (United States)

Jiao, Yang; Zhang, Lei; Zhou, Peng

2016-04-01

This work presented the design, syntheses and photophysical properties of a rhodamine B-based fluorescence probe, which exhibited a sensitive and selective recognition towards mercury (II). The chemosensor RA (Rhodamine- amide- derivative) contained a 5-aminoisophthalic acid diethyl ester and a rhodamine group, and the property of spirolactone of this chemosensor RA was detected by X-ray crystal structure analyses. Chemosensor RA afforded turn-on fluorescence enhancement and displayed high brightness for Hg(2+), which leaded to the opening of the spirolactone ring and consequently caused the appearance of strong absorption at visible range, moreover, the obvious and characteristic color changed from colorless to pink was observed. We envisioned that the chemosensor RA exhibited a considerable specificity with two mercury (II) ions which was attributed to the open of spirolactone over other interference metal ions. Copyright © 2015 Elsevier B.V. All rights reserved.

Space Based Infrared System High (SBIRS High)

Science.gov (United States)

2015-12-01

elements (five SMGTs) for the S2E2 Mobile Ground System. ​ SBIRS Block Buy (GEO 5-6) The GEO 5-6 Tech Refresh (TR) Engineering Change Proposal was...Selected Acquisition Report (SAR) RCS: DD-A&T(Q&A)823-210 Space Based Infrared System High ( SBIRS High) As of FY 2017 President’s Budget Defense...Acquisition Management Information Retrieval (DAMIR) March 23, 2016 11:24:26 UNCLASSIFIED SBIRS High December 2015 SAR March 23, 2016 11:24:26

Highly selective and sensitive phosphate anion sensors based on AlGaN/GaN high electron mobility transistors functionalized by ion imprinted polymer.

Science.gov (United States)

Jia, Xiuling; Chen, Dunjun; Bin, Liu; Lu, Hai; Zhang, Rong; Zheng, Youdou

2016-06-09

A novel ion-imprinted electrochemical sensor based on AlGaN/GaN high electron mobility transistors (HEMTs) was developed to detect trace amounts of phosphate anion. This sensor combined the advantages of the ion sensitivity of AlGaN/GaN HEMTs and specific recognition of ion imprinted polymers. The current response showed that the fabricated sensor is highly sensitive and selective to phosphate anions. The current change exhibited approximate linear dependence for phosphate concentration from 0.02 mg L(-1) to 2 mg L(-1), the sensitivity and detection limit of the sensor is 3.191 μA/mg L(-1) and 1.97 μg L(-1), respectively. The results indicated that this AlGaN/GaN HEMT-based electrochemical sensor has the potential applications on phosphate anion detection.

Highly selective detection of p-nitrophenol using fluorescence assay based on boron, nitrogen co-doped carbon dots.

Science.gov (United States)

Xiao, Na; Liu, Shi Gang; Mo, Shi; Li, Na; Ju, Yan Jun; Ling, Yu; Li, Nian Bing; Luo, Hong Qun

2018-07-01

p-Nitrophenol (p-NP) contaminants seriously endanger environmental and living beings health, hence to establish a sensitive and selective method is of great importance for the determination of p-NP. In this work, boron and nitrogen co-doped carbon dots (B,N-CDs) were synthesized by one-step hydrothermal method using 3-aminophenylboronic acid as the sole precursor. The product was characterized through high-resolution transmission electron microscopy, fluorescence spectroscopy, UV-visible absorption spectroscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy. Without any functionalized modification, B,N-CDs can be directly applied as a 'turn-off' fluorescent probe for rapid, highly selective, and sensitive detection of p-NP. The fluorescent sensor based on the B,N-CDs exhibited a broad linear response to the concentration of p-NP in the range of 0.5 - 60 μM and 60 - 200 μM, respectively, and provided a detection limit of 0.2 μM. It was found that only the absorption spectrum of p-NP has a wide overlap with the fluorescence excitation and emission spectra of B,N-CDs compared to those of other representative analogues. The response mechanism was due to the inner filter effect and the formation of dynamic covalent B-O bonds between B,N-CDs and p-NP, which endowed the sensing platform with the rapid response and high selectivity to p-NP. Finally, the sensor showed the practicability of p-NP determination in environmental water samples. Copyright © 2018 Elsevier B.V. All rights reserved.

Phase associations and potential selective extraction methods for selected high-tech metals from ferromanganese nodules and crusts with siderophores

International Nuclear Information System (INIS)

Mohwinkel, Dennis; Kleint, Charlotte; Koschinsky, Andrea

2014-01-01

Highlights: • Phase associations of metals in marine Fe–Mn nodules and crusts were determined. • Selective leaching experiments with siderophore desferrioxamine B were conducted. • Siderophores selectively mobilize high-tech metals associated with Fe carrier phases. • Base metal liberation including Fe and Mn is limited. • Siderophores have promising potential for application in ore processing industries. - Abstract: Deep-sea ferromanganese deposits contain a wide range of economically important metals. Ferromanganese crusts and nodules represent an important future resource, since they not only contain base metals such as Mn, Ni, Co, Cu and Zn, but are also enriched in critical or rare high-technology elements such as Li, Mo, Nb, W, the rare earth elements and yttrium (REY). These metals could be extracted from nodules and crusts as a by-product to the base metal production. However, there are no proper separation techniques available that selectively extract certain metals out of the carrier phases. By sequential leaching, we demonstrated that, except for Li, which is present in an easily soluble form, all other high-tech metals enriched in ferromanganese nodules and crusts are largely associated with the Fe-oxyhydroxide phases and only to subordinate extents with Mn-oxide phases. Based on this fact, we conducted selective leaching experiments with the Fe-specific organic ligand desferrioxamine-B, a naturally occurring and ubiquitous siderophore. We showed by leaching of ferromanganese nodules and crusts with desferrioxamine-B that a significant and selective extraction of high-tech metals such as Li, Mo, Zr, Hf and Ta is possible, while other elements like Fe and the base metals Mn, Ni, Cu, Co and Zn are not extracted to large extents. The set of selectively extracted elements can be extended to Nb and W if Mn and carbonate phases are stripped from the bulk nodule or crust prior to the siderophore leach by e.g. a sequential leaching technique. This

A novel microfluidic origami photoelectrochemical sensor based on CdTe quantum dots modified molecularly imprinted polymer and its highly selective detection of S-fenvalerate

International Nuclear Information System (INIS)

Wang, Yanhu; Zang, Dejin; Ge, Shenguang; Ge, Lei; Yu, Jinghua; Yan, Mei

2013-01-01

Driven by the urgent demand of high-selectively point-of-care testing device for pesticide, molecular imprinting-photoelectrochemistry (MI-PEC) was introduced into microfluidic paper-based analytical strategy to design a novel paper-based photoelectrochemical (paper-based PEC) protocol. The MI-PEC strategy was constructed based on CdTe quantum dots dotted molecular imprinted polymers (CdTe QDs@MIPs), and triggered by a common ultraviolet lamp (∼365 nm, 50$). The paper-based PEC sensor was fabricated by immobilizing CdTe QDs@MIPs on paper-based screen-printed working electrodes (WEs) via gold nanoparticles (Au NPs), which was electrodeposited on the surface of WE to improve the electron transfer efficiency for high sensitivity. Using S-fenvalerate as model analyte, the produced photocurrent from the proposed paper-based MI-PEC sensor upon ultraviolet radiation decreased with the increasing concentrations of S-fenvalerate solution, and the quenched paper-based MI-PEC showed a low detection limit of 3.2 × 10 −9 mol L −1 . This study has made a successful attempt in the development of highly selective and sensitive photoelectrochemical sensor for S-fenvalerate monitoring

Emotional bookkeeping and high partner selectivity are necessary for the emergence of partner-specific reciprocal affiliation in an agent-based model of primate groups.

Directory of Open Access Journals (Sweden)

Ellen Evers

Full Text Available Primate affiliative relationships are differentiated, individual-specific and often reciprocal. However, the required cognitive abilities are still under debate. Recently, we introduced the EMO-model, in which two emotional dimensions regulate social behaviour: anxiety-FEAR and satisfaction-LIKE. Emotional bookkeeping is modelled by providing each individual with partner-specific LIKE attitudes in which the emotional experiences of earlier affiliations with others are accumulated. Individuals also possess fixed partner-specific FEAR attitudes, reflecting the stable dominance hierarchy. In this paper, we focus on one key parameter of the model, namely the degree of partner selectivity, i.e. the extent to which individuals rely on their LIKE attitudes when choosing affiliation partners. Studying the effect of partner selectivity on the emergent affiliative relationships, we found that at high selectivity, individuals restricted their affiliative behaviours more to similar-ranking individuals and that reciprocity of affiliation was enhanced. We compared the emotional bookkeeping model with a control model, in which individuals had fixed LIKE attitudes simply based on the (fixed rank-distance, instead of dynamic LIKE attitudes based on earlier events. Results from the control model were very similar to the emotional bookkeeping model: high selectivity resulted in preference of similar-ranking partners and enhanced reciprocity. However, only in the emotional bookkeeping model did high selectivity result in the emergence of reciprocal affiliative relationships that were highly partner-specific. Moreover, in the emotional bookkeeping model, LIKE attitude predicted affiliative behaviour better than rank-distance, especially at high selectivity. Our model suggests that emotional bookkeeping is a likely candidate mechanism to underlie partner-specific reciprocal affiliation.

A flavone-based turn-on fluorescent probe for intracellular cysteine/homocysteine sensing with high selectivity.

Science.gov (United States)

Zhang, Jian; Lv, Yanlin; Zhang, Wei; Ding, Hui; Liu, Rongji; Zhao, Yongsheng; Zhang, Guangjin; Tian, Zhiyuan

2016-01-01

A new type of flavone-based fluorescent probe (DMAF) capable of cysteine (Cys)/homocysteine (Hcy) sensing with high selectivity over other amino acids was developed. Such type of probe undergoes Cys/Hcy-mediated cyclization reaction with the involvement of its aldehyde group, which suppresses of the photoinduced electron transfer (PET) process of the probe molecule and consequently leads to the enhancement of fluorescence emission upon excitation using visible light. The formation of product of the Cys/Hcy-mediated cyclization reaction was confirmed and the preliminary fluorescence imaging experiments revealed the biocompatibility of the as-prepared probe and validated its practicability for intracellular Cys/Hcy sensing. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation and selection of candidate high-level waste forms

International Nuclear Information System (INIS)

1982-03-01

Seven candidate waste forms being developed under the direction of the Department of Energy's National High-Level Waste (HLW) Technology Program, were evaluated as potential media for the immobilization and geologic disposal of high-level nuclear wastes. The evaluation combined preliminary waste form evaluations conducted at DOE defense waste-sites and independent laboratories, peer review assessments, a product performance evaluation, and a processability analysis. Based on the combined results of these four inputs, two of the seven forms, borosilicate glass and a titanate based ceramic, SYNROC, were selected as the reference and alternative forms for continued development and evaluation in the National HLW Program. Both the glass and ceramic forms are viable candidates for use at each of the DOE defense waste-sites; they are also potential candidates for immobilization of commercial reprocessing wastes. This report describes the waste form screening process, and discusses each of the four major inputs considered in the selection of the two forms

High selection pressure promotes increase in cumulative adaptive culture.

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Carolin Vegvari

Full Text Available The evolution of cumulative adaptive culture has received widespread interest in recent years, especially the factors promoting its occurrence. Current evolutionary models suggest that an increase in population size may lead to an increase in cultural complexity via a higher rate of cultural transmission and innovation. However, relatively little attention has been paid to the role of natural selection in the evolution of cultural complexity. Here we use an agent-based simulation model to demonstrate that high selection pressure in the form of resource pressure promotes the accumulation of adaptive culture in spite of small population sizes and high innovation costs. We argue that the interaction of demography and selection is important, and that neither can be considered in isolation. We predict that an increase in cultural complexity is most likely to occur under conditions of population pressure relative to resource availability. Our model may help to explain why culture change can occur without major environmental change. We suggest that understanding the interaction between shifting selective pressures and demography is essential for explaining the evolution of cultural complexity.

A selective electrocatalyst-based direct methanol fuel cell operated at high concentrations of methanol.

Science.gov (United States)

Feng, Yan; Liu, Hui; Yang, Jun

2017-06-01

Owing to the serious crossover of methanol from the anode to the cathode through the polymer electrolyte membrane, direct methanol fuel cells (DMFCs) usually use dilute methanol solutions as fuel. However, the use of high-concentration methanol is highly demanded to improve the energy density of a DMFC system. Instead of the conventional strategies (for example, improving the fuel-feed system, membrane development, modification of electrode, and water management), we demonstrate the use of selective electrocatalysts to run a DMFC at high concentrations of methanol. In particular, at an operating temperature of 80°C, the as-fabricated DMFC with core-shell-shell Au@Ag 2 S@Pt nanocomposites at the anode and core-shell Au@Pd nanoparticles at the cathode produces a maximum power density of 89.7 mW cm -2 at a methanol feed concentration of 10 M and maintains good performance at a methanol concentration of up to 15 M. The high selectivity of the electrocatalysts achieved through structural construction accounts for the successful operation of the DMFC at high concentrations of methanol.

A selective electrocatalyst–based direct methanol fuel cell operated at high concentrations of methanol

Science.gov (United States)

Feng, Yan; Liu, Hui; Yang, Jun

2017-01-01

Owing to the serious crossover of methanol from the anode to the cathode through the polymer electrolyte membrane, direct methanol fuel cells (DMFCs) usually use dilute methanol solutions as fuel. However, the use of high-concentration methanol is highly demanded to improve the energy density of a DMFC system. Instead of the conventional strategies (for example, improving the fuel-feed system, membrane development, modification of electrode, and water management), we demonstrate the use of selective electrocatalysts to run a DMFC at high concentrations of methanol. In particular, at an operating temperature of 80°C, the as-fabricated DMFC with core-shell-shell Au@Ag2S@Pt nanocomposites at the anode and core-shell Au@Pd nanoparticles at the cathode produces a maximum power density of 89.7 mW cm−2 at a methanol feed concentration of 10 M and maintains good performance at a methanol concentration of up to 15 M. The high selectivity of the electrocatalysts achieved through structural construction accounts for the successful operation of the DMFC at high concentrations of methanol. PMID:28695199

Reference satellite selection method for GNSS high-precision relative positioning

Directory of Open Access Journals (Sweden)

Xiao Gao

2017-03-01

Full Text Available Selecting the optimal reference satellite is an important component of high-precision relative positioning because the reference satellite directly influences the strength of the normal equation. The reference satellite selection methods based on elevation and positional dilution of precision (PDOP value were compared. Results show that all the above methods cannot select the optimal reference satellite. We introduce condition number of the design matrix in the reference satellite selection method to improve structure of the normal equation, because condition number can indicate the ill condition of the normal equation. The experimental results show that the new method can improve positioning accuracy and reliability in precise relative positioning.

Covariance-Based Measurement Selection Criterion for Gaussian-Based Algorithms

Directory of Open Access Journals (Sweden)

Fernando A. Auat Cheein

2013-01-01

Full Text Available Process modeling by means of Gaussian-based algorithms often suffers from redundant information which usually increases the estimation computational complexity without significantly improving the estimation performance. In this article, a non-arbitrary measurement selection criterion for Gaussian-based algorithms is proposed. The measurement selection criterion is based on the determination of the most significant measurement from both an estimation convergence perspective and the covariance matrix associated with the measurement. The selection criterion is independent from the nature of the measured variable. This criterion is used in conjunction with three Gaussian-based algorithms: the EIF (Extended Information Filter, the EKF (Extended Kalman Filter and the UKF (Unscented Kalman Filter. Nevertheless, the measurement selection criterion shown herein can also be applied to other Gaussian-based algorithms. Although this work is focused on environment modeling, the results shown herein can be applied to other Gaussian-based algorithm implementations. Mathematical descriptions and implementation results that validate the proposal are also included in this work.

Pure- and Mixed-Gas Permeation Properties of Highly Selective and Plasticization Resistant Hydroxyl-Diamine-Based 6FDA Polyimides for CO2/CH4 Separation

KAUST Repository

Alaslai, Nasser Y.

2016-01-05

The effect of hydroxyl functionalization on the m-phenylene diamine moiety of 6FDA dianhydride-based polyimides was investigated for gas separation applications. Pure-gas permeability coefficients of He, H2, N2, O2, CH4, and CO2 were measured at 35 °C and 2 atm. The introduction of hydroxyl groups in the diamine moiety of 6FDA-diaminophenol (DAP) and 6FDA-diamino resorcinol (DAR) polyimides tightened the overall polymer structure due to increased charge transfer complex formation compared to unfunctionalized 6FDA-m-phenylene diamine (mPDA). The BET surface areas based on nitrogen adsorption of 6FDA-DAP (54 m2g−1) and of 6FDA-DAR (45 m2g−1) were ~18% and 32% lower than that of 6FDA-mPDA (66 m2g−1). 6FDA-mPDA had a pure-gas CO2 permeability of 14 Barrer and CO2/CH4 selectivity of 70. The hydroxyl-functionalized polyimides 6FDA-DAP and 6FDA-DAR exhibited very high pure-gas CO2/CH4 selectivities of 92 and 94 with moderate CO2 permeability of 11 and 8 Barrer, respectively. It was demonstrated that hydroxyl-containing polyimide membranes maintained very high CO2/CH4 selectivity (~ 75 at CO2 partial pressure of 10 atm) due to CO2 plasticization resistance when tested under high-pressure mixed-gas conditions. Functionalization with hydroxyl groups may thus be a promising strategy towards attaining highly selective polyimides for economical membrane-based natural gas sweetening.

Pure- and Mixed-Gas Permeation Properties of Highly Selective and Plasticization Resistant Hydroxyl-Diamine-Based 6FDA Polyimides for CO2/CH4 Separation

KAUST Repository

Alaslai, Nasser Y.; Ghanem, Bader; Alghunaimi, Fahd; Litwiller, Eric; Pinnau, Ingo

2016-01-01

The effect of hydroxyl functionalization on the m-phenylene diamine moiety of 6FDA dianhydride-based polyimides was investigated for gas separation applications. Pure-gas permeability coefficients of He, H2, N2, O2, CH4, and CO2 were measured at 35 °C and 2 atm. The introduction of hydroxyl groups in the diamine moiety of 6FDA-diaminophenol (DAP) and 6FDA-diamino resorcinol (DAR) polyimides tightened the overall polymer structure due to increased charge transfer complex formation compared to unfunctionalized 6FDA-m-phenylene diamine (mPDA). The BET surface areas based on nitrogen adsorption of 6FDA-DAP (54 m2g−1) and of 6FDA-DAR (45 m2g−1) were ~18% and 32% lower than that of 6FDA-mPDA (66 m2g−1). 6FDA-mPDA had a pure-gas CO2 permeability of 14 Barrer and CO2/CH4 selectivity of 70. The hydroxyl-functionalized polyimides 6FDA-DAP and 6FDA-DAR exhibited very high pure-gas CO2/CH4 selectivities of 92 and 94 with moderate CO2 permeability of 11 and 8 Barrer, respectively. It was demonstrated that hydroxyl-containing polyimide membranes maintained very high CO2/CH4 selectivity (~ 75 at CO2 partial pressure of 10 atm) due to CO2 plasticization resistance when tested under high-pressure mixed-gas conditions. Functionalization with hydroxyl groups may thus be a promising strategy towards attaining highly selective polyimides for economical membrane-based natural gas sweetening.

Highly Sensitive and Selective Sensing of Free Bilirubin Using Metal-Organic Frameworks-Based Energy Transfer Process.

Science.gov (United States)

Du, Yaran; Li, Xiqian; Lv, Xueju; Jia, Qiong

2017-09-13

Free bilirubin, a key biomarker for jaundice, was detected with a newly designed fluorescent postsynthetically modified metal organic framework (MOF) (UIO-66-PSM) sensor. UiO-66-PSM was prepared based on the aldimine condensation reaction of UiO-66-NH 2 with 2,3,4-trihydroxybenzaldehyde. The fluorescence of UIO-66-PSM could be effectively quenched by free bilirubin via a fluorescent resonant energy transfer process, thus achieving its recognition of free bilirubin. It was the first attempt to design a MOF-based fluorescent probe for sensing free bilirubin. The probe exhibited fast response time, low detection limit, wide linear range, and high selectivity toward free bilirubin. The sensing system enabled the monitor of free bilirubin in real human serum. Hence, the reported free bilirubin sensing platform has potential applications for clinical diagnosis of jaundice.

Design of a highly selective quenched activity-based probe and its application in dual color imaging studies of cathepsin S activity localization.

Science.gov (United States)

Oresic Bender, Kristina; Ofori, Leslie; van der Linden, Wouter A; Mock, Elliot D; Datta, Gopal K; Chowdhury, Somenath; Li, Hao; Segal, Ehud; Sanchez Lopez, Mateo; Ellman, Jonathan A; Figdor, Carl G; Bogyo, Matthew; Verdoes, Martijn

2015-04-15

The cysteine cathepsins are a group of 11 proteases whose function was originally believed to be the degradation of endocytosed material with a high degree of redundancy. However, it has become clear that these enzymes are also important regulators of both health and disease. Thus, selective tools that can discriminate between members of this highly related class of enzymes will be critical to further delineate the unique biological functions of individual cathepsins. Here we present the design and synthesis of a near-infrared quenched activity-based probe (qABP) that selectively targets cathepsin S which is highly expressed in immune cells. Importantly, this high degree of selectivity is retained both in vitro and in vivo. In combination with a new green-fluorescent pan-reactive cysteine cathepsin qABP we performed dual color labeling studies in bone marrow-derived immune cells and identified vesicles containing exclusively cathepsin S activity. This observation demonstrates the value of our complementary cathepsin probes and provides evidence for the existence of specific localization of cathepsin S activity in dendritic cells.

Colorimetric biomimetic sensor systems based on molecularly imprinted polymer membranes for highly-selective detection of phenol in environmental samples

Directory of Open Access Journals (Sweden)

Sergeyeva T. A.

2014-05-01

Full Text Available Aim. Development of an easy-to-use colorimetric sensor system for fast and accurate detection of phenol in envi- ronmental samples. Methods. Technique of molecular imprinting, method of in situ polymerization of molecularly imprinted polymer membranes. Results. The proposed sensor is based on free-standing molecularly imprinted polymer (MIP membranes, synthesized by in situ polymerization, and having in their structure artificial binding sites capable of selective phenol recognition. The quantitative detection of phenol, selectively adsorbed by the MIP membranes, is based on its reaction with 4-aminoantipyrine, which gives a pink-colored product. The intensity of staining of the MIP membrane is proportional to phenol concentration in the analyzed sample. Phenol can be detected within the range 50 nM–10 mM with limit of detection 50 nM, which corresponds to the concentrations that have to be detected in natural and waste waters in accordance with environmental protection standards. Stability of the MIP-membrane-based sensors was assessed during 12 months storage at room temperature. Conclusions. The sensor system provides highly-selective and sensitive detection of phenol in both mo- del and real (drinking, natural, and waste water samples. As compared to traditional methods of phenol detection, the proposed system is characterized by simplicity of operation and can be used in non-laboratory conditions.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

Directory of Open Access Journals (Sweden)

Lei Shi

2018-01-01

Full Text Available In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA and tabu search (TS is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy.

Feature Selection for Object-Based Classification of High-Resolution Remote Sensing Images Based on the Combination of a Genetic Algorithm and Tabu Search

Science.gov (United States)

Shi, Lei; Wan, Youchuan; Gao, Xianjun

2018-01-01

In object-based image analysis of high-resolution images, the number of features can reach hundreds, so it is necessary to perform feature reduction prior to classification. In this paper, a feature selection method based on the combination of a genetic algorithm (GA) and tabu search (TS) is presented. The proposed GATS method aims to reduce the premature convergence of the GA by the use of TS. A prematurity index is first defined to judge the convergence situation during the search. When premature convergence does take place, an improved mutation operator is executed, in which TS is performed on individuals with higher fitness values. As for the other individuals with lower fitness values, mutation with a higher probability is carried out. Experiments using the proposed GATS feature selection method and three other methods, a standard GA, the multistart TS method, and ReliefF, were conducted on WorldView-2 and QuickBird images. The experimental results showed that the proposed method outperforms the other methods in terms of the final classification accuracy. PMID:29581721

Highly Selective Fluorescent Sensing of Proteins Based on a Fluorescent Molecularly Imprinted Nanosensor

Directory of Open Access Journals (Sweden)

Shuo Wang

2013-09-01

Full Text Available A fluorescent molecularly imprinted nanosensor was obtained by grafting imprinted polymer onto the surface of multi-wall carbon nanotubes and post-imprinting treatment with fluorescein isothiocyanate (FITC. The fluorescence of lysozyme-imprinted polymer (Lys-MIP was quenched more strongly by Lys than that of nonimprinted polymer (NIP, which indicated that the Lys-MIP could recognize Lys. The resulted imprinted material has the ability to selectively sense a target protein, and an imprinting factor of 3.34 was achieved. The Lys-MIP also showed selective detection for Lys among other proteins such as cytochrome C (Cyt C, hemoglobin (HB and bovine serum albumin (BSA due to the imprinted sites in the Lys-MIP. This approach combines the high selectivity of surface molecular imprinting technology and fluorescence, and converts binding events into detectable signals by monitoring fluorescence spectra. Therefore, it will have further applications for Lys sensing.

Toehold-mediated strand displacement reaction triggered isothermal DNA amplification for highly sensitive and selective fluorescent detection of single-base mutation.

Science.gov (United States)

Zhu, Jing; Ding, Yongshun; Liu, Xingti; Wang, Lei; Jiang, Wei

2014-09-15

Highly sensitive and selective detection strategy for single-base mutations is essential for risk assessment of malignancy and disease prognosis. In this work, a fluorescent detection method for single-base mutation was proposed based on high selectivity of toehold-mediated strand displacement reaction (TSDR) and powerful signal amplification capability of isothermal DNA amplification. A discrimination probe was specially designed with a stem-loop structure and an overhanging toehold domain. Hybridization between the toehold domain and the perfect matched target initiated the TSDR along with the unfolding of the discrimination probe. Subsequently, the target sequence acted as a primer to initiate the polymerization and nicking reactions, which released a great abundant of short sequences. Finally, the released strands were annealed with the reporter probe, launching another polymerization and nicking reaction to produce lots of G-quadruplex DNA, which could bind the N-methyl mesoporphyrin IX to yield an enhanced fluorescence response. However, when there was even a single base mismatch in the target DNA, the TSDR was suppressed and so subsequent isothermal DNA amplification and fluorescence response process could not occur. The proposed approach has been successfully implemented for the identification of the single-base mutant sequences in the human KRAS gene with a detection limit of 1.8 pM. Furthermore, a recovery of 90% was obtained when detecting the target sequence in spiked HeLa cells lysate, demonstrating the feasibility of this detection strategy for single-base mutations in biological samples. Copyright © 2014 Elsevier B.V. All rights reserved.

Highly selective and sensitive coumarin-triazole-based fluorometric 'turn-off' sensor for detection of Pb2+ ions.

Science.gov (United States)

Shaily; Kumar, Ajay; Parveen, Iram; Ahmed, Naseem

2018-06-01

Exposure to even very low concentrations of Pb 2+ is known to cause cardiovascular, neurological, developmental, and reproductive disorders, and affects children in particular more severely. Consequently, much effort has been dedicated to the development of colorimetric and fluorescent sensors that can selectively detect Pb 2+ ions. Here, we describe the development of a triazole-based fluorescent sensor L5 for Pb 2+ ion detection. The fluorescence intensity of chemosensor L5 was selectively quenched by Pb 2+ ions and a clear color change from colorless to yellow could be observed by the naked eye. Chemosensor L5 exhibited high sensitivity and selectivity towards Pb 2+ ions in phosphate-buffered solution [20 mM, 1:9 DMSO/H 2 O (v/v), pH 8.0] with a 1:1 binding stoichiometry, a detection limit of 1.9 nM and a 6.76 × 10 6  M -1 binding constant. Additionally, low-cost and easy-to-prepare test strips impregnated with chemosensor L5 were also produced for efficient of Pb 2+ detection and proved the practical use of this test. Copyright © 2018 John Wiley & Sons, Ltd.

Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives.

Science.gov (United States)

Podevin, Michael; Fotidis, Ioannis A; Angelidaki, Irini

2018-08-01

Microalgae are well known for their ability to accumulate lipids intracellularly, which can be used for biofuels and mitigate CO 2 emissions. However, due to economic challenges, microalgae bioprocesses have maneuvered towards the simultaneous production of food, feed, fuel, and various high-value chemicals in a biorefinery concept. On-line and in-line monitoring of macromolecules such as lipids, proteins, carbohydrates, and high-value pigments will be more critical to maintain product quality and consistency for downstream processing in a biorefinery to maintain and valorize these markets. The main contribution of this review is to present current and prospective advances of on-line and in-line process analytical technology (PAT), with high-selectivity - the capability of monitoring several analytes simultaneously - in the interest of improving product quality, productivity, and process automation of a microalgal biorefinery. The high-selectivity PAT under consideration are mid-infrared (MIR), near-infrared (NIR), and Raman vibrational spectroscopies. The current review contains a critical assessment of these technologies in the context of recent advances in software and hardware in order to move microalgae production towards process automation through multivariate process control (MVPC) and software sensors trained on "big data". The paper will also include a comprehensive overview of off-line implementations of vibrational spectroscopy in microalgal research as it pertains to spectral interpretation and process automation to aid and motivate development.

Curved Microneedle Array-Based sEMG Electrode for Robust Long-Term Measurements and High Selectivity

Directory of Open Access Journals (Sweden)

Minjae Kim

2015-07-01

Full Text Available Surface electromyography is widely used in many fields to infer human intention. However, conventional electrodes are not appropriate for long-term measurements and are easily influenced by the environment, so the range of applications of sEMG is limited. In this paper, we propose a flexible band-integrated, curved microneedle array electrode for robust long-term measurements, high selectivity, and easy applicability. Signal quality, in terms of long-term usability and sensitivity to perspiration, was investigated. Its motion-discriminating performance was also evaluated. The results show that the proposed electrode is robust to perspiration and can maintain a high-quality measuring ability for over 8 h. The proposed electrode also has high selectivity for motion compared with a commercial wet electrode and dry electrode.

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

Science.gov (United States)

Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

Discrete Biogeography Based Optimization for Feature Selection in Molecular Signatures.

Science.gov (United States)

Liu, Bo; Tian, Meihong; Zhang, Chunhua; Li, Xiangtao

2015-04-01

Biomarker discovery from high-dimensional data is a complex task in the development of efficient cancer diagnoses and classification. However, these data are usually redundant and noisy, and only a subset of them present distinct profiles for different classes of samples. Thus, selecting high discriminative genes from gene expression data has become increasingly interesting in the field of bioinformatics. In this paper, a discrete biogeography based optimization is proposed to select the good subset of informative gene relevant to the classification. In the proposed algorithm, firstly, the fisher-markov selector is used to choose fixed number of gene data. Secondly, to make biogeography based optimization suitable for the feature selection problem; discrete migration model and discrete mutation model are proposed to balance the exploration and exploitation ability. Then, discrete biogeography based optimization, as we called DBBO, is proposed by integrating discrete migration model and discrete mutation model. Finally, the DBBO method is used for feature selection, and three classifiers are used as the classifier with the 10 fold cross-validation method. In order to show the effective and efficiency of the algorithm, the proposed algorithm is tested on four breast cancer dataset benchmarks. Comparison with genetic algorithm, particle swarm optimization, differential evolution algorithm and hybrid biogeography based optimization, experimental results demonstrate that the proposed method is better or at least comparable with previous method from literature when considering the quality of the solutions obtained. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Risk-based audit selection of dairy farms.

Science.gov (United States)

van Asseldonk, M A P M; Velthuis, A G J

2014-02-01

Dairy farms are audited in the Netherlands on numerous process standards. Each farm is audited once every 2 years. Increasing demands for cost-effectiveness in farm audits can be met by introducing risk-based principles. This implies targeting subpopulations with a higher risk of poor process standards. To select farms for an audit that present higher risks, a statistical analysis was conducted to test the relationship between the outcome of farm audits and bulk milk laboratory results before the audit. The analysis comprised 28,358 farm audits and all conducted laboratory tests of bulk milk samples 12 mo before the audit. The overall outcome of each farm audit was classified as approved or rejected. Laboratory results included somatic cell count (SCC), total bacterial count (TBC), antimicrobial drug residues (ADR), level of butyric acid spores (BAB), freezing point depression (FPD), level of free fatty acids (FFA), and cleanliness of the milk (CLN). The bulk milk laboratory results were significantly related to audit outcomes. Rejected audits are likely to occur on dairy farms with higher mean levels of SCC, TBC, ADR, and BAB. Moreover, in a multivariable model, maxima for TBC, SCC, and FPD as well as standard deviations for TBC and FPD are risk factors for negative audit outcomes. The efficiency curve of a risk-based selection approach, on the basis of the derived regression results, dominated the current random selection approach. To capture 25, 50, or 75% of the population with poor process standards (i.e., audit outcome of rejected), respectively, only 8, 20, or 47% of the population had to be sampled based on a risk-based selection approach. Milk quality information can thus be used to preselect high-risk farms to be audited more frequently. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

A Robust Service Selection Method Based on Uncertain QoS

Directory of Open Access Journals (Sweden)

Yanping Chen

2016-01-01

Full Text Available Nowadays, the number of Web services on the Internet is quickly increasing. Meanwhile, different service providers offer numerous services with the similar functions. Quality of Service (QoS has become an important factor used to select the most appropriate service for users. The most prominent QoS-based service selection models only take the certain attributes into account, which is an ideal assumption. In the real world, there are a large number of uncertain factors. In particular, at the runtime, QoS may become very poor or unacceptable. In order to solve the problem, a global service selection model based on uncertain QoS was proposed, including the corresponding normalization and aggregation functions, and then a robust optimization model adopted to transform the model. Experiment results show that the proposed method can effectively select services with high robustness and optimality.

Tracking and flavour tagging selection in the ATLAS High Level Trigger

CERN Document Server

Calvetti, Milene; The ATLAS collaboration

2017-01-01

In high-energy physics experiments, track based selection in the online environment is crucial for the efficient real time selection of the rare physics process of interest. This is of particular importance at the Large Hadron Collider (LHC), where the increasingly harsh collision environment is challenging the experiments to improve the performance of their online selection. Principal among these challenges is the increasing number of interactions per bunch crossing, known as pileup. In the ATLAS experiment the challenge has been addressed with multiple strategies. Firstly, specific trigger objects have been improved by building algorithms using detailed tracking and vertexing in specific detector regions to improve background rejection without loosing signal efficiency. Secondly, since 2015 all trigger areas have benefited from a new high performance Inner Detector (ID) software tracking system implemented in the High Level Trigger. Finally, performance will be further enhanced in future by the installation...

Highly selective probe based on imine linkage for Zn{sup 2+} and HSO{sub 3}{sup −} in mixed aqueous media

Energy Technology Data Exchange (ETDEWEB)

Kaur, Kamaljot; Chaudhary, Savita; Singh, Sukhjinder; Mehta, S.K., E-mail: skmehta@pu.ac.in

2015-04-15

A simple salicylaldehyde derived Schiff base N, N′- bis (p-chloro salicylidene)-1, 2- ethylenediamine (L) was synthesized and characterized. The receptor demonstrates simultaneous dual channel chromogenic and fluorogenic signaling towards HSO{sub 3}{sup −} and Zn{sup 2+} in mixed aqueous media. Solvatochromism was employed systematically for modulating its optoelectronic properties. The probe was successfully assessed to monitor HSO{sub 3}{sup −} detection via UV–vis spectroscopy. DFT calculations and {sup 1}H NMR spectroscopy further support the results based on shifting of equilibrium. Moreover, the sensor showed large fluorescence enhancement with blue-shift of 48 nm after addition of Zn{sup 2+}. The probe exhibits high selectivity over other competitive ions with high detection limit of 6.54×10{sup −5} M and 3.21×10{sup −6} M for HSO{sub 3}{sup −} and Zn{sup 2+}, respectively. Importantly, this is one of the rare reports in which Schiff base was utilized for the fabrication of chromogenic or fluorogenic sensor using solvent effect for multianalyte detection. - Highlights: • Easy synthesis of highly selective and sensitive Salicylideneaniline moiety. • Solvatochromism induced tautomerism between the enol-imine and keto-amine forms. • Computational studies revealing the effect of solvent on stability of NH form. • Discriminative detection of HSO{sub 3}{sup −} and Zn{sup 2+} by different spectroscopic techniques. • Optical feedbacks as absorption transitions with HSO{sub 3}{sup −} on bisulphite adduct formation. • Fluorescence enhancement for Zn{sup 2+} based on imine binding mechanism.

Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection*

Science.gov (United States)

Fan, Jianqing; Li, Yingying; Yu, Ke

2012-01-01

Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of “pairwise-refresh time” and “all-refresh time” methods based on the concept of “refresh time” proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index. PMID:23264708

Vast Volatility Matrix Estimation using High Frequency Data for Portfolio Selection.

Science.gov (United States)

Fan, Jianqing; Li, Yingying; Yu, Ke

2012-01-01

Portfolio allocation with gross-exposure constraint is an effective method to increase the efficiency and stability of portfolios selection among a vast pool of assets, as demonstrated in Fan et al. (2011). The required high-dimensional volatility matrix can be estimated by using high frequency financial data. This enables us to better adapt to the local volatilities and local correlations among vast number of assets and to increase significantly the sample size for estimating the volatility matrix. This paper studies the volatility matrix estimation using high-dimensional high-frequency data from the perspective of portfolio selection. Specifically, we propose the use of "pairwise-refresh time" and "all-refresh time" methods based on the concept of "refresh time" proposed by Barndorff-Nielsen et al. (2008) for estimation of vast covariance matrix and compare their merits in the portfolio selection. We establish the concentration inequalities of the estimates, which guarantee desirable properties of the estimated volatility matrix in vast asset allocation with gross exposure constraints. Extensive numerical studies are made via carefully designed simulations. Comparing with the methods based on low frequency daily data, our methods can capture the most recent trend of the time varying volatility and correlation, hence provide more accurate guidance for the portfolio allocation in the next time period. The advantage of using high-frequency data is significant in our simulation and empirical studies, which consist of 50 simulated assets and 30 constituent stocks of Dow Jones Industrial Average index.

Synthesis and application of a highly selective copper ions fluorescent probe based on the coumarin group

Science.gov (United States)

He, Guangjie; Liu, Xiangli; Xu, Jinhe; Ji, Liguo; Yang, Linlin; Fan, Aiying; Wang, Songjun; Wang, Qingzhi

2018-02-01

A highly selective copper ions fluorescent probe based on the coumarin-type Schiff base derivative 1 (probe) was produced by condensation reaction between coumarin carbohydrazide and 1H-indazole-3-carbaldehyde. The UV-vis spectroscopy showed that the maximum absorption peak of compound 1 appeared at 439 nm. In the presence of Cu2 + ions, the maximum peak decreased remarkably compared with other physiological important metal ions and a new absorption peak at 500 nm appeared. The job's plot experiments showed that complexes of 1:2 binding mode were formed in CH3CN:HEPES (3:2, v/v) solution. Compound 1 exhibited a strong blue fluorescence. Upon addition of copper ions, the fluorescence gradually decreased and reached a plateau with the fluorescence quenching rate up to 98.73%. The detection limit for Cu2 + ions was estimated to 0.384 ppm. Fluorescent microscopy experiments demonstrated that probe 1 had potential to be used to investigate biological processes involving Cu2 + ions within living cells.

Selective excitation of atoms or molecules to high-lying states

International Nuclear Information System (INIS)

Ducas, T.W.

1978-01-01

This specification relates to the selective excitation of atoms or molecules to high lying states and a method of separating different isotopes of the same element by selective excitation of the isotopes. (U.K.)

pH-Responsive chromogenic-sensing molecule based on bis(indolylmethene for the highly selective recognition of aspartate and glutamate

Directory of Open Access Journals (Sweden)

Shijun Shao

2011-02-01

Full Text Available Bis(indolylmethene displays high selectivity and sensitivity for aspartate and glutamate in water-containing medium based on the proton transfer signaling mode. The presence of acid can easily induce proton transfer to the basic H-bond acceptor moiety, which modulates the internal charge transfer state of the bis(indolylmethene skeleton and gives rise to dramatic change in color. The detection limits for aspartate and glutamate were 0.80 ppm and 1.12 ppm, respectively.

Plastic antibody based surface plasmon resonance nanosensors for selective atrazine detection

Energy Technology Data Exchange (ETDEWEB)

Yılmaz, Erkut [Department of Chemistry, Aksaray University, 68100 Aksaray (Turkey); Özgür, Erdoğan; Bereli, Nilay; Türkmen, Deniz [Department of Chemistry, Hacettepe University, 06800 Ankara (Turkey); Denizli, Adil, E-mail: denizli@hacettepe.edu.tr [Department of Chemistry, Hacettepe University, 06800 Ankara (Turkey)

2017-04-01

This study reports a surface plasmon resonance (SPR) based affinity sensor system with the use of molecular imprinted nanoparticles (plastic antibodies) to enhance the pesticide detection. Molecular imprinting based affinity sensor is prepared by the attachment of atrazine (chosen as model pesticide) imprinted nanoparticles onto the gold surface of SPR chip. Recognition element of the affinity sensor is polymerizable form of aspartic acid. The imprinted nanoparticles were characterized via FTIR and zeta-sizer measurements. SPR sensors are characterized with atomic force microscopy (AFM), scanning electron microscopy (SEM), Fourier transform infrared spectrophotometry (FTIR) and contact angle measurements. The imprinted nanoparticles showed more sensitivity to atrazine than the non-imprinted ones. Different concentrations of atrazine solutions are applied to SPR system to determine the adsorption kinetics. Langmuir adsorption model is found as the most suitable model for this affinity nanosensor system. In order to show the selectivity of the atrazine-imprinted nanoparticles, competitive adsorption of atrazine, simazine and amitrole is investigated. The results showed that the imprinted nanosensor has high selectivity and sensitivity for atrazine. - Highlights: • SPR based affinity sensor system was developed via molecular imprinting. • Recognition element of the affinity sensor is polymerizable form of an amino acid. • Combination of SPR and MIP offers highly selective sensor with long shelf-life. • Plastic antibody based biomimetic sensors offer relatively cheaper production. • Plastic antibody based biomimetic sensors offer high physical, chemical stability.

Plastic antibody based surface plasmon resonance nanosensors for selective atrazine detection

International Nuclear Information System (INIS)

Yılmaz, Erkut; Özgür, Erdoğan; Bereli, Nilay; Türkmen, Deniz; Denizli, Adil

2017-01-01

This study reports a surface plasmon resonance (SPR) based affinity sensor system with the use of molecular imprinted nanoparticles (plastic antibodies) to enhance the pesticide detection. Molecular imprinting based affinity sensor is prepared by the attachment of atrazine (chosen as model pesticide) imprinted nanoparticles onto the gold surface of SPR chip. Recognition element of the affinity sensor is polymerizable form of aspartic acid. The imprinted nanoparticles were characterized via FTIR and zeta-sizer measurements. SPR sensors are characterized with atomic force microscopy (AFM), scanning electron microscopy (SEM), Fourier transform infrared spectrophotometry (FTIR) and contact angle measurements. The imprinted nanoparticles showed more sensitivity to atrazine than the non-imprinted ones. Different concentrations of atrazine solutions are applied to SPR system to determine the adsorption kinetics. Langmuir adsorption model is found as the most suitable model for this affinity nanosensor system. In order to show the selectivity of the atrazine-imprinted nanoparticles, competitive adsorption of atrazine, simazine and amitrole is investigated. The results showed that the imprinted nanosensor has high selectivity and sensitivity for atrazine. - Highlights: • SPR based affinity sensor system was developed via molecular imprinting. • Recognition element of the affinity sensor is polymerizable form of an amino acid. • Combination of SPR and MIP offers highly selective sensor with long shelf-life. • Plastic antibody based biomimetic sensors offer relatively cheaper production. • Plastic antibody based biomimetic sensors offer high physical, chemical stability.

Feature selection for neural network based defect classification of ceramic components using high frequency ultrasound.

Science.gov (United States)

Kesharaju, Manasa; Nagarajah, Romesh

2015-09-01

The motivation for this research stems from a need for providing a non-destructive testing method capable of detecting and locating any defects and microstructural variations within armour ceramic components before issuing them to the soldiers who rely on them for their survival. The development of an automated ultrasonic inspection based classification system would make possible the checking of each ceramic component and immediately alert the operator about the presence of defects. Generally, in many classification problems a choice of features or dimensionality reduction is significant and simultaneously very difficult, as a substantial computational effort is required to evaluate possible feature subsets. In this research, a combination of artificial neural networks and genetic algorithms are used to optimize the feature subset used in classification of various defects in reaction-sintered silicon carbide ceramic components. Initially wavelet based feature extraction is implemented from the region of interest. An Artificial Neural Network classifier is employed to evaluate the performance of these features. Genetic Algorithm based feature selection is performed. Principal Component Analysis is a popular technique used for feature selection and is compared with the genetic algorithm based technique in terms of classification accuracy and selection of optimal number of features. The experimental results confirm that features identified by Principal Component Analysis lead to improved performance in terms of classification percentage with 96% than Genetic algorithm with 94%. Copyright © 2015 Elsevier B.V. All rights reserved.

A highly sensitive, selective and turn-off fluorescent sensor based on phenylamine-oligothiophene derivative for rapid detection of Hg{sup 2+}

Energy Technology Data Exchange (ETDEWEB)

Wu, Xingxing; Niu, Qingfen, E-mail: qf_niu1216@qlu.edu.cn; Li, Tianduo; Cui, Yuezhi; Zhang, Shanshan

2016-07-15

A fluorescent sensor based on phenylamine-oligothiophene derivative 3TEA was reported. This sensor showed highly selective and sensitive detection of Hg{sup 2+} ion in THF/H{sub 2}O (7/3, v/v) solution through fluorescence quenching. The detection was unaffected by other competitive metal ions. The detection limit was found to be as low as 3.952×10{sup −7} M estimated by the titration method. The recognition process is reversible and confirmed by EDTA experiment. The turn-off fluorescence behavior of mercury interaction with 3TEA has been found to be so fast that it can be used for its qualitative as well as quantitative estimation. - Highlights: • A highly sensitive and selective fluorescence chemosensor 3TEA was reported. • 3TEA features high sensitive with the detection limit for Hg{sup 2+} ions was as low as 3.952×10{sup −7} M. • 3TEA can detect Hg{sup 2+} ion on-line and in real time.

Highly CO2-Selective Gas Separation Membranes Based on Segmented Copolymers of Poly(Ethylene oxide) Reinforced with Pentiptycene-Containing Polyimide Hard Segments.

Science.gov (United States)

Luo, Shuangjiang; Stevens, Kevin A; Park, Jae Sung; Moon, Joshua D; Liu, Qiang; Freeman, Benny D; Guo, Ruilan

2016-01-27

Poly(ethylene oxide) (PEO)-containing polymer membranes are attractive for CO2-related gas separations due to their high selectivity toward CO2. However, the development of PEO-rich membranes is frequently challenged by weak mechanical properties and a high crystallization tendency of PEO that hinders gas transport. Here we report a new series of highly CO2-selective, amorphous PEO-containing segmented copolymers prepared from commercial Jeffamine polyetheramines and pentiptycene-based polyimide. The copolymers are much more mechanically robust than the nonpentiptycene containing counterparts due to the molecular reinforcement mechanism of supramolecular chain threading and interlocking interactions induced by the pentiptycene structures, which also effectively suppresses PEO crystallization leading to a completely amorphous structure even at 60% PEO weight content. Membrane transport properties are sensitively affected by both PEO weight content and PEO chain length. A nonlinear correlation between CO2 permeability with PEO weight content was observed due to the competition between solubility and diffusivity contributions, whereby the copolymers change from being size-selective to solubility-selective when PEO content reaches 40%. CO2 selectivities over H2 and N2 increase monotonically with both PEO content and chain length, indicating strong CO2-philicity of the copolymers. The copolymer film with the longest PEO sequence (PEO2000) and highest PEO weight content (60%) showed a measured CO2 pure gas permeability of 39 Barrer, and ideal CO2/H2 and CO2/N2 selectivities of 4.1 and 46, respectively, at 35 °C and 3 atm, making them attractive for hydrogen purification and carbon capture.

Directional enhancement of selected high-order-harmonics from intense laser irradiated blazed grating targets.

Science.gov (United States)

Zhang, Guobo; Chen, Min; Liu, Feng; Yuan, Xiaohui; Weng, Suming; Zheng, Jun; Ma, Yanyun; Shao, Fuqiu; Sheng, Zhengming; Zhang, Jie

2017-10-02

Relativistically intense laser solid target interaction has been proved to be a promising way to generate high-order harmonics, which can be used to diagnose ultrafast phenomena. However, their emission direction and spectra still lack tunability. Based upon two-dimensional particle-in-cell simulations, we show that directional enhancement of selected high-order-harmonics can be realized using blazed grating targets. Such targets can select harmonics with frequencies being integer times of the grating frequency. Meanwhile, the radiation intensity and emission area of the harmonics are increased. The emission direction is controlled by tailoring the local blazed structure. Theoretical and electron dynamics analysis for harmonics generation, selection and directional enhancement from the interaction between multi-cycle laser and grating target are carried out. These studies will benefit the generation and application of laser plasma-based high order harmonics.

FOOD SECURITY SITUATION OF SELECTED HIGHLY DEVELOPED COUNTRIES AGAINST DEVELOPING COUNTRIES

OpenAIRE

Karolina Pawlak

2016-01-01

The aim of the paper is to present the food security situation in selected highly developed countries and to identify consumption disparities between them and developing countries. The research is based on the data from the United Nations Food and Agriculture Organization (FAO), the Statistical Office of the European Union (Eurostat), the United Nations Statistics Division, the Organisation for Economic Co-operation and Development (OECD), World Food Programme (WFP) and selected measures used...

Computational intelligence-based polymerase chain reaction primer selection based on a novel teaching-learning-based optimisation.

Science.gov (United States)

Cheng, Yu-Huei

2014-12-01

Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.

High-efficiency single cell encapsulation and size selective capture of cells in picoliter droplets based on hydrodynamic micro-vortices.

Science.gov (United States)

Kamalakshakurup, Gopakumar; Lee, Abraham P

2017-12-05

Single cell analysis has emerged as a paradigm shift in cell biology to understand the heterogeneity of individual cells in a clone for pathological interrogation. Microfluidic droplet technology is a compelling platform to perform single cell analysis by encapsulating single cells inside picoliter-nanoliter (pL-nL) volume droplets. However, one of the primary challenges for droplet based single cell assays is single cell encapsulation in droplets, currently achieved either randomly, dictated by Poisson statistics, or by hydrodynamic techniques. In this paper, we present an interfacial hydrodynamic technique which initially traps the cells in micro-vortices, and later releases them one-to-one into the droplets, controlled by the width of the outer streamline that separates the vortex from the flow through the streaming passage adjacent to the aqueous-oil interface (d gap ). One-to-one encapsulation is achieved at a d gap equal to the radius of the cell, whereas complete trapping of the cells is realized at a d gap smaller than the radius of the cell. The unique feature of this technique is that it can perform 1. high efficiency single cell encapsulations and 2. size-selective capturing of cells, at low cell loading densities. Here we demonstrate these two capabilities with a 50% single cell encapsulation efficiency and size selective separation of platelets, RBCs and WBCs from a 10× diluted blood sample (WBC capture efficiency at 70%). The results suggest a passive, hydrodynamic micro-vortex based technique capable of performing high-efficiency single cell encapsulation for cell based assays.

Highly selective coextraction of rhodamine B and dibenzyl phthalate based on high-density dual-template imprinted shells on silica microparticles.

Science.gov (United States)

Long, Zerong; Xu, Weiwei; Peng, Yumei; Lu, Yi; Luo, Qian; Qiu, Hongdeng

2017-01-01

A simple one-pot approach based on molecularly imprinted polymer shells dispersed on the surface of silica for simultaneous determination of rhodamine B and dibenzyl phthalate (DBzP) has been developed. Highly dense molecularly imprinted polymer shells were formed in the mixture of acetonitrile and toluene by the copolymerization of methacrylic acid and ethylene glycol dimethacrylate, as well as two templates, rhodamine B and dibenzyl phthalate, directed by the vinyl end groups functional monolayer at surface silica microspheres after 3-methacryloxypropyl trimethoxysilane modification. The obtained imprinted polymer shells showed large average pore diameter (102.5 nm) and about 100 nm shell thickness. The imprinted particles also showed high imprinting factor (α RhB = 3.52 and α DBzP = 3.94), rapid binding kinetics, and excellent selective affinity capacity for rhodamine B and dibenzyl phthalate containing another three competitors in mixed solution. Moreover, the imprinted particles coupled with ultra high performance liquid chromatography was successfully applied to simultaneous analysis of rhodamine B and dibenzyl phthalate in two spiked beverage samples with average recoveries in the range of 88.0-93.0% for rhodamine B and 84.0-92.0% for dibenzyl phthalate with the relative standard deviation lower than 5.1%. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly sensitive and selective cholesterol biosensor based on direct electron transfer of hemoglobin.

Science.gov (United States)

Zhao, Changzhi; Wan, Li; Jiang, Li; Wang, Qin; Jiao, Kui

2008-12-01

A cholesterol biosensor based on direct electron transfer of a hemoglobin-encapsulated chitosan-modified glassy carbon electrode has been developed for highly sensitive and selective analysis of serum samples. Modified by films containing hemoglobin and cholesterol oxidase, the electrode was prepared by encapsulation of enzyme in chitosan matrix. The hydrogen peroxide produced by the catalytic oxidation of cholesterol by cholesterol oxidase was reduced electrocatalytically by immobilized hemoglobin and used to obtain a sensitive amperometric response to cholesterol. The linear response of cholesterol concentrations ranged from 1.00 x 10(-5) to 6.00 x 10(-4) mol/L, with a correlation coefficient of 0.9969 and estimated detection limit of cholesterol of 9.5 micromol/L at a signal/noise ratio of 3. The cholesterol biosensor can efficiently exclude interference by the commonly coexisting ascorbic acid, uric acid, dopamine, and epinephrine. The sensitivity to the change in the concentration of cholesterol as the slope of the calibration curve was 0.596 A/M. The relative standard deviation was under 4.0% (n=5) for the determination of real samples. The biosensor is satisfactory in the determination of human serum samples.

Selective hydrogen detection at high temperature by using yttria-stabilized zirconia-based sensor with coupled metal-oxide-based sensing electrodes

International Nuclear Information System (INIS)

Yamaguchi, Mami; Anggraini, Sri Ayu; Fujio, Yuki; Breedon, Michael; Plashnitsa, Vladimir V.; Miura, Norio

2012-01-01

A selective and sensitive hydrogen (H 2 ) sensor capable of working at a high operating temperature was developed by using a pair of metal-oxide-based SEs formed on a yttria-stabilized zirconia (YSZ) tube, operating as a mixed-potential type sensor. The utilization of SnO 2 (+30 wt.% YSZ) electrode together with NiO-TiO 2 electrode configured as a combined-type sensor, successfully diminished the response of the examined interfering gases (especially propene), while maintaining high response toward H 2 at an operating temperature of 600 °C under humid operating conditions. The developed sensor exhibited quick response to 100 ppm H 2 , as the 90% response time was observed to be 9 s. The sensing performance of the combined-type sensor was barely affected by changes in water vapor concentration within the range of 1–4 vol.%, suggesting the resilience of the sensor to function in realistic working conditions. This sensor exhibited a linear relationship between sensitivity and H 2 concentration on a logarithmic scale.

High Altitude Balloon Flight Path Prediction and Site Selection Based On Computer Simulations

Science.gov (United States)

Linford, Joel

2010-10-01

Interested in the upper atmosphere, Weber State University Physics department has developed a High Altitude Reconnaissance Balloon for Outreach and Research team, also known as HARBOR. HARBOR enables Weber State University to take a variety of measurements from ground level to altitudes as high as 100,000 feet. The flight paths of these balloons can extend as long as 100 miles from the launch zone, making the choice of where and when to fly critical. To ensure the ability to recover the packages in a reasonable amount of time, days and times are carefully selected using computer simulations limiting flight tracks to approximately 40 miles from the launch zone. The computer simulations take atmospheric data collected by National Oceanic and Atmospheric Administration (NOAA) to plot what flights might have looked like in the past, and to predict future flights. Using these simulations a launch zone has been selected in Duchesne Utah, which has hosted eight successful flights over the course of the last three years, all of which have been recovered. Several secondary launch zones in western Wyoming, Southern Idaho, and Northern Utah are also being considered.

High-throughput selection for cellulase catalysts using chemical complementation.

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T; Lin, Hening; Tao, Haiyan; Cornish, Virginia W

2008-12-24

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases, however, is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Because of the large number of enzyme variants that selections can now test as compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity.

Improved targeted immunization strategies based on two rounds of selection

Science.gov (United States)

Xia, Ling-Ling; Song, Yu-Rong; Li, Chan-Chan; Jiang, Guo-Ping

2018-04-01

In the case of high degree targeted immunization where the number of vaccine is limited, when more than one node associated with the same degree meets the requirement of high degree centrality, how can we choose a certain number of nodes from those nodes, so that the number of immunized nodes will not exceed the limit? In this paper, we introduce a new idea derived from the selection process of second-round exam to solve this problem and then propose three improved targeted immunization strategies. In these proposed strategies, the immunized nodes are selected through two rounds of selection, where we increase the quotas of first-round selection according the evaluation criterion of degree centrality and then consider another characteristic parameter of node, such as node's clustering coefficient, betweenness and closeness, to help choose targeted nodes in the second-round selection. To validate the effectiveness of the proposed strategies, we compare them with the degree immunizations including the high degree targeted and the high degree adaptive immunizations using two metrics: the size of the largest connected component of immunized network and the number of infected nodes. Simulation results demonstrate that the proposed strategies based on two rounds of sorting are effective for heterogeneous networks and their immunization effects are better than that of the degree immunizations.

“Stereoscopic” 2D super-microporous phosphazene-based covalent organic framework: Design, synthesis and selective sorption towards uranium at high acidic condition

Energy Technology Data Exchange (ETDEWEB)

Zhang, Shuang; Zhao, Xiaosheng; Li, Bo; Bai, Chiyao; Li, Yang; Wang, Lei; Wen, Rui; Zhang, Meicheng; Ma, Lijian; Li, Shoujian, E-mail: sjli000616@scu.edu.cn

2016-08-15

Highlights: • Phosphorus element was first introduced into covalent organic frameworks (COFs). • Monomer in C{sub 3}-like spatial configuration was first used to construct COF materials. • A new 2D super-microporous phosphazene-based sorbent (MPCOF) was synthesized. • Separation of U (VI) by MPCOF at high acidic media (up to 1M HNO{sub 3}) was achieved. • Selectivity for U (VI) separation from multi-ion solution can reach unreported 92%. - Abstract: So far, only five primary elements (C, H, O, N and B) and two types of spatial configuration (C{sub 2}–C{sub 4}, C{sub 6} and T{sub d}) are reported to build the monomers for synthesis of covalent organic frameworks (COFs), which have partially limited the route selection for accessing COFs with new topological structure and novel properties. Here, we reported the design and synthesis of a new “stereoscopic” 2D super-microporous phosphazene-based covalent organic framework (MPCOF) by using hexachorocyclotriphosphazene (a P-containing monomer in a C{sub 3}-like spatial configuration) and p-phenylenediamine (a linker). The as-synthesized MPCOF shows high crystallinity, relatively high heat and acid stability and distinctive super-microporous structure with narrow pore-size distributions ranging from 1.0–2.1 nm. The results of batch sorption experiments with a multi-ion solution containing 12 co-existing cations show that in the pH range of 1–2.5, MPCOF exhibits excellent separation efficiency for uranium with adsorption capacity more than 71 mg/g and selectivity up to record-breaking 92%, and furthermore, an unreported sorption capacity (>50 mg/g) and selectivity (>60%) were obtained under strong acidic condition (1 M HNO{sub 3}). Studies on sorption mechanism indicate that the uranium separation by MPCOF in acidic solution is realized mainly through both intra-particle diffusion and size-sieving effect.

Selective fluorescence sensors for detection of nitroaniline and metal Ions based on ligand-based luminescent metal-organic frameworks

International Nuclear Information System (INIS)

Yu, Zongchao; Wang, Fengqin; Lin, Xiangyi; Wang, Chengmiao; Fu, Yiyuan; Wang, Xiaojun; Zhao, Yongnan; Li, Guodong

2015-01-01

Metal-organic frameworks (MOFs) are porous crystalline materials with high potential for applications in fluorescence sensors. In this work, two solvent-induced Zn(II)–based metal-organic frameworks, Zn_3L_3(DMF)_2 (1) and Zn_3L_3(DMA)_2(H_2O)_3 (2) (L=4,4′-stilbenedicarboxylic acid), were investigated as selective sensing materials for detection of nitroaromatic compounds and metal ions. The sensing experiments show that 1 and 2 both exhibit selective fluorescence quenching toward nitroaniline with a low detection limit. In addition, 1 exhibits high selectivity for detection of Fe"3"+ and Al"3"+ by significant fluorescence quenching or enhancement effect. While for 2, it only exhibits significant fluorescence quenching effect for Fe"3"+. The results indicate that 1 and 2 are both promising fluorescence sensors for detecting and recognizing nitroaniline and metal ions with high sensitivity and selectivity. - Graphical abstract: Two MOFs have been selected as the fluorescence sensing materials for selectively sensing mitroaromatic compounds and metal ions. The high selectivity makes them promising fluorescence sensors for detecting and recognizing nitroaniline and Fe"3"+ or Al"3"+.

EEG feature selection method based on decision tree.

Science.gov (United States)

Duan, Lijuan; Ge, Hui; Ma, Wei; Miao, Jun

2015-01-01

This paper aims to solve automated feature selection problem in brain computer interface (BCI). In order to automate feature selection process, we proposed a novel EEG feature selection method based on decision tree (DT). During the electroencephalogram (EEG) signal processing, a feature extraction method based on principle component analysis (PCA) was used, and the selection process based on decision tree was performed by searching the feature space and automatically selecting optimal features. Considering that EEG signals are a series of non-linear signals, a generalized linear classifier named support vector machine (SVM) was chosen. In order to test the validity of the proposed method, we applied the EEG feature selection method based on decision tree to BCI Competition II datasets Ia, and the experiment showed encouraging results.

Highly selective single-use fluoride ion optical sensor based on aluminum(III)-salen complex in thin polymeric film

International Nuclear Information System (INIS)

Badr, Ibrahim H.A.; Meyerhoff, Mark E.

2005-01-01

A highly selective optical sensor for fluoride ion based on the use of an aluminum(III)-salen complex as an ionophore within a thin polymeric film is described. The sensor is prepared by embedding the aluminum(III)-salen ionophore and a suitable lipophilic pH-sensitive indicator (ETH-7075) in a plasticized poly(vinyl chloride) (PVC) film. Optical response to fluoride occurs due to fluoride extraction into the polymer via formation of a strong complex with the aluminum(III)-salen species. Co-extraction of protons occurs simultaneously, with protonation of the indicator dye yielding the optical response at 529 nm. Films prepared using dioctylsebacate (DOS) are shown to exhibit better response (e.g., linear range, detection limit, and optical signal stability) compared to those prepared using ortho-nitrophenyloctyl ether (o-NPOE). Films formulated with aluminum(III)-salen and ETH-7075 indicator in 2 DOS:1 PVC, exhibit a significantly enhanced selectivity for fluoride over a wide range of lipophilic anions including salicylate, perchlorate, nitrate, and thiocyanate. The optimized films exhibit a sub-micromolar detection limit, using glycine-phosphate buffer, pH 3.00, as the test sample. The response times of the fluoride optical sensing films are in the range of 1-10 min depending on the fluoride ion concentration in the sample. The sensor exhibits very poor reversibility owing to a high co-extraction constant (log K = 8.5 ± 0.4), indicating that it can best be employed as a single-use transduction device. The utility of the aluminum(III)-salen based fluoride sensitive films as single-use sensors is demonstrated by casting polymeric films on the bottom of standard polypropylene microtiter plate wells (96 wells/plate). The modified microtiter plate optode format sensors exhibit response characteristics comparable to the classical optode films cast on quartz slides. The modified microtiter is utilized for the analysis of fluoride in diluted anti-cavity fluoride rinse

Quantization selection in the high-throughput H.264/AVC encoder based on the RD

Science.gov (United States)

Pastuszak, Grzegorz

2013-10-01

In the hardware video encoder, the quantization is responsible for quality losses. On the other hand, it allows the reduction of bit rates to the target one. If the mode selection is based on the rate-distortion criterion, the quantization can also be adjusted to obtain better compression efficiency. Particularly, the use of Lagrangian function with a given multiplier enables the encoder to select the most suitable quantization step determined by the quantization parameter QP. Moreover, the quantization offset added before discarding the fraction value after quantization can be adjusted. In order to select the best quantization parameter and offset in real time, the HD/SD encoder should be implemented in the hardware. In particular, the hardware architecture should embed the transformation and quantization modules able to process the same residuals many times. In this work, such an architecture is used. Experimental results show what improvements in terms of compression efficiency are achievable for Intra coding.

Multi-Objective Particle Swarm Optimization Approach for Cost-Based Feature Selection in Classification.

Science.gov (United States)

Zhang, Yong; Gong, Dun-Wei; Cheng, Jian

2017-01-01

Feature selection is an important data-preprocessing technique in classification problems such as bioinformatics and signal processing. Generally, there are some situations where a user is interested in not only maximizing the classification performance but also minimizing the cost that may be associated with features. This kind of problem is called cost-based feature selection. However, most existing feature selection approaches treat this task as a single-objective optimization problem. This paper presents the first study of multi-objective particle swarm optimization (PSO) for cost-based feature selection problems. The task of this paper is to generate a Pareto front of nondominated solutions, that is, feature subsets, to meet different requirements of decision-makers in real-world applications. In order to enhance the search capability of the proposed algorithm, a probability-based encoding technology and an effective hybrid operator, together with the ideas of the crowding distance, the external archive, and the Pareto domination relationship, are applied to PSO. The proposed PSO-based multi-objective feature selection algorithm is compared with several multi-objective feature selection algorithms on five benchmark datasets. Experimental results show that the proposed algorithm can automatically evolve a set of nondominated solutions, and it is a highly competitive feature selection method for solving cost-based feature selection problems.

Spectrally selective solar absorber with sharp and temperature dependent cut-off based on semiconductor nanowire arrays

Science.gov (United States)

Wang, Yang; Zhou, Lin; Zheng, Qinghui; Lu, Hong; Gan, Qiaoqiang; Yu, Zongfu; Zhu, Jia

2017-05-01

Spectrally selective absorbers (SSA) with high selectivity of absorption and sharp cut-off between high absorptivity and low emissivity are critical for efficient solar energy conversion. Here, we report the semiconductor nanowire enabled SSA with not only high absorption selectivity but also temperature dependent sharp absorption cut-off. By taking advantage of the temperature dependent bandgap of semiconductors, we systematically demonstrate that the absorption cut-off profile of the semiconductor-nanowire-based SSA can be flexibly tuned, which is quite different from most of the other SSA reported so far. As an example, silicon nanowire based selective absorbers are fabricated, with the measured absorption efficiency above (below) bandgap ˜97% (15%) combined with an extremely sharp absorption cut-off (transition region ˜200 nm), the sharpest SSA demonstrated so far. The demonstrated semiconductor-nanowire-based SSA can enable a high solar thermal efficiency of ≳86% under a wide range of operating conditions, which would be competitive candidates for the concentrated solar energy utilizations.

Development, evaluation, and selection of candidate high-level waste forms

International Nuclear Information System (INIS)

Bernadzikowski, T.A.; Allender, J.S.; Gordon, D.E.; Gould, T.H. Jr.

1982-01-01

The seven candidate waste forms, evaluated as potential media for the immobilization and gelogic disposal of high-level nuclear wastes were borosilicate glass, SYNROC, tailored ceramic, high-silica glass, FUETAP concrete, coated sol-gel particles, and glass marbles in a lead matrix. The evaluation, completed on August 1, 1981, combined preliminary waste form evaluations conducted at Department of Energy (DOE) defense waste-sites and at independent laboratories, peer review assessments, a product performance evaluation, and a processability analysis. Based on the combined results of these four inputs, two of the seven forms, borosilicate glass and a titanate-based ceramic, SYNROC, were selected as the reference and alternative forms, respectively, for continued development and evaluation in the National HLW Program. The borosilicate glass and ceramic forms were further compared during FY-1982 on the basis of risk assessments, cost comparisons, properties comparisons, and conformance with proposed regulatory and repository criteria. Both the glass and ceramic forms are viable candidates for use at DOE defense HLW sites; they are also candidates for immobilization of commercial reprocessing wastes. This paper describes the waste form screening process, discusses each of the four major inputs considered in the selection of the two forms in 1981, and presents a brief summary of the comparisons of the two forms during 1982 and the selection process to determine the final form for SRP defense HLW

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

Directory of Open Access Journals (Sweden)

Jaesung Lee

2016-11-01

Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

Multilayered ion-imprinted membranes with high selectivity towards Li+ based on the synergistic effect of 12-crown-4 and polyether sulfone

Science.gov (United States)

Lu, Jian; Qin, Yingying; Zhang, Qi; Wu, Yilin; Cui, Jiuyun; Li, Chunxiang; Wang, Liang; Yan, Yongsheng

2018-01-01

High-selective multilayered Li+-imprinted membranes (Li-IIMs) with enhanced hydrophilicity and stability were developed based on polyether sulfone substrate membranes. The multilayered structure was prepared with polydopamine (pDA) as the interfacial adhesion layer, SiO2 nanoparticles as the hydrophilic layer and Li+-imprinted polymers as the imprinted layer. The selective ;Li+-recognition sites; were formed using 12-crown-4 (12C4) as the adsorbing units. The optimal relative selectivity coefficients (α) of Li+/Na+ and Li+/K+ reached up to 1.85 and 2.07 with the imprinting factor (β) of 2.51, and the high permselectivity factors (γ) of Na+/Li+ (7.39) and K+/Li+ (9.86) were achieved on Li-IIMs. The Langmuir isotherm model and the pseudo-second-order kinetics model best fitted the rebinding data of Li-IIMs, as well as the rebinding capacities reached up to 90.3% of initial binding after 5 cycles of adsorption/desorption and just declined to 88.1% after another 5 cycles a month later. Therefore, the as-prepared Li-IIMs would have potential applications for the separation of lithium ions from salt lake brines.

Analysis of severe feather pecking behavior in a high feather pecking selection line

DEFF Research Database (Denmark)

Labouriau, R; Kjaer, J B; Abreu, G C G

2009-01-01

Even though feather pecking (FP) in laying hens has been extensively studied, a good solution to prevent chickens from this behavior under commercial circumstances has not been found. Selection against FP behavior is possible, but for a more effective selection across different populations......, it is necessary to characterize the genetic mechanism associated with this behavior. In this study, we use a high FP selection line, which has been selected for 8 generations. We present evidence of the presence of a major dominant allele affecting the FP behavior by using an argument based on the presence...

Highly selective potentiometric and colorimetric determinations of cobalt (II) ion using thiazole based ligands.

Science.gov (United States)

Singhal, Divya; Singh, Ashok Kumar; Upadhyay, Anjali

2014-12-01

New PVC-membrane electrodes were prepared by using 2-((thiazol-2-ylimino)methyl)phenol (L1) and 2-((thiazol-2-ylamino)methyl)phenol (L2) and explored as Co(II) selective electrodes. The effect of various plasticizers and anion excluder was studied in detail and improved performance was observed. It was found that the electrode based on L1 shows better response characteristics in comparison to L2. Optimum performance was observed for the membrane electrode having a composition of L1:NaTPB:DBP:PVC≡2:8:78:62 (w/w, mg). The performance of PME based on L1 was compared with that of CGE. The electrodes exhibit Nernstian slope for Co(II) ions with a limit of detection of 6.91×10(-7) mol L(-1) for PME and 7.94×10(-8) mol L(-1) for CGE. The response time for PME and CGE was found to be 15s and 12 s respectively. The potentiometric responses are independent in the pH range 3.0-9.0 for CGE. The CGE could be used for a period of 90 days. The CGE was used as an indicator electrode in potentiometric titration of EDTA with Co(2+) ion. Further the selectivity of the L1 and L2 was also confirmed by the UV-vis and colorimetric studies and found that L1 is more selective for Co(II) ion. Copyright © 2014 Elsevier B.V. All rights reserved.

Complexity control algorithm based on adaptive mode selection for interframe coding in high efficiency video coding

Science.gov (United States)

Chen, Gang; Yang, Bing; Zhang, Xiaoyun; Gao, Zhiyong

2017-07-01

The latest high efficiency video coding (HEVC) standard significantly increases the encoding complexity for improving its coding efficiency. Due to the limited computational capability of handheld devices, complexity constrained video coding has drawn great attention in recent years. A complexity control algorithm based on adaptive mode selection is proposed for interframe coding in HEVC. Considering the direct proportionality between encoding time and computational complexity, the computational complexity is measured in terms of encoding time. First, complexity is mapped to a target in terms of prediction modes. Then, an adaptive mode selection algorithm is proposed for the mode decision process. Specifically, the optimal mode combination scheme that is chosen through offline statistics is developed at low complexity. If the complexity budget has not been used up, an adaptive mode sorting method is employed to further improve coding efficiency. The experimental results show that the proposed algorithm achieves a very large complexity control range (as low as 10%) for the HEVC encoder while maintaining good rate-distortion performance. For the lowdelayP condition, compared with the direct resource allocation method and the state-of-the-art method, an average gain of 0.63 and 0.17 dB in BDPSNR is observed for 18 sequences when the target complexity is around 40%.

Salicylimine-Based Colorimetric and Fluorescent Chemosensor for Selective Detection of Cyanide in Aqueous Buffer

Energy Technology Data Exchange (ETDEWEB)

Noh, Jin Young; Hwang, In Hong; Kim, Hyun; Song, Eun Joo; Kim, Kyung Beom; Kim, Cheal [Seoul National Univ., Seoul (Korea, Republic of)

2013-07-15

A simple colorimetric and fluorescent anion sensor 1 based on salicylimine showed a high selectivity and sensitivity for detection of cyanide in aqueous solution. The receptor 1 showed high selectivity toward CN{sup -} ions in a 1:1 stoichiometric manner, which induces a fast color change from colorless to orange and a dramatic enhancement in fluorescence intensity selectively for cyanide anions over other anions. Such selectivity resulted from the nucleophilic addition of CN{sup -} to the carbon atom of an electron-deficient imine group. The sensitivity of the fluorescence-based assay (0.06 μM) is below the 1.9 μM suggested by the World Health Organization (WHO) as the maximum allowable cyanide concentration in drinking water, capable of being a practical system for the monitoring of CN. concentrations in aqueous samples.

Discovery of Highly Selective and Nanomolar Carbamate-Based Butyrylcholinesterase Inhibitors by Rational Investigation into Their Inhibition Mode.

Science.gov (United States)

Sawatzky, Edgar; Wehle, Sarah; Kling, Beata; Wendrich, Jan; Bringmann, Gerhard; Sotriffer, Christoph A; Heilmann, Jörg; Decker, Michael

2016-03-10

Butyrylcholinesterase (BChE) is a promising target for the treatment of later stage cognitive decline in Alzheimer's disease. A set of pseudo-irreversible BChE inhibitors with high selectivity over hAChE was synthesized based on carbamates attached to tetrahydroquinazoline scaffolds with the 2-thiophenyl compound 2p as the most potent inhibitor of eqBChE (KC = 14.3 nM) and also of hBChE (KC = 19.7 nM). The inhibitors transfer the carbamate moiety onto the active site under release of the phenolic tetrahydroquinazoline scaffolds that themselves act as neuroprotectants. By combination of kinetic data with molecular docking studies, a plausible binding model was probed describing how the tetrahydroquinazoline scaffold guides the carbamate into a close position to the active site. The model explains the influence of the carrier scaffold onto the affinity of an inhibitor just before carbamate transfer. This strategy can be used to utilize the binding mode of other carbamate-based inhibitors.

A Primer on High-Throughput Computing for Genomic Selection

Directory of Open Access Journals (Sweden)

Xiao-Lin eWu

2011-02-01

Full Text Available High-throughput computing (HTC uses computer clusters to solve advanced computational problems, with the goal of accomplishing high throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general purpose computation on a graphics processing unit (GPU provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin – Madison, which can be leveraged for genomic selection, in terms of central processing unit (CPU capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of

Highly selective direct determination of chlorate ions by using a newly developed potentiometric electrode based on modified smectite.

Science.gov (United States)

Topcu, Cihan

2016-12-01

A novel polyvinyl chloride membrane chlorate (ClO 3 - ) selective electrode based on modified smectite was developed for the direct determination of chlorate ions and the potentiometric performance characteristics of its were examined. The best selectivity and sensitivity for chlorate ions were obtained for the electrode membrane containing ionophore/polyvinylchloride/o-nitrophenyloctylether in composition of 12/28/60 (w/w%). The proposed electrode showed a Nernstian response toward chlorate ions at pH=7 in the concentration range of 1×10 -7 -1×10 -1 M and the limit of detection was calculated as 9×10 -8 M from the constructed response plot. The linear slope of the electrode was -61±1mVdecade -1 for chlorate activity in the mentioned linear working range. The selectivity coefficients were calculated according to both the matched potential method and the separate solution method. The calculated selectivity coefficients showed that the electrode performed excellent selectivity for chlorate ions. The potentiometric response of electrode toward chlorate ions was found to be highly reproducible. The electrode potential was stable between pH=4-10 and it had a dynamic response time of <5s. The potentiometric behavior of the electrode in partial non-aqueous medium was also investigated and the obtained results (up to 5% (v/v) alcohol) were satisfactory. The proposed electrode was used during 15 weeks without any significant change in its potential response. Additionally, the electrode was very useful in water analysis studies such as dam water, river water, tap water, and swimming pool water where the direct determination of chlorate ions was required. Copyright © 2016 Elsevier B.V. All rights reserved.

An opinion formation based binary optimization approach for feature selection

Science.gov (United States)

Hamedmoghadam, Homayoun; Jalili, Mahdi; Yu, Xinghuo

2018-02-01

This paper proposed a novel optimization method based on opinion formation in complex network systems. The proposed optimization technique mimics human-human interaction mechanism based on a mathematical model derived from social sciences. Our method encodes a subset of selected features to the opinion of an artificial agent and simulates the opinion formation process among a population of agents to solve the feature selection problem. The agents interact using an underlying interaction network structure and get into consensus in their opinions, while finding better solutions to the problem. A number of mechanisms are employed to avoid getting trapped in local minima. We compare the performance of the proposed method with a number of classical population-based optimization methods and a state-of-the-art opinion formation based method. Our experiments on a number of high dimensional datasets reveal outperformance of the proposed algorithm over others.

A new simple phthalimide-based fluorescent probe for highly selective cysteine and bioimaging for living cells

Science.gov (United States)

Shen, Youming; Zhang, Xiangyang; Zhang, Youyu; Zhang, Chunxiang; Jin, Junling; Li, Haitao

2017-10-01

A new turn-on phthalimide fluorescent probe has designed and synthesized for sensing cysteine (Cys) based on excited state intramolecular proton transfer (ESIPT) process. It is consisted of a 3-hydroxyphthalimide derivative moiety as the fluorophore and an acrylic ester group as a recognition receptor. The acrylic ester acts as an ESIPT blocking agent. Upon addition of cystein, intermolecular nucleophilic attack of cysteine on acrylic ester releases the fluorescent 3-hydroxyphthalimide derivative, thereby enabling the ESIPT process and leading to enhancement of fluorescence. The probe displays high sensitivity, excellent selectivity and with large Stokes shift toward cysteine. The linear interval range of the fluorescence titration ranged from 0 to 1.0 × 10- 5 M and detection limit is low (6 × 10- 8 M). In addition, the probe could be used for bio-imaging in living cells.

Design of highly selective ethanol dehydration nanocatalysts for ethylene production.

Science.gov (United States)

Austin, Natalie; Kostetskyy, Pavlo; Mpourmpakis, Giannis

2018-02-22

Rational design of catalysts for selective conversion of alcohols to olefins is key since product selectivity remains an issue due to competing etherification reactions. Using first principles calculations and chemical rules, we designed novel metal-oxide-protected metal nanoclusters (M 13 X 4 O 12 , with M = Cu, Ag, and Au and X = Al, Ga, and In) exhibiting strong Lewis acid sites on their surface, active for the selective formation of olefins from alcohols. These symmetrical nanocatalysts, due to their curvature, show unfavorable etherification chemistries, while favoring the olefin production. Furthermore, we determined that water removal and regeneration of the nanocatalysts is more feasible compared to the equivalent strong acid sites on solid acids used for alcohol dehydration. Our results demonstrate an exceptional stability of these new nanostructures with the most energetically favorable being Cu-based. Thus, the high selectivity and stability of these in-silico-predicted novel nanoclusters (e.g. Cu 13 Al 4 O 12 ) make them attractive catalysts for the selective dehydration of alcohols to olefins.

Phenylmercuric hydroxide. A highly selective reagent for the hydration of nonconjugated terminal alkynes

International Nuclear Information System (INIS)

Janout, V.; Regen, S.L.

1982-01-01

This article describes an unusual and highly selective method for hydrating nonconjugated terminal alkynes based on the use of phenylmercuric hydroxide as a reagent. Unlike classical mercury catalyzed procedures, sigma-bonded mercury acetylides are formed initially as stable intermediates and subsequently reacted with water under neutral pH to form the corresponding methyl ketone. Isolated yields which have been obtained by using this approach lie in the range of 49-65%. The high selectivity toward nonconjugated terminal alkynes which characterizes the procedure described herein should make it a useful supplement to existing hydration methods

Content-based image retrieval: Color-selection exploited

NARCIS (Netherlands)

Broek, E.L. van den; Vuurpijl, L.G.; Kisters, P. M. F.; Schmid, J.C.M. von; Moens, M.F.; Busser, R. de; Hiemstra, D.; Kraaij, W.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

Content-Based Image Retrieval: Color-selection exploited

NARCIS (Netherlands)

Moens, Marie-Francine; van den Broek, Egon; Vuurpijl, L.G.; de Brusser, Rik; Kisters, P.M.F.; Hiemstra, Djoerd; Kraaij, Wessel; von Schmid, J.C.M.

2002-01-01

This research presents a new color selection interface that facilitates query-by-color in Content-Based Image Retrieval (CBIR). Existing CBIR color selection interfaces, are being judged as non-intuitive and difficult to use. Our interface copes with these problems of usability. It is based on 11

Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

KAUST Repository

Abbas, Ahmed; Kong, Xin-Bing; Liu, Zhi; Jing, Bing-Yi; Gao, Xin

2013-01-01

A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into p-values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013

Automatic Peak Selection by a Benjamini-Hochberg-Based Algorithm

KAUST Repository

Abbas, Ahmed

2013-01-07

A common issue in bioinformatics is that computational methods often generate a large number of predictions sorted according to certain confidence scores. A key problem is then determining how many predictions must be selected to include most of the true predictions while maintaining reasonably high precision. In nuclear magnetic resonance (NMR)-based protein structure determination, for instance, computational peak picking methods are becoming more and more common, although expert-knowledge remains the method of choice to determine how many peaks among thousands of candidate peaks should be taken into consideration to capture the true peaks. Here, we propose a Benjamini-Hochberg (B-H)-based approach that automatically selects the number of peaks. We formulate the peak selection problem as a multiple testing problem. Given a candidate peak list sorted by either volumes or intensities, we first convert the peaks into p-values and then apply the B-H-based algorithm to automatically select the number of peaks. The proposed approach is tested on the state-of-the-art peak picking methods, including WaVPeak [1] and PICKY [2]. Compared with the traditional fixed number-based approach, our approach returns significantly more true peaks. For instance, by combining WaVPeak or PICKY with the proposed method, the missing peak rates are on average reduced by 20% and 26%, respectively, in a benchmark set of 32 spectra extracted from eight proteins. The consensus of the B-H-selected peaks from both WaVPeak and PICKY achieves 88% recall and 83% precision, which significantly outperforms each individual method and the consensus method without using the B-H algorithm. The proposed method can be used as a standard procedure for any peak picking method and straightforwardly applied to some other prediction selection problems in bioinformatics. The source code, documentation and example data of the proposed method is available at http://sfb.kaust.edu.sa/pages/software.aspx. © 2013

Two-stage atlas subset selection in multi-atlas based image segmentation

Energy Technology Data Exchange (ETDEWEB)

Zhao, Tingting, E-mail: tingtingzhao@mednet.ucla.edu; Ruan, Dan, E-mail: druan@mednet.ucla.edu [The Department of Radiation Oncology, University of California, Los Angeles, California 90095 (United States)

2015-06-15

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

Two-stage atlas subset selection in multi-atlas based image segmentation.

Science.gov (United States)

Zhao, Tingting; Ruan, Dan

2015-06-01

Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. The authors have developed a novel two-stage atlas

Two-stage atlas subset selection in multi-atlas based image segmentation

International Nuclear Information System (INIS)

Zhao, Tingting; Ruan, Dan

2015-01-01

Purpose: Fast growing access to large databases and cloud stored data presents a unique opportunity for multi-atlas based image segmentation and also presents challenges in heterogeneous atlas quality and computation burden. This work aims to develop a novel two-stage method tailored to the special needs in the face of large atlas collection with varied quality, so that high-accuracy segmentation can be achieved with low computational cost. Methods: An atlas subset selection scheme is proposed to substitute a significant portion of the computationally expensive full-fledged registration in the conventional scheme with a low-cost alternative. More specifically, the authors introduce a two-stage atlas subset selection method. In the first stage, an augmented subset is obtained based on a low-cost registration configuration and a preliminary relevance metric; in the second stage, the subset is further narrowed down to a fusion set of desired size, based on full-fledged registration and a refined relevance metric. An inference model is developed to characterize the relationship between the preliminary and refined relevance metrics, and a proper augmented subset size is derived to ensure that the desired atlases survive the preliminary selection with high probability. Results: The performance of the proposed scheme has been assessed with cross validation based on two clinical datasets consisting of manually segmented prostate and brain magnetic resonance images, respectively. The proposed scheme demonstrates comparable end-to-end segmentation performance as the conventional single-stage selection method, but with significant computation reduction. Compared with the alternative computation reduction method, their scheme improves the mean and medium Dice similarity coefficient value from (0.74, 0.78) to (0.83, 0.85) and from (0.82, 0.84) to (0.95, 0.95) for prostate and corpus callosum segmentation, respectively, with statistical significance. Conclusions: The authors

A High-throughput Selection for Cellulase Catalysts Using Chemical Complementation

Science.gov (United States)

Peralta-Yahya, Pamela; Carter, Brian T.; Lin, Hening; Tao, Haiyan; Cornish, Virginia W.

2010-01-01

Efficient enzymatic hydrolysis of lignocellulosic material remains one of the major bottlenecks to cost-effective conversion of biomass to ethanol. Improvement of glycosylhydrolases however is limited by existing medium-throughput screening technologies. Here, we report the first high-throughput selection for cellulase catalysts. This selection was developed by adapting chemical complementation to provide a growth assay for bond cleavage reactions. First, a URA3 counter selection was adapted to link chemical dimerizer activated gene transcription to cell death. Next, the URA3 counter selection was shown to detect cellulase activity based on cleavage of a tetrasaccharide chemical dimerizer substrate and decrease in expression of the toxic URA3 reporter. Finally, the utility of the cellulase selection was assessed by isolating cellulases with improved activity from a cellulase library created by family DNA shuffling. This application provides further evidence that chemical complementation can be readily adapted to detect different enzymatic activities for important chemical transformations for which no natural selection exists. Due to the large number of enzyme variants selections can test compared to existing medium-throughput screens for cellulases, this assay has the potential to impact the discovery of improved cellulases and other glycosylhydrolases for biomass conversion from libraries of cellulases created by mutagenesis or obtained from natural biodiversity. PMID:19053460

Comparative studies of praseodymium(III) selective sensors based on newly synthesized Schiff's bases

International Nuclear Information System (INIS)

Gupta, Vinod K.; Goyal, Rajendra N.; Pal, Manoj K.; Sharma, Ram A.

2009-01-01

Praseodymium ion selective polyvinyl chloride (PVC) membrane sensors, based on two new Schiff's bases 1,3-diphenylpropane-1,3-diylidenebis(azan-1-ylidene)diphenol (M 1 ) and N,N'-bis(pyridoxylideneiminato) ethylene (M 2 ) have been developed and studied. The sensor having membrane composition of PVC: o-NPOE: ionophore (M 1 ): NaTPB (w/w; mg) of 150: 300: 8: 5 showed best performances in comparison to M 2 based membranes. The sensor based on (M 1 ) exhibits the working concentration range 1.0 x 10 -8 to 1.0 x 10 -2 M with a detection limit of 5.0 x 10 -9 M and a Nernstian slope 20.0 ± 0.3 mV decade -1 of activity. It exhibited a quick response time as <8 s and its potential responses were pH independent across the range of 3.5-8.5.The influence of the membrane composition and possible interfering ions have also been investigated on the response properties of the electrode. The sensor has been found to work satisfactorily in partially non-aqueous media up to 15% (v/v) content of methanol, ethanol or acetonitrile and could be used for a period of 3 months. The selectivity coefficients determined by using fixed interference method (FIM) indicate high selectivity for praseodymium(III) ions over wide variety of other cations. To asses its analytical applicability the prepared sensor was successfully applied for determination of praseodymium(III) in spiked water samples.

A primer on high-throughput computing for genomic selection.

Science.gov (United States)

Wu, Xiao-Lin; Beissinger, Timothy M; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J M; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin-Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

Comparison of core-shell and totally porous ultra high performance liquid chromatographic stationary phases based on their selectivity towards alfuzosin compounds.

Science.gov (United States)

Szulfer, Jarosław; Plenis, Alina; Bączek, Tomasz

2014-06-13

This paper focuses on the application of a column classification system based on the Katholieke Universiteit Leuven for the characterization of physicochemical properties of core-shell and ultra-high performance liquid chromatographic stationary phases, followed by the verification of the reliability of the obtained column classification in pharmaceutical practice. In the study, 7 stationary phases produced in core-shell technology and 18 ultra-high performance liquid chromatographic columns were chromatographically tested, and ranking lists were built on the FKUL-values calculated against two selected reference columns. In the column performance test, an analysis of alfuzosin in the presence of related substances was carried out using the brands of the stationary phases with the highest ranking positions. Next, a system suitability test as described by the European Pharmacopoeia monograph was performed. Moreover, a study was also performed to achieve a purposeful shortening of the analysis time of the compounds of interest using the selected stationary phases. Finally, it was checked whether methods using core-shell and ultra-high performance liquid chromatographic columns can be an interesting alternative to the high-performance liquid chromatographic method for the analysis of alfuzosin in pharmaceutical practice. Copyright © 2014 Elsevier B.V. All rights reserved.

Tracking and flavour tagging selection in the ATLAS High Level Trigger

CERN Document Server

Calvetti, Milene; The ATLAS collaboration

2017-01-01

In high-energy physics experiments, track based selection in the online environment is crucial for the detection of physics processes of interest for further study. This is of particular importance at the Large Hadron Collider (LHC), where the increasingly harsh collision environment is challenging participating experiments to improve the performance of their online selection. Principle among these challenges is the increasing number of interactions per bunch crossing, known as pileup. In the ATLAS experiment the challenge has been addressed with multiple strategies. Firstly, individual trigger groups focusing on specific physics objects have implemented novel algorithms which make use of the detailed tracking and vertexing performed within the trigger to improve rejection without losing efficiency. Secondly, since 2015 all trigger areas have also benefited from a new high performance inner detector software tracking system implemented in the High Level Trigger. Finally, performance will be further enhanced i...

Highly sensitive and selective room-temperature NO_2 gas sensor based on bilayer transferred chemical vapor deposited graphene

International Nuclear Information System (INIS)

Seekaew, Yotsarayuth; Phokharatkul, Ditsayut; Wisitsoraat, Anurat; Wongchoosuk, Chatchawal

2017-01-01

Highlights: • Simple and low-cost fabrication of bilayer graphene gas sensor was presented. • Layer effects of graphene on NO_2 gas-sensing properties were investigated. • Bilayer graphene sensor exhibited a high linear NO_2 sensitivity of 1.409 ppm"−"1. • The NO_2-sensing mechanisms based on band diagram were highlighted. - Abstract: This work presents a highly sensitive room-temperature gas sensor based on bilayer graphene fabricated by an interfacial transfer of chemical vapor deposited graphene onto nickel interdigitated electrodes. Scanning electron microscopic and Raman spectroscopic characterizations confirm the presence of graphene on interdigitated nickel electrodes with varying numbers of graphene layers. The NO_2 detection performances of bilayer graphene gas sensor have been investigated in comparison with those of monolayer and multilayer graphene gas sensors at room temperature. From results, the bilayer graphene gas sensor exhibits higher response, sensitivity and selectivity to NO_2 than monolayer and multilayer graphene. The sensitivity of bilayer graphene gas sensor is 1.409 ppm"−"1 towards NO_2 over a concentration range of 1–25 ppm, which is more than twice higher than that of monolayer graphene. The NO_2-sensing mechanism of graphene sensing film has been explained based on the direct charge transfer process due to the adsorption of NO_2 molecules.

Reliable selection of earthquake ground motions for performance-based design

DEFF Research Database (Denmark)

Katsanos, Evangelos; Sextos, A.G.

2016-01-01

A decision support process is presented to accommodate selecting and scaling of earthquake motions as required for the time domain analysis of structures. Prequalified code-compatible suites of seismic motions are provided through a multi-criterion approach to satisfy prescribed reduced variability...... of the method, by being subjected to numerous suites of motions that were highly ranked according to both the proposed approach (δsv-sc) and the conventional index (δconv), already used by most existing code-based earthquake records selection and scaling procedures. The findings reveal the superiority...

Rhodium Nanoparticle-mesoporous Silicon Nanowire Nanohybrids for Hydrogen Peroxide Detection with High Selectivity

Science.gov (United States)

Song, Zhiqian; Chang, Hucheng; Zhu, Weiqin; Xu, Chenlong; Feng, Xinjian

2015-01-01

Developing nanostructured electrocatalysts, with low overpotential, high selectivity and activity has fundamental and technical importance in many fields. We report here rhodium nanoparticle and mesoporous silicon nanowire (RhNP@mSiNW) hybrids for hydrogen peroxide (H2O2) detection with high electrocatalytic activity and selectivity. By employing electrodes that loaded with RhNP@mSiNW nanohybrids, interference caused from both many electroactive substances and dissolved oxygen were eliminated by electrochemical assaying at an optimal potential of +75 mV. Furthermore, the electrodes exhibited a high detection sensitivity of 0.53 μA/mM and fast response (< 5 s). This high-performance nanohybrid electrocatalyst has great potential for future practical application in various oxidase-base biosensors. PMID:25588953

PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

Directory of Open Access Journals (Sweden)

Renata Bujak

2016-07-01

Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

Supplier selection an MCDA-based approach

CERN Document Server

Mukherjee, Krishnendu

2017-01-01

The purpose of this book is to present a comprehensive review of the latest research and development trends at the international level for modeling and optimization of the supplier selection process for different industrial sectors. It is targeted to serve two audiences: the MBA and PhD student interested in procurement, and the practitioner who wishes to gain a deeper understanding of procurement analysis with multi-criteria based decision tools to avoid upstream risks to get better supply chain visibility. The book is expected to serve as a ready reference for supplier selection criteria and various multi-criteria based supplier’s evaluation methods for forward, reverse and mass customized supply chain. This book encompasses several criteria, methods for supplier selection in a systematic way based on extensive literature review from 1998 to 2012. It provides several case studies and some useful links which can serve as a starting point for interested researchers. In the appendix several computer code wri...

A colorimetric nitrite detection system with excellent selectivity and high sensitivity based on Ag@Au nanoparticles.

Science.gov (United States)

Li, Tianhua; Li, Yonglong; Zhang, Yujie; Dong, Chen; Shen, Zheyu; Wu, Aiguo

2015-02-21

Excessive uptake of NO2(-) is detrimental to human health, but the currently available methods used to sensitively detect this ion in the environment are cumbersome and expensive. In this study, we developed an improved NO2(-) detection system based on a redox etching strategy of CTAB-stabilized Ag-Au core-shell nanoparticles (Ag@AuNPs). The detection mechanism was verified by UV-Vis spectroscopy, TEM and XPS. The detection system produces a color change from purple to colorless in response to an increase of NO2(-) concentration. The selectivity of detection of NO2(-), both with the unaided eye and by measurement of UV-Vis spectra, is excellent in relation to other ions, including Cu(2+), Co(2+), Ni(2+), Cr(3+), Al(3+), Pb(2+), Cd(2+), Ca(2+), Ba(2+), Zn(2+), Mn(2+), Mg(2+), Fe(3+), Hg(2+), Ag(+), K(+), F(-), PO4(3-), C2O4(2-), SO3(2-), CO3(2-), SO4(2-), NO3(-) and CH3-COO(-) (Ac(-)). The limit of detection (LOD) for NO2(-) is 1.0 μM by eye and 0.1 μM by UV-Vis spectroscopy. The LOD by eye is lower than the lowest previously reported value (4.0 μM). There is a good linear relationship between A/A0 and the concentration of NO2(-) from 1.0 to 20.0 μM NO2(-), which permits a quantitative assay. The applicability of our detection system was also verified by analysis of NO2(-) in tap water and lake water. The results demonstrate that our Ag@AuNP-based detection system can be used for the rapid colorimetric detection of NO2(-) in complex environmental samples, with excellent selectivity and high sensitivity.

FiGS: a filter-based gene selection workbench for microarray data

Directory of Open Access Journals (Sweden)

Yun Taegyun

2010-01-01

Full Text Available Abstract Background The selection of genes that discriminate disease classes from microarray data is widely used for the identification of diagnostic biomarkers. Although various gene selection methods are currently available and some of them have shown excellent performance, no single method can retain the best performance for all types of microarray datasets. It is desirable to use a comparative approach to find the best gene selection result after rigorous test of different methodological strategies for a given microarray dataset. Results FiGS is a web-based workbench that automatically compares various gene selection procedures and provides the optimal gene selection result for an input microarray dataset. FiGS builds up diverse gene selection procedures by aligning different feature selection techniques and classifiers. In addition to the highly reputed techniques, FiGS diversifies the gene selection procedures by incorporating gene clustering options in the feature selection step and different data pre-processing options in classifier training step. All candidate gene selection procedures are evaluated by the .632+ bootstrap errors and listed with their classification accuracies and selected gene sets. FiGS runs on parallelized computing nodes that capacitate heavy computations. FiGS is freely accessible at http://gexp.kaist.ac.kr/figs. Conclusion FiGS is an web-based application that automates an extensive search for the optimized gene selection analysis for a microarray dataset in a parallel computing environment. FiGS will provide both an efficient and comprehensive means of acquiring optimal gene sets that discriminate disease states from microarray datasets.

New competitive dendrimer-based and highly selective immunosensor for determination of atrazine in environmental, feed and food samples: the importance of antibody selectivity for discrimination among related triazinic metabolites.

Science.gov (United States)

Giannetto, Marco; Umiltà, Eleonora; Careri, Maria

2014-01-02

A new voltammetric competitive immunosensor selective for atrazine, based on the immobilization of a conjugate atrazine-bovine serum albumine on a nanostructured gold substrate previously functionalized with poliamidoaminic dendrimers, was realized, characterized, and validated in different real samples of environmental and food concern. Response of the sensor was reliable, highly selective and suitable for the detection and quantification of atrazine at trace levels in complex matrices such as territorial waters, corn-cultivated soils, corn-containing poultry and bovine feeds and corn flakes for human use. Selectivity studies were focused on desethylatrazine, the principal metabolite generated by long-term microbiological degradation of atrazine, terbutylazine-2-hydroxy and simazine as potential interferents. The response of the developed immunosensor for atrazine was explored over the 10(-2)-10(3) ng mL(-1) range. Good sensitivity was proved, as limit of detection and limit of quantitation of 1.2 and 5 ng mL(-1), respectively, were estimated for atrazine. RSD values <5% over the entire explored range attested a good precision of the device. Copyright © 2013 Elsevier B.V. All rights reserved.

Microalgal process-monitoring based on high-selectivity spectroscopy tools: status and future perspectives

DEFF Research Database (Denmark)

Podevin, Michael Paul Ambrose; Fotidis, Ioannis; Angelidaki, Irini

2018-01-01

microalgae production towards process automation through multivariate process control (MVPC) and software sensors trained on “big data”. The paper will also include a comprehensive overview of off-line implementations of vibrational spectroscopy in microalgal research as it pertains to spectral...... contribution of this review is to present current and prospective advances of on-line and in-line process analytical technology (PAT), with high-selectivity – the capability of monitoring several analytes simultaneously – in the interest of improving product quality, productivity, and process automation...... interpretation and process automation to aid and motivate development....

Improving Classification of Protein Interaction Articles Using Context Similarity-Based Feature Selection.

Science.gov (United States)

Chen, Yifei; Sun, Yuxing; Han, Bing-Qing

2015-01-01

Protein interaction article classification is a text classification task in the biological domain to determine which articles describe protein-protein interactions. Since the feature space in text classification is high-dimensional, feature selection is widely used for reducing the dimensionality of features to speed up computation without sacrificing classification performance. Many existing feature selection methods are based on the statistical measure of document frequency and term frequency. One potential drawback of these methods is that they treat features separately. Hence, first we design a similarity measure between the context information to take word cooccurrences and phrase chunks around the features into account. Then we introduce the similarity of context information to the importance measure of the features to substitute the document and term frequency. Hence we propose new context similarity-based feature selection methods. Their performance is evaluated on two protein interaction article collections and compared against the frequency-based methods. The experimental results reveal that the context similarity-based methods perform better in terms of the F1 measure and the dimension reduction rate. Benefiting from the context information surrounding the features, the proposed methods can select distinctive features effectively for protein interaction article classification.

Highly selective and sensitive macrocycle-based dinuclear foldamer for fluorometric and colorimetric sensing of citrate in water.

Science.gov (United States)

Rhaman, Md Mhahabubur; Hasan, Mohammad H; Alamgir, Azmain; Xu, Lihua; Powell, Douglas R; Wong, Bryan M; Tandon, Ritesh; Hossain, Md Alamgir

2018-01-10

The selective detection of citrate anions is essential for various biological functions in living systems. A quantitative assessment of citrate is required for the diagnosis of various diseases in the human body; however, it is extremely challenging to develop efficient fluorescence and color-detecting molecular probes for sensing citrate in water. Herein, we report a macrocycle-based dinuclear foldamer (1) assembled with eosin Y (EY) that has been studied for anion binding by fluorescence and colorimetric techniques in water at neutral pH. Results from the fluorescence titrations reveal that the 1·EY ensemble strongly binds citrate anions, showing remarkable selectivity over a wide range of inorganic and carboxylate anions. The addition of citrate anions to the 1·EY adduct led to a large fluorescence enhancement, displaying a detectable color change under both visible and UV light in water up to 2 μmol. The biocompatibility of 1·EY as an intracellular carrier in a biological system was evaluated on primary human foreskin fibroblast (HF) cells, showing an excellent cell viability. The strong binding properties of the ensemble allow it to be used as a highly sensitive, detective probe for biologically relevant citrate anions in various applications.

Ceramic-supported thin PVA pervaporation membranes combining high flux and high selectivity : contradicting the flux-selectivity paradigm

NARCIS (Netherlands)

Peters, T.A.; Poeth, C.H.S.; Benes, N.E.; Buijs, H.C.W.M.; Vercauteren, F.F.; Keurentjes, J.T.F.

2006-01-01

Thin, high-flux and highly selective cross-linked poly(vinyl)alcohol waterselective layers have been prepared on top of hollow fibre ceramic supports. The supports consist of an alpha-Al2O3 hollow fibre substrate and an intermediate gamma-Al2O3 layer, which provides a sufficiently smooth surface for

Bacterial clonal diagnostics as a tool for evidence-based empiric antibiotic selection.

Science.gov (United States)

Tchesnokova, Veronika; Avagyan, Hovhannes; Rechkina, Elena; Chan, Diana; Muradova, Mariya; Haile, Helen Ghirmai; Radey, Matthew; Weissman, Scott; Riddell, Kim; Scholes, Delia; Johnson, James R; Sokurenko, Evgeni V

2017-01-01

Despite the known clonal distribution of antibiotic resistance in many bacteria, empiric (pre-culture) antibiotic selection still relies heavily on species-level cumulative antibiograms, resulting in overuse of broad-spectrum agents and excessive antibiotic/pathogen mismatch. Urinary tract infections (UTIs), which account for a large share of antibiotic use, are caused predominantly by Escherichia coli, a highly clonal pathogen. In an observational clinical cohort study of urgent care patients with suspected UTI, we assessed the potential for E. coli clonal-level antibiograms to improve empiric antibiotic selection. A novel PCR-based clonotyping assay was applied to fresh urine samples to rapidly detect E. coli and the urine strain's clonotype. Based on a database of clonotype-specific antibiograms, the acceptability of various antibiotics for empiric therapy was inferred using a 20%, 10%, and 30% allowed resistance threshold. The test's performance characteristics and possible effects on prescribing were assessed. The rapid test identified E. coli clonotypes directly in patients' urine within 25-35 minutes, with high specificity and sensitivity compared to culture. Antibiotic selection based on a clonotype-specific antibiogram could reduce the relative likelihood of antibiotic/pathogen mismatch by ≥ 60%. Compared to observed prescribing patterns, clonal diagnostics-guided antibiotic selection could safely double the use of trimethoprim/sulfamethoxazole and minimize fluoroquinolone use. In summary, a rapid clonotyping test showed promise for improving empiric antibiotic prescribing for E. coli UTI, including reversing preferential use of fluoroquinolones over trimethoprim/sulfamethoxazole. The clonal diagnostics approach merges epidemiologic surveillance, antimicrobial stewardship, and molecular diagnostics to bring evidence-based medicine directly to the point of care.

Toward Annealing-Stable Molybdenum-Oxide-Based Hole-Selective Contacts For Silicon Photovoltaics

KAUST Repository

Essig, Stephanie

2018-02-21

Molybdenum oxide (MoOX) combines a high work function with broadband optical transparency. Sandwiched between a hydrogenated intrinsic amorphous silicon passivation layer and a transparent conductive oxide, this material allows a highly efficient hole-selective front contact stack for crystalline silicon solar cells. However, hole extraction from the Si wafer and transport through this stack degrades upon annealing at 190 °C, which is needed to cure the screen-printed Ag metallization applied to typical Si solar cells. Here, we show that effusion of hydrogen from the adjacent layers is a likely cause for this degradation, highlighting the need for hydrogen-lean passivation layers when using such metal-oxide-based carrier-selective contacts. Pre-MoOX-deposition annealing of the passivating a-Si:H layer is shown to be a straightforward approach to manufacturing MoOX-based devices with high fill factors using screen-printed metallization cured at 190 °C.

Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis.

Science.gov (United States)

Pan, Yuchen; Ding, Shuai; Fan, Wenjuan; Li, Jing; Yang, Shanlin

2015-01-01

Cloud computing technology plays a very important role in many areas, such as in the construction and development of the smart city. Meanwhile, numerous cloud services appear on the cloud-based platform. Therefore how to how to select trustworthy cloud services remains a significant problem in such platforms, and extensively investigated owing to the ever-growing needs of users. However, trust relationship in social network has not been taken into account in existing methods of cloud service selection and recommendation. In this paper, we propose a cloud service selection model based on the trust-enhanced similarity. Firstly, the direct, indirect, and hybrid trust degrees are measured based on the interaction frequencies among users. Secondly, we estimate the overall similarity by combining the experience usability measured based on Jaccard's Coefficient and the numerical distance computed by Pearson Correlation Coefficient. Then through using the trust degree to modify the basic similarity, we obtain a trust-enhanced similarity. Finally, we utilize the trust-enhanced similarity to find similar trusted neighbors and predict the missing QoS values as the basis of cloud service selection and recommendation. The experimental results show that our approach is able to obtain optimal results via adjusting parameters and exhibits high effectiveness. The cloud services ranking by our model also have better QoS properties than other methods in the comparison experiments.

Innovation in values based public health nursing student selection: A qualitative evaluation of candidate and selection panel member perspectives.

Science.gov (United States)

McGraw, Caroline; Abbott, Stephen; Brook, Judy

2018-02-19

Values based recruitment emerges from the premise that a high degree of value congruence, or the extent to which an individual's values are similar to those of the health organization in which they work, leads to organizational effectiveness. The aim of this evaluation was to explore how candidates and selection panel members experienced and perceived innovative methods of values based public health nursing student selection. The evaluation was framed by a qualitative exploratory design involving semi-structured interviews and a group exercise. Data were thematically analyzed. Eight semi-structured interviews were conducted with selection panel members. Twenty-two successful candidates took part in a group exercise. The use of photo elicitation interviews and situational judgment questions in the context of selection to a university-run public health nursing educational program was explored. While candidates were ambivalent about the use of photo elicitation interviews, with some misunderstanding the task, selection panel members saw the benefits for improving candidate expression and reducing gaming and deception. Situational interview questions were endorsed by candidates and selection panel members due to their fidelity to real-life problems and the ability of panel members to discern value congruence from candidates' responses. Both techniques offered innovative solutions to candidate selection for entry to the public health nursing education program. © 2018 Wiley Periodicals, Inc.

Carbon Nanotube-Based Ion Selective Sensors for Wearable Applications.

Science.gov (United States)

Roy, Soumyendu; David-Pur, Moshe; Hanein, Yael

2017-10-11

Wearable electronics offer new opportunities in a wide range of applications, especially sweat analysis using skin sensors. A fundamental challenge in these applications is the formation of sensitive and stable electrodes. In this article we report the development of a wearable sensor based on carbon nanotube (CNT) electrode arrays for sweat sensing. Solid-state ion selective electrodes (ISEs), sensitive to Na + ions, were prepared by drop coating plasticized poly(vinyl chloride) (PVC) doped with ionophore and ion exchanger on CNT electrodes. The ion selective membrane (ISM) filled the intertubular spaces of the highly porous CNT film and formed an attachment that was stronger than that achieved with flat Au, Pt, or carbon electrodes. Concentration of the ISM solution used influenced the attachment to the CNT film, the ISM surface morphology, and the overall performance of the sensor. Sensitivity of 56 ± 3 mV/decade to Na + ions was achieved. Optimized solid-state reference electrodes (REs), suitable for wearable applications, were prepared by coating CNT electrodes with colloidal dispersion of Ag/AgCl, agarose hydrogel with 0.5 M NaCl, and a passivation layer of PVC doped with NaCl. The CNT-based REs had low sensitivity (-1.7 ± 1.2 mV/decade) toward the NaCl solution and high repeatability and were superior to bare Ag/AgCl, metals, carbon, and CNT films, reported previously as REs. CNT-based ISEs were calibrated against CNT-based REs, and the short-term stability of the system was tested. We demonstrate that CNT-based devices implemented on a flexible support are a very attractive platform for future wearable technology devices.

Peptide-Based Selective Inhibitors of Matrix Metalloproteinase-Mediated Activities

Directory of Open Access Journals (Sweden)

Margaret W. Ndinguri

2012-11-01

Full Text Available The matrix metalloproteinases (MMPs exhibit a broad array of activities, some catalytic and some non-catalytic in nature. An overall lack of selectivity has rendered small molecule, active site targeted MMP inhibitors problematic in execution. Inhibitors that favor few or individual members of the MMP family often take advantage of interactions outside the enzyme active site. We presently focus on peptide-based MMP inhibitors and probes that do not incorporate conventional Zn2+ binding groups. In some cases, these inhibitors and probes function by binding only secondary binding sites (exosites, while others bind both exosites and the active site. A myriad of MMP mediated-activities beyond selective catalysis can be inhibited by peptides, particularly cell adhesion, proliferation, motility, and invasion. Selective MMP binding peptides comprise highly customizable, unique imaging agents. Areas of needed improvement for MMP targeting peptides include binding affinity and stability.

Selecting a risk-based tool to aid in decision making

Energy Technology Data Exchange (ETDEWEB)

Bendure, A.O.

1995-03-01

Selecting a risk-based tool to aid in decision making is as much of a challenge as properly using the tool once it has been selected. Failure to consider customer and stakeholder requirements and the technical bases and differences in risk-based decision making tools will produce confounding and/or politically unacceptable results when the tool is used. Selecting a risk-based decisionmaking tool must therefore be undertaken with the same, if not greater, rigor than the use of the tool once it is selected. This paper presents a process for selecting a risk-based tool appropriate to a set of prioritization or resource allocation tasks, discusses the results of applying the process to four risk-based decision-making tools, and identifies the ``musts`` for successful selection and implementation of a risk-based tool to aid in decision making.

Linear feature selection in texture analysis - A PLS based method

DEFF Research Database (Denmark)

Marques, Joselene; Igel, Christian; Lillholm, Martin

2013-01-01

We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

Distance based control system for machine vision-based selective spraying

NARCIS (Netherlands)

Steward, B.L.; Tian, L.F.; Tang, L.

2002-01-01

For effective operation of a selective sprayer with real-time local weed sensing, herbicides must be delivered, accurately to weed targets in the field. With a machine vision-based selective spraying system, acquiring sequential images and switching nozzles on and off at the correct locations are

Holey graphene frameworks for highly selective post-combustion carbon capture

Science.gov (United States)

Chowdhury, Shamik; Balasubramanian, Rajasekhar

2016-02-01

Atmospheric CO2 concentrations continue to rise rapidly in response to increased combustion of fossil fuels, contributing to global climate change. In order to mitigate the effects of global warming, development of new materials for cost-effective and energy-efficient CO2 capture is critically important. Graphene-based porous materials are an emerging class of solid adsorbents for selectively removing CO2 from flue gases. Herein, we report a simple and scalable approach to produce three-dimensional holey graphene frameworks with tunable porosity and pore geometry, and demonstrate their application as high-performance CO2 adsorbents. These holey graphene macrostructures exhibit a significantly improved specific surface area and pore volume compared to their pristine counterparts, and can be effectively used in post-combustion CO2 adsorption systems because of their intrinsic hydrophobicity together with good gravimetric storage capacities, rapid removal capabilities, superior cycling stabilities, and moderate initial isosteric heats. In addition, an exceptionally high CO2 over N2 selectivity can be achieved under conditions relevant to capture from the dry exhaust gas stream of a coal burning power plant, suggesting the possibility of recovering highly pure CO2 for long-term sequestration and/or utilization for downstream applications.

Empirical tests of natural selection-based evolutionary accounts of ADHD: a systematic review.

Science.gov (United States)

Thagaard, Marthe S; Faraone, Stephen V; Sonuga-Barke, Edmund J; Østergaard, Søren D

2016-10-01

ADHD is a prevalent and highly heritable mental disorder associated with significant impairment, morbidity and increased rates of mortality. This combination of high prevalence and high morbidity/mortality seen in ADHD and other mental disorders presents a challenge to natural selection-based models of human evolution. Several hypotheses have been proposed in an attempt to resolve this apparent paradox. The aim of this study was to review the evidence for these hypotheses. We conducted a systematic review of the literature on empirical investigations of natural selection-based evolutionary accounts for ADHD in adherence with the PRISMA guideline. The PubMed, Embase, and PsycINFO databases were screened for relevant publications, by combining search terms covering evolution/selection with search terms covering ADHD. The search identified 790 records. Of these, 15 full-text articles were assessed for eligibility, and three were included in the review. Two of these reported on the evolution of the seven-repeat allele of the ADHD-associated dopamine receptor D4 gene, and one reported on the results of a simulation study of the effect of suggested ADHD-traits on group survival. The authors of the three studies interpreted their findings as favouring the notion that ADHD-traits may have been associated with increased fitness during human evolution. However, we argue that none of the three studies really tap into the core symptoms of ADHD, and that their conclusions therefore lack validity for the disorder. This review indicates that the natural selection-based accounts of ADHD have not been subjected to empirical test and therefore remain hypothetical.

Molecularly imprinted sol-gel nanofibers based solid phase microextraction coupled on-line with high performance liquid chromatography for selective determination of acesulfame.

Science.gov (United States)

Moein, Mohammad Mahdi; Javanbakht, Mehran; Karimi, Mohammad; Akbari-Adergani, Behrouz

2015-03-01

Sol-gel based molecularly imprinted polymer (MIP) nanofiber was successfully fabricated by electrospinning technique on the surface of a stainless steel bar. The manufactured tool was applied for on-line selective solid phase microextraction (SPME) and determination of acesulfame (ACF) as an artificial sweetener with high performance liquid chromatography (HPLC). The selective ability of method for the extraction of ACF was investigated in the presence of some selected sweeteners such as saccharine (SCH), aspartame (ASP) and caffeine (CAF). Electrospinning of MIP sol-gel solution on the stainless steel bar provided an unbreakable sorbent with high thermal, mechanical, and chemical stability. Moreover, application of the MIP-SPME tool revealed a unique approach for the selective microextraction of the analyte in beverage samples. In this work, 3-(triethoxysilyl)-propylamine (TMSPA) was chosen as a precursor due to its ability to imprint the analyte by hydrogen bonding, Van der Walls, and dipole-dipole interactions. Nylon 6 was also added as a backbone and support for the precursor in which sol could greatly growth during the sol-gel process and makes the solution electrospinable. Various effective parameters in the extraction efficiency of the MIP-SPME tool such as loading time, flow rate, desorption time, selectivity, and the sample volume were evaluated. The linearity for the ACF in beverage sample was in the range of 0.78-100.5 ng mL(-1). Limit of detection (LOD) and quantification (LOQ) were 0.23 and 0.78 ng mL(-1) respectively. The RSD values (n=5) were all below 3.5%at the 20 ng mL(-1) level. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel piperazine-bis(rhodamine-B)-based chemosensor for highly sensitive and selective naked-eye detection of Cu{sup 2+} and its application as an INHIBIT logic device

Energy Technology Data Exchange (ETDEWEB)

Sun, Zebin; Li, Haizhen; Guo, Dan; Liu, Yan; Tian, Zhang; Yan, Shiqiang, E-mail: yansq@lzu.edu.cn

2015-11-15

Abstact: We report the design and synthesis of a new piperazine-bis(rhodamine-B) (RB-P-RB)-based indicator for selective detection of Cu{sup 2+} ion. Optical sensing behavior toward various metal ions including alkali, alkaline earth and transition metal ions (Na{sup +}, K{sup +}, Ba{sup 2+}, Mg{sup 2+}, Ca{sup 2+}, Zn{sup 2+}, Cd{sup 2+}, Mn{sup 2+}, Co{sup 2+}, Ni{sup 2+}, Pb{sup 2+}, Cu{sup 2+}, Hg{sup 2+}, and Ag{sup +}) were investigated by UV–vis and fluorescence spectroscopy in ethassnol solution. The indicator showed highly selective and sensitive colorimetric and “turn-on” fluorescence enhancement responses toward Cu{sup 2+} ion owing to the ring-opening structure of the rhodamine spirolactam. The significant change from colorless to pink upon the addition of Cu{sup 2+} could make it a suitable “naked-eye” indicator for Cu{sup 2+}. Furthermore, a possible ring-opening mechanism (off-on) of the rhodamine spirolactam induced by Cu{sup 2+} binding is supported by Job plot, ESI-mass, FT-IR, and {sup 1}H NMR. More significantly, the probe displayed highly selective Cu{sup 2+}-amplified absorption in the presence of Cu{sup 2+} ions. Finally, using Cu{sup 2+} and EDTA as inputs and the fluorescence emission intensity as output, an INHIBIT logic gate can be constructed at the molecular level. - Highlights: • A novel piperazine-bis(rhodamine-B)-based sensor for selective detection of Cu{sup 2+} ion was synthesized via simple synthetic procedures. • The probe exhibited highly selective and sensitive colorimetric and “turn on” fluorescence enhancement responses to Cu{sup 2+}. • The probe can serve as a reversible and selective “naked eye” indicator for Cu{sup 2+} ions in ethanol solution. • The probe can be utilized to construct an INHIBIT logic gate at the molecular level. • The probe displays highly selective Cu{sup 2+}-amplified absorption in ethanol solution.

Bacterial clonal diagnostics as a tool for evidence-based empiric antibiotic selection.

Directory of Open Access Journals (Sweden)

Veronika Tchesnokova

Full Text Available Despite the known clonal distribution of antibiotic resistance in many bacteria, empiric (pre-culture antibiotic selection still relies heavily on species-level cumulative antibiograms, resulting in overuse of broad-spectrum agents and excessive antibiotic/pathogen mismatch. Urinary tract infections (UTIs, which account for a large share of antibiotic use, are caused predominantly by Escherichia coli, a highly clonal pathogen. In an observational clinical cohort study of urgent care patients with suspected UTI, we assessed the potential for E. coli clonal-level antibiograms to improve empiric antibiotic selection. A novel PCR-based clonotyping assay was applied to fresh urine samples to rapidly detect E. coli and the urine strain's clonotype. Based on a database of clonotype-specific antibiograms, the acceptability of various antibiotics for empiric therapy was inferred using a 20%, 10%, and 30% allowed resistance threshold. The test's performance characteristics and possible effects on prescribing were assessed. The rapid test identified E. coli clonotypes directly in patients' urine within 25-35 minutes, with high specificity and sensitivity compared to culture. Antibiotic selection based on a clonotype-specific antibiogram could reduce the relative likelihood of antibiotic/pathogen mismatch by ≥ 60%. Compared to observed prescribing patterns, clonal diagnostics-guided antibiotic selection could safely double the use of trimethoprim/sulfamethoxazole and minimize fluoroquinolone use. In summary, a rapid clonotyping test showed promise for improving empiric antibiotic prescribing for E. coli UTI, including reversing preferential use of fluoroquinolones over trimethoprim/sulfamethoxazole. The clonal diagnostics approach merges epidemiologic surveillance, antimicrobial stewardship, and molecular diagnostics to bring evidence-based medicine directly to the point of care.

Highly sensitive and selective room-temperature NO{sub 2} gas sensor based on bilayer transferred chemical vapor deposited graphene

Energy Technology Data Exchange (ETDEWEB)

Seekaew, Yotsarayuth [Department of Physics, Faculty of Science, Kasetsart University, Chatuchak, Bangkok 10900 (Thailand); Phokharatkul, Ditsayut; Wisitsoraat, Anurat [Nanoelectronics and MEMS Laboratory, National Electronics and Computer Technology Center, Klong Luang, Pathumthani 12120 (Thailand); Wongchoosuk, Chatchawal, E-mail: chatchawal.w@ku.ac.th [Department of Physics, Faculty of Science, Kasetsart University, Chatuchak, Bangkok 10900 (Thailand)

2017-05-15

Highlights: • Simple and low-cost fabrication of bilayer graphene gas sensor was presented. • Layer effects of graphene on NO{sub 2} gas-sensing properties were investigated. • Bilayer graphene sensor exhibited a high linear NO{sub 2} sensitivity of 1.409 ppm{sup −1}. • The NO{sub 2}-sensing mechanisms based on band diagram were highlighted. - Abstract: This work presents a highly sensitive room-temperature gas sensor based on bilayer graphene fabricated by an interfacial transfer of chemical vapor deposited graphene onto nickel interdigitated electrodes. Scanning electron microscopic and Raman spectroscopic characterizations confirm the presence of graphene on interdigitated nickel electrodes with varying numbers of graphene layers. The NO{sub 2} detection performances of bilayer graphene gas sensor have been investigated in comparison with those of monolayer and multilayer graphene gas sensors at room temperature. From results, the bilayer graphene gas sensor exhibits higher response, sensitivity and selectivity to NO{sub 2} than monolayer and multilayer graphene. The sensitivity of bilayer graphene gas sensor is 1.409 ppm{sup −1} towards NO{sub 2} over a concentration range of 1–25 ppm, which is more than twice higher than that of monolayer graphene. The NO{sub 2}-sensing mechanism of graphene sensing film has been explained based on the direct charge transfer process due to the adsorption of NO{sub 2} molecules.

A Dynamic and Adaptive Selection Radar Tracking Method Based on Information Entropy

Directory of Open Access Journals (Sweden)

Ge Jianjun

2017-12-01

Full Text Available Nowadays, the battlefield environment has become much more complex and variable. This paper presents a quantitative method and lower bound for the amount of target information acquired from multiple radar observations to adaptively and dynamically organize the detection of battlefield resources based on the principle of information entropy. Furthermore, for minimizing the given information entropy’s lower bound for target measurement at every moment, a method to dynamically and adaptively select radars with a high amount of information for target tracking is proposed. The simulation results indicate that the proposed method has higher tracking accuracy than that of tracking without adaptive radar selection based on entropy.

Highly sensitive and selective detection of Bis-phenol A based on hydroxyapatite decorated reduced graphene oxide nanocomposites

International Nuclear Information System (INIS)

Alam, Mohammad K.; Rahman, Mohammed M.; Elzwawy, Amir; Torati, Sri Ramulu; Islam, Mohammad S.; Todo, Mitsugu; Asiri, Abdullah M.; Kim, Dojin; Kim, CheolGi

2017-01-01

Highlights: •Simple chemical reduction method was used for preparation of reduced graphene oxide/hydroxyapatite (rGO/HAp) nanocomposites. •The rGO/HAp nanocomposites exhibited good biocompatibility with hMSCs. •Selective chemical sensor based on rGO/HAp nanocomposites was developed for detection of Bis-phenol A. •The fabricated rGO/HAp/Nafion/GCE sensor exhibited good detection limit of 60 pmol L −1 . -- Abstract: A facile and cost effective chemical reduction method is employed for the preparation of reduced graphene oxide/hydroxyapatite (rGO/HAp) nanocomposites. The transmission electron microscopy images revealed that the HAp flakes are well decorated on the surface of rGO. The morphological structure of the as-synthesized rGO/HAp nanocomposites was confirmed through X-ray diffraction, Fourier transform infrared spectroscopy and Raman spectroscopy, while the composition and thermal stability were analyzed by energy dispersive spectra and thermogravimetric analysis, respectively. Furthermore, the effect of rGO/HAp nanocomposites for the proliferation of Human Mesenchymal Stem Cell (hMSC) was performed to confirm the biocompatibility. A selective chemical sensor based on rGO/HAp modified glassy carbon electrode (GCE) for sensitive detection of Bis-phenol A (BPA) has been developed. Several important parameters controlling the performance of the BPA chemi-sensor were investigated and optimized at room conditions. The rGO/HAp/Nafion/GCE sensor offers a fast response and highly sensitive BPA detection. Under the optimal conditions, a linear range from 0.2 nmol L −1 to 2.0 mmol L −1 for the detection of BPA was observed with the detection limit of 60.0 pmol L −1 (signal-to-noise ratio, at an SNR of 3) and sensitivity of 18.98 × 10 4 μA.L/μmol.m 2 . Meanwhile, the fabricated chemi-sensor showed an excellent, specific and selective recognition to target BPA molecules among coexistence of other analytes in the buffer system. This novel effort initiated

A Selective Group Authentication Scheme for IoT-Based Medical Information System.

Science.gov (United States)

Park, YoHan; Park, YoungHo

2017-04-01

The technology of IoT combined with medical systems is expected to support advanced medical services. However, unsolved security problems, such as misuse of medical devices, illegal access to the medical server and so on, make IoT-based medical systems not be applied widely. In addition, users have a high burden of computation to access Things for the explosive growth of IoT devices. Because medical information is critical and important, but users have a restricted computing power, IoT-based medical systems are required to provide secure and efficient authentication for users. In this paper, we propose a selective group authentication scheme using Shamir's threshold technique. The property of selectivity gives the right of choice to users to form a group which consists of things users select and access. And users can get an access authority for those Things at a time. Thus, our scheme provides an efficient user authentication for multiple Things and conditional access authority for safe IoT-based medical information system. To the best of our knowledge, our proposed scheme is the first in which selectivity is combined with group authentication in IoT environments.

Highly Selective Polypyrrole MIP-Based Gravimetric and Electrochemical Sensors for Picomolar Detection of Glyphosate

Directory of Open Access Journals (Sweden)

Zouhour Mazouz

2017-11-01

Full Text Available There is a global debate and concern about the use of glyphosate (Gly as an herbicide. New toxicological studies will determine its use in the future under new strict conditions or its replacement by alternative synthetic or natural herbicides. In this context, we designed biomimetic polymer sensing layers for the selective molecular recognition of Gly. Towards this end, complementary surface acoustic wave (SAW and electrochemical sensors were functionalized with polypyrrole (PPy-imprinted polymer for the selective detection of Gly. Their corresponding limits of detection were on the order of 1 pM, which are among the lowest values ever reported in literature. The relevant dissociation constants between PPy and Gly were estimated at [Kd1 = (0.7 ± 0.3 pM and Kd2 = (1.6 ± 1.4 µM] and [Kd1 = (2.4 ± 0.9 pM and Kd2 = (0.3 ± 0.1 µM] for electrochemical and gravimetric measurements, respectively. Quantum chemical calculations permitted to estimate the interaction energy between Gly and PPy film: ΔE = −145 kJ/mol. Selectivity and competitivity tests were investigated with the most common pesticides. This work conclusively shows that gravimetric and electrochemical results indicate that both MIP-based sensors are perfectly able to detect and distinguish glyphosate without any ambiguity.

High efficiency GaN-based LEDs using plasma selective treatment of p-GaN surface

Energy Technology Data Exchange (ETDEWEB)

Lee, Young-Bae; Naoi, Yoshiki; Sakai, Shiro [Department of Electrical and Electronic Engineering, University of Tokushima, 2-1 Minami-josanjima, Tokushima 770-8506 (Japan); Takaki, Ryohei; Sato, Hisao [Nitride Semiconductor Co., Ltd., 115-7 Itayajima, Akinokami, Seto-cho, Naruto, Tokushima 771-0360 (Japan)

2003-11-01

We have studied a new method of increasing the extraction efficiency of a GaN-based light-emitting diode (LED) using a plasma surface treatment. In this method, prior to the evaporation of a semitransparent p-metal, the surface of a p-GaN located beneath a p-pad is selectively exposed to a nitrogen plasma in a reactive ion etching (RIE) chamber. The electrical characteristics of the plasma treated p-GaN remarkably changes its resistivity into semi-insulator without any parasitic damage. Since the LEDs with a new method have no light absorption in a p-pad region, a higher optical power can be extracted compared to a conventional LEDs without plasma selective treatment on the p-GaN surface. (copyright 2003 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

Personnel Selection Based on Fuzzy Methods

Directory of Open Access Journals (Sweden)

Lourdes Cañós

2011-03-01

Full Text Available The decisions of managers regarding the selection of staff strongly determine the success of the company. A correct choice of employees is a source of competitive advantage. We propose a fuzzy method for staff selection, based on competence management and the comparison with the valuation that the company considers the best in each competence (ideal candidate. Our method is based on the Hamming distance and a Matching Level Index. The algorithms, implemented in the software StaffDesigner, allow us to rank the candidates, even when the competences of the ideal candidate have been evaluated only in part. Our approach is applied in a numerical example.

Multi-atlas pancreas segmentation: Atlas selection based on vessel structure.

Science.gov (United States)

Karasawa, Ken'ichi; Oda, Masahiro; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Chu, Chengwen; Zheng, Guoyan; Rueckert, Daniel; Mori, Kensaku

2017-07-01

Automated organ segmentation from medical images is an indispensable component for clinical applications such as computer-aided diagnosis (CAD) and computer-assisted surgery (CAS). We utilize a multi-atlas segmentation scheme, which has recently been used in different approaches in the literature to achieve more accurate and robust segmentation of anatomical structures in computed tomography (CT) volume data. Among abdominal organs, the pancreas has large inter-patient variability in its position, size and shape. Moreover, the CT intensity of the pancreas closely resembles adjacent tissues, rendering its segmentation a challenging task. Due to this, conventional intensity-based atlas selection for pancreas segmentation often fails to select atlases that are similar in pancreas position and shape to those of the unlabeled target volume. In this paper, we propose a new atlas selection strategy based on vessel structure around the pancreatic tissue and demonstrate its application to a multi-atlas pancreas segmentation. Our method utilizes vessel structure around the pancreas to select atlases with high pancreatic resemblance to the unlabeled volume. Also, we investigate two types of applications of the vessel structure information to the atlas selection. Our segmentations were evaluated on 150 abdominal contrast-enhanced CT volumes. The experimental results showed that our approach can segment the pancreas with an average Jaccard index of 66.3% and an average Dice overlap coefficient of 78.5%. Copyright © 2017 Elsevier B.V. All rights reserved.

Differential evolution algorithm-based kernel parameter selection for Fukunaga-Koontz Transform subspaces construction

Science.gov (United States)

Binol, Hamidullah; Bal, Abdullah; Cukur, Huseyin

2015-10-01

The performance of the kernel based techniques depends on the selection of kernel parameters. That's why; suitable parameter selection is an important problem for many kernel based techniques. This article presents a novel technique to learn the kernel parameters in kernel Fukunaga-Koontz Transform based (KFKT) classifier. The proposed approach determines the appropriate values of kernel parameters through optimizing an objective function constructed based on discrimination ability of KFKT. For this purpose we have utilized differential evolution algorithm (DEA). The new technique overcomes some disadvantages such as high time consumption existing in the traditional cross-validation method, and it can be utilized in any type of data. The experiments for target detection applications on the hyperspectral images verify the effectiveness of the proposed method.

Cyclic cholecystokinin analogues with high selectivity for central receptors

International Nuclear Information System (INIS)

Charpentier, B.; Pelaprat, D.; Durieux, C.; Dor, A.; Roques, B.P.; Reibaud, M.; Blanchard, J.C.

1988-01-01

Taking as a model the N-terminal folding of the cholecystokinin tyrosine-sulfated octapeptide deduced from conformational studies, two cyclic cholecystokinin (CCK) analogues were synthesized by conventional peptide synthesis. The binding characteristics of these peptides were investigated on brain cortex membranes and pancreatic acini of guinea pig. Compounds I and II were competitive inhibitors of [ 3 H]Boc[Ahx 28,31 ]CCK-(27-33) binding to central CCK receptors and showed a high degree of selectivity for these binding sites. This high selectivity was associated with a high affinity for central CCK receptors. Similar affinities and selectivities were found when 125 I Bolton-Hunter-labeled CCK-8 was used as a ligand. Moreover, these compounds were only weakly active in the stimulation of amylase release from guinea pig pancreatic acini and were unable to induce contractions in the guinea pig ileum. The two cyclic CCK analogues, therefore, appear to be synthetic ligands exhibiting both high affinity and high selectivity for central CCK binding sites. These compounds could help clarify the respective role of central and peripheral receptors for various CCK-8-induced pharmacological effects

Improved selectivity towards NO₂ of phthalocyanine-based chemosensors by means of original indigo/nanocarbons hybrid material.

Science.gov (United States)

Brunet, J; Pauly, A; Dubois, M; Rodriguez-Mendez, M L; Ndiaye, A L; Varenne, C; Guérin, K

2014-09-01

A new and original gas sensor-system dedicated to the selective monitoring of nitrogen dioxide in air and in the presence of ozone, has been successfully achieved. Because of its high sensitivity and its partial selectivity towards oxidizing pollutants (nitrogen dioxide and ozone), copper phthalocyanine-based chemoresistors are relevant. The selectivity towards nitrogen dioxide results from the implementation of a high efficient and selective ozone filter upstream the sensing device. Thus, a powdered indigo/nanocarbons hybrid material has been developed and investigated for such an application. If nanocarbonaceous material acts as a highly permeable matrix with a high specific surface area, immobilized indigo nanoparticles are involved into an ozonolysis reaction with ozone leading to the selective removal of this analytes from air sample. The filtering yields towards each gas have been experimentally quantified and establish the complete removal of ozone while having the concentration of nitrogen dioxide unchanged. Long-term gas exposures reveal the higher durability of hybrid material as compared to nanocarbons and indigo separately. Synthesis, characterizations by many complementary techniques and tests of hybrid filters are detailed. Results on sensor-system including CuPc-based chemoresistors and indigo/carbon nanotubes hybrid material as in-line filter are illustrated. Sensing performances will be especially discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Ultra-microporous triptycene-based polyimide membranes for high-performance gas separation

KAUST Repository

Ghanem, Bader

2014-03-11

A highly permeable and highly selective polyimide of intrinsic microporosity is prepared using a 9,10-diisopropyl-triptycene contortion center. The three-dimensionality and shape-persistence of triptycene afford exceptional sieving-based gas separation performance transcending the latest permeability/selectivity trade-offs for industrial gas separations involving oxygen and hydrogen. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Ultra-microporous triptycene-based polyimide membranes for high-performance gas separation

KAUST Repository

Ghanem, Bader; Swaidan, Raja; Litwiller, Eric; Pinnau, Ingo

2014-01-01

A highly permeable and highly selective polyimide of intrinsic microporosity is prepared using a 9,10-diisopropyl-triptycene contortion center. The three-dimensionality and shape-persistence of triptycene afford exceptional sieving-based gas separation performance transcending the latest permeability/selectivity trade-offs for industrial gas separations involving oxygen and hydrogen. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Highly selective and sensitive paper-based colorimetric sensor using thiosulfate catalytic etching of silver nanoplates for trace determination of copper ions.

Science.gov (United States)

Chaiyo, Sudkate; Siangproh, Weena; Apilux, Amara; Chailapakul, Orawon

2015-03-25

A novel, highly selective and sensitive paper-based colorimetric sensor for trace determination of copper (Cu(2+)) ions was developed. The measurement is based on the catalytic etching of silver nanoplates (AgNPls) by thiosulfate (S2O3(2-)). Upon the addition of Cu(2+) to the ammonium buffer at pH 11, the absorption peak intensity of AuNPls/S2O3(2-) at 522 nm decreased and the pinkish violet AuNPls became clear in color as visible to the naked eye. This assay provides highly sensitive and selective detection of Cu(2+) over other metal ions (K(+), Cr(3+), Cd(2+), Zn(2+), As(3+), Mn(2+), Co(2+), Pb(2+), Al(3+), Ni(2+), Fe(3+), Mg(2+), Hg(2+) and Bi(3+)). A paper-based colorimetric sensor was then developed for the simple and rapid determination of Cu(2+) using the catalytic etching of AgNPls. Under optimized conditions, the modified AgNPls coated at the test zone of the devices immediately changes in color in the presence of Cu(2+). The limit of detection (LOD) was found to be 1.0 ng mL(-1) by visual detection. For semi-quantitative measurement with image processing, the method detected Cu(2+) in the range of 0.5-200 ng mL(-1)(R(2)=0.9974) with an LOD of 0.3 ng mL(-1). The proposed method was successfully applied to detect Cu(2+) in the wide range of real samples including water, food, and blood. The results were in good agreement according to a paired t-test with results from inductively coupled plasma-optical emission spectrometry (ICP-OES). Copyright © 2015. Published by Elsevier B.V.

An Entropy-based gene selection method for cancer classification using microarray data

Directory of Open Access Journals (Sweden)

Krishnan Arun

2005-03-01

Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

Biological Select Agents and Toxins: Risk-Based Assessment Management and Oversight.

Energy Technology Data Exchange (ETDEWEB)

Burnett, LouAnn Crawford; Brodsky, Benjamin H.

2016-12-01

Sandia National Laboratories' International Biological and Chemical Threat Reduction (SNL/IBCTR) conducted, on behalf of the Federal Select Agent Program (FSAP), a review of risk assessment in modern select agent laboratories. This review and analysis consisted of literature review, interviews of FSAP staff, entities regulated by FSAP, and deliberations of an expert panel. Additionally, SNL/IBCTR reviewed oversight mechanisms used by industries, US agencies, and other countries for high-consequence risks (e.g, nuclear, chemical, or biological materials, aviation, off-shore drilling, etc.) to determine if alternate oversight mechanisms existed that might be applicable to FSAP oversight of biological select agents and toxins. This report contains five findings, based on these reviews and analyses, with recommendations and suggested actions for FSAP to consider.

Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

Directory of Open Access Journals (Sweden)

Zhehuang Huang

2015-01-01

Full Text Available Artificial fish swarm algorithm (AFSA is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

Log-linear model based behavior selection method for artificial fish swarm algorithm.

Science.gov (United States)

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

A Novel Approach to Selecting Contractor in Agent-based Multi-sensor Battlefield Reconnaissance Simulation

Directory of Open Access Journals (Sweden)

Xiong Li

2012-11-01

Full Text Available This paper presents a novel approach towards showing how contractor in agent-based simulation for complex warfare system such as multi-sensor battlefield reconnaissance system can be selected in Contract Net Protocol (CNP with high efficiency. We first analyze agent and agent-based simulation framework, CNP and collaborators, and present agents interaction chain used to actualize CNP and establish agents trust network. We then obtain contractor's importance weight and dynamic trust by presenting fuzzy similarity-based algorithm and trust modifying algorithm, thus we propose contractor selecting approach based on maximum dynamic integrative trust. We validate the feasibility and capability of this approach by implementing simulation, analyzing compared results and checking the model.

Design of Highly Selective Gas Sensors via Physicochemical Modification of Oxide Nanowires: Overview

Directory of Open Access Journals (Sweden)

Hyung-Sik Woo

2016-09-01

Full Text Available Strategies for the enhancement of gas sensing properties, and specifically the improvement of gas selectivity of metal oxide semiconductor nanowire (NW networks grown by chemical vapor deposition and thermal evaporation, are reviewed. Highly crystalline NWs grown by vapor-phase routes have various advantages, and thus have been applied in the field of gas sensors over the years. In particular, n-type NWs such as SnO2, ZnO, and In2O3 are widely studied because of their simple synthetic preparation and high gas response. However, due to their usually high responses to C2H5OH and NO2, the selective detection of other harmful and toxic gases using oxide NWs remains a challenging issue. Various strategies—such as doping/loading of noble metals, decorating/doping of catalytic metal oxides, and the formation of core–shell structures—have been explored to enhance gas selectivity and sensitivity, and are discussed herein. Additional methods such as the transformation of n-type into p-type NWs and the formation of catalyst-doped hierarchical structures by branch growth have also proven to be promising for the enhancement of gas selectivity. Accordingly, the physicochemical modification of oxide NWs via various methods provides new strategies to achieve the selective detection of a specific gas, and after further investigations, this approach could pave a new way in the field of NW-based semiconductor-type gas sensors.

Affinity selection-mass spectrometry and its emerging application to the high throughput screening of G protein-coupled receptors.

Science.gov (United States)

Whitehurst, Charles E; Annis, D Allen

2008-07-01

Advances in combinatorial chemistry and genomics have inspired the development of novel affinity selection-based screening techniques that rely on mass spectrometry to identify compounds that preferentially bind to a protein target. Of the many affinity selection-mass spectrometry techniques so far documented, only a few solution-based implementations that separate target-ligand complexes away from unbound ligands persist today as routine high throughput screening platforms. Because affinity selection-mass spectrometry techniques do not rely on radioactive or fluorescent reporters or enzyme activities, they can complement traditional biochemical and cell-based screening assays and enable scientists to screen targets that may not be easily amenable to other methods. In addition, by employing mass spectrometry for ligand detection, these techniques enable high throughput screening of massive library collections of pooled compound mixtures, vastly increasing the chemical space that a target can encounter during screening. Of all drug targets, G protein coupled receptors yield the highest percentage of therapeutically effective drugs. In this manuscript, we present the emerging application of affinity selection-mass spectrometry to the high throughput screening of G protein coupled receptors. We also review how affinity selection-mass spectrometry can be used as an analytical tool to guide receptor purification, and further used after screening to characterize target-ligand binding interactions, enabling the classification of orthosteric and allosteric binders.

Portable, universal, and visual ion sensing platform based on the light emitting diode-based self-referencing-ion selective field-effect transistor.

Science.gov (United States)

Zhang, Xiaowei; Han, Yanchao; Li, Jing; Zhang, Libing; Jia, Xiaofang; Wang, Erkang

2014-02-04

In this work, a novel and universal ion sensing platform was presented, which enables the visual detection of various ions with high sensitivity and selectivity. Coaxial potential signals (millivolt-scale) of the sample from the self-referencing (SR) ion selective chip can be transferred into the ad620-based amplifier with an output of volt-scale potentials. The amplified voltage is high enough to drive a light emitting diode (LED), which can be used as an amplifier and indicator to report the sample information. With this double amplification device (light emitting diode-based self-referencing-ion selective field-effect transistor, LED-SR-ISFET), a tiny change of the sample concentration can be observed with a distinguishable variation of LED brightness by visual inspection. This LED-based luminescent platform provided a facile, low-cost, and rapid sensing strategy without the need of additional expensive chemiluminescence reagent and instruments. Moreover, the SR mode also endows this device excellent stability and reliability. With this innovative design, sensitive determination of K(+), H(+), and Cl(-) by the naked eye was achieved. It should also be noticed that this sensing strategy can easily be extended to other ions (or molecules) by simply integrating the corresponding ion (or molecule) selective electrode.

Solar selective performance of metal nitride/oxynitride based magnetron sputtered thin film coatings: a comprehensive review

Science.gov (United States)

Ibrahim, Khalil; Taha, Hatem; Mahbubur Rahman, M.; Kabir, Humayun; Jiang, Zhong-Tao

2018-03-01

Since solar-thermal collectors are considered to be the most direct way of converting solar energy into usable forms, in the last few years growing attention has been paid to the development of transition metal nitride and metal oxynitride based thin film selective surfaces for solar-thermal collectors, in order to harvest more solar energy. A solar-thermal energy system, generally, shows very high solar absorption of incident solar radiation from the solar-thermal collectors in the visible range (0.3 to 2.5 μm) and extremely low thermal losses through emission (or high reflection) in the infrared region (≥2.5 μm). The efficiency of a solar-thermal energy conversion system can be improved by the use of solar selective surfaces consisting of novel metallic nanoparticles embedded in metal nitride/oxynitride systems. In order to enhance the effectiveness of solar-thermal devices, solar selective surfaces with high thermal stability are a prerequisite. Over the years, substantial efforts have been made in the field of solar selective surfaces to attain higher solar absorptance and lower thermal emittance in high temperature (above 400 °C) applications. In this article, we review the present state-of-the-art transition metal nitride and/or oxynitride based vacuum sputtered nanostructured thin film coatings, with respect to their optical and solar selective surface applications. We have also summarized the solar selectivity data from recently published investigations, including discussion on some potential applications for these materials.

Cermet based solar selective absorbers : further selectivity improvement and developing new fabrication technique

OpenAIRE

Nejati, Mohammadreza

2008-01-01

Spectral selectivity of cermet based selective absorbers were increased by inducing surface roughness on the surface of the cermet layer using a roughening technique (deposition on hot substrates) or by micro-structuring the metallic substrates before deposition of the absorber coating using laser and imprint structuring techniques. Cu-Al2O3 cermet absorbers with very rough surfaces and excellent selectivity were obtained by employing a roughness template layer under the infrared reflective l...

Novel Distance Measure in Fuzzy TOPSIS for Supply Chain Strategy Based Supplier Selection

Directory of Open Access Journals (Sweden)

B. Pardha Saradhi

2016-01-01

Full Text Available In today’s highly competitive environment, organizations need to evaluate and select suppliers based on their manufacturing strategy. Identification of supply chain strategy of the organization, determination of decision criteria, and methods of supplier selection are appearing to be the most important components in research area in the field of supply chain management. In this paper, evaluation of suppliers is done based on the balanced scorecard framework using new distance measure in fuzzy TOPSIS by considering the supply chain strategy of the manufacturing organization. To take care of vagueness in decision making, trapezoidal fuzzy number is assumed for pairwise comparisons to determine relative weights of perspectives and criteria of supplier selection. Also, linguistic variables specified in terms of trapezoidal fuzzy number are considered for the payoff values of criteria of the suppliers. These fuzzy numbers satisfied the Jensen based inequality. A detailed application of the proposed methodology is illustrated.

Dual mode operation, highly selective nanohole array-based plasmonic colour filters

Science.gov (United States)

Fouladi Mahani, Fatemeh; Mokhtari, Arash; Mehran, Mahdiyeh

2017-09-01

Taking advantage of nanostructured metal films as plasmonic colour filters (PCFs) has been evolved remarkably as an alternative to the conventional technologies of chemical colour filtering. However, most of the proposed PCFs depict a poor colour purity focusing on generating either the additive or subtractive colours. In this paper, we present dual mode operation PCFs employing an opaque aluminium film patterned with sub-wavelength holes. Subtractive colours like cyan, magenta, and yellow are the results of reflection mode of these filters yielding optical efficiencies as high as 70%-80% and full width at half maximum of the stop-bands up to 40-50 nm. The colour selectivity of the transmission mode for the additive colours is also significant due to their enhanced performance through the utilization of a relatively thick aluminium film in contact with a modified dielectric environment. These filters provide a simple design with one-step lithography in addition to compatibility with the conventional CMOS processes. Moreover, they are polarization insensitive due to their symmetric geometry. A complete palette of pure subtractive and additive colours has been realized with potential applications, such as multispectral imaging, CMOS image sensors, displays, and colour printing.

A schiff-base receptor based naphthalimide derivative: Highly selective and colorimetric fluorescent turn-on sensor for Al{sup 3+}

Energy Technology Data Exchange (ETDEWEB)

Kang, Lei; Liu, Ya-Tong; Li, Na-Na; Dang, Qian-Xi [Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin 150030 (China); Xing, Zhi-Yong, E-mail: zyxing@neau.edu.cn [Department of Applied Chemistry, College of Science, Northeast Agricultural University, Harbin 150030 (China); Li, Jin-Long; Zhang, Yu [College of Heilongjiang Province Key Laboratory of Fine Chemicals, Qiqihar University, Qiqihar 161006 (China)

2017-06-15

A new schiff-base receptor L based on naphthalimide had been investigated as a selective and sensitive chemosensor for Al{sup 3+} in CH{sub 3}OH. Upon addition of Al{sup 3+}, L showed a 39-fold enhancement at 508 nm with colorimetric and fluorometric dual-signaling response which might be induced by the integration of ICT and CHEF. A 1:1 stoichiometry for the L-Al{sup 3+} complex was formed with an association constant of 1.62×10{sup 4} M{sup −1}, and the limit of detection for Al{sup 3+} was determined as 7.4 nM. In addition, the potential utility of L in sensing Al{sup 3+} was also examined in real water samples.

A Reagentless Amperometric Formaldehyde-Selective Chemosensor Based on Platinized Gold Electrodes.

Science.gov (United States)

Demkiv, Olha; Smutok, Oleh; Gonchar, Mykhailo; Nisnevitch, Marina

2017-05-06

Fabrication and characterization of a new amperometric chemosensor for accurate formaldehyde analysis based on platinized gold electrodes is described. The platinization process was performed electrochemically on the surface of 4 mm gold planar electrodes by both electrolysis and cyclic voltamperometry. The produced electrodes were characterized using scanning electron microscopy and X-ray spectral analysis. Using a low working potential (0.0 V vs. Ag/AgCl) enabled an essential increase in the chemosensor's selectivity for the target analyte. The sensitivity of the best chemosensor prototype to formaldehyde is uniquely high (28180 A·M -1 ·m -2 ) with a detection limit of 0.05 mM. The chemosensor remained stable over a one-year storage period. The formaldehye-selective chemosensor was tested on samples of commercial preparations. A high correlation was demonstrated between the results obtained by the proposed chemosensor, chemical and enzymatic methods ( R = 0.998). The developed formaldehyde-selective amperometric chemosensor is very promising for use in industry and research, as well as for environmental control.

Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

Science.gov (United States)

Zeng, Xueqiang; Luo, Gang

2017-12-01

Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

Electronic excitation of composite systems. Progress report, August 1, 1975--July 31, 1976

International Nuclear Information System (INIS)

Ashraf El-Bayoumi, M.

1976-04-01

The effects of pH and temperature solvent deuteration on the fluorescence spectra and quantum yields of 7-azaindole in ethanol and in water were studied. Evidence was provided for double proton transfer in 7-azaindole complexes with alcohol and water. Observation of double proton transfer in a model system azacarbazole (α-carboline) was made. Synthesis of the compound and its corresponding tautomer were completed. Fluorescence measurements under various conditions were performed. The effects of temperature and polarity of the medium on the fluorescence yield and life-time of a fluorescence-polarity probe (namely, Dansylsulfonamide) was also studied along with the effect of the solvent-deuterium isotope substitution. Polarization decay measurements of rhodamine B in glycerol at room temperature were performed. The anisotropy decay was found to be double exponential with values of approximately 9 nsec and 96 nsec for rotation about the major and minor axes, respectively. The study of rotational relaxations of dansylated lysozyme at two different temperatures indicated the possibility of monomer-dimer equilibrium

Performance-Based Technology Selection Filter description report

International Nuclear Information System (INIS)

O'Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

1992-05-01

A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL)

Discriminative Projection Selection Based Face Image Hashing

Science.gov (United States)

Karabat, Cagatay; Erdogan, Hakan

Face image hashing is an emerging method used in biometric verification systems. In this paper, we propose a novel face image hashing method based on a new technique called discriminative projection selection. We apply the Fisher criterion for selecting the rows of a random projection matrix in a user-dependent fashion. Moreover, another contribution of this paper is to employ a bimodal Gaussian mixture model at the quantization step. Our simulation results on three different databases demonstrate that the proposed method has superior performance in comparison to previously proposed random projection based methods.

Performance-Based Technology Selection Filter description report

Energy Technology Data Exchange (ETDEWEB)

O' Brien, M.C.; Morrison, J.L.; Morneau, R.A.; Rudin, M.J.; Richardson, J.G.

1992-05-01

A formal methodology has been developed for identifying technology gaps and assessing innovative or postulated technologies for inclusion in proposed Buried Waste Integrated Demonstration (BWID) remediation systems. Called the Performance-Based Technology Selection Filter, the methodology provides a formalized selection process where technologies and systems are rated and assessments made based on performance measures, and regulatory and technical requirements. The results are auditable, and can be validated with field data. This analysis methodology will be applied to the remedial action of transuranic contaminated waste pits and trenches buried at the Idaho National Engineering Laboratory (INEL).

Bayesian Multiresolution Variable Selection for Ultra-High Dimensional Neuroimaging Data.

Science.gov (United States)

Zhao, Yize; Kang, Jian; Long, Qi

2018-01-01

Ultra-high dimensional variable selection has become increasingly important in analysis of neuroimaging data. For example, in the Autism Brain Imaging Data Exchange (ABIDE) study, neuroscientists are interested in identifying important biomarkers for early detection of the autism spectrum disorder (ASD) using high resolution brain images that include hundreds of thousands voxels. However, most existing methods are not feasible for solving this problem due to their extensive computational costs. In this work, we propose a novel multiresolution variable selection procedure under a Bayesian probit regression framework. It recursively uses posterior samples for coarser-scale variable selection to guide the posterior inference on finer-scale variable selection, leading to very efficient Markov chain Monte Carlo (MCMC) algorithms. The proposed algorithms are computationally feasible for ultra-high dimensional data. Also, our model incorporates two levels of structural information into variable selection using Ising priors: the spatial dependence between voxels and the functional connectivity between anatomical brain regions. Applied to the resting state functional magnetic resonance imaging (R-fMRI) data in the ABIDE study, our methods identify voxel-level imaging biomarkers highly predictive of the ASD, which are biologically meaningful and interpretable. Extensive simulations also show that our methods achieve better performance in variable selection compared to existing methods.

Robust Feature Selection from Microarray Data Based on Cooperative Game Theory and Qualitative Mutual Information

Directory of Open Access Journals (Sweden)

Atiyeh Mortazavi

2016-01-01

Full Text Available High dimensionality of microarray data sets may lead to low efficiency and overfitting. In this paper, a multiphase cooperative game theoretic feature selection approach is proposed for microarray data classification. In the first phase, due to high dimension of microarray data sets, the features are reduced using one of the two filter-based feature selection methods, namely, mutual information and Fisher ratio. In the second phase, Shapley index is used to evaluate the power of each feature. The main innovation of the proposed approach is to employ Qualitative Mutual Information (QMI for this purpose. The idea of Qualitative Mutual Information causes the selected features to have more stability and this stability helps to deal with the problem of data imbalance and scarcity. In the third phase, a forward selection scheme is applied which uses a scoring function to weight each feature. The performance of the proposed method is compared with other popular feature selection algorithms such as Fisher ratio, minimum redundancy maximum relevance, and previous works on cooperative game based feature selection. The average classification accuracy on eleven microarray data sets shows that the proposed method improves both average accuracy and average stability compared to other approaches.

Integrative approaches to the prediction of protein functions based on the feature selection

Directory of Open Access Journals (Sweden)

Lee Hyunju

2009-12-01

Full Text Available Abstract Background Protein function prediction has been one of the most important issues in functional genomics. With the current availability of various genomic data sets, many researchers have attempted to develop integration models that combine all available genomic data for protein function prediction. These efforts have resulted in the improvement of prediction quality and the extension of prediction coverage. However, it has also been observed that integrating more data sources does not always increase the prediction quality. Therefore, selecting data sources that highly contribute to the protein function prediction has become an important issue. Results We present systematic feature selection methods that assess the contribution of genome-wide data sets to predict protein functions and then investigate the relationship between genomic data sources and protein functions. In this study, we use ten different genomic data sources in Mus musculus, including: protein-domains, protein-protein interactions, gene expressions, phenotype ontology, phylogenetic profiles and disease data sources to predict protein functions that are labelled with Gene Ontology (GO terms. We then apply two approaches to feature selection: exhaustive search feature selection using a kernel based logistic regression (KLR, and a kernel based L1-norm regularized logistic regression (KL1LR. In the first approach, we exhaustively measure the contribution of each data set for each function based on its prediction quality. In the second approach, we use the estimated coefficients of features as measures of contribution of data sources. Our results show that the proposed methods improve the prediction quality compared to the full integration of all data sources and other filter-based feature selection methods. We also show that contributing data sources can differ depending on the protein function. Furthermore, we observe that highly contributing data sets can be similar among

SU-E-J-128: Two-Stage Atlas Selection in Multi-Atlas-Based Image Segmentation

International Nuclear Information System (INIS)

Zhao, T; Ruan, D

2015-01-01

Purpose: In the new era of big data, multi-atlas-based image segmentation is challenged by heterogeneous atlas quality and high computation burden from extensive atlas collection, demanding efficient identification of the most relevant atlases. This study aims to develop a two-stage atlas selection scheme to achieve computational economy with performance guarantee. Methods: We develop a low-cost fusion set selection scheme by introducing a preliminary selection to trim full atlas collection into an augmented subset, alleviating the need for extensive full-fledged registrations. More specifically, fusion set selection is performed in two successive steps: preliminary selection and refinement. An augmented subset is first roughly selected from the whole atlas collection with a simple registration scheme and the corresponding preliminary relevance metric; the augmented subset is further refined into the desired fusion set size, using full-fledged registration and the associated relevance metric. The main novelty of this work is the introduction of an inference model to relate the preliminary and refined relevance metrics, based on which the augmented subset size is rigorously derived to ensure the desired atlases survive the preliminary selection with high probability. Results: The performance and complexity of the proposed two-stage atlas selection method were assessed using a collection of 30 prostate MR images. It achieved comparable segmentation accuracy as the conventional one-stage method with full-fledged registration, but significantly reduced computation time to 1/3 (from 30.82 to 11.04 min per segmentation). Compared with alternative one-stage cost-saving approach, the proposed scheme yielded superior performance with mean and medium DSC of (0.83, 0.85) compared to (0.74, 0.78). Conclusion: This work has developed a model-guided two-stage atlas selection scheme to achieve significant cost reduction while guaranteeing high segmentation accuracy. The benefit

An objective method for High Dynamic Range source content selection

DEFF Research Database (Denmark)

Narwaria, Manish; Mantel, Claire; Da Silva, Matthieu Perreira

2014-01-01

With the aim of improving the immersive experience of the end user, High Dynamic Range (HDR) imaging has been gaining popularity. Therefore, proper validation and performance benchmarking of HDR processing algorithms is a key step towards standardization and commercial deployment. A crucial...... component of such validation studies is the selection of a challenging and balanced set of source (reference) HDR content. In order to facilitate this, we present an objective method based on the premise that a more challenging HDR scene encapsulates higher contrast, and as a result will show up more...

Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

International Nuclear Information System (INIS)

Wang Xiaojia; Mao Qirong; Zhan Yongzhao

2008-01-01

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions. The experiments show that this method can improve the recognition rate and the time of feature extraction

Variable selection for confounder control, flexible modeling and Collaborative Targeted Minimum Loss-based Estimation in causal inference

Science.gov (United States)

Schnitzer, Mireille E.; Lok, Judith J.; Gruber, Susan

2015-01-01

This paper investigates the appropriateness of the integration of flexible propensity score modeling (nonparametric or machine learning approaches) in semiparametric models for the estimation of a causal quantity, such as the mean outcome under treatment. We begin with an overview of some of the issues involved in knowledge-based and statistical variable selection in causal inference and the potential pitfalls of automated selection based on the fit of the propensity score. Using a simple example, we directly show the consequences of adjusting for pure causes of the exposure when using inverse probability of treatment weighting (IPTW). Such variables are likely to be selected when using a naive approach to model selection for the propensity score. We describe how the method of Collaborative Targeted minimum loss-based estimation (C-TMLE; van der Laan and Gruber, 2010) capitalizes on the collaborative double robustness property of semiparametric efficient estimators to select covariates for the propensity score based on the error in the conditional outcome model. Finally, we compare several approaches to automated variable selection in low-and high-dimensional settings through a simulation study. From this simulation study, we conclude that using IPTW with flexible prediction for the propensity score can result in inferior estimation, while Targeted minimum loss-based estimation and C-TMLE may benefit from flexible prediction and remain robust to the presence of variables that are highly correlated with treatment. However, in our study, standard influence function-based methods for the variance underestimated the standard errors, resulting in poor coverage under certain data-generating scenarios. PMID:26226129

Radiosynthesis of 3-{l_brace}[4-(4-[{sup 18}F]fluorobenzyl)]piperazin-1-yl{r_brace}methyl-1H-pyrrolo[2,3-b]pyridine: A potential dopamine D{sub 4} receptor imaging agent

Energy Technology Data Exchange (ETDEWEB)

Haibin Tian; Duanzhi Yin; Junling Li; Lan Zhang; Cunfu Zhang; Yongxian Wang; Wei Zhou [Radiopharmaceutical Research Center, Shanghai Inst. of Nuclear Research, The Chinese Academy of Sciences, Shanghai, SH (China)

2003-07-01

The dopamine D{sub 4} receptor (D{sub 4}R) is expressed in low density in various extrastriatal brain regions. This receptor subtype is discussed in relation to the pathophysiology and treatment of schizophrenia but to date no selective positron emission tomography (PET) ligand is available to study its distribution in vivo. The 7-azaindole derivative 3-([4-(4-iodophenyl)piperazin-1-yl]-methyl)-1H-pyrrolo [2,3-b]pyridine (L-750,667) is a novel, high-affinity (K{sub i}=0.51nM) and selective D{sub 4}R ligand. L-750,667 analogue 3-[4-(4-[{sup 18}F]fluorobenzyl)]piperazin-1-yl methyl-1H-pyrrolo[2,3-b]-pyridine was prepared by reacting 3-(piperazin-1-yl)-methyl-1H-pyrrolo[2,3-b]pyridine with 4-[ 18F]fluorobenzaldehyde, which was labeled with no carrier added [ 18F]fluoride. The radiochemical yield of 3-[4-(4-[{sup 18}F]fluorobenzyl)]piperazin-1-yl methyl-1H-pyrrolo[2,3-b]pyridine was 12.0% at end of synthesis (EOS), and the synthesis time was 73min. The labeled benzaldehydes may be useful precursors for the radiosyntheses of other complex radiotracers for PET.

Selectivity in Postencoding Connectivity with High-Level Visual Cortex Is Associated with Reward-Motivated Memory.

Science.gov (United States)

Murty, Vishnu P; Tompary, Alexa; Adcock, R Alison; Davachi, Lila

2017-01-18

Reward motivation has been demonstrated to enhance declarative memory by facilitating systems-level consolidation. Although high-reward information is often intermixed with lower reward information during an experience, memory for high value information is prioritized. How is this selectivity achieved? One possibility is that postencoding consolidation processes bias memory strengthening to those representations associated with higher reward. To test this hypothesis, we investigated the influence of differential reward motivation on the selectivity of postencoding markers of systems-level memory consolidation. Human participants encoded intermixed, trial-unique memoranda that were associated with either high or low-value during fMRI acquisition. Encoding was interleaved with periods of rest, allowing us to investigate experience-dependent changes in connectivity as they related to later memory. Behaviorally, we found that reward motivation enhanced 24 h associative memory. Analysis of patterns of postencoding connectivity showed that, even though learning trials were intermixed, there was significantly greater connectivity with regions of high-level, category-selective visual cortex associated with high-reward trials. Specifically, increased connectivity of category-selective visual cortex with both the VTA and the anterior hippocampus predicted associative memory for high- but not low-reward memories. Critically, these results were independent of encoding-related connectivity and univariate activity measures. Thus, these findings support a model by which the selective stabilization of memories for salient events is supported by postencoding interactions with sensory cortex associated with reward. Reward motivation is thought to promote memory by supporting memory consolidation. Yet, little is known as to how brain selects relevant information for subsequent consolidation based on reward. We show that experience-dependent changes in connectivity of both the

A Preference Model for Supplier Selection Based on Hesitant Fuzzy Sets

Directory of Open Access Journals (Sweden)

Zhexuan Zhou

2018-03-01

Full Text Available The supplier selection problem is a widespread concern in the modern commercial economy. Ranking suppliers involves many factors and poses significant difficulties for decision makers. Supplier selection is a multi-criteria and multi-objective problem, which leads to decision makers forming their own preferences. In addition, there are both quantifiable and non-quantifiable attributes related to their preferences. To solve this problem, this paper presents a preference model based on hesitant fuzzy sets (HFS to select suppliers. The cost and service quality of suppliers are the main considerations in the proposed model. HFS with interactive and multi-criteria decision making are used to evaluate the non-quantifiable attributes of service quality, which include competitive display, qualification ability, suitability and competitiveness of solutions, and relational fitness and dynamics. Finally, a numerical example of supplier selection for a high-end equipment manufacturer is provided to illustrate the applicability of the proposed model. The preferences of a decision maker are then analyzed by altering preference parameters.

Highly selective room temperature NO2 gas sensor based on rGO-ZnO composite

Science.gov (United States)

Jyoti, Kanaujiya, Neha; Varma, G. D.

2018-05-01

Blending metal oxide nanoparticles with graphene or its derivatives can greatly enhance gas sensing characteristics. In the present work, ZnO nanoparticles have been synthesized via reflux method. Thin films of reduced graphene oxide (rGO) and composite of rGO-ZnO have been fabricated by drop casting method for gas sensing application. The samples have been characterized by X-ray diffraction (XRD) and Field-emission scanning electron microscope (FESEM) for the structural and morphological studies respectively. Sensing measurements have been carried out for the composite film of rGO-ZnO for different concentrations of NO2 ranging from 4 to 100 ppm. Effect of increasing temperature on the sensing performance has also been studied and the rGO-ZnO composite sensor shows maximum percentage response at room temperature. The limit of detection (LOD) for rGO-ZnO composite sensor is 4ppm and it exhibits a high response of 48.4% for 40 ppm NO2 at room temperature. To check the selectivity of the composite sensor, sensor film has been exposed to 40 ppm different gases like CO, NH3, H2S and Cl2 at room temperature and the sensor respond negligibly to these gases. The present work suggests that rGO-ZnO composite material can be a better candidate for fabrication of highly selective room temperature NO2 gas sensor.

Utilization of highly robust and selective crosslinked polymeric ionic liquid-based sorbent coatings in direct-immersion solid-phase microextraction and high-performance liquid chromatography for determining polar organic pollutants in waters.

Science.gov (United States)

Pacheco-Fernández, Idaira; Najafi, Ali; Pino, Verónica; Anderson, Jared L; Ayala, Juan H; Afonso, Ana M

2016-09-01

Several crosslinked polymeric ionic liquid (PIL)-based sorbent coatings of different nature were prepared by UV polymerization onto nitinol wires. They were evaluated in a direct-immersion solid-phase microextraction (DI-SPME) method in combination with high-performance liquid chromatography (HPLC) and diode array detection (DAD). The studied PIL coatings contained either vinyl alkyl or vinylbenzyl imidazolium-based (ViCnIm- or ViBCnIm-) IL monomers with different anions, as well as different dicationic IL crosslinkers. The analytical performance of these PIL-based SPME coatings was firstly evaluated for the extraction of a group of 10 different model analytes, including hydrocarbons and phenols, while exhaustively comparing the performance with commercial SPME fibers such as polydimethylsyloxane (PDMS), polyacrylate (PA) and polydimethylsiloxane/divinylbenzene (PDMS/DVB), and using all fibers under optimized conditions. Those fibers exhibiting a high selectivity for polar compounds were selected to carry out an analytical method for a group of 5 alkylphenols, including bisphenol-A (BPA) and nonylphenol (n-NP). Under optimum conditions, average relative recoveries of 108% and inter-day precision values (3 non-consecutive days) lower than 19% were obtained for a spiked level of 10µgL(-1). Correlations coefficients for the overall method ranged between 0.990 and 0.999, and limits of detection were down to 1µgL(-1). Tap water, river water, and bottled water were analyzed to evaluate matrix effects. Comparison with the PA fiber was also performed in terms of analytical performance. Partition coefficients (logKfs) of the alkylphenols to the SPME coating varied from 1.69 to 2.45 for the most efficient PIL-based fiber, and from 1.58 to 2.30 for the PA fiber. These results agree with those obtained by the normalized calibration slopes, pointing out the affinity of these PILs-based coatings. Copyright © 2016 Elsevier B.V. All rights reserved.

Highly sensitive and selective cartap nanosensor based on luminescence resonance energy transfer between NaYF4:Yb,Ho nanocrystals and gold nanoparticles.

Science.gov (United States)

Wang, Zhijiang; Wu, Lina; Shen, Baozhong; Jiang, Zhaohua

2013-09-30

Fluorescent detection is an attractive method for the detection of toxic chemicals. However, most chemosensors that are currently utilized in fluorescent detection are based on organic dyes or quantum dots, which suffer from instability, high background noise and interference from organic impurities in solution, which can also be excited by UV radiation. In the present research, we developed a novel NaYF4:Yb,Ho/Au nanocomposite-based chemosensor with high sensitivity (10 ppb) and selectivity over competing analytes for the detection of the insecticide cartap. This nanosensor is excited with a 970-nm laser instead of UV radiation to give an emission peak at 541 nm. In the presence of cartap, the nanocomposites aggregate, resulting in enhanced luminescence resonance energy transfer between the NaYF4:Yb,Ho nanocrystals and the gold nanoparticles, which decreases the emission intensity at 541 nm. The relative luminescence intensity at 541 nm has a linear relationship with the concentration of cartap in the solution. Based on this behavior, the developed nanosensor successfully detected cartap in farm produce and water samples with satisfactory results. Copyright © 2013 Elsevier B.V. All rights reserved.

Theory of mind selectively predicts preschoolers' knowledge-based selective word learning.

Science.gov (United States)

Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

2015-11-01

Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory-of-mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children's preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children's developing social cognition and early learning. © 2015 The British Psychological Society.

Theory of mind selectively predicts preschoolers’ knowledge-based selective word learning

Science.gov (United States)

Brosseau-Liard, Patricia; Penney, Danielle; Poulin-Dubois, Diane

2015-01-01

Children can selectively attend to various attributes of a model, such as past accuracy or physical strength, to guide their social learning. There is a debate regarding whether a relation exists between theory-of-mind skills and selective learning. We hypothesized that high performance on theory-of-mind tasks would predict preference for learning new words from accurate informants (an epistemic attribute), but not from physically strong informants (a non-epistemic attribute). Three- and 4-year-olds (N = 65) completed two selective learning tasks, and their theory of mind abilities were assessed. As expected, performance on a theory-of-mind battery predicted children’s preference to learn from more accurate informants but not from physically stronger informants. Results thus suggest that preschoolers with more advanced theory of mind have a better understanding of knowledge and apply that understanding to guide their selection of informants. This work has important implications for research on children’s developing social cognition and early learning. PMID:26211504

Selection of High Performance Alloy for Gas Turbine Blade Using Multiphysics Analysis

Directory of Open Access Journals (Sweden)

H Khawaja

2016-09-01

Full Text Available With the extensive increase in the utilization of energy resources in the modern era, the need of energy extraction from various resources has pronounced in recent years. Thus comprehensive efforts have been made around the globe in the technological development of turbo machines where means of energy extraction is energized fluids. This development led the aviation industry to power boost due to better performing engines. Meanwhile, the structural conformability requirements relative to the functional requirements have also increased with the advent of newer, better performing materials. Thus there is a need to study the material behavior and its usage with the idea of selecting the best possible material for its application. In this work a gas turbine blade of a small turbofan engine, where geometry and aerodynamic data was available, was analyzed for its structural behavior in the proposed mission envelope, where the engine turbine is subjected to high thermal, inertial and aerodynamic loads. Multiphysics Finite Element (FE linear stress analysis was carried out on the turbine blade. The results revealed the upper limit of Ultimate Tensile Strength (UTS for the blade. Based on the limiting factor, high performance alloys were selected from the literature. The two most recommended alloy categories for gas turbine blades are NIMONIC and INCONEL from where total of 21 types of INCONEL alloys and 12 of NIMONIC alloys, available on commercial bases, were analyzed individually to meet the structural requirements. After applying selection criteria, four alloys were finalized from NIMONIC and INCONEL alloys for further analysis. On the basis of stress-strain behavior of finalized alloys, the Multiphysics FE nonlinear stress analysis was then carried out for the selection of the individual alloy by imposing a restriction of Ultimate Factor of Safety (UFOS of 1.33 and yield strength. Final selection is made keeping in view other factors

Perceptions of selected science careers by African American high school males

Science.gov (United States)

Ijames, Erika Denise

Research indicates that internal and external factors such as role models, stereotypes, and pressures placed on African American males by their family and friends influence their perceptions of science careers (Assibey-Mensah, 1997; Hess & Leal, 1997; Jacobowitz, 1983; Maple & Stage, 1991; Thomas, 1989; Ware & Lee, 1988). The purpose of this research was to investigate the perceptions of African American high school males about selected science careers based on apparent internal and external factors. Two questions guided this research: (1) What are high school African American males' perceptions of science careers? (2) What influences high school African American males' perceptions of science careers? This research was based on a pilot study in which African American college males perceived a selection of science careers along racial and gender lines. The follow-up investigation was conducted at Rockriver High School in Acorn County, and the participants were three college-bound African American males. The decision to choose males was based on the concept of occupational niching along gender lines. In biology, niching is defined as the role of a particular species regarding space and reproduction, and its interactions with other factors. During the seven-week period of the students' senior year, they met with the researcher to discuss their perceptions of science careers. An ethnographic approach was used to allow a richer and thicker narrative to occur. Critical theory was used to describe and interpret the voices of the participants from a social perspective. The data collected were analyzed using a constant comparative analysis technique. The participants revealed role models, negative stereotypes, peer pressure, social pressures, and misconceptions as some of the factors that influenced their perceptions of science careers. Results of this research suggest that by dispelling the misconceptions, educators can positively influence the attitudes and perceptions of

Construction Tender Subcontract Selection using Case-based Reasoning

Directory of Open Access Journals (Sweden)

Due Luu

2012-11-01

Full Text Available Obtaining competitive quotations from suitably qualified subcontractors at tender tim n significantly increase the chance of w1nmng a construction project. Amidst an increasingly growing trend to subcontracting in Australia, selecting appropriate subcontractors for a construction project can be a daunting task requiring the analysis of complex and dynamic criteria such as past performance, suitable experience, track record of competitive pricing, financial stability and so on. Subcontractor selection is plagued with uncertainty and vagueness and these conditions are difficul_t o represent in generalised sets of rules. DeciSIOns pertaining to the selection of subcontr:act?s tender time are usually based on the mtu1t1onand past experience of construction estimators. Case-based reasoning (CBR may be an appropriate method of addressing the chal_lenges of selecting subcontractors because CBR 1s able to harness the experiential knowledge of practitioners. This paper reviews the practicality and suitability of a CBR approach for subcontractor tender selection through the development of a prototype CBR procurement advisory system. In this system, subcontractor selection cases are represented by a set of attributes elicited from experienced construction estimators. The results indicate that CBR can enhance the appropriateness of the selection of subcontractors for construction projects.

Chemiluminescence analyzer of NOx as a high-throughput screening tool in selective catalytic reduction of NO

International Nuclear Information System (INIS)

Oh, Kwang Seok; Woo, Seong Ihl

2011-01-01

A chemiluminescence-based analyzer of NO x gas species has been applied for high-throughput screening of a library of catalytic materials. The applicability of the commercial NO x analyzer as a rapid screening tool was evaluated using selective catalytic reduction of NO gas. A library of 60 binary alloys composed of Pt and Co, Zr, La, Ce, Fe or W on Al 2 O 3 substrate was tested for the efficiency of NO x removal using a home-built 64-channel parallel and sequential tubular reactor. The NO x concentrations measured by the NO x analyzer agreed well with the results obtained using micro gas chromatography for a reference catalyst consisting of 1 wt% Pt on γ-Al 2 O 3 . Most alloys showed high efficiency at 275 °C, which is typical of Pt-based catalysts for selective catalytic reduction of NO. The screening with NO x analyzer allowed to select Pt-Ce (X) (X=1–3) and Pt–Fe (2) as the optimal catalysts for NO x removal: 73% NO x conversion was achieved with the Pt–Fe (2) alloy, which was much better than the results for the reference catalyst and the other library alloys. This study demonstrates a sequential high-throughput method of practical evaluation of catalysts for the selective reduction of NO.

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

Science.gov (United States)

2012-01-01

Background Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible. Results We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension – UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high-end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent

Highly Selective Enrichment of Glycopeptides Based on Zwitterionically Functionalized Soluble Nanopolymers

Science.gov (United States)

Cao, Weiqian; Huang, Jiangming; Jiang, Biyun; Gao, Xing; Yang, Pengyuan

2016-07-01

Efficient glycopeptides enrichment prior to mass spectrometry analysis is essential for glycoproteome study. ZIC-HILIC (zwitterionic hydrophilic interaction liquid chromatography) based glycopeptides enrichment approaches have been attracting more attention for several benefits like easy operating, high enrichment specificity and intact glycopeptide retained. In this study, Poly (amidoamine) dendrimer (PAMAM) was adopted for the synthesis of zwitterionically functionalized (ZICF) materials for glycopeptide enrichment. The multiple branched structure and good solubility of ZICF-PAMAM enables a sufficient interaction with glycopeptides. The ZICF-PAMAM combined with the FASP-mode enrichment strategy exhibits more superior performance compared with the existing methods. It has the minimum detectable concentration of femtomolar level and high recovery rate of over 90.01%, and can efficiently enrich glycopeptides from complex biological samples even for merely 0.1 μL human serum. The remarkable glycopeptides enrichment capacity of ZICF-PAMAM highlights the potential application in in-depth glycoproteome research, which may open up new opportunities for the development of glycoproteomics.

Perylene Diimide Based Fluorescent Dyes for Selective Sensing of Nitroaromatic Compounds: Selective Sensing in Aqueous Medium Across Wide pH Range.

Science.gov (United States)

Hariharan, P S; Pitchaimani, J; Madhu, Vedichi; Anthony, Savarimuthu Philip

2016-03-01

Water soluble perylenediimide based fluorophore salt, N,N'-bis(ethelenetrimethyl ammoniumiodide)-perylene-3,4,9,10-tetracarboxylicbisimide (PDI-1), has been used for selective fluorescence sensing of picric acid (PA) and 4-nitroaniline (4-NA) in organic as well as aqueous medium across wide pH range (1.0 to 10.0). PDI-1 showed strong fluorescence in dimethylformamide (DMF) (Φf = 0.26 (DMF) and moderate fluorescence in water. Addition of picric acid (PA) and 4-nitroaniline (4-NA) into PDI-1 in DMF/aqueous solution selectively quenches the fluorescence. The concentration dependent studies showed decrease of fluorescence linearly with increase of PA and 4-NA concentration. The interference studies demonstrate high selectivity for PA and 4-NA. Interestingly, PDI-1 showed selective fluorescence sensing of PA and 4-NA across wide pH range (1.0 to 10.0). Selective fluorescence sensing of PA and 4-NA has also been observed with trifluoroacetate (PDI-2), sulfate (PDI-3) salt of PDI-1 as well as octyl chain substituted PDI (PDI-4) without amine functionality. These studies suggest that PA and 4-NA might be having preferential interaction with PDI aromatic core and quenches the fluorescence. Thus PDI based dyes have been used for selective fluorescent sensing of explosive NACs for the first time to the best our knowledge.

Using Improved Entropy-Cloud Model to Select High-Speed Railway Express Freight Train Service Sites

Directory of Open Access Journals (Sweden)

Wencheng Huang

2017-01-01

Full Text Available High-speed railway (HSR express freight train service sites selection is critical to the development of China’s Third Party Logistics market. In this paper, we formulate an improved entropy-cloud model based approach to solve the HSR express sites selection problem for the first time. The basic data of the indicators, for example, existing railway network conditions, traffic environment, express freight market demand, and policy, will be used as the inputs. We apply improved entropy method to obtain each subindicator’s weight. The cloud model will be used to select and classify each station under evaluation.

A synbio approach for selection of highly expressed gene variants in Gram-positive bacteria

DEFF Research Database (Denmark)

Ferro, Roberto; Rennig, Maja; Hernández Rollán, Cristina

2018-01-01

with a long history in food fermentation. We have developed a synbio approach for increasing gene expression in two Gram-positive bacteria. First of all, the gene of interest was coupled to an antibiotic resistance gene to create a growth-based selection system. We then randomised the translation initiation...... region (TIR) preceding the gene of interest and selected clones that produced high protein titres, as judged by their ability to survive on high concentrations of antibiotic. Using this approach, we were able to significantly increase production of two industrially relevant proteins; sialidase in B....... subtilis and tyrosine ammonia lyase in L. lactis. Gram-positive bacteria are widely used to produce industrial enzymes. High titres are necessary to make the production economically feasible. The synbio approach presented here is a simple and inexpensive way to increase protein titres, which can be carried...

A novel method based on selective laser sintering for preparing high-performance carbon fibres/polyamide12/epoxy ternary composites

Science.gov (United States)

Zhu, Wei; Yan, Chunze; Shi, Yunsong; Wen, Shifeng; Liu, Jie; Wei, Qingsong; Shi, Yusheng

2016-09-01

A novel method based on selective laser sintering (SLS) process is proposed for the first time to prepare complex and high-performance carbon fibres/polyamide12/epoxy (CF/PA12/EP) ternary composites. The procedures are briefly described as follows: prepare polyamide12 (PA12) coated carbon fibre (CF) composite powder; build porous green parts by SLS; infiltrate the green parts with high-performance thermosetting epoxy (EP) resin; and finally cure the resin at high temperature. The obtained composites are a ternary composite system consisting of the matrix of novolac EP resin, the reinforcement of CFs and the transition thin layer of PA12 with a thickness of 595 nm. The SEM images and micro-CT analysis prove that the ternary system is a three-dimensional co-continuous structure and the reinforcement of CFs are well dispersed in the matrix of EP with the volume fraction of 31%. Mechanical tests show that the composites fabricated by this method yield an ultimate tensile strength of 101.03 MPa and a flexural strength of 153.43 MPa, which are higher than those of most of the previously reported SLS materials. Therefore, the process proposed in this paper shows great potential for manufacturing complex, lightweight and high-performance CF reinforced composite components in aerospace, automotive industries and other areas.

Feature Selection Based on Mutual Correlation

Czech Academy of Sciences Publication Activity Database

Haindl, Michal; Somol, Petr; Ververidis, D.; Kotropoulos, C.

2006-01-01

Roč. 19, č. 4225 (2006), s. 569-577 ISSN 0302-9743. [Iberoamerican Congress on Pattern Recognition. CIARP 2006 /11./. Cancun, 14.11.2006-17.11.2006] R&D Projects: GA AV ČR 1ET400750407; GA MŠk 1M0572; GA AV ČR IAA2075302 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : feature selection Subject RIV: BD - Theory of Information Impact factor: 0.402, year: 2005 http://library.utia.cas.cz/separaty/historie/haindl-feature selection based on mutual correlation.pdf

Designing the nanobiointerface of fluorescent nanodiamonds: highly selective targeting of glioma cancer cells.

Science.gov (United States)

Slegerova, Jitka; Hajek, Miroslav; Rehor, Ivan; Sedlak, Frantisek; Stursa, Jan; Hruby, Martin; Cigler, Petr

2015-01-14

Core-shell nanoparticles based on fluorescent nanodiamonds coated with a biocompatible N-(2-hydroxypropyl)methacrylamide copolymer shell were developed for background-free near-infrared imaging of cancer cells. The particles showed excellent colloidal stability in buffers and culture media. After conjugation with a cyclic RGD peptide they selectively targeted integrin αvβ3 receptors on glioblastoma cells with high internalization efficacy.

Highly spectrum-selective ultraviolet photodetector based on p-NiO/n-IGZO thin film heterojunction structure.

Science.gov (United States)

Li, H K; Chen, T P; Hu, S G; Li, X D; Liu, Y; Lee, P S; Wang, X P; Li, H Y; Lo, G Q

2015-10-19

Ultraviolet photodetector with p-n heterojunction is fabricated by magnetron sputtering deposition of n-type indium gallium zinc oxide (n-IGZO) and p-type nickel oxide (p-NiO) thin films on ITO glass. The performance of the photodetector is largely affected by the conductivity of the p-NiO thin film, which can be controlled by varying the oxygen partial pressure during the deposition of the p-NiO thin film. A highly spectrum-selective ultraviolet photodetector has been achieved with the p-NiO layer with a high conductivity. The results can be explained in terms of the "optically-filtering" function of the NiO layer.

Selective suppression of high-order harmonics within phase-matched spectral regions.

Science.gov (United States)

Lerner, Gavriel; Diskin, Tzvi; Neufeld, Ofer; Kfir, Ofer; Cohen, Oren

2017-04-01

Phase matching in high-harmonic generation leads to enhancement of multiple harmonics. It is sometimes desired to control the spectral structure within the phase-matched spectral region. We propose a scheme for selective suppression of high-order harmonics within the phase-matched spectral region while weakly influencing the other harmonics. The method is based on addition of phase-mismatched segments within a phase-matched medium. We demonstrate the method numerically in two examples. First, we show that one phase-mismatched segment can significantly suppress harmonic orders 9, 15, and 21. Second, we show that two phase-mismatched segments can efficiently suppress circularly polarized harmonics with one helicity over the other when driven by a bi-circular field. The new method may be useful for various applications, including the generation of highly helical bright attosecond pulses.

Impact of Menu Sequencing on Internet-Based Educational Module Selection

Science.gov (United States)

Bensley, Robert; Brusk, John J.; Rivas, Jason; Anderson, Judith V.

2006-01-01

Patterns of Internet-based menu item selection can occur for a number of reasons, many of which may not be based on interest in topic. It then becomes important to ensure menu order is devised in a way that ensures the greatest accuracy in matching user need with selection. This study examined the impact of menu rotation on the selection of…

Preparation of inorganic ion exchangers with high selectivity for lithium isotopes

International Nuclear Information System (INIS)

Oi, Takao

2004-01-01

Development of ion exchangers that show large lithium isotope effects is hoped for to establish highly efficient chromatographic processes of lithium isotope separation. In this paper, preparation, characterization, ion exchange properties, and lithium isotope selectivity of inorganic materials that have been and still are being studied by my research group at Sophia University are reviewed. They include manganese oxides-based ion exchangers, antimonic acids and titanium/zirconium phosphates-based ion exchangers. As a result, the lithium isotope separation effects that were one order of magnitude larger than those of organic ion exchangers were obtained. Some inorganic ion exchangers were found to show ion exchange rates more than comparable to those of organic ones. (author)

Simultaneous Channel and Feature Selection of Fused EEG Features Based on Sparse Group Lasso

Directory of Open Access Journals (Sweden)

Jin-Jia Wang

2015-01-01

Full Text Available Feature extraction and classification of EEG signals are core parts of brain computer interfaces (BCIs. Due to the high dimension of the EEG feature vector, an effective feature selection algorithm has become an integral part of research studies. In this paper, we present a new method based on a wrapped Sparse Group Lasso for channel and feature selection of fused EEG signals. The high-dimensional fused features are firstly obtained, which include the power spectrum, time-domain statistics, AR model, and the wavelet coefficient features extracted from the preprocessed EEG signals. The wrapped channel and feature selection method is then applied, which uses the logistical regression model with Sparse Group Lasso penalized function. The model is fitted on the training data, and parameter estimation is obtained by modified blockwise coordinate descent and coordinate gradient descent method. The best parameters and feature subset are selected by using a 10-fold cross-validation. Finally, the test data is classified using the trained model. Compared with existing channel and feature selection methods, results show that the proposed method is more suitable, more stable, and faster for high-dimensional feature fusion. It can simultaneously achieve channel and feature selection with a lower error rate. The test accuracy on the data used from international BCI Competition IV reached 84.72%.

A Brief Opportunity to Run Does Not Function as a Reinforcer for Mice Selected for High Daily Wheel-Running Rates

Science.gov (United States)

Belke, Terry W.; Garland, Theodore, Jr.

2007-01-01

Mice from replicate lines, selectively bred based on high daily wheel-running rates, run more total revolutions and at higher average speeds than do mice from nonselected control lines. Based on this difference it was assumed that selected mice would find the opportunity to run in a wheel a more efficacious consequence. To assess this assumption…

Highly Sensitive Fluorescence Probe Based on Functional SBA-15 for Selective Detection of Hg2+

Directory of Open Access Journals (Sweden)

Wang Xiaoyu

2010-01-01

Full Text Available Abstract An inorganic–organic hybrid fluorescence chemosensor (DA/SBA-15 was prepared by covalent immobilization of a dansylamide derivative into the channels of mesoporous silica material SBA-15 via (3-aminopropyltriethoxysilane (APTES groups. The primary hexagonally ordered mesoporous structure of SBA-15 was preserved after the grafting procedure. Fluorescence characterization shows that the obtained inorganic–organic hybrid composite is highly selective and sensitive to Hg2+ detection, suggesting the possibility for real-time qualitative or quantitative detection of Hg2+ and the convenience for potential application in toxicology and environmental science.

Fabrication of high efficacy selective solar absorbers

CSIR Research Space (South Africa)

Tile, N

2012-03-01

Full Text Available High efficiency tandem selective solar absorber materials of carbon in nickel oxide (C-NiO) composite were fabricated on an aluminium substrate using a simple and cost effective sol-gel process. The process involved preparation of carbon and nickel...

Robust Ground Target Detection by SAR and IR Sensor Fusion Using Adaboost-Based Feature Selection

Science.gov (United States)

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

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

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

Energy Technology Data Exchange (ETDEWEB)

Guo, Xuejiang; Tang, Keqi

2017-06-14

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers would ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode

Nanoporous amide networks based on tetraphenyladamantane for selective CO2capture

KAUST Repository

Zulfiqar, Sonia; Mantione, Daniele; El Tall, Omar; Sarwar, Muhammad Ilyas; Ruipé rez, Fernando; Rothenberger, Alexander; Mecerreyes, David

2016-01-01

Reduction of anthropogenic CO2 emissions and CO2 separation from post-combustion flue gases are among the imperative issues in the spotlight at present. Hence, it is highly desirable to develop efficient adsorbents for mitigating climate change with possible energy savings. Here, we report the design of a facile one pot catalyst-free synthetic protocol for the generation of three different nitrogen rich nanoporous amide networks (NANs) based on tetraphenyladamantane. Besides the porous architecture, CO2 capturing potential and high thermal stability, these NANs possess notable CO2/N2 selectivity with reasonable retention while increasing the temperature from 273 K to 298 K. The quantum chemical calculations also suggest that CO2 interacts mainly in the region of polar amide groups (-CONH-) present in NANs and this interaction is much stronger than that with N2 thus leading to better selectivity and affirming them as promising contenders for efficient gas separation. © The Royal Society of Chemistry 2016.

Nanoporous amide networks based on tetraphenyladamantane for selective CO2capture

KAUST Repository

Zulfiqar, Sonia

2016-04-19

Reduction of anthropogenic CO2 emissions and CO2 separation from post-combustion flue gases are among the imperative issues in the spotlight at present. Hence, it is highly desirable to develop efficient adsorbents for mitigating climate change with possible energy savings. Here, we report the design of a facile one pot catalyst-free synthetic protocol for the generation of three different nitrogen rich nanoporous amide networks (NANs) based on tetraphenyladamantane. Besides the porous architecture, CO2 capturing potential and high thermal stability, these NANs possess notable CO2/N2 selectivity with reasonable retention while increasing the temperature from 273 K to 298 K. The quantum chemical calculations also suggest that CO2 interacts mainly in the region of polar amide groups (-CONH-) present in NANs and this interaction is much stronger than that with N2 thus leading to better selectivity and affirming them as promising contenders for efficient gas separation. © The Royal Society of Chemistry 2016.

A Distributed Dynamic Super Peer Selection Method Based on Evolutionary Game for Heterogeneous P2P Streaming Systems

Directory of Open Access Journals (Sweden)

Jing Chen

2013-01-01

Full Text Available Due to high efficiency and good scalability, hierarchical hybrid P2P architecture has drawn more and more attention in P2P streaming research and application fields recently. The problem about super peer selection, which is the key problem in hybrid heterogeneous P2P architecture, is becoming highly challenging because super peers must be selected from a huge and dynamically changing network. A distributed super peer selection (SPS algorithm for hybrid heterogeneous P2P streaming system based on evolutionary game is proposed in this paper. The super peer selection procedure is modeled based on evolutionary game framework firstly, and its evolutionarily stable strategies are analyzed. Then a distributed Q-learning algorithm (ESS-SPS according to the mixed strategies by analysis is proposed for the peers to converge to the ESSs based on its own payoff history. Compared to the traditional randomly super peer selection scheme, experiments results show that the proposed ESS-SPS algorithm achieves better performance in terms of social welfare and average upload rate of super peers and keeps the upload capacity of the P2P streaming system increasing steadily with the number of peers increasing.

Why do adults entitled to free or highly subsidized dental services select fully out-of-pocket-paid care?

Science.gov (United States)

Bayat, Fariborz; Vehkalahti, Miira M; Murtomaa, Heikki; Tala, Heikki

2010-02-01

To investigate patients' reasons for selecting a dental clinic given their choice of free or highly-subsidized dental services. The study was based on cross-sectional data obtained through phone interviews with adults in Tehran, Iran. The present study included those entitled to free or highly-subsidized dental services (n = 726). The data covered the patients' awareness of subsidized dental services and type of dental clinic for their most recent visit and their reasons for selecting that clinic. Awareness of subsidized dental services was dichotomized as being either aware or unaware of such subsidy. The type of clinic was dichotomized as providing either free or highly-subsidized (FHS) or fully out-of-pocket paid (FOP) services. Free format answers about the subjects' reasons for selecting a particular clinic were later sub-grouped as: convenient access, good technical aspects, good interpersonal aspects, low or reasonable fees, recommendation by a friend, and no reason. Socio-demographic status was based on background. Data analysis included the chi-square test and logistic regression model. Of the subjects (n = 726), 60% were women and 58% were under 35 years of age. The subjects' mean age was 33.5 years with no difference by gender (P = 0.24) and the majority had public insurance (91%). Of all the subjects, 60% selected FOP. Good interpersonal aspects were the strongest reason for selecting FOP (OR = 4.6), follow by good technical aspects (OR = 2.3). Those subjects who were unaware of their benefit had 4.6 times the odds of selecting FOP. Despite the opportunity to use highly-subsidized dental services, good interpersonal and good technical aspects lead patients to select private dentists and to pay fully out of pocket.

Model-based Clustering of High-Dimensional Data in Astrophysics

Science.gov (United States)

Bouveyron, C.

2016-05-01

The nature of data in Astrophysics has changed, as in other scientific fields, in the past decades due to the increase of the measurement capabilities. As a consequence, data are nowadays frequently of high dimensionality and available in mass or stream. Model-based techniques for clustering are popular tools which are renowned for their probabilistic foundations and their flexibility. However, classical model-based techniques show a disappointing behavior in high-dimensional spaces which is mainly due to their dramatical over-parametrization. The recent developments in model-based classification overcome these drawbacks and allow to efficiently classify high-dimensional data, even in the "small n / large p" situation. This work presents a comprehensive review of these recent approaches, including regularization-based techniques, parsimonious modeling, subspace classification methods and classification methods based on variable selection. The use of these model-based methods is also illustrated on real-world classification problems in Astrophysics using R packages.

Test methods for selection of materials of construction for high-level radioactive waste vitrification. Revision

International Nuclear Information System (INIS)

Bickford, D.F.; Corbett, R.A.; Morrison, W.S.

1986-01-01

Candidate materials of construction were evaluated for a facility at the Department of Energy's Savannah River Plant to vitrify high-level radioactive waste. Limited operating experience was available under the corrosive conditions of the complex vitrification process. The objective of the testing program was to provide a high degree of assurance that equipment will meet or exceed design lifetimes. To meet this objective in reasonable time and minimum cost, a program was designed consisting of a combination of coupon immersion and electrochemical laboratory tests and pilot-scale tests. Stainless steels and nickel-based alloys were tested. Alloys that were most resistant to general and local attack contained nickel, molybdenum (>9%), and chromium (where Cr + Mo > 30%). Alloy C-276 was selected as the reference material for process equipment. Stellite 6 was selected for abrasive service in the presence of formic acid. Alloy 690 and ALLCORR were selected for specific applications

Evaluation of gene importance in microarray data based upon probability of selection

Directory of Open Access Journals (Sweden)

Fu Li M

2005-03-01

Full Text Available Abstract Background Microarray devices permit a genome-scale evaluation of gene function. This technology has catalyzed biomedical research and development in recent years. As many important diseases can be traced down to the gene level, a long-standing research problem is to identify specific gene expression patterns linking to metabolic characteristics that contribute to disease development and progression. The microarray approach offers an expedited solution to this problem. However, it has posed a challenging issue to recognize disease-related genes expression patterns embedded in the microarray data. In selecting a small set of biologically significant genes for classifier design, the nature of high data dimensionality inherent in this problem creates substantial amount of uncertainty. Results Here we present a model for probability analysis of selected genes in order to determine their importance. Our contribution is that we show how to derive the P value of each selected gene in multiple gene selection trials based on different combinations of data samples and how to conduct a reliability analysis accordingly. The importance of a gene is indicated by its associated P value in that a smaller value implies higher information content from information theory. On the microarray data concerning the subtype classification of small round blue cell tumors, we demonstrate that the method is capable of finding the smallest set of genes (19 genes with optimal classification performance, compared with results reported in the literature. Conclusion In classifier design based on microarray data, the probability value derived from gene selection based on multiple combinations of data samples enables an effective mechanism for reducing the tendency of fitting local data particularities.

Norm based Threshold Selection for Fault Detectors

DEFF Research Database (Denmark)

Rank, Mike Lind; Niemann, Henrik

1998-01-01

The design of fault detectors for fault detection and isolation (FDI) in dynamic systems is considered from a norm based point of view. An analysis of norm based threshold selection is given based on different formulations of FDI problems. Both the nominal FDI problem as well as the uncertain FDI...... problem are considered. Based on this analysis, a performance index based on norms of the involved transfer functions is given. The performance index allows us also to optimize the structure of the fault detection filter directly...

Data re-arranging techniques leading to proper variable selections in high energy physics

Science.gov (United States)

Kůs, Václav; Bouř, Petr

2017-12-01

We introduce a new data based approach to homogeneity testing and variable selection carried out in high energy physics experiments, where one of the basic tasks is to test the homogeneity of weighted samples, mainly the Monte Carlo simulations (weighted) and real data measurements (unweighted). This technique is called ’data re-arranging’ and it enables variable selection performed by means of the classical statistical homogeneity tests such as Kolmogorov-Smirnov, Anderson-Darling, or Pearson’s chi-square divergence test. P-values of our variants of homogeneity tests are investigated and the empirical verification through 46 dimensional high energy particle physics data sets is accomplished under newly proposed (equiprobable) quantile binning. Particularly, the procedure of homogeneity testing is applied to re-arranged Monte Carlo samples and real DATA sets measured at the particle accelerator Tevatron in Fermilab at DØ experiment originating from top-antitop quark pair production in two decay channels (electron, muon) with 2, 3, or 4+ jets detected. Finally, the variable selections in the electron and muon channels induced by the re-arranging procedure for homogeneity testing are provided for Tevatron top-antitop quark data sets.

Repair of Ischemic Injury by Pluripotent Stem Cell Based Cell Therapy without Teratoma through Selective Photosensitivity

Directory of Open Access Journals (Sweden)

Seung-Ju Cho

2015-12-01

Full Text Available Stem-toxic small molecules have been developed to induce selective cell death of pluripotent stem cells (PSCs to lower the risk of teratoma formation. However, despite their high efficacies, chemical-based approaches may carry unexpected toxicities on specific differentiated cell types. Herein, we took advantage of KillerRed (KR as a suicide gene, to selectively induce phototoxicity using visible light via the production of reactive oxygen species. PSCs in an undifferentiated state that exclusively expressed KR (KR-PSCs were eliminated by a single exposure to visible light. This highly selective cell death in KR-PSCs was exploited to successfully inhibit teratoma formation. In particular, endothelial cells from KR-mPSCs remained fully functional in vitro and sufficient to repair ischemic injury in vivo regardless of light exposure, suggesting that a genetic approach in which KR is expressed in a tightly controlled manner would be a viable strategy to inhibit teratoma formation for future safe PSC-based therapies.

SNP calling using genotype model selection on high-throughput sequencing data

KAUST Repository

You, Na

2012-01-16

Motivation: A review of the available single nucleotide polymorphism (SNP) calling procedures for Illumina high-throughput sequencing (HTS) platform data reveals that most rely mainly on base-calling and mapping qualities as sources of error when calling SNPs. Thus, errors not involved in base-calling or alignment, such as those in genomic sample preparation, are not accounted for.Results: A novel method of consensus and SNP calling, Genotype Model Selection (GeMS), is given which accounts for the errors that occur during the preparation of the genomic sample. Simulations and real data analyses indicate that GeMS has the best performance balance of sensitivity and positive predictive value among the tested SNP callers. © The Author 2012. Published by Oxford University Press. All rights reserved.

Selective high-affinity polydentate ligands and methods of making such

Energy Technology Data Exchange (ETDEWEB)

Denardo, Sally J.; Denardo, Gerald L.; Balhorn, Rodney L.

2018-02-06

This invention provides novel polydentate selective high affinity ligands (SHALs) that can be used in a variety of applications in a manner analogous to the use of antibodies. SHALs typically comprise a multiplicity of ligands that each bind different region son the target molecule. The ligands are joined directly or through a linker thereby forming a polydentate moiety that typically binds the target molecule with high selectivity and avidity.

Fabrication of a highly selective cadmium (II) sensor based on 1,13-bis(8-quinolyl)-1,4,7,10,13-pentaoxatridecane as a supramolecular ionophore

Energy Technology Data Exchange (ETDEWEB)

Ghaemi, Arezoo, E-mail: arezooghaemi@yahoo.com; Tavakkoli, Haman; Mombeni, Tayebeh

2014-05-01

A new cadmium (II) ion selective sensor based on 1,13-bis(8-quinolyl)-1,4,7,10,13-pentaoxatridecane (kryptofix5) as a supramolecular carrier has been developed. The membrane solutions containing polyvinyl chloride (PVC), plasticizer, sodium tetraphenylborate (NaTPB) as a lipophilic ionic additive and kryptofix5 as an ionophore were directly coated on the surface of graphite rods. The best composition of the coated membrane (w/w%) was found to be: 30.0% PVC, 61.0% dioctyl sebacate (DOS), 6.0% NaTPB and 3.0% kryptofix5. The sensor indicates a good linear response for Cd{sup 2+} cation over a wide concentration range from 1.0 × 10{sup −5} to 1.0 × 10{sup −1} M with a Nernstian slope of 29.8 ± 0.1 mV/decade and the detection limit is 8.4 × 10{sup −6} M. The response time of the sensor is 15 s and it can be used for 7 weeks without significant drift in potential. The sensor operates in the wide pH range of 1.0–6.0. This sensor reveals a very good selectivity toward Cd{sup 2+} ion over a wide range of alkali, transition and heavy metal cations. The sensor was used as an indicator electrode for potentiometric titration of Cd{sup 2+} using sodium fluoride and ethylenediaminetetraacetic acid (EDTA) solutions with a sharp potential change that occurred at the end point. In addition, the proposed sensor was successfully used for determination of Cd{sup 2+} cation in real water samples. - Graphical abstract: Fabrication of a highly selective cadmium (II) sensor based on 1,13-bis(8-quinolyl)-1,4,7,10,13-pentaoxatridecane as a supramolecular ionophore. - Highlights: • Fabrication of a novel Cd{sup 2+} selective sensor with high sensitivity and selectivity • Using fabricated sensor in a wide pH range with fast response time • Replacing expensive techniques with this low cost sensor with low detection limit • Excellent capability of this sensor for measuring Cd{sup 2+} in real samples.

Stock selection of high-dose-irradiation-resistant materials for filter press under high-dose irradiation operation

International Nuclear Information System (INIS)

Ishiyama, Shintaro; Minami, Mamoru; Hara, Kouji; Yamashita, Manabu

2015-01-01

In a volume reduction process for the decontamination of contained soil, the performance degradation of a filter press is expected owing to material deterioration under high-dose irradiation. Eleven-stock selection of candidate materials including polymers, fibers and rubbers for the filter press was conducted to achieve a high performance of volume reduction of contaminated soil and the following results were derived. Crude rubber and nylon were selected as prime candidates for packing, diaphragm and filter plate materials. Polyethylene was also selected as a prime candidate for the filter cloth material. (author)

[Electroencephalogram Feature Selection Based on Correlation Coefficient Analysis].

Science.gov (United States)

Zhou, Jinzhi; Tang, Xiaofang

2015-08-01

In order to improve the accuracy of classification with small amount of motor imagery training data on the development of brain-computer interface (BCD systems, we proposed an analyzing method to automatically select the characteristic parameters based on correlation coefficient analysis. Throughout the five sample data of dataset IV a from 2005 BCI Competition, we utilized short-time Fourier transform (STFT) and correlation coefficient calculation to reduce the number of primitive electroencephalogram dimension, then introduced feature extraction based on common spatial pattern (CSP) and classified by linear discriminant analysis (LDA). Simulation results showed that the average rate of classification accuracy could be improved by using correlation coefficient feature selection method than those without using this algorithm. Comparing with support vector machine (SVM) optimization features algorithm, the correlation coefficient analysis can lead better selection parameters to improve the accuracy of classification.

A highly selective and sensitive "turn-on" fluorescence chemodosimeter for the detection of mustard gas.

Science.gov (United States)

Raghavender Goud, D; Purohit, Ajay Kumar; Tak, Vijay; Dubey, Devendra Kumar; Kumar, Pravin; Pardasani, Deepak

2014-10-21

A new chemodosimetric protocol based on a tandem S-alkylation followed by desulfurisation reaction of rhodamine-thioamide with mustard gas is reported. The chemodosimeter is highly selective for potential DNA alkylating agents like sulfur mustard, over other simple alkyl halides with the limit of detection of 4.75 μM.

Fusion set selection with surrogate metric in multi-atlas based image segmentation

International Nuclear Information System (INIS)

Zhao, Tingting; Ruan, Dan

2016-01-01

Multi-atlas based image segmentation sees unprecedented opportunities but also demanding challenges in the big data era. Relevant atlas selection before label fusion plays a crucial role in reducing potential performance loss from heterogeneous data quality and high computation cost from extensive data. This paper starts with investigating the image similarity metric (termed ‘surrogate’), an alternative to the inaccessible geometric agreement metric (termed ‘oracle’) in atlas relevance assessment, and probes into the problem of how to select the ‘most-relevant’ atlases and how many such atlases to incorporate. We propose an inference model to relate the surrogates and the oracle geometric agreement metrics. Based on this model, we quantify the behavior of the surrogates in mimicking oracle metrics for atlas relevance ordering. Finally, analytical insights on the choice of fusion set size are presented from a probabilistic perspective, with the integrated goal of including the most relevant atlases and excluding the irrelevant ones. Empirical evidence and performance assessment are provided based on prostate and corpus callosum segmentation. (paper)

A selective iodide ion sensor electrode based on functionalized ZnO nanotubes.

Science.gov (United States)

Ibupoto, Zafar Hussain; Khun, Kimleang; Willander, Magnus

2013-02-04

In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF) was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10-6 to 1 × 10-1 M) and excellent sensitivity of -62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10-7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples.

A Selective Iodide Ion Sensor Electrode Based on Functionalized ZnO Nanotubes

Directory of Open Access Journals (Sweden)

Magnus Willander

2013-02-01

Full Text Available In this research work, ZnO nanotubes were fabricated on a gold coated glass substrate through chemical etching by the aqueous chemical growth method. For the first time a nanostructure-based iodide ion selective electrode was developed. The ZnO nanotubes were functionalized with miconazole ion exchanger and the electromotive force (EMF was measured by the potentiometric method. The iodide ion sensor exhibited a linear response over a wide range of concentrations (1 × 10−6 to 1 × 10−1 M and excellent sensitivity of –62 ± 1 mV/decade. The detection limit of the proposed sensor was found to be 5 × 10−7 M. The effects of pH, temperature, additive, plasticizer and stabilizer on the potential response of iodide ion selective electrode were also studied. The proposed iodide ion sensor demonstrated a fast response time of less than 5 s and high selectivity against common organic and the inorganic anions. All the obtained results revealed that the iodide ion sensor based on functionalized ZnO nanotubes may be used for the detection of iodide ion in environmental water samples, pharmaceutical products and other real samples.

Multispectral iris recognition based on group selection and game theory

Science.gov (United States)

Ahmad, Foysal; Roy, Kaushik

2017-05-01

A commercially available iris recognition system uses only a narrow band of the near infrared spectrum (700-900 nm) while iris images captured in the wide range of 405 nm to 1550 nm offer potential benefits to enhance recognition performance of an iris biometric system. The novelty of this research is that a group selection algorithm based on coalition game theory is explored to select the best patch subsets. In this algorithm, patches are divided into several groups based on their maximum contribution in different groups. Shapley values are used to evaluate the contribution of patches in different groups. Results show that this group selection based iris recognition

SELECTION OF RECIPIENTS FOR HEART TRANSPLANTATION BASED ON URGENCY STATUS

Directory of Open Access Journals (Sweden)

O. A. Sujayeva

2014-01-01

Full Text Available The article provides the overview of current international recommendations dedicated to selection of heart transplantation recipients based on urgency status. Authors found that cardiopulmonary bicycle stress test allowed to reveal additional criteria of high death risk within 1 year. These additional criteria were: the maximal oxygen consumption VO2max < 30% of the expected considering the age; VD/VT (ratio of physiologic dead space over tidal volume increasing during the test; maximal tolerance to physical loading ≤50 Wt and/or < 20% of the expected considering the age. Authors created mathematical model for prediction of death within 1 year based on above mentioned data. Special software estimating the probability of death within 1 year was also created.

Development of Base Transceiver Station Selection Algorithm for ...

African Journals Online (AJOL)

TEMS) equipment was carried out on the existing BTSs, and a linear algorithm optimization program based on the spectral link efficiency of each BTS was developed, the output of this site optimization gives the selected number of base station sites ...

A Simple K-Map Based Variable Selection Scheme in the Direct ...

African Journals Online (AJOL)

A multiplexer with (n-l) data select inputs can realise directly a function of n variables. In this paper, a simple k-map based variable selection scheme is proposed such that an n variable logic function can be synthesised using a multiplexer with (n-q) data input variables and q data select variables. The procedure is based on ...

Highly selective and sensitive fluorogenic ferric probes based on aggregation-enhanced emission with - SiMe3 substituted polybenzene

Science.gov (United States)

Wang, Xuefeng; Wang, Hua; Jiang, Qin; Lee, Yong-Ill; Feng, Shengyu; Liu, Hong-Guo

2018-01-01

In this study, thiophene was linked to polybenzene to generate novel fluorescent probes, namely 3,4-diphenyl-2,5-di(2-thienyl)phenyl-trimethylsilane (DPTB-TMS) with a - SiMe3 substituent and 3,4-diphenyl-2,5-di(2-thienyl)phenyl (DPTB) without the - SiMe3 substituent, respectively. Both of the two compounds exhibit aggregation-enhanced emission (AEE) properties in tetrahydrofuran/water mixtures due to restricted intramolecular rotation of the peripheral groups, which make the two compounds good candidates for the detection of Fe3 + ions in aqueous-based solutions. The fluorescence intensity of the two compounds decreases immediately and obviously upon addition of a trace amount of Fe3 +, and decreases continuously as the amount of Fe3 + increases. The fluorescence was quenched to 92% of its initial intensity when the amount of Fe3 + ions reached 6 μmol for DPTB-TMS and to 80% for DPTB in the systems, indicating that the compound with the - SiMe3 group is a more effective probe. The detection limit was found to be 1.17 μM (65 ppb). The detection mechanism is proposed to be static quenching. DPTB-TMS is highly efficient for the detection of ferric ions even in the presence of other metal ions. In addition, the method is also successfully applied to the detection of ferric ions in water, blood serum, or solid films. This indicates that these polybenzene compounds can be applied as low-cost, high selectivity, and high efficiency Fe3 + probes in water or in clinical applications.

“Turn-off” fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides

Energy Technology Data Exchange (ETDEWEB)

Fan, Yao; Liu, Li; Sun, Donglei; Lan, Hanyue [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China); Fu, Haiyan, E-mail: fuhaiyan@mail.scuec.edu.cn [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China); Yang, Tianming, E-mail: tmyang@mail.scuec.edu.cn [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China); She, Yuanbin, E-mail: sheyb@zjut.edu.cn [State Key Laboratory Breeding Base of Green Chemistry-Synthesis Technology, College of Chemical Engineering, Zhejiang University of Technology, Hangzhou 310032 (China); Ni, Chuang [The Modernization Engineering Technology Research Center of Ethnic Minority Medicine of Hubei Province, College of Pharmacy, South-Central University for Nationalities, Wuhan 430074 (China)

2016-04-15

As a popular detection model, the fluorescence “turn-off” sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence “turn-off” model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10{sup −8} mol L{sup −1} and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. - Highlights: • A new model based on double QDs is established for pesticide residues detection. • The fluorescent data array sensor is coupled with chmometrics methods. • The sensor can be highly sensitive and selective detection in actual samples.

“Turn-off” fluorescent data array sensor based on double quantum dots coupled with chemometrics for highly sensitive and selective detection of multicomponent pesticides

International Nuclear Information System (INIS)

Fan, Yao; Liu, Li; Sun, Donglei; Lan, Hanyue; Fu, Haiyan; Yang, Tianming; She, Yuanbin; Ni, Chuang

2016-01-01

As a popular detection model, the fluorescence “turn-off” sensor based on quantum dots (QDs) has already been successfully employed in the detections of many materials, especially in the researches on the interactions between pesticides. However, the previous studies are mainly focused on simple single track or the comparison based on similar concentration of drugs. In this work, a new detection method based on the fluorescence “turn-off” model with water-soluble ZnCdSe and CdSe QDs simultaneously as the fluorescent probes is established to detect various pesticides. The fluorescence of the two QDs can be quenched by different pesticides with varying degrees, which leads to the differences in positions and intensities of two peaks. By combining with chemometrics methods, all the pesticides can be qualitative and quantitative respectively even in real samples with the limit of detection was 2 × 10"−"8 mol L"−"1 and a recognition rate of 100%. This work is, to the best of our knowledge, the first report on the detection of pesticides based on the fluorescence quenching phenomenon of double quantum dots combined with chemometrics methods. What's more, the excellent selectivity of the system has been verified in different mediums such as mixed ion disruption, waste water, tea and water extraction liquid drugs. - Highlights: • A new model based on double QDs is established for pesticide residues detection. • The fluorescent data array sensor is coupled with chmometrics methods. • The sensor can be highly sensitive and selective detection in actual samples.

A checkerboard selective absorber with excellent spectral selectivity

Energy Technology Data Exchange (ETDEWEB)

Yang, Liu, E-mail: optyang@zju.edu.cn [Centre for Optical and Electromagnetic Research, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310058 (China); School of Electrical, Computer, and Engineering, Arizona State University, Tempe, Arizona 85287 (United States); Mo, Lei; Chen, Tuo [Centre for Optical and Electromagnetic Research, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310058 (China); Department of Physics, Zhejiang University, Hangzhou 310027 (China); Forsberg, Erik [Centre for Optical and Electromagnetic Research, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310058 (China); He, Sailing [Centre for Optical and Electromagnetic Research, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310058 (China); Department of Electromagnetic Engineering, JORCEP, Roy Institute of Technology (KTH), S-100 44 Stockholm (Sweden)

2015-11-14

A selective absorber with excellent spectral selectivity is proposed and analyzed. The absorber is based on a germanium (Ge) checkerboard on top of a tantalum (Ta) substrate. At wavelengths shorter than the 1.2 μm cutoff, a very high absorption is achieved due to strong cavity resonances in the Ge nanosquares, and their interactions with adjacent nanocavities and the bottom Ta substrate. At longer wavelengths, absorption is greatly suppressed due to destructive interference between the transparent checkerboard layer and the highly reflective Ta substrate. To better describe the superior selectivity of our configuration, a new figure of merit (FOM) is introduced. We observe a FOM value of 0.88 compared to 0.69 for its planar counterpart. We also conduct a thermal analysis to verify the excellent selectivity of our absorber. A high temperature can be achieved and maintained, promising good potential for applications in solar thermophotovoltaic systems.

Hydrogen bond based smart polymer for highly selective and tunable capture of multiply phosphorylated peptides.

Science.gov (United States)

Qing, Guangyan; Lu, Qi; Li, Xiuling; Liu, Jing; Ye, Mingliang; Liang, Xinmiao; Sun, Taolei

2017-09-06

Multisite phosphorylation is an important and common mechanism for finely regulating protein functions and subsequent cellular responses. However, this study is largely restricted by the difficulty to capture low-abundance multiply phosphorylated peptides (MPPs) from complex biosamples owing to the limitation of enrichment materials and their interactions with phosphates. Here we show that smart polymer can serve as an ideal platform to resolve this challenge. Driven by specific but tunable hydrogen bonding interactions, the smart polymer displays differential complexation with MPPs, singly phosphorylated and non-modified peptides. Importantly, MPP binding can be modulated conveniently and precisely by solution conditions, resulting in highly controllable MPP adsorption on material surface. This facilitates excellent performance in MPP enrichment and separation from model proteins and real biosamples. High enrichment selectivity and coverage, extraordinary adsorption capacities and recovery towards MPPs, as well as high discovery rates of unique phosphorylation sites, suggest its great potential in phosphoproteomics studies.Capture of low-abundance multiply phosphorylated peptides (MPPs) is difficult due to limitation of enrichment materials and their interactions with phosphates. Here the authors show, a smart polymer driven by specific but tunable hydrogen bonding interactions can differentially complex with MPPs, singly phosphorylated and non-modified peptides.

High-energy, high-rate consolidation of tungsten and tungsten-based composite powders

Energy Technology Data Exchange (ETDEWEB)

Raghunathan, S.K.; Persad, C.; Bourell, D.L.; Marcus, H.L. (Center for Materials Science and Engineering, Univ. of Texas, Austin (USA))

1991-01-20

Tungsten and tungsten-based heavy alloys are well known for their superior mechanical properties at elevated temperatures. However, unalloyed tungsten is difficult to consolidate owing to its very high melting temperature (3683 K). The additions of small amounts of low-melting elements such as iron, nickel, cobalt and copper, facilitate the powder processing of dense heavy alloys at moderate temperatures. Energetic high-current pulses have been used recently for powder consolidation. In this paper, the use of a homopolar generator as a power source to consolidate selected tungsten and tungsten-based alloys is examined. Various materials were consolidated including unalloyed tungsten, W-Nb, W-Ni, and tungsten heavy alloy with boron carbide. The effect of process parameters such as pressure and specific energy input on the consolidation of different alloy systems is described in terms of microstructure and property relationships. (orig.).

[Experimental and computation studies of polar solvation

International Nuclear Information System (INIS)

1990-01-01

This report from the Pennsylvania State University contains seven sections: (1) radiative rate effects in solvatlvatochromic probes; (2) intramolecular charge transfer reactions; (3) Solvation dynamics in low temperature alcohols; (4) Ionic solvation dynamics; (5) solvation and proton-transfer dynamics in 7-azaindole; (6) computer simulations of solvation dynamics; (7) solvation in supercritical fluids. 20 refs., 11 figs

Genomic selection in plant breeding.

Science.gov (United States)

Newell, Mark A; Jannink, Jean-Luc

2014-01-01

Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor and major marker effects. Thus, the GEBV may capture more of the genetic variation for the particular trait under selection.

Absolute cosine-based SVM-RFE feature selection method for prostate histopathological grading.

Science.gov (United States)

Sahran, Shahnorbanun; Albashish, Dheeb; Abdullah, Azizi; Shukor, Nordashima Abd; Hayati Md Pauzi, Suria

2018-04-18

Feature selection (FS) methods are widely used in grading and diagnosing prostate histopathological images. In this context, FS is based on the texture features obtained from the lumen, nuclei, cytoplasm and stroma, all of which are important tissue components. However, it is difficult to represent the high-dimensional textures of these tissue components. To solve this problem, we propose a new FS method that enables the selection of features with minimal redundancy in the tissue components. We categorise tissue images based on the texture of individual tissue components via the construction of a single classifier and also construct an ensemble learning model by merging the values obtained by each classifier. Another issue that arises is overfitting due to the high-dimensional texture of individual tissue components. We propose a new FS method, SVM-RFE(AC), that integrates a Support Vector Machine-Recursive Feature Elimination (SVM-RFE) embedded procedure with an absolute cosine (AC) filter method to prevent redundancy in the selected features of the SV-RFE and an unoptimised classifier in the AC. We conducted experiments on H&E histopathological prostate and colon cancer images with respect to three prostate classifications, namely benign vs. grade 3, benign vs. grade 4 and grade 3 vs. grade 4. The colon benchmark dataset requires a distinction between grades 1 and 2, which are the most difficult cases to distinguish in the colon domain. The results obtained by both the single and ensemble classification models (which uses the product rule as its merging method) confirm that the proposed SVM-RFE(AC) is superior to the other SVM and SVM-RFE-based methods. We developed an FS method based on SVM-RFE and AC and successfully showed that its use enabled the identification of the most crucial texture feature of each tissue component. Thus, it makes possible the distinction between multiple Gleason grades (e.g. grade 3 vs. grade 4) and its performance is far superior to

Targeting hunter distribution based on host resource selection and kill sites to manage disease risk.

Science.gov (United States)

Dugal, Cherie J; van Beest, Floris M; Vander Wal, Eric; Brook, Ryan K

2013-10-01

Endemic and emerging diseases are rarely uniform in their spatial distribution or prevalence among cohorts of wildlife. Spatial models that quantify risk-driven differences in resource selection and hunter mortality of animals at fine spatial scales can assist disease management by identifying high-risk areas and individuals. We used resource selection functions (RSFs) and selection ratios (SRs) to quantify sex- and age-specific resource selection patterns of collared (n = 67) and hunter-killed (n = 796) nonmigratory elk (Cervus canadensis manitobensis) during the hunting season between 2002 and 2012, in southwestern Manitoba, Canada. Distance to protected area was the most important covariate influencing resource selection and hunter-kill sites of elk (AICw = 1.00). Collared adult males (which are most likely to be infected with bovine tuberculosis (Mycobacterium bovis) and chronic wasting disease) rarely selected for sites outside of parks during the hunting season in contrast to adult females and juvenile males. The RSFs showed selection by adult females and juvenile males to be negatively associated with landscape-level forest cover, high road density, and water cover, whereas hunter-kill sites of these cohorts were positively associated with landscape-level forest cover and increasing distance to streams and negatively associated with high road density. Local-level forest was positively associated with collared animal locations and hunter-kill sites; however, selection was stronger for collared juvenile males and hunter-killed adult females. In instances where disease infects a metapopulation and eradication is infeasible, a principle goal of management is to limit the spread of disease among infected animals. We map high-risk areas that are regularly used by potentially infectious hosts but currently underrepresented in the distribution of kill sites. We present a novel application of widely available data to target hunter distribution based on host resource

A Meta-Heuristic Regression-Based Feature Selection for Predictive Analytics

Directory of Open Access Journals (Sweden)

Bharat Singh

2014-11-01

Full Text Available A high-dimensional feature selection having a very large number of features with an optimal feature subset is an NP-complete problem. Because conventional optimization techniques are unable to tackle large-scale feature selection problems, meta-heuristic algorithms are widely used. In this paper, we propose a particle swarm optimization technique while utilizing regression techniques for feature selection. We then use the selected features to classify the data. Classification accuracy is used as a criterion to evaluate classifier performance, and classification is accomplished through the use of k-nearest neighbour (KNN and Bayesian techniques. Various high dimensional data sets are used to evaluate the usefulness of the proposed approach. Results show that our approach gives better results when compared with other conventional feature selection algorithms.

Novel extractants with high selectivity for valuable metals in seawater. Calixarene derivatives

International Nuclear Information System (INIS)

Kakoi, Takahiko; Goto, Masahiro

1997-01-01

Seawater contains various valuable metals such as uranium and lithium. Therefore, attempts are being made to develop highly selective extractants which recognize target metal ions in reclaimed seawater. In this review, we have focused our study on the application of novel cyclic compound calixarene based extractants. A novel host compound calixarene, which is a cyclic compound connecting some phenol rings, is capable of forming several different extractant ring sizes and introducing various kinds of functional groups towards targeting of metal ions in seawater. Therefore, calixarene derivatives are capable of extracting valuable metals such as uranium, alkaline metals, heavy metals, rare earth metals and noble metals selectively by varying structural ring size and functional groups. The novel host compound calixarene has given promising results which line it up as a potential extractant for the separation of valuable metal ions in seawater. (author)

Supplier selection based on multi-criterial AHP method

Directory of Open Access Journals (Sweden)

Jana Pócsová

2010-03-01

Full Text Available This paper describes a case-study of supplier selection based on multi-criterial Analytic Hierarchy Process (AHP method.It is demonstrated that using adequate mathematical method can bring us “unprejudiced” conclusion, even if the alternatives (suppliercompanies are very similar in given selection-criteria. The result is the best possible supplier company from the viewpoint of chosen criteriaand the price of the product.

Automatic learning-based beam angle selection for thoracic IMRT

International Nuclear Information System (INIS)

Amit, Guy; Marshall, Andrea; Purdie, Thomas G.; Jaffray, David A.; Levinshtein, Alex; Hope, Andrew J.; Lindsay, Patricia; Pekar, Vladimir

2015-01-01

Purpose: The treatment of thoracic cancer using external beam radiation requires an optimal selection of the radiation beam directions to ensure effective coverage of the target volume and to avoid unnecessary treatment of normal healthy tissues. Intensity modulated radiation therapy (IMRT) planning is a lengthy process, which requires the planner to iterate between choosing beam angles, specifying dose–volume objectives and executing IMRT optimization. In thorax treatment planning, where there are no class solutions for beam placement, beam angle selection is performed manually, based on the planner’s clinical experience. The purpose of this work is to propose and study a computationally efficient framework that utilizes machine learning to automatically select treatment beam angles. Such a framework may be helpful for reducing the overall planning workload. Methods: The authors introduce an automated beam selection method, based on learning the relationships between beam angles and anatomical features. Using a large set of clinically approved IMRT plans, a random forest regression algorithm is trained to map a multitude of anatomical features into an individual beam score. An optimization scheme is then built to select and adjust the beam angles, considering the learned interbeam dependencies. The validity and quality of the automatically selected beams evaluated using the manually selected beams from the corresponding clinical plans as the ground truth. Results: The analysis included 149 clinically approved thoracic IMRT plans. For a randomly selected test subset of 27 plans, IMRT plans were generated using automatically selected beams and compared to the clinical plans. The comparison of the predicted and the clinical beam angles demonstrated a good average correspondence between the two (angular distance 16.8° ± 10°, correlation 0.75 ± 0.2). The dose distributions of the semiautomatic and clinical plans were equivalent in terms of primary target volume

Synthesis of Novel Fluorescent Sensors Based on Naphthalimide Fluorophores for the Highly Selective Hg2+-Sensing

Directory of Open Access Journals (Sweden)

Yordkhuan Tachapermpon

2015-01-01

Full Text Available With an aim to develop the new sensors for optical detection of Hg2+ ions, two novel fluorometric sensors were designed and successfully prepared using 2-(3-(2-aminoethylsulfanylpropylsulfanylethanamine and one or two N-methylnaphthalimide moieties (1 and 2. Sensor 1 was obtained via N-alkylation, N-imidation and a one-pot nucleophilic aromatic substitution, and N-formylation of the amine, while sensor 2 was prepared via N-alkylation, N-imidation, and nucleophilic aromatic substitution. The characterization, including 1H NMR, 13C NMR, and mass spectrometry, was then performed for 1 and 2. The Hg2+-binding behaviors of the sensors were investigated in terms of sensitivity and selectivity by fluorescence spectroscopy. Sensor 1 especially provided the reversible and highly Hg2+-selective ON-OFF fluorescence behavior by discriminating various interfering ions such as Pb2+, Co2+, Cd2+, Mn2+, Fe2+, K+, Na+, and in particular Cu2+ and Ag+ with a detection limit of 22 ppb toward Hg2+ ions.

Highly selective transformation of ammonia nitrogen to N2 based on a novel solar-driven photoelectrocatalytic-chlorine radical reactions system.

Science.gov (United States)

Ji, Youzhi; Bai, Jing; Li, Jinhua; Luo, Tao; Qiao, Li; Zeng, Qingyi; Zhou, Baoxue

2017-11-15

A highly selective method for transforming ammonia nitrogen to N 2 was proposed, based on a novel solar-driven photoelectrocatalytic-chlorine radical reactions (PEC-chlorine) system. The PEC-chlorine system was facilitated by a visible light response WO 3 nanoplate array (NPA) electrode in an ammonia solution containing chloride ions (Cl - ). Under illumination, photoholes from WO 3 promote the oxidation of Cl - to chlorine radical (Cl). This radical can selectively transform ammonia nitrogen to N 2 (79.9%) and NO 3 - (19.2%), similar to the breakpoint chlorination reaction. The ammonia nitrogen removal efficiency increased from 10.6% (PEC without Cl - ) to 99.9% with the PEC-chlorine system within 90 min operation, which can be attributed to the cyclic reactions between Cl - /Cl and the reaction intermediates (NH 2 , NHCl, etc.) that expand the degradation reactions from the surface of the electrodes to the whole solution system. Moreover, Cl is the main radical species contributing to the transformation of ammonia nitrogen to N 2 , which is confirmed by the tBuOH capture experiment. Compared to conventional breakpoint chlorination, the PEC-chlorine system is a more economical and efficient means for ammonia nitrogen degradation because of the fast removal rate, no additional chlorine cost, and its use of clean energy (since it is solar-driven). Copyright © 2017 Elsevier Ltd. All rights reserved.

Variability-based active galactic nucleus selection using image subtraction in the SDSS and LSST era

Energy Technology Data Exchange (ETDEWEB)

Choi, Yumi; Gibson, Robert R.; Becker, Andrew C.; Ivezić, Željko; Connolly, Andrew J.; Ruan, John J.; Anderson, Scott F. [Department of Astronomy, University of Washington, Box 351580, Seattle, WA 98195 (United States); MacLeod, Chelsea L., E-mail: ymchoi@astro.washington.edu [Physics Department, U.S. Naval Academy, 572 Holloway Road, Annapolis, MD 21402 (United States)

2014-02-10

With upcoming all-sky surveys such as LSST poised to generate a deep digital movie of the optical sky, variability-based active galactic nucleus (AGN) selection will enable the construction of highly complete catalogs with minimum contamination. In this study, we generate g-band difference images and construct light curves (LCs) for QSO/AGN candidates listed in Sloan Digital Sky Survey Stripe 82 public catalogs compiled from different methods, including spectroscopy, optical colors, variability, and X-ray detection. Image differencing excels at identifying variable sources embedded in complex or blended emission regions such as Type II AGNs and other low-luminosity AGNs that may be omitted from traditional photometric or spectroscopic catalogs. To separate QSOs/AGNs from other sources using our difference image LCs, we explore several LC statistics and parameterize optical variability by the characteristic damping timescale (τ) and variability amplitude. By virtue of distinguishable variability parameters of AGNs, we are able to select them with high completeness of 93.4% and efficiency (i.e., purity) of 71.3%. Based on optical variability, we also select highly variable blazar candidates, whose infrared colors are consistent with known blazars. One-third of them are also radio detected. With the X-ray selected AGN candidates, we probe the optical variability of X-ray detected optically extended sources using their difference image LCs for the first time. A combination of optical variability and X-ray detection enables us to select various types of host-dominated AGNs. Contrary to the AGN unification model prediction, two Type II AGN candidates (out of six) show detectable variability on long-term timescales like typical Type I AGNs. This study will provide a baseline for future optical variability studies of extended sources.

Knowledge based expert system approach to instrumentation selection (INSEL

Directory of Open Access Journals (Sweden)

S. Barai

2004-08-01

Full Text Available The selection of appropriate instrumentation for any structural measurement of civil engineering structure is a complex task. Recent developments in Artificial Intelligence (AI can help in an organized use of experiential knowledge available on instrumentation for laboratory and in-situ measurement. Usually, the instrumentation decision is based on the experience and judgment of experimentalists. The heuristic knowledge available for different types of measurement is domain dependent and the information is scattered in varied knowledge sources. The knowledge engineering techniques can help in capturing the experiential knowledge. This paper demonstrates a prototype knowledge based system for INstrument SELection (INSEL assistant where the experiential knowledge for various structural domains can be captured and utilized for making instrumentation decision. In particular, this Knowledge Based Expert System (KBES encodes the heuristics on measurement and demonstrates the instrument selection process with reference to steel bridges. INSEL runs on a microcomputer and uses an INSIGHT 2+ environment.

Diversified models for portfolio selection based on uncertain semivariance

Science.gov (United States)

Chen, Lin; Peng, Jin; Zhang, Bo; Rosyida, Isnaini

2017-02-01

Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' estimations due to lack of historical data. This paper proposes a semivariance method for diversified portfolio selection, in which the security returns are given subjective to experts' estimations and depicted as uncertain variables. In the paper, three properties of the semivariance of uncertain variables are verified. Based on the concept of semivariance of uncertain variables, two types of mean-semivariance diversified models for uncertain portfolio selection are proposed. Since the models are complex, a hybrid intelligent algorithm which is based on 99-method and genetic algorithm is designed to solve the models. In this hybrid intelligent algorithm, 99-method is applied to compute the expected value and semivariance of uncertain variables, and genetic algorithm is employed to seek the best allocation plan for portfolio selection. At last, several numerical examples are presented to illustrate the modelling idea and the effectiveness of the algorithm.

A target recognition method for maritime surveillance radars based on hybrid ensemble selection

Science.gov (United States)

Fan, Xueman; Hu, Shengliang; He, Jingbo

2017-11-01

In order to improve the generalisation ability of the maritime surveillance radar, a novel ensemble selection technique, termed Optimisation and Dynamic Selection (ODS), is proposed. During the optimisation phase, the non-dominated sorting genetic algorithm II for multi-objective optimisation is used to find the Pareto front, i.e. a set of ensembles of classifiers representing different tradeoffs between the classification error and diversity. During the dynamic selection phase, the meta-learning method is used to predict whether a candidate ensemble is competent enough to classify a query instance based on three different aspects, namely, feature space, decision space and the extent of consensus. The classification performance and time complexity of ODS are compared against nine other ensemble methods using a self-built full polarimetric high resolution range profile data-set. The experimental results clearly show the effectiveness of ODS. In addition, the influence of the selection of diversity measures is studied concurrently.

Feature Selection and Kernel Learning for Local Learning-Based Clustering.

Science.gov (United States)

Zeng, Hong; Cheung, Yiu-ming

2011-08-01

The performance of the most clustering algorithms highly relies on the representation of data in the input space or the Hilbert space of kernel methods. This paper is to obtain an appropriate data representation through feature selection or kernel learning within the framework of the Local Learning-Based Clustering (LLC) (Wu and Schölkopf 2006) method, which can outperform the global learning-based ones when dealing with the high-dimensional data lying on manifold. Specifically, we associate a weight to each feature or kernel and incorporate it into the built-in regularization of the LLC algorithm to take into account the relevance of each feature or kernel for the clustering. Accordingly, the weights are estimated iteratively in the clustering process. We show that the resulting weighted regularization with an additional constraint on the weights is equivalent to a known sparse-promoting penalty. Hence, the weights of those irrelevant features or kernels can be shrunk toward zero. Extensive experiments show the efficacy of the proposed methods on the benchmark data sets.

44 CFR 321.2 - Selection of the mobilization base.

Science.gov (United States)

2010-10-01

... base. 321.2 Section 321.2 Emergency Management and Assistance FEDERAL EMERGENCY MANAGEMENT AGENCY, DEPARTMENT OF HOMELAND SECURITY PREPAREDNESS MAINTENANCE OF THE MOBILIZATION BASE (DEPARTMENT OF DEFENSE, DEPARTMENT OF ENERGY, MARITIME ADMINISTRATION) § 321.2 Selection of the mobilization base. (a) The Department...

Plans, Patterns, and Move Categories Guiding a Highly Selective Search

Science.gov (United States)

Trippen, Gerhard

In this paper we present our ideas for an Arimaa-playing program (also called a bot) that uses plans and pattern matching to guide a highly selective search. We restrict move generation to moves in certain move categories to reduce the number of moves considered by the bot significantly. Arimaa is a modern board game that can be played with a standard Chess set. However, the rules of the game are not at all like those of Chess. Furthermore, Arimaa was designed to be as simple and intuitive as possible for humans, yet challenging for computers. While all established Arimaa bots use alpha-beta search with a variety of pruning techniques and other heuristics ending in an extensive positional leaf node evaluation, our new bot, Rat, starts with a positional evaluation of the current position. Based on features found in the current position - supported by pattern matching using a directed position graph - our bot Rat decides which of a given set of plans to follow. The plan then dictates what types of moves can be chosen. This is another major difference from bots that generate "all" possible moves for a particular position. Rat is only allowed to generate moves that belong to certain categories. Leaf nodes are evaluated only by a straightforward material evaluation to help avoid moves that lose material. This highly selective search looks, on average, at only 5 moves out of 5,000 to over 40,000 possible moves in a middle game position.

An automatic fuzzy-based multi-temporal brain digital subtraction angiography image fusion algorithm using curvelet transform and content selection strategy.

Science.gov (United States)

Momeni, Saba; Pourghassem, Hossein

2014-08-01

Recently image fusion has prominent role in medical image processing and is useful to diagnose and treat many diseases. Digital subtraction angiography is one of the most applicable imaging to diagnose brain vascular diseases and radiosurgery of brain. This paper proposes an automatic fuzzy-based multi-temporal fusion algorithm for 2-D digital subtraction angiography images. In this algorithm, for blood vessel map extraction, the valuable frames of brain angiography video are automatically determined to form the digital subtraction angiography images based on a novel definition of vessel dispersion generated by injected contrast material. Our proposed fusion scheme contains different fusion methods for high and low frequency contents based on the coefficient characteristic of wrapping second generation of curvelet transform and a novel content selection strategy. Our proposed content selection strategy is defined based on sample correlation of the curvelet transform coefficients. In our proposed fuzzy-based fusion scheme, the selection of curvelet coefficients are optimized by applying weighted averaging and maximum selection rules for the high frequency coefficients. For low frequency coefficients, the maximum selection rule based on local energy criterion is applied to better visual perception. Our proposed fusion algorithm is evaluated on a perfect brain angiography image dataset consisting of one hundred 2-D internal carotid rotational angiography videos. The obtained results demonstrate the effectiveness and efficiency of our proposed fusion algorithm in comparison with common and basic fusion algorithms.

Customer Order Decoupling Point Selection Model in Mass Customization Based on MAS

Institute of Scientific and Technical Information of China (English)

XU Xuanguo; LI Xiangyang

2006-01-01

Mass customization relates to the ability of providing individually designed products or services to customer with high process flexibility or integration. Literatures on mass customization have been focused on mechanism of MC, but little on customer order decoupling point selection. The aim of this paper is to present a model for customer order decoupling point selection of domain knowledge interactions between enterprises and customers in mass customization. Based on the analysis of other researchers' achievements combining the demand problems of customer and enterprise, a model of group decision for customer order decoupling point selection is constructed based on quality function deployment and multi-agent system. Considering relatively the decision makers of independent functional departments as independent decision agents, a decision agent set is added as the third dimensionality to house of quality, the cubic quality function deployment is formed. The decision-making can be consisted of two procedures: the first one is to build each plane house of quality in various functional departments to express each opinions; the other is to evaluate and gather the foregoing sub-decisions by a new plane quality function deployment. Thus, department decision-making can well use its domain knowledge by ontology, and total decision-making can keep simple by avoiding too many customer requirements.

Object width modulates object-based attentional selection.

Science.gov (United States)

Nah, Joseph C; Neppi-Modona, Marco; Strother, Lars; Behrmann, Marlene; Shomstein, Sarah

2018-04-24

Visual input typically includes a myriad of objects, some of which are selected for further processing. While these objects vary in shape and size, most evidence supporting object-based guidance of attention is drawn from paradigms employing two identical objects. Importantly, object size is a readily perceived stimulus dimension, and whether it modulates the distribution of attention remains an open question. Across four experiments, the size of the objects in the display was manipulated in a modified version of the two-rectangle paradigm. In Experiment 1, two identical parallel rectangles of two sizes (thin or thick) were presented. Experiments 2-4 employed identical trapezoids (each having a thin and thick end), inverted in orientation. In the experiments, one end of an object was cued and participants performed either a T/L discrimination or a simple target-detection task. Combined results show that, in addition to the standard object-based attentional advantage, there was a further attentional benefit for processing information contained in the thick versus thin end of objects. Additionally, eye-tracking measures demonstrated increased saccade precision towards thick object ends, suggesting that Fitts's Law may play a role in object-based attentional shifts. Taken together, these results suggest that object-based attentional selection is modulated by object width.

Semiconductor-based Multilayer Selective Solar Absorber for Unconcentrated Solar Thermal Energy Conversion.

Science.gov (United States)

Thomas, Nathan H; Chen, Zhen; Fan, Shanhui; Minnich, Austin J

2017-07-13

Solar thermal energy conversion has attracted substantial renewed interest due to its applications in industrial heating, air conditioning, and electricity generation. Achieving stagnation temperatures exceeding 200 °C, pertinent to these technologies, with unconcentrated sunlight requires spectrally selective absorbers with exceptionally low emissivity in the thermal wavelength range and high visible absorptivity for the solar spectrum. In this Communication, we report a semiconductor-based multilayer selective absorber that exploits the sharp drop in optical absorption at the bandgap energy to achieve a measured absorptance of 76% at solar wavelengths and a low emittance of approximately 5% at thermal wavelengths. In field tests, we obtain a peak temperature of 225 °C, comparable to that achieved with state-of-the-art selective surfaces. With straightforward optimization to improve solar absorption, our work shows the potential for unconcentrated solar thermal systems to reach stagnation temperatures exceeding 300 °C, thereby eliminating the need for solar concentrators for mid-temperature solar applications such as supplying process heat.

PARAMETER ESTIMATION AND MODEL SELECTION FOR INDOOR ENVIRONMENTS BASED ON SPARSE OBSERVATIONS

Directory of Open Access Journals (Sweden)

Y. Dehbi

2017-09-01

Full Text Available This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

Parameter Estimation and Model Selection for Indoor Environments Based on Sparse Observations

Science.gov (United States)

Dehbi, Y.; Loch-Dehbi, S.; Plümer, L.

2017-09-01

This paper presents a novel method for the parameter estimation and model selection for the reconstruction of indoor environments based on sparse observations. While most approaches for the reconstruction of indoor models rely on dense observations, we predict scenes of the interior with high accuracy in the absence of indoor measurements. We use a model-based top-down approach and incorporate strong but profound prior knowledge. The latter includes probability density functions for model parameters and sparse observations such as room areas and the building footprint. The floorplan model is characterized by linear and bi-linear relations with discrete and continuous parameters. We focus on the stochastic estimation of model parameters based on a topological model derived by combinatorial reasoning in a first step. A Gauss-Markov model is applied for estimation and simulation of the model parameters. Symmetries are represented and exploited during the estimation process. Background knowledge as well as observations are incorporated in a maximum likelihood estimation and model selection is performed with AIC/BIC. The likelihood is also used for the detection and correction of potential errors in the topological model. Estimation results are presented and discussed.

High Selectivity Oxygen Delignification

Energy Technology Data Exchange (ETDEWEB)

Lucian A. Lucia

2005-11-15

Project Objective: The objectives of this project are as follows: (1) Examine the physical and chemical characteristics of a partner mill pre- and post-oxygen delignified pulp and compare them to lab generated oxygen delignified pulps; (2) Apply the chemical selectivity enhancement system to the partner pre-oxygen delignified pulps under mill conditions (with and without any predetermined amounts of carryover) to determine how efficiently viscosity is preserved, how well selectivity is enhanced, if strength is improved, measure any yield differences and/or bleachability differences; and (3) Initiate a mill scale oxygen delignification run using the selectivity enhancement agent, collect the mill data, analyze it, and propose any future plans for implementation.

Facile preparation of an alternating copolymer-based high molecular shape-selective organic phase for reversed-phase liquid chromatography.

Science.gov (United States)

Mallik, Abul K; Noguchi, Hiroki; Rahman, Mohammed Mizanur; Takafuji, Makoto; Ihara, Hirotaka

2018-06-22

The synthesis of a new alternating copolymer-grafted silica phase is described for the separation of shape-constrained isomers of polycyclic aromatic hydrocarbons (PAHs) and tocopherols in reversed-phase high-performance liquid chromatography (RP-HPLC). Telomerization of the monomers (octadecyl acrylate and N-methylmaleimide) was carried out with a silane coupling agent; 3-mercaptopropyltrimethoxysilane (MPS), and the telomer (T) was grafted onto porous silica surface to prepare the alternating copolymer-grafted silica phase (Sil-alt-T). The new hybrid material was characterized by elemental analyses, diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy, and solid-state 13 C and 29 Si cross-polarization magic-angle spinning (CP/MAS) NMR spectroscopy. The results of 13 C CP/MAS NMR demonstrated that the alkyl chains of the grafted polymers in Sil-alt-T remained disordered, amorphous, and mobile represented by gauche conformational form. Separation abilities and molecular-shape selectivities of the prepared organic phase were evaluated by the separation of PAHs isomers and Standard Reference Material 869b, Column Selectivity Test Mixture for Liquid Chromatography, respectively and compared with commercially available octadecylsilylated silica (ODS) and C 30 columns as well as previously reported alternating copolymer-based column. The effectiveness of this phase is also demonstrated by the separation of tocopherol isomers. Oriented functional groups along the polymer main chains and cavity formations are investigated to be the driving force for better separation with multiple-interactions with the solutes. One of the advantages of the Sil-alt-T phase to that of the previously reported phase is the synthesis of the telomer first and then immobilized onto silica surface. In this case, the telomer was characterized easily with simple spectroscopic techniques and the molecular mass and polydispersity index of the telomer were determined by size exclusion

Selective Sequential Zero-Base Budgeting Procedures Based on Total Factor Productivity Indicators

OpenAIRE

A. Ishikawa; E. F. Sudit

1981-01-01

The authors' purpose in this paper is to develop productivity-based sequential budgeting procedures designed to expedite identification of major problem areas in bugetary performance, as well as to reduce the costs associated with comprehensive zero-base analyses. The concept of total factor productivity is reviewed and its relations to ordinary and zero-based budgeting are discussed in detail. An outline for a selective sequential analysis based on monitoring of three key indicators of (a) i...

A highly selective fluorescent chemosensor for CN- based on a novel bis(salamo)-type tetraoxime ligand

Science.gov (United States)

Wang, Fei; Gao, Lei; Zhao, Qing; Zhang, Yang; Dong, Wen-Kui; Ding, Yu-Jie

2018-02-01

The optical properties of a novel chemosensor for cyanide anions based on a symmetric bis(salamo)-type ligand (H3L) were investigated by UV-Vis and fluorescence spectroscopy in MeOH/H2O (1:1 v/v) solution. Sensor H3L can selectively sense CN- based on prominent color changes among other anions. The chemosensor exhibits an apparent fluorescence enhancement at 482 nm to CN- which because cyanide ions interact with Cdbnd N bonds. Combining the corrected Benesi-Hildebrand formula, the binding constant of the formed host-guest complex was calculated as 2.42 × 105 M- 1. Meanwhile, the detection limit of the sensor toward CN- was 8.91 × 10- 7 M. It is worth noting that the designed sensor can be used for rapid detection of cyanide anions in basic pH range, and has great practical value.

Highly selective enrichment of phosphorylated peptides from peptide mixtures using titanium dioxide microcolumns

DEFF Research Database (Denmark)

Larsen, Martin Røssel; Thingholm, Tine E; Jensen, Ole N

2005-01-01

based on TiO2microcolumns and peptide loading in 2,5-dihydroxybenzoic acid (DHB). The effect of DHB was a very efficient reduction in the binding of nonphosphorylated peptides to TiO2 while retaining its high binding affinity for phosphorylated peptides. Thus, inclusion of DHB dramatically increased...... the selectivity of the enrichment of phosphorylated peptides by TiO2. We demonstrated that this new procedure was more selective for binding phosphorylated peptides than IMAC using MALDI mass spectrometry. In addition, we showed that LC-ESI-MSMS was biased toward monophosphorylated peptides, whereas MALDI MS...... was not. Other substituted aromatic carboxylic acids were also capable of specifically reducing binding of nonphosphorylated peptides, whereas phosphoric acid reduced binding of both phosphorylated and nonphosphorylated peptides. A putative mechanism for this intriguing effect is presented....

A high sensitivity nanomaterial based SAW humidity sensor

Energy Technology Data Exchange (ETDEWEB)

Wu, T-T; Chou, T-H [Institute of Applied Mechanics, National Taiwan University, Taipei 106, Taiwan (China); Chen, Y-Y [Department of Mechanical Engineering, Tatung University, Taipei 104, Taiwan (China)], E-mail: wutt@ndt.iam.ntu.edu.tw

2008-04-21

In this paper, a highly sensitive humidity sensor is reported. The humidity sensor is configured by a 128{sup 0}YX-LiNbO{sub 3} based surface acoustic wave (SAW) resonator whose operating frequency is at 145 MHz. A dual delay line configuration is realized to eliminate external temperature fluctuations. Moreover, for nanostructured materials possessing high surface-to-volume ratio, large penetration depth and fast charge diffusion rate, camphor sulfonic acid doped polyaniline (PANI) nanofibres are synthesized by the interfacial polymerization method and further deposited on the SAW resonator as selective coating to enhance sensitivity. The humidity sensor is used to measure various relative humidities in the range 5-90% at room temperature. Results show that the PANI nanofibre based SAW humidity sensor exhibits excellent sensitivity and short-term repeatability.

Mercury(II) selective sensors based on AlGaN/GaN transistors.

Science.gov (United States)

Asadnia, Mohsen; Myers, Matthew; Akhavan, N D; O'Donnell, Kane; Umana-Membreno, Gilberto A; Mishra, U K; Nener, Brett; Baker, Murray; Parish, Giacinta

2016-11-02

This work presents the first polymer approach to detect metal ions using AlGaN/GaN transistor-based sensor. The sensor utilised an AlGaN/GaN high electron mobility transistor-type structure by functionalising the gate area with a polyvinyl chloride (PVC) based ion selective membrane. Sensors based on this technology are portable, robust and typically highly sensitive to the target analyte; in this case Hg 2+ . This sensor showed a rapid and stable response when it was introduced to solutions of varying Hg 2+ concentrations. At pH 2.8 in a 10 -2  M KNO 3 ion buffer, a detection limit below 10 -8  M and a linear response range between 10 -8  M-10 -4  M were achieved. This detection limit is an order of magnitude lower than the reported detection limit of 10 -7  M for thioglycolic acid monolayer functionalised AlGaN/GaN HEMT devices. Detection limits of approximately 10 -7  M and 10 -6  M in 10 -2  M Cd(NO 3 ) 2 and 10 -2  M Pb(NO 3 ) 2 ion buffers were also achieved, respectively. Furthermore, we show that the apparent gate response was near-Nernstian under various conditions. X-ray photoelectron spectroscopy (XPS) experiments confirmed that the sensing membrane is reversible after being exposed to Hg 2+ solution and rinsed with deionised water. The success of this study precedes the development of this technology in selectively sensing multiple ions in water with use of the appropriate polymer based membranes on arrays of devices. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.

SADA: Ecological Risk Based Decision Support System for Selective Remediation

Science.gov (United States)

Spatial Analysis and Decision Assistance (SADA) is freeware that implements terrestrial ecological risk assessment and yields a selective remediation design using its integral geographical information system, based on ecological and risk assessment inputs. Selective remediation ...

Computer-assisted electrochemical fabrication of a highly selective and sensitive amperometric nitrite sensor based on surface decoration of electrochemically reduced graphene oxide nanosheets with CoNi bimetallic alloy nanoparticles.

Science.gov (United States)

Gholivand, Mohammad-Bagher; Jalalvand, Ali R; Goicoechea, Hector C

2014-07-01

For the first time, a novel, robust and very attractive statistical experimental design (ED) using minimum-run equireplicated resolution IV factorial design (Min-Run Res IV FD) coupled with face centered central composite design (FCCCD) and Derringer's desirability function (DF) was developed to fabricate a highly selective and sensitive amperometric nitrite sensor based on electrodeposition of CoNi bimetallic alloy nanoparticles (NPs) on electrochemically reduced graphene oxide (ERGO) nanosheets. The modifications were characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), energy dispersive X-ray spectroscopic (EDS), scanning electron microscopy (SEM) techniques. The CoNi bimetallic alloy NPs were characterized using digital image processing (DIP) for particle counting (density estimation) and average diameter measurement. Under the identified optimal conditions, the novel sensor detects nitrite in concentration ranges of 0.1-30.0 μM and 30.0-330.0 μM with a limit of detection (LOD) of 0.05 μM. This sensor selectively detects nitrite even in the presence of high concentration of common ions and biological interferents therefore, we found that the sensor is highly selective. The sensor also demonstrated an excellent operational stability and good antifouling properties. The proposed sensor was used to the determination of nitrite in several foodstuff and water samples. Copyright © 2014. Published by Elsevier B.V.

Opportunity structures for selective exposure

DEFF Research Database (Denmark)

Skovsgaard, Morten; Shehata, Adam; Strömbäck, Jesper

2016-01-01

Abstract The transition from low-choice to high-choice media environments has raised new concerns about selective exposure. In this context, two types of selective media exposure are relevant. One is selectivity based on political ideological preferences, the other selectivity based on political...... interest. Evidence for both has been found primarily in an American context, while there is less research on European countries. This is problematic, as the opportunity structures for different forms of selectivity vary across media environments. Against this background, the purpose of this study...

Mobile phone based imaging system for selected tele-healthcare applications

OpenAIRE

Condominas Guàrdia, Jordi

2013-01-01

A mobile phone based telemedicine study is developed to see how feasible phone usage is in selected health care applications. The research is divided into three different objectives. The first objective is to compile the technical characteristics of selected mobile phones from telemedicine perspective. The second objective is to develop techniques to acquire quality images of skin with mobile phones. Finally a smartphone based telemedicine application will be developed to asses...

On the benefits of location-based relay selection in mobile wireless networks

DEFF Research Database (Denmark)

Nielsen, Jimmy Jessen; Madsen, Tatiana Kozlova; Schwefel, Hans-Peter

2016-01-01

We consider infrastructure-based mobile networks that are assisted by a single relay transmission where both the downstream destination and relay nodes are mobile. Selecting the optimal transmission path for a destination node requires up-to-date link quality estimates of all relevant links....... If the relay selection is based on link quality measurements, the number of links to update grows quadratically with the number of nodes, and measurements need to be updated frequently when nodes are mobile. In this paper, we consider a location-based relay selection scheme where link qualities are estimated...... from node positions; in the scenario of a node-based location system such as GPS, the location-based approach reduces signaling overhead, which in this case only grows linearly with the number of nodes. This paper studies these two relay selection approaches and investigates how they are affected...

A highly selective and sensitive cocaine aptasensor based on covalent attachment of the aptamer-functionalized AuNPs onto nanocomposite as the support platform

Energy Technology Data Exchange (ETDEWEB)

Roushani, Mahmoud, E-mail: mahmoudroushani@yahoo.com; Shahdost-fard, Faezeh

2015-01-01

Highlights: • Functionalized thiol-terminated cocaine aptamer was functionalized with AuNPs. • MWCNTs/IL/Chit was employed for covalent attachment of Apt-capture probe onto electrode. • (K{sub 3}Fe(CN){sub 6}) was used as the redox probe and DPV as analytical technique. • The aptasensor showed high sensitivity and selectivity. • Linear range from 1 nM to 11,000 nM with LOD of 100 pM for cocaine detection was obtained. - Abstract: Based on the conformational changes of the aptamer-functionalized gold nanoparticles (AuNPs) onto MWCNTs/IL/Chit nanocomposite as the support platform, we have developed a sensitive and selective electrochemical aptasensor for the detection of cocaine. The 5′-amine-3′-AuNP terminated aptamer is covalently attached to a MWCNTs/IL/Chit nanocomposite. The interaction of cocaine with the aptamer functionalized AuNP caused the aptamer to be folded and the AuNPs with negative charge at the end of the aptamer came to the near of electrode surface therefore, the electron transfer between ferricyanide (K{sub 3}Fe(CN){sub 6}) as redox probe and electrode surface was inhibited. A decreased current of (K{sub 3}Fe(CN){sub 6}) was monitored by differential pulse voltammetry technique. In an optimized condition the calibration curve for cocaine concentration was linear up to 11 μM with detection limit (signal-to-noise ratio of 3) of 100 pM. To test the selectivity of the prepared aptasensor sensing platform applicability, some analgesic drugs as the interferes were examined. The potential of the aptasensor was successfully applied for measuring cocaine concentration in human blood serum. Based on our experiments it can be said that the present method is absolutely beneficial in developing other electrochemical aptasensor.

A highly selective and sensitive cocaine aptasensor based on covalent attachment of the aptamer-functionalized AuNPs onto nanocomposite as the support platform

International Nuclear Information System (INIS)

Roushani, Mahmoud; Shahdost-fard, Faezeh

2015-01-01

Highlights: • Functionalized thiol-terminated cocaine aptamer was functionalized with AuNPs. • MWCNTs/IL/Chit was employed for covalent attachment of Apt-capture probe onto electrode. • (K 3 Fe(CN) 6 ) was used as the redox probe and DPV as analytical technique. • The aptasensor showed high sensitivity and selectivity. • Linear range from 1 nM to 11,000 nM with LOD of 100 pM for cocaine detection was obtained. - Abstract: Based on the conformational changes of the aptamer-functionalized gold nanoparticles (AuNPs) onto MWCNTs/IL/Chit nanocomposite as the support platform, we have developed a sensitive and selective electrochemical aptasensor for the detection of cocaine. The 5′-amine-3′-AuNP terminated aptamer is covalently attached to a MWCNTs/IL/Chit nanocomposite. The interaction of cocaine with the aptamer functionalized AuNP caused the aptamer to be folded and the AuNPs with negative charge at the end of the aptamer came to the near of electrode surface therefore, the electron transfer between ferricyanide (K 3 Fe(CN) 6 ) as redox probe and electrode surface was inhibited. A decreased current of (K 3 Fe(CN) 6 ) was monitored by differential pulse voltammetry technique. In an optimized condition the calibration curve for cocaine concentration was linear up to 11 μM with detection limit (signal-to-noise ratio of 3) of 100 pM. To test the selectivity of the prepared aptasensor sensing platform applicability, some analgesic drugs as the interferes were examined. The potential of the aptasensor was successfully applied for measuring cocaine concentration in human blood serum. Based on our experiments it can be said that the present method is absolutely beneficial in developing other electrochemical aptasensor

High-throughput Sequencing Based Immune Repertoire Study during Infectious Disease

Directory of Open Access Journals (Sweden)

Dongni Hou

2016-08-01

Full Text Available The selectivity of the adaptive immune response is based on the enormous diversity of T and B cell antigen-specific receptors. The immune repertoire, the collection of T and B cells with functional diversity in the circulatory system at any given time, is dynamic and reflects the essence of immune selectivity. In this article, we review the recent advances in immune repertoire study of infectious diseases that achieved by traditional techniques and high-throughput sequencing techniques. High-throughput sequencing techniques enable the determination of complementary regions of lymphocyte receptors with unprecedented efficiency and scale. This progress in methodology enhances the understanding of immunologic changes during pathogen challenge, and also provides a basis for further development of novel diagnostic markers, immunotherapies and vaccines.

High-level radioactive waste repositories site selection plan

International Nuclear Information System (INIS)

Castanon, A.; Recreo, F.

1985-01-01

A general vision of the high level nuclear waste (HLNW) and/or nuclear spent fuel facilities site selection processes is given, according to the main international nuclear safety regulatory organisms quidelines and the experience from those countries which have reached a larger development of their national nuclear programs. (author)

Study on a highly selective fluorescent chemosensor for Cu{sup 2+} and its direct sensing for proton based on 1,3,4-oxadiazole

Energy Technology Data Exchange (ETDEWEB)

Zhu, Ling [College of Chemistry, Jilin University, Changchun 130024 (China); Gu, Caiying [Faculty of Chemistry, Northeast Normal University, Changchun 130024 (China); He, Yi [College of Chemistry, Jilin University, Changchun 130024 (China); Wang, Guang, E-mail: wangg923@nenu.edu.cn [Faculty of Chemistry, Northeast Normal University, Changchun 130024 (China)

2014-09-15

A photoinduced electron transfer cation sensor, oxadiazole-bridge-bis(N,N-bis(2-pyridylmethyl)amine), was designed and prepared. This sensor displayed an “off–on–off” fluorescent switch for proton and an “on–off” fluorescent switch for Cu{sup 2+}. The fluorescence emission of the sensor was quenched upon addition of Cu{sup 2+} and proton in CH{sub 3}CN/H{sub 2}O solution (v/v, 4:1) due to electron transfer between the N,N-bis(2-pyridylmethyl)amine and the oxadiazole. The sensor presented high selectivity for Cu{sup 2+} over other metal ions and determined Cu{sup 2+} concentration in a linear fashion from 5×10{sup −7} M to 8×10{sup −5} M. Stern–Volmer analysis showed the binding stoichiometry to be 1:2 (host-guest) with a binding constant of 1.8×10{sup 10} M{sup −2}, calculated using the Benesi–Hilderbrand equation. The response of the sensor to Cu{sup 2+} was instantaneous and reversible, and the usual anions did not influence the selectivity for Cu{sup 2+}. - Highlights: • A new fluorescent sensor based on oxadiazole and N,N-bis-(2-pyridylmethyl)amine was designed. • The sensor displayed sensitive fluorescence response “on–off” to Cu{sup 2+} and “on–off–on” for protons. • Fluorescence intensity showed good linear correlation with Cu{sup 2+} concentration from 5×10{sup −7} M to 8×10{sup −5} M. • The high concentration of metal ions and usual anions did not influence the selectivity for Cu{sup 2+}. • The short response time of the sensor for Cu{sup 2+} (within 20 s) meets practical requirements.

Personnel Selection Method Based on Personnel-Job Matching

OpenAIRE

Li Wang; Xilin Hou; Lili Zhang

2013-01-01

The existing personnel selection decisions in practice are based on the evaluation of job seeker's human capital, and it may be difficult to make personnel-job matching and make each party satisfy. Therefore, this paper puts forward a new personnel selection method by consideration of bilateral matching. Starting from the employment thoughts of ¡°satisfy¡±, the satisfaction evaluation indicator system of each party are constructed. The multi-objective optimization model is given according to ...

High-performance functional ecopolymers based on flora and fauna.

Science.gov (United States)

Kaneko, Tatsuo

2007-01-01

Liquid crystalline (LC) polymers of rigid monomers based on flora and fauna were prepared by in-bulk polymerization. Para-coumaric (p-coumaric) acid [4-hydroxycinnamic acid (4HCA)] and its derivatives were selected as phytomonomers and bile acids were selected as biomonomers. The 4HCA homopolymer showed a thermotropic LC phase only in a state of low molecular weight. The copolymers of 4HCA with bile acids such as lithocholic acid (LCA) and cholic acid (CA) showed excellent cell compatibilities but low molecular weights. However, P(4HCA-co-CA)s allowed LC spinning to create molecularly oriented biofibers, presumably due to the chain entanglement that occurs during in-bulk chain propagation into hyperbranching architecture. P[4HCA-co-3,4-dihydroxycinnamic acid (DHCA)]s showed high molecular weight, high mechanical strength, high Young's modulus, and high softening temperature, which may be achieved through the entanglement by in-bulk formation of hyperbranching, rigid structures. P(4HCA-co-DHCA)s showed a smooth hydrolysis, in-soil degradation, and photo-tunable hydrolysis. Thus, P(4HCA-co-DHCA)s might be applied as an environmentally degradable plastic with extremely high performance.

High-dimensional model estimation and model selection

CERN Multimedia

CERN. Geneva

2015-01-01

I will review concepts and algorithms from high-dimensional statistics for linear model estimation and model selection. I will particularly focus on the so-called p>>n setting where the number of variables p is much larger than the number of samples n. I will focus mostly on regularized statistical estimators that produce sparse models. Important examples include the LASSO and its matrix extension, the Graphical LASSO, and more recent non-convex methods such as the TREX. I will show the applicability of these estimators in a diverse range of scientific applications, such as sparse interaction graph recovery and high-dimensional classification and regression problems in genomics.

Polymeric membrane sensors based on Cd(II) Schiff base complexes for selective iodide determination in environmental and medicinal samples.

Science.gov (United States)

Singh, Ashok Kumar; Mehtab, Sameena

2008-01-15

The two cadmium chelates of schiff bases, N,N'-bis(salicylidene)-1,4-diaminobutane, (Cd-S(1)) and N,N'-bis(salicylidene)-3,4-diaminotoluene (Cd-S(2)), have been synthesized and explored as ionophores for preparing PVC-based membrane sensors selective to iodide(I) ion. Potentiometric investigations indicate high affinity of these receptors for iodide ion. Polyvinyl chloride (PVC)-based membranes of Cd-S(1) and Cd-S(2) using as hexadecyltrimethylammonium bromide (HTAB) cation discriminator and o-nitrophenyloctyl ether (o-NPOE), dibutylphthalate (DBP), acetophenone (AP) and tributylphosphate (TBP) as plasticizing solvent mediators were prepared and investigated as iodide-selective sensors. The best performance was shown by the membrane of composition (w/w) of (Cd-S(1)) (7%):PVC (31%):DBP (60%):HTAB (2%). The sensor works well over a wide concentration range 5.3x10(-7) to 1.0x10(-2)M with Nernstian compliance (59.2mVdecade(-1) of activity) within pH range 2.5-9.0 with a response time of 11s and showed good selectivity for iodide ion over a number of anions. The sensor exhibits adequate life (3 months) with good reproducibility (S.D.+/-0.24mV) and could be used successfully for the determination of iodide content in environmental water samples and mouth wash samples.

Greater fruit selection following an appearance-based compared with a health-based health promotion poster

Science.gov (United States)

2016-01-01

Abstract Background This study investigated the impact of an appearance-based compared with a traditional health-based public health message for healthy eating. Methods A total of 166 British University students (41 males; aged 20.6 ± 1.9 years) were randomized to view either an appearance-based (n = 82) or a health-based (n = 84) fruit promotion poster. Intentions to consume fruit and immediate fruit selection (laboratory observation) were assessed immediately after poster viewing, and subsequent self-report fruit consumption was assessed 3 days later. Results Intentions to consume fruit were not predicted by poster type (largest β = 0.03, P = 0.68) but were associated with fruit-based liking, past consumption, attitudes and social norms (smallest β = 0.16, P = 0.04). Immediate fruit selection was greater following the appearance-based compared with the health-based poster (β = −0.24, P poster (β = −0.22, P = 0.03), but this effect became non-significant on consideration of participant characteristics (β = −0.15, P = 0.13), and was instead associated with fruit-based liking and past consumption (smallest β = 0.24, P = 0.03). Conclusions These findings demonstrate the clear value of an appearance-based compared with a health-based health promotion poster for increasing fruit selection. A distinction between outcome measures and the value of a behavioural measure is also demonstrated. PMID:28158693

Gene-Based Multiclass Cancer Diagnosis with Class-Selective Rejections

Science.gov (United States)

Jrad, Nisrine; Grall-Maës, Edith; Beauseroy, Pierre

2009-01-01

Supervised learning of microarray data is receiving much attention in recent years. Multiclass cancer diagnosis, based on selected gene profiles, are used as adjunct of clinical diagnosis. However, supervised diagnosis may hinder patient care, add expense or confound a result. To avoid this misleading, a multiclass cancer diagnosis with class-selective rejection is proposed. It rejects some patients from one, some, or all classes in order to ensure a higher reliability while reducing time and expense costs. Moreover, this classifier takes into account asymmetric penalties dependant on each class and on each wrong or partially correct decision. It is based on ν-1-SVM coupled with its regularization path and minimizes a general loss function defined in the class-selective rejection scheme. The state of art multiclass algorithms can be considered as a particular case of the proposed algorithm where the number of decisions is given by the classes and the loss function is defined by the Bayesian risk. Two experiments are carried out in the Bayesian and the class selective rejection frameworks. Five genes selected datasets are used to assess the performance of the proposed method. Results are discussed and accuracies are compared with those computed by the Naive Bayes, Nearest Neighbor, Linear Perceptron, Multilayer Perceptron, and Support Vector Machines classifiers. PMID:19584932

Label free selective detection of estriol using graphene oxide-based fluorescence sensor

Science.gov (United States)

Kushwaha, H. S.; Sao, Reshma; Vaish, Rahul

2014-07-01

Water-soluble and fluorescent Graphene oxide (GO) is biocompatible, easy, and economical to synthesize. Interestingly, GO is also capable of quenching fluorescence. On the basis of its fluorescence and quenching abilities, GO has been reported to serve as an energy acceptor in a fluorescence resonance energy transfer (FRET) sensor. GO-based FRET biosensors have been widely reported for sensing of proteins, nucleic acid, ATP (Adenosine triphosphate), etc. GO complexes with fluorescent dyes and enzymes have been used to sense metal ions. Graphene derivatives have been used for sensing endocrine-disrupting chemicals like bisphenols and chlorophenols with high sensitivity and good reproducibility. On this basis, a novel GO based fluorescent sensor has been successfully designed to detect estriol with remarkable selectivity and sensitivity. Estriol is one of the three estrogens in women and is considered to be medically important. Estriol content of maternal urine or plasma acts as an important screening marker for estimating foetal growth and development. In addition, estriol is also used as diagnostic marker for diseases like breast cancer, osteoporosis, neurodegenerative and cardiovascular diseases, insulin resistance, lupus erythematosus, endometriosis, etc. In this present study, we report for the first time a rapid, sensitive with detection limit of 1.3 nM, selective and highly biocompatible method for label free detection of estriol under physiological conditions using fluorescence assay.

Genome-Wide Analysis of the World's Sheep Breeds Reveals High Levels of Historic Mixture and Strong Recent Selection

Science.gov (United States)

Kijas, James W.; Lenstra, Johannes A.; Hayes, Ben; Boitard, Simon; Porto Neto, Laercio R.; San Cristobal, Magali; Servin, Bertrand; McCulloch, Russell; Whan, Vicki; Gietzen, Kimberly; Paiva, Samuel; Barendse, William; Ciani, Elena; Raadsma, Herman; McEwan, John; Dalrymple, Brian

2012-01-01

Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species. PMID:22346734

Genome-wide analysis of the world's sheep breeds reveals high levels of historic mixture and strong recent selection.

Directory of Open Access Journals (Sweden)

James W Kijas

2012-02-01

Full Text Available Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.

A copper ion-selective electrode with high selectivity prepared by sol-gel and coated wire techniques.

Science.gov (United States)

Mazloum Ardakani, M; Salavati-Niasari, M; Khayat Kashani, M; Ghoreishi, S M

2004-03-01

A sol-gel electrode and a coated wire ion-selective poly(vinyl chloride) membrane, based on thiosemicarbazone as a neutral carrier, were successfully developed for the detection of Cu (II) in aqueous solutions. The sol-gel electrode and coated electrode exhibited linear response with Nernstian slopes of 29.2 and 28.1 mV per decade respectively, within the copper ion concentration ranges 1.0 x 10(-5) - 1.0 x 10(-1) M and 6.0 x 10(-6) - 1.0 x 10(-1) M for coated and sol-gel sensors. The coated and sol-gel electrodes show detection limits of 3.0 x 10(-6) and 6.0 x 10(-6) M respectively. The electrodes exhibited good selectivities for a number of alkali, alkaline earth, transition and heavy metal ions. The proposed electrodes have response times ranging from 10-50 s to achieve a 95% steady potential for Cu2+ concentration. The electrodes are suitable for use in aqueous solutions over a wide pH range (4-7.5). Applications of these electrodes for the determination of copper in real samples, and as an indicator electrode for potentiometric titration of Cu2+ ion using EDTA, are reported. The lifetimes of the electrodes were tested over a period of six months to investigate their stability. No significant change in the performance of the sol-gel electrode was observed over this period, but after two months the coated wire copper-selective electrode exhibited a gradual decrease in the slope. The selectivity of the sol-gel electrode was found to be better than that of the coated wire copper-selective electrode. Based on these results, a novel sol-gel copper-selective electrode is proposed for the determination of copper, and applied to real sample assays.

A Cancer Gene Selection Algorithm Based on the K-S Test and CFS

Directory of Open Access Journals (Sweden)

Qiang Su

2017-01-01

Full Text Available Background. To address the challenging problem of selecting distinguished genes from cancer gene expression datasets, this paper presents a gene subset selection algorithm based on the Kolmogorov-Smirnov (K-S test and correlation-based feature selection (CFS principles. The algorithm selects distinguished genes first using the K-S test, and then, it uses CFS to select genes from those selected by the K-S test. Results. We adopted support vector machines (SVM as the classification tool and used the criteria of accuracy to evaluate the performance of the classifiers on the selected gene subsets. This approach compared the proposed gene subset selection algorithm with the K-S test, CFS, minimum-redundancy maximum-relevancy (mRMR, and ReliefF algorithms. The average experimental results of the aforementioned gene selection algorithms for 5 gene expression datasets demonstrate that, based on accuracy, the performance of the new K-S and CFS-based algorithm is better than those of the K-S test, CFS, mRMR, and ReliefF algorithms. Conclusions. The experimental results show that the K-S test-CFS gene selection algorithm is a very effective and promising approach compared to the K-S test, CFS, mRMR, and ReliefF algorithms.

ARTIFICIAL NEURAL NETWORKS BASED GEARS MATERIAL SELECTION HYBRID INTELLIGENT SYSTEM

Institute of Scientific and Technical Information of China (English)

X.C. Li; W.X. Zhu; G. Chen; D.S. Mei; J. Zhang; K.M. Chen

2003-01-01

An artificial neural networks(ANNs) based gear material selection hybrid intelligent system is established by analyzing the individual advantages and weakness of expert system (ES) and ANNs and the applications in material select of them. The system mainly consists of tow parts: ES and ANNs. By being trained with much data samples,the back propagation (BP) ANN gets the knowledge of gear materials selection, and is able to inference according to user input. The system realizes the complementing of ANNs and ES. Using this system, engineers without materials selection experience can conveniently deal with gear materials selection.

Tetrasubstituted phenanthrolines as highly potent, water-soluble, and selective g-quadruplex ligands

DEFF Research Database (Denmark)

Larsen, Anders Foller; Nielsen, Mads Corvinius; Ulven, Trond

2012-01-01

Small molecules capable of stabilizing the G-quadruplex (G4) structure are of interest for the development of improved anticancer drugs. Novel 4,7-diamino-substituted 1,10-phenanthroline-2,9-dicarboxamides that represent hybrid structures of known phenanthroline-based ligands have been designed....... An efficient synthetic route to the compounds has been developed and their interactions with various G4 sequences have been evaluated by Förster resonance energy transfer (FRET) melting assays, fluorescent intercalator displacement (FID), electrospray ionization mass spectrometry (ESI-MS), and circular...... dichroism (CD) spectroscopy. The preferred compounds have high aqueous solubility and are strong and potent G4 binders with a high selectivity over duplex DNA; thus, they represent a significant improvement over the lead compounds. Two of the compounds are inhibitors of HeLa and HT1080 cell proliferation....

Selective detection of heavy metal ions by calixarene-based fluorescent molecular sensors

Science.gov (United States)

Zhang, Haitao; Faye, Djibril; Zhang, Han; Lefevre, Jean-Pierre; Delaire, J. A.; Leray, Isabelle

2012-06-01

The synthesis, spectroscopic characterization and complexing properties of calixarene-based fluorescent sensors are reported. The calixarene bearing four dansyl fluorophores (Calix-DANS4) exhibits a very high affinity for the detection of lead. A fluorimetric micro-device based on the use of a Y-shape microchannel was developed and allows lead detection with a 5 ppb detection limit. For mercury detection, a fluorescent molecular sensor containing a calixarene anchored with four 8-quinolinoloxy groups (Calix-Q) has been synthesized. The absorption and fluorescence spectra of this sensor are sensitive to the presence of metal cations. An efficient fluorescence quenching is observed upon mercury complexation because of a photoinduced electron transfer from the fluorophore to the bound mercury. Calix-Q shows a high selectivity towards Hg2+ over interfering cations (Na+, K+, Ca2+, Cu2+, Zn2+, Cd2+ and Pb2+) and a 70 ppb sensitivity.

Optimal load suitability based RAT selection for HSDPA and IEEE 802.11e

DEFF Research Database (Denmark)

Prasad, Ramjee; Cabral, O.; Felez, F.J.

2009-01-01

are a premium. This paper investigates cooperation between networks based Radio Access Technology (RAT) selection algorithm that uses suitability to optimize the choice between WiFi and High Speed Downlink Packet Access (HSDPA). It has been shown that this approach has the potential to provide gain...... by allocating a user terminal to the most preferred network based on traffic type and network load. Optimal load threshold values that maximise the total QoS throughput for the given interworking scenario are 0.6 and 0.53 for HSDPA and WiFi, respectively. This corresponds to a CRRM gain on throughput of 80...

Highly selective and efficient imprinted polymers based on carboxyl-functionalized magnetic nanoparticles for the extraction of gallic acid from pomegranate rind.

Science.gov (United States)

Zhang, Junjie; Li, Benqiang; Yue, Huijuan; Wang, Jing; Zheng, Yuansuo

2018-01-01

With the combined surface imprinting technique and immobilized template strategy, molecularly imprinted magnetic nanoparticles were successfully prepared and coupled with high-performance liquid chromatography to selectively separate and determine gallic acid from the pomegranate rind. On the surface of carboxyl-functionalized magnetic nanospheres, thin imprinting shells were formed using dopamine as monomer and crosslinker. The characteristics, polymerization conditions, and adsorption performances of the resultant nanomaterials were investigated in detail. In addition of good crystallinity, satisfactory magnetism, and uniform morphology of the obtained polymers, they had rapid binding kinetics, high adsorption capacity, and favorable reusability. In the mixed solution of four hydroxybenzoic acids, the prepared nanomaterials have an excellent selectivity to gallic acid with an imprinting factor of as high as 17.5. Therefore, the polymers have great potentials in specific extraction and enrichment of gallic acid from the complex natural resources. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Evaporation rate-based selection of supramolecular chirality.

Science.gov (United States)

Hattori, Shingo; Vandendriessche, Stefaan; Koeckelberghs, Guy; Verbiest, Thierry; Ishii, Kazuyuki

2017-03-09

We demonstrate the evaporation rate-based selection of supramolecular chirality for the first time. P-type aggregates prepared by fast evaporation, and M-type aggregates prepared by slow evaporation are kinetic and thermodynamic products under dynamic reaction conditions, respectively. These findings provide a novel solution reaction chemistry under the dynamic reaction conditions.

A Soft Computing Based Approach Using Modified Selection Strategy for Feature Reduction of Medical Systems

Directory of Open Access Journals (Sweden)

Kursat Zuhtuogullari

2013-01-01

Full Text Available The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

A soft computing based approach using modified selection strategy for feature reduction of medical systems.

Science.gov (United States)

Zuhtuogullari, Kursat; Allahverdi, Novruz; Arikan, Nihat

2013-01-01

The systems consisting high input spaces require high processing times and memory usage. Most of the attribute selection algorithms have the problems of input dimensions limits and information storage problems. These problems are eliminated by means of developed feature reduction software using new modified selection mechanism with middle region solution candidates adding. The hybrid system software is constructed for reducing the input attributes of the systems with large number of input variables. The designed software also supports the roulette wheel selection mechanism. Linear order crossover is used as the recombination operator. In the genetic algorithm based soft computing methods, locking to the local solutions is also a problem which is eliminated by using developed software. Faster and effective results are obtained in the test procedures. Twelve input variables of the urological system have been reduced to the reducts (reduced input attributes) with seven, six, and five elements. It can be seen from the obtained results that the developed software with modified selection has the advantages in the fields of memory allocation, execution time, classification accuracy, sensitivity, and specificity values when compared with the other reduction algorithms by using the urological test data.

Selection of a high performance alloy for gas turbine blade using finite element methods

International Nuclear Information System (INIS)

Khawaja, H.A.; Khan, A.M.; Ali, S.T.

2007-01-01

With the extensive increase in the utilization of energy resources in the modern era, the need of energy extraction from various resources has pronounced in recent years. Thus comprehensive efforts have been made around the globe in the technological development of turbo machines where means of energy extraction is energized fluids. This development led the eviation industry to power boost due to better performing engines. Meanwhile, the structural conformability requirements relative to the functional requirements have also increased with the advent of newer, better performing materials. Thus there is a need to study the material behavior and its usage with the idea of selecting the best possible material for its application. In this work a gas turbine blade of a small turbofan engine, where geometry and aerodynamic data was available, was analyzed for its structural behavior in the proposed mission envelope, where the engine turbine is subjected to high thermal, inertial and aerodynamic loads. FE linear stress analysis was carried out on the turbine blade. The results revealed the upper limit of UTS for the blade. Based on the limiting factor, high performance alloys were selected from the literature. The two most recommended alloy categories for gas turbine blades are NIMONIC and INCONEL from where total of 21 types of INCONEL alloys and 12 of NIMONIC alloys, available on on commercial bases, were analyzed individually to meet the INCONEL alloys for further analysis. On the basis of stress-strain behavior of finalized alloys, the FE restriction of UFOS of 1.33 and yield strength. Final selection is made keeping in view other factors like manufacturability and workability in due consideration. (author)

vuv fluorescence from selective high-order multiphoton excitation of N2

International Nuclear Information System (INIS)

Coffee, Ryan N.; Gibson, George N.

2004-01-01

Recent fluorescence studies suggest that ultrashort pulse laser excitation may be highly selective. Selective high-intensity laser excitation holds important consequences for the physics of multiphoton processes. To establish the extent of this selectivity, we performed a detailed comparative study of the vacuum ultraviolet fluorescence resulting from the interaction of N 2 and Ar with high-intensity infrared ultrashort laser pulses. Both N 2 and Ar reveal two classes of transitions, inner-valence ns ' l ' . From their pressure dependence, we associate each transition with either plasma or direct laser excitation. Furthermore, we qualitatively confirm such associations with the time dependence of the fluorescence signal. Remarkably, only N 2 presents evidence of direct laser excitation. This direct excitation produces ionic nitrogen fragments with inner-valence (2s) holes, two unidentified transitions, and one molecular transition, the N 2 + :X 2 Σ g + 2 Σ u + . We discuss these results in the light of a recently proposed model for multiphoton excitation

Selection of Yeast Strains for Tequila Fermentation Based on Growth Dynamics in Combined Fructose and Ethanol Media.

Science.gov (United States)

Aldrete-Tapia, J A; Miranda-Castilleja, D E; Arvizu-Medrano, S M; Hernández-Iturriaga, M

2018-02-01

The high concentration of fructose in agave juice has been associated with reduced ethanol tolerance of commercial yeasts used for tequila production and low fermentation yields. The selection of autochthonous strains, which are better adapted to agave juice, could improve the process. In this study, a 2-step selection process of yeasts isolated from spontaneous fermentations for tequila production was carried out based on analysis of the growth dynamics in combined conditions of high fructose and ethanol. First, yeast isolates (605) were screened to identify strains tolerant to high fructose (20%) and to ethanol (10%), yielding 89 isolates able to grow in both conditions. From the 89 isolates, the growth curves under 8 treatments of combined fructose (from 20% to 5%) and ethanol (from 0% to 10%) were obtained, and the kinetic parameters were analyzed with principal component analysis and k-means clustering. The resulting yeast strain groups corresponded to the fast, medium and slow growers. A second clustering of only the fast growers led to the selection of 3 Saccharomyces strains (199, 230, 231) that were able to grow rapidly in 4 out of the 8 conditions evaluated. This methodology differentiated strains phenotypically and could be further used for strain selection in other processes. A method to select yeast strains for fermentation taking into account the natural differences of yeast isolates. This methodology is based on the cell exposition to combinations of sugar and ethanol, which are the most important stress factors in fermentation. This strategy will help to identify the most tolerant strain that could improve ethanol yield and reduce fermentation time. © 2018 Institute of Food Technologists®.

Unprecedented Proline-Based Heterogeneous Organocatalyst for Selective Production of Vanillin

Directory of Open Access Journals (Sweden)

Farveh Saberi

2018-04-01

Full Text Available An organocatalytic system based on an unprecedented proline analogue and iron oxide magnetic nanoparticles (Prn/Fe2O3@SiO2 was designed and employed in vanillin production from isoeugenol and vanillyl alcohol. Full characterization of the obtained catalyst revealed the successful functionalization of the nanoparticle surface with the organic moieties. The activity of the magnetic bifunctional material was compared with its proton-unexchanged counterpart. Interestingly, the oxidation of isoeugenol resulted in being highly dependent on the acidic functionalities of the organocatalyst. Nonetheless, the catalytic performance of the proton-unexchanged catalyst suggested that the acidic and basic sites of the Prn/Fe2O3@SiO2 exhibited a synergic effect, giving rise to higher conversion and selectivity. The presence of bifunctional groups in the proline analogue, together with the magnetic properties of the iron oxide nanoparticles, could lead to high efficiency, versatility, recoverability, and reusability.

A Novel Mechanism for Chemical Sensing Based on Solvent-Fluorophore-Substrate Interaction: Highly Selective Alcohol and Water Sensor with Large Fluorescence Signal Contrast.

Science.gov (United States)

Chung, Kyeongwoon; Yang, Da Seul; Jung, Jaehun; Seo, Deokwon; Kwon, Min Sang; Kim, Jinsang

2016-10-06

Differentiation of solvents having similar physicochemical properties, such as ethanol and methanol, is an important issue of interest. However, without performing chemical analyses, discrimination between methanol and ethanol is highly challenging due to their similarity in chemical structure as well as properties. Here, we present a novel type of alcohol and water sensor based on the subtle differences in interaction among solvent analytes, fluorescent organic molecules, and a mesoporous silica gel substrate. A gradual change in the chemical structure of the fluorescent diketopyrrolopyrrole (DPP) derivatives alters their interaction with the substrate and solvent analyte, which creates a distinct intermolecular aggregation of the DPP derivatives on the silica gel substrate depending on the solvent environment and produces a change in the fluorescence color and intensity as a sensory signal. The devised sensor device, which is fabricated with simple drop-casting of the DPP derivative solutions onto a silica gel substrate, exhibited a completely reversible fluorescence signal change with large fluorescence signal contrast, which allows selective solvent detection by simple optical observation with the naked eye under UV light. Superior selectivity of the alcohol and water sensor system, which can clearly distinguish among ethanol, methanol, ethylene glycol, and water, is demonstrated.

Review of Mid- to High-Temperature Solar Selective Absorber Materials

Energy Technology Data Exchange (ETDEWEB)

Kennedy, C. E.

2002-07-01

This report describes the concentrating solar power (CSP) systems using solar absorbers to convert concentrated sunlight to thermal electric power. It is possible to achieve solar absorber surfaces for efficient photothermal conversion having high solar absorptance (a) for solar radiation and a low thermal emittance (e) at the operational temperature. A low reflectance (?'' 0) at wavelengths (?) 3 mm and a high reflectance (?'' 1) at l 3 mm characterize spectrally selective surfaces. The operational temperature ranges of these materials for solar applications can be categorized as low temperature (T< 100 C), mid-temperature (100 C< T< 400 C), and high-temperature (T> 400 C). High- and mid-temperature applications are needed for CSP applications. For CSP applications, the ideal spectrally selective surface would be low-cost and easy to manufacture, chemically and thermally stable in air at elevated operating temperatures (T= 500 C), and have a solar absorptance= 0.98 and a thermal emittance= 0.05 at 500 C.

Large motion high cycle high speed optical fibers for space based applications.

Energy Technology Data Exchange (ETDEWEB)

Stromberg, Peter G. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Tandon, Rajan [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Gibson, Cory S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Reedlunn, Benjamin [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rasberry, Roger David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Rohr, Garth David [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2014-10-01

Future remote sensing applications will require higher resolution and therefore higher data rates (up to perhaps 100 gigabits per second) while achieving lower mass and cost. A current limitation to the design space is high speed high bandwidth data does not cross movable gimbals because of cabling issues. This requires the detectors to be off gimbal. The ability to get data across the gimbal would open up efficiencies in designs where the detectors and the electronics can be placed anywhere on the system. Fiber optic cables provide light weight high speed high bandwidth connections. Current options are limited to 20,000 cycles as opposed to the 1,000,000 cycles needed for future space based applications. To extend this to the million+ regime, requires a thorough understanding of the failure mechanisms and the materials, proper selection of materials (e.g., glass and jacket material) allowable geometry changes to the cable, radiation hardness, etc.

Highly selective detection of single-nucleotide polymorphisms using a quartz crystal microbalance biosensor based on the toehold-mediated strand displacement reaction.

Science.gov (United States)

Wang, Dingzhong; Tang, Wei; Wu, Xiaojie; Wang, Xinyi; Chen, Gengjia; Chen, Qiang; Li, Na; Liu, Feng

2012-08-21

Toehold-mediated strand displacement reaction (SDR) is first introduced to develop a simple quartz crystal microbalance (QCM) biosensor without an enzyme or label at normal temperature for highly selective and sensitive detection of single-nucleotide polymorphism (SNP) in the p53 tumor suppressor gene. A hairpin capture probe with an external toehold is designed and immobilized on the gold electrode surface of QCM. A successive SDR is initiated by the target sequence hybridization with the toehold domain and ends with the unfolding of the capture probe. Finally, the open-loop capture probe hybridizes with the streptavidin-coupled reporter probe as an efficient mass amplifier to enhance the QCM signal. The proposed biosensor displays remarkable specificity to target the p53 gene fragment against single-base mutant sequences (e.g., the largest discrimination factor is 63 to C-C mismatch) and high sensitivity with the detection limit of 0.3 nM at 20 °C. As the crucial component of the fabricated biosensor for providing the high discrimination capability, the design rationale of the capture probe is further verified by fluorescence sensing and atomic force microscopy imaging. Additionally, a recovery of 84.1% is obtained when detecting the target sequence in spiked HeLa cells lysate, demonstrating the feasibility of employing this biosensor in detecting SNPs in biological samples.

Genetic variability, partial regression, Co-heritability studies and their implication in selection of high yielding potato gen

International Nuclear Information System (INIS)

Iqbal, Z.M.; Khan, S.A.

2003-01-01

Partial regression coefficient, genotypic and phenotypic variabilities, heritability co-heritability and genetic advance were studied in 15 Potato varieties of exotic and local origin. Both genotypic and phenotypic coefficients of variations were high for scab and rhizoctonia incidence percentage. Significant partial regression coefficient for emergence percentage indicated its relative importance in tuber yield. High heritability (broadsense) estimates coupled with high genetic advance for plant height, number of stems per plant and scab percentage revealed substantial contribution of additive genetic variance in the expression of these traits. Hence, the selection based on these characters could play a significant role in their improvement the dominance and epistatic variance was more important for character expression of yield ha/sup -1/, emergence and rhizoctonia percentage. This phenomenon is mainly due to the accumulative effects of low heritability and low to moderate genetic advance. The high co-heritability coupled with negative genotypic and phenotypic covariance revealed that selection of varieties having low scab and rhizoctonia percentage resulted in more potato yield. (author)

Performance analysis of a threshold-based parallel multiple beam selection scheme for WDM-based systems for Gamma-Gamma distributions

KAUST Repository

Nam, Sung Sik

2017-03-02

In this paper, we statistically analyze the performance of a threshold-based parallel multiple beam selection scheme (TPMBS) for Free-space optical (FSO) based system with wavelength division multiplexing (WDM) in cases where a pointing error has occurred for practical consideration over independent identically distributed (i.i.d.) Gamma-Gamma fading conditions. Specifically, we statistically analyze the characteristics in operation under conventional heterodyne detection (HD) scheme for both adaptive modulation (AM) case in addition to non-AM case (i.e., coherentnon-coherent binary modulation). Then, based on the statistically derived results, we evaluate the outage probability (CDF) of a selected beam, the average spectral efficiency (ASE), the average number of selected beams (ANSB), and the average bit error rate (BER). Some selected results shows that we can obtain the higher spectral efficiency and simultaneously reduce the potential increasing of the complexity of implementation caused by applying the selection based beam selection scheme without a considerable performance loss.

Depth-Based Selective Blurring in Stereo Images Using Accelerated Framework

Science.gov (United States)

Mukherjee, Subhayan; Guddeti, Ram Mohana Reddy

2014-09-01

We propose a hybrid method for stereo disparity estimation by combining block and region-based stereo matching approaches. It generates dense depth maps from disparity measurements of only 18 % image pixels (left or right). The methodology involves segmenting pixel lightness values using fast K-Means implementation, refining segment boundaries using morphological filtering and connected components analysis; then determining boundaries' disparities using sum of absolute differences (SAD) cost function. Complete disparity maps are reconstructed from boundaries' disparities. We consider an application of our method for depth-based selective blurring of non-interest regions of stereo images, using Gaussian blur to de-focus users' non-interest regions. Experiments on Middlebury dataset demonstrate that our method outperforms traditional disparity estimation approaches using SAD and normalized cross correlation by up to 33.6 % and some recent methods by up to 6.1 %. Further, our method is highly parallelizable using CPU-GPU framework based on Java Thread Pool and APARAPI with speed-up of 5.8 for 250 stereo video frames (4,096 × 2,304).

Comparison of a rational vs. high throughput approach for rapid salt screening and selection.

Science.gov (United States)

Collman, Benjamin M; Miller, Jonathan M; Seadeek, Christopher; Stambek, Julie A; Blackburn, Anthony C

2013-01-01

In recent years, high throughput (HT) screening has become the most widely used approach for early phase salt screening and selection in a drug discovery/development setting. The purpose of this study was to compare a rational approach for salt screening and selection to those results previously generated using a HT approach. The rational approach involved a much smaller number of initial trials (one salt synthesis attempt per counterion) that were selected based on a few strategic solubility determinations of the free form combined with a theoretical analysis of the ideal solvent solubility conditions for salt formation. Salt screening results for sertraline, tamoxifen, and trazodone using the rational approach were compared to those previously generated by HT screening. The rational approach produced similar results to HT screening, including identification of the commercially chosen salt forms, but with a fraction of the crystallization attempts. Moreover, the rational approach provided enough solid from the very initial crystallization of a salt for more thorough and reliable solid-state characterization and thus rapid decision-making. The crystallization techniques used in the rational approach mimic larger-scale process crystallization, allowing smoother technical transfer of the selected salt to the process chemist.

High levels of absorption in orientation-unbiased, radio-selected 3CR Active Galaxies

Science.gov (United States)

Wilkes, Belinda J.; Haas, Martin; Barthel, Peter; Leipski, Christian; Kuraszkiewicz, Joanna; Worrall, Diana; Birkinshaw, Mark; Willner, Steven P.

2014-08-01

A critical problem in understanding active galaxies (AGN) is the separation of intrinsic physical differences from observed differences that are due to orientation. Obscuration of the active nucleus is anisotropic and strongly frequency dependent leading to complex selection effects for observations in most wavebands. These can only be quantified using a sample that is sufficiently unbiased to test orientation effects. Low-frequency radio emission is one way to select a close-to orientation-unbiased sample, albeit limited to the minority of AGN with strong radio emission.Recent Chandra, Spitzer and Herschel observations combined with multi-wavelength data for a complete sample of high-redshift (1half the sample is significantly obscured with ratios of unobscured: Compton thin (22 24.2) = 2.5:1.4:1 in these high-luminosity (log L(0.3-8keV) ~ 44-46) sources. These ratios are consistent with current expectations based on modelingthe Cosmic X-ray Background. A strong correlation with radio orientation constrains the geometry of the obscuring disk/torus to have a ~60 degree opening angle and ~12 degree Compton-thick cross-section. The deduced ~50% obscured fraction of the population contrasts with typical estimates of ~20% obscured in optically- and X-ray-selected high-luminosity samples. Once the primary nuclear emission is obscured, AGN X-ray spectra are frequently dominated by unobscured non-nuclear or scattered nuclear emission which cannot be distinguished from direct nuclear emission with a lower obscuration level unless high quality data is available. As a result, both the level of obscuration and the estimated instrinsic luminosities of highly-obscured AGN are likely to be significantly (*10-1000) underestimated for 25-50% of the population. This may explain the lower obscured fractions reported for optical and X-ray samples which have no independent measure of the AGN luminosity. Correcting AGN samples for these underestimated luminosities would result in

Selection for the compactness of highly expressed genes in Gallus gallus

Directory of Open Access Journals (Sweden)

Zhou Ming

2010-05-01

Full Text Available Abstract Background Coding sequence (CDS length, gene size, and intron length vary within a genome and among genomes. Previous studies in diverse organisms, including human, D. Melanogaster, C. elegans, S. cerevisiae, and Arabidopsis thaliana, indicated that there are negative relationships between expression level and gene size, CDS length as well as intron length. Different models such as selection for economy model, genomic design model, and mutational bias hypotheses have been proposed to explain such observation. The debate of which model is a superior one to explain the observation has not been settled down. The chicken (Gallus gallus is an important model organism that bridges the evolutionary gap between mammals and other vertebrates. As D. Melanogaster, chicken has a larger effective population size, selection for chicken genome is expected to be more effective in increasing protein synthesis efficiency. Therefore, in this study the chicken was used as a model organism to elucidate the interaction between gene features and expression pattern upon selection pressure. Results Based on different technologies, we gathered expression data for nuclear protein coding, single-splicing genes from Gallus gallus genome and compared them with gene parameters. We found that gene size, CDS length, first intron length, average intron length, and total intron length are negatively correlated with expression level and expression breadth significantly. The tissue specificity is positively correlated with the first intron length but negatively correlated with the average intron length, and not correlated with the CDS length and protein domain numbers. Comparison analyses showed that ubiquitously expressed genes and narrowly expressed genes with the similar expression levels do not differ in compactness. Our data provided evidence that the genomic design model can not, at least in part, explain our observations. We grouped all somatic-tissue-specific genes

An enhanced PSO-DEFS based feature selection with biometric authentication for identification of diabetic retinopathy

Directory of Open Access Journals (Sweden)

Umarani Balakrishnan

2016-11-01

Full Text Available Recently, automatic diagnosis of diabetic retinopathy (DR from the retinal image is the most significant research topic in the medical applications. Diabetic macular edema (DME is the major reason for the loss of vision in patients suffering from DR. Early identification of the DR enables to prevent the vision loss and encourage diabetic control activities. Many techniques are developed to diagnose the DR. The major drawbacks of the existing techniques are low accuracy and high time complexity. To overcome these issues, this paper proposes an enhanced particle swarm optimization-differential evolution feature selection (PSO-DEFS based feature selection approach with biometric authentication for the identification of DR. Initially, a hybrid median filter (HMF is used for pre-processing the input images. Then, the pre-processed images are embedded with each other by using least significant bit (LSB for authentication purpose. Simultaneously, the image features are extracted using convoluted local tetra pattern (CLTrP and Tamura features. Feature selection is performed using PSO-DEFS and PSO-gravitational search algorithm (PSO-GSA to reduce time complexity. Based on some performance metrics, the PSO-DEFS is chosen as a better choice for feature selection. The feature selection is performed based on the fitness value. A multi-relevance vector machine (M-RVM is introduced to classify the 13 normal and 62 abnormal images among 75 images from 60 patients. Finally, the DR patients are further classified by M-RVM. The experimental results exhibit that the proposed approach achieves better accuracy, sensitivity, and specificity than the existing techniques.

Selective carbon monoxide oxidation over Ag-based composite oxides

Energy Technology Data Exchange (ETDEWEB)

Guldur, C. [Gazi University, Ankara (Turkey). Chemical Engineering Department; Balikci, F. [Gazi University, Ankara (Turkey). Institute of Science and Technology, Environmental Science Department

2002-02-01

We report our results of the synthesis of 1 : 1 molar ratio of the silver cobalt and silver manganese composite oxide catalysts to remove carbon monoxide from hydrogen-rich fuels by the catalytic oxidation reaction. Catalysts were synthesized by the co-precipitation method. XRD, BET, TGA, catalytic activity and catalyst deactivation studies were used to identify active catalysts. Both CO oxidation and selective CO oxidation were carried out in a microreactor using a reaction gas mixture of 1 vol% CO in air and another gas mixture was prepared by mixing 1 vol% CO, 2 vol% O{sub 2}, 84 vol% H{sub 2}, the balance being He. 15 vol% CO{sub 2} was added to the reactant gas mixture in order to determine the effect of CO{sub 2}, reaction gases were passed through the humidifier to determine the effect of the water vapor on the oxidation reaction. It was demonstrated that metal oxide base was decomposed to the metallic phase and surface areas of the catalysts were decreased when the calcination temperature increased from 200{sup o}C to 500{sup o}C. Ag/Co composite oxide catalyst calcined at 200{sup o}C gave good activity at low temperatures and 90% of CO conversion at 180{sup o}C was obtained for the selective CO oxidation reaction. The addition of the impurities (CO{sub 2} or H{sub 2}O) decreased the activity of catalyst for selective CO oxidation in order to get highly rich hydrogen fuels. (author)

Using genomic DNA-based probe-selection to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species

Directory of Open Access Journals (Sweden)

Townsend Henrik J

2005-11-01

Full Text Available Abstract High-density oligonucleotide (oligo arrays are a powerful tool for transcript profiling. Arrays based on GeneChip® technology are amongst the most widely used, although GeneChip® arrays are currently available for only a small number of plant and animal species. Thus, we have developed a method to improve the sensitivity of high-density oligonucleotide arrays when applied to heterologous species and tested the method by analysing the transcriptome of Brassica oleracea L., a species for which no GeneChip® array is available, using a GeneChip® array designed for Arabidopsis thaliana (L. Heynh. Genomic DNA from B. oleracea was labelled and hybridised to the ATH1-121501 GeneChip® array. Arabidopsis thaliana probe-pairs that hybridised to the B. oleracea genomic DNA on the basis of the perfect-match (PM probe signal were then selected for subsequent B. oleracea transcriptome analysis using a .cel file parser script to generate probe mask files. The transcriptional response of B. oleracea to a mineral nutrient (phosphorus; P stress was quantified using probe mask files generated for a wide range of gDNA hybridisation intensity thresholds. An example probe mask file generated with a gDNA hybridisation intensity threshold of 400 removed > 68 % of the available PM probes from the analysis but retained >96 % of available A. thaliana probe-sets. Ninety-nine of these genes were then identified as significantly regulated under P stress in B. oleracea, including the homologues of P stress responsive genes in A. thaliana. Increasing the gDNA hybridisation intensity thresholds up to 500 for probe-selection increased the sensitivity of the GeneChip® array to detect regulation of gene expression in B. oleracea under P stress by up to 13-fold. Our open-source software to create probe mask files is freely available http://affymetrix.arabidopsis.info/xspecies/ and may be used to facilitate transcriptomic analyses of a wide range of plant and animal

A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism

Science.gov (United States)

Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

2015-03-01

In recent years, a variety of chaos-based image cryptosystems have been investigated to meet the increasing demand for real-time secure image transmission. Most of them are based on permutation-diffusion architecture, in which permutation and diffusion are two independent procedures with fixed control parameters. This property results in two flaws. (1) At least two chaotic state variables are required for encrypting one plain pixel, in permutation and diffusion stages respectively. Chaotic state variables produced with high computation complexity are not sufficiently used. (2) The key stream solely depends on the secret key, and hence the cryptosystem is vulnerable against known/chosen-plaintext attacks. In this paper, a fast chaos-based image encryption scheme with a dynamic state variables selection mechanism is proposed to enhance the security and promote the efficiency of chaos-based image cryptosystems. Experimental simulations and extensive cryptanalysis have been carried out and the results prove the superior security and high efficiency of the scheme.

High-power, cladding-pumped all-fiber laser with selective transverse mode generation property.

Science.gov (United States)

Li, Lei; Wang, Meng; Liu, Tong; Leng, Jinyong; Zhou, Pu; Chen, Jinbao

2017-06-10

We demonstrate, to the best of our knowledge, the first cladding-pumped all-fiber oscillator configuration with selective transverse mode generation based on a mode-selective fiber Bragg grating pair. Operating in the second-order (LP 11 ) mode, maximum output power of 4.2 W is obtained with slope efficiency of about 38%. This is the highest reported output power of single higher-order transverse mode generation in an all-fiber configuration. The intensity distribution profile and spectral evolution have also been investigated in this paper. Our work suggests the potential of realizing higher power with selective transverse mode operation based on a mode-selective fiber Bragg grating pair.

Molecularly imprinted fluorescent probe based on FRET for selective and sensitive detection of doxorubicin

Energy Technology Data Exchange (ETDEWEB)

Xu, Zhifeng, E-mail: 897061147@qq.com [College of Chemistry and Materials Science, Hengyang Normal University, Key Laboratory of Functional Organometallic Materials of Hunan Province University, Hengyang 421008 (China); Deng, Peihong; Li, Junhua [College of Chemistry and Materials Science, Hengyang Normal University, Key Laboratory of Functional Organometallic Materials of Hunan Province University, Hengyang 421008 (China); Xu, Li [Department of Applied Chemistry, College of Materials and Energy, South China Agricultural University, Guangzhou 510642 (China); Tang, Siping [College of Chemistry and Materials Science, Hengyang Normal University, Key Laboratory of Functional Organometallic Materials of Hunan Province University, Hengyang 421008 (China)

2017-04-15

Highlights: • FRET-based molecularly imprinted probe for detection of doxorubicin was prepared. • The detection limit of the probe was 13.8 nM for doxorubicin. • The FRET-based probe had a higher selectivity for the template than ordinary MIMs. - Abstract: In this work, a new type of fluorescent probe for detection of doxorubicin has been constructed by the combined use of fluorescence resonance energy transfer (FRET) technology and molecular imprinting technique (MIT). Using doxorubicin as the template, the molecularly imprinted polymer thin layer was fabricated on the surfaces of carbon dot (CD) modified silica by sol-gel polymerization. The excitation energy of the fluorescent donor (CDs) could be transferred to the fluorescent acceptor (doxorubicin). The FRET based fluorescent probe demonstrated high sensitivity and selectivity for doxorubicin. The detection limit was 13.8 nM. The fluorescent probe was successfully applied for detecting doxorubicin in doxorubicin-spiked plasmas with a recovery of 96.8–103.8%, a relative standard deviation (RSD) of 1.3–2.8%. The strategy for construction of FRET-based molecularly imprinted materials developed in this work is very promising for analytical applications.

Network based on statistical multiplexing for event selection and event builder systems in high energy physics experiments

International Nuclear Information System (INIS)

Calvet, D.

2000-03-01

Systems for on-line event selection in future high energy physics experiments will use advanced distributed computing techniques and will need high speed networks. After a brief description of projects at the Large Hadron Collider, the architectures initially proposed for the Trigger and Data AcQuisition (TD/DAQ) systems of ATLAS and CMS experiments are presented and analyzed. A new architecture for the ATLAS T/DAQ is introduced. Candidate network technologies for this system are described. This thesis focuses on ATM. A variety of network structures and topologies suited to partial and full event building are investigated. The need for efficient networking is shown. Optimization techniques for high speed messaging and their implementation on ATM components are described. Small scale demonstrator systems consisting of up to 48 computers (∼1:20 of the final level 2 trigger) connected via ATM are described. Performance results are presented. Extrapolation of measurements and evaluation of needs lead to a proposal of implementation for the main network of the ATLAS T/DAQ system. (author)

The Availability and Utilization of School Library Resources in Some Selected Secondary Schools (High School) in Rivers State

Science.gov (United States)

Owate, C. N.; Iroha, Okpa

2013-01-01

This study investigates the availability and utilization of school library resources by Secondary School (High School) Students. Eight Selected Secondary Schools in Rivers State, Nigeria were chosen based on their performance in external examinations and geographic locations. In carrying out the research, questionnaires were administered to both…

FPGA-Based Efficient Hardware/Software Co-Design for Industrial Systems with Consideration of Output Selection

Science.gov (United States)

Deliparaschos, Kyriakos M.; Michail, Konstantinos; Zolotas, Argyrios C.; Tzafestas, Spyros G.

2016-05-01

This work presents a field programmable gate array (FPGA)-based embedded software platform coupled with a software-based plant, forming a hardware-in-the-loop (HIL) that is used to validate a systematic sensor selection framework. The systematic sensor selection framework combines multi-objective optimization, linear-quadratic-Gaussian (LQG)-type control, and the nonlinear model of a maglev suspension. A robustness analysis of the closed-loop is followed (prior to implementation) supporting the appropriateness of the solution under parametric variation. The analysis also shows that quantization is robust under different controller gains. While the LQG controller is implemented on an FPGA, the physical process is realized in a high-level system modeling environment. FPGA technology enables rapid evaluation of the algorithms and test designs under realistic scenarios avoiding heavy time penalty associated with hardware description language (HDL) simulators. The HIL technique facilitates significant speed-up in the required execution time when compared to its software-based counterpart model.

Different cortical mechanisms for spatial vs. feature-based attentional selection in visual working memory

Directory of Open Access Journals (Sweden)

Anna Heuer

2016-08-01

Full Text Available The limited capacity of visual working memory necessitates attentional mechanisms that selectively update and maintain only the most task-relevant content. Psychophysical experiments have shown that the retroactive selection of memory content can be based on visual properties such as location or shape, but the neural basis for such differential selection is unknown. For example, it is not known if there are different cortical modules specialized for spatial versus feature-based mnemonic attention, in the same way that has been demonstrated for attention to perceptual input. Here, we used transcranial magnetic stimulation (TMS to identify areas in human parietal and occipital cortex involved in the selection of objects from memory based on cues to their location (spatial information or their shape (featural information. We found that TMS over the supramarginal gyrus (SMG selectively facilitated spatial selection, whereas TMS over the lateral occipital cortex selectively enhanced feature-based selection for remembered objects in the contralateral visual field. Thus, different cortical regions are responsible for spatial vs. feature-based selection of working memory representations. Since the same regions are involved in attention to external events, these new findings indicate overlapping mechanisms for attentional control over perceptual input and mnemonic representations.

Highly selective piezoelectric sensor for lead(II) based on the lead-catalyzed release of gold nanoparticles from a self-assembled nanosurface

International Nuclear Information System (INIS)

Xie, Yunfeng; Jin, Yulong; Huang, Yanyan; Liu, Guoquan; Zhao, Rui

2014-01-01

A novel quartz crystal microbalance (QCM) sensor has been developed for highly selective and sensitive detection of Pb 2+ by exploiting the catalytic effect of Pb 2+ ions on the leaching of gold nanoparticles from the surface of a QCM sensor. The use of self-assembled gold nanoparticles (AuNPs) strongly enlarges the size of the interface and thus amplifies the analytical response resulting from the loss of mass. This results in a very low detection limit for Pb 2+ (30 nM). The high selectivity is demonstrated by studying the effect of potentially interfering ions both in the absence and presence of Pb 2+ ions. This simple and well reproducible sensor was applied to the determination of lead in the spiked drinking water. This work provides a novel strategy for fabricating QCM sensors towards Pb 2+ in real samples. (author)

Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

Directory of Open Access Journals (Sweden)

Rakesh Garg

2015-06-01

Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

Uniform design based SVM model selection for face recognition

Science.gov (United States)

Li, Weihong; Liu, Lijuan; Gong, Weiguo

2010-02-01

Support vector machine (SVM) has been proved to be a powerful tool for face recognition. The generalization capacity of SVM depends on the model with optimal hyperparameters. The computational cost of SVM model selection results in application difficulty in face recognition. In order to overcome the shortcoming, we utilize the advantage of uniform design--space filling designs and uniformly scattering theory to seek for optimal SVM hyperparameters. Then we propose a face recognition scheme based on SVM with optimal model which obtained by replacing the grid and gradient-based method with uniform design. The experimental results on Yale and PIE face databases show that the proposed method significantly improves the efficiency of SVM model selection.

Highly selective apo-arginase based method for sensitive enzymatic assay of manganese (II) and cobalt (II) ions

Science.gov (United States)

Stasyuk, Nataliya; Gayda, Galina; Zakalskiy, Andriy; Zakalska, Oksana; Errachid, Abdelhamid; Gonchar, Mykhailo

2018-03-01

A novel enzymatic method of manganese (II) and cobalt (II) ions assay, based on using apo-enzyme of Mn2 +-dependent recombinant arginase I (arginase) and 2,3-butanedione monoxime (DMO) as a chemical reagent is proposed. The principle of the method is the evaluation of the activity of L-arginine-hydrolyzing of arginase holoenzyme after the specific binding of Mn2 + or Co2 + with apo-arginase. Urea, which is the product of enzymatic hydrolysis of L-arginine (Arg), reacts with DMO and the resulted compound is detected by both fluorometry and visual spectrophotometry. Thus, the content of metal ions in the tested samples can be determined by measuring the level of urea generated after enzymatic hydrolysis of Arg by reconstructed arginase holoenzyme in the presence of tested metal ions. The linearity range of the fluorometric apo-arginase-DMO method in the case of Mn2 + assay is from 4 pM to 1.10 nM with a limit of detection of 1 pM Mn2 +, whereas the linearity range of the present method in the case of Co2 + assay is from 8 pM to 45 nM with a limit of detection of 2.5 pM Co2 +. The proposed method being highly sensitive, selective, valid and low-cost, may be useful to monitor Mn2 + and Co2 + content in clinical laboratories, food industry and environmental control service.

Natural Selection on Genes Related to Cardiovascular Health in High-Altitude Adapted Andeans.

Science.gov (United States)

Crawford, Jacob E; Amaru, Ricardo; Song, Jihyun; Julian, Colleen G; Racimo, Fernando; Cheng, Jade Yu; Guo, Xiuqing; Yao, Jie; Ambale-Venkatesh, Bharath; Lima, João A; Rotter, Jerome I; Stehlik, Josef; Moore, Lorna G; Prchal, Josef T; Nielsen, Rasmus

2017-11-02

The increase in red blood cell mass (polycythemia) due to the reduced oxygen availability (hypoxia) of residence at high altitude or other conditions is generally thought to be beneficial in terms of increasing tissue oxygen supply. However, the extreme polycythemia and accompanying increased mortality due to heart failure in chronic mountain sickness most likely reduces fitness. Tibetan highlanders have adapted to high altitude, possibly in part via the selection of genetic variants associated with reduced polycythemic response to hypoxia. In contrast, high-altitude-adapted Quechua- and Aymara-speaking inhabitants of the Andean Altiplano are not protected from high-altitude polycythemia in the same way, yet they exhibit other adaptive features for which the genetic underpinnings remain obscure. Here, we used whole-genome sequencing to scan high-altitude Andeans for signals of selection. The genes showing the strongest evidence of selection-including BRINP3, NOS2, and TBX5-are associated with cardiovascular development and function but are not in the response-to-hypoxia pathway. Using association mapping, we demonstrated that the haplotypes under selection are associated with phenotypic variations related to cardiovascular health. We hypothesize that selection in response to hypoxia in Andeans could have vascular effects and could serve to mitigate the deleterious effects of polycythemia rather than reduce polycythemia itself. Copyright © 2017. Published by Elsevier Inc.

Attribute based selection of thermoplastic resin for vacuum infusion process

DEFF Research Database (Denmark)

Prabhakaran, R.T. Durai; Lystrup, Aage; Løgstrup Andersen, Tom

2011-01-01

The composite industry looks toward a new material system (resins) based on thermoplastic polymers for the vacuum infusion process, similar to the infusion process using thermosetting polymers. A large number of thermoplastics are available in the market with a variety of properties suitable...... for different engineering applications, and few of those are available in a not yet polymerised form suitable for resin infusion. The proper selection of a new resin system among these thermoplastic polymers is a concern for manufactures in the current scenario and a special mathematical tool would...... be beneficial. In this paper, the authors introduce a new decision making tool for resin selection based on significant attributes. This article provides a broad overview of suitable thermoplastic material systems for vacuum infusion process available in today’s market. An illustrative example—resin selection...

Selectivity Enhancement by Using Double-Layer MOX-Based Gas Sensors Prepared by Flame Spray Pyrolysis (FSP

Directory of Open Access Journals (Sweden)

Julia Rebholz

2016-09-01

Full Text Available Here we present a novel concept for the selective recognition of different target gases with a multilayer semiconducting metal oxide (SMOX-based sensor device. Direct current (DC electrical resistance measurements were performed during exposure to CO and ethanol as single gases and mixtures of highly porous metal oxide double- and single-layer sensors obtained by flame spray pyrolysis. The results show that the calculated resistance ratios of the single- and double-layer sensors are a good indicator for the presence of specific gases in the atmosphere, and can constitute some building blocks for the development of chemical logic devices. Due to the inherent lack of selectivity of SMOX-based gas sensors, such devices could be especially relevant for domestic applications.

High throughput route selection in multi-rate wireless mesh networks

Institute of Scientific and Technical Information of China (English)

WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

2008-01-01

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

Road network selection for small-scale maps using an improved centrality-based algorithm

Directory of Open Access Journals (Sweden)

Roy Weiss

2014-12-01

Full Text Available The road network is one of the key feature classes in topographic maps and databases. In the task of deriving road networks for products at smaller scales, road network selection forms a prerequisite for all other generalization operators, and is thus a fundamental operation in the overall process of topographic map and database production. The objective of this work was to develop an algorithm for automated road network selection from a large-scale (1:10,000 to a small-scale database (1:200,000. The project was pursued in collaboration with swisstopo, the national mapping agency of Switzerland, with generic mapping requirements in mind. Preliminary experiments suggested that a selection algorithm based on betweenness centrality performed best for this purpose, yet also exposed problems. The main contribution of this paper thus consists of four extensions that address deficiencies of the basic centrality-based algorithm and lead to a significant improvement of the results. The first two extensions improve the formation of strokes concatenating the road segments, which is crucial since strokes provide the foundation upon which the network centrality measure is computed. Thus, the first extension ensures that roundabouts are detected and collapsed, thus avoiding interruptions of strokes by roundabouts, while the second introduces additional semantics in the process of stroke formation, allowing longer and more plausible strokes to built. The third extension detects areas of high road density (i.e., urban areas using density-based clustering and then locally increases the threshold of the centrality measure used to select road segments, such that more thinning takes place in those areas. Finally, since the basic algorithm tends to create dead-ends—which however are not tolerated in small-scale maps—the fourth extension reconnects these dead-ends to the main network, searching for the best path in the main heading of the dead-end.

Biotin-tagged proteins: Reagents for efficient ELISA-based serodiagnosis and phage display-based affinity selection.

Science.gov (United States)

Verma, Vaishali; Kaur, Charanpreet; Grover, Payal; Gupta, Amita; Chaudhary, Vijay K

2018-01-01

The high-affinity interaction between biotin and streptavidin has opened avenues for using recombinant proteins with site-specific biotinylation to achieve efficient and directional immobilization. The site-specific biotinylation of proteins carrying a 15 amino acid long Biotin Acceptor Peptide tag (BAP; also known as AviTag) is effected on a specific lysine either by co-expressing the E. coli BirA enzyme in vivo or by using purified recombinant E. coli BirA enzyme in the presence of ATP and biotin in vitro. In this paper, we have designed a T7 promoter-lac operator-based expression vector for rapid and efficient cloning, and high-level cytosolic expression of proteins carrying a C-terminal BAP tag in E. coli with TEV protease cleavable N-terminal deca-histidine tag, useful for initial purification. Furthermore, a robust three-step purification pipeline integrated with well-optimized protocols for TEV protease-based H10 tag removal, and recombinant BirA enzyme-based site-specific in vitro biotinylation is described to obtain highly pure biotinylated proteins. Most importantly, the paper demonstrates superior sensitivities in indirect ELISA with directional and efficient immobilization of biotin-tagged proteins on streptavidin-coated surfaces in comparison to passive immobilization. The use of biotin-tagged proteins through specific immobilization also allows more efficient selection of binders from a phage-displayed naïve antibody library. In addition, for both these applications, specific immobilization requires much less amount of protein as compared to passive immobilization and can be easily multiplexed. The simplified strategy described here for the production of highly pure biotin-tagged proteins will find use in numerous applications, including those, which may require immobilization of multiple proteins simultaneously on a solid surface.

Highly selective enrichment of phosphorylated peptides using titanium dioxide

DEFF Research Database (Denmark)

Thingholm, Tine; Jørgensen, Thomas J D; Jensen, Ole N

2006-01-01

-column. Although phosphopeptide enrichment can be achieved by using TFA and acetonitrile alone, the selectivity is dramatically enhanced by adding DHB or phthalic acid since these compounds, in conjunction with the low pH caused by TFA, prevent binding of nonphosphorylated peptides to TiO2. Using an alkaline...... a protocol for selective phosphopeptide enrichment using titanium dioxide (TiO2) chromatography. The selectivity toward phosphopeptides is obtained by loading the sample in a 2,5-dihydroxybenzoic acid (DHB) or phthalic acid solution containing acetonitrile and trifluoroacetic acid (TFA) onto a TiO2 micro...... solution (pH > or = 10.5) both monophosphorylated and multiphosphorylated peptides are eluted from the TiO2 beads. This highly efficient method for purification of phosphopeptides is well suited for the characterization of phosphoproteins from both in vitro and in vivo studies in combination with mass...

Robot soccer action selection based on Q learning

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements

[Employees in high-reliability organizations: systematic selection of personnel as a final criterion].

Science.gov (United States)

Oubaid, V; Anheuser, P

2014-05-01

Employees represent an important safety factor in high-reliability organizations. The combination of clear organizational structures, a nonpunitive safety culture, and psychological personnel selection guarantee a high level of safety. The cockpit personnel selection process of a major German airline is presented in order to demonstrate a possible transferability into medicine and urology.

Space-based visual attention: a marker of immature selective attention in toddlers?

Science.gov (United States)

Rivière, James; Brisson, Julie

2014-11-01

Various studies suggested that attentional difficulties cause toddlers' failure in some spatial search tasks. However, attention is not a unitary construct and this study investigated two attentional mechanisms: location selection (space-based attention) and object selection (object-based attention). We investigated how toddlers' attention is distributed in the visual field during a manual search task for objects moving out of sight, namely the moving boxes task. Results show that 2.5-year-olds who failed this task allocated more attention to the location of the relevant object than to the object itself. These findings suggest that in some manual search tasks the primacy of space-based attention over object-based attention could be a marker of immature selective attention in toddlers. © 2014 Wiley Periodicals, Inc.

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition.

Science.gov (United States)

Zhang, Jianhai; Chen, Ming; Zhao, Shaokai; Hu, Sanqing; Shi, Zhiguo; Cao, Yu

2016-09-22

Electroencephalogram (EEG) signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI) environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP). Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation). Furthermore, support vector machine (SVM) was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels' weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels). In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a contribution to the

ReliefF-Based EEG Sensor Selection Methods for Emotion Recognition

Directory of Open Access Journals (Sweden)

Jianhai Zhang

2016-09-01

Full Text Available Electroencephalogram (EEG signals recorded from sensor electrodes on the scalp can directly detect the brain dynamics in response to different emotional states. Emotion recognition from EEG signals has attracted broad attention, partly due to the rapid development of wearable computing and the needs of a more immersive human-computer interface (HCI environment. To improve the recognition performance, multi-channel EEG signals are usually used. A large set of EEG sensor channels will add to the computational complexity and cause users inconvenience. ReliefF-based channel selection methods were systematically investigated for EEG-based emotion recognition on a database for emotion analysis using physiological signals (DEAP. Three strategies were employed to select the best channels in classifying four emotional states (joy, fear, sadness and relaxation. Furthermore, support vector machine (SVM was used as a classifier to validate the performance of the channel selection results. The experimental results showed the effectiveness of our methods and the comparison with the similar strategies, based on the F-score, was given. Strategies to evaluate a channel as a unity gave better performance in channel reduction with an acceptable loss of accuracy. In the third strategy, after adjusting channels’ weights according to their contribution to the classification accuracy, the number of channels was reduced to eight with a slight loss of accuracy (58.51% ± 10.05% versus the best classification accuracy 59.13% ± 11.00% using 19 channels. In addition, the study of selecting subject-independent channels, related to emotion processing, was also implemented. The sensors, selected subject-independently from frontal, parietal lobes, have been identified to provide more discriminative information associated with emotion processing, and are distributed symmetrically over the scalp, which is consistent with the existing literature. The results will make a

Revealing metabolite biomarkers for acupuncture treatment by linear programming based feature selection.

Science.gov (United States)

Wang, Yong; Wu, Qiao-Feng; Chen, Chen; Wu, Ling-Yun; Yan, Xian-Zhong; Yu, Shu-Guang; Zhang, Xiang-Sun; Liang, Fan-Rong

2012-01-01

Acupuncture has been practiced in China for thousands of years as part of the Traditional Chinese Medicine (TCM) and has gradually accepted in western countries as an alternative or complementary treatment. However, the underlying mechanism of acupuncture, especially whether there exists any difference between varies acupoints, remains largely unknown, which hinders its widespread use. In this study, we develop a novel Linear Programming based Feature Selection method (LPFS) to understand the mechanism of acupuncture effect, at molecular level, by revealing the metabolite biomarkers for acupuncture treatment. Specifically, we generate and investigate the high-throughput metabolic profiles of acupuncture treatment at several acupoints in human. To select the subsets of metabolites that best characterize the acupuncture effect for each meridian point, an optimization model is proposed to identify biomarkers from high-dimensional metabolic data from case and control samples. Importantly, we use nearest centroid as the prototype to simultaneously minimize the number of selected features and the leave-one-out cross validation error of classifier. We compared the performance of LPFS to several state-of-the-art methods, such as SVM recursive feature elimination (SVM-RFE) and sparse multinomial logistic regression approach (SMLR). We find that our LPFS method tends to reveal a small set of metabolites with small standard deviation and large shifts, which exactly serves our requirement for good biomarker. Biologically, several metabolite biomarkers for acupuncture treatment are revealed and serve as the candidates for further mechanism investigation. Also biomakers derived from five meridian points, Zusanli (ST36), Liangmen (ST21), Juliao (ST3), Yanglingquan (GB34), and Weizhong (BL40), are compared for their similarity and difference, which provide evidence for the specificity of acupoints. Our result demonstrates that metabolic profiling might be a promising method to

Carbon molecular sieve membrane from a microporous spirobisindane-based polyimide precursor with enhanced ethylene/ethane mixed-gas selectivity

KAUST Repository

Salinas, Octavio

2017-01-13

Ethylene is typically produced by steam cracking of various hydrocarbon feedstocks. The gaseous products are then separated in a demethanizer followed by a deethanizer unit and finally sent to a C splitter for the final purification step. Cryogenic distillation of ethylene from ethane is the most energy-intensive unit operation process in the chemical industry. Therefore, the development of more energy-efficient processes for ethylene purification is highly desirable. Membrane-based separation has been proposed as an alternative option for replacement or debottlenecking of C splitters but current polymer membrane materials exhibit insufficient mixed-gas CH/CH selectivity (<7) to be technically and economically attractive. In this work, a highly selective carbon molecular sieve (CMS) membrane derived from a novel spirobisindane-based polyimide of intrinsic microporosity (PIM-6FDA) was developed and characterized. PIM-6FDA showed a single-stage degradation process under an inert nitrogen atmosphere which commenced at ∼480 °C. The CMS formed by pyrolysis at 800 °C had a diffusion/size-sieving-controlled morphology with a mixed-gas (50% CH/50% CH) ethylene/ethane selectivity of 15.6 at 20 bar feed pressure at 35 °C. The mixed-gas ethylene/ethane selectivity is the highest reported value for CMS-type membranes to date.

Wave impedance selection for passivity-based bilateral teleoperation

Science.gov (United States)

D'Amore, Nicholas John

When a task must be executed in a remote or dangerous environment, teleoperation systems may be employed to extend the influence of the human operator. In the case of manipulation tasks, haptic feedback of the forces experienced by the remote (slave) system is often highly useful in improving an operator's ability to perform effectively. In many of these cases (especially teleoperation over the internet and ground-to-space teleoperation), substantial communication latency exists in the control loop and has the strong tendency to cause instability of the system. The first viable solution to this problem in the literature was based on a scattering/wave transformation from transmission line theory. This wave transformation requires the designer to select a wave impedance parameter appropriate to the teleoperation system. It is widely recognized that a small value of wave impedance is well suited to free motion and a large value is preferable for contact tasks. Beyond this basic observation, however, very little guidance exists in the literature regarding the selection of an appropriate value. Moreover, prior research on impedance selection generally fails to account for the fact that in any realistic contact task there will simultaneously exist contact considerations (perpendicular to the surface of contact) and quasi-free-motion considerations (parallel to the surface of contact). The primary contribution of the present work is to introduce an approximate linearized optimum for the choice of wave impedance and to apply this quasi-optimal choice to the Cartesian reality of such a contact task, in which it cannot be expected that a given joint will be either perfectly normal to or perfectly parallel to the motion constraint. The proposed scheme selects a wave impedance matrix that is appropriate to the conditions encountered by the manipulator. This choice may be implemented as a static wave impedance value or as a time-varying choice updated according to the

A threshold-based multiple optical signal selection scheme for WDM FSO systems

KAUST Repository

Nam, Sung Sik

2017-07-20

In this paper, we propose a threshold-based-multiple optical signal selection scheme (TMOS) for free-space optical systems based on wavelength division multiplexing. With the proposed TMOS, we can obtain higher spectral efficiency while reducing the potential increase in complexity of implementation caused by applying a selection-based beam selection scheme without a considerable performance loss. Here, to accurately characterize the performance of the proposed TMOS, we statistically analyze the characteristics with heterodyne detection technique over independent and identically distributed Log-normal turbulence conditions taking into considerations the impact of pointing error. Specifically, we derive exact closed-form expressions for the average bit error rate, and the average spectral efficiency by adopting an adaptive modulation. Some selected results shows that the average spectral efficiency can be increased with TMOS while the system requirement is satisfied.

A threshold-based multiple optical signal selection scheme for WDM FSO systems

KAUST Repository

Nam, Sung Sik; Alouini, Mohamed-Slim; Ko, Young-Chai; Cho, Sung Ho

2017-01-01

In this paper, we propose a threshold-based-multiple optical signal selection scheme (TMOS) for free-space optical systems based on wavelength division multiplexing. With the proposed TMOS, we can obtain higher spectral efficiency while reducing the potential increase in complexity of implementation caused by applying a selection-based beam selection scheme without a considerable performance loss. Here, to accurately characterize the performance of the proposed TMOS, we statistically analyze the characteristics with heterodyne detection technique over independent and identically distributed Log-normal turbulence conditions taking into considerations the impact of pointing error. Specifically, we derive exact closed-form expressions for the average bit error rate, and the average spectral efficiency by adopting an adaptive modulation. Some selected results shows that the average spectral efficiency can be increased with TMOS while the system requirement is satisfied.

Individual-based models for adaptive diversification in high-dimensional phenotype spaces.

Science.gov (United States)

Ispolatov, Iaroslav; Madhok, Vaibhav; Doebeli, Michael

2016-02-07

Most theories of evolutionary diversification are based on equilibrium assumptions: they are either based on optimality arguments involving static fitness landscapes, or they assume that populations first evolve to an equilibrium state before diversification occurs, as exemplified by the concept of evolutionary branching points in adaptive dynamics theory. Recent results indicate that adaptive dynamics may often not converge to equilibrium points and instead generate complicated trajectories if evolution takes place in high-dimensional phenotype spaces. Even though some analytical results on diversification in complex phenotype spaces are available, to study this problem in general we need to reconstruct individual-based models from the adaptive dynamics generating the non-equilibrium dynamics. Here we first provide a method to construct individual-based models such that they faithfully reproduce the given adaptive dynamics attractor without diversification. We then show that a propensity to diversify can be introduced by adding Gaussian competition terms that generate frequency dependence while still preserving the same adaptive dynamics. For sufficiently strong competition, the disruptive selection generated by frequency-dependence overcomes the directional evolution along the selection gradient and leads to diversification in phenotypic directions that are orthogonal to the selection gradient. Copyright © 2015 Elsevier Ltd. All rights reserved.

Initial characterisation of low and high seed dormancy populations of Lolium rigidum produced by repeated selection.

Science.gov (United States)

Goggin, Danica E; Emery, R J Neil; Powles, Stephen B; Steadman, Kathryn J

2010-10-15

The physiological and biochemical bases of seed dormancy in Lolium rigidum (annual ryegrass) are largely unknown, and study of this process is complicated by the outcrossing nature of the species and the strong influence of environment on seed dormancy. In order to identify heritable biochemical factors contributing to seed dormancy in L. rigidum, seeds from a field-collected population were used to select sub-populations with consistently low or high seed dormancy over four generations. Low-dormancy seeds showed constitutive alpha-amylase activity prior to imbibition, higher concentrations of polyphenols and cis-zeatin, and lower abscisic acid and cis-zeatin riboside concentrations than high-dormancy seeds. Selection for high dormancy was associated with a reduction in response to dark-stratification for 21d at 20 degrees C (an effective means of releasing dormancy in the original, unselected population) over successive generations, but fluridone remained effective in breaking dormancy. Crossing of low- and high-dormancy populations indicated that dormancy level was not dependent upon the maternal genotype of the seed, and that the constitutive alpha-amylase activity and high seed anthocyanin concentrations characteristic of the low-dormancy populations were not correlated to high basal germination ability. Copyright (c) 2010 Elsevier GmbH. All rights reserved.

Transmit antenna selection based on shadowing side information

KAUST Repository

Yilmaz, Ferkan

2011-05-01

In this paper, we propose a new transmit antenna selection scheme based on shadowing side information. In the proposed scheme, single transmit antenna which has the highest shadowing coefficient is selected. By the proposed technique, usage of the feedback channel and channel estimation complexity at the receiver can be reduced. We consider independent but not identically distributed Generalized-K composite fading model, which is a general composite fading & shadowing channel model for wireless environments. Exact closed-form outage probability, moment generating function and symbol error probability expressions are derived. In addition, theoretical performance results are validated by Monte Carlo simulations. © 2011 IEEE.

Transmit antenna selection based on shadowing side information

KAUST Repository

Yilmaz, Ferkan; Yilmaz, Ahmet Oǧuz; Alouini, Mohamed-Slim; Kucur, Oǧuz

2011-01-01

In this paper, we propose a new transmit antenna selection scheme based on shadowing side information. In the proposed scheme, single transmit antenna which has the highest shadowing coefficient is selected. By the proposed technique, usage of the feedback channel and channel estimation complexity at the receiver can be reduced. We consider independent but not identically distributed Generalized-K composite fading model, which is a general composite fading & shadowing channel model for wireless environments. Exact closed-form outage probability, moment generating function and symbol error probability expressions are derived. In addition, theoretical performance results are validated by Monte Carlo simulations. © 2011 IEEE.

Acrylamide exposure among Turkish toddlers from selected cereal-based baby food samples.

Science.gov (United States)

Cengiz, Mehmet Fatih; Gündüz, Cennet Pelin Boyacı

2013-10-01

In this study, acrylamide exposure from selected cereal-based baby food samples was investigated among toddlers aged 1-3 years in Turkey. The study contained three steps. The first step was collecting food consumption data and toddlers' physical properties, such as gender, age and body weight, using a questionnaire given to parents by a trained interviewer between January and March 2012. The second step was determining the acrylamide levels in food samples that were reported on by the parents in the questionnaire, using a gas chromatography-mass spectrometry (GC-MS) method. The last step was combining the determined acrylamide levels in selected food samples with individual food consumption and body weight data using a deterministic approach to estimate the acrylamide exposure levels. The mean acrylamide levels of baby biscuits, breads, baby bread-rusks, crackers, biscuits, breakfast cereals and powdered cereal-based baby foods were 153, 225, 121, 604, 495, 290 and 36 μg/kg, respectively. The minimum, mean and maximum acrylamide exposures were estimated to be 0.06, 1.43 and 6.41 μg/kg BW per day, respectively. The foods that contributed to acrylamide exposure were aligned from high to low as bread, crackers, biscuits, baby biscuits, powdered cereal-based baby foods, baby bread-rusks and breakfast cereals. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Proposal for IoT Dynamic Routes Selection Based on Contextual Information.

Science.gov (United States)

Araújo, Harilton da Silva; Filho, Raimir Holanda; Rodrigues, Joel J P C; Rabelo, Ricardo de A L; Sousa, Natanael de C; Filho, José C C L S; Sobral, José V V

2018-01-26

The Internet of Things (IoT) is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information). This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs) are proposed for the Routing Protocol for Low Power and Loss Networks (RPL); such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX), Number of Hops (NH) and Energy Consumed (EC). The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration.

A Proposal for IoT Dynamic Routes Selection Based on Contextual Information

Directory of Open Access Journals (Sweden)

Harilton da Silva Araújo

2018-01-01

Full Text Available The Internet of Things (IoT is based on interconnection of intelligent and addressable devices, allowing their autonomy and proactive behavior with Internet connectivity. Data dissemination in IoT usually depends on the application and requires context-aware routing protocols that must include auto-configuration features (which adapt the behavior of the network at runtime, based on context information. This paper proposes an approach for IoT route selection using fuzzy logic in order to attain the requirements of specific applications. In this case, fuzzy logic is used to translate in math terms the imprecise information expressed by a set of linguistic rules. For this purpose, four Objective Functions (OFs are proposed for the Routing Protocol for Low Power and Loss Networks (RPL; such OFs are dynamically selected based on context information. The aforementioned OFs are generated from the fusion of the following metrics: Expected Transmission Count (ETX, Number of Hops (NH and Energy Consumed (EC. The experiments performed through simulation, associated with the statistical data analysis, conclude that this proposal provides high reliability by successfully delivering nearly 100% of data packets, low delay for data delivery and increase in QoS. In addition, an 30% improvement is attained in the network life time when using one of proposed objective function, keeping the devices alive for longer duration.

Wavelength selection for portable noninvasive blood component measurement system based on spectral difference coefficient and dynamic spectrum

Science.gov (United States)

Feng, Ximeng; Li, Gang; Yu, Haixia; Wang, Shaohui; Yi, Xiaoqing; Lin, Ling

2018-03-01

Noninvasive blood component analysis by spectroscopy has been a hotspot in biomedical engineering in recent years. Dynamic spectrum provides an excellent idea for noninvasive blood component measurement, but studies have been limited to the application of broadband light sources and high-resolution spectroscopy instruments. In order to remove redundant information, a more effective wavelength selection method has been presented in this paper. In contrast to many common wavelength selection methods, this method is based on sensing mechanism which has a clear mechanism and can effectively avoid the noise from acquisition system. The spectral difference coefficient was theoretically proved to have a guiding significance for wavelength selection. After theoretical analysis, the multi-band spectral difference coefficient-wavelength selection method combining with the dynamic spectrum was proposed. An experimental analysis based on clinical trial data from 200 volunteers has been conducted to illustrate the effectiveness of this method. The extreme learning machine was used to develop the calibration models between the dynamic spectrum data and hemoglobin concentration. The experiment result shows that the prediction precision of hemoglobin concentration using multi-band spectral difference coefficient-wavelength selection method is higher compared with other methods.

Ship Classification with High Resolution TerraSAR-X Imagery Based on Analytic Hierarchy Process

Directory of Open Access Journals (Sweden)

Zhi Zhao

2013-01-01

Full Text Available Ship surveillance using space-borne synthetic aperture radar (SAR, taking advantages of high resolution over wide swaths and all-weather working capability, has attracted worldwide attention. Recent activity in this field has concentrated mainly on the study of ship detection, but the classification is largely still open. In this paper, we propose a novel ship classification scheme based on analytic hierarchy process (AHP in order to achieve better performance. The main idea is to apply AHP on both feature selection and classification decision. On one hand, the AHP based feature selection constructs a selection decision problem based on several feature evaluation measures (e.g., discriminability, stability, and information measure and provides objective criteria to make comprehensive decisions for their combinations quantitatively. On the other hand, we take the selected feature sets as the input of KNN classifiers and fuse the multiple classification results based on AHP, in which the feature sets’ confidence is taken into account when the AHP based classification decision is made. We analyze the proposed classification scheme and demonstrate its results on a ship dataset that comes from TerraSAR-X SAR images.

Materials selection for cutting tools

International Nuclear Information System (INIS)

Burkhis, Adel M.

2008-01-01

The selection of proper tool steel for a given application is a difficult task. So; the most important selection factors in choosing cutting tool materials are based on their tool material requirements, cutting tool design and service conditions which is mainly considered as functional requirements. The processability requirements concerns in heat treat ability of the material tool. The classification of these tool materials were discussed with their properties requirement and percent of alloying element which is added to give best properties with a little increase in cost that highly appear in comparison of the selection. The cutting tool materials were evaluated based on two cases; The first was in case of rough surface; the high speed steels is the best material and the other was the ceramic material is the highest performance in cutting of soft or high rate of metal removal. (author)

An automatic optimum number of well-distributed ground control lines selection procedure based on genetic algorithm

Science.gov (United States)

Yavari, Somayeh; Valadan Zoej, Mohammad Javad; Salehi, Bahram

2018-05-01

The procedure of selecting an optimum number and best distribution of ground control information is important in order to reach accurate and robust registration results. This paper proposes a new general procedure based on Genetic Algorithm (GA) which is applicable for all kinds of features (point, line, and areal features). However, linear features due to their unique characteristics are of interest in this investigation. This method is called Optimum number of Well-Distributed ground control Information Selection (OWDIS) procedure. Using this method, a population of binary chromosomes is randomly initialized. The ones indicate the presence of a pair of conjugate lines as a GCL and zeros specify the absence. The chromosome length is considered equal to the number of all conjugate lines. For each chromosome, the unknown parameters of a proper mathematical model can be calculated using the selected GCLs (ones in each chromosome). Then, a limited number of Check Points (CPs) are used to evaluate the Root Mean Square Error (RMSE) of each chromosome as its fitness value. The procedure continues until reaching a stopping criterion. The number and position of ones in the best chromosome indicate the selected GCLs among all conjugate lines. To evaluate the proposed method, a GeoEye and an Ikonos Images are used over different areas of Iran. Comparing the obtained results by the proposed method in a traditional RFM with conventional methods that use all conjugate lines as GCLs shows five times the accuracy improvement (pixel level accuracy) as well as the strength of the proposed method. To prevent an over-parametrization error in a traditional RFM due to the selection of a high number of improper correlated terms, an optimized line-based RFM is also proposed. The results show the superiority of the combination of the proposed OWDIS method with an optimized line-based RFM in terms of increasing the accuracy to better than 0.7 pixel, reliability, and reducing systematic

On dark matter selected high-scale supersymmetry

Energy Technology Data Exchange (ETDEWEB)

Zheng, Sibo [Department of Physics, Chongqing University,Chongqing 401331 (China)

2015-03-11

The prediction for the Higgs mass in the dark matter selected high-scale SUSY is explored. We show the bounds on SUSY-breaking scale in models of SM +w-tilde and SM +h-tilde/s-tilde due to the observed Higgs mass at the LHC. We propose that effective theory below scale m-tilde described by SM +w-tilde is possibly realized in gauge mediation with multiple spurion fields that exhibit significant mass hierarchy, and that by SM +h-tilde/s-tilde can be realized with direct singlet-messenger-messenger coupling for singlet Yukawa coupling λ∼(v/m-tilde){sup 1/2}g{sub SM}. Finally, the constraint on high-scale SUSY is investigated in the light of inflation physics if these two subjects are directly related.

Molecularly imprinted polymer decorated nanoporous gold for highly selective and sensitive electrochemical sensors

Science.gov (United States)

Li, Yingchun; Liu, Yuan; Liu, Jie; Liu, Jiang; Tang, Hui; Cao, Cong; Zhao, Dongsheng; Ding, Yi

2015-01-01

Electrochemical nanosensors based on nanoporous gold leaf (NPGL) and molecularly imprinted polymer (MIP) are developed for pharmaceutical analysis by using metronidazole (MNZ) as a model analyte. NPGL, serving as the loading platform for MIP immobilization, possesses large accessible surface area with superb electric conductivity, while electrochemically synthesized MIP thin layer affords selectivity for specific recognition of MNZ molecules. For MNZ determination, the hybrid electrode shows two dynamic linear range of 5 × 10-11 to 1 × 10-9 mol L-1 and 1 × 10-9 to 1.4 × 10-6 mol L-1 with a remarkably low detection limit of 1.8 × 10-11 mol L-1 (S/N = 3). In addition, the sensor exhibits high binding affinity and selectivity towards MNZ with excellent reproducibility and stability. Finally, the reliability of MIP-NPGL for MNZ detection is proved in real fish tissue samples, demonstrating the potential for the proposed electrochemical sensors in monitoring drug and biological samples.

A highly sensitive, single selective, fluorescent sensor for Al3+ detection and its application in living cell imaging

International Nuclear Information System (INIS)

Ye, Xing-Pei; Sun, Shao-bo; Li, Ying-dong; Zhi, Li-hua; Wu, Wei-na; Wang, Yuan

2014-01-01

A new o-aminophenol-based fluorogenic chemosensor methyl 3,5-bis((E)-(2-hydroxyphenylimino)methyl)-4-hydroxybenzoate 1 have been synthesized by Schiff base condensation of methyl 3,5-diformyl-4-hydroxybenzoate with o-aminophenol, which exhibits high selectivity and sensitivity toward Al 3+ . Fluorescence titration studies of receptors 1 with different metal cations in CH 3 OH medium showed highly selective and sensitive towards Al 3+ ions even in the presence of other commonly coexisting metal ions. The detection limit of Al 3+ ions is at the parts per billion level. Interestingly, the Al(III) complex of 1 offered a large Stokes shift (>120 nm), which can miximize the selfquenching effect. In addition, possible utilization of this receptor as bio-imaging fluorescent probe to detect Al 3+ in human cervical HeLa cancer cell lines was also investigated by confocal fluorescence microscopy. - Highlights: • A new Schiff base chemosensor is reported. • The sensor for Al 3+ offers large Stokes shift. • The detection limit of Al 3+ in CH 3 OH solution is at the parts per billion level. • The utilization of sensor for the monitoring of Al 3+ levels in living cells was examined

SVM Based Descriptor Selection and Classification of Neurodegenerative Disease Drugs for Pharmacological Modeling.

Science.gov (United States)

Shahid, Mohammad; Shahzad Cheema, Muhammad; Klenner, Alexander; Younesi, Erfan; Hofmann-Apitius, Martin

2013-03-01

Systems pharmacological modeling of drug mode of action for the next generation of multitarget drugs may open new routes for drug design and discovery. Computational methods are widely used in this context amongst which support vector machines (SVM) have proven successful in addressing the challenge of classifying drugs with similar features. We have applied a variety of such SVM-based approaches, namely SVM-based recursive feature elimination (SVM-RFE). We use the approach to predict the pharmacological properties of drugs widely used against complex neurodegenerative disorders (NDD) and to build an in-silico computational model for the binary classification of NDD drugs from other drugs. Application of an SVM-RFE model to a set of drugs successfully classified NDD drugs from non-NDD drugs and resulted in overall accuracy of ∼80 % with 10 fold cross validation using 40 top ranked molecular descriptors selected out of total 314 descriptors. Moreover, SVM-RFE method outperformed linear discriminant analysis (LDA) based feature selection and classification. The model reduced the multidimensional descriptors space of drugs dramatically and predicted NDD drugs with high accuracy, while avoiding over fitting. Based on these results, NDD-specific focused libraries of drug-like compounds can be designed and existing NDD-specific drugs can be characterized by a well-characterized set of molecular descriptors. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An Unbiased Distance-based Outlier Detection Approach for High-dimensional Data

DEFF Research Database (Denmark)

Nguyen, Hoang Vu; Gopalkrishnan, Vivekanand; Assent, Ira

2011-01-01

than a global property. Different from existing approaches, it is not grid-based and dimensionality unbiased. Thus, its performance is impervious to grid resolution as well as the curse of dimensionality. In addition, our approach ranks the outliers, allowing users to select the number of desired...... outliers, thus mitigating the issue of high false alarm rate. Extensive empirical studies on real datasets show that our approach efficiently and effectively detects outliers, even in high-dimensional spaces....