WorldWideScience

Sample records for previously unreported deep

  1. Mediastinal involvement in lymphangiomatosis: a previously unreported MRI sign

    Energy Technology Data Exchange (ETDEWEB)

    Shah, Vikas; Shah, Sachit; Barnacle, Alex; McHugh, Kieran [Great Ormond Street Hospital for Children, Department of Radiology, London (United Kingdom); Sebire, Neil J. [Great Ormond Street Hospital for Children, Department of Histopathology, London (United Kingdom); Brock, Penelope [Great Ormond Street Hospital for Children, Department of Oncology, London (United Kingdom); Harper, John I. [Great Ormond Street Hospital for Children, Department of Dermatology, London (United Kingdom)

    2011-08-15

    Multifocal lymphangiomatosis is a rare systemic disorder affecting children. Due to its rarity and wide spectrum of clinical, histological and imaging features, establishing the diagnosis of multifocal lymphangiomatosis can be challenging. The purpose of this study was to describe a new imaging sign in this disorder: paraspinal soft tissue and signal abnormality at MRI. We retrospectively reviewed the imaging, clinical and histopathological findings in a cohort of eight children with thoracic involvement from this condition. Evidence of paraspinal chest disease was identified at MRI and CT in all eight of these children. The changes comprise heterogeneous intermediate-to-high signal parallel to the thoracic vertebrae on T2-weighted sequences at MRI, with abnormal paraspinal soft tissue at CT and plain radiography. Multifocal lymphangiomatosis is a rare disorder with a broad range of clinicopathological and imaging features. MRI allows complete evaluation of disease extent without the use of ionising radiation and has allowed us to describe a previously unreported imaging sign in this disorder, namely, heterogeneous hyperintense signal in abnormal paraspinal tissue on T2-weighted images. (orig.)

  2. Previously unreported abnormalities in Wolfram Syndrome Type 2.

    Science.gov (United States)

    Akturk, Halis Kaan; Yasa, Seda

    2017-01-01

    Wolfram syndrome (WFS) is a rare autosomal recessive disease with non-autoimmune childhood onset insulin dependent diabetes and optic atrophy. WFS type 2 (WFS2) differs from WFS type 1 (WFS1) with upper intestinal ulcers, bleeding tendency and the lack ofdiabetes insipidus. Li-fespan is short due to related comorbidities. Only a few familieshave been reported with this syndrome with the CISD2 mutation. Here we report two siblings with a clinical diagnosis of WFS2, previously misdiagnosed with type 1 diabetes mellitus and diabetic retinopathy-related blindness. We report possible additional clinical and laboratory findings that have not been pre-viously reported, such as asymptomatic hypoparathyroidism, osteomalacia, growth hormone (GH) deficiency and hepatomegaly. Even though not a requirement for the diagnosis of WFS2 currently, our case series confirm hypogonadotropic hypogonadism to be also a feature of this syndrome, as reported before. © Polish Society for Pediatric Endocrinology and Diabetology.

  3. Wolff-Parkinson-White syndrome with cleft lip and palate: A rare, previously unreported association

    Directory of Open Access Journals (Sweden)

    K Kannan

    2008-01-01

    Full Text Available Wolff-Parkinson-White syndrome, also called Pre Excitation Syndrome, is characterized by an extra pathway that conducts the electrical impulses from the atria to the ventricles without the normal delay. We are reporting a case of WPW syndrome with a cleft lip and palate, which is a rare association and previously unreported in literature.

  4. Congenital costo-vertebral fibrous band and congenital kyphoscoliosis: a previously unreported combination.

    Science.gov (United States)

    Eid, Tony; Ghostine, Bachir; Kreichaty, Gaby; Daher, Paul; Ghanem, Ismat

    2013-05-01

    Congenital kyphoscoliosis (CKS) results from abnormal vertebral chondrification. Congenital fibrous bands occur in several locations with variable impact on vertebral development. We report a previously unreported case of a female infant with CKS presenting with an L2 hypoplastic vertebra and a costo-vertebral fibrous band extending to the skin in the form of a dimple. We also describe the therapeutic approach, consisting of surgical excision of the fibrous band and postoperative fulltime bracing, with a 7-year follow-up. We recommend a high index of suspicion in any unusual presentation of CKS and insist on case by case management in such cases.

  5. Poly-epiphyseal overgrowth: description of a previously unreported skeletal dysplasia

    Energy Technology Data Exchange (ETDEWEB)

    Pazzaglia, Ugo E.; Bonaspetti, Giovanni [University of Brescia, Orthopaedic Clinic, Brescia (Italy); Beluffi, Giampiero [Fondazione IRCCS Policlinico San Matteo, Department of Paediatric Radiology, Pavia (Italy); Marchi, Antonietta; Bozzola, Mauro; Savasta, Salvatore [Fondazione IRCCS Policlinico San Matteo, Paediatric Clinic, University of Pavia, Pavia (Italy)

    2007-10-15

    A skeletal dysplasia with previously unreported features is presented. Its evolution was characterized by growth abnormalities of bones without involvement of other organs. Advanced bone age, increased stature and irregular epiphyseal ossification with stippling of the main long bones were documented. Physeal overgrowth was massive in the left proximal humerus and femur. Furthermore, the hip joint appeared fused with an abundant mass of pathological calcific tissue extending from the femur to the ilium. Pathological epiphyses were characterized by anarchic cartilaginous proliferation with multiple ossification centres, while lamellar bone apposition and remodelling were normal. The observed bone changes were different from those in any previously reported syndrome, metabolic defect or bone dysplasia. However, they clearly indicated a defect of endochondral ossification with some resemblance to phenotypes observed in dysplasia epiphysealis hemimelica. (orig.)

  6. Poly-epiphyseal overgrowth: description of a previously unreported skeletal dysplasia

    International Nuclear Information System (INIS)

    Pazzaglia, Ugo E.; Bonaspetti, Giovanni; Beluffi, Giampiero; Marchi, Antonietta; Bozzola, Mauro; Savasta, Salvatore

    2007-01-01

    A skeletal dysplasia with previously unreported features is presented. Its evolution was characterized by growth abnormalities of bones without involvement of other organs. Advanced bone age, increased stature and irregular epiphyseal ossification with stippling of the main long bones were documented. Physeal overgrowth was massive in the left proximal humerus and femur. Furthermore, the hip joint appeared fused with an abundant mass of pathological calcific tissue extending from the femur to the ilium. Pathological epiphyses were characterized by anarchic cartilaginous proliferation with multiple ossification centres, while lamellar bone apposition and remodelling were normal. The observed bone changes were different from those in any previously reported syndrome, metabolic defect or bone dysplasia. However, they clearly indicated a defect of endochondral ossification with some resemblance to phenotypes observed in dysplasia epiphysealis hemimelica. (orig.)

  7. Echinocandin Failure Case Due to a Previously Unreported FKS1 Mutation in Candida krusei

    DEFF Research Database (Denmark)

    Jensen, Rasmus Hare; Justesen, Ulrik Stenz; Rewes, Annika

    2014-01-01

    Echinocandins are the preferred therapy for invasive infections due to Candida krusei. We present here a case of clinical failure involving C. krusei with a characteristic FKS1 hot spot mutation not previously reported in C. krusei that was isolated after 14 days of treatment. Anidulafungin MICs...... were elevated by ≥5 dilution steps above the clinical breakpoint but by only 1 step for a Candida albicans isolate harboring the corresponding mutation, suggesting a notable species-specific difference in the MIC increase conferred by this mutation....

  8. A previously unreported association between Nance-Horan syndrome and spontaneous dental abscesses.

    Science.gov (United States)

    Hibbert, Sally

    2005-02-01

    Atypical dentofacial structures may be the first indicator of other anomalies linked to a syndrome. This case describes the management of a 9-year-old girl referred for the routine management of supernumerary teeth. The anomalous form of her teeth, together with multiple supernumerary units and a history of congenital cataracts, were suggestive of a diagnosis of Nance-Horan syndrome. This is an X-linked disorder, in which females usually demonstrate mild expression; this case was unusual in respect to the marked phenotype expressed. Unusually, the girl developed 2 spontaneous abscesses of her noncarious upper incisor teeth; a feature never previously described in this syndrome. This report details the patient's dental management and discusses the possible pathogenesis of the dental abscesses, together with the genetic implications of this syndrome.

  9. PHACES syndrome: a review of eight previously unreported cases with late arterial occlusions

    International Nuclear Information System (INIS)

    Bhattacharya, J.J.; Luo, C.B.; Alvarez, H.; Rodesch, G.; Lasjaunias, P.L.; Pongpech, S.

    2004-01-01

    PHACE and PHACES are acronyms for a syndrome of variable expression comprising posterior cranial fossa malformations, facial haemangiomas, arterial anomalies, aortic coarctation and other cardiac disorders, ocular abnormalities and stenotic arterial disease. We review five girls and three boys aged 1 month-14 years with disorders from this spectrum. Six had large facial haemangiomas but recent reports suggest that small haemangiomas may occur; hence our inclusion of two possible cases. We also focus on the recently recognised feature of progressive intracranial arterial occlusions, present in four of our patients, later than previously recognised, from 4 to 14 years of age. We suggest that many elements of this disorder could reflect an abnormality of cell proliferation and apoptosis. (orig.)

  10. A previously unreported variant of the synostotic sagittal suture: Case report and review of salient literature

    Directory of Open Access Journals (Sweden)

    Madison Budinich

    2016-12-01

    Full Text Available Introduction: Sagittal synostosis is a rare congenital disease caused by the premature fusion of the sagittal suture. Craniosynostosis occurs for a variety of reasons, different for every case, and often the etiology is unclear but the anomaly can frequently be seen as part of Crouzon's or Apert's syndromes. Herein, we discuss a rare case of craniosynostosis where the patient presented with a, to our knowledge, a previously undescribed variant of sagittal synostosis. Case report: A 3-month-old female infant presented to a craniofacial clinic for a consultation regarding an abnormal head shape. Images of the skull were performed, demonstrating that the patient had craniosynostosis. The patient displayed no other significant symptoms besides abnormalities in head shape. The sagittal suture was found to extend into the occipital bone where it was synostotic. Conclusion: To our knowledge, a synostotic sagittal suture has not been reported that extended posteriorly it involve the occipital bone. Those who interpret imaging or operate on this part of the skull should consider such a variation. Keywords: Anatomy, Craniosynostosis, Skull, Malformation, Pediatrics

  11. Deep vein thrombosis, an unreported first manifestation of polyglandular autoimmune syndrome type III

    Directory of Open Access Journals (Sweden)

    M Horsey

    2016-07-01

    Full Text Available A 71-year-old woman with severe right lower leg pain, edema and erythema was presented to the Emergency Department and was found to have an extensive deep vein thrombosis (DVT confirmed by ultrasound. She underwent an extensive evaluation due to her prior history of malignancy and new hypercoagulable state, but no evidence of recurrent disease was detected. Further investigation revealed pernicious anemia (PA, confirmed by the presence of a macrocytic anemia (MCV=115.8fL/red cell, Hgb=9.0g/dL, decreased serum B12 levels (56pg/mL, with resultant increased methylmalonic acid (5303nmol/L and hyperhomocysteinemia (131μmol/L, the presumed etiology of the DVT. The patient also suffered from autoimmune thyroid disease (AITD, and both antithyroglobulin and anti-intrinsic factor antibodies were detected. She responded briskly to anticoagulation with heparin and coumadin and treatment of PA with intramuscular vitamin B12 injections. Our case suggests that a DVT secondary to hyperhomocystenemia may represent the first sign of polyglandular autoimmune syndrome III-B (PAS III-B, defined as the coexistent autoimmune conditions AITD and PA. It is important to recognize this clinical entity, as patients may not only require acute treatment with vitamin B12 supplementation and prolonged anticoagulation, as in this patient, but may also harbor other autoimmune diseases.

  12. Previously unreported intense absorption band and the pK/sub A/ of protonated triplet methylene blue

    Energy Technology Data Exchange (ETDEWEB)

    Ohno, T.; Osif, T.L.; Lichtin, N.N.

    1979-01-01

    Excitation by a Q-switched giant ruby laser (1.2 joule output at 694 nm, approx. 50 nsec flash) of 2-10 ..mu..M solutions of methylene blue in water, 30% ethanol in water or 50 v/v% water - CH/sub 3/CN at pH values in the range 2.0 - 9.3 converted the dye essentially completely to its T/sub 1/ state. The absorption spectrum of T/sub 1/ dye was measured in different media at pH 2.0 and 8.2 by kinetic spectrophotometry. Previously reported T-T absorption in the violet in acidic and alkaline solutions and in the near infrared in alkaline solution was confirmed. Values found for these absorptions in the present work with 30% ethanol in water as solvent are lambda/sub max/ approx. 370 nm, epsilon/sub max/ approx. 13,200 M/sup -1/ cm/sup -1/ at pH 2 and lambda/sub max/ approx. 420 nm, epsilon/sub max/ approx. 9,000 M/sup -1/ cm/sup -1/, lambda/sub max/ approx. 840 nm, epsilon/sub max/ approx. 20,000 M/sup -1/ cm/sup -1/ at pH 8.2. Long-wavelength T-T absorption in acidic solution is reported here for the first time: lambda/sub max/ approx. 680 nm, epsilon/sub max/ approx. 19,000 M/sup -1/ cm/sup -1/ in 30% ethanol in water at pH 2. Observation of a pH-independent isobestic point approx. 720 nm confirms that the long-wavelength absorptions are due to different protonated states of the same species, MB/sup +/(T/sub 1/) and MBH/sup 2 +/(T/sub 1/). The pK/sub A/ of MBH/sup 2 +/(T/sub 1/) in water was determined from the dependence on pH of absorption at 700 and 825 nm to be 7.1/sub 4/ +- .1 and from the kinetics of decay of triplet absorption to be 7.2. The specific rate of protonation of MB/sup +/(T/sub 1/) by H/sub 2/PO/sub 4//sup -/ in water at pH 4.4 was found to be 4.5 +- .4 x 10/sup 8/ M/sup -1/ sec/sup -1/.

  13. Early severe scoliosis in a patient with atypical progressive pseudorheumatoid dysplasia (PPD): Identification of two WISP3 mutations, one previously unreported.

    Science.gov (United States)

    Montané, Lucia Sentchordi; Marín, Oliver R; Rivera-Pedroza, Carlos I; Vallespín, Elena; Del Pozo, Ángela; Heath, Karen E

    2016-06-01

    Progressive pseudorheumatoid dysplasia (PPD) is a rare autosomal recessive disorder characterized by spondyloepiphyseal dysplasia associated with pain and stiffness of multiple joints, enlargement of the interphalangeal joints, normal inflammatory parameters, and absence of extra-skeletal manifestations. Homozygous or compound heterozygous WISP3 mutations cause PPD. We report two siblings from a non-consanguineous Ecuadorian family with a late-onset spondyloepiphyseal dysplasia. Mutation screening was undertaken in the two affected siblings using a customized skeletal dysplasia next generation sequencing (NGS) panel and confirmed by Sanger sequencing. Two compound heterozygous mutations were identified in WISP3 exon 2, c.[190G>A];[197G>A] (p.[(Gly64Arg)];[(Ser66Asn)]) in the two siblings, both of which had been inherited. The p. (Gly64Arg) mutation has not been previously described whilst the p. (Ser66Asn) mutation has been reported in two PPD families. The two siblings presented with atypical PPD, as they presented during late childhood, yet the severity was different between them. The progression was particularly aggressive in the male sibling who suffered severe scoliosis by the age of 13 years. This case reaffirms the clinical heterogeneity of this disorder and the clinical utility of NGS to genetically diagnose skeletal dysplasias, enabling adequate management, monitorization, and genetic counseling. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

  14. Response to deep TMS in depressive patients with previous electroconvulsive treatment.

    Science.gov (United States)

    Rosenberg, Oded; Zangen, Abraham; Stryjer, Rafael; Kotler, Moshe; Dannon, Pinhas N

    2010-10-01

    The efficacy of transcranial magnetic stimulation (TMS) in the treatment of major depression has already been shown. Novel TMS coils allowing stimulation of deeper brain regions have recently been developed and studied. Our study is aimed at exploring the possible efficacy of deep TMS in patients with resistant depression, who previously underwent electroconvalsive therapy (ECT). Using Brainsway's deep TMS H1 coil, six patients who previously underwent ECT, were treated with 120% power of the motor threshold at a frequency of 20 Hz. Patients underwent five sessions per week, up to 4 weeks. Before the study, patients were evaluated using the Hamilton depression rating scale (HDRS, 24 items), the Hamilton anxiety scale, and the Beck depression inventory and were again evaluated after 5, 10, 15, and 20 daily treatments. Response to treatment was considered a reduction in the HDRS of at least 50%, and remission was considered a reduction of the HDRS-24 below 10 points. Two of six patients responded to the treatment with deep TMS, including one who achieved full remission. Our results suggest the possibility of a subpopulation of depressed patients who may benefit from deep TMS treatment, including patients who did not respond to ECT previously. However, the power of the study is small and similar larger samples are needed. Copyright © 2010 Elsevier Inc. All rights reserved.

  15. Central diabetes insipidus: a previously unreported side effect of temozolomide.

    Science.gov (United States)

    Faje, Alexander T; Nachtigall, Lisa; Wexler, Deborah; Miller, Karen K; Klibanski, Anne; Makimura, Hideo

    2013-10-01

    Temozolomide (TMZ) is an alkylating agent primarily used to treat tumors of the central nervous system. We describe 2 patients with apparent TMZ-induced central diabetes insipidus. Using our institution's Research Patient Database Registry, we identified 3 additional potential cases of TMZ-induced diabetes insipidus among a group of 1545 patients treated with TMZ. A 53-year-old male with an oligoastrocytoma and a 38-year-old male with an oligodendroglioma each developed symptoms of polydipsia and polyuria approximately 2 months after the initiation of TMZ. Laboratory analyses demonstrated hypernatremia and urinary concentrating defects, consistent with the presence of diabetes insipidus, and the patients were successfully treated with desmopressin acetate. Desmopressin acetate was withdrawn after the discontinuation of TMZ, and diabetes insipidus did not recur. Magnetic resonance imaging of the pituitary and hypothalamus was unremarkable apart from the absence of a posterior pituitary bright spot in both of the cases. Anterior pituitary function tests were normal in both cases. Using the Research Patient Database Registry database, we identified the 2 index cases and 3 additional potential cases of diabetes insipidus for an estimated prevalence of 0.3% (5 cases of diabetes insipidus per 1545 patients prescribed TMZ). Central diabetes insipidus is a rare but reversible side effect of treatment with TMZ.

  16. Unreported workplace violence in nursing.

    Science.gov (United States)

    Kvas, A; Seljak, J

    2014-09-01

    Workplace violence occurs on a frequent basis in nursing. Most violent acts remain unreported. Consequently, we do not know the actual frequency of the occurrence of workplace violence. This requires research of nurses' actions following workplace violence and identification of reasons why most victims do not report violent acts in the appropriate manner. To explore violence in nursing as experienced by nurses in Slovenia. A survey was carried out with a representative sample of nurses in Slovenia. The questionnaire Workplace Violence in Nursing was submitted to 3756 nurses, with 692 completing the questionnaire. A total of 61.6% of the nurses surveyed had been exposed to violence in the past year. Most victims were exposed to psychological (60.1%) and economic violence (28.9%). Victims reported acts of violence in formal written form in a range from 6.5% (psychological violence) to 10.9% (physical violence). The largest share of victims who did not report violence and did not speak to anyone about it were victims of sexual violence (17.9%). The main reason for not reporting the violence was the belief that reporting it would not change anything, followed by the fear of losing one's job. Only a small share of the respondents reported violence in written form, the main reason being the victims' belief that reporting it would not change anything. This represents a severe criticism of the system for preventing workplace violence for it reveals the failure of response by leadership structures in healthcare organizations. Professional associations and the education system must prepare nurses for the prevention of violence and appropriate actions in the event of violent acts. Healthcare organizations must ensure the necessary conditions for enabling and encouraging appropriate actions following violent acts according to relevant protocols. © 2014 International Council of Nurses.

  17. Normal endothelial function after meals rich in olive or safflower oil previously used for deep frying.

    Science.gov (United States)

    Williams, M J; Sutherland, W H; McCormick, M P; Yeoman, D; de Jong, S A; Walker, R J

    2001-06-01

    Polyunsaturated fats are more susceptible to oxidation during heating than monounsaturated fats but their effects on endothelial function when heated are unknown. The aim of this study was to compare the effect of meals rich in heat-modified safflower and olive oils on postprandial flow-mediated endothelium-dependent dilation (EDD) in healthy men. Flow-mediated EDD and glyceryltrinitrate-induced endothelium-independent dilation of the brachial artery were investigated in 14 subjects before and 4 hours after meals rich in olive oil and safflower oil used hourly for deep-frying for 8 hours in a double-blind crossover study design. There were high levels of lipid oxidation products (peroxides and carbonyls) in both heated oils. Plasma triglycerides were markedly increased at 4 hours after heated olive oil (1.26 +/- 0.43 vs 2.06 +/- 0.97 mmol/L) and heated safflower oil (1.44 +/- 0.63 vs 1.99 +/- 0.88 mmol/L). There was no change in EDD between fasting and postprandial studies and the response during the postprandial period was not significantly (p = 0.51) different between the meals (heated olive oil: 4.9 +/- 2.2% vs 4.9 +/- 2.5%; heated safflower oil: 5.1 +/- 3.1% vs 5.6 +/- 3.4%). Meals rich in olive and safflower oils previously used for deep frying and containing high levels of lipid oxidation products increase postprandial serum triglycerides without affecting endothelial function. These findings suggest that relatively short-term use of these vegetable oils for frying may not adversely affect postprandial endothelial function when foods containing the heat-modified oils are consumed.

  18. Deep brain stimulation of the subthalamic nucleus: effectiveness in advanced Parkinson's disease patients previously reliant on apomorphine

    OpenAIRE

    Varma, T; Fox, S; Eldridge, P; Littlechild, P; Byrne, P; Forster, A; Marshall, A; Cameron, H; McIver, K; Fletcher, N; Steiger, M

    2003-01-01

    Objectives: To assess the efficacy of bilateral subthalamic nucleus (STN) deep brain stimulation (DBS) in patients with advanced Parkinson's disease previously reliant on apomorphine as their main antiparkinsonian medication.

  19. Prevalence of pre-diabetes and unreported diabetes mellitus in ...

    African Journals Online (AJOL)

    Background: Unreported diabetes mellitus and glucose intolerance have substantial clinical importance. Glucose intolerance precedes diabetes mellitus and it is associated with cardiovascular complications. Subjects with prediabetes have near normal glycated haemoglobin and may only be detected when oral glucose ...

  20. Concurrent Multilocular Cystic Renal Cell Carcinoma and Leiomyoma in the Same Kidney: Previously Unreported Association

    Directory of Open Access Journals (Sweden)

    Min Su Cheong

    2010-07-01

    Full Text Available We present an unusual case of concurrent occurrence of a multilocular cystic renal cell carcinoma and a leiomyoma in the same kidney of a patient with no evident clinical symptoms. A 38-year-old man was found incidentally to have a cystic right renal mass on computed tomography. Laparoscopic radical nephrectomy was performed under a preoperative diagnosis of cystic renal cell carcinoma. Histology revealed a multilocular cystic renal cell carcinoma and a leiomyoma. This is the first report of this kind of presentation.

  1. Oral Bilateral Collagenous Fibroma: A previously unreported case and literature review.

    Science.gov (United States)

    Vasconcelos, Ana-Carolina; Gomes, Ana-Paula; Tarquinio, Sandra; Abduch-Rodrigues, Eduardo; Mesquita, Ricardo; Silva, Karine

    2018-01-01

    Collagenous fibroma, also known as desmoplastic fibroblastoma, is a rare benign slow growing tumor particularly uncommon in the oral cavity. The aim of this study was to analyze the clinical and histopathological features of an oral collagenous fibroma as well as to compare this data with those reported in an English-literature review. The thirteenth case of collagenous fibroma in the oral cavity and the first to present clinically as a bilateral mass was described. A 48-years-old female patient was referred to a School of Dentistry, complaining about an asymptomatic swelling on the hard palate, lasting around ten years. The intraoral examination revealed two well-defined mass, bilaterally in the hard palate. An excisional biopsy was performed. Microscopically, the connective tissue consisted of dense collagen bundles in which were seen scarcely distributed spindle-shaped to stellate fibroblastic cells. Blood vessels were few, as well as inflammatory cells. Immunohistochemical staining was positive for vimentin, α-smooth muscle actin and factor XIIIa and negative for S-100, CD68, CD34, HHF35, desmin and AE1/AE3. The patient remains disease-free 24 months after excision. In conclusion, oral collagenous fibroma should be included in the differential diagnosis of bilateral sessile nodules in the oral cavity. Key words: Connective tissue, mouth diseases, mouth neoplasms, oral diagnosis, oral pathology.

  2. Pulmonary carcinosarcoma initially presenting as invasive aspergillosis: a case report of previously unreported combination

    Directory of Open Access Journals (Sweden)

    Van Thien

    2010-01-01

    Full Text Available Abstract Carcinosarcoma of the lung is a malignant tumor composed of a mixture of carcinoma and sarcoma elements. The carcinomatous component is most commonly squamous followed by adenocarcinoma. The sarcomatous component commonly comprises the bulk of the tumor and shows poorly differentiated spindle cell features. Foci of differentiated sarcomatous elements such as chondrosarcoma and osteosarcoma may be seen. Aspergillus pneumonia is the most common form of invasive aspergillosis and occurs mainly in patients with malignancy, immunocompromizing or debilitating diseases. Patients with Aspergillus pneumonia present with fever, cough, chest pain and occasionally hemoptysis. Tissue examination is the most reliable method for diagnosis, and mortality rate is high. We describe a case of primary carcinosarcoma of the lung concurrently occurring with invasive pulmonary aspergillosis in a 66-year old patient.

  3. Disseminated Kaposi sarcoma with epithelioid morphology in an HIV/AIDS patient: A previously unreported variant.

    Science.gov (United States)

    Basra, Pukhraz; Paramo, Juan; Alexis, John

    2018-04-16

    Kaposi sarcoma is an oligoclonal HHV-8-driven vascular proliferation that was first described by a Viennese dermatologist Dr Moritz Kaposi. The disease has been seen in different clinical-epidemiological settings with a wide morphologic spectrum. We report a 52-year-old Caucasian man with HIV/AIDS and Kaposi sarcoma who presented with dyspnea and pleural effusion. He reported numerous tender subcutaneous nodules developing over the past few months on his chest, back and abdomen. An excisional biopsy of one of the nodules was performed. Touch preps revealed malignant cells in clusters. Microscopically, the neoplasm appeared undifferentiated with an epithelioid morphology, and involved the dermis and subcutaneous fat. Despite the medical history, Kaposi sarcoma was not considered foremost in the differential diagnosis. The malignant cells were positive for vimentin and negative for S100 protein, keratin AE1/3, CK7, CK20, napsin A, TTF-1 and synaptophysin. Additional stains revealed positivity for HHV-8, CD31 and D2-40, supporting the diagnosis of Kaposi sarcoma. Kaposi sarcoma has been well described with many variants that may cause diagnostic difficulty. An epithelioid variant has not been reported and consequently, may cause misinterpretation of an otherwise well-known entity that may become life threatening if appropriate treatment is not initiated in a timely manner. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  4. New, previously unreported correlations between latent Toxoplasma gondii infection and excessive ethanol consumption.

    Science.gov (United States)

    Samojłowicz, Dorota; Borowska-Solonynko, Aleksandra; Kruczyk, Marcin

    2017-11-01

    A number of world literature reports indicate that a latent Toxoplasma gondii infection leads to development of central nervous system disorders, which in turn may lead to altered behavior in the affected individuals. T. gondii infection has been observed to play the greatest role in drivers, suicides, and psychiatric patients. Studies conducted for this manuscript involve a different, never before really reported correlation between latent T. gondii infection and ethanol abuse. A total of 538 decedents with a known cause of death were included in the study. These individuals were divided into three groups: the risky behavior group, inconclusively risky behavior group, and control group. The criterion for this division was the likely effect of the individual's behavior on the mechanism and cause of his/her death. The material used for analyses were blood samples collected during routine medico-legal examinations in these cases. The blood samples were used to measure anti-T. gondii IgG antibodies with an enzyme-linked immunosorbent assay (ELISA). Moreover, the following data were recorded for each decedent: sex, age, circumstances of death, cause of death, time from death to autopsy, and (if provided) substance abuse status (alcohol, illicit drugs). In those cases where blood alcohol level or toxicology tests were requested by the Prosecutor's Office, their results were also included in our analysis. Test results demonstrated a strong correlation between latent T. gondii infection and engaging in risky behaviors leading to death. Moreover, analyses demonstrated a positive correlation between the presence of anti-T. gondii IgG antibodies and psychoactive substance (especially ethanol) abuse, however, the causal relationship remains unclear. Due to the fact that alcohol abuse constitutes a significant social problem, searching for eliminable risk factors for addiction is extremely important. Our analyses provided new important information on the possible effects of latent T. gondii infection in humans. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Chronic pain in Noonan Syndrome: A previously unreported but common symptom.

    Science.gov (United States)

    Vegunta, Sravanthi; Cotugno, Richard; Williamson, Amber; Grebe, Theresa A

    2015-12-01

    Noonan syndrome (NS) is a multiple malformation syndrome characterized by pulmonic stenosis, cardiomyopathy, short stature, lymphatic dysplasia, craniofacial anomalies, cryptorchidism, clotting disorders, and learning disabilities. Eight genes in the RAS/MAPK signaling pathway are implicated in NS. Chronic pain is an uncommon feature. To investigate the prevalence of pain in NS, we distributed a two-part questionnaire about pain among NS individuals at the Third International Meeting on Genetic Syndromes of the Ras/MAPK Pathway. The first part of the questionnaire queried demographic information among all NS participants. The second part was completed by individuals with chronic pain. Questions included musculoskeletal problems and clinical features of pain. Forty-five questionnaires were analyzed; 53% of subjects were female. Mean age was 17 (2-48) years; 47% had a PTPN11 mutation. Sixty-two percent (28/45) of individuals with NS experienced chronic pain. There was a significant relationship between prevalence of pain and residing in a cold climate (P = 0.004). Pain occurred commonly in extremities/joints and head/trunk, but more commonly in extremities/joints (P = 0.066). Subjects with hypermobile joints were more likely to have pain (P = 0.052). Human growth hormone treatment was not statistically significant among subjects without chronic pain (P = 0.607). We conclude that pain is a frequent and under-recognized clinical feature of NS. Chronic pain may be associated with joint hypermobility and aggravated by colder climate. Our study is a preliminary investigation that should raise awareness about pain as a common symptom in children and adults with NS. © 2015 Wiley Periodicals, Inc.

  6. Unreported location and presentation for a parasitic ovarian dermoid cyst: A case report

    Directory of Open Access Journals (Sweden)

    Amr Hassan Wahba

    2010-07-01

    Full Text Available Dermoid cysts are one of the most common ovarian tumors especially in young patients; however, parasitic dermoid cysts are extremely rare with the most common site being the omentum. This case demonstrates a new site for parasitic dermoid cyst; on the reflection of uterovesical pouch onto the anterior abdominal wall which is known anatomically as the median umbilical fold, as well as previously unreported clinical presentation which is the perception of something moving inside the abdomen, that can be explained by the presence of the parasitic dermoid cyst close to the anterior abdominal wall in this case.

  7. Managerial improvement efforts after finding unreported cracks in reactor components

    International Nuclear Information System (INIS)

    Kawamura, S.

    2006-01-01

    In 2002 TEPCO found that there were unreported cracks in reactor components, of which inspection records had been falsified. Stress Corrosion Cracking indications found in Core Shrouds and Primary Loop Re-circulation pipes at some plants were removed from the inspection records and not reported to the regulators. Top management of TEPCO took the responsibility and resigned, and recovery was started under the leadership of new management team. First of all, behavioral standards were reconstituted to strongly support safety-first value. Ethics education was introduced and corporate ethics committee was organized with participation of external experts. Independent assessment organization was established to enhance quality assurance. Information became more transparent through Non-conformance Control Program. As for the material management, prevention and mitigation programs for the Stress Corrosion Cracking of reactor components were re-established. In addition to the above immediate recovery actions, long term improvement initiatives have also been launched and driven by our aspiration to excellence in safe operation of nuclear power plants. Vision and core values were set to align the people. Organizational learning was enhanced by benchmark studies, better systematic use of operational experience, self-assessment and external assessment. Based on these foundation blocks and with strong sponsorship from the top management, work processes were analyzed and improved by Peer Groups. (author)

  8. Using online reviews by restaurant patrons to identify unreported cases of foodborne illness - New York City, 2012-2013.

    Science.gov (United States)

    Harrison, Cassandra; Jorder, Mohip; Stern, Henri; Stavinsky, Faina; Reddy, Vasudha; Hanson, Heather; Waechter, HaeNa; Lowe, Luther; Gravano, Luis; Balter, Sharon

    2014-05-23

    While investigating an outbreak of gastrointestinal disease associated with a restaurant, the New York City Department of Health and Mental Hygiene (DOHMH) noted that patrons had reported illnesses on the business review website Yelp (http://www.yelp.com) that had not been reported to DOHMH. To explore the potential of using Yelp to identify unreported outbreaks, DOHMH worked with Columbia University and Yelp on a pilot project to prospectively identify restaurant reviews on Yelp that referred to foodborne illness. During July 1, 2012-March 31, 2013, approximately 294,000 Yelp restaurant reviews were analyzed by a software program developed for the project. The program identified 893 reviews that required further evaluation by a foodborne disease epidemiologist. Of the 893 reviews, 499 (56%) described an event consistent with foodborne illness (e.g., patrons reported diarrhea or vomiting after their meal), and 468 of those described an illness within 4 weeks of the review or did not provide a period. Only 3% of the illnesses referred to in the 468 reviews had also been reported directly to DOHMH via telephone and online systems during the same period. Closer examination determined that 129 of the 468 reviews required further investigation, resulting in telephone interviews with 27 reviewers. From those 27 interviews, three previously unreported restaurant-related outbreaks linked to 16 illnesses met DOHMH outbreak investigation criteria; environmental investigation of the three restaurants identified multiple food-handling violations. The results suggest that online restaurant reviews might help to identify unreported outbreaks of foodborne illness and restaurants with deficiencies in food handling. However, investigating reports of illness in this manner might require considerable time and resources.

  9. Lateral cervical cleft: a previously unreported anomaly resulting from incomplete disappearance of the second pharyngeal (branchial) cleft.

    Science.gov (United States)

    Gürsoy, M H; Gedikoğlu, G; Tanyel, F C

    1999-03-01

    The authors present a 2-year-old boy with a skin defect located in the right lateral side of the neck. They suggest the defect is a partial failure of disappearance of the second pharyngeal (branchial) cleft and propose a name of lateral cervical cleft.

  10. SAGE II observations of a previously unreported stratospheric volcanic aerosol cloud in the northern polar summer of 1990

    Science.gov (United States)

    Yue, Glenn K.; Veiga, Robert E.; Wang, Pi-Huan

    1994-01-01

    Analysis of aerosol extinction profiles obtained by the spaceborne SAGE II sensor reveals that there was an anomalous increase of aerosol extinction below 18.5 km at latitudes poleward of 50 deg N from July 28 to September 9, 1990. This widespread increase of aerosol extinction in the lower stratosphere was apparently due to a remote high-latitude volcanic eruption that has not been reported to date. The increase in stratospheric optical depth in the northern polar region was about 50% in August and had diminished by October 1990. This eruption caused an increase in stratospheric aerosol mass of about 0.33 x 10(exp 5) tons, assuming the aerosol was composed of sulfuric acid and water.

  11. Multiple bilateral lower limb fractures in a 2-year-old child: previously unreported injury with a unique mechanism

    Directory of Open Access Journals (Sweden)

    Anuj Jain

    2014-10-01

    Full Text Available 【Abstract】Fall from height is a common cause of unintentional injuries in children and accounts for 6% of all trauma-related childhood deaths, usually from head injury. We report a case of a 2-year-old child with multiple fractures of the bilateral lower limbs due to this reason. A child fell from a height of around 15 feet after toppling from a alcony. He developed multiple fractures involving the right femoral shaft, right distal femoral epiphysis (Salter Harris type 2, right distal metaphysis of the tibia and fi bula, and undisplaced Salter Harris type 2 epiphyseal injury of the left distal tibia. There were no head, abdominal or spinal injuries. The patient was taken into emergency operation theatre after initial management which consisted of intravenous fl uids, blood transfusion, and splintage of both lower limbs. Fracture of the femoral shaft was treated by closed reduction and fixation using two titanium elastic nails. Distal femoral physeal injury required open eduction and fixation with K wires. Distal tibia fractures were closely reduced and managed nonoperatively in both the lower limbs. All the fractures united in four weeks. At the last follow-up, the child had no disability and was able to perform daily ctivities comfortably. We also proposed the unique mechanism of injury in this report. Key words: Multiple bilateral lower limb fractures; Fall; Child

  12. Karnyothrips flavipes, a previously unreported predatory thrips of the coffee berry borer: DNA-based gut content analysis

    Science.gov (United States)

    A new predator of the coffee berry borer, Hypothenemus hampei, was found in the coffee growing area of Kisii in Western Kenya. Field observations, laboratory trials and gut content analysis using molecular tools have confirmed the role of the predatory thrips Karnyothrips flavipes Jones (Phlaeothrip...

  13. A Case of Acute Myeloid Leukemia with a Previously Unreported Translocation (14; 15 (q32; q13

    Directory of Open Access Journals (Sweden)

    Mohamad Khawandanah

    2014-01-01

    Full Text Available Background. We hereby describe what we believe to be the first reported case of t (14; 15 (q32; q13 associated with acute myeloid leukemia (AML. Methods. PubMed, Embase, and OVID search engines were used to review the related literature and similar published cases. Case. A47-year-old female presented in December 2011 with AML (acute myelomonocytic leukemia with normal cytogenetics; molecular testing revealed FLT-3 internal tandem duplication (ITD mutation, while no mutations involving FLT3 D385/I836, NPM1 exon 12, or KIT exons 8 and 17 were detected. She was induced with 7 + 3 (cytarabine + idarubicin and achieved complete remission after a second induction with high-dose cytarabine (HiDAC followed by uneventful consolidation. She presented 19 months after diagnosis with relapsed disease. Of note, at relapse cytogenetic analysis revealed t (14; 15 (q32; q13, while FLT-3 analysis showed a codon D835 mutation (no ITD mutation was detected. She proved refractory to the initial clofarabine-based regimen, so FLAG-idarubicin then was used. She continued to have persistent disease, and she was discharged on best supportive care. Conclusion. Based on this single case of AML with t (14; 15 (q32; q13, this newly reported translocation may be associated with refractory disease.

  14. Unreported employment and tax evasion in mid-transition : comparing developments and causes in the Baltic States

    OpenAIRE

    Jaanika Meriküll; Karsten Staehr

    2008-01-01

    This paper compares the prevalence and determinants of unreported employment in the three Baltic States in 1998 and 2002 using a hitherto little used dataset. The prevalence of unreported employment varies substantially across the three countries and across the two sampling years. Microeconometric estimations show that firm-related characteristics, such as sectoral activity, firm size and employment trends, are important determinants of unreported employment in all three countries, whereas th...

  15. Extensive forearm deep venous thrombosis following a severe infliximab infusion reaction.

    Science.gov (United States)

    Ryan, Barbara M; Romberg, Marielle; Wolters, Frank; Stockbrugger, Reinhold W

    2004-09-01

    Here we describe a patient with Crohn's disease who developed a severe infliximab infusion reaction (IIR), complicated 1 day later by severe swelling of the forearm and hand ipsilateral to the site of infliximab infusion. This proved to be extensive forearm deep venous thrombosis. The site of thrombosis and the chronological relationship with the IIR implicates a hypersensitivity to infliximab in the causation of the venous thrombosis in this case. With an increasing trend towards re-treating patients with known IIRs, clinicians should be aware of this potentially serious and previously unreported complication.

  16. Family Business or Social Problem? The Cost of Unreported Domestic Violence

    Science.gov (United States)

    Carrell, Scott E.; Hoekstra, Mark

    2012-01-01

    Social interest in problems such as domestic violence is typically motivated by concerns regarding equity, rather than efficiency. However, we document that taking steps to reduce domestic violence by reporting it yields substantial benefits to external parties. Specifically, we find that although children exposed to as-yet-unreported domestic…

  17. Duane retraction syndrome type 1 with Usher syndrome type 2: an unreported association.

    Science.gov (United States)

    Khurana, Bhawna Piplani; Khurana, Aruj Kumar; Grover, Sumit

    2015-05-07

    Duane retraction syndrome is characterized by globe retraction and palpebral fissure narrowing on adduction, with restriction of abduction, adduction, or both. Usher syndrome type 2 consists of congenital bilateral sensorineural hearing loss and retinitis pigmentosa. The authors present a case with a yet unreported association between Duane retraction syndrome type 1 and Usher syndrome type 2. Copyright 2015, SLACK Incorporated.

  18. An unreported type of coronary artery naomaly in congenitally corrected transposition of great arteries

    Energy Technology Data Exchange (ETDEWEB)

    Kwak, Min Kyu; Jeong, Yeon Joo; Lee, Gee Won; Lee, Nam Kyung; Choi, Jung Hyun; Lee, Ji Won [Medical Research Institute, Pusan National University Hospital, Busan (Korea, Republic of)

    2016-07-15

    Coronary artery variations are associated anomalies in 45% of congenitally corrected transposition of the great arteries (ccTGA) cases, and it is important to detect any coronary artery anomalies before cardiac surgery. We report a case of a 51-year-old woman with ccTGA and an unreported type of coronary artery anomaly.

  19. Public and Private Sector Jobs, Unreported Income and Consumption Gap in India: Evidence from Micro-Data

    OpenAIRE

    Kar, Saibal; Roy, Poulomi; Saha, Sarani

    2012-01-01

    This paper tries to document the presence of unreported income among public sector employees in India. We investigate empirically the wage gap as well as consumption expenditure parity between public and private sector workers. It tests the hypothesis that despite a lower level of public sector income in some of the quantiles, if the level of durable goods consumption between the private and the public sector employees are similar, then it might be indicative of the presence of unreported inc...

  20. Heuristics in primary care for recognition of unreported vision loss in older people: a technology development study.

    Science.gov (United States)

    Wijeyekoon, Skanda; Kharicha, Kalpa; Iliffe, Steve

    2015-09-01

    To evaluate heuristics (rules of thumb) for recognition of undetected vision loss in older patients in primary care. Vision loss is associated with ageing, and its prevalence is increasing. Visual impairment has a broad impact on health, functioning and well-being. Unrecognised vision loss remains common, and screening interventions have yet to reduce its prevalence. An alternative approach is to enhance practitioners' skills in recognising undetected vision loss, by having a more detailed picture of those who are likely not to act on vision changes, report symptoms or have eye tests. This paper describes a qualitative technology development study to evaluate heuristics for recognition of undetected vision loss in older patients in primary care. Using a previous modelling study, two heuristics in the form of mnemonics were developed to aid pattern recognition and allow general practitioners to identify potential cases of unreported vision loss. These heuristics were then analysed with experts. Findings It was concluded that their implementation in modern general practice was unsuitable and an alternative solution should be sort.

  1. Calcium hydroxyapatite crystal deposition with intraosseous penetration involving the posterior aspect of the cervical spine: a previously unreported cause of neck pain.

    Science.gov (United States)

    Urrutia, Julio; Contreras, Oscar

    2017-05-01

    Calcific tendinitis is a frequent disorder caused by hydroxyapatite crystal deposition; however, bone erosions from calcific tendinitis are unusual. The spinal manifestation of this disease is calcific tendinitis of the longus colli muscle; this disease has never been described in the posterior aspect of the spine. We report a case of calcium hydroxyapatite crystal deposition involving the posterior cervical spine eroding the bone cortex. A 57-year-old woman presented with a 5-month history of left-sided neck pain. Radiographs showed C4-C5 interspinous calcification with lytic compromise of the posterior arch of C4. Magnetic resonance imaging confirmed a lytic lesion of the posterior arch of C4, with a soft tissue mass extending to the C4-C5 interspinous space; calcifications were observed as very low signal intensity areas on T1 and T2 sequences, surrounded by gadolinium-enhanced soft tissues. A computed tomography (CT) scan confirmed the bone erosions and the soft tissue calcifications. A CT-guided needle biopsy was performed; it showed vascularized connective tissue with inflammatory histiocytic infiltration and multinucleated giant cells; Alizarin Red stain confirmed the presence of hydroxyapatite crystals. The patient was treated with anti-inflammatories for 2 weeks. She has been asymptomatic in a 6-month follow-up; a CT scan at the last follow-up revealed reparative remodeling of bone erosions. This is the first report of calcium hydroxyapatite crystal deposition with intraosseous penetration involving the posterior aspect of the cervical spine. Considering that this unusual lesion can be misinterpreted as a tumor or infection, high suspicion is required to avoid unnecessary surgical procedures.

  2. Molecular diagnosis of a previously unreported predator-prey association in coffee: Karnyothrips flavipes Jones (Thysanoptera: Phlaeothripidae) predation on the coffee berry borer

    Science.gov (United States)

    Jaramillo, Juliana; Chapman, Eric G.; Vega, Fernando E.; Harwood, James D.

    2010-03-01

    The coffee berry borer, Hypothenemus hampei, is the most important pest of coffee throughout the world, causing losses estimated at US 500 million/year. The thrips Karnyothrips flavipes was observed for the first time feeding on immature stages of H. hampei in April 2008 from samples collected in the Kisii area of Western Kenya. Since the trophic interactions between H. hampei and K. flavipes are carried out entirely within the coffee berry, and because thrips feed by liquid ingestion, we used molecular gut-content analysis to confirm the potential role of K. flavipes as a predator of H. hampei in an organic coffee production system. Species-specific COI primers designed for H. hampei were shown to have a high degree of specificity for H. hampei DNA and did not produce any PCR product from DNA templates of the other insects associated with the coffee agroecosystems. In total, 3,327 K. flavipes emerged from 17,792 H. hampei-infested berries collected from the field between April and September 2008. Throughout the season, 8.3% of K. flavipes tested positive for H. hampei DNA, although at times this figure approached 50%. Prey availability was significantly correlated with prey consumption, thus indicating the potential impact on H. hampei populations.

  3. A Bottom-Up Understanding of Illegal, Unreported, and Unregulated Fishing in Lake Victoria

    Directory of Open Access Journals (Sweden)

    Joseph Luomba

    2016-10-01

    Full Text Available Illegal, unreported, and unregulated (IUU fishing is a major concern in fisheries management around the world. Several measures have been taken to address the problem. In Lake Victoria, the alleviation of IUU fishing is implemented through the Regional Plan of Action (RPOA-IUU, which restricts use of certain fishing gear, as well as prohibits fishing in closed areas and during closed seasons. Despite the long-term efforts to monitor and control what goes on in the fisheries, IUU fishing has persisted in Lake Victoria. Inspired by interactive governance theory, this paper argues that the persistence of IUU fishing could be due to different images that stakeholders have about the situation, rather than the lack of management competency. Through structured interviews with 150 fisheries stakeholders on Ijinga Island in the southeastern part of Lake Victoria, Tanzania, using paired comparison questionnaires, the study elicits stakeholders’ perspective about the severity of different locally-pertinent fishing-related activities. The results show that while fisheries stakeholder groups agree on their judgments about certain fishing gears, some differences are also apparent. For instance, fisheries managers and scientists do not always agree with fishing people about what activities cause the most damage to fisheries resources and ecosystem. Further, they tend to consider some IUU fishing-related activities less damaging than some non-IUU fishing. Such disparity creates governability challenges, pointing to the need to revisit relevant regulatory measures and to make them consistent with the knowledge and judgments of all stakeholders. Based on these findings, we discuss governing interventions that may contribute to addressing IUU fishing in Lake Victoria and elsewhere.

  4. Unreported links between trial registrations and published articles were identified using document similarity measures in a cross-sectional analysis of ClinicalTrials.gov.

    Science.gov (United States)

    Dunn, Adam G; Coiera, Enrico; Bourgeois, Florence T

    2018-03-01

    Trial registries can be used to measure reporting biases and support systematic reviews, but 45% of registrations do not provide a link to the article reporting on the trial. We evaluated the use of document similarity methods to identify unreported links between ClinicalTrials.gov and PubMed. We extracted terms and concepts from a data set of 72,469 ClinicalTrials.gov registrations and 276,307 PubMed articles and tested methods for ranking articles across 16,005 reported links and 90 manually identified unreported links. Performance was measured by the median rank of matching articles and the proportion of unreported links that could be found by screening ranked candidate articles in order. The best-performing concept-based representation produced a median rank of 3 (interquartile range [IQR] 1-21) for reported links and 3 (IQR 1-19) for the manually identified unreported links, and term-based representations produced a median rank of 2 (1-20) for reported links and 2 (IQR 1-12) in unreported links. The matching article was ranked first for 40% of registrations, and screening 50 candidate articles per registration identified 86% of the unreported links. Leveraging the growth in the corpus of reported links between ClinicalTrials.gov and PubMed, we found that document similarity methods can assist in the identification of unreported links between trial registrations and corresponding articles. Copyright © 2017 Elsevier Inc. All rights reserved.

  5. Laparoscopy After Previous Laparotomy

    Directory of Open Access Journals (Sweden)

    Zulfo Godinjak

    2006-11-01

    Full Text Available Following the abdominal surgery, extensive adhesions often occur and they can cause difficulties during laparoscopic operations. However, previous laparotomy is not considered to be a contraindication for laparoscopy. The aim of this study is to present that an insertion of Veres needle in the region of umbilicus is a safe method for creating a pneumoperitoneum for laparoscopic operations after previous laparotomy. In the last three years, we have performed 144 laparoscopic operations in patients that previously underwent one or two laparotomies. Pathology of digestive system, genital organs, Cesarean Section or abdominal war injuries were the most common causes of previouslaparotomy. During those operations or during entering into abdominal cavity we have not experienced any complications, while in 7 patients we performed conversion to laparotomy following the diagnostic laparoscopy. In all patients an insertion of Veres needle and trocar insertion in the umbilical region was performed, namely a technique of closed laparoscopy. Not even in one patient adhesions in the region of umbilicus were found, and no abdominal organs were injured.

  6. On detection of the possible use of VVERs for unreported production of plutonium. Final report for the period July 1988 - December 1989

    International Nuclear Information System (INIS)

    Simov, R.; Nelov, N.; Stoyanova, I.; Kovachev, N.; Yonchev, P.

    1989-01-01

    The study includes an analysis of the feasibility of unreported production of plutonium-239 in VVER-440 reactors. It is shown that for VVER-440 reactors 36 natural uranium oxide fuel assemblies in the peripheral region of the core need to be loaded to produce 8 kg of extra plutonium in one cycle. Substituting the peripheral fuel assemblies with natural uranium oxide fuel assemblies, the changes in the power peaking are negligible and do not affect reactor safety. Unreported production outside the core is not practical due to physical and mechanical constraints, low flux level, etc. The feasibility of unreported removal of irradiated material in spent fuel cask has been also assessed. After about a month cooling time, still within the refueling period, the irradiated natural uranium fuel assemblies could be removed off-site without significant health hazard to the workers. To improve the effectiveness of the safeguards objectives, additional inspection activities are suggested. 10 figs

  7. Echinocandin failure case due to a yet unreported FKS mutation in Candida krusei

    DEFF Research Database (Denmark)

    Jensen, Rasmus Hare; Justesen, Ulrik Stenz; Rewes, Annika

    Echinocandins are the preferred therapy for invasive infections due to Candida krusei. We present here a case of clinical failure involving C. krusei with a characteristic FKS1 hot spot mutation not previously reported in C. krusei that was isolated after 14 days of treatment. Anidulafungin MICs...... were elevated by ≥5 dilution steps above the clinical breakpoint but by only 1 step for a Candida albicans isolate harboring the corresponding mutation, suggesting a notable species-specific difference in the MIC increase conferred by this mutation....

  8. Confronting Illegal, Unreported and Unregulated (IUU) fishing with proper port and flagged states policies: The case of South Korea and European Union

    Czech Academy of Sciences Publication Activity Database

    Midani, Rahimi Amaj; Lee, S.G.

    2016-01-01

    Roč. 10, č. 3 (2016), s. 43-51 E-ISSN 1307-234X Institutional support: RVO:60077344 Keywords : illegal unreported and unregulated * South Korea * distant water fishing * European Union * normative power * market power Subject RIV: GL - Fishing www. fisheries sciences.com

  9. Clinical report of a 17q12 microdeletion with additionally unreported clinical features.

    Science.gov (United States)

    Roberts, Jennifer L; Gandomi, Stephanie K; Parra, Melissa; Lu, Ira; Gau, Chia-Ling; Dasouki, Majed; Butler, Merlin G

    2014-01-01

    Copy number variations involving the 17q12 region have been associated with developmental and speech delay, autism, aggression, self-injury, biting and hitting, oppositional defiance, inappropriate language, and auditory hallucinations. We present a tall-appearing 17-year-old boy with marfanoid habitus, hypermobile joints, mild scoliosis, pectus deformity, widely spaced nipples, pes cavus, autism spectrum disorder, intellectual disability, and psychiatric manifestations including physical and verbal aggression, obsessive-compulsive behaviors, and oppositional defiance. An echocardiogram showed borderline increased aortic root size. An abdominal ultrasound revealed a small pancreas, mild splenomegaly with a 1.3 cm accessory splenule, and normal kidneys and liver. A testing panel for Marfan, aneurysm, and related disorders was negative. Subsequently, a 400 K array-based comparative genomic hybridization (aCGH) + SNP analysis was performed which identified a de novo suspected pathogenic deletion on chromosome 17q12 encompassing 28 genes. Despite the limited number of cases described in the literature with 17q12 rearrangements, our proband's phenotypic features both overlap and expand on previously reported cases. Since syndrome-specific DNA sequencing studies failed to provide an explanation for this patient's unusual habitus, we postulate that this case represents an expansion of the 17q12 microdeletion phenotype. Further analysis of the deleted interval is recommended for new genotype-phenotype correlations.

  10. Clinical Report of a 17q12 Microdeletion with Additionally Unreported Clinical Features

    Directory of Open Access Journals (Sweden)

    Jennifer L. Roberts

    2014-01-01

    Full Text Available Copy number variations involving the 17q12 region have been associated with developmental and speech delay, autism, aggression, self-injury, biting and hitting, oppositional defiance, inappropriate language, and auditory hallucinations. We present a tall-appearing 17-year-old boy with marfanoid habitus, hypermobile joints, mild scoliosis, pectus deformity, widely spaced nipples, pes cavus, autism spectrum disorder, intellectual disability, and psychiatric manifestations including physical and verbal aggression, obsessive-compulsive behaviors, and oppositional defiance. An echocardiogram showed borderline increased aortic root size. An abdominal ultrasound revealed a small pancreas, mild splenomegaly with a 1.3 cm accessory splenule, and normal kidneys and liver. A testing panel for Marfan, aneurysm, and related disorders was negative. Subsequently, a 400 K array-based comparative genomic hybridization (aCGH + SNP analysis was performed which identified a de novo suspected pathogenic deletion on chromosome 17q12 encompassing 28 genes. Despite the limited number of cases described in the literature with 17q12 rearrangements, our proband’s phenotypic features both overlap and expand on previously reported cases. Since syndrome-specific DNA sequencing studies failed to provide an explanation for this patient’s unusual habitus, we postulate that this case represents an expansion of the 17q12 microdeletion phenotype. Further analysis of the deleted interval is recommended for new genotype-phenotype correlations.

  11. COST-EFFECTIVE APPROACH TO ESTIMATE UNREPORTED DATA: REBUILDING HISTORY OF LIFT-NET FISHING IN KWANDANG WATERS

    Directory of Open Access Journals (Sweden)

    Andhika Prima Prasetyo

    2014-12-01

    Full Text Available This paper aims to develop cost-effective approach regarding the estimation unreported annual catch data of lift-net fishery using Google Earth imagery. Lift net fishery is one of the main fishing activities of coastal community in Kwandang Bay, it has been faced problem of uncertain fisheries status due to limited recorded data. Combination of a Monte Carlo procedure was applied by involving couple of assumptions on parameters such as estimate growth rate of the total number of lift-net per years (10%, day at sea per unit per month (21 days and operated lift-net per month (50% and 80%. The results showed that 101 units of lift-nets were found around Kwandang waters based on Google Earth imagery recorded in October, 7th 2010, and this were used as a benchmark of calculation. This prediction was 28 units higher than official data from North Gorontalo District of Marine Affairs and Fisheries Services (DKP Gorontalo Utara. Compared with capture fisheries statistics issued by Kwandang CFP, the estimated lift-net catches based on two-scenarios represent additional catches of 46 % and 86 %. These results suggested and could be used as a correction index to improve the reliability of Kwandang District officially reported fisheries statistics as a baseline to develop a local common fisheries policy.

  12. Erysipelothrix endocarditis with previous cutaneous lesion: report of a case and review of the literature

    Directory of Open Access Journals (Sweden)

    Marion P. Rocha

    1989-08-01

    Full Text Available This report describes the first documented case of Erysipelothrix rhusiopathiae endocarditis in Latin America. The patient was a 51-years-old male, moderate alcoholic, with a previous history of aortic failure. He was used to fishing and cooking as a hobby and had his left hand wounded by a fish-bone. The disease began with erysipeloid form and developed to septicemia and endocarditis. He was treated with antibiotics and surgery for aortic valve replacement. There are only 46 cases of E. rhusiopathiae endocarditis reported to date. The authors wonder if several other cases might go unreported for lack of microbiological laboratorial diagnosis.

  13. Unreported births and deaths, a severe obstacle for improved neonatal survival in low-income countries; a population based study

    Directory of Open Access Journals (Sweden)

    Wallin Lars

    2008-03-01

    Full Text Available Abstract Background In order to improve child survival there is a need to target neonatal mortality. In this pursuit, valid local and national statistics on child health are essential. We analyze to what extent births and neonatal deaths are unreported in a low-income country and discuss the consequences at local and international levels for efforts to save newborn lives. Methods Information on all births and neonatal deaths in Quang Ninh province in Northern Vietnam in 2005 was ascertained by systematic inventory through group interviews with key informants, questionnaires and examination of health facility records. Health care staff at 187 Community Health Centers (CHC and 18 hospitals, in addition to 1372 Village Health Workers (VHW, were included in the study. Results were compared with the official reports of the Provincial Health Bureau. Results The neonatal mortality rate (NMR was 16/1000 (284 neonatal deaths/17 519 births, as compared to the official rate of 4.2/1000. The NMR varied between 44/1000 and 10/1000 in the different districts of the province. The under-reporting was mainly attributable to a dysfunctional reporting system and the fact that families, not the health system, were made responsible to register births and deaths. This under-reporting has severe consequences at local, national and international levels. At a local level, it results in a lack of awareness of the magnitude and differentials in NMR, leading to an indifference towards the problem. At a national and international level the perceived low mortality rate is manifested in a lack of investments in perinatal health programs. Conclusion This example of a faulty health information system is reportedly not unique in low and middle income countries where needs for neonatal health reforms are greatest. Improving reporting systems on births and neonatal deaths is a matter of human rights and a prerequisite for reducing neonatal mortality in order to reach the fourth

  14. Fish product mislabelling: failings of traceability in the production chain and implications for illegal, unreported and unregulated (IUU) fishing.

    Science.gov (United States)

    Helyar, Sarah J; Lloyd, Hywel Ap D; de Bruyn, Mark; Leake, Jonathan; Bennett, Niall; Carvalho, Gary R

    2014-01-01

    Increasing consumer demand for seafood, combined with concern over the health of our oceans, has led to many initiatives aimed at tackling destructive fishing practices and promoting the sustainability of fisheries. An important global threat to sustainable fisheries is Illegal, Unreported and Unregulated (IUU) fishing, and there is now an increased emphasis on the use of trade measures to prevent IUU-sourced fish and fish products from entering the international market. Initiatives encompass new legislation in the European Union requiring the inclusion of species names on catch labels throughout the distribution chain. Such certification measures do not, however, guarantee accuracy of species designation. Using two DNA-based methods to compare species descriptions with molecular ID, we examined 386 samples of white fish, or products labelled as primarily containing white fish, from major UK supermarket chains. Species specific real-time PCR probes were used for cod (Gadus morhua) and haddock (Melanogrammus aeglefinus) to provide a highly sensitive and species-specific test for the major species of white fish sold in the UK. Additionally, fish-specific primers were used to sequence the forensically validated barcoding gene, mitochondrial cytochrome oxidase I (COI). Overall levels of congruence between product label and genetic species identification were high, with 94.34% of samples correctly labelled, though a significant proportion in terms of potential volume, were mislabelled. Substitution was usually for a cheaper alternative and, in one case, extended to a tropical species. To our knowledge, this is the first published study encompassing a large-scale assessment of UK retailers, and if representative, indicates a potentially significant incidence of incorrect product designation.

  15. Fish product mislabelling: failings of traceability in the production chain and implications for illegal, unreported and unregulated (IUU fishing.

    Directory of Open Access Journals (Sweden)

    Sarah J Helyar

    Full Text Available Increasing consumer demand for seafood, combined with concern over the health of our oceans, has led to many initiatives aimed at tackling destructive fishing practices and promoting the sustainability of fisheries. An important global threat to sustainable fisheries is Illegal, Unreported and Unregulated (IUU fishing, and there is now an increased emphasis on the use of trade measures to prevent IUU-sourced fish and fish products from entering the international market. Initiatives encompass new legislation in the European Union requiring the inclusion of species names on catch labels throughout the distribution chain. Such certification measures do not, however, guarantee accuracy of species designation. Using two DNA-based methods to compare species descriptions with molecular ID, we examined 386 samples of white fish, or products labelled as primarily containing white fish, from major UK supermarket chains. Species specific real-time PCR probes were used for cod (Gadus morhua and haddock (Melanogrammus aeglefinus to provide a highly sensitive and species-specific test for the major species of white fish sold in the UK. Additionally, fish-specific primers were used to sequence the forensically validated barcoding gene, mitochondrial cytochrome oxidase I (COI. Overall levels of congruence between product label and genetic species identification were high, with 94.34% of samples correctly labelled, though a significant proportion in terms of potential volume, were mislabelled. Substitution was usually for a cheaper alternative and, in one case, extended to a tropical species. To our knowledge, this is the first published study encompassing a large-scale assessment of UK retailers, and if representative, indicates a potentially significant incidence of incorrect product designation.

  16. Cucullanid nematodes (Nematoda: Cucullanidae) from deep-sea marine fishes off New Caledonia, including Dichelyne etelidis n. sp.

    Science.gov (United States)

    Moravec, František; Justine, Jean-Lou

    2011-02-01

    Three nematode species of the family Cucullanidae, intestinal parasites of marine perciform fishes, are reported from off New Caledonia: Cucullanus bourdini Petter & Le Bel, 1992 from the crimson jobfish Pristipomoides filamentosus (Valenciennes) and the goldflag jobfish Pristipomoides auricilla (Jordan, Evermann & Tanaka) (new host record) (both Lutjanidae); Dichelyne etelidis n. sp. from the deep-water red snapper Etelis carbunculus Cuvier (type-host) and the deep-water longtail red snapper Etelis coruscans Valenciennes (both Lutjanidae); and Dichelyne sp. (only one female) from the trumpet emperor Lethrinus miniatus (Forster) (Lethrinidae). Detailed light and electron microscopical studies revealed in C. bourdini some taxonomically important, previously unreported features, such as the location of the excretory pore, nature of the vulva and the size of fully-developed eggs. The new species, D. etelidis, is characterised mainly by the length of the spicules (462-748 μm), a single intestinal caecum, the location of the deirids and excretory pore, the arrangement of the genital papillae and the host group.

  17. Deep frying

    NARCIS (Netherlands)

    Koerten, van K.N.

    2016-01-01

    Deep frying is one of the most used methods in the food processing industry. Though practically any food can be fried, French fries are probably the most well-known deep fried products. The popularity of French fries stems from their unique taste and texture, a crispy outside with a mealy soft

  18. Deep learning

    CERN Document Server

    Goodfellow, Ian; Courville, Aaron

    2016-01-01

    Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language proces...

  19. AB072. Novel mutation in the hepatocyte nuclear factor 1b/maturity-onset diabetes of the young type 5 gene—unreported Vietnamese case

    OpenAIRE

    Dung, Vu Chi; Thao, Bui Phuong; Ngoc, Can Thi Bich; Khanh, Nguyen Ngoc; Ellard, Sian

    2015-01-01

    Maturity-onset diabetes of the young type 5 (MODY5), a type of dominantly inherited diabetes mellitus and nephropathy, has been associated with mutations of the hepatocyte nuclear factor-1 (HNF-1β) gene, mostly generating truncated protein. Various phenotypes are related to HNF-1β mutations. Our aim to describe clinical and genetic findings in the unreported Vietnamese case identified with HNF-1β mutations. The proband with kidney failure from 7.5 years of age and diabetes diagnosed at 13.5 y...

  20. Previously unknown species of Aspergillus.

    Science.gov (United States)

    Gautier, M; Normand, A-C; Ranque, S

    2016-08-01

    The use of multi-locus DNA sequence analysis has led to the description of previously unknown 'cryptic' Aspergillus species, whereas classical morphology-based identification of Aspergillus remains limited to the section or species-complex level. The current literature highlights two main features concerning these 'cryptic' Aspergillus species. First, the prevalence of such species in clinical samples is relatively high compared with emergent filamentous fungal taxa such as Mucorales, Scedosporium or Fusarium. Second, it is clearly important to identify these species in the clinical laboratory because of the high frequency of antifungal drug-resistant isolates of such Aspergillus species. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been shown to enable the identification of filamentous fungi with an accuracy similar to that of DNA sequence-based methods. As MALDI-TOF MS is well suited to the routine clinical laboratory workflow, it facilitates the identification of these 'cryptic' Aspergillus species at the routine mycology bench. The rapid establishment of enhanced filamentous fungi identification facilities will lead to a better understanding of the epidemiology and clinical importance of these emerging Aspergillus species. Based on routine MALDI-TOF MS-based identification results, we provide original insights into the key interpretation issues of a positive Aspergillus culture from a clinical sample. Which ubiquitous species that are frequently isolated from air samples are rarely involved in human invasive disease? Can both the species and the type of biological sample indicate Aspergillus carriage, colonization or infection in a patient? Highly accurate routine filamentous fungi identification is central to enhance the understanding of these previously unknown Aspergillus species, with a vital impact on further improved patient care. Copyright © 2016 European Society of Clinical Microbiology and

  1. Temporary Efficacy of Pyrimethamine in Juvenile-Onset Tay-Sachs Disease Caused by 2 Unreported HEXA Mutations in the Indian Population

    Directory of Open Access Journals (Sweden)

    Anaita Udwadia-Hegde MD, DCH, MRCPCH

    2017-01-01

    Full Text Available Background: Juvenile Tay-Sachs disease is rarer than other forms of Tay-Sachs disease and is usually seen in children between the age of 2 and 10 years. Pyrimethamine as a pharmacological chaperone was used to increase β-hexosaminidase A activity in this patient. Patient: We describe a patient with Tay-Sachs disease from the Indian population, a juvenile case who presented with developmental regression starting at the age of three, initially with motor followed by language regression. She is currently incapacitated with severe behavioral issues. Conclusion: This brief communication gives an insight into the efficacy of pharmacological chaperones. It also describes two unreported mutations in hexosaminidase A gene from the Indian population. After commencing Pyrimethamine, though initial benefits with increase in levels corresponded with briefly halting the motor regression, the observed increase was only transient and not associated with discernible beneficial neurological or psychiatric effects.

  2. Temporary Efficacy of Pyrimethamine in Juvenile-Onset Tay-Sachs Disease Caused by 2 Unreported HEXA Mutations in the Indian Population.

    Science.gov (United States)

    Udwadia-Hegde, Anaita; Hajirnis, Omkar

    2017-01-01

    Juvenile Tay-Sachs disease is rarer than other forms of Tay-Sachs disease and is usually seen in children between the age of 2 and 10 years. Pyrimethamine as a pharmacological chaperone was used to increase β-hexosaminidase A activity in this patient. We describe a patient with Tay-Sachs disease from the Indian population, a juvenile case who presented with developmental regression starting at the age of three, initially with motor followed by language regression. She is currently incapacitated with severe behavioral issues. This brief communication gives an insight into the efficacy of pharmacological chaperones. It also describes two unreported mutations in hexosaminidase A gene from the Indian population. After commencing Pyrimethamine, though initial benefits with increase in levels corresponded with briefly halting the motor regression, the observed increase was only transient and not associated with discernible beneficial neurological or psychiatric effects.

  3. Two novel POC1A mutations in the primordial dwarfism, SOFT syndrome: Clinical homogeneity but also unreported malformations.

    Science.gov (United States)

    Barraza-García, Jimena; Iván Rivera-Pedroza, Carlos; Salamanca, Luis; Belinchón, Alberta; López-González, Vanesa; Sentchordi-Montané, Lucía; del Pozo, Ángela; Santos-Simarro, Fernando; Campos-Barros, Ángel; Lapunzina, Pablo; Guillén-Navarro, Encarna; González-Casado, Isabel; García-Miñaur, Sixto; Heath, Karen E

    2016-01-01

    Primordial dwarfism encompasses rare conditions characterized by severe intrauterine growth retardation and growth deficiency throughout life. Recently, three POC1A mutations have been reported in six families with the primordial dwarfism, SOFT syndrome (Short stature, Onychodysplasia, Facial dysmorphism, and hypoTrichosis). Using a custom-designed Next-generation sequencing skeletal dysplasia panel, we have identified two novel homozygous POC1A mutations in two individuals with primordial dwarfism. The severe growth retardation and the facial profiles are strikingly similar between our patients and those described previously. However, one of our patients was diagnosed with severe foramen magnum stenosis and subglottic tracheal stenosis, malformations not previously associated with this syndrome. Our findings confirm that POC1A mutations cause SOFT syndrome and that mutations in this gene should be considered in patients with severe pre- and postnatal short stature, symmetric shortening of long bones, triangular facies, sparse hair and short, thickened distal phalanges. © 2015 Wiley Periodicals, Inc.

  4. Deep Learning

    DEFF Research Database (Denmark)

    Jensen, Morten Bornø; Bahnsen, Chris Holmberg; Nasrollahi, Kamal

    2018-01-01

    I løbet af de sidste 10 år er kunstige neurale netværk gået fra at være en støvet, udstødt tekno-logi til at spille en hovedrolle i udviklingen af kunstig intelligens. Dette fænomen kaldes deep learning og er inspireret af hjernens opbygning.......I løbet af de sidste 10 år er kunstige neurale netværk gået fra at være en støvet, udstødt tekno-logi til at spille en hovedrolle i udviklingen af kunstig intelligens. Dette fænomen kaldes deep learning og er inspireret af hjernens opbygning....

  5. Deep geothermics

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    The hot-dry-rocks located at 3-4 km of depth correspond to low permeable rocks carrying a large amount of heat. The extraction of this heat usually requires artificial hydraulic fracturing of the rock to increase its permeability before water injection. Hot-dry-rocks geothermics or deep geothermics is not today a commercial channel but only a scientific and technological research field. The Soultz-sous-Forets site (Northern Alsace, France) is characterized by a 6 degrees per meter geothermal gradient and is used as a natural laboratory for deep geothermal and geological studies in the framework of a European research program. Two boreholes have been drilled up to 3600 m of depth in the highly-fractured granite massif beneath the site. The aim is to create a deep heat exchanger using only the natural fracturing for water transfer. A consortium of german, french and italian industrial companies (Pfalzwerke, Badenwerk, EdF and Enel) has been created for a more active participation to the pilot phase. (J.S.). 1 fig., 2 photos

  6. Occam paradox? A variation of tapia syndrome and an unreported complication of guidewire-assisted pedicle screw insertion.

    Science.gov (United States)

    Emohare, Osa; Peterson, Erik; Slinkard, Nathaniel; Janus, Seth; Morgan, Robert

    2013-10-01

    Study Design Case report. Clinical Question The clinical aim is to report on a previously unknown association between guidewire-assisted pedicle screw insertion and neuropraxia of the recurrent laryngeal nerve (RLN), and how this may overlap with the signs of Tapia syndrome; we also report our approach to the clinical management of this patient. Methods A 17-year-old male patient with idiopathic scoliosis experienced Tapia syndrome after posterior instrumentation and arthrodesis at the level of T1-L1. After extubation, the patient had a hoarse voice and difficulty in swallowing. Imaging showed a breach in the cortex of the anterior body of T1 corresponding to the RLN on the right. Results Otolaryngological examination noted right vocal fold immobility, decreased sensation of the endolarynx, and pooling of secretions on flexible laryngoscopy that indicated right-sided cranial nerve X injury and left-sided tongue deviation. Aspiration during a modified barium swallow prompted insertion of a percutaneous endoscopic gastrostomy tube before the patient was sent home. On postoperative day 20, a barium swallow demonstrated reduced aspiration, and the patient reported complete resolution of symptoms. The feeding tube was removed, and the patient resumed a normal diet 1 month later. Tapia syndrome, or persistent unilateral laryngeal and hypoglossal paralysis, is an uncommon neuropraxia, which has previously not been observed in association with a breached vertebral body at T1 along the course of the RLN. Conclusion Tapia syndrome should be a differential diagnostic consideration whenever these symptoms persist postoperatively and spine surgeons should be aware of this as a potential complication of guidewires in spinal instrumentation.

  7. Deep Visual Attention Prediction

    Science.gov (United States)

    Wang, Wenguan; Shen, Jianbing

    2018-05-01

    In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

  8. Deep smarts.

    Science.gov (United States)

    Leonard, Dorothy; Swap, Walter

    2004-09-01

    When a person sizes up a complex situation and rapidly comes to a decision that proves to be not just good but brilliant, you think, "That was smart." After you watch him do this a few times, you realize you're in the presence of something special. It's not raw brainpower, though that helps. It's not emotional intelligence, either, though that, too, is often involved. It's deep smarts. Deep smarts are not philosophical--they're not"wisdom" in that sense, but they're as close to wisdom as business gets. You see them in the manager who understands when and how to move into a new international market, in the executive who knows just what kind of talk to give when her organization is in crisis, in the technician who can track a product failure back to an interaction between independently produced elements. These are people whose knowledge would be hard to purchase on the open market. Their insight is based on know-how more than on know-what; it comprises a system view as well as expertise in individual areas. Because deep smarts are experienced based and often context specific, they can't be produced overnight or readily imported into an organization. It takes years for an individual to develop them--and no time at all for an organization to lose them when a valued veteran walks out the door. They can be taught, however, with the right techniques. Drawing on their forthcoming book Deep Smarts, Dorothy Leonard and Walter Swap say the best way to transfer such expertise to novices--and, on a larger scale, to make individual knowledge institutional--isn't through PowerPoint slides, a Web site of best practices, online training, project reports, or lectures. Rather, the sage needs to teach the neophyte individually how to draw wisdom from experience. Companies have to be willing to dedicate time and effort to such extensive training, but the investment more than pays for itself.

  9. Is Multitask Deep Learning Practical for Pharma?

    Science.gov (United States)

    Ramsundar, Bharath; Liu, Bowen; Wu, Zhenqin; Verras, Andreas; Tudor, Matthew; Sheridan, Robert P; Pande, Vijay

    2017-08-28

    Multitask deep learning has emerged as a powerful tool for computational drug discovery. However, despite a number of preliminary studies, multitask deep networks have yet to be widely deployed in the pharmaceutical and biotech industries. This lack of acceptance stems from both software difficulties and lack of understanding of the robustness of multitask deep networks. Our work aims to resolve both of these barriers to adoption. We introduce a high-quality open-source implementation of multitask deep networks as part of the DeepChem open-source platform. Our implementation enables simple python scripts to construct, fit, and evaluate sophisticated deep models. We use our implementation to analyze the performance of multitask deep networks and related deep models on four collections of pharmaceutical data (three of which have not previously been analyzed in the literature). We split these data sets into train/valid/test using time and neighbor splits to test multitask deep learning performance under challenging conditions. Our results demonstrate that multitask deep networks are surprisingly robust and can offer strong improvement over random forests. Our analysis and open-source implementation in DeepChem provide an argument that multitask deep networks are ready for widespread use in commercial drug discovery.

  10. Deep learning in neural networks: an overview.

    Science.gov (United States)

    Schmidhuber, Jürgen

    2015-01-01

    In recent years, deep artificial neural networks (including recurrent ones) have won numerous contests in pattern recognition and machine learning. This historical survey compactly summarizes relevant work, much of it from the previous millennium. Shallow and Deep Learners are distinguished by the depth of their credit assignment paths, which are chains of possibly learnable, causal links between actions and effects. I review deep supervised learning (also recapitulating the history of backpropagation), unsupervised learning, reinforcement learning & evolutionary computation, and indirect search for short programs encoding deep and large networks.

  11. DeepPy: Pythonic deep learning

    DEFF Research Database (Denmark)

    Larsen, Anders Boesen Lindbo

    This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly...... be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mathematical expressions as directed graphs. The latest version is available at http...

  12. Greedy Deep Dictionary Learning

    OpenAIRE

    Tariyal, Snigdha; Majumdar, Angshul; Singh, Richa; Vatsa, Mayank

    2016-01-01

    In this work we propose a new deep learning tool called deep dictionary learning. Multi-level dictionaries are learnt in a greedy fashion, one layer at a time. This requires solving a simple (shallow) dictionary learning problem, the solution to this is well known. We apply the proposed technique on some benchmark deep learning datasets. We compare our results with other deep learning tools like stacked autoencoder and deep belief network; and state of the art supervised dictionary learning t...

  13. Preoperative screening: value of previous tests.

    Science.gov (United States)

    Macpherson, D S; Snow, R; Lofgren, R P

    1990-12-15

    To determine the frequency of tests done in the year before elective surgery that might substitute for preoperative screening tests and to determine the frequency of test results that change from a normal value to a value likely to alter perioperative management. Retrospective cohort analysis of computerized laboratory data (complete blood count, sodium, potassium, and creatinine levels, prothrombin time, and partial thromboplastin time). Urban tertiary care Veterans Affairs Hospital. Consecutive sample of 1109 patients who had elective surgery in 1988. At admission, 7549 preoperative tests were done, 47% of which duplicated tests performed in the previous year. Of 3096 previous results that were normal as defined by hospital reference range and done closest to the time of but before admission (median interval, 2 months), 13 (0.4%; 95% CI, 0.2% to 0.7%), repeat values were outside a range considered acceptable for surgery. Most of the abnormalities were predictable from the patient's history, and most were not noted in the medical record. Of 461 previous tests that were abnormal, 78 (17%; CI, 13% to 20%) repeat values at admission were outside a range considered acceptable for surgery (P less than 0.001, frequency of clinically important abnormalities of patients with normal previous results with those with abnormal previous results). Physicians evaluating patients preoperatively could safely substitute the previous test results analyzed in this study for preoperative screening tests if the previous tests are normal and no obvious indication for retesting is present.

  14. Deep-water polychaetes (Annelida from the southeastern Gulf of California, Mexico

    Directory of Open Access Journals (Sweden)

    Nuria Méndez

    2006-09-01

    Full Text Available Polychaetes inhabiting deep-sea soft bottoms from the southeastern Gulf of California were collected during four oceanographic cruises during 2000 and 2001. Sampling of benthic organisms was performed with a benthic sledge to collect epifauna and a Karling dredge for epifauna and infauna, in a depth range from 732 to 2 250 m. A list of the polychaetes that were collected and their distribution are presented here. A total of 73 species (distributed among 33 families were identified. Moreover, 11 species were identified only to genus level and 20 species only to family level. With the exception of Ancistrosyllis hartmanae and Melinnampharete eoa, all identified species have been previously reported in soft bottoms of the Gulf of California or in adjacent areas. Additional previously unreported information is provided herein regarding depth ranges, geographical distribution, morphology and tubes inhabited by the organisms. The morphology of the ampharetids Amage sp. and Samytha sp. does not coincide with that of other species in these genera reported for the Gulf of California, which suggests that they are probably undescribed species. Rev. Biol. Trop. 54 (3: 773-785. Epub 2006 Sept. 29.Se recolectaron anélidos poliquetos de fondos profundos del SE del golfo de California durante cuatro campañas oceanográficas entre 2000 y 2001. El muestreo de organismos bentónicos se llevó a cabo mediante una draga de arrastre bentónica para recolectar epifauna y una draga tipo Karling para epifauna y endofauna, en un intervalo de profundidad de 732 a 2 250 m. Se presenta un listado de poliquetos con su distribución dentro del área de estudio. En total se identificaron 73 especies (distribuidas en 33 familias. Además, 11 especies fueron identificadas a nivel genérico y 20 a nivel de familia. Con excepción de Ancistrosyllis hartmanae y Melinnampharete eoa, todas las especies habían sido registradas en fondos blandos del golfo de California o zonas

  15. Taoism and Deep Ecology.

    Science.gov (United States)

    Sylvan, Richard; Bennett, David

    1988-01-01

    Contrasted are the philosophies of Deep Ecology and ancient Chinese. Discusses the cosmology, morality, lifestyle, views of power, politics, and environmental philosophies of each. Concludes that Deep Ecology could gain much from Taoism. (CW)

  16. Deep Incremental Boosting

    OpenAIRE

    Mosca, Alan; Magoulas, George D

    2017-01-01

    This paper introduces Deep Incremental Boosting, a new technique derived from AdaBoost, specifically adapted to work with Deep Learning methods, that reduces the required training time and improves generalisation. We draw inspiration from Transfer of Learning approaches to reduce the start-up time to training each incremental Ensemble member. We show a set of experiments that outlines some preliminary results on some common Deep Learning datasets and discuss the potential improvements Deep In...

  17. Automatic electromagnetic valve for previous vacuum

    International Nuclear Information System (INIS)

    Granados, C. E.; Martin, F.

    1959-01-01

    A valve which permits the maintenance of an installation vacuum when electric current fails is described. It also lets the air in the previous vacuum bomb to prevent the oil ascending in the vacuum tubes. (Author)

  18. Deep Space Telecommunications

    Science.gov (United States)

    Kuiper, T. B. H.; Resch, G. M.

    2000-01-01

    The increasing load on NASA's deep Space Network, the new capabilities for deep space missions inherent in a next-generation radio telescope, and the potential of new telescope technology for reducing construction and operation costs suggest a natural marriage between radio astronomy and deep space telecommunications in developing advanced radio telescope concepts.

  19. Deep learning with Python

    CERN Document Server

    Chollet, Francois

    2018-01-01

    DESCRIPTION Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. KEY FEATURES • Practical code examples • In-depth introduction to Keras • Teaches the difference between Deep Learning and AI ABOUT THE TECHNOLOGY Deep learning is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more. AUTHOR BIO Francois Chollet is the author of Keras, one of the most widely used libraries for deep learning in Python. He has been working with deep neural ...

  20. Deep learning evaluation using deep linguistic processing

    OpenAIRE

    Kuhnle, Alexander; Copestake, Ann

    2017-01-01

    We discuss problems with the standard approaches to evaluation for tasks like visual question answering, and argue that artificial data can be used to address these as a complement to current practice. We demonstrate that with the help of existing 'deep' linguistic processing technology we are able to create challenging abstract datasets, which enable us to investigate the language understanding abilities of multimodal deep learning models in detail, as compared to a single performance value ...

  1. 77 FR 70176 - Previous Participation Certification

    Science.gov (United States)

    2012-11-23

    ... participants' previous participation in government programs and ensure that the past record is acceptable prior... information is designed to be 100 percent automated and digital submission of all data and certifications is... government programs and ensure that the past record is acceptable prior to granting approval to participate...

  2. On the Tengiz petroleum deposit previous study

    International Nuclear Information System (INIS)

    Nysangaliev, A.N.; Kuspangaliev, T.K.

    1997-01-01

    Tengiz petroleum deposit previous study is described. Some consideration about structure of productive formation, specific characteristic properties of petroleum-bearing collectors are presented. Recommendation on their detail study and using of experience on exploration and development of petroleum deposit which have analogy on most important geological and industrial parameters are given. (author)

  3. Subsequent pregnancy outcome after previous foetal death

    NARCIS (Netherlands)

    Nijkamp, J. W.; Korteweg, F. J.; Holm, J. P.; Timmer, A.; Erwich, J. J. H. M.; van Pampus, M. G.

    Objective: A history of foetal death is a risk factor for complications and foetal death in subsequent pregnancies as most previous risk factors remain present and an underlying cause of death may recur. The purpose of this study was to evaluate subsequent pregnancy outcome after foetal death and to

  4. DeepInfer: open-source deep learning deployment toolkit for image-guided therapy

    Science.gov (United States)

    Mehrtash, Alireza; Pesteie, Mehran; Hetherington, Jorden; Behringer, Peter A.; Kapur, Tina; Wells, William M.; Rohling, Robert; Fedorov, Andriy; Abolmaesumi, Purang

    2017-03-01

    Deep learning models have outperformed some of the previous state-of-the-art approaches in medical image analysis. Instead of using hand-engineered features, deep models attempt to automatically extract hierarchical representations at multiple levels of abstraction from the data. Therefore, deep models are usually considered to be more flexible and robust solutions for image analysis problems compared to conventional computer vision models. They have demonstrated significant improvements in computer-aided diagnosis and automatic medical image analysis applied to such tasks as image segmentation, classification and registration. However, deploying deep learning models often has a steep learning curve and requires detailed knowledge of various software packages. Thus, many deep models have not been integrated into the clinical research work ows causing a gap between the state-of-the-art machine learning in medical applications and evaluation in clinical research procedures. In this paper, we propose "DeepInfer" - an open-source toolkit for developing and deploying deep learning models within the 3D Slicer medical image analysis platform. Utilizing a repository of task-specific models, DeepInfer allows clinical researchers and biomedical engineers to deploy a trained model selected from the public registry, and apply it to new data without the need for software development or configuration. As two practical use cases, we demonstrate the application of DeepInfer in prostate segmentation for targeted MRI-guided biopsy and identification of the target plane in 3D ultrasound for spinal injections.

  5. Subsequent childbirth after a previous traumatic birth.

    Science.gov (United States)

    Beck, Cheryl Tatano; Watson, Sue

    2010-01-01

    Nine percent of new mothers in the United States who participated in the Listening to Mothers II Postpartum Survey screened positive for meeting the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition criteria for posttraumatic stress disorder after childbirth. Women who have had a traumatic birth experience report fewer subsequent children and a longer length of time before their second baby. Childbirth-related posttraumatic stress disorder impacts couples' physical relationship, communication, conflict, emotions, and bonding with their children. The purpose of this study was to describe the meaning of women's experiences of a subsequent childbirth after a previous traumatic birth. Phenomenology was the research design used. An international sample of 35 women participated in this Internet study. Women were asked, "Please describe in as much detail as you can remember your subsequent pregnancy, labor, and delivery following your previous traumatic birth." Colaizzi's phenomenological data analysis approach was used to analyze the stories of the 35 women. Data analysis yielded four themes: (a) riding the turbulent wave of panic during pregnancy; (b) strategizing: attempts to reclaim their body and complete the journey to motherhood; (c) bringing reverence to the birthing process and empowering women; and (d) still elusive: the longed-for healing birth experience. Subsequent childbirth after a previous birth trauma has the potential to either heal or retraumatize women. During pregnancy, women need permission and encouragement to grieve their prior traumatic births to help remove the burden of their invisible pain.

  6. Deep learning relevance

    DEFF Research Database (Denmark)

    Lioma, Christina; Larsen, Birger; Petersen, Casper

    2016-01-01

    train a Recurrent Neural Network (RNN) on existing relevant information to that query. We then use the RNN to "deep learn" a single, synthetic, and we assume, relevant document for that query. We design a crowdsourcing experiment to assess how relevant the "deep learned" document is, compared...... to existing relevant documents. Users are shown a query and four wordclouds (of three existing relevant documents and our deep learned synthetic document). The synthetic document is ranked on average most relevant of all....

  7. WFIRST: Science from Deep Field Surveys

    Science.gov (United States)

    Koekemoer, Anton; Foley, Ryan; WFIRST Deep Field Working Group

    2018-01-01

    WFIRST will enable deep field imaging across much larger areas than those previously obtained with Hubble, opening up completely new areas of parameter space for extragalactic deep fields including cosmology, supernova and galaxy evolution science. The instantaneous field of view of the Wide Field Instrument (WFI) is about 0.3 square degrees, which would for example yield an Ultra Deep Field (UDF) reaching similar depths at visible and near-infrared wavelengths to that obtained with Hubble, over an area about 100-200 times larger, for a comparable investment in time. Moreover, wider fields on scales of 10-20 square degrees could achieve depths comparable to large HST surveys at medium depths such as GOODS and CANDELS, and would enable multi-epoch supernova science that could be matched in area to LSST Deep Drilling fields or other large survey areas. Such fields may benefit from being placed on locations in the sky that have ancillary multi-band imaging or spectroscopy from other facilities, from the ground or in space. The WFIRST Deep Fields Working Group has been examining the science considerations for various types of deep fields that may be obtained with WFIRST, and present here a summary of the various properties of different locations in the sky that may be considered for future deep fields with WFIRST.

  8. S3 HMBC: Spin-State-Selective HMBC for accurate measurement of homonuclear coupling constants. Application to strychnine yielding thirteen hitherto unreported JHH

    DEFF Research Database (Denmark)

    Kjaerulff, Louise; Benie, Andrew J.; Hoeck, Casper

    2016-01-01

    A novel method, Spin-State-Selective (S3) HMBC, for accurate measurement of homonuclear coupling constants is introduced. As characteristic for S3 techniques, S3 HMBC yields independent subspectra corresponding to particular passive spin states and thus allows determination of coupling constants ...... are demonstrated by an application to strychnine where thirteen JHH coupling constants not previously reported could be measured....

  9. Books average previous decade of economic misery.

    Science.gov (United States)

    Bentley, R Alexander; Acerbi, Alberto; Ormerod, Paul; Lampos, Vasileios

    2014-01-01

    For the 20(th) century since the Depression, we find a strong correlation between a 'literary misery index' derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade.

  10. Books Average Previous Decade of Economic Misery

    Science.gov (United States)

    Bentley, R. Alexander; Acerbi, Alberto; Ormerod, Paul; Lampos, Vasileios

    2014-01-01

    For the 20th century since the Depression, we find a strong correlation between a ‘literary misery index’ derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade. PMID:24416159

  11. Deep Vein Thrombosis

    African Journals Online (AJOL)

    OWNER

    Deep Vein Thrombosis: Risk Factors and Prevention in Surgical Patients. Deep Vein ... preventable morbidity and mortality in hospitalized surgical patients. ... the elderly.3,4 It is very rare before the age ... depends on the risk level; therefore an .... but also in the post-operative period. ... is continuing uncertainty regarding.

  12. Deep Echo State Network (DeepESN): A Brief Survey

    OpenAIRE

    Gallicchio, Claudio; Micheli, Alessio

    2017-01-01

    The study of deep recurrent neural networks (RNNs) and, in particular, of deep Reservoir Computing (RC) is gaining an increasing research attention in the neural networks community. The recently introduced deep Echo State Network (deepESN) model opened the way to an extremely efficient approach for designing deep neural networks for temporal data. At the same time, the study of deepESNs allowed to shed light on the intrinsic properties of state dynamics developed by hierarchical compositions ...

  13. Underestimation of Severity of Previous Whiplash Injuries

    Science.gov (United States)

    Naqui, SZH; Lovell, SJ; Lovell, ME

    2008-01-01

    INTRODUCTION We noted a report that more significant symptoms may be expressed after second whiplash injuries by a suggested cumulative effect, including degeneration. We wondered if patients were underestimating the severity of their earlier injury. PATIENTS AND METHODS We studied recent medicolegal reports, to assess subjects with a second whiplash injury. They had been asked whether their earlier injury was worse, the same or lesser in severity. RESULTS From the study cohort, 101 patients (87%) felt that they had fully recovered from their first injury and 15 (13%) had not. Seventy-six subjects considered their first injury of lesser severity, 24 worse and 16 the same. Of the 24 that felt the violence of their first accident was worse, only 8 had worse symptoms, and 16 felt their symptoms were mainly the same or less than their symptoms from their second injury. Statistical analysis of the data revealed that the proportion of those claiming a difference who said the previous injury was lesser was 76% (95% CI 66–84%). The observed proportion with a lesser injury was considerably higher than the 50% anticipated. CONCLUSIONS We feel that subjects may underestimate the severity of an earlier injury and associated symptoms. Reasons for this may include secondary gain rather than any proposed cumulative effect. PMID:18201501

  14. [Electronic cigarettes - effects on health. Previous reports].

    Science.gov (United States)

    Napierała, Marta; Kulza, Maksymilian; Wachowiak, Anna; Jabłecka, Katarzyna; Florek, Ewa

    2014-01-01

    Currently very popular in the market of tobacco products have gained electronic cigarettes (ang. E-cigarettes). These products are considered to be potentially less harmful in compared to traditional tobacco products. However, current reports indicate that the statements of the producers regarding to the composition of the e- liquids not always are sufficient, and consumers often do not have reliable information on the quality of the product used by them. This paper contain a review of previous reports on the composition of e-cigarettes and their impact on health. Most of the observed health effects was related to symptoms of the respiratory tract, mouth, throat, neurological complications and sensory organs. Particularly hazardous effects of the e-cigarettes were: pneumonia, congestive heart failure, confusion, convulsions, hypotension, aspiration pneumonia, face second-degree burns, blindness, chest pain and rapid heartbeat. In the literature there is no information relating to passive exposure by the aerosols released during e-cigarette smoking. Furthermore, the information regarding to the use of these products in the long term are not also available.

  15. DeepWind - from Idea to 5 MW Concept

    DEFF Research Database (Denmark)

    Schmidt Paulsen, Uwe; Aagaard Madsen, Helge; Kragh, Knud Abildgaard

    2014-01-01

    The DeepWind concept has been described previously on challenges and potentials, this new offshore floating technology can offer to the wind industry [1]. The paper describes state of the art design improvements, new simulation results of the DeepWind floating vertical axis wind turbine concept...

  16. Deep learning in bioinformatics.

    Science.gov (United States)

    Min, Seonwoo; Lee, Byunghan; Yoon, Sungroh

    2017-09-01

    In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  17. Deep subsurface microbial processes

    Science.gov (United States)

    Lovley, D.R.; Chapelle, F.H.

    1995-01-01

    Information on the microbiology of the deep subsurface is necessary in order to understand the factors controlling the rate and extent of the microbially catalyzed redox reactions that influence the geophysical properties of these environments. Furthermore, there is an increasing threat that deep aquifers, an important drinking water resource, may be contaminated by man's activities, and there is a need to predict the extent to which microbial activity may remediate such contamination. Metabolically active microorganisms can be recovered from a diversity of deep subsurface environments. The available evidence suggests that these microorganisms are responsible for catalyzing the oxidation of organic matter coupled to a variety of electron acceptors just as microorganisms do in surface sediments, but at much slower rates. The technical difficulties in aseptically sampling deep subsurface sediments and the fact that microbial processes in laboratory incubations of deep subsurface material often do not mimic in situ processes frequently necessitate that microbial activity in the deep subsurface be inferred through nonmicrobiological analyses of ground water. These approaches include measurements of dissolved H2, which can predict the predominant microbially catalyzed redox reactions in aquifers, as well as geochemical and groundwater flow modeling, which can be used to estimate the rates of microbial processes. Microorganisms recovered from the deep subsurface have the potential to affect the fate of toxic organics and inorganic contaminants in groundwater. Microbial activity also greatly influences 1 the chemistry of many pristine groundwaters and contributes to such phenomena as porosity development in carbonate aquifers, accumulation of undesirably high concentrations of dissolved iron, and production of methane and hydrogen sulfide. Although the last decade has seen a dramatic increase in interest in deep subsurface microbiology, in comparison with the study of

  18. Training Deep Spiking Neural Networks Using Backpropagation.

    Science.gov (United States)

    Lee, Jun Haeng; Delbruck, Tobi; Pfeiffer, Michael

    2016-01-01

    Deep spiking neural networks (SNNs) hold the potential for improving the latency and energy efficiency of deep neural networks through data-driven event-based computation. However, training such networks is difficult due to the non-differentiable nature of spike events. In this paper, we introduce a novel technique, which treats the membrane potentials of spiking neurons as differentiable signals, where discontinuities at spike times are considered as noise. This enables an error backpropagation mechanism for deep SNNs that follows the same principles as in conventional deep networks, but works directly on spike signals and membrane potentials. Compared with previous methods relying on indirect training and conversion, our technique has the potential to capture the statistics of spikes more precisely. We evaluate the proposed framework on artificially generated events from the original MNIST handwritten digit benchmark, and also on the N-MNIST benchmark recorded with an event-based dynamic vision sensor, in which the proposed method reduces the error rate by a factor of more than three compared to the best previous SNN, and also achieves a higher accuracy than a conventional convolutional neural network (CNN) trained and tested on the same data. We demonstrate in the context of the MNIST task that thanks to their event-driven operation, deep SNNs (both fully connected and convolutional) trained with our method achieve accuracy equivalent with conventional neural networks. In the N-MNIST example, equivalent accuracy is achieved with about five times fewer computational operations.

  19. Deep Water Survey Data

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The deep water biodiversity surveys explore and describe the biodiversity of the bathy- and bentho-pelagic nekton using Midwater and bottom trawls centered in the...

  20. Deep Space Habitat Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Deep Space Habitat was closed out at the end of Fiscal Year 2013 (September 30, 2013). Results and select content have been incorporated into the new Exploration...

  1. Deep Learning in Neuroradiology.

    Science.gov (United States)

    Zaharchuk, G; Gong, E; Wintermark, M; Rubin, D; Langlotz, C P

    2018-02-01

    Deep learning is a form of machine learning using a convolutional neural network architecture that shows tremendous promise for imaging applications. It is increasingly being adapted from its original demonstration in computer vision applications to medical imaging. Because of the high volume and wealth of multimodal imaging information acquired in typical studies, neuroradiology is poised to be an early adopter of deep learning. Compelling deep learning research applications have been demonstrated, and their use is likely to grow rapidly. This review article describes the reasons, outlines the basic methods used to train and test deep learning models, and presents a brief overview of current and potential clinical applications with an emphasis on how they are likely to change future neuroradiology practice. Facility with these methods among neuroimaging researchers and clinicians will be important to channel and harness the vast potential of this new method. © 2018 by American Journal of Neuroradiology.

  2. Deep inelastic lepton scattering

    International Nuclear Information System (INIS)

    Nachtmann, O.

    1977-01-01

    Deep inelastic electron (muon) nucleon and neutrino nucleon scattering as well as electron positron annihilation into hadrons are reviewed from a theoretical point of view. The emphasis is placed on comparisons of quantum chromodynamics with the data. (orig.) [de

  3. Case report of deep vein thrombosis caused by artificial urinary sphincter reservoir compressing right external iliac vein

    Directory of Open Access Journals (Sweden)

    Marcus J Yip

    2015-01-01

    Full Text Available Artificial urinary sphincters (AUSs are commonly used after radical prostatectomy for those who are incontinent of urine. However, they are associated with complications, the most common being reservoir uprising or migration. We present a unique case of occlusive external iliac and femoral vein obstruction by the AUS reservoir causing thrombosis. Deflation of the reservoir and anticoagulation has, thus far, not been successful at decreasing thrombus burden. We present this case as a rare, but significant surgical complication; explore the risk factors that may have contributed, and other potential endovascular therapies to address this previously unreported AUS complication.

  4. Neuromorphic Deep Learning Machines

    OpenAIRE

    Neftci, E; Augustine, C; Paul, S; Detorakis, G

    2017-01-01

    An ongoing challenge in neuromorphic computing is to devise general and computationally efficient models of inference and learning which are compatible with the spatial and temporal constraints of the brain. One increasingly popular and successful approach is to take inspiration from inference and learning algorithms used in deep neural networks. However, the workhorse of deep learning, the gradient descent Back Propagation (BP) rule, often relies on the immediate availability of network-wide...

  5. Pathogenesis of deep endometriosis.

    Science.gov (United States)

    Gordts, Stephan; Koninckx, Philippe; Brosens, Ivo

    2017-12-01

    The pathophysiology of (deep) endometriosis is still unclear. As originally suggested by Cullen, change the definition "deeper than 5 mm" to "adenomyosis externa." With the discovery of the old European literature on uterine bleeding in 5%-10% of the neonates and histologic evidence that the bleeding represents decidual shedding, it is postulated/hypothesized that endometrial stem/progenitor cells, implanted in the pelvic cavity after birth, may be at the origin of adolescent and even the occasionally premenarcheal pelvic endometriosis. Endometriosis in the adolescent is characterized by angiogenic and hemorrhagic peritoneal and ovarian lesions. The development of deep endometriosis at a later age suggests that deep infiltrating endometriosis is a delayed stage of endometriosis. Another hypothesis is that the endometriotic cell has undergone genetic or epigenetic changes and those specific changes determine the development into deep endometriosis. This is compatible with the hereditary aspects, and with the clonality of deep and cystic ovarian endometriosis. It explains the predisposition and an eventual causal effect by dioxin or radiation. Specific genetic/epigenetic changes could explain the various expressions and thus typical, cystic, and deep endometriosis become three different diseases. Subtle lesions are not a disease until epi(genetic) changes occur. A classification should reflect that deep endometriosis is a specific disease. In conclusion the pathophysiology of deep endometriosis remains debated and the mechanisms of disease progression, as well as the role of genetics and epigenetics in the process, still needs to be unraveled. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  6. DeepPicker: A deep learning approach for fully automated particle picking in cryo-EM.

    Science.gov (United States)

    Wang, Feng; Gong, Huichao; Liu, Gaochao; Li, Meijing; Yan, Chuangye; Xia, Tian; Li, Xueming; Zeng, Jianyang

    2016-09-01

    Particle picking is a time-consuming step in single-particle analysis and often requires significant interventions from users, which has become a bottleneck for future automated electron cryo-microscopy (cryo-EM). Here we report a deep learning framework, called DeepPicker, to address this problem and fill the current gaps toward a fully automated cryo-EM pipeline. DeepPicker employs a novel cross-molecule training strategy to capture common features of particles from previously-analyzed micrographs, and thus does not require any human intervention during particle picking. Tests on the recently-published cryo-EM data of three complexes have demonstrated that our deep learning based scheme can successfully accomplish the human-level particle picking process and identify a sufficient number of particles that are comparable to those picked manually by human experts. These results indicate that DeepPicker can provide a practically useful tool to significantly reduce the time and manual effort spent in single-particle analysis and thus greatly facilitate high-resolution cryo-EM structure determination. DeepPicker is released as an open-source program, which can be downloaded from https://github.com/nejyeah/DeepPicker-python. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. Why & When Deep Learning Works: Looking Inside Deep Learnings

    OpenAIRE

    Ronen, Ronny

    2017-01-01

    The Intel Collaborative Research Institute for Computational Intelligence (ICRI-CI) has been heavily supporting Machine Learning and Deep Learning research from its foundation in 2012. We have asked six leading ICRI-CI Deep Learning researchers to address the challenge of "Why & When Deep Learning works", with the goal of looking inside Deep Learning, providing insights on how deep networks function, and uncovering key observations on their expressiveness, limitations, and potential. The outp...

  8. Deep learning in medical imaging: General overview

    Energy Technology Data Exchange (ETDEWEB)

    Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug [University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)

    2017-08-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

  9. Deep learning in medical imaging: General overview

    International Nuclear Information System (INIS)

    Lee, June Goo; Jun, Sang Hoon; Cho, Young Won; Lee, Hyun Na; KIm, Guk Bae; Seo, Joon Beom; Kim, Nam Kug

    2017-01-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and health care, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging

  10. Deep learning in jet reconstruction at CMS

    CERN Document Server

    Stoye, Markus

    2017-01-01

    Deep learning has led to several breakthroughs outside the field of high energy physics, yet in jet reconstruction for the CMS experiment at the CERN LHC it has not been used so far. This report shows results of applying deep learning strategies to jet reconstruction at the stage of identifying the original parton association of the jet (jet tagging), which is crucial for physics analyses at the LHC experiments. We introduce a custom deep neural network architecture for jet tagging. We compare the performance of this novel method with the other established approaches at CMS and show that the proposed strategy provides a significant improvement. The strategy provides the first multi-class classifier, instead of the few binary classifiers that previously were used, and thus yields more information and in a more convenient way. The performance results obtained with simulation imply a significant improvement for a large number of important physics analysis at the CMS experiment.

  11. Deep Learning in Medical Imaging: General Overview

    Science.gov (United States)

    Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae

    2017-01-01

    The artificial neural network (ANN)–a machine learning technique inspired by the human neuronal synapse system–was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging. PMID:28670152

  12. Deep Learning in Medical Imaging: General Overview.

    Science.gov (United States)

    Lee, June-Goo; Jun, Sanghoon; Cho, Young-Won; Lee, Hyunna; Kim, Guk Bae; Seo, Joon Beom; Kim, Namkug

    2017-01-01

    The artificial neural network (ANN)-a machine learning technique inspired by the human neuronal synapse system-was introduced in the 1950s. However, the ANN was previously limited in its ability to solve actual problems, due to the vanishing gradient and overfitting problems with training of deep architecture, lack of computing power, and primarily the absence of sufficient data to train the computer system. Interest in this concept has lately resurfaced, due to the availability of big data, enhanced computing power with the current graphics processing units, and novel algorithms to train the deep neural network. Recent studies on this technology suggest its potentially to perform better than humans in some visual and auditory recognition tasks, which may portend its applications in medicine and healthcare, especially in medical imaging, in the foreseeable future. This review article offers perspectives on the history, development, and applications of deep learning technology, particularly regarding its applications in medical imaging.

  13. Sacrococcygeal pilonidal disease: analysis of previously proposed risk factors

    Directory of Open Access Journals (Sweden)

    Ali Harlak

    2010-01-01

    Full Text Available PURPOSE: Sacrococcygeal pilonidal disease is a source of one of the most common surgical problems among young adults. While male gender, obesity, occupations requiring sitting, deep natal clefts, excessive body hair, poor body hygiene and excessive sweating are described as the main risk factors for this disease, most of these need to be verified with a clinical trial. The present study aimed to evaluate the value and effect of these factors on pilonidal disease. METHOD: Previously proposed main risk factors were evaluated in a prospective case control study that included 587 patients with pilonidal disease and 2,780 healthy control patients. RESULTS: Stiffness of body hair, number of baths and time spent seated per day were the three most predictive risk factors. Adjusted odds ratios were 9.23, 6.33 and 4.03, respectively (p<0.001. With an adjusted odds ratio of 1.3 (p<.001, body mass index was another risk factor. Family history was not statistically different between the groups and there was no specific occupation associated with the disease. CONCLUSIONS: Hairy people who sit down for more than six hours a day and those who take a bath two or less times per week are at a 219-fold increased risk for sacrococcygeal pilonidal disease than those without these risk factors. For people with a great deal of hair, there is a greater need for them to clean their intergluteal sulcus. People who engage in work that requires sitting in a seat for long periods of time should choose more comfortable seats and should also try to stand whenever possible.

  14. Auxiliary Deep Generative Models

    DEFF Research Database (Denmark)

    Maaløe, Lars; Sønderby, Casper Kaae; Sønderby, Søren Kaae

    2016-01-01

    Deep generative models parameterized by neural networks have recently achieved state-of-the-art performance in unsupervised and semi-supervised learning. We extend deep generative models with auxiliary variables which improves the variational approximation. The auxiliary variables leave...... the generative model unchanged but make the variational distribution more expressive. Inspired by the structure of the auxiliary variable we also propose a model with two stochastic layers and skip connections. Our findings suggest that more expressive and properly specified deep generative models converge...... faster with better results. We show state-of-the-art performance within semi-supervised learning on MNIST (0.96%), SVHN (16.61%) and NORB (9.40%) datasets....

  15. Deep Learning from Crowds

    DEFF Research Database (Denmark)

    Rodrigues, Filipe; Pereira, Francisco Camara

    Over the last few years, deep learning has revolutionized the field of machine learning by dramatically improving the stateof-the-art in various domains. However, as the size of supervised artificial neural networks grows, typically so does the need for larger labeled datasets. Recently...... networks from crowds. We begin by describing an EM algorithm for jointly learning the parameters of the network and the reliabilities of the annotators. Then, a novel general-purpose crowd layer is proposed, which allows us to train deep neural networks end-to-end, directly from the noisy labels......, crowdsourcing has established itself as an efficient and cost-effective solution for labeling large sets of data in a scalable manner, but it often requires aggregating labels from multiple noisy contributors with different levels of expertise. In this paper, we address the problem of learning deep neural...

  16. Deep boreholes; Tiefe Bohrloecher

    Energy Technology Data Exchange (ETDEWEB)

    Bracke, Guido [Gesellschaft fuer Anlagen- und Reaktorsicherheit gGmbH Koeln (Germany); Charlier, Frank [NSE international nuclear safety engineering gmbh, Aachen (Germany); Geckeis, Horst [Karlsruher Institut fuer Technologie (Germany). Inst. fuer Nukleare Entsorgung; and others

    2016-02-15

    The report on deep boreholes covers the following subject areas: methods for safe enclosure of radioactive wastes, requirements concerning the geological conditions of possible boreholes, reversibility of decisions and retrievability, status of drilling technology. The introduction covers national and international activities. Further chapters deal with the following issues: basic concept of the storage in deep bore holes, status of the drilling technology, safe enclosure, geomechanics and stability, reversibility of decisions, risk scenarios, compliancy with safe4ty requirements and site selection criteria, research and development demand.

  17. Deep Water Acoustics

    Science.gov (United States)

    2016-06-28

    the Deep Water project and participate in the NPAL Workshops, including Art Baggeroer (MIT), J. Beron- Vera (UMiami), M. Brown (UMiami), T...Kathleen E . Wage. The North Pacific Acoustic Laboratory deep-water acoustic propagation experiments in the Philippine Sea. J. Acoust. Soc. Am., 134(4...estimate of the angle α during PhilSea09, made from ADCP measurements at the site of the DVLA. Sim. A B1 B2 B3 C D E F Prof. # 0 4 4 4 5 10 16 20 α

  18. Constructing Long Short-Term Memory based Deep Recurrent Neural Networks for Large Vocabulary Speech Recognition

    OpenAIRE

    Li, Xiangang; Wu, Xihong

    2014-01-01

    Long short-term memory (LSTM) based acoustic modeling methods have recently been shown to give state-of-the-art performance on some speech recognition tasks. To achieve a further performance improvement, in this research, deep extensions on LSTM are investigated considering that deep hierarchical model has turned out to be more efficient than a shallow one. Motivated by previous research on constructing deep recurrent neural networks (RNNs), alternative deep LSTM architectures are proposed an...

  19. Deep diode atomic battery

    International Nuclear Information System (INIS)

    Anthony, T.R.; Cline, H.E.

    1977-01-01

    A deep diode atomic battery is made from a bulk semiconductor crystal containing three-dimensional arrays of columnar and lamellar P-N junctions. The battery is powered by gamma rays and x-ray emission from a radioactive source embedded in the interior of the semiconductor crystal

  20. Deep Learning Policy Quantization

    NARCIS (Netherlands)

    van de Wolfshaar, Jos; Wiering, Marco; Schomaker, Lambertus

    2018-01-01

    We introduce a novel type of actor-critic approach for deep reinforcement learning which is based on learning vector quantization. We replace the softmax operator of the policy with a more general and more flexible operator that is similar to the robust soft learning vector quantization algorithm.

  1. Deep-sea fungi

    Digital Repository Service at National Institute of Oceanography (India)

    Raghukumar, C; Damare, S.R.

    significant in terms of carbon sequestration (5, 8). In light of this, the diversity, abundance, and role of fungi in deep-sea sediments may form an important link in the global C biogeochemistry. This review focuses on issues related to collection...

  2. Deep inelastic scattering

    International Nuclear Information System (INIS)

    Aubert, J.J.

    1982-01-01

    Deep inelastic lepton-nucleon interaction experiments are renewed. Singlet and non-singlet structure functions are measured and the consistency of the different results is checked. A detailed analysis of the scaling violation is performed in terms of the quantum chromodynamics predictions [fr

  3. Deep Vein Thrombosis

    Centers for Disease Control (CDC) Podcasts

    2012-04-05

    This podcast discusses the risk for deep vein thrombosis in long-distance travelers and ways to minimize that risk.  Created: 4/5/2012 by National Center for Emerging and Zoonotic Infectious Diseases (NCEZID).   Date Released: 4/5/2012.

  4. Deep Learning Microscopy

    KAUST Repository

    Rivenson, Yair; Gorocs, Zoltan; Gunaydin, Harun; Zhang, Yibo; Wang, Hongda; Ozcan, Aydogan

    2017-01-01

    regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably

  5. The deep universe

    CERN Document Server

    Sandage, AR; Longair, MS

    1995-01-01

    Discusses the concept of the deep universe from two conflicting theoretical viewpoints: firstly as a theory embracing the evolution of the universe from the Big Bang to the present; and secondly through observations gleaned over the years on stars, galaxies and clusters.

  6. Teaching for Deep Learning

    Science.gov (United States)

    Smith, Tracy Wilson; Colby, Susan A.

    2007-01-01

    The authors have been engaged in research focused on students' depth of learning as well as teachers' efforts to foster deep learning. Findings from a study examining the teaching practices and student learning outcomes of sixty-four teachers in seventeen different states (Smith et al. 2005) indicated that most of the learning in these classrooms…

  7. Deep Trawl Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Otter trawl (36' Yankee and 4-seam net deepwater gear) catches from mid-Atlantic slope and canyons at 200 - 800 m depth. Deep-sea (200-800 m depth) flat otter trawls...

  8. [Deep vein thrombosis prophylaxis.

    Science.gov (United States)

    Sandoval-Chagoya, Gloria Alejandra; Laniado-Laborín, Rafael

    2013-01-01

    Background: despite the proven effectiveness of preventive therapy for deep vein thrombosis, a significant proportion of patients at risk for thromboembolism do not receive prophylaxis during hospitalization. Our objective was to determine the adherence to thrombosis prophylaxis guidelines in a general hospital as a quality control strategy. Methods: a random audit of clinical charts was conducted at the Tijuana General Hospital, Baja California, Mexico, to determine the degree of adherence to deep vein thrombosis prophylaxis guidelines. The instrument used was the Caprini's checklist for thrombosis risk assessment in adult patients. Results: the sample included 300 patient charts; 182 (60.7 %) were surgical patients and 118 were medical patients. Forty six patients (15.3 %) received deep vein thrombosis pharmacologic prophylaxis; 27.1 % of medical patients received deep vein thrombosis prophylaxis versus 8.3 % of surgical patients (p < 0.0001). Conclusions: our results show that adherence to DVT prophylaxis at our hospital is extremely low. Only 15.3 % of our patients at risk received treatment, and even patients with very high risk received treatment in less than 25 % of the cases. We have implemented strategies to increase compliance with clinical guidelines.

  9. More Far-Side Deep Moonquake Nests Discovered

    Science.gov (United States)

    Nakamura, Y.; Jackson, John A.; Jackson, Katherine G.

    2004-01-01

    As reported last year, we started to reanalyze the seismic data acquired from 1969 to 1977 with a network of stations established on the Moon during the Apollo mission. The reason for the reanalysis was because recent advances in computer technology make it possible to employ much more sophisticated analysis techniques than was possible previously. The primary objective of the reanalysis was to search for deep moonquakes on the far side of the Moon and, if found, to use them to infer the structure of the Moon's deep interior, including a possible central core. The first step was to identify any new deep moonquakes that escaped our earlier search by applying a combination of waveform cross-correlation and single-link cluster analysis, and then to see if any of them are from previously unknown nests of deep moonquakes. We positively identified 7245 deep moonquakes, more than a five-fold increase from the previous 1360. We also found at least 88 previously unknown deep-moonquake nests. The question was whether any of these newly discovered nets were on the far side of the Moon, and we now report that our analysis of the data indicates that some of them are indeed on the far side.

  10. Dual pathology—An unreported case

    Science.gov (United States)

    Yap, Darren; Rasheed, Ashraf; Rashid, Majid

    2015-01-01

    Introduction Symptomatic biliary disease in children and young adults requiring surgical intervention are uncommon. However even rarer is the occurrence of a spontaneous gallbladder necrosis in a child. We report a case of spontaneous necrosis in a child with no apparent causative factors. Case Fit and well 16 year-old boy presented with acute generalized lower abdominal pain. Examination revealed mild epigastric pain with rebound tenderness and guarding of the right iliac fossa. Diagnostic laparoscopy showed a necrotic gallbladder and incidental finding of a Meckel’s diverticulum. He had a cholecystectomy and Meckel’s diverticulum resection. Patient recovered uneventfully and was discharged home. He was reviewed 2 months later and recovered well with no evidence of any post-operative complication. He was discharged without any further follow up. Discussion Gall bladder necrosis is a rare cause of an acute abdomen. We present the first reported case of a spontaneous gallbladder necrosis with no apparent cause. Literature review showed various causes of gall bladder necrosis including trauma, acalculous cholecystitis, gallbladder torsion, gangrenous cholecystitis and etc. Conclusion We report a case of spontaneous gallbladder necrosis in a young healthy male with no family history of thrombotic disorders or any history of sepsis, intervention, trauma and no obvious underlying anatomical or histological abnormalities. This is an exceedingly rare pathology and one would be forgiven for not including it on the list of a differential diagnosis in such circumstance. However it is important to send tissue sample to exclude any underlying histological aetiological factors. PMID:26657530

  11. Dual pathology-An unreported case.

    Science.gov (United States)

    Yap, Darren; Rasheed, Ashraf; Rashid, Majid

    2015-01-01

    Symptomatic biliary disease in children and young adults requiring surgical intervention are uncommon. However even rarer is the occurrence of a spontaneous gallbladder necrosis in a child. We report a case of spontaneous necrosis in a child with no apparent causative factors. Fit and well 16 year-old boy presented with acute generalized lower abdominal pain. Examination revealed mild epigastric pain with rebound tenderness and guarding of the right iliac fossa. Diagnostic laparoscopy showed a necrotic gallbladder and incidental finding of a Meckel's diverticulum. He had a cholecystectomy and Meckel's diverticulum resection. Patient recovered uneventfully and was discharged home. He was reviewed 2 months later and recovered well with no evidence of any post-operative complication. He was discharged without any further follow up. Gall bladder necrosis is a rare cause of an acute abdomen. We present the first reported case of a spontaneous gallbladder necrosis with no apparent cause. Literature review showed various causes of gall bladder necrosis including trauma, acalculous cholecystitis, gallbladder torsion, gangrenous cholecystitis and etc. We report a case of spontaneous gallbladder necrosis in a young healthy male with no family history of thrombotic disorders or any history of sepsis, intervention, trauma and no obvious underlying anatomical or histological abnormalities. This is an exceedingly rare pathology and one would be forgiven for not including it on the list of a differential diagnosis in such circumstance. However it is important to send tissue sample to exclude any underlying histological aetiological factors. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

  12. Deep Learning for Computer Vision: A Brief Review

    Science.gov (United States)

    Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

    2018-01-01

    Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein. PMID:29487619

  13. Deep Learning for Computer Vision: A Brief Review

    Directory of Open Access Journals (Sweden)

    Athanasios Voulodimos

    2018-01-01

    Full Text Available Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

  14. Deep Learning for Computer Vision: A Brief Review.

    Science.gov (United States)

    Voulodimos, Athanasios; Doulamis, Nikolaos; Doulamis, Anastasios; Protopapadakis, Eftychios

    2018-01-01

    Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep learning schemes used in computer vision problems, that is, Convolutional Neural Networks, Deep Boltzmann Machines and Deep Belief Networks, and Stacked Denoising Autoencoders. A brief account of their history, structure, advantages, and limitations is given, followed by a description of their applications in various computer vision tasks, such as object detection, face recognition, action and activity recognition, and human pose estimation. Finally, a brief overview is given of future directions in designing deep learning schemes for computer vision problems and the challenges involved therein.

  15. A deep learning method for lincRNA detection using auto-encoder algorithm.

    Science.gov (United States)

    Yu, Ning; Yu, Zeng; Pan, Yi

    2017-12-06

    RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly

  16. Deep inelastic scattering

    International Nuclear Information System (INIS)

    Zakharov, V.I.

    1977-01-01

    The present status of the quark-parton-gluon picture of deep inelastic scattering is reviewed. The general framework is mostly theoretical and covers investigations since 1970. Predictions of the parton model and of the asymptotically free field theories are compared with experimental data available. The valence quark approximation is concluded to be valid in most cases, but fails to account for the data on the total momentum transfer. On the basis of gluon corrections introduced to the parton model certain predictions concerning both the deep inelastic structure functions and form factors are made. The contributions of gluon exchanges and gluon bremsstrahlung are highlighted. Asymptotic freedom is concluded to be very attractive and provide qualitative explanation to some experimental observations (scaling violations, breaking of the Drell-Yan-West type relations). Lepton-nuclear scattering is pointed out to be helpful in probing the nature of nuclear forces and studying the space-time picture of the parton model

  17. Deep Energy Retrofit

    DEFF Research Database (Denmark)

    Zhivov, Alexander; Lohse, Rüdiger; Rose, Jørgen

    Deep Energy Retrofit – A Guide to Achieving Significant Energy User Reduction with Major Renovation Projects contains recommendations for characteristics of some of core technologies and measures that are based on studies conducted by national teams associated with the International Energy Agency...... Energy Conservation in Buildings and Communities Program (IEA-EBC) Annex 61 (Lohse et al. 2016, Case, et al. 2016, Rose et al. 2016, Yao, et al. 2016, Dake 2014, Stankevica et al. 2016, Kiatreungwattana 2014). Results of these studies provided a base for setting minimum requirements to the building...... envelope-related technologies to make Deep Energy Retrofit feasible and, in many situations, cost effective. Use of energy efficiency measures (EEMs) in addition to core technologies bundle and high-efficiency appliances will foster further energy use reduction. This Guide also provides best practice...

  18. Deep groundwater chemistry

    International Nuclear Information System (INIS)

    Wikberg, P.; Axelsen, K.; Fredlund, F.

    1987-06-01

    Starting in 1977 and up till now a number of places in Sweden have been investigated in order to collect the necessary geological, hydrogeological and chemical data needed for safety analyses of repositories in deep bedrock systems. Only crystalline rock is considered and in many cases this has been gneisses of sedimentary origin but granites and gabbros are also represented. Core drilled holes have been made at nine sites. Up to 15 holes may be core drilled at one site, the deepest down to 1000 m. In addition to this a number of boreholes are percussion drilled at each site to depths of about 100 m. When possible drilling water is taken from percussion drilled holes. The first objective is to survey the hydraulic conditions. Core drilled boreholes and sections selected for sampling of deep groundwater are summarized. (orig./HP)

  19. Deep Reinforcement Fuzzing

    OpenAIRE

    Böttinger, Konstantin; Godefroid, Patrice; Singh, Rishabh

    2018-01-01

    Fuzzing is the process of finding security vulnerabilities in input-processing code by repeatedly testing the code with modified inputs. In this paper, we formalize fuzzing as a reinforcement learning problem using the concept of Markov decision processes. This in turn allows us to apply state-of-the-art deep Q-learning algorithms that optimize rewards, which we define from runtime properties of the program under test. By observing the rewards caused by mutating with a specific set of actions...

  20. Cultivating the Deep Subsurface Microbiome

    Science.gov (United States)

    Casar, C. P.; Osburn, M. R.; Flynn, T. M.; Masterson, A.; Kruger, B.

    2017-12-01

    Subterranean ecosystems are poorly understood because many microbes detected in metagenomic surveys are only distantly related to characterized isolates. Cultivating microorganisms from the deep subsurface is challenging due to its inaccessibility and potential for contamination. The Deep Mine Microbial Observatory (DeMMO) in Lead, SD however, offers access to deep microbial life via pristine fracture fluids in bedrock to a depth of 1478 m. The metabolic landscape of DeMMO was previously characterized via thermodynamic modeling coupled with genomic data, illustrating the potential for microbial inhabitants of DeMMO to utilize mineral substrates as energy sources. Here, we employ field and lab based cultivation approaches with pure minerals to link phylogeny to metabolism at DeMMO. Fracture fluids were directed through reactors filled with Fe3O4, Fe2O3, FeS2, MnO2, and FeCO3 at two sites (610 m and 1478 m) for 2 months prior to harvesting for subsequent analyses. We examined mineralogical, geochemical, and microbiological composition of the reactors via DNA sequencing, microscopy, lipid biomarker characterization, and bulk C and N isotope ratios to determine the influence of mineralogy on biofilm community development. Pre-characterized mineral chips were imaged via SEM to assay microbial growth; preliminary results suggest MnO2, Fe3O4, and Fe2O3 were most conducive to colonization. Solid materials from reactors were used as inoculum for batch cultivation experiments. Media designed to mimic fracture fluid chemistry was supplemented with mineral substrates targeting metal reducers. DNA sequences and microscopy of iron oxide-rich biofilms and fracture fluids suggest iron oxidation is a major energy source at redox transition zones where anaerobic fluids meet more oxidizing conditions. We utilized these biofilms and fluids as inoculum in gradient cultivation experiments targeting microaerophilic iron oxidizers. Cultivation of microbes endemic to DeMMO, a system

  1. Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks.

    Science.gov (United States)

    Burt, Jeremy R; Torosdagli, Neslisah; Khosravan, Naji; RaviPrakash, Harish; Mortazi, Aliasghar; Tissavirasingham, Fiona; Hussein, Sarfaraz; Bagci, Ulas

    2018-04-10

    Deep learning has demonstrated tremendous revolutionary changes in the computing industry and its effects in radiology and imaging sciences have begun to dramatically change screening paradigms. Specifically, these advances have influenced the development of computer-aided detection and diagnosis (CAD) systems. These technologies have long been thought of as "second-opinion" tools for radiologists and clinicians. However, with significant improvements in deep neural networks, the diagnostic capabilities of learning algorithms are approaching levels of human expertise (radiologists, clinicians etc.), shifting the CAD paradigm from a "second opinion" tool to a more collaborative utility. This paper reviews recently developed CAD systems based on deep learning technologies for breast cancer diagnosis, explains their superiorities with respect to previously established systems, defines the methodologies behind the improved achievements including algorithmic developments, and describes remaining challenges in breast cancer screening and diagnosis. We also discuss possible future directions for new CAD models that continue to change as artificial intelligence algorithms evolve.

  2. Deep inelastic scattering near the Coulomb barrier

    International Nuclear Information System (INIS)

    Gehring, J.; Back, B.; Chan, K.

    1995-01-01

    Deep inelastic scattering was recently observed in heavy ion reactions at incident energies near and below the Coulomb barrier. Traditional models of this process are based on frictional forces and are designed to predict the features of deep inelastic processes at energies above the barrier. They cannot be applied at energies below the barrier where the nuclear overlap is small and friction is negligible. The presence of deep inelastic scattering at these energies requires a different explanation. The first observation of deep inelastic scattering near the barrier was in the systems 124,112 Sn + 58,64 Ni by Wolfs et al. We previously extended these measurements to the system 136 Xe + 64 Ni and currently measured the system 124 Xe + 58 Ni. We obtained better statistics, better mass and energy resolution, and more complete angular coverage in the Xe + Ni measurements. The cross sections and angular distributions are similar in all of the Sn + Ni and Xe + Ni systems. The data are currently being analyzed and compared with new theoretical calculations. They will be part of the thesis of J. Gehring

  3. Deep inelastic scattering near the Coulomb barrier

    Energy Technology Data Exchange (ETDEWEB)

    Gehring, J.; Back, B.; Chan, K. [and others

    1995-08-01

    Deep inelastic scattering was recently observed in heavy ion reactions at incident energies near and below the Coulomb barrier. Traditional models of this process are based on frictional forces and are designed to predict the features of deep inelastic processes at energies above the barrier. They cannot be applied at energies below the barrier where the nuclear overlap is small and friction is negligible. The presence of deep inelastic scattering at these energies requires a different explanation. The first observation of deep inelastic scattering near the barrier was in the systems {sup 124,112}Sn + {sup 58,64}Ni by Wolfs et al. We previously extended these measurements to the system {sup 136}Xe + {sup 64}Ni and currently measured the system {sup 124}Xe + {sup 58}Ni. We obtained better statistics, better mass and energy resolution, and more complete angular coverage in the Xe + Ni measurements. The cross sections and angular distributions are similar in all of the Sn + Ni and Xe + Ni systems. The data are currently being analyzed and compared with new theoretical calculations. They will be part of the thesis of J. Gehring.

  4. Deep Red (Profondo Rosso)

    CERN Multimedia

    Cine Club

    2015-01-01

    Wednesday 29 April 2015 at 20:00 CERN Council Chamber    Deep Red (Profondo Rosso) Directed by Dario Argento (Italy, 1975) 126 minutes A psychic who can read minds picks up the thoughts of a murderer in the audience and soon becomes a victim. An English pianist gets involved in solving the murders, but finds many of his avenues of inquiry cut off by new murders, and he begins to wonder how the murderer can track his movements so closely. Original version Italian; English subtitles

  5. Reversible deep disposal

    International Nuclear Information System (INIS)

    2009-10-01

    This presentation, given by the national agency of radioactive waste management (ANDRA) at the meeting of October 8, 2009 of the high committee for the nuclear safety transparency and information (HCTISN), describes the concept of deep reversible disposal for high level/long living radioactive wastes, as considered by the ANDRA in the framework of the program law of June 28, 2006 about the sustainable management of radioactive materials and wastes. The document presents the social and political reasons of reversibility, the technical means considered (containers, disposal cavities, monitoring system, test facilities and industrial prototypes), the decisional process (progressive development and blocked off of the facility, public information and debate). (J.S.)

  6. Deep inelastic neutron scattering

    International Nuclear Information System (INIS)

    Mayers, J.

    1989-03-01

    The report is based on an invited talk given at a conference on ''Neutron Scattering at ISIS: Recent Highlights in Condensed Matter Research'', which was held in Rome, 1988, and is intended as an introduction to the techniques of Deep Inelastic Neutron Scattering. The subject is discussed under the following topic headings:- the impulse approximation I.A., scaling behaviour, kinematical consequences of energy and momentum conservation, examples of measurements, derivation of the I.A., the I.A. in a harmonic system, and validity of the I.A. in neutron scattering. (U.K.)

  7. [Deep mycoses rarely described].

    Science.gov (United States)

    Charles, D

    1986-01-01

    Beside deep mycoses very well known: histoplasmosis, candidosis, cryptococcosis, there are other mycoses less frequently described. Some of them are endemic in some countries: South American blastomycosis in Brazil, coccidioidomycosis in California; some others are cosmopolitan and may affect everyone: sporotrichosis, or may affect only immunodeficient persons: mucormycosis. They do not spare Africa, we may encounter basidiobolomycosis, rhinophycomycosis, dermatophytosis, sporotrichosis and, more recently reported, rhinosporidiosis. Important therapeutic progresses have been accomplished with amphotericin B and with antifungus imidazole compounds (miconazole and ketoconazole). Surgical intervention is sometime recommended in chromomycosis and rhinosporidiosis.

  8. Deep penetration calculations

    International Nuclear Information System (INIS)

    Thompson, W.L.; Deutsch, O.L.; Booth, T.E.

    1980-04-01

    Several Monte Carlo techniques are compared in the transport of neutrons of different source energies through two different deep-penetration problems each with two parts. The first problem involves transmission through a 200-cm concrete slab. The second problem is a 90 0 bent pipe jacketed by concrete. In one case the pipe is void, and in the other it is filled with liquid sodium. Calculations are made with two different Los Alamos Monte Carlo codes: the continuous-energy code MCNP and the multigroup code MCMG

  9. Deep Super Learner: A Deep Ensemble for Classification Problems

    OpenAIRE

    Young, Steven; Abdou, Tamer; Bener, Ayse

    2018-01-01

    Deep learning has become very popular for tasks such as predictive modeling and pattern recognition in handling big data. Deep learning is a powerful machine learning method that extracts lower level features and feeds them forward for the next layer to identify higher level features that improve performance. However, deep neural networks have drawbacks, which include many hyper-parameters and infinite architectures, opaqueness into results, and relatively slower convergence on smaller datase...

  10. Randomized Clinical Trials on Deep Carious Lesions

    DEFF Research Database (Denmark)

    Bjørndal, Lars; Fransson, Helena; Bruun, Gitte

    2017-01-01

    nonselective carious removal to hard dentin with or without pulp exposure. The aim of this article was to report the 5-y outcome on these previously treated patients having radiographically well-defined carious lesions extending into the pulpal quarter of the dentin but with a well-defined radiodense zone...... pulp exposures per se were included as failures. Pulp exposure rate was significantly lower in the stepwise carious removal group (21.2% vs. 35.5%; P = 0.014). Irrespective of pulp exposure status, the difference (13.3%) was still significant when sustained pulp vitality without apical radiolucency......) in deep carious lesions in adults. In conclusion, the stepwise carious removal group had a significantly higher proportion of pulps with sustained vitality without apical radiolucency versus nonselective carious removal of deep carious lesions in adult teeth at 5-y follow-up (ClinicalTrials.gov NCT...

  11. DAPs: Deep Action Proposals for Action Understanding

    KAUST Repository

    Escorcia, Victor

    2016-09-17

    Object proposals have contributed significantly to recent advances in object understanding in images. Inspired by the success of this approach, we introduce Deep Action Proposals (DAPs), an effective and efficient algorithm for generating temporal action proposals from long videos. We show how to take advantage of the vast capacity of deep learning models and memory cells to retrieve from untrimmed videos temporal segments, which are likely to contain actions. A comprehensive evaluation indicates that our approach outperforms previous work on a large scale action benchmark, runs at 134 FPS making it practical for large-scale scenarios, and exhibits an appealing ability to generalize, i.e. to retrieve good quality temporal proposals of actions unseen in training.

  12. Deep sea biophysics

    International Nuclear Information System (INIS)

    Yayanos, A.A.

    1982-01-01

    A collection of deep-sea bacterial cultures was completed. Procedures were instituted to shelter the culture collection from accidential warming. A substantial data base on the rates of reproduction of more than 100 strains of bacteria from that collection was obtained from experiments and the analysis of that data was begun. The data on the rates of reproduction were obtained under conditions of temperature and pressure found in the deep sea. The experiments were facilitated by inexpensively fabricated pressure vessels, by the streamlining of the methods for the study of kinetics at high pressures, and by computer-assisted methods. A polybarothermostat was used to study the growth of bacteria along temperature gradients at eight distinct pressures. This device should allow for the study of microbial processes in the temperature field simulating the environment around buried HLW. It is small enough to allow placement in a radiation field in future studies. A flow fluorocytometer was fabricated. This device will be used to determine the DNA content per cell in bacteria grown in laboratory culture and in microorganisms in samples from the ocean. The technique will be tested for its rapidity in determining the concentration of cells (standing stock of microorganisms) in samples from the ocean

  13. Deep Learning in Radiology.

    Science.gov (United States)

    McBee, Morgan P; Awan, Omer A; Colucci, Andrew T; Ghobadi, Comeron W; Kadom, Nadja; Kansagra, Akash P; Tridandapani, Srini; Auffermann, William F

    2018-03-29

    As radiology is inherently a data-driven specialty, it is especially conducive to utilizing data processing techniques. One such technique, deep learning (DL), has become a remarkably powerful tool for image processing in recent years. In this work, the Association of University Radiologists Radiology Research Alliance Task Force on Deep Learning provides an overview of DL for the radiologist. This article aims to present an overview of DL in a manner that is understandable to radiologists; to examine past, present, and future applications; as well as to evaluate how radiologists may benefit from this remarkable new tool. We describe several areas within radiology in which DL techniques are having the most significant impact: lesion or disease detection, classification, quantification, and segmentation. The legal and ethical hurdles to implementation are also discussed. By taking advantage of this powerful tool, radiologists can become increasingly more accurate in their interpretations with fewer errors and spend more time to focus on patient care. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

  14. Deep Learning Microscopy

    KAUST Repository

    Rivenson, Yair

    2017-05-12

    We demonstrate that a deep neural network can significantly improve optical microscopy, enhancing its spatial resolution over a large field-of-view and depth-of-field. After its training, the only input to this network is an image acquired using a regular optical microscope, without any changes to its design. We blindly tested this deep learning approach using various tissue samples that are imaged with low-resolution and wide-field systems, where the network rapidly outputs an image with remarkably better resolution, matching the performance of higher numerical aperture lenses, also significantly surpassing their limited field-of-view and depth-of-field. These results are transformative for various fields that use microscopy tools, including e.g., life sciences, where optical microscopy is considered as one of the most widely used and deployed techniques. Beyond such applications, our presented approach is broadly applicable to other imaging modalities, also spanning different parts of the electromagnetic spectrum, and can be used to design computational imagers that get better and better as they continue to image specimen and establish new transformations among different modes of imaging.

  15. Deep Transfer Metric Learning.

    Science.gov (United States)

    Junlin Hu; Jiwen Lu; Yap-Peng Tan; Jie Zhou

    2016-12-01

    Conventional metric learning methods usually assume that the training and test samples are captured in similar scenarios so that their distributions are assumed to be the same. This assumption does not hold in many real visual recognition applications, especially when samples are captured across different data sets. In this paper, we propose a new deep transfer metric learning (DTML) method to learn a set of hierarchical nonlinear transformations for cross-domain visual recognition by transferring discriminative knowledge from the labeled source domain to the unlabeled target domain. Specifically, our DTML learns a deep metric network by maximizing the inter-class variations and minimizing the intra-class variations, and minimizing the distribution divergence between the source domain and the target domain at the top layer of the network. To better exploit the discriminative information from the source domain, we further develop a deeply supervised transfer metric learning (DSTML) method by including an additional objective on DTML, where the output of both the hidden layers and the top layer are optimized jointly. To preserve the local manifold of input data points in the metric space, we present two new methods, DTML with autoencoder regularization and DSTML with autoencoder regularization. Experimental results on face verification, person re-identification, and handwritten digit recognition validate the effectiveness of the proposed methods.

  16. Impact of previously disadvantaged land-users on sustainable ...

    African Journals Online (AJOL)

    Impact of previously disadvantaged land-users on sustainable agricultural ... about previously disadvantaged land users involved in communal farming systems ... of input, capital, marketing, information and land use planning, with effect on ...

  17. 22 CFR 40.91 - Certain aliens previously removed.

    Science.gov (United States)

    2010-04-01

    ... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Certain aliens previously removed. 40.91... IMMIGRANTS UNDER THE IMMIGRATION AND NATIONALITY ACT, AS AMENDED Aliens Previously Removed § 40.91 Certain aliens previously removed. (a) 5-year bar. An alien who has been found inadmissible, whether as a result...

  18. Deep Reinforcement Learning: An Overview

    OpenAIRE

    Li, Yuxi

    2017-01-01

    We give an overview of recent exciting achievements of deep reinforcement learning (RL). We discuss six core elements, six important mechanisms, and twelve applications. We start with background of machine learning, deep learning and reinforcement learning. Next we discuss core RL elements, including value function, in particular, Deep Q-Network (DQN), policy, reward, model, planning, and exploration. After that, we discuss important mechanisms for RL, including attention and memory, unsuperv...

  19. Deep Feature Consistent Variational Autoencoder

    OpenAIRE

    Hou, Xianxu; Shen, Linlin; Sun, Ke; Qiu, Guoping

    2016-01-01

    We present a novel method for constructing Variational Autoencoder (VAE). Instead of using pixel-by-pixel loss, we enforce deep feature consistency between the input and the output of a VAE, which ensures the VAE's output to preserve the spatial correlation characteristics of the input, thus leading the output to have a more natural visual appearance and better perceptual quality. Based on recent deep learning works such as style transfer, we employ a pre-trained deep convolutional neural net...

  20. Deep learning for image classification

    Science.gov (United States)

    McCoppin, Ryan; Rizki, Mateen

    2014-06-01

    This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.

  1. Determining root correspondence between previously and newly detected objects

    Science.gov (United States)

    Paglieroni, David W.; Beer, N Reginald

    2014-06-17

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  2. Deep learning? What deep learning? | Fourie | South African ...

    African Journals Online (AJOL)

    In teaching generally over the past twenty years, there has been a move towards teaching methods that encourage deep, rather than surface approaches to learning. The reason for this being that students, who adopt a deep approach to learning are considered to have learning outcomes of a better quality and desirability ...

  3. Angiographic findings of collateral vessels in cervicofacial vascular lesions with previously ligated carotid artery

    International Nuclear Information System (INIS)

    Na, Dong Gyu; Han, Moon Hee; Chang, Kee Hyun; Han, Gi Seok; Yeon, Kung Mo

    1995-01-01

    The purpose of this study is to describe the angiographic findings of collateral vessels in cervicofacial vascular lesions with previously ligated carotid arteries and to evaluate the extent of angiographic assessment needed before embolization. We retrospectively reviewed 10 cervicofacial vascular lesions with previously ligated carotid artery, which were 6 cases of arteriovenous malformation, 2 cases of carotid cavernous fistula, 1 case of hemangioma and 1 case of arteriovenous malformation with carotid cavernous fistula. The previously ligated arteries are proximal external carotid artery (n = 5), branches of external carotid artery (n = 2) and common carotid artery (n = 3). Common carotid artery or internal carotid artery (n = 9), vertebral artery (n = 5), ipsilateral external carotid artery (n = 4), contralateral external carotid artery (n = 5), costocervical trunk (n = 2), thyrocervical trunk (n = 2) were assessed by conventional angiography. Angiography of both carotid and vertebral arteries was performed in 5 cases. The collateral vascular channels were inferolateral trunk of internal carotid artery (n = 8), vertebral artery (n = 5), contralateral external carotid artery (n = 5), ipsilateral external carotid artery (n = 4), deep cervical artery (n = 2) and ascending cervical artery (n = 1). Embolization were performed in 9 cases with operative cannulation (n = 4), embolization via collateral branches of ipsilateral external carotid artery (n = 1), embolization via collateral branches of contralateral external carotid artery (n = 3) and balloon occlusion via direct puncture (n = 1). The collateral channels in cervicofacial vascular lesions with previously ligated carotid artery were inferolateral trunk of internal carotid artery, contralateral or ipsilateral external carotid artery, vertebral artery, deep cervical artery and ascending cervical artery on angiography. Complete angiographic assessment of possible collateral channels is mandatory for the

  4. Deep sea radionuclides

    International Nuclear Information System (INIS)

    Kanisch, G.; Vobach, M.

    1993-01-01

    Every year since 1979, either in sping or in summer, the fishing research vessel 'Walther Herwig' goes to the North Atlantic disposal areas of solid radioactive wastes, and, for comparative purposes, to other areas, in order to collect water samples, plankton and nekton, and, from the deep sea bed, sediment samples and benthos organisms. In addition to data on the radionuclide contents of various media, information about the plankton, nekton and benthos organisms living in those areas and about their biomasses could be gathered. The investigations are aimed at acquiring scientifically founded knowledge of the uptake of radioactive substances by microorganisms, and their migration from the sea bottom to the areas used by man. (orig.) [de

  5. Deep inelastic phenomena

    International Nuclear Information System (INIS)

    Aubert, J.J.

    1982-01-01

    The experimental situation of the deep inelastic scattering for electrons (muons) is reviewed. A brief history of experimentation highlights Mohr and Nicoll's 1932 experiment on electron-atom scattering and Hofstadter's 1950 experiment on electron-nucleus scattering. The phenomenology of electron-nucleon scattering carried out between 1960 and 1970 is described, with emphasis on the parton model, and scaling. Experiments at SLAC and FNAL since 1974 exhibit scaling violations. Three muon-nucleon scattering experiments at BFP, BCDMA, and EMA, currently producing new results in the high Q 2 domain suggest a rather flat behaviour of the structure function at fixed x as a function of Q 2 . It is seen that the structure measured in DIS can then be projected into a pure hadronic process to predict a cross section. Protonneutron difference, moment analysis, and Drell-Yan pairs are also considered

  6. 30 CFR 203.31 - If I have a qualified phase 2 or qualified phase 3 ultra-deep well, what royalty relief would...

    Science.gov (United States)

    2010-07-01

    ... water less than 400 meters deep (see § 203.30(a)), has no existing deep or ultra-deep wells and that the... depths partly or entirely less than 200 meters and has not previously produced from a deep well (§ 203.30... which is 16,000 feet TVD SS and your lease is located in water 100 meters deep. Then in 2008, you drill...

  7. DEWS (DEep White matter hyperintensity Segmentation framework): A fully automated pipeline for detecting small deep white matter hyperintensities in migraineurs.

    Science.gov (United States)

    Park, Bo-Yong; Lee, Mi Ji; Lee, Seung-Hak; Cha, Jihoon; Chung, Chin-Sang; Kim, Sung Tae; Park, Hyunjin

    2018-01-01

    Migraineurs show an increased load of white matter hyperintensities (WMHs) and more rapid deep WMH progression. Previous methods for WMH segmentation have limited efficacy to detect small deep WMHs. We developed a new fully automated detection pipeline, DEWS (DEep White matter hyperintensity Segmentation framework), for small and superficially-located deep WMHs. A total of 148 non-elderly subjects with migraine were included in this study. The pipeline consists of three components: 1) white matter (WM) extraction, 2) WMH detection, and 3) false positive reduction. In WM extraction, we adjusted the WM mask to re-assign misclassified WMHs back to WM using many sequential low-level image processing steps. In WMH detection, the potential WMH clusters were detected using an intensity based threshold and region growing approach. For false positive reduction, the detected WMH clusters were classified into final WMHs and non-WMHs using the random forest (RF) classifier. Size, texture, and multi-scale deep features were used to train the RF classifier. DEWS successfully detected small deep WMHs with a high positive predictive value (PPV) of 0.98 and true positive rate (TPR) of 0.70 in the training and test sets. Similar performance of PPV (0.96) and TPR (0.68) was attained in the validation set. DEWS showed a superior performance in comparison with other methods. Our proposed pipeline is freely available online to help the research community in quantifying deep WMHs in non-elderly adults.

  8. Top tagging with deep neural networks [Vidyo

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Recent literature on deep neural networks for top tagging has focussed on image based techniques or multivariate approaches using high level jet substructure variables. Here, we take a sequential approach to this task by using anordered sequence of energy deposits as training inputs. Unlike previous approaches, this strategy does not result in a loss of information during pixelization or the calculation of high level features. We also propose new preprocessing methods that do not alter key physical quantities such as jet mass. We compare the performance of this approach to standard tagging techniques and present results evaluating the robustness of the neural network to pileup.

  9. Context and Deep Learning Design

    Science.gov (United States)

    Boyle, Tom; Ravenscroft, Andrew

    2012-01-01

    Conceptual clarification is essential if we are to establish a stable and deep discipline of technology enhanced learning. The technology is alluring; this can distract from deep design in a surface rush to exploit the affordances of the new technology. We need a basis for design, and a conceptual unit of organization, that are applicable across…

  10. Deep Learning for Population Genetic Inference.

    Science.gov (United States)

    Sheehan, Sara; Song, Yun S

    2016-03-01

    Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

  11. Deep Learning for Population Genetic Inference.

    Directory of Open Access Journals (Sweden)

    Sara Sheehan

    2016-03-01

    Full Text Available Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data to the output (e.g., population genetic parameters of interest. We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history. Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme.

  12. Deep Learning for Population Genetic Inference

    Science.gov (United States)

    Sheehan, Sara; Song, Yun S.

    2016-01-01

    Given genomic variation data from multiple individuals, computing the likelihood of complex population genetic models is often infeasible. To circumvent this problem, we introduce a novel likelihood-free inference framework by applying deep learning, a powerful modern technique in machine learning. Deep learning makes use of multilayer neural networks to learn a feature-based function from the input (e.g., hundreds of correlated summary statistics of data) to the output (e.g., population genetic parameters of interest). We demonstrate that deep learning can be effectively employed for population genetic inference and learning informative features of data. As a concrete application, we focus on the challenging problem of jointly inferring natural selection and demography (in the form of a population size change history). Our method is able to separate the global nature of demography from the local nature of selection, without sequential steps for these two factors. Studying demography and selection jointly is motivated by Drosophila, where pervasive selection confounds demographic analysis. We apply our method to 197 African Drosophila melanogaster genomes from Zambia to infer both their overall demography, and regions of their genome under selection. We find many regions of the genome that have experienced hard sweeps, and fewer under selection on standing variation (soft sweep) or balancing selection. Interestingly, we find that soft sweeps and balancing selection occur more frequently closer to the centromere of each chromosome. In addition, our demographic inference suggests that previously estimated bottlenecks for African Drosophila melanogaster are too extreme. PMID:27018908

  13. A previously unidentified deletion in G protein-coupled receptor 143 causing X-linked congenital nystagmus in a Chinese family

    Directory of Open Access Journals (Sweden)

    Jing Liu

    2016-01-01

    Full Text Available Background: Congenital nystagmus (CN is characterized by conjugated, spontaneous, and involuntary ocular oscillations. It is an inherited disease and the most common inheritance pattern is X-linked CN. In this study, our aim is to identify the disease-causing mutation in a large sixth-generation Chinese family with X-linked CN. Methods: It has been reported that mutations in four-point-one, ezrin, radixin, moesin domain-containing 7 gene (FRMD7 and G protein-coupled receptor 143 gene (GPR143 account for the majority patients of X-linked nystagmus. We collected 8 ml blood samples from members of a large sixth-generation pedigree with X-linked CN and 100 normal controls. FRMD7 and GPR143 were scanned by polymerase chain reaction (PCR-based DNA sequencing assays, and multiplex PCR assays were applied to detect deletions. Results: We identified a previously unreported deletion covering 7 exons in GPR143 in a Chinese family. The heterozygous deletion from exon 3 to exon 9 of GPR143 was detected in all affected males in the family, while it was not detected in other unaffected relatives or 100 normal controls. Conclusions: This is the first report of molecular characterization in GPR143 gene in the CN family. Our results expand the spectrum of GPR143 mutations causing CN and further confirm the role of GPR143 in the pathogenesis of CN.

  14. Molecular analysis of clinical isolates previously diagnosed as Mycobacterium intracellulare reveals incidental findings of "Mycobacterium indicus pranii" genotypes in human lung infection.

    Science.gov (United States)

    Kim, Su-Young; Park, Hye Yun; Jeong, Byeong-Ho; Jeon, Kyeongman; Huh, Hee Jae; Ki, Chang-Seok; Lee, Nam Yong; Han, Seung-Jung; Shin, Sung Jae; Koh, Won-Jung

    2015-09-30

    Mycobacterium intracellulare is a major cause of Mycobacterium avium complex lung disease in many countries. Molecular studies have revealed several new Mycobacteria species that are closely related to M. intracellulare. The aim of this study was to re-identify and characterize clinical isolates from patients previously diagnosed with M. intracellulare lung disease at the molecular level. Mycobacterial isolates from 77 patients, initially diagnosed with M. intracellulare lung disease were re-analyzed by multi-locus sequencing and pattern of insertion sequences. Among the 77 isolates, 74 (96 %) isolates were designated as M. intracellulare based on multigene sequence-based analysis. Interestingly, the three remaining strains (4 %) were re-identified as "Mycobacterium indicus pranii" according to distinct molecular phylogenetic positions in rpoB and hsp65 sequence-based typing. In hsp65 sequevar analysis, code 13 was found in the majority of cases and three unreported codes were identified. In 16S-23S rRNA internal transcribed spacer (ITS) sequevar analysis, all isolates of both species were classified within the Min-A ITS sequevar. Interestingly, four of the M. intracellulare isolates harbored IS1311, a M. avium-specific element. Two of three patients infected with "M. indicus pranii" had persistent positive sputum cultures after antibiotic therapy, indicating the clinical relevance of this study. This analysis highlights the importance of precise identification of clinical isolates genetically close to Mycobacterium species, and suggests that greater attention should be paid to nontuberculous mycobacteria lung disease caused by "M. indicus pranii".

  15. 49 CFR 173.23 - Previously authorized packaging.

    Science.gov (United States)

    2010-10-01

    ... 49 Transportation 2 2010-10-01 2010-10-01 false Previously authorized packaging. 173.23 Section... REQUIREMENTS FOR SHIPMENTS AND PACKAGINGS Preparation of Hazardous Materials for Transportation § 173.23 Previously authorized packaging. (a) When the regulations specify a packaging with a specification marking...

  16. 28 CFR 10.5 - Incorporation of papers previously filed.

    Science.gov (United States)

    2010-07-01

    ... 28 Judicial Administration 1 2010-07-01 2010-07-01 false Incorporation of papers previously filed... CARRYING ON ACTIVITIES WITHIN THE UNITED STATES Registration Statement § 10.5 Incorporation of papers previously filed. Papers and documents already filed with the Attorney General pursuant to the said act and...

  17. 75 FR 76056 - FEDERAL REGISTER CITATION OF PREVIOUS ANNOUNCEMENT:

    Science.gov (United States)

    2010-12-07

    ... SECURITIES AND EXCHANGE COMMISSION Sunshine Act Meeting FEDERAL REGISTER CITATION OF PREVIOUS ANNOUNCEMENT: STATUS: Closed meeting. PLACE: 100 F Street, NE., Washington, DC. DATE AND TIME OF PREVIOUSLY ANNOUNCED MEETING: Thursday, December 9, 2010 at 2 p.m. CHANGE IN THE MEETING: Time change. The closed...

  18. No discrimination against previous mates in a sexually cannibalistic spider

    Science.gov (United States)

    Fromhage, Lutz; Schneider, Jutta M.

    2005-09-01

    In several animal species, females discriminate against previous mates in subsequent mating decisions, increasing the potential for multiple paternity. In spiders, female choice may take the form of selective sexual cannibalism, which has been shown to bias paternity in favor of particular males. If cannibalistic attacks function to restrict a male's paternity, females may have little interest to remate with males having survived such an attack. We therefore studied the possibility of female discrimination against previous mates in sexually cannibalistic Argiope bruennichi, where females almost always attack their mate at the onset of copulation. We compared mating latency and copulation duration of males having experienced a previous copulation either with the same or with a different female, but found no evidence for discrimination against previous mates. However, males copulated significantly shorter when inserting into a used, compared to a previously unused, genital pore of the female.

  19. Implant breast reconstruction after salvage mastectomy in previously irradiated patients.

    Science.gov (United States)

    Persichetti, Paolo; Cagli, Barbara; Simone, Pierfranco; Cogliandro, Annalisa; Fortunato, Lucio; Altomare, Vittorio; Trodella, Lucio

    2009-04-01

    The most common surgical approach in case of local tumor recurrence after quadrantectomy and radiotherapy is salvage mastectomy. Breast reconstruction is the subsequent phase of the treatment and the plastic surgeon has to operate on previously irradiated and manipulated tissues. The medical literature highlights that breast reconstruction with tissue expanders is not a pursuable option, considering previous radiotherapy a contraindication. The purpose of this retrospective study is to evaluate the influence of previous radiotherapy on 2-stage breast reconstruction (tissue expander/implant). Only patients with analogous timing of radiation therapy and the same demolitive and reconstructive procedures were recruited. The results of this study prove that, after salvage mastectomy in previously irradiated patients, implant reconstruction is still possible. Further comparative studies are, of course, advisable to draw any conclusion on the possibility to perform implant reconstruction in previously irradiated patients.

  20. Deep Learning Fluid Mechanics

    Science.gov (United States)

    Barati Farimani, Amir; Gomes, Joseph; Pande, Vijay

    2017-11-01

    We have developed a new data-driven model paradigm for the rapid inference and solution of the constitutive equations of fluid mechanic by deep learning models. Using generative adversarial networks (GAN), we train models for the direct generation of solutions to steady state heat conduction and incompressible fluid flow without knowledge of the underlying governing equations. Rather than using artificial neural networks to approximate the solution of the constitutive equations, GANs can directly generate the solutions to these equations conditional upon an arbitrary set of boundary conditions. Both models predict temperature, velocity and pressure fields with great test accuracy (>99.5%). The application of our framework for inferring and generating the solutions of partial differential equations can be applied to any physical phenomena and can be used to learn directly from experiments where the underlying physical model is complex or unknown. We also have shown that our framework can be used to couple multiple physics simultaneously, making it amenable to tackle multi-physics problems.

  1. Deep video deblurring

    KAUST Repository

    Su, Shuochen

    2016-11-25

    Motion blur from camera shake is a major problem in videos captured by hand-held devices. Unlike single-image deblurring, video-based approaches can take advantage of the abundant information that exists across neighboring frames. As a result the best performing methods rely on aligning nearby frames. However, aligning images is a computationally expensive and fragile procedure, and methods that aggregate information must therefore be able to identify which regions have been accurately aligned and which have not, a task which requires high level scene understanding. In this work, we introduce a deep learning solution to video deblurring, where a CNN is trained end-to-end to learn how to accumulate information across frames. To train this network, we collected a dataset of real videos recorded with a high framerate camera, which we use to generate synthetic motion blur for supervision. We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

  2. Deep space telescopes

    CERN Multimedia

    CERN. Geneva

    2006-01-01

    The short series of seminars will address results and aims of current and future space astrophysics as the cultural framework for the development of deep space telescopes. It will then present such new tools, as they are currently available to, or imagined by, the scientific community, in the context of the science plans of ESA and of all major world space agencies. Ground-based astronomy, in the 400 years since Galileo’s telescope, has given us a profound phenomenological comprehension of our Universe, but has traditionally been limited to the narrow band(s) to which our terrestrial atmosphere is transparent. Celestial objects, however, do not care about our limitations, and distribute most of the information about their physics throughout the complete electromagnetic spectrum. Such information is there for the taking, from millimiter wavelengths to gamma rays. Forty years astronomy from space, covering now most of the e.m. spectrum, have thus given us a better understanding of our physical Universe then t...

  3. Deep inelastic final states

    International Nuclear Information System (INIS)

    Girardi, G.

    1980-11-01

    In these lectures we attempt to describe the final states of deep inelastic scattering as given by QCD. In the first section we shall briefly comment on the parton model and give the main properties of decay functions which are of interest for the study of semi-inclusive leptoproduction. The second section is devoted to the QCD approach to single hadron leptoproduction. First we recall basic facts on QCD log's and derive after that the evolution equations for the fragmentation functions. For this purpose we make a short detour in e + e - annihilation. The rest of the section is a study of the factorization of long distance effects associated with the initial and final states. We then show how when one includes next to leading QCD corrections one induces factorization breaking and describe the double moments useful for testing such effects. The next section contains a review on the QCD jets in the hadronic final state. We begin by introducing the notion of infrared safe variable and defining a few useful examples. Distributions in these variables are studied to first order in QCD, with some comments on the resummation of logs encountered in higher orders. Finally the last section is a 'gaullimaufry' of jet studies

  4. DIEP flap customization using Fluobeam® indocyanine green tissue perfusion assessment with large previous abdominal scar

    Directory of Open Access Journals (Sweden)

    Michael A. Fallucco

    2017-06-01

    Full Text Available The Fluobeam® is a portable, near-infrared camera that is held and controlled by the surgeon to visualize tissue perfusion using indocyanine green (ICG fluorescence imaging. This case report describes how data obtained from ICG imaging allows intraoperative customization in a previously surgically scarred abdomen during autologous Deep Inferior Epigastric Artery Perforator (DIEP flap bilateral breast reconstruction. The outcome was successful breast mound recreation without fat necrosis.

  5. Deep Mapping and Spatial Anthropology

    Directory of Open Access Journals (Sweden)

    Les Roberts

    2016-01-01

    Full Text Available This paper provides an introduction to the Humanities Special Issue on “Deep Mapping”. It sets out the rationale for the collection and explores the broad-ranging nature of perspectives and practices that fall within the “undisciplined” interdisciplinary domain of spatial humanities. Sketching a cross-current of ideas that have begun to coalesce around the concept of “deep mapping”, the paper argues that rather than attempting to outline a set of defining characteristics and “deep” cartographic features, a more instructive approach is to pay closer attention to the multivalent ways deep mapping is performatively put to work. Casting a critical and reflexive gaze over the developing discourse of deep mapping, it is argued that what deep mapping “is” cannot be reduced to the otherwise a-spatial and a-temporal fixity of the “deep map”. In this respect, as an undisciplined survey of this increasing expansive field of study and practice, the paper explores the ways in which deep mapping can engage broader discussion around questions of spatial anthropology.

  6. Deep learning for computational chemistry.

    Science.gov (United States)

    Goh, Garrett B; Hodas, Nathan O; Vishnu, Abhinav

    2017-06-15

    The rise and fall of artificial neural networks is well documented in the scientific literature of both computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on multilayer neural networks. Within the last few years, we have seen the transformative impact of deep learning in many domains, particularly in speech recognition and computer vision, to the extent that the majority of expert practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties that distinguish them from traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including quantitative structure activity relationship, virtual screening, protein structure prediction, quantum chemistry, materials design, and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non-neural networks state-of-the-art models across disparate research topics, and deep neural network-based models often exceeded the "glass ceiling" expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a valuable tool for computational chemistry. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  7. Deep learning for computational chemistry

    Energy Technology Data Exchange (ETDEWEB)

    Goh, Garrett B. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Hodas, Nathan O. [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354; Vishnu, Abhinav [Advanced Computing, Mathematics, and Data Division, Pacific Northwest National Laboratory, 902 Battelle Blvd Richland Washington 99354

    2017-03-08

    The rise and fall of artificial neural networks is well documented in the scientific literature of both the fields of computer science and computational chemistry. Yet almost two decades later, we are now seeing a resurgence of interest in deep learning, a machine learning algorithm based on “deep” neural networks. Within the last few years, we have seen the transformative impact of deep learning the computer science domain, notably in speech recognition and computer vision, to the extent that the majority of practitioners in those field are now regularly eschewing prior established models in favor of deep learning models. In this review, we provide an introductory overview into the theory of deep neural networks and their unique properties as compared to traditional machine learning algorithms used in cheminformatics. By providing an overview of the variety of emerging applications of deep neural networks, we highlight its ubiquity and broad applicability to a wide range of challenges in the field, including QSAR, virtual screening, protein structure modeling, QM calculations, materials synthesis and property prediction. In reviewing the performance of deep neural networks, we observed a consistent outperformance against non neural networks state-of-the-art models across disparate research topics, and deep neural network based models often exceeded the “glass ceiling” expectations of their respective tasks. Coupled with the maturity of GPU-accelerated computing for training deep neural networks and the exponential growth of chemical data on which to train these networks on, we anticipate that deep learning algorithms will be a useful tool and may grow into a pivotal role for various challenges in the computational chemistry field.

  8. DeepSimulator: a deep simulator for Nanopore sequencing

    KAUST Repository

    Li, Yu; Han, Renmin; Bi, Chongwei; Li, Mo; Wang, Sheng; Gao, Xin

    2017-01-01

    or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments

  9. Extracting Databases from Dark Data with DeepDive.

    Science.gov (United States)

    Zhang, Ce; Shin, Jaeho; Ré, Christopher; Cafarella, Michael; Niu, Feng

    2016-01-01

    DeepDive is a system for extracting relational databases from dark data : the mass of text, tables, and images that are widely collected and stored but which cannot be exploited by standard relational tools. If the information in dark data - scientific papers, Web classified ads, customer service notes, and so on - were instead in a relational database, it would give analysts a massive and valuable new set of "big data." DeepDive is distinctive when compared to previous information extraction systems in its ability to obtain very high precision and recall at reasonable engineering cost; in a number of applications, we have used DeepDive to create databases with accuracy that meets that of human annotators. To date we have successfully deployed DeepDive to create data-centric applications for insurance, materials science, genomics, paleontologists, law enforcement, and others. The data unlocked by DeepDive represents a massive opportunity for industry, government, and scientific researchers. DeepDive is enabled by an unusual design that combines large-scale probabilistic inference with a novel developer interaction cycle. This design is enabled by several core innovations around probabilistic training and inference.

  10. Predicting healthcare trajectories from medical records: A deep learning approach.

    Science.gov (United States)

    Pham, Trang; Tran, Truyen; Phung, Dinh; Venkatesh, Svetha

    2017-05-01

    Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, stored in electronic medical records are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors and models patient health state trajectories by the memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces methods to handle irregularly timed events by moderating the forgetting and consolidation of memory. DeepCare also explicitly models medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden - diabetes and mental health - the results show improved prediction accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Deep UV LEDs

    Science.gov (United States)

    Han, Jung; Amano, Hiroshi; Schowalter, Leo

    2014-06-01

    Deep ultraviolet (DUV) photons interact strongly with a broad range of chemical and biological molecules; compact DUV light sources could enable a wide range of applications in chemi/bio-sensing, sterilization, agriculture, and industrial curing. The much shorter wavelength also results in useful characteristics related to optical diffraction (for lithography) and scattering (non-line-of-sight communication). The family of III-N (AlGaInN) compound semiconductors offers a tunable energy gap from infrared to DUV. While InGaN-based blue light emitters have been the primary focus for the obvious application of solid state lighting, there is a growing interest in the development of efficient UV and DUV light-emitting devices. In the past few years we have witnessed an increasing investment from both government and industry sectors to further the state of DUV light-emitting devices. The contributions in Semiconductor Science and Technology 's special issue on DUV devices provide an up-to-date snapshot covering many relevant topics in this field. Given the expected importance of bulk AlN substrate in DUV technology, we are pleased to include a review article by Hartmann et al on the growth of AlN bulk crystal by physical vapour transport. The issue of polarization field within the deep ultraviolet LEDs is examined in the article by Braut et al. Several commercial companies provide useful updates in their development of DUV emitters, including Nichia (Fujioka et al ), Nitride Semiconductors (Muramoto et al ) and Sensor Electronic Technology (Shatalov et al ). We believe these articles will provide an excellent overview of the state of technology. The growth of AlGaN heterostructures by molecular beam epitaxy, in contrast to the common organo-metallic vapour phase epitaxy, is discussed by Ivanov et al. Since hexagonal boron nitride (BN) has received much attention as both a UV and a two-dimensional electronic material, we believe it serves readers well to include the

  12. Personality disorders in previously detained adolescent females: a prospective study

    NARCIS (Netherlands)

    Krabbendam, A.; Colins, O.F.; Doreleijers, T.A.H.; van der Molen, E.; Beekman, A.T.F.; Vermeiren, R.R.J.M.

    2015-01-01

    This longitudinal study investigated the predictive value of trauma and mental health problems for the development of antisocial personality disorder (ASPD) and borderline personality disorder (BPD) in previously detained women. The participants were 229 detained adolescent females who were assessed

  13. Payload specialist Reinhard Furrer show evidence of previous blood sampling

    Science.gov (United States)

    1985-01-01

    Payload specialist Reinhard Furrer shows evidence of previous blood sampling while Wubbo J. Ockels, Dutch payload specialist (only partially visible), extends his right arm after a sample has been taken. Both men show bruises on their arms.

  14. Choice of contraception after previous operative delivery at a family ...

    African Journals Online (AJOL)

    Choice of contraception after previous operative delivery at a family planning clinic in Northern Nigeria. Amina Mohammed‑Durosinlorun, Joel Adze, Stephen Bature, Caleb Mohammed, Matthew Taingson, Amina Abubakar, Austin Ojabo, Lydia Airede ...

  15. Previous utilization of service does not improve timely booking in ...

    African Journals Online (AJOL)

    Previous utilization of service does not improve timely booking in antenatal care: Cross sectional study ... Journal Home > Vol 24, No 3 (2010) > ... Results: Past experience on antenatal care service utilization did not come out as a predictor for ...

  16. DEEP INFILTRATING ENDOMETRIOSIS

    Directory of Open Access Journals (Sweden)

    Martina Ribič-Pucelj

    2018-02-01

    Full Text Available Background: Endometriosis is not considered a unified disease, but a disease encompassing three differ- ent forms differentiated by aetiology and pathogenesis: peritoneal endometriosis, ovarian endometriosis and deep infiltrating endometriosis (DIE. The disease is classified as DIE when the lesions penetrate 5 mm or more into the retroperitoneal space. The estimated incidence of endometriosis in women of reproductive age ranges from 10–15 % and that of DIE from 3–10 %, the highest being in infertile women and in those with chronic pelvic pain. The leading symptoms of DIE are chronic pelvic pain which increases with age and correlates with the depth of infiltration and infertility. The most important diagnostic procedures are patient’s history and proper gynecological examination. The diagnosis is confirmed with laparoscopy. DIE can affect, beside reproductive organs, also bowel, bladder and ureters, therefore adi- tional diagnostic procedures must be performed preopertively to confirm or to exclude the involvement of the mentioned organs. Endometriosis is hormon dependent disease, there- fore several hormonal treatment regims are used to supress estrogen production but the symptoms recurr soon after caesation of the treatment. At the moment, surgical treatment with excision of all lesions, including those of bowel, bladder and ureters, is the method of choice but requires frequently interdisciplinary approach. Surgical treatment significantly reduces pain and improves fertility in inferile patients. Conclusions: DIE is not a rare form of endometriosis characterized by chronic pelvic pain and infertility. Medical treatment is not efficient. The method of choice is surgical treatment with excision of all lesions. It significantly reduces pelvic pain and enables high spontaneus and IVF preg- nacy rates.Therefore such patients should be treated at centres with experience in treatment of DIE and with possibility of interdisciplinary approach.

  17. A previous hamstring injury affects kicking mechanics in soccer players.

    Science.gov (United States)

    Navandar, Archit; Veiga, Santiago; Torres, Gonzalo; Chorro, David; Navarro, Enrique

    2018-01-10

    Although the kicking skill is influenced by limb dominance and sex, how a previous hamstring injury affects kicking has not been studied in detail. Thus, the objective of this study was to evaluate the effect of sex and limb dominance on kicking in limbs with and without a previous hamstring injury. 45 professional players (males: n=19, previously injured players=4, age=21.16 ± 2.00 years; females: n=19, previously injured players=10, age=22.15 ± 4.50 years) performed 5 kicks each with their preferred and non-preferred limb at a target 7m away, which were recorded with a three-dimensional motion capture system. Kinematic and kinetic variables were extracted for the backswing, leg cocking, leg acceleration and follow through phases. A shorter backswing (20.20 ± 3.49% vs 25.64 ± 4.57%), and differences in knee flexion angle (58 ± 10o vs 72 ± 14o) and hip flexion velocity (8 ± 0rad/s vs 10 ± 2rad/s) were observed in previously injured, non-preferred limb kicks for females. A lower peak hip linear velocity (3.50 ± 0.84m/s vs 4.10 ± 0.45m/s) was observed in previously injured, preferred limb kicks of females. These differences occurred in the backswing and leg-cocking phases where the hamstring muscles were the most active. A variation in the functioning of the hamstring muscles and that of the gluteus maximus and iliopsoas in the case of a previous injury could account for the differences observed in the kicking pattern. Therefore, the effects of a previous hamstring injury must be considered while designing rehabilitation programs to re-educate kicking movement.

  18. A deep sea community at the Kebrit brine pool in the Red Sea

    KAUST Repository

    Vestheim, Hege; Kaartvedt, Stein

    2015-01-01

    Approximately 25 deep sea brine pools occur along the mid axis of the Red Sea. These hypersaline, anoxic, and acidic environments have previously been reported to host diverse microbial communities. We visited the Kebrit brine pool in April 2013

  19. Telepresence for Deep Space Missions

    Data.gov (United States)

    National Aeronautics and Space Administration — Incorporating telepresence technologies into deep space mission operations can give the crew and ground personnel the impression that they are in a location at time...

  20. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-01-01

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during

  1. pathways to deep decarbonization - 2014 report

    International Nuclear Information System (INIS)

    Sachs, Jeffrey; Guerin, Emmanuel; Mas, Carl; Schmidt-Traub, Guido; Tubiana, Laurence; Waisman, Henri; Colombier, Michel; Bulger, Claire; Sulakshana, Elana; Zhang, Kathy; Barthelemy, Pierre; Spinazze, Lena; Pharabod, Ivan

    2014-09-01

    network comprising 15 Country Research Partners, and several Partner Organizations who develop and share methods, assumptions, and findings related to deep decarbonization. Each DDPP Country Research Team develops illustrative pathway analysis for the transition to a low-carbon economy, with the intent of taking into account national socio-economic conditions, development aspirations, infrastructure stocks, resource endowments, and other relevant factors. This document starts with a short outline of key results from previous global studies (discussed in chapter I to IV) and then turns to what is new and special about the country-level approach of the DDPP (explained in chapter V). It summarizes the main preliminary findings from the Deep Decarbonization Pathways (DDPs) developed by the Country Research Partners (included in chapter VI) and draws some lessons for the international negotiations leading up to the 21. Conference of the Parties (COP-21) of the UN Framework Convention on Climate Change (UNFCCC) to be held in Paris in December 2015

  2. The DEEP-South: Scheduling and Data Reduction Software System

    Science.gov (United States)

    Yim, Hong-Suh; Kim, Myung-Jin; Bae, Youngho; Moon, Hong-Kyu; Choi, Young-Jun; Roh, Dong-Goo; the DEEP-South Team

    2015-08-01

    The DEep Ecliptic Patrol of the Southern sky (DEEP-South), started in October 2012, is currently in test runs with the first Korea Microlensing Telescope Network (KMTNet) 1.6 m wide-field telescope located at CTIO in Chile. While the primary objective for the DEEP-South is physical characterization of small bodies in the Solar System, it is expected to discover a large number of such bodies, many of them previously unknown.An automatic observation planning and data reduction software subsystem called "The DEEP-South Scheduling and Data reduction System" (the DEEP-South SDS) is currently being designed and implemented for observation planning, data reduction and analysis of huge amount of data with minimum human interaction. The DEEP-South SDS consists of three software subsystems: the DEEP-South Scheduling System (DSS), the Local Data Reduction System (LDR), and the Main Data Reduction System (MDR). The DSS manages observation targets, makes decision on target priority and observation methods, schedules nightly observations, and archive data using the Database Management System (DBMS). The LDR is designed to detect moving objects from CCD images, while the MDR conducts photometry and reconstructs lightcurves. Based on analysis made at the LDR and the MDR, the DSS schedules follow-up observation to be conducted at other KMTNet stations. In the end of 2015, we expect the DEEP-South SDS to achieve a stable operation. We also have a plan to improve the SDS to accomplish finely tuned observation strategy and more efficient data reduction in 2016.

  3. Deep Learning and Bayesian Methods

    OpenAIRE

    Prosper Harrison B.

    2017-01-01

    A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such meth...

  4. Density functionals from deep learning

    OpenAIRE

    McMahon, Jeffrey M.

    2016-01-01

    Density-functional theory is a formally exact description of a many-body quantum system in terms of its density; in practice, however, approximations to the universal density functional are required. In this work, a model based on deep learning is developed to approximate this functional. Deep learning allows computational models that are capable of naturally discovering intricate structure in large and/or high-dimensional data sets, with multiple levels of abstraction. As no assumptions are ...

  5. Secondary recurrent miscarriage is associated with previous male birth.

    LENUS (Irish Health Repository)

    Ooi, Poh Veh

    2012-01-31

    Secondary recurrent miscarriage (RM) is defined as three or more consecutive pregnancy losses after delivery of a viable infant. Previous reports suggest that a firstborn male child is associated with less favourable subsequent reproductive potential, possibly due to maternal immunisation against male-specific minor histocompatibility antigens. In a retrospective cohort study of 85 cases of secondary RM we aimed to determine if secondary RM was associated with (i) gender of previous child, maternal age, or duration of miscarriage history, and (ii) increased risk of pregnancy complications. Fifty-three women (62.0%; 53\\/85) gave birth to a male child prior to RM compared to 32 (38.0%; 32\\/85) who gave birth to a female child (p=0.002). The majority (91.7%; 78\\/85) had uncomplicated, term deliveries and normal birth weight neonates, with one quarter of the women previously delivered by Caesarean section. All had routine RM investigations and 19.0% (16\\/85) had an abnormal result. Fifty-seven women conceived again and 33.3% (19\\/57) miscarried, but there was no significant difference in failure rates between those with a previous male or female child (13\\/32 vs. 6\\/25, p=0.2). When patients with abnormal results were excluded, or when women with only one previous child were considered, there was still no difference in these rates. A previous male birth may be associated with an increased risk of secondary RM but numbers preclude concluding whether this increases recurrence risk. The suggested association with previous male birth provides a basis for further investigations at a molecular level.

  6. Secondary recurrent miscarriage is associated with previous male birth.

    LENUS (Irish Health Repository)

    Ooi, Poh Veh

    2011-01-01

    Secondary recurrent miscarriage (RM) is defined as three or more consecutive pregnancy losses after delivery of a viable infant. Previous reports suggest that a firstborn male child is associated with less favourable subsequent reproductive potential, possibly due to maternal immunisation against male-specific minor histocompatibility antigens. In a retrospective cohort study of 85 cases of secondary RM we aimed to determine if secondary RM was associated with (i) gender of previous child, maternal age, or duration of miscarriage history, and (ii) increased risk of pregnancy complications. Fifty-three women (62.0%; 53\\/85) gave birth to a male child prior to RM compared to 32 (38.0%; 32\\/85) who gave birth to a female child (p=0.002). The majority (91.7%; 78\\/85) had uncomplicated, term deliveries and normal birth weight neonates, with one quarter of the women previously delivered by Caesarean section. All had routine RM investigations and 19.0% (16\\/85) had an abnormal result. Fifty-seven women conceived again and 33.3% (19\\/57) miscarried, but there was no significant difference in failure rates between those with a previous male or female child (13\\/32 vs. 6\\/25, p=0.2). When patients with abnormal results were excluded, or when women with only one previous child were considered, there was still no difference in these rates. A previous male birth may be associated with an increased risk of secondary RM but numbers preclude concluding whether this increases recurrence risk. The suggested association with previous male birth provides a basis for further investigations at a molecular level.

  7. Pregnancy after catheter-directed thrombolysis for acute iliofemoral deep venous thrombosis

    DEFF Research Database (Denmark)

    Jørgensen, M; Broholm, R; Bækgaard, N

    2013-01-01

    To assess the safety and efficacy of low-molecular-weight heparin (LMWH) in pregnancy and puerperium in women with previous acute iliofemoral deep venous thrombosis (DVT) treated with catheter-directed thrombolysis (CDT).......To assess the safety and efficacy of low-molecular-weight heparin (LMWH) in pregnancy and puerperium in women with previous acute iliofemoral deep venous thrombosis (DVT) treated with catheter-directed thrombolysis (CDT)....

  8. Deep Unfolding for Topic Models.

    Science.gov (United States)

    Chien, Jen-Tzung; Lee, Chao-Hsi

    2018-02-01

    Deep unfolding provides an approach to integrate the probabilistic generative models and the deterministic neural networks. Such an approach is benefited by deep representation, easy interpretation, flexible learning and stochastic modeling. This study develops the unsupervised and supervised learning of deep unfolded topic models for document representation and classification. Conventionally, the unsupervised and supervised topic models are inferred via the variational inference algorithm where the model parameters are estimated by maximizing the lower bound of logarithm of marginal likelihood using input documents without and with class labels, respectively. The representation capability or classification accuracy is constrained by the variational lower bound and the tied model parameters across inference procedure. This paper aims to relax these constraints by directly maximizing the end performance criterion and continuously untying the parameters in learning process via deep unfolding inference (DUI). The inference procedure is treated as the layer-wise learning in a deep neural network. The end performance is iteratively improved by using the estimated topic parameters according to the exponentiated updates. Deep learning of topic models is therefore implemented through a back-propagation procedure. Experimental results show the merits of DUI with increasing number of layers compared with variational inference in unsupervised as well as supervised topic models.

  9. Exploring the Earth Using Deep Learning Techniques

    Science.gov (United States)

    Larraondo, P. R.; Evans, B. J. K.; Antony, J.

    2016-12-01

    Research using deep neural networks have significantly matured in recent times, and there is now a surge in interest to apply such methods to Earth systems science and the geosciences. When combined with Big Data, we believe there are opportunities for significantly transforming a number of areas relevant to researchers and policy makers. In particular, by using a combination of data from a range of satellite Earth observations as well as computer simulations from climate models and reanalysis, we can gain new insights into the information that is locked within the data. Global geospatial datasets describe a wide range of physical and chemical parameters, which are mostly available using regular grids covering large spatial and temporal extents. This makes them perfect candidates to apply deep learning methods. So far, these techniques have been successfully applied to image analysis through the use of convolutional neural networks. However, this is only one field of interest, and there is potential for many more use cases to be explored. The deep learning algorithms require fast access to large amounts of data in the form of tensors and make intensive use of CPU in order to train its models. The Australian National Computational Infrastructure (NCI) has recently augmented its Raijin 1.2 PFlop supercomputer with hardware accelerators. Together with NCI's 3000 core high performance OpenStack cloud, these computational systems have direct access to NCI's 10+ PBytes of datasets and associated Big Data software technologies (see http://geonetwork.nci.org.au/ and http://nci.org.au/systems-services/national-facility/nerdip/). To effectively use these computing infrastructures requires that both the data and software are organised in a way that readily supports the deep learning software ecosystem. Deep learning software, such as the open source TensorFlow library, has allowed us to demonstrate the possibility of generating geospatial models by combining information from

  10. Hot, deep origin of petroleum: deep basin evidence and application

    Science.gov (United States)

    Price, Leigh C.

    1978-01-01

    Use of the model of a hot deep origin of oil places rigid constraints on the migration and entrapment of crude oil. Specifically, oil originating from depth migrates vertically up faults and is emplaced in traps at shallower depths. Review of petroleum-producing basins worldwide shows oil occurrence in these basins conforms to the restraints of and therefore supports the hypothesis. Most of the world's oil is found in the very deepest sedimentary basins, and production over or adjacent to the deep basin is cut by or directly updip from faults dipping into the basin deep. Generally the greater the fault throw the greater the reserves. Fault-block highs next to deep sedimentary troughs are the best target areas by the present concept. Traps along major basin-forming faults are quite prospective. The structural style of a basin governs the distribution, types, and amounts of hydrocarbons expected and hence the exploration strategy. Production in delta depocenters (Niger) is in structures cut by or updip from major growth faults, and structures not associated with such faults are barren. Production in block fault basins is on horsts next to deep sedimentary troughs (Sirte, North Sea). In basins whose sediment thickness, structure and geologic history are known to a moderate degree, the main oil occurrences can be specifically predicted by analysis of fault systems and possible hydrocarbon migration routes. Use of the concept permits the identification of significant targets which have either been downgraded or ignored in the past, such as production in or just updip from thrust belts, stratigraphic traps over the deep basin associated with major faulting, production over the basin deep, and regional stratigraphic trapping updip from established production along major fault zones.

  11. Deep learning classification in asteroseismology using an improved neural network

    DEFF Research Database (Denmark)

    Hon, Marc; Stello, Dennis; Yu, Jie

    2018-01-01

    Deep learning in the form of 1D convolutional neural networks have previously been shown to be capable of efficiently classifying the evolutionary state of oscillating red giants into red giant branch stars and helium-core burning stars by recognizing visual features in their asteroseismic...... frequency spectra. We elaborate further on the deep learning method by developing an improved convolutional neural network classifier. To make our method useful for current and future space missions such as K2, TESS, and PLATO, we train classifiers that are able to classify the evolutionary states of lower...

  12. Erlotinib-induced rash spares previously irradiated skin

    International Nuclear Information System (INIS)

    Lips, Irene M.; Vonk, Ernest J.A.; Koster, Mariska E.Y.; Houwing, Ronald H.

    2011-01-01

    Erlotinib is an epidermal growth factor receptor inhibitor prescribed to patients with locally advanced or metastasized non-small cell lung carcinoma after failure of at least one earlier chemotherapy treatment. Approximately 75% of the patients treated with erlotinib develop acneiform skin rashes. A patient treated with erlotinib 3 months after finishing concomitant treatment with chemotherapy and radiotherapy for non-small cell lung cancer is presented. Unexpectedly, the part of the skin that had been included in his previously radiotherapy field was completely spared from the erlotinib-induced acneiform skin rash. The exact mechanism of erlotinib-induced rash sparing in previously irradiated skin is unclear. The underlying mechanism of this phenomenon needs to be explored further, because the number of patients being treated with a combination of both therapeutic modalities is increasing. The therapeutic effect of erlotinib in the area of the previously irradiated lesion should be assessed. (orig.)

  13. Reasoning with Previous Decisions: Beyond the Doctrine of Precedent

    DEFF Research Database (Denmark)

    Komárek, Jan

    2013-01-01

    in different jurisdictions use previous judicial decisions in their argument, we need to move beyond the concept of precedent to a wider notion, which would embrace practices and theories in legal systems outside the Common law tradition. This article presents the concept of ‘reasoning with previous decisions...... law method’, but they are no less rational and intellectually sophisticated. The reason for the rather conceited attitude of some comparatists is in the dominance of the common law paradigm of precedent and the accompanying ‘case law method’. If we want to understand how courts and lawyers......’ as such an alternative and develops its basic models. The article first points out several shortcomings inherent in limiting the inquiry into reasoning with previous decisions by the common law paradigm (1). On the basis of numerous examples provided in section (1), I will present two basic models of reasoning...

  14. [Prevalence of previously diagnosed diabetes mellitus in Mexico.

    Science.gov (United States)

    Rojas-Martínez, Rosalba; Basto-Abreu, Ana; Aguilar-Salinas, Carlos A; Zárate-Rojas, Emiliano; Villalpando, Salvador; Barrientos-Gutiérrez, Tonatiuh

    2018-01-01

    To compare the prevalence of previously diagnosed diabetes in 2016 with previous national surveys and to describe treatment and its complications. Mexico's national surveys Ensa 2000, Ensanut 2006, 2012 and 2016 were used. For 2016, logistic regression models and measures of central tendency and dispersion were obtained. The prevalence of previously diagnosed diabetes in 2016 was 9.4%. The increase of 2.2% relative to 2012 was not significant and only observed in patients older than 60 years. While preventive measures have increased, the access to medical treatment and lifestyle has not changed. The treatment has been modified, with an increase in insulin and decrease in hypoglycaemic agents. Population aging, lack of screening actions and the increase in diabetes complications will lead to an increase on the burden of disease. Policy measures targeting primary and secondary prevention of diabetes are crucial.

  15. First biological measurements of deep-sea corals from the Red Sea.

    Science.gov (United States)

    Roder, C; Berumen, M L; Bouwmeester, J; Papathanassiou, E; Al-Suwailem, A; Voolstra, C R

    2013-10-03

    It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with 'deep-sea' and 'cold-water' corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited.

  16. First biological measurements of deep-sea corals from the Red Sea.

    KAUST Repository

    Roder, Cornelia

    2013-10-03

    It is usually assumed that metabolic constraints restrict deep-sea corals to cold-water habitats, with \\'deep-sea\\' and \\'cold-water\\' corals often used as synonymous. Here we report on the first measurements of biological characters of deep-sea corals from the central Red Sea, where they occur at temperatures exceeding 20°C in highly oligotrophic and oxygen-limited waters. Low respiration rates, low calcification rates, and minimized tissue cover indicate that a reduced metabolism is one of the key adaptations to prevailing environmental conditions. We investigated four sites and encountered six species of which at least two appear to be undescribed. One species is previously reported from the Red Sea but occurs in deep cold waters outside the Red Sea raising interesting questions about presumed environmental constraints for other deep-sea corals. Our findings suggest that the present understanding of deep-sea coral persistence and resilience needs to be revisited.

  17. Cardiovascular magnetic resonance in adults with previous cardiovascular surgery.

    Science.gov (United States)

    von Knobelsdorff-Brenkenhoff, Florian; Trauzeddel, Ralf Felix; Schulz-Menger, Jeanette

    2014-03-01

    Cardiovascular magnetic resonance (CMR) is a versatile non-invasive imaging modality that serves a broad spectrum of indications in clinical cardiology and has proven evidence. Most of the numerous applications are appropriate in patients with previous cardiovascular surgery in the same manner as in non-surgical subjects. However, some specifics have to be considered. This review article is intended to provide information about the application of CMR in adults with previous cardiovascular surgery. In particular, the two main scenarios, i.e. following coronary artery bypass surgery and following heart valve surgery, are highlighted. Furthermore, several pictorial descriptions of other potential indications for CMR after cardiovascular surgery are given.

  18. How Stressful Is "Deep Bubbling"?

    Science.gov (United States)

    Tyrmi, Jaana; Laukkanen, Anne-Maria

    2017-03-01

    Water resistance therapy by phonating through a tube into the water is used to treat dysphonia. Deep submersion (≥10 cm in water, "deep bubbling") is used for hypofunctional voice disorders. Using it with caution is recommended to avoid vocal overloading. This experimental study aimed to investigate how strenuous "deep bubbling" is. Fourteen subjects, half of them with voice training, repeated the syllable [pa:] in comfortable speaking pitch and loudness, loudly, and in strained voice. Thereafter, they phonated a vowel-like sound both in comfortable loudness and loudly into a glass resonance tube immersed 10 cm into the water. Oral pressure, contact quotient (CQ, calculated from electroglottographic signal), and sound pressure level were studied. The peak oral pressure P(oral) during [p] and shuttering of the outer end of the tube was measured to estimate the subglottic pressure P(sub) and the mean P(oral) during vowel portions to enable calculation of transglottic pressure P(trans). Sensations during phonation were reported with an open-ended interview. P(sub) and P(oral) were higher in "deep bubbling" and P(trans) lower than in loud syllable phonation, but the CQ did not differ significantly. Similar results were obtained for the comparison between loud "deep bubbling" and strained phonation, although P(sub) did not differ significantly. Most of the subjects reported "deep bubbling" to be stressful only for respiratory and lip muscles. No big differences were found between trained and untrained subjects. The CQ values suggest that "deep bubbling" may increase vocal fold loading. Further studies should address impact stress during water resistance exercises. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

  19. Squamous cell carcinoma arising in previously burned or irradiated skin

    International Nuclear Information System (INIS)

    Edwards, M.J.; Hirsch, R.M.; Broadwater, J.R.; Netscher, D.T.; Ames, F.C.

    1989-01-01

    Squamous cell carcinoma (SCC) arising in previously burned or irradiated skin was reviewed in 66 patients treated between 1944 and 1986. Healing of the initial injury was complicated in 70% of patients. Mean interval from initial injury to diagnosis of SCC was 37 years. The overwhelming majority of patients presented with a chronic intractable ulcer in previously injured skin. The regional relapse rate after surgical excision was very high, 58% of all patients. Predominant patterns of recurrence were in local skin and regional lymph nodes (93% of recurrences). Survival rates at 5, 10, and 20 years were 52%, 34%, and 23%, respectively. Five-year survival rates in previously burned and irradiated patients were not significantly different (53% and 50%, respectively). This review, one of the largest reported series, better defines SCC arising in previously burned or irradiated skin as a locally aggressive disease that is distinct from SCC arising in sunlight-damaged skin. An increased awareness of the significance of chronic ulceration in scar tissue may allow earlier diagnosis. Regional disease control and survival depend on surgical resection of all known disease and may require radical lymph node dissection or amputation

  20. Outcome Of Pregnancy Following A Previous Lower Segment ...

    African Journals Online (AJOL)

    Background: A previous ceasarean section is an important variable that influences patient management in subsequent pregnancies. A trial of vaginal delivery in such patients is a feasible alternative to a secondary section, thus aiding to reduce the ceasarean section rate and its associated co-morbidities. Objective: To ...

  1. 24 CFR 1710.552 - Previously accepted state filings.

    Science.gov (United States)

    2010-04-01

    ... of Substantially Equivalent State Law § 1710.552 Previously accepted state filings. (a) Materials... and contracts or agreements contain notice of purchaser's revocation rights. In addition see § 1715.15..., unless the developer is obligated to do so in the contract. (b) If any such filing becomes inactive or...

  2. The job satisfaction of principals of previously disadvantaged schools

    African Journals Online (AJOL)

    The aim of this study was to identify influences on the job satisfaction of previously disadvantaged ..... I am still riding the cloud … I hope it lasts. .... as a way of creating a climate and culture in schools where individuals are willing to explore.

  3. Haemophilus influenzae type f meningitis in a previously healthy boy

    DEFF Research Database (Denmark)

    Ronit, Andreas; Berg, Ronan M G; Bruunsgaard, Helle

    2013-01-01

    Non-serotype b strains of Haemophilus influenzae are extremely rare causes of acute bacterial meningitis in immunocompetent individuals. We report a case of acute bacterial meningitis in a 14-year-old boy, who was previously healthy and had been immunised against H influenzae serotype b (Hib...

  4. Research Note Effects of previous cultivation on regeneration of ...

    African Journals Online (AJOL)

    We investigated the effects of previous cultivation on regeneration potential under miombo woodlands in a resettlement area, a spatial product of Zimbabwe's land reforms. We predicted that cultivation would affect population structure, regeneration, recruitment and potential grazing capacity of rangelands. Plant attributes ...

  5. Cryptococcal meningitis in a previously healthy child | Chimowa ...

    African Journals Online (AJOL)

    An 8-year-old previously healthy female presented with a 3 weeks history of headache, neck stiffness, deafness, fever and vomiting and was diagnosed with cryptococcal meningitis. She had documented hearing loss and was referred to tertiary-level care after treatment with fluconazole did not improve her neurological ...

  6. Investigation of previously derived Hyades, Coma, and M67 reddenings

    International Nuclear Information System (INIS)

    Taylor, B.J.

    1980-01-01

    New Hyades polarimetry and field star photometry have been obtained to check the Hyades reddening, which was found to be nonzero in a previous paper. The new Hyades polarimetry implies essentially zero reddening; this is also true of polarimetry published by Behr (which was incorrectly interpreted in the previous paper). Four photometric techniques which are presumed to be insensitive to blanketing are used to compare the Hyades to nearby field stars; these four techniques also yield essentially zero reddening. When all of these results are combined with others which the author has previously published and a simultaneous solution for the Hyades, Coma, and M67 reddenings is made, the results are E (B-V) =3 +- 2 (sigma) mmag, -1 +- 3 (sigma) mmag, and 46 +- 6 (sigma) mmag, respectively. No support for a nonzero Hyades reddening is offered by the new results. When the newly obtained reddenings for the Hyades, Coma, and M67 are compared with results from techniques given by Crawford and by users of the David Dunlap Observatory photometric system, no differences between the new and other reddenings are found which are larger than about 2 sigma. The author had previously found that the M67 main-sequence stars have about the same blanketing as that of Coma and less blanketing than the Hyades; this conclusion is essentially unchanged by the revised reddenings

  7. Rapid fish stock depletion in previously unexploited seamounts: the ...

    African Journals Online (AJOL)

    Rapid fish stock depletion in previously unexploited seamounts: the case of Beryx splendens from the Sierra Leone Rise (Gulf of Guinea) ... A spectral analysis and red-noise spectra procedure (REDFIT) algorithm was used to identify the red-noise spectrum from the gaps in the observed time-series of catch per unit effort by ...

  8. 18 CFR 154.302 - Previously submitted material.

    Science.gov (United States)

    2010-04-01

    ... 18 Conservation of Power and Water Resources 1 2010-04-01 2010-04-01 false Previously submitted material. 154.302 Section 154.302 Conservation of Power and Water Resources FEDERAL ENERGY REGULATORY... concurrently with the rate change filing. There must be furnished to the Director, Office of Energy Market...

  9. Process cells dismantling of EUREX pant: previous activities

    International Nuclear Information System (INIS)

    Gili, M.

    1998-01-01

    In the '98-'99 period some process cells of the EUREX pant will be dismantled, in order to place there the liquid wastes conditioning plant 'CORA'. This report resumes the previous activities (plant rinsing campaigns and inactive Cell 014 dismantling), run in the past three years and the drawn experience [it

  10. The job satisfaction of principals of previously disadvantaged schools

    African Journals Online (AJOL)

    The aim of this study was to identify influences on the job satisfaction of previously disadvantaged school principals in North-West Province. Evans's theory of job satisfaction, morale and motivation was useful as a conceptual framework. A mixedmethods explanatory research design was important in discovering issues with ...

  11. Obstructive pulmonary disease in patients with previous tuberculosis ...

    African Journals Online (AJOL)

    Obstructive pulmonary disease in patients with previous tuberculosis: Pathophysiology of a community-based cohort. B.W. Allwood, R Gillespie, M Galperin-Aizenberg, M Bateman, H Olckers, L Taborda-Barata, G.L. Calligaro, Q Said-Hartley, R van Zyl-Smit, C.B. Cooper, E van Rikxoort, J Goldin, N Beyers, E.D. Bateman ...

  12. Abiraterone in metastatic prostate cancer without previous chemotherapy

    NARCIS (Netherlands)

    Ryan, Charles J.; Smith, Matthew R.; de Bono, Johann S.; Molina, Arturo; Logothetis, Christopher J.; de Souza, Paul; Fizazi, Karim; Mainwaring, Paul; Piulats, Josep M.; Ng, Siobhan; Carles, Joan; Mulders, Peter F. A.; Basch, Ethan; Small, Eric J.; Saad, Fred; Schrijvers, Dirk; van Poppel, Hendrik; Mukherjee, Som D.; Suttmann, Henrik; Gerritsen, Winald R.; Flaig, Thomas W.; George, Daniel J.; Yu, Evan Y.; Efstathiou, Eleni; Pantuck, Allan; Winquist, Eric; Higano, Celestia S.; Taplin, Mary-Ellen; Park, Youn; Kheoh, Thian; Griffin, Thomas; Scher, Howard I.; Rathkopf, Dana E.; Boyce, A.; Costello, A.; Davis, I.; Ganju, V.; Horvath, L.; Lynch, R.; Marx, G.; Parnis, F.; Shapiro, J.; Singhal, N.; Slancar, M.; van Hazel, G.; Wong, S.; Yip, D.; Carpentier, P.; Luyten, D.; de Reijke, T.

    2013-01-01

    Abiraterone acetate, an androgen biosynthesis inhibitor, improves overall survival in patients with metastatic castration-resistant prostate cancer after chemotherapy. We evaluated this agent in patients who had not received previous chemotherapy. In this double-blind study, we randomly assigned

  13. Response to health insurance by previously uninsured rural children.

    Science.gov (United States)

    Tilford, J M; Robbins, J M; Shema, S J; Farmer, F L

    1999-08-01

    To examine the healthcare utilization and costs of previously uninsured rural children. Four years of claims data from a school-based health insurance program located in the Mississippi Delta. All children who were not Medicaid-eligible or were uninsured, were eligible for limited benefits under the program. The 1987 National Medical Expenditure Survey (NMES) was used to compare utilization of services. The study represents a natural experiment in the provision of insurance benefits to a previously uninsured population. Premiums for the claims cost were set with little or no information on expected use of services. Claims from the insurer were used to form a panel data set. Mixed model logistic and linear regressions were estimated to determine the response to insurance for several categories of health services. The use of services increased over time and approached the level of utilization in the NMES. Conditional medical expenditures also increased over time. Actuarial estimates of claims cost greatly exceeded actual claims cost. The provision of a limited medical, dental, and optical benefit package cost approximately $20-$24 per member per month in claims paid. An important uncertainty in providing health insurance to previously uninsured populations is whether a pent-up demand exists for health services. Evidence of a pent-up demand for medical services was not supported in this study of rural school-age children. States considering partnerships with private insurers to implement the State Children's Health Insurance Program could lower premium costs by assembling basic data on previously uninsured children.

  14. Reoperative sentinel lymph node biopsy after previous mastectomy.

    Science.gov (United States)

    Karam, Amer; Stempel, Michelle; Cody, Hiram S; Port, Elisa R

    2008-10-01

    Sentinel lymph node (SLN) biopsy is the standard of care for axillary staging in breast cancer, but many clinical scenarios questioning the validity of SLN biopsy remain. Here we describe our experience with reoperative-SLN (re-SLN) biopsy after previous mastectomy. Review of the SLN database from September 1996 to December 2007 yielded 20 procedures done in the setting of previous mastectomy. SLN biopsy was performed using radioisotope with or without blue dye injection superior to the mastectomy incision, in the skin flap in all patients. In 17 of 20 patients (85%), re-SLN biopsy was performed for local or regional recurrence after mastectomy. Re-SLN biopsy was successful in 13 of 20 patients (65%) after previous mastectomy. Of the 13 patients, 2 had positive re-SLN, and completion axillary dissection was performed, with 1 having additional positive nodes. In the 11 patients with negative re-SLN, 2 patients underwent completion axillary dissection demonstrating additional negative nodes. One patient with a negative re-SLN experienced chest wall recurrence combined with axillary recurrence 11 months after re-SLN biopsy. All others remained free of local or axillary recurrence. Re-SLN biopsy was unsuccessful in 7 of 20 patients (35%). In three of seven patients, axillary dissection was performed, yielding positive nodes in two of the three. The remaining four of seven patients all had previous modified radical mastectomy, so underwent no additional axillary surgery. In this small series, re-SLN was successful after previous mastectomy, and this procedure may play some role when axillary staging is warranted after mastectomy.

  15. Deep Sludge Gas Release Event Analytical Evaluation

    International Nuclear Information System (INIS)

    Sams, Terry L.

    2013-01-01

    Long Abstract. Full Text. The purpose of the Deep Sludge Gas Release Event Analytical Evaluation (DSGRE-AE) is to evaluate the postulated hypothesis that a hydrogen GRE may occur in Hanford tanks containing waste sludges at levels greater than previously experienced. There is a need to understand gas retention and release hazards in sludge beds which are 200 -300 inches deep. These sludge beds are deeper than historical Hanford sludge waste beds, and are created when waste is retrieved from older single-shell tanks (SST) and transferred to newer double-shell tanks (DST).Retrieval of waste from SSTs reduces the risk to the environment from leakage or potential leakage of waste into the ground from these tanks. However, the possibility of an energetic event (flammable gas accident) in the retrieval receiver DST is worse than slow leakage. Lines of inquiry, therefore, are (1) can sludge waste be stored safely in deep beds; (2) can gas release events (GRE) be prevented by periodically degassing the sludge (e.g., mixer pump); or (3) does the retrieval strategy need to be altered to limit sludge bed height by retrieving into additional DSTs? The scope of this effort is to provide expert advice on whether or not to move forward with the generation of deep beds of sludge through retrieval of C-Farm tanks. Evaluation of possible mitigation methods (e.g., using mixer pumps to release gas, retrieving into an additional DST) are being evaluated by a second team and are not discussed in this report. While available data and engineering judgment indicate that increased gas retention (retained gas fraction) in DST sludge at depths resulting from the completion of SST 241-C Tank Farm retrievals is not expected and, even if gas releases were to occur, they would be small and local, a positive USQ was declared (Occurrence Report EM-RP--WRPS-TANKFARM-2012-0014, 'Potential Exists for a Large Spontaneous Gas Release Event in Deep Settled Waste Sludge'). The purpose of this technical

  16. Accelerating Deep Learning with Shrinkage and Recall

    OpenAIRE

    Zheng, Shuai; Vishnu, Abhinav; Ding, Chris

    2016-01-01

    Deep Learning is a very powerful machine learning model. Deep Learning trains a large number of parameters for multiple layers and is very slow when data is in large scale and the architecture size is large. Inspired from the shrinking technique used in accelerating computation of Support Vector Machines (SVM) algorithm and screening technique used in LASSO, we propose a shrinking Deep Learning with recall (sDLr) approach to speed up deep learning computation. We experiment shrinking Deep Lea...

  17. What Really is Deep Learning Doing?

    OpenAIRE

    Xiong, Chuyu

    2017-01-01

    Deep learning has achieved a great success in many areas, from computer vision to natural language processing, to game playing, and much more. Yet, what deep learning is really doing is still an open question. There are a lot of works in this direction. For example, [5] tried to explain deep learning by group renormalization, and [6] tried to explain deep learning from the view of functional approximation. In order to address this very crucial question, here we see deep learning from perspect...

  18. [Fatal amnioinfusion with previous choriocarcinoma in a parturient woman].

    Science.gov (United States)

    Hrgović, Z; Bukovic, D; Mrcela, M; Hrgović, I; Siebzehnrübl, E; Karelovic, D

    2004-04-01

    The case of 36-year-old tercipare is described who developed choriocharcinoma in a previous pregnancy. During the first term labour the patient developed cardiac arrest, so reanimation and sectio cesarea was performed. A male new-born was delivered in good condition, but even after intensive therapy and reanimation occurred death of parturient woman with picture of disseminate intravascular coagulopathia (DIK). On autopsy and on histology there was no sign of malignant disease, so it was not possible to connect previous choricarcinoma with amniotic fluid embolism. Maybe was place of choriocarcinoma "locus minoris resistentiae" which later resulted with failure in placentation what was hard to prove. On autopsy we found embolia of lung with a microthrombosis of terminal circulation with punctiformis bleeding in mucous, what stands for DIK.

  19. Challenging previous conceptions of vegetarianism and eating disorders.

    Science.gov (United States)

    Fisak, B; Peterson, R D; Tantleff-Dunn, S; Molnar, J M

    2006-12-01

    The purpose of this study was to replicate and expand upon previous research that has examined the potential association between vegetarianism and disordered eating. Limitations of previous research studies are addressed, including possible low reliability of measures of eating pathology within vegetarian samples, use of only a few dietary restraint measures, and a paucity of research examining potential differences in body image and food choice motives of vegetarians versus nonvegetarians. Two hundred and fifty-six college students completed a number of measures of eating pathology and body image, and a food choice motives questionnaire. Interestingly, no significant differences were found between vegetarians and nonvegetarians in measures of eating pathology or body image. However, significant differences in food choice motives were found. Implications for both researchers and clinicians are discussed.

  20. Previous climatic alterations are caused by the sun

    International Nuclear Information System (INIS)

    Groenaas, Sigbjoern

    2003-01-01

    The article surveys the scientific results of previous research into the contribution of the sun to climatic alterations. The author concludes that there is evidence of eight cold periods after the last ice age and that the alterations largely were due to climate effects from the sun. However, these effects are only causing a fraction of the registered global warming. It is assumed that the human activities are contributing to the rest of the greenhouse effect

  1. Influence of previous knowledge in Torrance tests of creative thinking

    OpenAIRE

    Aranguren, María; Consejo Nacional de Investigaciones Científicas y Técnicas CONICET

    2015-01-01

    The aim of this work is to analyze the influence of study field, expertise and recreational activities participation in Torrance Tests of Creative Thinking (TTCT, 1974) performance. Several hypotheses were postulated to explore the possible effects of previous knowledge in TTCT verbal and TTCT figural university students’ outcomes. Participants in this study included 418 students from five study fields: Psychology;Philosophy and Literature, Music; Engineering; and Journalism and Advertisin...

  2. Opportunities and obstacles for deep learning in biology and medicine

    Science.gov (United States)

    2018-01-01

    Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems—patient classification, fundamental biological processes and treatment of patients—and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine. PMID:29618526

  3. Opportunities and obstacles for deep learning in biology and medicine.

    Science.gov (United States)

    Ching, Travers; Himmelstein, Daniel S; Beaulieu-Jones, Brett K; Kalinin, Alexandr A; Do, Brian T; Way, Gregory P; Ferrero, Enrico; Agapow, Paul-Michael; Zietz, Michael; Hoffman, Michael M; Xie, Wei; Rosen, Gail L; Lengerich, Benjamin J; Israeli, Johnny; Lanchantin, Jack; Woloszynek, Stephen; Carpenter, Anne E; Shrikumar, Avanti; Xu, Jinbo; Cofer, Evan M; Lavender, Christopher A; Turaga, Srinivas C; Alexandari, Amr M; Lu, Zhiyong; Harris, David J; DeCaprio, Dave; Qi, Yanjun; Kundaje, Anshul; Peng, Yifan; Wiley, Laura K; Segler, Marwin H S; Boca, Simina M; Swamidass, S Joshua; Huang, Austin; Gitter, Anthony; Greene, Casey S

    2018-04-01

    Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine. © 2018 The Authors.

  4. Deep Learning and Bayesian Methods

    Directory of Open Access Journals (Sweden)

    Prosper Harrison B.

    2017-01-01

    Full Text Available A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding. Particle physicists have taken notice and have started to deploy these methods, achieving results that suggest a potentially significant shift in how data might be analyzed in the not too distant future. We discuss a few recent developments in the application of deep neural networks and then indulge in speculation about how such methods might be used to automate certain aspects of data analysis in particle physics. Next, the connection to Bayesian methods is discussed and the paper ends with thoughts on a significant practical issue, namely, how, from a Bayesian perspective, one might optimize the construction of deep neural networks.

  5. Deep Learning in Drug Discovery.

    Science.gov (United States)

    Gawehn, Erik; Hiss, Jan A; Schneider, Gisbert

    2016-01-01

    Artificial neural networks had their first heyday in molecular informatics and drug discovery approximately two decades ago. Currently, we are witnessing renewed interest in adapting advanced neural network architectures for pharmaceutical research by borrowing from the field of "deep learning". Compared with some of the other life sciences, their application in drug discovery is still limited. Here, we provide an overview of this emerging field of molecular informatics, present the basic concepts of prominent deep learning methods and offer motivation to explore these techniques for their usefulness in computer-assisted drug discovery and design. We specifically emphasize deep neural networks, restricted Boltzmann machine networks and convolutional networks. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Eric Davidson and deep time.

    Science.gov (United States)

    Erwin, Douglas H

    2017-10-13

    Eric Davidson had a deep and abiding interest in the role developmental mechanisms played in generating evolutionary patterns documented in deep time, from the origin of the euechinoids to the processes responsible for the morphological architectures of major animal clades. Although not an evolutionary biologist, Davidson's interests long preceded the current excitement over comparative evolutionary developmental biology. Here I discuss three aspects at the intersection between his research and evolutionary patterns in deep time: First, understanding the mechanisms of body plan formation, particularly those associated with the early diversification of major metazoan clades. Second, a critique of early claims about ancestral metazoans based on the discoveries of highly conserved genes across bilaterian animals. Third, Davidson's own involvement in paleontology through a collaborative study of the fossil embryos from the Ediacaran Doushantuo Formation in south China.

  7. Analysis of previous screening examinations for patients with breast cancer

    International Nuclear Information System (INIS)

    Lee, Eun Hye; Cha, Joo Hee; Han, Dae Hee; Choi, Young Ho; Hwang, Ki Tae; Ryu, Dae Sik; Kwak, Jin Ho; Moon, Woo Kyung

    2007-01-01

    We wanted to improve the quality of subsequent screening by reviewing the previous screening of breast cancer patients. Twenty-four breast cancer patients who underwent previous screening were enrolled. All 24 took mammograms and 15 patients also took sonograms. We reviewed the screening retrospectively according to the BI-RADS criteria and we categorized the results into false negative, true negative, true positive and occult cancers. We also categorized the causes of false negative cancers into misperception, misinterpretation and technical factors and then we analyzed the attributing factors. Review of the previous screening revealed 66.7% (16/24) false negative, 25.0% (6/24) true negative, and 8.3% (2/24) true positive cancers. False negative cancers were caused by the mammogram in 56.3% (9/16) and by the sonogram in 43.7% (7/16). For the false negative cases, all of misperception were related with mammograms and this was attributed to dense breast, a lesion located at the edge of glandular tissue or the image, and findings seen on one view only. Almost all misinterpretations were related with sonograms and attributed to loose application of the final assessment. To improve the quality of breast screening, it is essential to overcome the main causes of false negative examinations, including misperception and misinterpretation. We need systematic education and strict application of final assessment categories of BI-RADS. For effective communication among physicians, it is also necessary to properly educate them about BI-RADS

  8. Deep Learning in Gastrointestinal Endoscopy.

    Science.gov (United States)

    Patel, Vivek; Armstrong, David; Ganguli, Malika; Roopra, Sandeep; Kantipudi, Neha; Albashir, Siwar; Kamath, Markad V

    2016-01-01

    Gastrointestinal (GI) endoscopy is used to inspect the lumen or interior of the GI tract for several purposes, including, (1) making a clinical diagnosis, in real time, based on the visual appearances; (2) taking targeted tissue samples for subsequent histopathological examination; and (3) in some cases, performing therapeutic interventions targeted at specific lesions. GI endoscopy is therefore predicated on the assumption that the operator-the endoscopist-is able to identify and characterize abnormalities or lesions accurately and reproducibly. However, as in other areas of clinical medicine, such as histopathology and radiology, many studies have documented marked interobserver and intraobserver variability in lesion recognition. Thus, there is a clear need and opportunity for techniques or methodologies that will enhance the quality of lesion recognition and diagnosis and improve the outcomes of GI endoscopy. Deep learning models provide a basis to make better clinical decisions in medical image analysis. Biomedical image segmentation, classification, and registration can be improved with deep learning. Recent evidence suggests that the application of deep learning methods to medical image analysis can contribute significantly to computer-aided diagnosis. Deep learning models are usually considered to be more flexible and provide reliable solutions for image analysis problems compared to conventional computer vision models. The use of fast computers offers the possibility of real-time support that is important for endoscopic diagnosis, which has to be made in real time. Advanced graphics processing units and cloud computing have also favored the use of machine learning, and more particularly, deep learning for patient care. This paper reviews the rapidly evolving literature on the feasibility of applying deep learning algorithms to endoscopic imaging.

  9. Deep mycoses in Amazon region.

    Science.gov (United States)

    Talhari, S; Cunha, M G; Schettini, A P; Talhari, A C

    1988-09-01

    Patients with deep mycoses diagnosed in dermatologic clinics of Manaus (state of Amazonas, Brazil) were studied from November 1973 to December 1983. They came from the Brazilian states of Amazonas, Pará, Acre, and Rondônia and the Federal Territory of Roraima. All of these regions, with the exception of Pará, are situated in the western part of the Amazon Basin. The climatic conditions in this region are almost the same: tropical forest, high rainfall, and mean annual temperature of 26C. The deep mycoses diagnosed, in order of frequency, were Jorge Lobo's disease, paracoccidioidomycosis, chromomycosis, sporotrichosis, mycetoma, cryptococcosis, zygomycosis, and histoplasmosis.

  10. Producing deep-water hydrocarbons

    International Nuclear Information System (INIS)

    Pilenko, Thierry

    2011-01-01

    Several studies relate the history and progress made in offshore production from oil and gas fields in relation to reserves and the techniques for producing oil offshore. The intention herein is not to review these studies but rather to argue that the activities of prospecting and producing deep-water oil and gas call for a combination of technology and project management and, above all, of devotion and innovation. Without this sense of commitment motivating men and women in this industry, the human adventure of deep-water production would never have taken place

  11. DeepSimulator: a deep simulator for Nanopore sequencing

    KAUST Repository

    Li, Yu

    2017-12-23

    Motivation: Oxford Nanopore sequencing is a rapidly developed sequencing technology in recent years. To keep pace with the explosion of the downstream data analytical tools, a versatile Nanopore sequencing simulator is needed to complement the experimental data as well as to benchmark those newly developed tools. However, all the currently available simulators are based on simple statistics of the produced reads, which have difficulty in capturing the complex nature of the Nanopore sequencing procedure, the main task of which is the generation of raw electrical current signals. Results: Here we propose a deep learning based simulator, DeepSimulator, to mimic the entire pipeline of Nanopore sequencing. Starting from a given reference genome or assembled contigs, we simulate the electrical current signals by a context-dependent deep learning model, followed by a base-calling procedure to yield simulated reads. This workflow mimics the sequencing procedure more naturally. The thorough experiments performed across four species show that the signals generated by our context-dependent model are more similar to the experimentally obtained signals than the ones generated by the official context-independent pore model. In terms of the simulated reads, we provide a parameter interface to users so that they can obtain the reads with different accuracies ranging from 83% to 97%. The reads generated by the default parameter have almost the same properties as the real data. Two case studies demonstrate the application of DeepSimulator to benefit the development of tools in de novo assembly and in low coverage SNP detection. Availability: The software can be accessed freely at: https://github.com/lykaust15/DeepSimulator.

  12. Stimulation Technologies for Deep Well Completions

    Energy Technology Data Exchange (ETDEWEB)

    None

    2003-09-30

    The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a study to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. An assessment of historical deep gas well drilling activity and forecast of future trends was completed during the first six months of the project; this segment of the project was covered in Technical Project Report No. 1. The second progress report covers the next six months of the project during which efforts were primarily split between summarizing rock mechanics and fracture growth in deep reservoirs and contacting operators about case studies of deep gas well stimulation.

  13. STIMULATION TECHNOLOGIES FOR DEEP WELL COMPLETIONS

    Energy Technology Data Exchange (ETDEWEB)

    Stephen Wolhart

    2003-06-01

    The Department of Energy (DOE) is sponsoring a Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies is conducting a project to evaluate the stimulation of deep wells. The objective of the project is to assess U.S. deep well drilling & stimulation activity, review rock mechanics & fracture growth in deep, high pressure/temperature wells and evaluate stimulation technology in several key deep plays. Phase 1 was recently completed and consisted of assessing deep gas well drilling activity (1995-2007) and an industry survey on deep gas well stimulation practices by region. Of the 29,000 oil, gas and dry holes drilled in 2002, about 300 were drilled in the deep well; 25% were dry, 50% were high temperature/high pressure completions and 25% were simply deep completions. South Texas has about 30% of these wells, Oklahoma 20%, Gulf of Mexico Shelf 15% and the Gulf Coast about 15%. The Rockies represent only 2% of deep drilling. Of the 60 operators who drill deep and HTHP wells, the top 20 drill almost 80% of the wells. Six operators drill half the U.S. deep wells. Deep drilling peaked at 425 wells in 1998 and fell to 250 in 1999. Drilling is expected to rise through 2004 after which drilling should cycle down as overall drilling declines.

  14. Moyamoya disease in a child with previous acute necrotizing encephalopathy

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Taik-Kun; Cha, Sang Hoon; Chung, Kyoo Byung; Kim, Jung Hyuck; Kim, Baek Hyun; Chung, Hwan Hoon [Department of Diagnostic Radiology, Korea University College of Medicine, Ansan Hospital, 516 Kojan-Dong, Ansan City, Kyungki-Do 425-020 (Korea); Eun, Baik-Lin [Department of Pediatrics, Korea University College of Medicine, Seoul (Korea)

    2003-09-01

    A previously healthy 24-day-old boy presented with a 2-day history of fever and had a convulsion on the day of admission. MRI showed abnormal signal in the thalami, caudate nuclei and central white matter. Acute necrotising encephalopathy was diagnosed, other causes having been excluded after biochemical and haematological analysis of blood, urine and CSF. He recovered, but with spastic quadriparesis. At the age of 28 months, he suffered sudden deterioration of consciousness and motor weakness of his right limbs. MRI was consistent with an acute cerebrovascular accident. Angiography showed bilateral middle cerebral artery stenosis or frank occlusion with numerous lenticulostriate collateral vessels consistent with moyamoya disease. (orig.)

  15. MCNP HPGe detector benchmark with previously validated Cyltran model.

    Science.gov (United States)

    Hau, I D; Russ, W R; Bronson, F

    2009-05-01

    An exact copy of the detector model generated for Cyltran was reproduced as an MCNP input file and the detection efficiency was calculated similarly with the methodology used in previous experimental measurements and simulation of a 280 cm(3) HPGe detector. Below 1000 keV the MCNP data correlated to the Cyltran results within 0.5% while above this energy the difference between MCNP and Cyltran increased to about 6% at 4800 keV, depending on the electron cut-off energy.

  16. HEART TRANSPLANTATION IN PATIENTS WITH PREVIOUS OPEN HEART SURGERY

    Directory of Open Access Journals (Sweden)

    R. Sh. Saitgareev

    2016-01-01

    Full Text Available Heart Transplantation (HTx to date remains the most effective and radical method of treatment of patients with end-stage heart failure. The defi cit of donor hearts is forcing to resort increasingly to the use of different longterm mechanical circulatory support systems, including as a «bridge» to the follow-up HTx. According to the ISHLT Registry the number of recipients underwent cardiopulmonary bypass surgery increased from 40% in the period from 2004 to 2008 to 49.6% for the period from 2009 to 2015. HTx performed in repeated patients, on the one hand, involves considerable technical diffi culties and high risks; on the other hand, there is often no alternative medical intervention to HTx, and if not dictated by absolute contradictions the denial of the surgery is equivalent to 100% mortality. This review summarizes the results of a number of published studies aimed at understanding the immediate and late results of HTx in patients, previously underwent open heart surgery. The effect of resternotomy during HTx and that of the specifi c features associated with its implementation in recipients previously operated on open heart, and its effects on the immediate and long-term survival were considered in this review. Results of studies analyzing the risk factors for perioperative complications in repeated recipients were also demonstrated. Separately, HTx risks after implantation of prolonged mechanical circulatory support systems were examined. The literature does not allow to clearly defi ning the impact factor of earlier performed open heart surgery on the course of perioperative period and on the prognosis of survival in recipients who underwent HTx. On the other hand, subject to the regular fl ow of HTx and the perioperative period the risks in this clinical situation are justifi ed as a long-term prognosis of recipients previously conducted open heart surgery and are comparable to those of patients who underwent primary HTx. Studies

  17. Deep Space Climate Observatory (DSCOVR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Deep Space Climate ObserVatoRy (DSCOVR) satellite is a NOAA operated asset at the first Lagrange (L1) point. The primary space weather instrument is the PlasMag...

  18. Ploughing the deep sea floor.

    Science.gov (United States)

    Puig, Pere; Canals, Miquel; Company, Joan B; Martín, Jacobo; Amblas, David; Lastras, Galderic; Palanques, Albert

    2012-09-13

    Bottom trawling is a non-selective commercial fishing technique whereby heavy nets and gear are pulled along the sea floor. The direct impact of this technique on fish populations and benthic communities has received much attention, but trawling can also modify the physical properties of seafloor sediments, water–sediment chemical exchanges and sediment fluxes. Most of the studies addressing the physical disturbances of trawl gear on the seabed have been undertaken in coastal and shelf environments, however, where the capacity of trawling to modify the seafloor morphology coexists with high-energy natural processes driving sediment erosion, transport and deposition. Here we show that on upper continental slopes, the reworking of the deep sea floor by trawling gradually modifies the shape of the submarine landscape over large spatial scales. We found that trawling-induced sediment displacement and removal from fishing grounds causes the morphology of the deep sea floor to become smoother over time, reducing its original complexity as shown by high-resolution seafloor relief maps. Our results suggest that in recent decades, following the industrialization of fishing fleets, bottom trawling has become an important driver of deep seascape evolution. Given the global dimension of this type of fishery, we anticipate that the morphology of the upper continental slope in many parts of the world’s oceans could be altered by intensive bottom trawling, producing comparable effects on the deep sea floor to those generated by agricultural ploughing on land.

  19. FOSTERING DEEP LEARNING AMONGST ENTREPRENEURSHIP ...

    African Journals Online (AJOL)

    An important prerequisite for this important objective to be achieved is that lecturers ensure that students adopt a deep learning approach towards entrepreneurship courses been taught, as this will enable them to truly understand key entrepreneurial concepts and strategies and how they can be implemented in the real ...

  20. Deep Space Gateway "Recycler" Mission

    Science.gov (United States)

    Graham, L.; Fries, M.; Hamilton, J.; Landis, R.; John, K.; O'Hara, W.

    2018-02-01

    Use of the Deep Space Gateway provides a hub for a reusable planetary sample return vehicle for missions to gather star dust as well as samples from various parts of the solar system including main belt asteroids, near-Earth asteroids, and Mars moon.

  1. Deep freezers with heat recovery

    Energy Technology Data Exchange (ETDEWEB)

    Kistler, J.

    1981-09-02

    Together with space and water heating systems, deep freezers are the biggest energy consumers in households. The article investigates the possibility of using the waste heat for water heating. The design principle of such a system is presented in a wiring diagram.

  2. A Deep-Sea Simulation.

    Science.gov (United States)

    Montes, Georgia E.

    1997-01-01

    Describes an activity that simulates exploration techniques used in deep-sea explorations and teaches students how this technology can be used to take a closer look inside volcanoes, inspect hazardous waste sites such as nuclear reactors, and explore other environments dangerous to humans. (DDR)

  3. Barbabos Deep-Water Sponges

    NARCIS (Netherlands)

    Soest, van R.W.M.; Stentoft, N.

    1988-01-01

    Deep-water sponges dredged up in two locations off the west coast of Barbados are systematically described. A total of 69 species is recorded, among which 16 are new to science, viz. Pachymatisma geodiformis, Asteropus syringiferus, Cinachyra arenosa, Theonella atlantica. Corallistes paratypus,

  4. Deep learning for visual understanding

    NARCIS (Netherlands)

    Guo, Y.

    2017-01-01

    With the dramatic growth of the image data on the web, there is an increasing demand of the algorithms capable of understanding the visual information automatically. Deep learning, served as one of the most significant breakthroughs, has brought revolutionary success in diverse visual applications,

  5. Deep-Sky Video Astronomy

    CERN Document Server

    Massey, Steve

    2009-01-01

    A guide to using modern integrating video cameras for deep-sky viewing and imaging with the kinds of modest telescopes available commercially to amateur astronomers. It includes an introduction and a brief history of the technology and camera types. It examines the pros and cons of this unrefrigerated yet highly efficient technology

  6. DM Considerations for Deep Drilling

    OpenAIRE

    Dubois-Felsmann, Gregory

    2016-01-01

    An outline of the current situation regarding the DM plans for the Deep Drilling surveys and an invitation to the community to provide feedback on what they would like to see included in the data processing and visualization of these surveys.

  7. Lessons from Earth's Deep Time

    Science.gov (United States)

    Soreghan, G. S.

    2005-01-01

    Earth is a repository of data on climatic changes from its deep-time history. Article discusses the collection and study of these data to predict future climatic changes, the need to create national study centers for the purpose, and the necessary cooperation between different branches of science in climatic research.

  8. Digging Deeper: The Deep Web.

    Science.gov (United States)

    Turner, Laura

    2001-01-01

    Focuses on the Deep Web, defined as Web content in searchable databases of the type that can be found only by direct query. Discusses the problems of indexing; inability to find information not indexed in the search engine's database; and metasearch engines. Describes 10 sites created to access online databases or directly search them. Lists ways…

  9. Deep Learning and Music Adversaries

    DEFF Research Database (Denmark)

    Kereliuk, Corey Mose; Sturm, Bob L.; Larsen, Jan

    2015-01-01

    the minimal perturbation of the input image such that the system misclassifies it with high confidence. We adapt this approach to construct and deploy an adversary of deep learning systems applied to music content analysis. In our case, however, the system inputs are magnitude spectral frames, which require...

  10. Proteomics Analysis Reveals Previously Uncharacterized Virulence Factors in Vibrio proteolyticus

    Directory of Open Access Journals (Sweden)

    Ann Ray

    2016-07-01

    Full Text Available Members of the genus Vibrio include many pathogens of humans and marine animals that share genetic information via horizontal gene transfer. Hence, the Vibrio pan-genome carries the potential to establish new pathogenic strains by sharing virulence determinants, many of which have yet to be characterized. Here, we investigated the virulence properties of Vibrio proteolyticus, a Gram-negative marine bacterium previously identified as part of the Vibrio consortium isolated from diseased corals. We found that V. proteolyticus causes actin cytoskeleton rearrangements followed by cell lysis in HeLa cells in a contact-independent manner. In search of the responsible virulence factor involved, we determined the V. proteolyticus secretome. This proteomics approach revealed various putative virulence factors, including active type VI secretion systems and effectors with virulence toxin domains; however, these type VI secretion systems were not responsible for the observed cytotoxic effects. Further examination of the V. proteolyticus secretome led us to hypothesize and subsequently demonstrate that a secreted hemolysin, belonging to a previously uncharacterized clan of the leukocidin superfamily, was the toxin responsible for the V. proteolyticus-mediated cytotoxicity in both HeLa cells and macrophages. Clearly, there remains an armory of yet-to-be-discovered virulence factors in the Vibrio pan-genome that will undoubtedly provide a wealth of knowledge on how a pathogen can manipulate host cells.

  11. Incidence of Acneform Lesions in Previously Chemically Damaged Persons-2004

    Directory of Open Access Journals (Sweden)

    N Dabiri

    2008-04-01

    Full Text Available ABSTRACT: Introduction & Objective: Chemical gas weapons especially nitrogen mustard which was used in Iraq-Iran war against Iranian troops have several harmful effects on skin. Some other chemical agents also can cause acne form lesions on skin. The purpose of this study was to compare the incidence of acneform in previously chemically damaged soldiers and non chemically damaged persons. Materials & Methods: In this descriptive and analytical study, 180 chemically damaged soldiers, who have been referred to dermatology clinic between 2000 – 2004, and forty non-chemically damaged people, were chosen randomly and examined for acneform lesions. SPSS software was used for statistic analysis of the data. Results: The mean age of the experimental group was 37.5 ± 5.2 and that of the control group was 38.7 ± 5.9 years. The mean percentage of chemical damage in cases was 31 percent and the time after the chemical damage was 15.2 ± 1.1 years. Ninety seven cases (53.9 percent of the subjects and 19 people (47.5 percent of the control group had some degree of acne. No significant correlation was found in incidence, degree of lesions, site of lesions and age of subjects between two groups. No significant correlation was noted between percentage of chemical damage and incidence and degree of lesions in case group. Conclusion: Incidence of acneform lesions among previously chemically injured peoples was not higher than the normal cases.

  12. Relationship of deer and moose populations to previous winters' snow

    Science.gov (United States)

    Mech, L.D.; McRoberts, R.E.; Peterson, R.O.; Page, R.E.

    1987-01-01

    (1) Linear regression was used to relate snow accumulation during single and consecutive winters with white-tailed deer (Odocoileus virginianus) fawn:doe ratios, mosse (Alces alces) twinning rates and calf:cow ratios, and annual changes in deer and moose populations. Significant relationships were found between snow accumulation during individual winters and these dependent variables during the following year. However, the strongest relationships were between the dependent variables and the sums of the snow accumulations over the previous three winters. The percentage of the variability explained was 36 to 51. (2) Significant relationships were also found between winter vulnerability of moose calves and the sum of the snow accumulations in the current, and up to seven previous, winters, with about 49% of the variability explained. (3) No relationship was found between wolf numbers and the above dependent variables. (4) These relationships imply that winter influences on maternal nutrition can accumulate for several years and that this cumulative effect strongly determines fecundity and/or calf and fawn survivability. Although wolf (Canis lupus L.) predation is the main direct mortality agent on fawns and calves, wolf density itself appears to be secondary to winter weather in influencing the deer and moose populations.

  13. Kidnapping Detection and Recognition in Previous Unknown Environment

    Directory of Open Access Journals (Sweden)

    Yang Tian

    2017-01-01

    Full Text Available An unaware event referred to as kidnapping makes the estimation result of localization incorrect. In a previous unknown environment, incorrect localization result causes incorrect mapping result in Simultaneous Localization and Mapping (SLAM by kidnapping. In this situation, the explored area and unexplored area are divided to make the kidnapping recovery difficult. To provide sufficient information on kidnapping, a framework to judge whether kidnapping has occurred and to identify the type of kidnapping with filter-based SLAM is proposed. The framework is called double kidnapping detection and recognition (DKDR by performing two checks before and after the “update” process with different metrics in real time. To explain one of the principles of DKDR, we describe a property of filter-based SLAM that corrects the mapping result of the environment using the current observations after the “update” process. Two classical filter-based SLAM algorithms, Extend Kalman Filter (EKF SLAM and Particle Filter (PF SLAM, are modified to show that DKDR can be simply and widely applied in existing filter-based SLAM algorithms. Furthermore, a technique to determine the adapted thresholds of metrics in real time without previous data is presented. Both simulated and experimental results demonstrate the validity and accuracy of the proposed method.

  14. Stimulation Technologies for Deep Well Completions

    Energy Technology Data Exchange (ETDEWEB)

    Stephen Wolhart

    2005-06-30

    The Department of Energy (DOE) is sponsoring the Deep Trek Program targeted at improving the economics of drilling and completing deep gas wells. Under the DOE program, Pinnacle Technologies conducted a study to evaluate the stimulation of deep wells. The objective of the project was to review U.S. deep well drilling and stimulation activity, review rock mechanics and fracture growth in deep, high-pressure/temperature wells and evaluate stimulation technology in several key deep plays. This report documents results from this project.

  15. [ANTITHROMBOTIC MEDICATION IN PREGNANT WOMEN WITH PREVIOUS INTRAUTERINE GROWTH RESTRICTION].

    Science.gov (United States)

    Neykova, K; Dimitrova, V; Dimitrov, R; Vakrilova, L

    2016-01-01

    To analyze pregnancy outcome in patients who were on antithrombotic medication (AM) because of previous pregnancy with fetal intrauterine growth restriction (IUGR). The studied group (SG) included 21 pregnancies in 15 women with history of previous IUGR. The patients were on low dose aspirin (LDA) and/or low molecular weight heparin (LMWH). Pregnancy outcome was compared to the one in two more groups: 1) primary group (PG) including the previous 15 pregnancies with IUGR of the same women; 2) control group (CG) including 45 pregnancies of women matched for parity with the ones in the SG, with no history of IUGR and without medication. The SG, PG and CG were compared for the following: mean gestational age (g.a.) at birth, mean birth weight (BW), proportion of cases with early preeclampsia (PE), IUGR (total, moderate, and severe), intrauterine fetal death (IUFD), neonatal death (NND), admission to NICU, cesarean section (CS) because of chronic or acute fetal distress (FD) related to IUGR, PE or placental abruption. Student's t-test was applied to assess differences between the groups. P values < 0.05 were considered statistically significant. The differences between the SG and the PG regarding mean g. a. at delivery (33.7 and 29.8 w.g. respectively) and the proportion of babies admitted to NICU (66.7% vs. 71.4%) were not statistically significant. The mean BW in the SG (2114,7 g.) was significantly higher than in the PG (1090.8 g.). In the SG compared with the PG there were significantly less cases of IUFD (14.3% and 53.3% respectively), early PE (9.5% vs. 46.7%) moderate and severe IUGR (10.5% and 36.8% vs. 41.7% and 58.3%). Neonatal mortality in the SG (5.6%) was significantly lower than in the PG (57.1%), The proportion of CS for FD was not significantly different--53.3% in the SG and 57.1% in the PG. On the other hand, comparison between the SG and the CG demonstrated significantly lower g.a. at delivery in the SG (33.7 vs. 38 w.g.) an lower BW (2114 vs. 3094 g

  16. Deep-inelastic scattering in 124,136Xe+58,64Ni at energies near the Coulomb barrier

    International Nuclear Information System (INIS)

    Gehring, J.; Back, B.B.; Chan, K.C.; Freer, M.; Henderson, D.; Jiang, C.L.; Rehm, K.E.; Schiffer, J.P.; Wolanski, M.; Wuosmaa, A.H.; Gehring, J.; Wolanski, M.

    1997-01-01

    Cross sections, angular distributions, and mass distributions have been measured for deep-inelastic scattering in 124 Xe+ 58 Ni and 136 Xe+ 64 Ni at laboratory energies in the vicinity of the Coulomb barrier. The mass distributions show distinct components due to deep-inelastic and fissionlike processes. The strength of deep-inelastic scattering is similar in the two systems measured and comparable to previous measurements in 58 Ni+ 112,124 Sn. copyright 1997 The American Physical Society

  17. Prediction of successful trial of labour in patients with a previous caesarean section

    International Nuclear Information System (INIS)

    Shaheen, N.; Khalil, S.; Iftikhar, P.

    2014-01-01

    Objective: To determine the prediction rate of success in trial of labour after one previous caesarean section. Methods: The cross-sectional study was conducted at the Department of Obstetrics and Gynaecology, Cantonment General Hospital, Rawalpindi, from January 1, 2012 to January 31, 2013, and comprised women with one previous Caesarean section and with single alive foetus at 37-41 weeks of gestation. Women with more than one Caesarean section, unknown site of uterine scar, bony pelvic deformity, placenta previa, intra-uterine growth restriction, deep transverse arrest in previous labour and non-reassuring foetal status at the time of admission were excluded. Intrapartum risk assessment included Bishop score at admission, rate of cervical dilatation and scar tenderness. SPSS 21 was used for statistical analysis. Results: Out of a total of 95 women, the trial was successful in 68 (71.6%). Estimated foetal weight and number of prior vaginal deliveries had a high predictive value for successful trial of labour after Caesarean section. Estimated foetal weight had an odds ratio of 0.46 (p<0.001), while number of prior vaginal deliveries had an odds ratio of 0.85 with (p=0.010). Other factors found to be predictive of successful trial included Bishop score at the time of admission (p<0.037) and rate of cervical dilatation in the first stage of labour (p<0.021). Conclusion: History of prior vaginal deliveries, higher Bishop score at the time of admission, rapid rate of cervical dilatation and lower estimated foetal weight were predictive of a successful trial of labour after Caesarean section. (author)

  18. Deepwater Gulf of Mexico more profitable than previously thought

    International Nuclear Information System (INIS)

    Craig, M.J.K.; Hyde, S.T.

    1997-01-01

    Economic evaluations and recent experience show that the deepwater Gulf of Mexico (GOM) is much more profitable than previously thought. Four factors contributing to the changed viewpoint are: First, deepwater reservoirs have proved to have excellent productive capacity, distribution, and continuity when compared to correlative-age shelf deltaic sands. Second, improved technologies and lower perceived risks have lowered the cost of floating production systems (FPSs). Third, projects now get on-line quicker. Fourth, a collection of other important factors are: Reduced geologic risk and associated high success rates for deepwater GOM wells due primarily to improved seismic imaging and processing tools (3D, AVO, etc.); absence of any political risk in the deepwater GOM (common overseas, and very significant in some international areas); and positive impact of deepwater federal royalty relief. This article uses hypothetical reserve distributions and price forecasts to illustrate indicative economics of deepwater prospects. Economics of Shell Oil Co.'s three deepwater projects are also discussed

  19. Corneal perforation after conductive keratoplasty with previous refractive surgery.

    Science.gov (United States)

    Kymionis, George D; Titze, Patrik; Markomanolakis, Marinos M; Aslanides, Ioannis M; Pallikaris, Ioannis G

    2003-12-01

    A 56-year-old woman had conductive keratoplasty (CK) for residual hyperopia and astigmatism. Three years before the procedure, the patient had arcuate keratotomy, followed by laser in situ keratomileusis 2 years later for high astigmatism correction in both eyes. During CK, a corneal perforation occurred in the right eye; during the postoperative examination, an iris perforation and anterior subcapsule opacification were seen beneath the perforation site. The perforation was managed with a bandage contact lens and an antibiotic-steroid ointment; it had a negative Seidel sign by the third day. The surgery in the left eye was uneventful. Three months after the procedure, the uncorrected visual acuity was 20/32 and the best corrected visual acuity 20/20 in both eyes with a significant improvement in corneal topography. Care must be taken to prevent CK-treated spots from coinciding with areas in the corneal stroma that might have been altered by previous refractive procedures.

  20. Interference from previous distraction disrupts older adults' memory.

    Science.gov (United States)

    Biss, Renée K; Campbell, Karen L; Hasher, Lynn

    2013-07-01

    Previously relevant information can disrupt the ability of older adults to remember new information. Here, the researchers examined whether prior irrelevant information, or distraction, can also interfere with older adults' memory for new information. Younger and older adults first completed a 1-back task on pictures that were superimposed with distracting words. After a delay, participants learned picture-word paired associates and memory was tested using picture-cued recall. In 1 condition (high interference), some pairs included pictures from the 1-back task now paired with new words. In a low-interference condition, the transfer list used all new items. Older adults had substantially lower cued-recall performance in the high- compared with the low-interference condition. In contrast, younger adults' performance did not vary across conditions. These findings suggest that even never-relevant information from the past can disrupt older adults' memory for new associations.

  1. The long-term consequences of previous hyperthyroidism

    DEFF Research Database (Denmark)

    Hjelm Brandt Kristensen, Frans

    2015-01-01

    Thyroid hormones affect every cell in the human body, and the cardiovascular changes associated with increased levels of thyroid hormones are especially well described. As an example, short-term hyperthyroidism has positive chronotropic and inotropic effects on the heart, leading to a hyperdynamic...... with CVD, LD and DM both before and after the diagnosis of hyperthyroidism. Although the design used does not allow a stringent distinction between cause and effect, the findings indicate a possible direct association between hyperthyroidism and these morbidities, or vice versa....... vascular state. While it is biologically plausible that these changes may induce long-term consequences, the insight into morbidity as well as mortality in patients with previous hyperthyroidism is limited. The reasons for this are a combination of inadequately powered studies, varying definitions...

  2. Is Previous Respiratory Disease a Risk Factor for Lung Cancer?

    Science.gov (United States)

    Denholm, Rachel; Schüz, Joachim; Straif, Kurt; Stücker, Isabelle; Jöckel, Karl-Heinz; Brenner, Darren R.; De Matteis, Sara; Boffetta, Paolo; Guida, Florence; Brüske, Irene; Wichmann, Heinz-Erich; Landi, Maria Teresa; Caporaso, Neil; Siemiatycki, Jack; Ahrens, Wolfgang; Pohlabeln, Hermann; Zaridze, David; Field, John K.; McLaughlin, John; Demers, Paul; Szeszenia-Dabrowska, Neonila; Lissowska, Jolanta; Rudnai, Peter; Fabianova, Eleonora; Dumitru, Rodica Stanescu; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Kendzia, Benjamin; Peters, Susan; Behrens, Thomas; Vermeulen, Roel; Brüning, Thomas; Kromhout, Hans

    2014-01-01

    Rationale: Previous respiratory diseases have been associated with increased risk of lung cancer. Respiratory conditions often co-occur and few studies have investigated multiple conditions simultaneously. Objectives: Investigate lung cancer risk associated with chronic bronchitis, emphysema, tuberculosis, pneumonia, and asthma. Methods: The SYNERGY project pooled information on previous respiratory diseases from 12,739 case subjects and 14,945 control subjects from 7 case–control studies conducted in Europe and Canada. Multivariate logistic regression models were used to investigate the relationship between individual diseases adjusting for co-occurring conditions, and patterns of respiratory disease diagnoses and lung cancer. Analyses were stratified by sex, and adjusted for age, center, ever-employed in a high-risk occupation, education, smoking status, cigarette pack-years, and time since quitting smoking. Measurements and Main Results: Chronic bronchitis and emphysema were positively associated with lung cancer, after accounting for other respiratory diseases and smoking (e.g., in men: odds ratio [OR], 1.33; 95% confidence interval [CI], 1.20–1.48 and OR, 1.50; 95% CI, 1.21–1.87, respectively). A positive relationship was observed between lung cancer and pneumonia diagnosed 2 years or less before lung cancer (OR, 3.31; 95% CI, 2.33–4.70 for men), but not longer. Co-occurrence of chronic bronchitis and emphysema and/or pneumonia had a stronger positive association with lung cancer than chronic bronchitis “only.” Asthma had an inverse association with lung cancer, the association being stronger with an asthma diagnosis 5 years or more before lung cancer compared with shorter. Conclusions: Findings from this large international case–control consortium indicate that after accounting for co-occurring respiratory diseases, chronic bronchitis and emphysema continue to have a positive association with lung cancer. PMID:25054566

  3. Twelve previously unknown phage genera are ubiquitous in global oceans.

    Science.gov (United States)

    Holmfeldt, Karin; Solonenko, Natalie; Shah, Manesh; Corrier, Kristen; Riemann, Lasse; Verberkmoes, Nathan C; Sullivan, Matthew B

    2013-07-30

    Viruses are fundamental to ecosystems ranging from oceans to humans, yet our ability to study them is bottlenecked by the lack of ecologically relevant isolates, resulting in "unknowns" dominating culture-independent surveys. Here we present genomes from 31 phages infecting multiple strains of the aquatic bacterium Cellulophaga baltica (Bacteroidetes) to provide data for an underrepresented and environmentally abundant bacterial lineage. Comparative genomics delineated 12 phage groups that (i) each represent a new genus, and (ii) represent one novel and four well-known viral families. This diversity contrasts the few well-studied marine phage systems, but parallels the diversity of phages infecting human-associated bacteria. Although all 12 Cellulophaga phages represent new genera, the podoviruses and icosahedral, nontailed ssDNA phages were exceptional, with genomes up to twice as large as those previously observed for each phage type. Structural novelty was also substantial, requiring experimental phage proteomics to identify 83% of the structural proteins. The presence of uncommon nucleotide metabolism genes in four genera likely underscores the importance of scavenging nutrient-rich molecules as previously seen for phages in marine environments. Metagenomic recruitment analyses suggest that these particular Cellulophaga phages are rare and may represent a first glimpse into the phage side of the rare biosphere. However, these analyses also revealed that these phage genera are widespread, occurring in 94% of 137 investigated metagenomes. Together, this diverse and novel collection of phages identifies a small but ubiquitous fraction of unknown marine viral diversity and provides numerous environmentally relevant phage-host systems for experimental hypothesis testing.

  4. Urethrotomy has a much lower success rate than previously reported.

    Science.gov (United States)

    Santucci, Richard; Eisenberg, Lauren

    2010-05-01

    We evaluated the success rate of direct vision internal urethrotomy as a treatment for simple male urethral strictures. A retrospective chart review was performed on 136 patients who underwent urethrotomy from January 1994 through March 2009. The Kaplan-Meier method was used to analyze stricture-free probability after the first, second, third, fourth and fifth urethrotomy. Patients with complex strictures (36) were excluded from the study for reasons including previous urethroplasty, neophallus or previous radiation, and 24 patients were lost to followup. Data were available for 76 patients. The stricture-free rate after the first urethrotomy was 8% with a median time to recurrence of 7 months. For the second urethrotomy stricture-free rate was 6% with a median time to recurrence of 9 months. For the third urethrotomy stricture-free rate was 9% with a median time to recurrence of 3 months. For procedures 4 and 5 stricture-free rate was 0% with a median time to recurrence of 20 and 8 months, respectively. Urethrotomy is a popular treatment for male urethral strictures. However, the performance characteristics are poor. Success rates were no higher than 9% in this series for first or subsequent urethrotomy during the observation period. Most of the patients in this series will be expected to experience failure with longer followup and the expected long-term success rate from any (1 through 5) urethrotomy approach is 0%. Urethrotomy should be considered a temporizing measure until definitive curative reconstruction can be planned. 2010 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

  5. Typing DNA profiles from previously enhanced fingerprints using direct PCR.

    Science.gov (United States)

    Templeton, Jennifer E L; Taylor, Duncan; Handt, Oliva; Linacre, Adrian

    2017-07-01

    Fingermarks are a source of human identification both through the ridge patterns and DNA profiling. Typing nuclear STR DNA markers from previously enhanced fingermarks provides an alternative method of utilising the limited fingermark deposit that can be left behind during a criminal act. Dusting with fingerprint powders is a standard method used in classical fingermark enhancement and can affect DNA data. The ability to generate informative DNA profiles from powdered fingerprints using direct PCR swabs was investigated. Direct PCR was used as the opportunity to generate usable DNA profiles after performing any of the standard DNA extraction processes is minimal. Omitting the extraction step will, for many samples, be the key to success if there is limited sample DNA. DNA profiles were generated by direct PCR from 160 fingermarks after treatment with one of the following dactyloscopic fingerprint powders: white hadonite; silver aluminium; HiFi Volcano silk black; or black magnetic fingerprint powder. This was achieved by a combination of an optimised double-swabbing technique and swab media, omission of the extraction step to minimise loss of critical low-template DNA, and additional AmpliTaq Gold ® DNA polymerase to boost the PCR. Ninety eight out of 160 samples (61%) were considered 'up-loadable' to the Australian National Criminal Investigation DNA Database (NCIDD). The method described required a minimum of working steps, equipment and reagents, and was completed within 4h. Direct PCR allows the generation of DNA profiles from enhanced prints without the need to increase PCR cycle numbers beyond manufacturer's recommendations. Particular emphasis was placed on preventing contamination by applying strict protocols and avoiding the use of previously used fingerprint brushes. Based on this extensive survey, the data provided indicate minimal effects of any of these four powders on the chance of obtaining DNA profiles from enhanced fingermarks. Copyright © 2017

  6. [Population policy and women: the relevance of previous studies].

    Science.gov (United States)

    De Barbieri, M T

    1983-01-01

    Although Mexico has had high rates of population growth since the 1930s caused by continuing high fertility but declining infant and general mortality, and has undergone deep structural change including declining agricultural production, rapid industrialization, urbanization, and increasing urban umemployment, it was not until the 1970s that the government began to adopt measures aimed at controlling population growth. Opponents of family planning argued that economic and social development would lead to fertility decline, but its proponents believed that reducing population growth would free resources for productive investment that otherwise would have to be used to finance services for the ever-growing population. At the same time that the constitution and laws were changed to allow or promote family planning, Mexican civil and labor laws were changed to provide for equality of men and women. Some background is necessary to understand the effect of such changes in the role and status of the Mexican woman. A relationship has been noted between demographic models--the form in which a society reproduces over a given time--and the social condition of women. Women have generally been subordinated to men during known history, but recent research indicates that their history has not been as uniform as once supposed. The particular form in which each society defines the natural-biological basis of sex roles varies; social definitions of sex and gender vary depending on the extension of "natural-biological" character to specific areas and tasks. The cases of French women in the 16th-18th centuries and German women under Hitler illustrate different ways in which demographic models and the condition of women have varied within a general framework of subordination of women. But when attempts are made to change a given demographic model, the condition of women is redefined at the level of practice as well as of value orientations concerning motherhood, female labor force

  7. Deep Web and Dark Web: Deep World of the Internet

    OpenAIRE

    Çelik, Emine

    2018-01-01

    The Internet is undoubtedly still a revolutionary breakthrough in the history of humanity. Many people use the internet for communication, social media, shopping, political and social agenda, and more. Deep Web and Dark Web concepts not only handled by computer, software engineers but also handled by social siciensists because of the role of internet for the States in international arenas, public institutions and human life. By the moving point that very importantrole of internet for social s...

  8. DeepNAT: Deep convolutional neural network for segmenting neuroanatomy.

    Science.gov (United States)

    Wachinger, Christian; Reuter, Martin; Klein, Tassilo

    2018-04-15

    We introduce DeepNAT, a 3D Deep convolutional neural network for the automatic segmentation of NeuroAnaTomy in T1-weighted magnetic resonance images. DeepNAT is an end-to-end learning-based approach to brain segmentation that jointly learns an abstract feature representation and a multi-class classification. We propose a 3D patch-based approach, where we do not only predict the center voxel of the patch but also neighbors, which is formulated as multi-task learning. To address a class imbalance problem, we arrange two networks hierarchically, where the first one separates foreground from background, and the second one identifies 25 brain structures on the foreground. Since patches lack spatial context, we augment them with coordinates. To this end, we introduce a novel intrinsic parameterization of the brain volume, formed by eigenfunctions of the Laplace-Beltrami operator. As network architecture, we use three convolutional layers with pooling, batch normalization, and non-linearities, followed by fully connected layers with dropout. The final segmentation is inferred from the probabilistic output of the network with a 3D fully connected conditional random field, which ensures label agreement between close voxels. The roughly 2.7million parameters in the network are learned with stochastic gradient descent. Our results show that DeepNAT compares favorably to state-of-the-art methods. Finally, the purely learning-based method may have a high potential for the adaptation to young, old, or diseased brains by fine-tuning the pre-trained network with a small training sample on the target application, where the availability of larger datasets with manual annotations may boost the overall segmentation accuracy in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

  9. Deep Phenotyping: Deep Learning For Temporal Phenotype/Genotype Classification

    OpenAIRE

    Najafi, Mohammad; Namin, Sarah; Esmaeilzadeh, Mohammad; Brown, Tim; Borevitz, Justin

    2017-01-01

    High resolution and high throughput, genotype to phenotype studies in plants are underway to accelerate breeding of climate ready crops. Complex developmental phenotypes are observed by imaging a variety of accessions in different environment conditions, however extracting the genetically heritable traits is challenging. In the recent years, deep learning techniques and in particular Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs) and Long-Short Term Memories (LSTMs), h...

  10. Deep Neuromuscular Blockade Improves Laparoscopic Surgical Conditions

    DEFF Research Database (Denmark)

    Rosenberg, Jacob; Herring, W Joseph; Blobner, Manfred

    2017-01-01

    INTRODUCTION: Sustained deep neuromuscular blockade (NMB) during laparoscopic surgery may facilitate optimal surgical conditions. This exploratory study assessed whether deep NMB improves surgical conditions and, in doing so, allows use of lower insufflation pressures during laparoscopic cholecys...

  11. Joint Training of Deep Boltzmann Machines

    OpenAIRE

    Goodfellow, Ian; Courville, Aaron; Bengio, Yoshua

    2012-01-01

    We introduce a new method for training deep Boltzmann machines jointly. Prior methods require an initial learning pass that trains the deep Boltzmann machine greedily, one layer at a time, or do not perform well on classifi- cation tasks.

  12. Deep Learning for Brain MRI Segmentation: State of the Art and Future Directions.

    Science.gov (United States)

    Akkus, Zeynettin; Galimzianova, Alfiia; Hoogi, Assaf; Rubin, Daniel L; Erickson, Bradley J

    2017-08-01

    Quantitative analysis of brain MRI is routine for many neurological diseases and conditions and relies on accurate segmentation of structures of interest. Deep learning-based segmentation approaches for brain MRI are gaining interest due to their self-learning and generalization ability over large amounts of data. As the deep learning architectures are becoming more mature, they gradually outperform previous state-of-the-art classical machine learning algorithms. This review aims to provide an overview of current deep learning-based segmentation approaches for quantitative brain MRI. First we review the current deep learning architectures used for segmentation of anatomical brain structures and brain lesions. Next, the performance, speed, and properties of deep learning approaches are summarized and discussed. Finally, we provide a critical assessment of the current state and identify likely future developments and trends.

  13. Bacteriological examination and biological characteristics of deep frozen bone preserved by gamma sterilization

    International Nuclear Information System (INIS)

    Pham Quang Ngoc; Le The Trung; Vo Van Thuan; Ho Minh Duc

    1999-01-01

    To promote the surgical success in Vietnam, we should supply bone allografts of different sizes. For this reason we have developed a standard procedure in procurement, deep freezing, packaging and radiation sterilization of massive bone. The achievement in this attempt will be briefly reported. The dose of 10-15 kGy is proved to be suitable for radiation sterilization of massive bone allografts being treated in clean condition and preserved in deep frozen. Neither deep freezing nor radiation sterilization cause any significant loss of biochemical stability of massive bone allografts especially when deep freezing combines with radiation. There were neither cross infection nor change of biological characteristics found after 6 months of storage since radiation treatment. In addition to results of the previous research and development of tissue grafts for medical care, the deep freezing radiation sterilization has been established for preservation of massive bone that is of high demand for surgery in Vietnam

  14. Developing Deep Learning Applications for Life Science and Pharma Industry.

    Science.gov (United States)

    Siegismund, Daniel; Tolkachev, Vasily; Heyse, Stephan; Sick, Beate; Duerr, Oliver; Steigele, Stephan

    2018-06-01

    Deep Learning has boosted artificial intelligence over the past 5 years and is seen now as one of the major technological innovation areas, predicted to replace lots of repetitive, but complex tasks of human labor within the next decade. It is also expected to be 'game changing' for research activities in pharma and life sciences, where large sets of similar yet complex data samples are systematically analyzed. Deep learning is currently conquering formerly expert domains especially in areas requiring perception, previously not amenable to standard machine learning. A typical example is the automated analysis of images which are typically produced en-masse in many domains, e. g., in high-content screening or digital pathology. Deep learning enables to create competitive applications in so-far defined core domains of 'human intelligence'. Applications of artificial intelligence have been enabled in recent years by (i) the massive availability of data samples, collected in pharma driven drug programs (='big data') as well as (ii) deep learning algorithmic advancements and (iii) increase in compute power. Such applications are based on software frameworks with specific strengths and weaknesses. Here, we introduce typical applications and underlying frameworks for deep learning with a set of practical criteria for developing production ready solutions in life science and pharma research. Based on our own experience in successfully developing deep learning applications we provide suggestions and a baseline for selecting the most suited frameworks for a future-proof and cost-effective development. © Georg Thieme Verlag KG Stuttgart · New York.

  15. Deep challenges for China's war on water pollution.

    Science.gov (United States)

    Han, Dongmei; Currell, Matthew J; Cao, Guoliang

    2016-11-01

    China's Central government has released an ambitious plan to tackle the nation's water pollution crisis. However, this is inhibited by a lack of data, particularly for groundwater. We compiled and analyzed water quality classification data from publicly available government sources, further revealing the scale and extent of the crisis. We also compiled nitrate data in shallow and deep groundwater from a range of literature sources, covering 52 of China's groundwater systems; the most comprehensive national-scale assessment yet. Nitrate pollution at levels exceeding the US EPA's maximum contaminant level (10 mg/L NO 3 N) occurs at the 90th percentile in 25 of 36 shallow aquifers and 10 out of 37 deep or karst aquifers. Isotopic compositions of groundwater nitrate (δ 15 N and δ 18 O NO3 values ranging from -14.9‰ to 35.5‰ and -8.1‰ to 51.0‰, respectively) indicate many nitrate sources including soil nitrogen, agricultural fertilizers, untreated wastewater and/or manure, and locally show evidence of de-nitrification. From these data, it is clear that contaminated groundwater is ubiquitous in deep aquifers as well as shallow groundwater (and surface water). Deep aquifers contain water recharged tens of thousands of years before present, long before widespread anthropogenic nitrate contamination. This groundwater has therefore likely been contaminated due to rapid bypass flow along wells or other conduits. Addressing the issue of well condition is urgently needed to stop further pollution of China's deep aquifers, which are some of China's most important drinking water sources. China's new 10-point Water Pollution Plan addresses previous shortcomings, however, control and remediation of deep groundwater pollution will take decades of sustained effort. Copyright © 2016. Published by Elsevier Ltd.

  16. Global diversity and biogeography of deep-sea pelagic prokaryotes

    KAUST Repository

    Salazar, Guillem

    2015-08-07

    The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean\\'s microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (∼3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.

  17. Global diversity and biogeography of deep-sea pelagic prokaryotes

    KAUST Repository

    Salazar, Guillem; Cornejo-Castillo, Francisco M.; Bení tez-Barrios, Veró nica; Fraile-Nuez, Eugenio; Á lvarez-Salgado, X. Antó n; Duarte, Carlos M.; Gasol, Josep M.; Acinas, Silvia G.

    2015-01-01

    The deep-sea is the largest biome of the biosphere, and contains more than half of the whole ocean's microbes. Uncovering their general patterns of diversity and community structure at a global scale remains a great challenge, as only fragmentary information of deep-sea microbial diversity exists based on regional-scale studies. Here we report the first globally comprehensive survey of the prokaryotic communities inhabiting the bathypelagic ocean using high-throughput sequencing of the 16S rRNA gene. This work identifies the dominant prokaryotes in the pelagic deep ocean and reveals that 50% of the operational taxonomic units (OTUs) belong to previously unknown prokaryotic taxa, most of which are rare and appear in just a few samples. We show that whereas the local richness of communities is comparable to that observed in previous regional studies, the global pool of prokaryotic taxa detected is modest (∼3600 OTUs), as a high proportion of OTUs are shared among samples. The water masses appear to act as clear drivers of the geographical distribution of both particle-attached and free-living prokaryotes. In addition, we show that the deep-oceanic basins in which the bathypelagic realm is divided contain different particle-attached (but not free-living) microbial communities. The combination of the aging of the water masses and a lack of complete dispersal are identified as the main drivers for this biogeographical pattern. All together, we identify the potential of the deep ocean as a reservoir of still unknown biological diversity with a higher degree of spatial complexity than hitherto considered.

  18. Building Program Vector Representations for Deep Learning

    OpenAIRE

    Mou, Lili; Li, Ge; Liu, Yuxuan; Peng, Hao; Jin, Zhi; Xu, Yan; Zhang, Lu

    2014-01-01

    Deep learning has made significant breakthroughs in various fields of artificial intelligence. Advantages of deep learning include the ability to capture highly complicated features, weak involvement of human engineering, etc. However, it is still virtually impossible to use deep learning to analyze programs since deep architectures cannot be trained effectively with pure back propagation. In this pioneering paper, we propose the "coding criterion" to build program vector representations, whi...

  19. Radon anomalies prior to earthquakes (1). Review of previous studies

    International Nuclear Information System (INIS)

    Ishikawa, Tetsuo; Tokonami, Shinji; Yasuoka, Yumi; Shinogi, Masaki; Nagahama, Hiroyuki; Omori, Yasutaka; Kawada, Yusuke

    2008-01-01

    The relationship between radon anomalies and earthquakes has been studied for more than 30 years. However, most of the studies dealt with radon in soil gas or in groundwater. Before the 1995 Hyogoken-Nanbu earthquake, an anomalous increase of atmospheric radon was observed at Kobe Pharmaceutical University. The increase was well fitted with a mathematical model related to earthquake fault dynamics. This paper reports the significance of this observation, reviewing previous studies on radon anomaly before earthquakes. Groundwater/soil radon measurements for earthquake prediction began in 1970's in Japan as well as foreign countries. One of the most famous studies in Japan is groundwater radon anomaly before the 1978 Izu-Oshima-kinkai earthquake. We have recognized the significance of radon in earthquake prediction research, but recently its limitation was also pointed out. Some researchers are looking for a better indicator for precursors; simultaneous measurements of radon and other gases are new trials in recent studies. Contrary to soil/groundwater radon, we have not paid much attention to atmospheric radon before earthquakes. However, it might be possible to detect precursors in atmospheric radon before a large earthquake. In the next issues, we will discuss the details of the anomalous atmospheric radon data observed before the Hyogoken-Nanbu earthquake. (author)

  20. Cerebral Metastasis from a Previously Undiagnosed Appendiceal Adenocarcinoma

    Directory of Open Access Journals (Sweden)

    Antonio Biroli

    2012-01-01

    Full Text Available Brain metastases arise in 10%–40% of all cancer patients. Up to one third of the patients do not have previous cancer history. We report a case of a 67-years-old male patient who presented with confusion, tremor, and apraxia. A brain MRI revealed an isolated right temporal lobe lesion. A thorax-abdomen-pelvis CT scan showed no primary lesion. The patient underwent a craniotomy with gross-total resection. Histopathology revealed an intestinal-type adenocarcinoma. A colonoscopy found no primary lesion, but a PET-CT scan showed elevated FDG uptake in the appendiceal nodule. A right hemicolectomy was performed, and the specimen showed a moderately differentiated mucinous appendiceal adenocarcinoma. Whole brain radiotherapy was administrated. A subsequent thorax-abdomen CT scan revealed multiple lung and hepatic metastasis. Seven months later, the patient died of disease progression. In cases of undiagnosed primary lesions, patients present in better general condition, but overall survival does not change. Eventual identification of the primary tumor does not affect survival. PET/CT might be a helpful tool in detecting lesions of the appendiceal region. To the best of our knowledge, such a case was never reported in the literature, and an appendiceal malignancy should be suspected in patients with brain metastasis from an undiagnosed primary tumor.

  1. Coronary collateral vessels in patients with previous myocardial infarction

    International Nuclear Information System (INIS)

    Nakatsuka, M.; Matsuda, Y.; Ozaki, M.

    1987-01-01

    To assess the degree of collateral vessels after myocardial infarction, coronary angiograms, left ventriculograms, and exercise thallium-201 myocardial scintigrams of 36 patients with previous myocardial infarction were reviewed. All 36 patients had total occlusion of infarct-related coronary artery and no more than 70% stenosis in other coronary arteries. In 19 of 36 patients with transient reduction of thallium-201 uptake in the infarcted area during exercise (Group A), good collaterals were observed in 10 patients, intermediate collaterals in 7 patients, and poor collaterals in 2 patients. In 17 of 36 patients without transient reduction of thallium-201 uptake in the infarcted area during exercise (Group B), good collaterals were seen in 2 patients, intermediate collaterals in 7 patients, and poor collaterals in 8 patients (p less than 0.025). Left ventricular contractions in the infarcted area were normal or hypokinetic in 10 patients and akinetic or dyskinetic in 9 patients in Group A. In Group B, 1 patient had hypokinetic contraction and 16 patients had akinetic or dyskinetic contraction (p less than 0.005). Thus, patients with transient reduction of thallium-201 uptake in the infarcted area during exercise had well developed collaterals and preserved left ventricular contraction, compared to those in patients without transient reduction of thallium-201 uptake in the infarcted area during exercise. These results suggest that the presence of viable myocardium in the infarcted area might be related to the degree of collateral vessels

  2. High-Grade Leiomyosarcoma Arising in a Previously Replanted Limb

    Directory of Open Access Journals (Sweden)

    Tiffany J. Pan

    2015-01-01

    Full Text Available Sarcoma development has been associated with genetics, irradiation, viral infections, and immunodeficiency. Reports of sarcomas arising in the setting of prior trauma, as in burn scars or fracture sites, are rare. We report a case of a leiomyosarcoma arising in an arm that had previously been replanted at the level of the elbow joint following traumatic amputation when the patient was eight years old. He presented twenty-four years later with a 10.8 cm mass in the replanted arm located on the volar forearm. The tumor was completely resected and pathology examination showed a high-grade, subfascial spindle cell sarcoma diagnosed as a grade 3 leiomyosarcoma with stage pT2bNxMx. The patient underwent treatment with brachytherapy, reconstruction with a free flap, and subsequently chemotherapy. To the best of our knowledge, this is the first case report of leiomyosarcoma developing in a replanted extremity. Development of leiomyosarcoma in this case could be related to revascularization, scar formation, or chronic injury after replantation. The patient remains healthy without signs of recurrence at three-year follow-up.

  3. Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

    Directory of Open Access Journals (Sweden)

    Pingzhao Hu

    2009-04-01

    Full Text Available One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans. Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

  4. Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

    Science.gov (United States)

    Hu, Pingzhao; Janga, Sarath Chandra; Babu, Mohan; Díaz-Mejía, J Javier; Butland, Gareth; Yang, Wenhong; Pogoutse, Oxana; Guo, Xinghua; Phanse, Sadhna; Wong, Peter; Chandran, Shamanta; Christopoulos, Constantine; Nazarians-Armavil, Anaies; Nasseri, Negin Karimi; Musso, Gabriel; Ali, Mehrab; Nazemof, Nazila; Eroukova, Veronika; Golshani, Ashkan; Paccanaro, Alberto; Greenblatt, Jack F; Moreno-Hagelsieb, Gabriel; Emili, Andrew

    2009-04-28

    One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

  5. Influence of Previous Knowledge in Torrance Tests of Creative Thinking

    Directory of Open Access Journals (Sweden)

    María Aranguren

    2015-07-01

    Full Text Available The aim of this work is to analyze the influence of study field, expertise and recreational activities participation in Torrance Tests of Creative Thinking (TTCT, 1974 performance. Several hypotheses were postulated to explore the possible effects of previous knowledge in TTCT verbal and TTCT figural university students’ outcomes. Participants in this study included 418 students from five study fields: Psychology;Philosophy and Literature, Music; Engineering; and Journalism and Advertising (Communication Sciences. Results found in this research seem to indicate that there in none influence of the study field, expertise and recreational activities participation in neither of the TTCT tests. Instead, the findings seem to suggest some kind of interaction between certain skills needed to succeed in specific studies fields and performance on creativity tests, such as the TTCT. These results imply that TTCT is a useful and valid instrument to measure creativity and that some cognitive process involved in innovative thinking can be promoted using different intervention programs in schools and universities regardless the students study field.

  6. Gastrointestinal tolerability with ibandronate after previous weekly bisphosphonate treatment.

    Science.gov (United States)

    Derman, Richard; Kohles, Joseph D; Babbitt, Ann

    2009-01-01

    Data from two open-label trials (PRIOR and CURRENT) of women with postmenopausal osteoporosis or osteopenia were evaluated to assess whether monthly oral and quarterly intravenous (IV) ibandronate dosing improved self-reported gastrointestinal (GI) tolerability for patients who had previously experienced GI irritation with bisphosphonate (BP) use. In PRIOR, women who had discontinued daily or weekly BP treatment due to GI intolerance received monthly oral or quarterly IV ibandronate for 12 months. The CURRENT subanalysis included women receiving weekly BP treatment who switched to monthly oral ibandronate for six months. GI symptom severity and frequency were assessed using the Osteoporosis Patient Satisfaction Questionnaire. In PRIOR, mean GI tolerability scores increased significantly at month 1 from screening for both treatment groups (oral: 79.3 versus 54.1; IV: 84.4 versus 51.0; p 90% at Month 10). In the CURRENT subanalysis >60% of patients reported improvements in heartburn or acid reflux and >70% indicated improvement in other stomach upset at month 6. Postmenopausal women with GI irritability with daily or weekly BPs experienced improvement in symptoms with extended dosing monthly or quarterly ibandronate compared with baseline.

  7. Pertussis-associated persistent cough in previously vaccinated children.

    Science.gov (United States)

    Principi, Nicola; Litt, David; Terranova, Leonardo; Picca, Marina; Malvaso, Concetta; Vitale, Cettina; Fry, Norman K; Esposito, Susanna

    2017-11-01

    To evaluate the role of Bordetella pertussis infection, 96 otherwise healthy 7- to 17-year-old subjects who were suffering from a cough lasting from 2 to 8 weeks were prospectively recruited. At enrolment, a nasopharyngeal swab and an oral fluid sample were obtained to search for pertussis infection by the detection of B. pertussis DNA and/or an elevated titre of anti-pertussis toxin IgG. Evidence of pertussis infection was found in 18 (18.7 %; 95 % confidence interval, 11.5-28.0) cases. In 15 cases, the disease occurred despite booster administration. In two cases, pertussis was diagnosed less than 2 years after the booster injection, whereas in the other cases it was diagnosed between 2 and 9 years after the booster dose. This study used non-invasive testing to show that pertussis is one of the most important causes of long-lasting cough in school-age subjects. Moreover, the protection offered by acellular pertussis vaccines currently wanes more rapidly than previously thought.

  8. Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

    Directory of Open Access Journals (Sweden)

    Danping Wang

    2017-01-01

    Full Text Available A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional, 10 CEC2005 benchmark functions (30-dimensional, and a real-world problem (multilevel image segmentation problems. Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests.

  9. Evaluation of the DeepWind concept

    DEFF Research Database (Denmark)

    Schmidt Paulsen, Uwe; Borg, Michael; Gonzales Seabra, Luis Alberto

    The report describes the DeepWind 5 MW conceptual design as a baseline for results obtained in the scientific and technical work packages of the DeepWind project. A comparison of DeepWi nd with existing VAWTs and paper projects are carried out and the evaluation of the concept in terms of cost...

  10. Consolidated Deep Actor Critic Networks (DRAFT)

    NARCIS (Netherlands)

    Van der Laan, T.A.

    2015-01-01

    The works [Volodymyr et al. Playing atari with deep reinforcement learning. arXiv preprint arXiv:1312.5602, 2013.] and [Volodymyr et al. Human-level control through deep reinforcement learning. Nature, 518(7540):529–533, 2015.] have demonstrated the power of combining deep neural networks with

  11. Simulator Studies of the Deep Stall

    Science.gov (United States)

    White, Maurice D.; Cooper, George E.

    1965-01-01

    Simulator studies of the deep-stall problem encountered with modern airplanes are discussed. The results indicate that the basic deep-stall tendencies produced by aerodynamic characteristics are augmented by operational considerations. Because of control difficulties to be anticipated in the deep stall, it is desirable that adequate safeguards be provided against inadvertent penetrations.

  12. TOPIC MODELING: CLUSTERING OF DEEP WEBPAGES

    OpenAIRE

    Muhunthaadithya C; Rohit J.V; Sadhana Kesavan; E. Sivasankar

    2015-01-01

    The internet is comprised of massive amount of information in the form of zillions of web pages.This information can be categorized into the surface web and the deep web. The existing search engines can effectively make use of surface web information.But the deep web remains unexploited yet. Machine learning techniques have been commonly employed to access deep web content.

  13. Active semi-supervised learning method with hybrid deep belief networks.

    Science.gov (United States)

    Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong

    2014-01-01

    In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.

  14. DeepFlavour in CMS

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Flavour-tagging of jets is an important task in collider based high energy physics and a field where machine learning tools are applied by all major experiments. A new tagger (DeepFlavour) was developed and commissioned in CMS that is based on an advanced machine learning procedure. A deep neural network is used to do multi-classification of jets that origin from a b-quark, two b-quarks, a c-quark, two c-quarks or light colored particles (u, d, s-quark or gluon). The performance was measured in both, data and simulation. The talk will also include the measured performance of all taggers in CMS. The different taggers and results will be discussed and compared with some focus on details of the newest tagger.

  15. Deep Learning for ECG Classification

    Science.gov (United States)

    Pyakillya, B.; Kazachenko, N.; Mikhailovsky, N.

    2017-10-01

    The importance of ECG classification is very high now due to many current medical applications where this problem can be stated. Currently, there are many machine learning (ML) solutions which can be used for analyzing and classifying ECG data. However, the main disadvantages of these ML results is use of heuristic hand-crafted or engineered features with shallow feature learning architectures. The problem relies in the possibility not to find most appropriate features which will give high classification accuracy in this ECG problem. One of the proposing solution is to use deep learning architectures where first layers of convolutional neurons behave as feature extractors and in the end some fully-connected (FCN) layers are used for making final decision about ECG classes. In this work the deep learning architecture with 1D convolutional layers and FCN layers for ECG classification is presented and some classification results are showed.

  16. Deep Space Habitat Concept Demonstrator

    Science.gov (United States)

    Bookout, Paul S.; Smitherman, David

    2015-01-01

    This project will develop, integrate, test, and evaluate Habitation Systems that will be utilized as technology testbeds and will advance NASA's understanding of alternative deep space mission architectures, requirements, and operations concepts. Rapid prototyping and existing hardware will be utilized to develop full-scale habitat demonstrators. FY 2014 focused on the development of a large volume Space Launch System (SLS) class habitat (Skylab Gen 2) based on the SLS hydrogen tank components. Similar to the original Skylab, a tank section of the SLS rocket can be outfitted with a deep space habitat configuration and launched as a payload on an SLS rocket. This concept can be used to support extended stay at the Lunar Distant Retrograde Orbit to support the Asteroid Retrieval Mission and provide a habitat suitable for human missions to Mars.

  17. Hybrid mask for deep etching

    KAUST Repository

    Ghoneim, Mohamed T.

    2017-08-10

    Deep reactive ion etching is essential for creating high aspect ratio micro-structures for microelectromechanical systems, sensors and actuators, and emerging flexible electronics. A novel hybrid dual soft/hard mask bilayer may be deposited during semiconductor manufacturing for deep reactive etches. Such a manufacturing process may include depositing a first mask material on a substrate; depositing a second mask material on the first mask material; depositing a third mask material on the second mask material; patterning the third mask material with a pattern corresponding to one or more trenches for transfer to the substrate; transferring the pattern from the third mask material to the second mask material; transferring the pattern from the second mask material to the first mask material; and/or transferring the pattern from the first mask material to the substrate.

  18. Soft-Deep Boltzmann Machines

    OpenAIRE

    Kiwaki, Taichi

    2015-01-01

    We present a layered Boltzmann machine (BM) that can better exploit the advantages of a distributed representation. It is widely believed that deep BMs (DBMs) have far greater representational power than its shallow counterpart, restricted Boltzmann machines (RBMs). However, this expectation on the supremacy of DBMs over RBMs has not ever been validated in a theoretical fashion. In this paper, we provide both theoretical and empirical evidences that the representational power of DBMs can be a...

  19. Evolving Deep Networks Using HPC

    Energy Technology Data Exchange (ETDEWEB)

    Young, Steven R. [ORNL, Oak Ridge; Rose, Derek C. [ORNL, Oak Ridge; Johnston, Travis [ORNL, Oak Ridge; Heller, William T. [ORNL, Oak Ridge; Karnowski, thomas P. [ORNL, Oak Ridge; Potok, Thomas E. [ORNL, Oak Ridge; Patton, Robert M. [ORNL, Oak Ridge; Perdue, Gabriel [Fermilab; Miller, Jonathan [Santa Maria U., Valparaiso

    2017-01-01

    While a large number of deep learning networks have been studied and published that produce outstanding results on natural image datasets, these datasets only make up a fraction of those to which deep learning can be applied. These datasets include text data, audio data, and arrays of sensors that have very different characteristics than natural images. As these “best” networks for natural images have been largely discovered through experimentation and cannot be proven optimal on some theoretical basis, there is no reason to believe that they are the optimal network for these drastically different datasets. Hyperparameter search is thus often a very important process when applying deep learning to a new problem. In this work we present an evolutionary approach to searching the possible space of network hyperparameters and construction that can scale to 18, 000 nodes. This approach is applied to datasets of varying types and characteristics where we demonstrate the ability to rapidly find best hyperparameters in order to enable practitioners to quickly iterate between idea and result.

  20. Deep Space Gateway Science Opportunities

    Science.gov (United States)

    Quincy, C. D.; Charles, J. B.; Hamill, Doris; Sidney, S. C.

    2018-01-01

    The NASA Life Sciences Research Capabilities Team (LSRCT) has been discussing deep space research needs for the last two years. NASA's programs conducting life sciences studies - the Human Research Program, Space Biology, Astrobiology, and Planetary Protection - see the Deep Space Gateway (DSG) as affording enormous opportunities to investigate biological organisms in a unique environment that cannot be replicated in Earth-based laboratories or on Low Earth Orbit science platforms. These investigations may provide in many cases the definitive answers to risks associated with exploration and living outside Earth's protective magnetic field. Unlike Low Earth Orbit or terrestrial locations, the Gateway location will be subjected to the true deep space spectrum and influence of both galactic cosmic and solar particle radiation and thus presents an opportunity to investigate their long-term exposure effects. The question of how a community of biological organisms change over time within the harsh environment of space flight outside of the magnetic field protection can be investigated. The biological response to the absence of Earth's geomagnetic field can be studied for the first time. Will organisms change in new and unique ways under these new conditions? This may be specifically true on investigations of microbial communities. The Gateway provides a platform for microbiology experiments both inside, to improve understanding of interactions between microbes and human habitats, and outside, to improve understanding of microbe-hardware interactions exposed to the space environment.

  1. Impact of Students’ Class Attendance on Recalling Previously Acquired Information

    Directory of Open Access Journals (Sweden)

    Camellia Hemyari

    2018-03-01

    Full Text Available Background: In recent years, availability of class material including typed lectures, the professor’s Power Point slides, sound recordings, and even videos made a group of students feel that it is unnecessary to attend the classes. These students usually read and memorize typed lectures within two or three days prior to the exams and usually pass the tests even with low attendance rate. Thus, the question is how effective is this learning system and how long the one-night memorized lessons may last.Methods: A group of medical students (62 out of 106 students, with their class attendance and educational achievements in the Medical Mycology and Parasitology course being recorded since two years ago, was selected and their knowledge about this course was tested by multiple choice questions (MCQ designed based on the previous lectures.Results: Although the mean re-exam score of the students at the end of the externship was lower than the corresponding final score, a significant association was found between the scores of the students in these two exams (r=0.48, P=0.01. Moreover, a significant negative association was predicted between the number of absences and re-exam scores (r=-0.26, P=0.037.Conclusion: As our findings show, the phenomenon of recalling the acquired lessons is preserved for a long period of time and it is associated with the students’ attendance. Many factors including generation effect (by taking notes and cued-recall (via slide picture might play a significant role in the better recalling of the learned information in students with good class attendance.Keywords: STUDENT, MEMORY, LONG-TERM, RECALL, ABSENTEEISM, LEARNING

  2. Repeat immigration: A previously unobserved source of heterogeneity?

    Science.gov (United States)

    Aradhya, Siddartha; Scott, Kirk; Smith, Christopher D

    2017-07-01

    Register data allow for nuanced analyses of heterogeneities between sub-groups which are not observable in other data sources. One heterogeneity for which register data is particularly useful is in identifying unique migration histories of immigrant populations, a group of interest across disciplines. Years since migration is a commonly used measure of integration in studies seeking to understand the outcomes of immigrants. This study constructs detailed migration histories to test whether misclassified migrations may mask important heterogeneities. In doing so, we identify a previously understudied group of migrants called repeat immigrants, and show that they differ systematically from permanent immigrants. In addition, we quantify the degree to which migration information is misreported in the registers. The analysis is carried out in two steps. First, we estimate income trajectories for repeat immigrants and permanent immigrants to understand the degree to which they differ. Second, we test data validity by cross-referencing migration information with changes in income to determine whether there are inconsistencies indicating misreporting. From the first part of the analysis, the results indicate that repeat immigrants systematically differ from permanent immigrants in terms of income trajectories. Furthermore, income trajectories differ based on the way in which years since migration is calculated. The second part of the analysis suggests that misreported migration events, while present, are negligible. Repeat immigrants differ in terms of income trajectories, and may differ in terms of other outcomes as well. Furthermore, this study underlines that Swedish registers provide a reliable data source to analyze groups which are unidentifiable in other data sources.

  3. Gastrointestinal tolerability with ibandronate after previous weekly bisphosphonate treatment

    Directory of Open Access Journals (Sweden)

    Richard Derman

    2009-09-01

    Full Text Available Richard Derman1, Joseph D Kohles2, Ann Babbitt31Department of Obstetrics and Gynecology, Christiana Hospital, Newark, DE, USA; 2Roche, Nutley, NJ, USA; 3Greater Portland Bone and Joint Specialists, Portland, ME, USAAbstract: Data from two open-label trials (PRIOR and CURRENT of women with postmenopausal osteoporosis or osteopenia were evaluated to assess whether monthly oral and quarterly intravenous (IV ibandronate dosing improved self-reported gastrointestinal (GI tolerability for patients who had previously experienced GI irritation with bisphosphonate (BP use. In PRIOR, women who had discontinued daily or weekly BP treatment due to GI intolerance received monthly oral or quarterly IV ibandronate for 12 months. The CURRENT subanalysis included women receiving weekly BP treatment who switched to monthly oral ibandronate for six months. GI symptom severity and frequency were assessed using the Osteoporosis Patient Satisfaction Questionnaire™. In PRIOR, mean GI tolerability scores increased significantly at month 1 from screening for both treatment groups (oral: 79.3 versus 54.1; IV: 84.4 versus 51.0; p < 0.001 for both. Most patients reported improvement in GI symptom severity and frequency from baseline at all post-screening assessments (>90% at Month 10. In the CURRENT subanalysis >60% of patients reported improvements in heartburn or acid reflux and >70% indicated improvement in other stomach upset at month 6. Postmenopausal women with GI irritability with daily or weekly BPs experienced improvement in symptoms with extended dosing monthly or quarterly ibandronate compared with baseline.Keywords: ibandronate, osteoporosis, bisphosphonate, gastrointestinal

  4. Deep learning improves prediction of CRISPR-Cpf1 guide RNA activity.

    Science.gov (United States)

    Kim, Hui Kwon; Min, Seonwoo; Song, Myungjae; Jung, Soobin; Choi, Jae Woo; Kim, Younggwang; Lee, Sangeun; Yoon, Sungroh; Kim, Hyongbum Henry

    2018-03-01

    We present two algorithms to predict the activity of AsCpf1 guide RNAs. Indel frequencies for 15,000 target sequences were used in a deep-learning framework based on a convolutional neural network to train Seq-deepCpf1. We then incorporated chromatin accessibility information to create the better-performing DeepCpf1 algorithm for cell lines for which such information is available and show that both algorithms outperform previous machine learning algorithms on our own and published data sets.

  5. Drying/rewetting cycles mobilize old C from deep soils from a California annual grassland

    OpenAIRE

    Schimel, JP; Wetterstedt, JAM; Holden, PA; Trumbore, SE

    2011-01-01

    We measured the 14 C and 13 C signatures of CO 2 respired from surface and deep soils released through multiple dry/rewetting cycles in laboratory incubations. The C respired from surface soils included components fixed before and after the 1960s. However, that respired from deep soils was derived from organic matter with a mean turnover time estimated in the range of 650-850 years. This reinforces previous research suggesting that a substantial amount of deep soil C is chemically labile b...

  6. First LOCSMITH locations of deep moonquakes

    Science.gov (United States)

    Hempel, S.; Knapmeyer, M.; Sens-Schönfelder, C.; Oberst, J.

    2008-09-01

    stacking we developed a complex multiparameter correlation algorithm to calculate the optimum time shift. Results We present relocations of selected deep moonquakes in context of data availability and quality. Previous locations are often contained in our location clouds, but realistic location uncertainties allow large deviations from the best fitting solutions, including locations on the far side of the Moon. Perspective By developing new methods for data processing and using the LOCSMITH locating algorithm we hope to reduce the location uncertainty sufficiently to make sure that all sources are on the near side, or to prove a far side origin of some of them. This would answer questions of hemispheric symmetry of lunar deep seismicity and the Moon's internal structure. References [1] Knapmeyer (2008) accepted to GJI. [2] Nakamura (2005) JGR, 110, E01001. [3] Lognonné (2003) EPSL, 211, 2744. [4] Bulow (2005) JGR, 110, E10003. [5] Sonnemann (2005) EGU05A07960. [6] Hempel, Knapmeyer, Oberst (2008) EGU2008A07989.

  7. From Parkinsonian thalamic activity to restoring thalamic relay using deep brain stimulation: new insights from computational modeling

    NARCIS (Netherlands)

    Meijer, Hil Gaétan Ellart; Krupa, M.; Cagnan, H.; Lourens, Marcel Antonius Johannes; Heida, Tjitske; Martens, H.C.F.; Bour, L.J.; van Gils, Stephanus A.

    2011-01-01

    We present a computational model of a thalamocortical relay neuron for exploring basal ganglia thalamocortical loop behavior in relation to Parkinson's disease and deep brain stimulation (DBS). Previous microelectrode, single-unit recording studies demonstrated that oscillatory interaction within

  8. Deep water recycling through time.

    Science.gov (United States)

    Magni, Valentina; Bouilhol, Pierre; van Hunen, Jeroen

    2014-11-01

    We investigate the dehydration processes in subduction zones and their implications for the water cycle throughout Earth's history. We use a numerical tool that combines thermo-mechanical models with a thermodynamic database to examine slab dehydration for present-day and early Earth settings and its consequences for the deep water recycling. We investigate the reactions responsible for releasing water from the crust and the hydrated lithospheric mantle and how they change with subduction velocity ( v s ), slab age ( a ) and mantle temperature (T m ). Our results show that faster slabs dehydrate over a wide area: they start dehydrating shallower and they carry water deeper into the mantle. We parameterize the amount of water that can be carried deep into the mantle, W (×10 5 kg/m 2 ), as a function of v s (cm/yr), a (Myrs), and T m (°C):[Formula: see text]. We generally observe that a 1) 100°C increase in the mantle temperature, or 2) ∼15 Myr decrease of plate age, or 3) decrease in subduction velocity of ∼2 cm/yr all have the same effect on the amount of water retained in the slab at depth, corresponding to a decrease of ∼2.2×10 5 kg/m 2 of H 2 O. We estimate that for present-day conditions ∼26% of the global influx water, or 7×10 8 Tg/Myr of H 2 O, is recycled into the mantle. Using a realistic distribution of subduction parameters, we illustrate that deep water recycling might still be possible in early Earth conditions, although its efficiency would generally decrease. Indeed, 0.5-3.7 × 10 8 Tg/Myr of H 2 O could still be recycled in the mantle at 2.8 Ga. Deep water recycling might be possible even in early Earth conditions We provide a scaling law to estimate the amount of H 2 O flux deep into the mantle Subduction velocity has a a major control on the crustal dehydration pattern.

  9. Vision in the deep sea.

    Science.gov (United States)

    Warrant, Eric J; Locket, N Adam

    2004-08-01

    The deep sea is the largest habitat on earth. Its three great faunal environments--the twilight mesopelagic zone, the dark bathypelagic zone and the vast flat expanses of the benthic habitat--are home to a rich fauna of vertebrates and invertebrates. In the mesopelagic zone (150-1000 m), the down-welling daylight creates an extended scene that becomes increasingly dimmer and bluer with depth. The available daylight also originates increasingly from vertically above, and bioluminescent point-source flashes, well contrasted against the dim background daylight, become increasingly visible. In the bathypelagic zone below 1000 m no daylight remains, and the scene becomes entirely dominated by point-like bioluminescence. This changing nature of visual scenes with depth--from extended source to point source--has had a profound effect on the designs of deep-sea eyes, both optically and neurally, a fact that until recently was not fully appreciated. Recent measurements of the sensitivity and spatial resolution of deep-sea eyes--particularly from the camera eyes of fishes and cephalopods and the compound eyes of crustaceans--reveal that ocular designs are well matched to the nature of the visual scene at any given depth. This match between eye design and visual scene is the subject of this review. The greatest variation in eye design is found in the mesopelagic zone, where dim down-welling daylight and bio-luminescent point sources may be visible simultaneously. Some mesopelagic eyes rely on spatial and temporal summation to increase sensitivity to a dim extended scene, while others sacrifice this sensitivity to localise pinpoints of bright bioluminescence. Yet other eyes have retinal regions separately specialised for each type of light. In the bathypelagic zone, eyes generally get smaller and therefore less sensitive to point sources with increasing depth. In fishes, this insensitivity, combined with surprisingly high spatial resolution, is very well adapted to the

  10. The deep Canary poleward undercurrent

    Science.gov (United States)

    Velez-Belchi, P. J.; Hernandez-Guerra, A.; González-Pola, C.; Fraile, E.; Collins, C. A.; Machín, F.

    2012-12-01

    Poleward undercurrents are well known features in Eastern Boundary systems. In the California upwelling system (CalCEBS), the deep poleward flow has been observed along the entire outer continental shelf and upper-slope, using indirect methods based on geostrophic estimates and also using direct current measurements. The importance of the poleward undercurrents in the CalCEBS, among others, is to maintain its high productivity by means of the transport of equatorial Pacific waters all the way northward to Vancouver Island and the subpolar gyre but there is also concern about the low oxygen concentration of these waters. However, in the case of the Canary Current Eastern Boundary upwelling system (CanCEBS), there are very few observations of the poleward undercurrent. Most of these observations are short-term mooring records, or drifter trajectories of the upper-slope flow. Hence, the importance of the subsurface poleward flow in the CanCEBS has been only hypothesized. Moreover, due to the large differences between the shape of the coastline and topography between the California and the Canary Current system, the results obtained for the CalCEBS are not completely applicable to the CanCEBS. In this study we report the first direct observations of the continuity of the deep poleward flow of the Canary Deep Poleward undercurrent (CdPU) in the North-Africa sector of the CanCEBS, and one of the few direct observations in the North-Africa sector of the Canary Current eastern boundary. The results indicate that the Canary Island archipelago disrupts the deep poleward undercurrent even at depths where the flow is not blocked by the bathymetry. The deep poleward undercurrent flows west around the eastern-most islands and north east of the Conception Bank to rejoin the intermittent branch that follows the African slope in the Lanzarote Passage. This hypothesis is consistent with the AAIW found west of Lanzarote, as far as 17 W. But also, this hypothesis would be coherent

  11. Simulating deep convection with a shallow convection scheme

    Directory of Open Access Journals (Sweden)

    C. Hohenegger

    2011-10-01

    Full Text Available Convective processes profoundly affect the global water and energy balance of our planet but remain a challenge for global climate modeling. Here we develop and investigate the suitability of a unified convection scheme, capable of handling both shallow and deep convection, to simulate cases of tropical oceanic convection, mid-latitude continental convection, and maritime shallow convection. To that aim, we employ large-eddy simulations (LES as a benchmark to test and refine a unified convection scheme implemented in the Single-column Community Atmosphere Model (SCAM. Our approach is motivated by previous cloud-resolving modeling studies, which have documented the gradual transition between shallow and deep convection and its possible importance for the simulated precipitation diurnal cycle.

    Analysis of the LES reveals that differences between shallow and deep convection, regarding cloud-base properties as well as entrainment/detrainment rates, can be related to the evaporation of precipitation. Parameterizing such effects and accordingly modifying the University of Washington shallow convection scheme, it is found that the new unified scheme can represent both shallow and deep convection as well as tropical and mid-latitude continental convection. Compared to the default SCAM version, the new scheme especially improves relative humidity, cloud cover and mass flux profiles. The new unified scheme also removes the well-known too early onset and peak of convective precipitation over mid-latitude continental areas.

  12. Radio-active waste disposal and deep-sea biology

    International Nuclear Information System (INIS)

    Rice, A.L.

    1978-01-01

    The deep-sea has been widely thought of as a remote, sparsely populated, and biologically inactive environment, well suited to receive the noxious products of nuclear fission processes. Much of what is known of abyssal biology tends to support this view, but there are a few disquieting contra-indications. The realisation, in recent years, that many animal groups show a previously unsuspected high species diversity in the deep-sea emphasized the paucity of our knowledge of this environment. More dramatically, the discovery of a large, active, and highly mobile abysso-bentho-pelagic fauna changed the whole concept of abyssal life. Finally, while there is little evidence for the existence of vertical migration patterns linking the deep-sea bottom communities with those of the overlying water layers, there are similarly too few negative results for the possibility of such transport mechanisms to be dismissed. In summary, biological knowledge of the abyss is insufficient to answer the questions raised in connection with deep-sea dumping, but in the absence of adequate answers it might be dangerous to ignore the questions

  13. Deep carbon storage potential of buried floodplain soils.

    Science.gov (United States)

    D'Elia, Amanda H; Liles, Garrett C; Viers, Joshua H; Smart, David R

    2017-08-15

    Soils account for the largest terrestrial pool of carbon and have the potential for even greater quantities of carbon sequestration. Typical soil carbon (C) stocks used in global carbon models only account for the upper 1 meter of soil. Previously unaccounted for deep carbon pools (>1 m) were generally considered to provide a negligible input to total C contents and represent less dynamic C pools. Here we assess deep soil C pools associated with an alluvial floodplain ecosystem transitioning from agricultural production to restoration of native vegetation. We analyzed the soil organic carbon (SOC) concentrations of 87 surface soil samples (0-15 cm) and 23 subsurface boreholes (0-3 m). We evaluated the quantitative importance of the burial process in the sequestration of subsurface C and found our subsurface soils (0-3 m) contained considerably more C than typical C stocks of 0-1 m. This deep unaccounted soil C could have considerable implications for global C accounting. We compared differences in surface soil C related to vegetation and land use history and determined that flooding restoration could promote greater C accumulation in surface soils. We conclude deep floodplain soils may store substantial quantities of C and floodplain restoration should promote active C sequestration.

  14. Part-based deep representation for product tagging and search

    Science.gov (United States)

    Chen, Keqing

    2017-06-01

    Despite previous studies, tagging and indexing the product images remain challenging due to the large inner-class variation of the products. In the traditional methods, the quantized hand-crafted features such as SIFTs are extracted as the representation of the product images, which are not discriminative enough to handle the inner-class variation. For discriminative image representation, this paper firstly presents a novel deep convolutional neural networks (DCNNs) architect true pre-trained on a large-scale general image dataset. Compared to the traditional features, our DCNNs representation is of more discriminative power with fewer dimensions. Moreover, we incorporate the part-based model into the framework to overcome the negative effect of bad alignment and cluttered background and hence the descriptive ability of the deep representation is further enhanced. Finally, we collect and contribute a well-labeled shoe image database, i.e., the TBShoes, on which we apply the part-based deep representation for product image tagging and search, respectively. The experimental results highlight the advantages of the proposed part-based deep representation.

  15. Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

    OpenAIRE

    R.Anita; V.Ganga Bharani; N.Nityanandam; Pradeep Kumar Sahoo

    2011-01-01

    The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based app...

  16. Deep Corals, Deep Learning: Moving the Deep Net Towards Real-Time Image Annotation

    OpenAIRE

    Lea-Anne Henry; Sankha S. Mukherjee; Neil M. Roberston; Laurence De Clippele; J. Murray Roberts

    2016-01-01

    The mismatch between human capacity and the acquisition of Big Data such as Earth imagery undermines commitments to Convention on Biological Diversity (CBD) and Aichi targets. Artificial intelligence (AI) solutions to Big Data issues are urgently needed as these could prove to be faster, more accurate, and cheaper. Reducing costs of managing protected areas in remote deep waters and in the High Seas is of great importance, and this is a realm where autonomous technology will be transformative.

  17. Invited talk: Deep Learning Meets Physics

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Deep Learning has emerged as one of the most successful fields of machine learning and artificial intelligence with overwhelming success in industrial speech, text and vision benchmarks. Consequently it evolved into the central field of research for IT giants like Google, facebook, Microsoft, Baidu, and Amazon. Deep Learning is founded on novel neural network techniques, the recent availability of very fast computers, and massive data sets. In its core, Deep Learning discovers multiple levels of abstract representations of the input. The main obstacle to learning deep neural networks is the vanishing gradient problem. The vanishing gradient impedes credit assignment to the first layers of a deep network or to early elements of a sequence, therefore limits model selection. Major advances in Deep Learning can be related to avoiding the vanishing gradient like stacking, ReLUs, residual networks, highway networks, and LSTM. For Deep Learning, we suggested self-normalizing neural networks (SNNs) which automatica...

  18. Ventilation of the deep Greenland and Norwegian seas: evidence from krypton-85, tritium, carbon-14 and argon-39

    International Nuclear Information System (INIS)

    Smethie, W.M. Jr.; Ostlund, H.G.; Loosli, H.H.

    1986-01-01

    On leg 5 of the TTO expedition, the distributions of 85 Kr, tritium, 14 C, 39 Ar, temperature, salinity, oxygen, carbon dioxide and nutrients were measured in the Greenland and Norwegian seas. These observations support previous observations that Greenland Sea Deep Water is formed by a deep convective process within the Greenland gyre. They also support AAGAARD et al.'s (1985, Journal of Geophysical Research, 90, 4833-4846) new hypothesis that Norwegian Sea Deep Water forms from a mixture of Greenland Sea Deep Water and Eurasian Basin Deep Water. Volume transports estimated from the distributions of 85 Kr, tritium, 14 C and 39 Ar range from 0.53 to 0.74 Sv for exchange between the surface and deep Greenland Sea and from 0.9 to 1.47 Sv for exchange between the deep Greenland and deep Norwegian Seas. The residence time of water and the deep Greenland Sea with respect to exchange with surface water ranges from 24 to 34 years reported by PETERSON and ROOTH (1976, Deep-Sea Research, 23, 273-283) and 35-42 years reported by BULLISTER and WEISS (1983, Science, 221, 265-268). The residence time of water in the deep Norwegian Sea with respect to exchange with the deep Greenland Sea ranges from 19 to 30 years compared to 97-107 years reported by PETERSON and ROOTH (1976) and 10-28 years reported by BULLISTER and WEISS (1983). The oxygen consumption rate was estimated to be at most 1.04 μM kg -1 y -1 for the deep Greenland Sea and to be between 0.47 and 0.79 μM kg -1 y -1 for the deep Norwegian Sea. (author)

  19. Deep remission: a new concept?

    Science.gov (United States)

    Colombel, Jean-Frédéric; Louis, Edouard; Peyrin-Biroulet, Laurent; Sandborn, William J; Panaccione, Remo

    2012-01-01

    Crohn's disease (CD) is a chronic inflammatory disorder characterized by periods of clinical remission alternating with periods of relapse defined by recurrent clinical symptoms. Persistent inflammation is believed to lead to progressive bowel damage over time, which manifests with the development of strictures, fistulae and abscesses. These disease complications frequently lead to a need for surgical resection, which in turn leads to disability. So CD can be characterized as a chronic, progressive, destructive and disabling disease. In rheumatoid arthritis, treatment paradigms have evolved beyond partial symptom control alone toward the induction and maintenance of sustained biological remission, also known as a 'treat to target' strategy, with the goal of improving long-term disease outcomes. In CD, there is currently no accepted, well-defined, comprehensive treatment goal that entails the treatment of both clinical symptoms and biologic inflammation. It is important that such a treatment concept begins to evolve for CD. A treatment strategy that delays or halts the progression of CD to increasing damage and disability is a priority. As a starting point, a working definition of sustained deep remission (that includes long-term biological remission and symptom control) with defined patient outcomes (including no disease progression) has been proposed. The concept of sustained deep remission represents a goal for CD management that may still evolve. It is not clear if the concept also applies to ulcerative colitis. Clinical trials are needed to evaluate whether treatment algorithms that tailor therapy to achieve deep remission in patients with CD can prevent disease progression and disability. Copyright © 2012 S. Karger AG, Basel.

  20. Topics in deep inelastic scattering

    International Nuclear Information System (INIS)

    Wandzura, S.M.

    1977-01-01

    Several topics in deep inelastic lepton--nucleon scattering are discussed, with emphasis on the structure functions appearing in polarized experiments. The major results are: infinite set of new sum rules reducing the number of independent spin dependent structure functions (for electroproduction) from two to one; the application of the techniques of Nachtmann to extract the coefficients appearing in the Wilson operator product expansion; and radiative corrections to the Wilson coefficients of free field theory. Also discussed are the use of dimensional regularization to simplify the calculation of these radiative corrections

  1. Milky Way Past Was More Turbulent Than Previously Known

    Science.gov (United States)

    2004-04-01

    Results of 1001 observing nights shed new light on our Galaxy [1] Summary A team of astronomers from Denmark, Switzerland and Sweden [2] has achieved a major breakthrough in our understanding of the Milky Way, the galaxy in which we live. After more than 1,000 nights of observations spread over 15 years, they have determined the spatial motions of more than 14,000 solar-like stars residing in the neighbourhood of the Sun. For the first time, the changing dynamics of the Milky Way since its birth can now be studied in detail and with a stellar sample sufficiently large to allow a sound analysis. The astronomers find that our home galaxy has led a much more turbulent and chaotic life than previously assumed. PR Photo 10a/04: Distribution on the sky of the observed stars. PR Photo 10b/04: Stars in the solar neigbourhood and the Milky Way galaxy (artist's view). PR Video Clip 04/04: The motions of the observed stars during the past 250 million years. Unknown history Home is the place we know best. But not so in the Milky Way - the galaxy in which we live. Our knowledge of our nearest stellar neighbours has long been seriously incomplete and - worse - skewed by prejudice concerning their behaviour. Stars were generally selected for observation because they were thought to be "interesting" in some sense, not because they were typical. This has resulted in a biased view of the evolution of our Galaxy. The Milky Way started out just after the Big Bang as one or more diffuse blobs of gas of almost pure hydrogen and helium. With time, it assembled into the flattened spiral galaxy which we inhabit today. Meanwhile, generation after generation of stars were formed, including our Sun some 4,700 million years ago. But how did all this really happen? Was it a rapid process? Was it violent or calm? When were all the heavier elements formed? How did the Milky Way change its composition and shape with time? Answers to these and many other questions are 'hot' topics for the

  2. White blood cells identification system based on convolutional deep neural learning networks.

    Science.gov (United States)

    Shahin, A I; Guo, Yanhui; Amin, K M; Sharawi, Amr A

    2017-11-16

    White blood cells (WBCs) differential counting yields valued information about human health and disease. The current developed automated cell morphology equipments perform differential count which is based on blood smear image analysis. Previous identification systems for WBCs consist of successive dependent stages; pre-processing, segmentation, feature extraction, feature selection, and classification. There is a real need to employ deep learning methodologies so that the performance of previous WBCs identification systems can be increased. Classifying small limited datasets through deep learning systems is a major challenge and should be investigated. In this paper, we propose a novel identification system for WBCs based on deep convolutional neural networks. Two methodologies based on transfer learning are followed: transfer learning based on deep activation features and fine-tuning of existed deep networks. Deep acrivation featues are extracted from several pre-trained networks and employed in a traditional identification system. Moreover, a novel end-to-end convolutional deep architecture called "WBCsNet" is proposed and built from scratch. Finally, a limited balanced WBCs dataset classification is performed through the WBCsNet as a pre-trained network. During our experiments, three different public WBCs datasets (2551 images) have been used which contain 5 healthy WBCs types. The overall system accuracy achieved by the proposed WBCsNet is (96.1%) which is more than different transfer learning approaches or even the previous traditional identification system. We also present features visualization for the WBCsNet activation which reflects higher response than the pre-trained activated one. a novel WBCs identification system based on deep learning theory is proposed and a high performance WBCsNet can be employed as a pre-trained network. Copyright © 2017. Published by Elsevier B.V.

  3. Background rejection in NEXT using deep neural networks

    CERN Document Server

    Renner, J.

    2017-01-01

    We investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

  4. Transcriptome sequences resolve deep relationships of the grape family.

    Science.gov (United States)

    Wen, Jun; Xiong, Zhiqiang; Nie, Ze-Long; Mao, Likai; Zhu, Yabing; Kan, Xian-Zhao; Ickert-Bond, Stefanie M; Gerrath, Jean; Zimmer, Elizabeth A; Fang, Xiao-Dong

    2013-01-01

    Previous phylogenetic studies of the grape family (Vitaceae) yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

  5. Transcriptome sequences resolve deep relationships of the grape family.

    Directory of Open Access Journals (Sweden)

    Jun Wen

    Full Text Available Previous phylogenetic studies of the grape family (Vitaceae yielded poorly resolved deep relationships, thus impeding our understanding of the evolution of the family. Next-generation sequencing now offers access to protein coding sequences very easily, quickly and cost-effectively. To improve upon earlier work, we extracted 417 orthologous single-copy nuclear genes from the transcriptomes of 15 species of the Vitaceae, covering its phylogenetic diversity. The resulting transcriptome phylogeny provides robust support for the deep relationships, showing the phylogenetic utility of transcriptome data for plants over a time scale at least since the mid-Cretaceous. The pros and cons of transcriptome data for phylogenetic inference in plants are also evaluated.

  6. Case report: accessory head of the deep forearm flexors

    Science.gov (United States)

    JONES, M.; ABRAHAMS, P. H.; SAÑUDO, J. R.

    1997-01-01

    In 1813 Gantzer described 2 accessory muscles in the human forearm which bear his name (Wood, 1868; Macalister, 1875) and these have subsequently been reported with variable attachments (Wood, 1868; Macalister, 1875; Turner, 1879; Schäfer & Thane, 1894; Le Double, 1897; Dykes & Anson, 1944; Mangini, 1960; Malhotra et al. 1982; Kida, 1988; Tountas & Bergman, 1993). The accessory heads of the deep flexors of the forearm (Gantzer's muscles) have been described as 2 different small bellies which insert either into FPL or FDP. There are no previous reports which have mentioned the existence of an accessory muscle which inserts into both of the 2 deep flexors of the forearm as in the case presented here. PMID:9306208

  7. Clustered deep shadow maps for integrated polyhedral and volume rendering

    KAUST Repository

    Bornik, Alexander

    2012-01-01

    This paper presents a hardware-accelerated approach for shadow computation in scenes containing both complex volumetric objects and polyhedral models. Our system is the first hardware accelerated complete implementation of deep shadow maps, which unifies the computation of volumetric and geometric shadows. Up to now such unified computation was limited to software-only rendering . Previous hardware accelerated techniques can handle only geometric or only volumetric scenes - both resulting in the loss of important properties of the original concept. Our approach supports interactive rendering of polyhedrally bounded volumetric objects on the GPU based on ray casting. The ray casting can be conveniently used for both the shadow map computation and the rendering. We show how anti-aliased high-quality shadows are feasible in scenes composed of multiple overlapping translucent objects, and how sparse scenes can be handled efficiently using clustered deep shadow maps. © 2012 Springer-Verlag.

  8. Background rejection in NEXT using deep neural networks

    International Nuclear Information System (INIS)

    Renner, J.; Farbin, A.; Vidal, J. Muñoz; Benlloch-Rodríguez, J. M.; Botas, A.

    2017-01-01

    Here, we investigate the potential of using deep learning techniques to reject background events in searches for neutrinoless double beta decay with high pressure xenon time projection chambers capable of detailed track reconstruction. The differences in the topological signatures of background and signal events can be learned by deep neural networks via training over many thousands of events. These networks can then be used to classify further events as signal or background, providing an additional background rejection factor at an acceptable loss of efficiency. The networks trained in this study performed better than previous methods developed based on the use of the same topological signatures by a factor of 1.2 to 1.6, and there is potential for further improvement.

  9. Systematic review of the risk of uterine rupture with the use of amnioinfusion after previous cesarean delivery.

    Science.gov (United States)

    Hicks, Paul

    2005-04-01

    Amnioinfusion is commonly used for the intrapartum treatment of women with pregnancy complicated by thick meconium or oligohydramnios with deep variable fetal heart rate decelerations. Its benefit in women with previous cesarean deliveries is less known. Theoretically, rapid increases in intrauterine volume would lead to a higher risk of uterine rupture. Searches of the Cochrane Library from inception to the third quarter of 2001 and MEDLINE, 1966 to November 2001, were performed by using keywords "cesarean" and "amnioinfusion." Search terms were expanded to maximize results. All languages were included. Review articles, editorials, and data previously published in other sites were not analyzed. Four studies were retrieved having unduplicated data describing amnioinfusion in women who were attempting a trial of labor after previous cesarean section. As the studies were of disparate types, meta-analysis was not possible. The use of amnioinfusion in women with previous cesarean delivery who are undergoing a trial of labor may be a safe procedure, but confirmatory large, controlled prospective studies are needed before definitive recommendations can be made.

  10. Deep groundwater flow at Palmottu

    International Nuclear Information System (INIS)

    Niini, H.; Vesterinen, M.; Tuokko, T.

    1993-01-01

    Further observations, measurements, and calculations aimed at determining the groundwater flow regimes and periodical variations in flow at deeper levels were carried out in the Lake Palmottu (a natural analogue study site for radioactive waste disposal in southwestern Finland) drainage basin. These water movements affect the migration of radionuclides from the Palmottu U-Th deposit. The deep water flow is essentially restricted to the bedrock fractures which developed under, and are still affected by, the stress state of the bedrock. Determination of the detailed variations was based on fracture-tectonic modelling of the 12 most significant underground water-flow channels that cross the surficial water of the Palmottu area. According to the direction of the hydraulic gradient the deep water flow is mostly outwards from the Palmottu catchment but in the westernmost section it is partly towards the centre. Estimation of the water flow through the U-Th deposit by the water-balance method is still only approximate and needs continued observation series and improved field measurements

  11. Deep ocean model penetrator experiments

    International Nuclear Information System (INIS)

    Freeman, T.J.; Burdett, J.R.F.

    1986-01-01

    Preliminary trials of experimental model penetrators in the deep ocean have been conducted as an international collaborative exercise by participating members (national bodies and the CEC) of the Engineering Studies Task Group of the Nuclear Energy Agency's Seabed Working Group. This report describes and gives the results of these experiments, which were conducted at two deep ocean study areas in the Atlantic: Great Meteor East and the Nares Abyssal Plain. Velocity profiles of penetrators of differing dimensions and weights have been determined as they free-fell through the water column and impacted the sediment. These velocity profiles are used to determine the final embedment depth of the penetrators and the resistance to penetration offered by the sediment. The results are compared with predictions of embedment depth derived from elementary models of a penetrator impacting with a sediment. It is tentatively concluded that once the resistance to penetration offered by a sediment at a particular site has been determined, this quantity can be used to sucessfully predict the embedment that penetrators of differing sizes and weights would achieve at the same site

  12. Academic Training: Deep Space Telescopes

    CERN Multimedia

    Françoise Benz

    2006-01-01

    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 20, 21, 22, 23, 24 February from 11:00 to 12:00 - Council Chamber on 20, 21, 23, 24 February, TH Auditorium, bldg 4 - 3-006, on 22 February Deep Space Telescopes G. BIGNAMI / CNRS, Toulouse, F & Univ. di Pavia, I The short series of seminars will address results and aims of current and future space astrophysics as the cultural framework for the development of deep space telescopes. It will then present such new tools, as they are currently available to, or imagined by, the scientific community, in the context of the science plans of ESA and of all major world space agencies. Ground-based astronomy, in the 400 years since Galileo's telescope, has given us a profound phenomenological comprehension of our Universe, but has traditionally been limited to the narrow band(s) to which our terrestrial atmosphere is transparent. Celestial objects, however, do not care about our limitations, and distribute most of the information about their physics thro...

  13. Image Captioning with Deep Bidirectional LSTMs

    OpenAIRE

    Wang, Cheng; Yang, Haojin; Bartz, Christian; Meinel, Christoph

    2016-01-01

    This work presents an end-to-end trainable deep bidirectional LSTM (Long-Short Term Memory) model for image captioning. Our model builds on a deep convolutional neural network (CNN) and two separate LSTM networks. It is capable of learning long term visual-language interactions by making use of history and future context information at high level semantic space. Two novel deep bidirectional variant models, in which we increase the depth of nonlinearity transition in different way, are propose...

  14. Deep inelastic processes and the parton model

    International Nuclear Information System (INIS)

    Altarelli, G.

    The lecture was intended as an elementary introduction to the physics of deep inelastic phenomena from the point of view of theory. General formulae and facts concerning inclusive deep inelastic processes in the form: l+N→l'+hadrons (electroproduction, neutrino scattering) are first recalled. The deep inelastic annihilation e + e - →hadrons is then envisaged. The light cone approach, the parton model and their relation are mainly emphasized

  15. Deep inelastic electron and muon scattering

    International Nuclear Information System (INIS)

    Taylor, R.E.

    1975-07-01

    From the review of deep inelastic electron and muon scattering it is concluded that the puzzle of deep inelastic scattering versus annihilation was replaced with the challenge of the new particles, that the evidence for the simplest quark-algebra models of deep inelastic processes is weaker than a year ago. Definite evidence of scale breaking was found but the specific form of that scale breaking is difficult to extract from the data. 59 references

  16. Fast, Distributed Algorithms in Deep Networks

    Science.gov (United States)

    2016-05-11

    shallow networks, additional work will need to be done in order to allow for the application of ADMM to deep nets. The ADMM method allows for quick...Quock V Le, et al. Large scale distributed deep networks. In Advances in Neural Information Processing Systems, pages 1223–1231, 2012. [11] Ken-Ichi...A TRIDENT SCHOLAR PROJECT REPORT NO. 446 Fast, Distributed Algorithms in Deep Networks by Midshipman 1/C Ryan J. Burmeister, USN

  17. Learning Transferable Features with Deep Adaptation Networks

    OpenAIRE

    Long, Mingsheng; Cao, Yue; Wang, Jianmin; Jordan, Michael I.

    2015-01-01

    Recent studies reveal that a deep neural network can learn transferable features which generalize well to novel tasks for domain adaptation. However, as deep features eventually transition from general to specific along the network, the feature transferability drops significantly in higher layers with increasing domain discrepancy. Hence, it is important to formally reduce the dataset bias and enhance the transferability in task-specific layers. In this paper, we propose a new Deep Adaptation...

  18. An Unsupervised Deep Hyperspectral Anomaly Detector

    Directory of Open Access Journals (Sweden)

    Ning Ma

    2018-02-01

    Full Text Available Hyperspectral image (HSI based detection has attracted considerable attention recently in agriculture, environmental protection and military applications as different wavelengths of light can be advantageously used to discriminate different types of objects. Unfortunately, estimating the background distribution and the detection of interesting local objects is not straightforward, and anomaly detectors may give false alarms. In this paper, a Deep Belief Network (DBN based anomaly detector is proposed. The high-level features and reconstruction errors are learned through the network in a manner which is not affected by previous background distribution assumption. To reduce contamination by local anomalies, adaptive weights are constructed from reconstruction errors and statistical information. By using the code image which is generated during the inference of DBN and modified by adaptively updated weights, a local Euclidean distance between under test pixels and their neighboring pixels is used to determine the anomaly targets. Experimental results on synthetic and recorded HSI datasets show the performance of proposed method outperforms the classic global Reed-Xiaoli detector (RXD, local RX detector (LRXD and the-state-of-the-art Collaborative Representation detector (CRD.

  19. Localization noise in deep subwavelength plasmonic devices

    Science.gov (United States)

    Ghoreyshi, Ali; Victora, R. H.

    2018-05-01

    The grain shape dependence of absorption has been investigated in metal-insulator thin films. We demonstrate that randomness in the size and shape of plasmonic particles can lead to Anderson localization of polarization modes in the deep subwavelength regime. These localized modes can contribute to significant variation in the local field. In the case of plasmonic nanodevices, the effects of the localized modes have been investigated by mapping an electrostatic Hamiltonian onto the Anderson Hamiltonian in the presence of a random vector potential. We show that local behavior of the optical beam can be understood in terms of the weighted local density of the localized modes of the depolarization field. Optical nanodevices that operate on a length scale with high variation in the density of states of localized modes will experience a previously unidentified localized noise. This localization noise contributes uncertainty to the output of plasmonic nanodevices and limits their scalability. In particular, the resulting impact on heat-assisted magnetic recording is discussed.

  20. MKID digital readout tuning with deep learning

    Science.gov (United States)

    Dodkins, R.; Mahashabde, S.; O'Brien, K.; Thatte, N.; Fruitwala, N.; Walter, A. B.; Meeker, S. R.; Szypryt, P.; Mazin, B. A.

    2018-04-01

    Microwave Kinetic Inductance Detector (MKID) devices offer inherent spectral resolution, simultaneous read out of thousands of pixels, and photon-limited sensitivity at optical wavelengths. Before taking observations the readout power and frequency of each pixel must be individually tuned, and if the equilibrium state of the pixels change, then the readout must be retuned. This process has previously been performed through manual inspection, and typically takes one hour per 500 resonators (20 h for a ten-kilo-pixel array). We present an algorithm based on a deep convolution neural network (CNN) architecture to determine the optimal bias power for each resonator. The bias point classifications from this CNN model, and those from alternative automated methods, are compared to those from human decisions, and the accuracy of each method is assessed. On a test feed-line dataset, the CNN achieves an accuracy of 90% within 1 dB of the designated optimal value, which is equivalent accuracy to a randomly selected human operator, and superior to the highest scoring alternative automated method by 10%. On a full ten-kilopixel array, the CNN performs the characterization in a matter of minutes - paving the way for future mega-pixel MKID arrays.

  1. Short circuit in deep brain stimulation.

    Science.gov (United States)

    Samura, Kazuhiro; Miyagi, Yasushi; Okamoto, Tsuyoshi; Hayami, Takehito; Kishimoto, Junji; Katano, Mitsuo; Kamikaseda, Kazufumi

    2012-11-01

    The authors undertook this study to investigate the incidence, cause, and clinical influence of short circuits in patients treated with deep brain stimulation (DBS). After the incidental identification of a short circuit during routine follow-up, the authors initiated a policy at their institution of routinely evaluating both therapeutic impedance and system impendence at every outpatient DBS follow-up visit, irrespective of the presence of symptoms suggesting possible system malfunction. This study represents a report of their findings after 1 year of this policy. Implanted DBS leads exhibiting short circuits were identified in 7 patients (8.9% of the patients seen for outpatient follow-up examinations during the 12-month study period). The mean duration from DBS lead implantation to the discovery of the short circuit was 64.7 months. The symptoms revealing short circuits included the wearing off of therapeutic effect, apraxia of eyelid opening, or dysarthria in 6 patients with Parkinson disease (PD), and dystonia deterioration in 1 patient with generalized dystonia. All DBS leads with short circuits had been anchored to the cranium using titanium miniplates. Altering electrode settings resulted in clinical improvement in the 2 PD cases in which patients had specific symptoms of short circuits (2.5%) but not in the other 4 cases. The patient with dystonia underwent repositioning and replacement of a lead because the previous lead was located too anteriorly, but did not experience symptom improvement. In contrast to the sudden loss of clinical efficacy of DBS caused by an open circuit, short circuits may arise due to a gradual decrease in impedance, causing the insidious development of neurological symptoms via limited or extended potential fields as well as shortened battery longevity. The incidence of short circuits in DBS may be higher than previously thought, especially in cases in which DBS leads are anchored with miniplates. The circuit impedance of DBS

  2. An overview of latest deep water technologies

    International Nuclear Information System (INIS)

    Anon.

    1995-01-01

    The 8th Deep Offshore Technology Conference (DOT VIII, Rio de Janeiro, October 30 - November 3, 1995) has brought together renowned specialists in deep water development projects, as well as managers from oil companies and engineering/service companies to discuss state-of-the-art technologies and ongoing projects in the deep offshore. This paper is a compilation of the session summaries about sub sea technologies, mooring and dynamic positioning, floaters (Tension Leg Platforms (TLP) and Floating Production Storage and Off loading (FPSO)), pipelines and risers, exploration and drilling, and other deep water techniques. (J.S.)

  3. The deep ocean under climate change

    Science.gov (United States)

    Levin, Lisa A.; Le Bris, Nadine

    2015-11-01

    The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems.

  4. Docker Containers for Deep Learning Experiments

    OpenAIRE

    Gerke, Paul K.

    2017-01-01

    Deep learning is a powerful tool to solve problems in the area of image analysis. The dominant compute platform for deep learning is Nvidia’s proprietary CUDA, which can only be used together with Nvidia graphics cards. The nivida-docker project allows exposing Nvidia graphics cards to docker containers and thus makes it possible to run deep learning experiments in docker containers.In our department, we use deep learning to solve problems in the area of medical image analysis and use docker ...

  5. Deep Brain Stimulation for Parkinson's Disease

    Science.gov (United States)

    ... about the BRAIN initiative, see www.nih.gov/science/brain . Show More Show Less Search Disorders SEARCH SEARCH Definition Treatment Prognosis Clinical Trials Organizations Publications Definition Deep ...

  6. Potential Osteoporosis Recovery by Deep Sea Water through Bone Regeneration in SAMP8 Mice

    Directory of Open Access Journals (Sweden)

    Hen-Yu Liu

    2013-01-01

    Full Text Available The aim of this study is to examine the therapeutic potential of deep sea water (DSW on osteoporosis. Previously, we have established the ovariectomized senescence-accelerated mice (OVX-SAMP8 and demonstrated strong recovery of osteoporosis by stem cell and platelet-rich plasma (PRP. Deep sea water at hardness (HD 1000 showed significant increase in proliferation of osteoblastic cell (MC3T3 by MTT assay. For in vivo animal study, bone mineral density (BMD was strongly enhanced followed by the significantly increased trabecular numbers through micro-CT examination after a 4-month deep sea water treatment, and biochemistry analysis showed that serum alkaline phosphatase (ALP activity was decreased. For stage-specific osteogenesis, bone marrow-derived stromal cells (BMSCs were harvested and examined. Deep sea water-treated BMSCs showed stronger osteogenic differentiation such as BMP2, RUNX2, OPN, and OCN, and enhanced colony forming abilities, compared to the control group. Interestingly, most untreated OVX-SAMP8 mice died around 10 months; however, approximately 57% of DSW-treated groups lived up to 16.6 months, a life expectancy similar to the previously reported life expectancy for SAMR1 24 months. The results demonstrated the regenerative potentials of deep sea water on osteogenesis, showing that deep sea water could potentially be applied in osteoporosis therapy as a complementary and alternative medicine (CAM.

  7. Supercement for Annular Seal and Long-Term Integrity in Deep, Hot Wells "DeepTrek"

    Energy Technology Data Exchange (ETDEWEB)

    CSI Technologies

    2007-08-31

    The purpose of this project is to formulate a 'Supercement' designed for improving the long-term sealing integrity in HPHT wells. Phase I concentrated on chemistry studies and screening tests to design and evaluate Portland-based, hybrid Portland, and non-Portland-based cement systems suitable for further scale-up testing. Phase II work concentrated on additional lab and field testing to reduce the candidate materials list to two systems, as well as scaleup activities aimed at verifying performance at the field scale. Phase II was extended thorough a proposal to develop additional testing capabilities aimed at quantifying cementing material properties and performance that were previously not possible. Phase III focused on bringing the material(s) developed in previous Phases to commercialization, through Field Trials, Cost/Benefit Analysis, and Technology Transfer. Extensive development and testing work throughout the project led to Phase III commercialization of two very different materials: (1) Highly-expansive cement (Portland-based), patent pending as 'PRESTRESSED CEMENT'; and (2) Epoxy Resin (non-Portland-based), patent pending. Trade name is Ultra Seal-R. In Phase III, work concentrated on application of the Supercement materials in various increasingly-challenging wells. Previous testing revealed that PRESTRESSED CEMENT, when applied in weak or unconsolidated formations, tends to expand away from the central pipe, restricting the applicability of this material to competent formations. Tests were devised to quantify this effect so the material could be applied in appropriate wells. Additionally, the testing was needed because of industry resistance to expansive cements, due to previous marketing attempts with other materials that were less than successful. Field trials with the Epoxy Resin currently numbers in the hundreds of jobs at up to 295 deg F, with a large percentage being completely successful. Both the PRESTRESSED CEMENT as well

  8. A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

    Science.gov (United States)

    Spencer, Matt; Eickholt, Jesse; Jianlin Cheng

    2015-01-01

    Ab initio protein secondary structure (SS) predictions are utilized to generate tertiary structure predictions, which are increasingly demanded due to the rapid discovery of proteins. Although recent developments have slightly exceeded previous methods of SS prediction, accuracy has stagnated around 80 percent and many wonder if prediction cannot be advanced beyond this ceiling. Disciplines that have traditionally employed neural networks are experimenting with novel deep learning techniques in attempts to stimulate progress. Since neural networks have historically played an important role in SS prediction, we wanted to determine whether deep learning could contribute to the advancement of this field as well. We developed an SS predictor that makes use of the position-specific scoring matrix generated by PSI-BLAST and deep learning network architectures, which we call DNSS. Graphical processing units and CUDA software optimize the deep network architecture and efficiently train the deep networks. Optimal parameters for the training process were determined, and a workflow comprising three separately trained deep networks was constructed in order to make refined predictions. This deep learning network approach was used to predict SS for a fully independent test dataset of 198 proteins, achieving a Q3 accuracy of 80.7 percent and a Sov accuracy of 74.2 percent.

  9. Deep inelastic scattering and disquarks

    International Nuclear Information System (INIS)

    Anselmino, M.

    1993-01-01

    The most comprehensive and detailed analyses of the existing data on the structure function F 2 (x, Q 2 ) of free nucleons, from the deep inelastic scattering (DIS) of charged leptons on hydrogen and deuterium targets, have proved beyond any doubt that higher twist, 1/Q 2 corrections are needed in order to obtain a perfect agreement between perturbative QCD predictions and the data. These higher twist corrections take into account two quark correlations inside the nucleon; it is then natural to try to model them in the quark-diquark model of the proton. In so doing all interactions between the two quarks inside the diquark, both perturbative and non perturbative, are supposed to be taken into account. (orig./HSI)

  10. Detector for deep well logging

    International Nuclear Information System (INIS)

    1976-01-01

    A substantial improvement in the useful life and efficiency of a deep-well scintillation detector is achieved by a unique construction wherein the steel cylinder enclosing the sodium iodide scintillation crystal is provided with a tapered recess to receive a glass window which has a high transmittance at the critical wavelength and, for glass, a high coefficient of thermal expansion. A special high-temperature epoxy adhesive composition is employed to form a relatively thick sealing annulus which keeps the glass window in the tapered recess and compensates for the differences in coefficients of expansion between the container and glass so as to maintain a hermetic seal as the unit is subjected to a wide range of temperature

  11. Deep borehole disposal of plutonium

    International Nuclear Information System (INIS)

    Gibb, F. G. F.; Taylor, K. J.; Burakov, B. E.

    2008-01-01

    Excess plutonium not destined for burning as MOX or in Generation IV reactors is both a long-term waste management problem and a security threat. Immobilisation in mineral and ceramic-based waste forms for interim safe storage and eventual disposal is a widely proposed first step. The safest and most secure form of geological disposal for Pu yet suggested is in very deep boreholes and we propose here that the key to successful combination of these immobilisation and disposal concepts is the encapsulation of the waste form in small cylinders of recrystallized granite. The underlying science is discussed and the results of high pressure and temperature experiments on zircon, depleted UO 2 and Ce-doped cubic zirconia enclosed in granitic melts are presented. The outcomes of these experiments demonstrate the viability of the proposed solution and that Pu could be successfully isolated from its environment for many millions of years. (authors)

  12. Automatic Differentiation and Deep Learning

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Statistical learning has been getting more and more interest from the particle-physics community in recent times, with neural networks and gradient-based optimization being a focus. In this talk we shall discuss three things: automatic differention tools: tools to quickly build DAGs of computation that are fully differentiable. We shall focus on one such tool "PyTorch".  Easy deployment of trained neural networks into large systems with many constraints: for example, deploying a model at the reconstruction phase where the neural network has to be integrated into CERN's bulk data-processing C++-only environment Some recent models in deep learning for segmentation and generation that might be useful for particle physics problems.

  13. Jets in deep inelastic scattering

    International Nuclear Information System (INIS)

    Joensson, L.

    1995-01-01

    Jet production in deep inelastic scattering provides a basis for the investigation of various phenomena related to QCD. Two-jet production at large Q 2 has been studied and the distributions with respect to the partonic scaling variables have been compared to models and to next to leading order calculations. The first observations of azimuthal asymmetries of jets produced in first order α s processes have been obtained. The gluon initiated boson-gluon fusion process permits a direct determination of the gluon density of the proton from an analysis of the jets produced in the hard scattering process. A comparison of these results with those from indirect extractions of the gluon density provides an important test of QCD. (author)

  14. NESTOR Deep Sea Neutrino Telescope

    International Nuclear Information System (INIS)

    Aggouras, G.; Anassontzis, E.G.; Ball, A.E.; Bourlis, G.; Chinowsky, W.; Fahrun, E.; Grammatikakis, G.; Green, C.; Grieder, P.; Katrivanos, P.; Koske, P.; Leisos, A.; Markopoulos, E.; Minkowsky, P.; Nygren, D.; Papageorgiou, K.; Przybylski, G.; Resvanis, L.K.; Siotis, I.; Sopher, J.; Staveris-Polikalas, A.; Tsagli, V.; Tsirigotis, A.; Tzamarias, S.; Zhukov, V.A.

    2006-01-01

    One module of NESTOR, the Mediterranean deep-sea neutrino telescope, was deployed at a depth of 4000m, 14km off the Sapienza Island, off the South West coast of Greece. The deployment site provides excellent environmental characteristics. The deployed NESTOR module is constructed as a hexagonal star like latticed titanium star with 12 Optical Modules and an one-meter diameter titanium sphere which houses the electronics. Power and data were transferred through a 30km electro-optical cable to the shore laboratory. In this report we describe briefly the detector and the detector electronics and discuss the first physics data acquired and give the zenith angular distribution of the reconstructed muons

  15. Deep Borehole Disposal Safety Analysis.

    Energy Technology Data Exchange (ETDEWEB)

    Freeze, Geoffrey A. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Stein, Emily [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Price, Laura L. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); MacKinnon, Robert J. [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States); Tillman, Jack Bruce [Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

    2016-10-01

    This report presents a preliminary safety analysis for the deep borehole disposal (DBD) concept, using a safety case framework. A safety case is an integrated collection of qualitative and quantitative arguments, evidence, and analyses that substantiate the safety, and the level of confidence in the safety, of a geologic repository. This safety case framework for DBD follows the outline of the elements of a safety case, and identifies the types of information that will be required to satisfy these elements. At this very preliminary phase of development, the DBD safety case focuses on the generic feasibility of the DBD concept. It is based on potential system designs, waste forms, engineering, and geologic conditions; however, no specific site or regulatory framework exists. It will progress to a site-specific safety case as the DBD concept advances into a site-specific phase, progressing through consent-based site selection and site investigation and characterization.

  16. DeepRT: deep learning for peptide retention time prediction in proteomics

    OpenAIRE

    Ma, Chunwei; Zhu, Zhiyong; Ye, Jun; Yang, Jiarui; Pei, Jianguo; Xu, Shaohang; Zhou, Ruo; Yu, Chang; Mo, Fan; Wen, Bo; Liu, Siqi

    2017-01-01

    Accurate predictions of peptide retention times (RT) in liquid chromatography have many applications in mass spectrometry-based proteomics. Herein, we present DeepRT, a deep learning based software for peptide retention time prediction. DeepRT automatically learns features directly from the peptide sequences using the deep convolutional Neural Network (CNN) and Recurrent Neural Network (RNN) model, which eliminates the need to use hand-crafted features or rules. After the feature learning, pr...

  17. 75 FR 39143 - Airworthiness Directives; Arrow Falcon Exporters, Inc. (previously Utah State University); AST...

    Science.gov (United States)

    2010-07-08

    ... (previously Precision Helicopters, LLC); Robinson Air Crane, Inc.; San Joaquin Helicopters (previously Hawkins... (Previously Hawkins & Powers Aviation); S.M. &T. Aircraft (Previously Us Helicopter Inc., UNC Helicopters, Inc...

  18. 75 FR 66009 - Airworthiness Directives; Cessna Aircraft Company (Type Certificate Previously Held by Columbia...

    Science.gov (United States)

    2010-10-27

    ... Company (Type Certificate Previously Held by Columbia Aircraft Manufacturing (Previously the Lancair... Company (Type Certificate Previously Held by Columbia Aircraft Manufacturing (Previously The Lancair...-15895. Applicability (c) This AD applies to the following Cessna Aircraft Company (type certificate...

  19. Impact disruption and recovery of the deep subsurface biosphere

    DEFF Research Database (Denmark)

    Cockell, Charles S.; Voytek, Mary A.; Gronstal, Aaaron L

    2012-01-01

    the 35 million-year-old Chesapeake Bay impact structure, USA, with robust contamination control. Microbial enumerations displayed a logarithmic downward decline, but the different gradient, when compared to previously studied sites, and the scatter of the data are consistent with a microbiota influenced......Although a large fraction of the world's biomass resides in the subsurface, there has been no study of the effects of catastrophic disturbance on the deep biosphere and the rate of its subsequent recovery. We carried out an investigation of the microbiology of a 1.76 km drill core obtained from...

  20. Departures from the impulse approximation in deep inelastic neutron scattering

    International Nuclear Information System (INIS)

    Mayers, J.

    1989-01-01

    A new formulation of the impulse approximation (IA) in deep inelastic neutron scattering is developed. It is shown that observed departures from the IA at intermediate momentum transfers are caused by the quantum nature of the initial state rather than final state effects, as has previously been assumed and that these effects become small at high temperatures. It is also argued that final state broadening is significant for He liquids in all feasible experiments, but that in other systems the IA is approached at high momentum transfers. (author)

  1. Expertize of hydrochemical investigation Know-how for deep underground

    International Nuclear Information System (INIS)

    Iwatsuki, Teruki; Mizuno, Takashi; Amano, Yuki; Kunimaru, Takanori; Semba, Takeshi

    2012-03-01

    This report summarizes technical basis and the Know-how on hydrochemical investigations for deep underground as a part of METI project 'Development of Information Synthesis and Interpretation System (ISIS)'. We describe the procedures and methods of hydrochemical investigation in following stages; 1) initial analysis of previous information, 2) planning of borehole investigation, 3) borehole investigation at field, and 4) construct the 'hydrochemical model' representing hydrochemical condition and the evolution process. The contents of this report are inputted to 'Expert system' developed by METI project and are available on WEB system (internet). (author)

  2. Initial study of deep inelastic scattering with ZEUS at HERA

    Science.gov (United States)

    Derrick, M.; Krakauer, D.; Magill, S.; Musgrave, B.; Repond, J.; Repond, S.; Stanek, R.; Talaga, R. L.; Thron, J.; Arzarello, F.; Ayad, R.; Barbagli, G.; Bari, G.; Basile, M.; Bellagamba, L.; Boscherini, D.; Bruni, A.; Bruni, G.; Bruni, P.; Cara Romeo, G.; Castellini, G.; Chiarini, M.; Cifarelli, L.; Cindolo, F.; Ciralli, F.; Contin, A.; D'Auria, S.; del Papa, C.; Frasconi, F.; Giusti, P.; Iacobucci, G.; Laurenti, G.; Levi, G.; Lin, Q.; Lisowski, B.; Maccarrone, G.; Margotti, A.; Massam, T.; Nania, R.; Nemoz, C.; Palmonari, F.; Sartorelli, G.; Timellini, R.; Zamora Garcia, Y.; Zichichi, A.; Bargende, A.; Crittenden, J.; Dabbous, H.; Desch, K.; Diekmann, B.; Doeker, T.; Geerts, M.; Geitz, G.; Gutjahr, B.; Hartmann, H.; Hartmann, J.; Haun, D.; Heinloth, K.; Hilger, E.; Jakob, H.-P.; Kramarczyk, S.; Kückes, M.; Mass, A.; Mengel, S.; Mollen, J.; Monaldi, D.; Müsch, H.; Paul, E.; Schattevoy, R.; Schneider, J.-L.; Wedemeyer, R.; Cassidy, A.; Cussans, D. G.; Dyce, N.; Fawcett, H. F.; Foster, B.; Gilmore, R.; Heath, G. P.; Lancaster, M.; Llewellyn, T. J.; Malos, J.; Morgado, C. J. S.; Tapper, R. J.; Wilson, S. S.; Rau, R. R.; Barillari, T.; Schioppa, M.; Susinno, G.; Bernstein, A.; Caldwell, A.; Gialas, I.; Parsons, J. A.; Ritz, S.; Sciulli, F.; Straub, P. B.; Wai, L.; Yang, S.; Burkot, W.; Eskreys, A.; Piotrzkowski, K.; Zachara, M.; Zawiejski, L.; Borzemski, P.; Jeleń, K.; Kisielewska, D.; Kowalski, T.; Rulikowska-Zerȩbska, E.; Suszycki, L.; Zajc, J.; Kȩdzierski, T.; Kotański, A.; Przybycień, M.; Bauerdick, L. A. T.; Behrens, U.; Bienlein, J. K.; Coldewey, C.; Dannemann, A.; Dierks, K.; Dorth, W.; Drews, G.; Erhard, P.; Flasiński, M.; Fleck, I.; Fürtjes, A.; Gläser, R.; Göttlicher, P.; Hass, T.; Hagge, L.; Hain, W.; Hasell, D.; Hultschig, H.; Jahnen, G.; Joos, P.; Kasemann, M.; Klanner, R.; Koch, W.; Kötz, U.; Kowalski, H.; Labs, J.; Ladage, A.; Löhr, B.; Lüke, D.; Mainusch, J.; Manczak, O.; Momayezi, M.; Ng, J. S. T.; Nicel, S.; Notz, D.; Park, I. H.; Pösnecker, K.-U.; Rohde, M.; Ros, E.; Schneekloth, S.; Schroeder, J.; Schulz, W.; Selonke, F.; Stiliaris, E.; Tscheslog, E.; Tsurugai, T.; Turkot, F.; Vogel, W.; Woeniger, T.; Wolf, G.; Youngman, C.; Grabosch, H. J.; Leich, A.; Meyer, A.; Rethfeldt, C.; Schlensthdt, S.; Casalbuoni, R.; de Curtis, S.; Dominici, D.; Francescato, A.; Nuti, M.; Pelfer, P.; Anzivino, G.; Casaccia, R.; de Pasquale, S.; Qian, S.; Votano, L.; Bamberger, A.; Freidhof, A.; Poser, T.; Söldner-Rembold, S.; Theisen, G.; Trefzger, T.; Brook, N. H.; Bussey, P. J.; Doyle, A. T.; Forbes, J. R.; Jamieson, V. A.; Raine, C.; Saxon, D. H.; Brückmann, H.; Gloth, G.; Holm, U.; Kammerdocher, H.; Krebs, B.; Neumann, T.; Wick, K.; Hofmann, A.; Kröger, W.; Krüger, J.; Lohrmann, E.; Milewski, J.; Nakahata, M.; Pavel, N.; Poelz, G.; Salomon, R.; Seidman, A.; Schott, W.; Wiik, B. H.; Zetsche, F.; Bacon, T. C.; Butterworth, I.; Markou, C.; McQuillan, D.; Miller, D. B.; Mobayyen, M. M.; Prinias, A.; Vorvolakos, A.; Bienz, T.; Kreutzmann, H.; Mallik, U.; McCliment, E.; Roco, M.; Wang, M. Z.; Cloth, P.; Filges, D.; Chen, L.; Imlay, R.; Kartik, S.; Kim, H.-J.; McNeil, R. R.; Metcalf, W.; Barreiro, F.; Cases, G.; Hervás, L.; Labarga, L.; del Peso, J.; Roldán, J.; Terrón, J.; de Trocóniz, J. F.; Ikraiam, F.; Mayer, J. K.; Smith, G. R.; Corriveau, F.; Gilkinson, D. J.; Hanna, D. S.; Hung, L. W.; Mitchell, J. W.; Patel, P. M.; Sinclair, L. E.; Stairs, D. G.; Ullmann, R.; Bashindzhagyan, G. L.; Ermolov, P. F.; Golubkov, Y. A.; Kuzmin, V. A.; Kuznetsov, E. N.; Savin, A. A.; Voronin, A. G.; Zotov, N. P.; Bentvelsen, S.; Dake, A.; Engelen, J.; de Jong, P.; de Jong, S.; de Kamps, M.; Kooijman, P.; Kruse, A.; van der Lugt, H.; O'dell, V.; Straver, J.; Tenner, A.; Tiecke, H.; Uijterwaal, H.; Vermeulen, J.; Wiggers, L.; de Wolf, E.; van Woudenberg, R.; Yoshida, R.; Bylsma, B.; Durkin, L. S.; Li, C.; Ling, T. Y.; McLean, K. W.; Murray, W. N.; Park, S. K.; Romanowski, T. A.; Seidlein, R.; Blair, G. A.; Butterworth, J. M.; Byrne, A.; Cashmore, R. J.; Cooper-Sarkar, A. M.; Devenish, R. C. E.; Gingrich, D. M.; Hallam-Baker, P. M.; Harnew, N.; Khatri, T.; Long, K. R.; Luffman, P.; McArthur, I.; Morawitz, P.; Nash, J.; Smith, S. J. P.; Roocroft, N. C.; Wilson, F. F.; Abbiendi, G.; Brugnera, R.; Carlin, R.; dal Corso, F.; de Giorgi, M.; Dosselli, U.; Gasparini, F.; Limentani, S.; Morandin, M.; Posocco, M.; Stanco, L.; Stroili, R.; Voci, C.; Field, G.; Lim, J. N.; Oh, B. Y.; Whitmore, J.; Contino, U.; D'Agostini, G.; Guida, M.; Iori, M.; Mari, S. M.; Marini, G.; Mattioli, M.; Nigro, A.; Hart, J. C.; McCubbin, N. A.; Shah, T. P.; Short, T. L.; Barberis, E.; Cartiglia, N.; Heusch, C.; Hubbard, B.; Leslie, J.; O'Shaughnessy, K.; Sadrozinski, H. F.; Seiden, A.; Badura, E.; Biltzinger, J.; Chaves, H.; Rost, M.; Seifert, R. J.; Walenta, A. H.; Weihs, W.; Zech, G.; Dagan, S.; Levy, A.; Zer-Zion, D.; Hasegawa, T.; Hazumi, M.; Ishii, T.; Kasai, S.; Kuze, M.; Nagasawa, Y.; Nakao, M.; Okuno, H.; Tokushuku, K.; Watanabe, T.; Yamada, S.; Chiba, M.; Hamatsu, R.; Hirose, T.; Kitamura, S.; Nagayama, S.; Nakamitsu, Y.; Arneodo, M.; Costa, M.; Ferrero, M. I.; Lamberti, L.; Maselli, S.; Peroni, C.; Solano, A.; Staiano, A.; Dardo, M.; Bailey, D. C.; Bandyopadhyay, D.; Benard, F.; Bhadra, S.; Brkic, M.; Burow, B. D.; Chlebana, F. S.; Crombie, M. B.; Hartner, G. F.; Levman, G. M.; Martin, J. F.; Orr, R. S.; Prentice, J. D.; Sampson, C. R.; Stairs, G. G.; Teuscher, R. J.; Yoon, T.-S.; Bullock, F. W.; Catterall, C. D.; Giddings, J. C.; Jones, T. W.; Khan, A. M.; Lane, J. B.; Makkar, P. L.; Shaw, D.; Shulman, J.; Blankenship, K.; Gibaut, D. B.; Kochocki, J.; Lu, B.; Mo, L. W.; Charchula, K.; Ciborowski, J.; Gajewski, J.; Grzelak, G.; Kasprzak, M.; Krzyżanowski, M.; Muchorowski, K.; Nowak, R. J.; Pawlak, J. M.; Stojda, K.; Stopczyński, A.; Szwed, R.; Tymieniecka, T.; Walczak, R.; Wróblewski, A. K.; Zakrzewski, J. A.; Zarnecki, A. F.; Adamus, M.; Abramowicz, H.; Eisenberg, Y.; Glasman, C.; Karshon, U.; Montag, A.; Revel, D.; Shapira, A.; Ali, I.; Behrens, B.; Camerini, U.; Dasu, S.; Fordham, C.; Foudas, C.; Goussiou, A.; Lomperski, M.; Loveless, R. J.; Nylander, P.; Ptacek, M.; Reeder, D. D.; Smith, W. H.; Silverstein, S.; Frisken, W. R.; Furutani, K. M.; Iga, Y.

    1993-04-01

    Results are presented on neutral current, deep inelastic scattering measured in collisions of 26.7 GeV electrons and 820 GeV protons. The events typically populate a range in Q2 from 10 to 100 GeV2. The values of x extend down to x ~ 10-4 which is two orders of magnitude lower than previously measured at such Q2 values in fixed target experiments. The measured cross sections are in accord with the extrapolations of current parametrisations of parton distributions.

  3. Equivalent drawbead performance in deep drawing simulations

    NARCIS (Netherlands)

    Meinders, Vincent T.; Geijselaers, Hubertus J.M.; Huetink, Han

    1999-01-01

    Drawbeads are applied in the deep drawing process to improve the control of the material flow during the forming operation. In simulations of the deep drawing process these drawbeads can be replaced by an equivalent drawbead model. In this paper the usage of an equivalent drawbead model in the

  4. Is deep dreaming the new collage?

    Science.gov (United States)

    Boden, Margaret A.

    2017-10-01

    Deep dreaming (DD) can combine and transform images in surprising ways. But, being based in deep learning (DL), it is not analytically understood. Collage is an art form that is constrained along various dimensions. DD will not be able to generate collages until DL can be guided in a disciplined fashion.

  5. Deep web search: an overview and roadmap

    NARCIS (Netherlands)

    Tjin-Kam-Jet, Kien; Trieschnigg, Rudolf Berend; Hiemstra, Djoerd

    2011-01-01

    We review the state-of-the-art in deep web search and propose a novel classification scheme to better compare deep web search systems. The current binary classification (surfacing versus virtual integration) hides a number of implicit decisions that must be made by a developer. We make these

  6. Research Proposal for Distributed Deep Web Search

    NARCIS (Netherlands)

    Tjin-Kam-Jet, Kien

    2010-01-01

    This proposal identifies two main problems related to deep web search, and proposes a step by step solution for each of them. The first problem is about searching deep web content by means of a simple free-text interface (with just one input field, instead of a complex interface with many input

  7. Development of Hydro-Mechanical Deep Drawing

    DEFF Research Database (Denmark)

    Zhang, Shi-Hong; Danckert, Joachim

    1998-01-01

    The hydro-mechanical deep-drawing process is reviewed in this article. The process principles and features are introduced and the developments of the hydro-mechanical deep-drawing process in process performances, in theory and in numerical simulation are described. The applications are summarized....... Some other related hydraulic forming processes are also dealt with as a comparison....

  8. Stable architectures for deep neural networks

    Science.gov (United States)

    Haber, Eldad; Ruthotto, Lars

    2018-01-01

    Deep neural networks have become invaluable tools for supervised machine learning, e.g. classification of text or images. While often offering superior results over traditional techniques and successfully expressing complicated patterns in data, deep architectures are known to be challenging to design and train such that they generalize well to new data. Critical issues with deep architectures are numerical instabilities in derivative-based learning algorithms commonly called exploding or vanishing gradients. In this paper, we propose new forward propagation techniques inspired by systems of ordinary differential equations (ODE) that overcome this challenge and lead to well-posed learning problems for arbitrarily deep networks. The backbone of our approach is our interpretation of deep learning as a parameter estimation problem of nonlinear dynamical systems. Given this formulation, we analyze stability and well-posedness of deep learning and use this new understanding to develop new network architectures. We relate the exploding and vanishing gradient phenomenon to the stability of the discrete ODE and present several strategies for stabilizing deep learning for very deep networks. While our new architectures restrict the solution space, several numerical experiments show their competitiveness with state-of-the-art networks.

  9. Temperature impacts on deep-sea biodiversity.

    Science.gov (United States)

    Yasuhara, Moriaki; Danovaro, Roberto

    2016-05-01

    Temperature is considered to be a fundamental factor controlling biodiversity in marine ecosystems, but precisely what role temperature plays in modulating diversity is still not clear. The deep ocean, lacking light and in situ photosynthetic primary production, is an ideal model system to test the effects of temperature changes on biodiversity. Here we synthesize current knowledge on temperature-diversity relationships in the deep sea. Our results from both present and past deep-sea assemblages suggest that, when a wide range of deep-sea bottom-water temperatures is considered, a unimodal relationship exists between temperature and diversity (that may be right skewed). It is possible that temperature is important only when at relatively high and low levels but does not play a major role in the intermediate temperature range. Possible mechanisms explaining the temperature-biodiversity relationship include the physiological-tolerance hypothesis, the metabolic hypothesis, island biogeography theory, or some combination of these. The possible unimodal relationship discussed here may allow us to identify tipping points at which on-going global change and deep-water warming may increase or decrease deep-sea biodiversity. Predicted changes in deep-sea temperatures due to human-induced climate change may have more adverse consequences than expected considering the sensitivity of deep-sea ecosystems to temperature changes. © 2014 Cambridge Philosophical Society.

  10. The Next Era: Deep Learning in Pharmaceutical Research.

    Science.gov (United States)

    Ekins, Sean

    2016-11-01

    Over the past decade we have witnessed the increasing sophistication of machine learning algorithms applied in daily use from internet searches, voice recognition, social network software to machine vision software in cameras, phones, robots and self-driving cars. Pharmaceutical research has also seen its fair share of machine learning developments. For example, applying such methods to mine the growing datasets that are created in drug discovery not only enables us to learn from the past but to predict a molecule's properties and behavior in future. The latest machine learning algorithm garnering significant attention is deep learning, which is an artificial neural network with multiple hidden layers. Publications over the last 3 years suggest that this algorithm may have advantages over previous machine learning methods and offer a slight but discernable edge in predictive performance. The time has come for a balanced review of this technique but also to apply machine learning methods such as deep learning across a wider array of endpoints relevant to pharmaceutical research for which the datasets are growing such as physicochemical property prediction, formulation prediction, absorption, distribution, metabolism, excretion and toxicity (ADME/Tox), target prediction and skin permeation, etc. We also show that there are many potential applications of deep learning beyond cheminformatics. It will be important to perform prospective testing (which has been carried out rarely to date) in order to convince skeptics that there will be benefits from investing in this technique.

  11. The deep hydrogeologic flow system underlying the Oak Ridge Reservation

    International Nuclear Information System (INIS)

    Nativ, R.; Hunley, A.E.

    1993-07-01

    The deep hydrogeologic system underlying the Oak Ridge Reservation contains some areas contaminated with radionuclides, heavy metals, nitrates, and organic compounds. The groundwater at that depth is saline and has previously been considered stagnant. On the basis of existing and newly collected data, the nature of flow of the saline groundwater and its potential discharge into shallow, freshwater systems was assessed. Data used for this purpose included (1) spatial and temporal pressures and hydraulic heads measured in the deep system, (2) hydraulic parameters of the formations in question, (3) spatial temperature variations, and (4) spatial and temporal chemical and isotopic composition of the saline groundwater. In addition, chemical analyses of brine in adjacent areas in Tennessee, Kentucky, Ohio, Pennsylvania, and West Virginia were compared with the deep water underlying the reservation to help assess the origin of the brine. Preliminary conclusions suggest that the saline water contained at depth is old but not isolated (in terms of recharge and discharge) from the overlying active and freshwater-bearing units. The confined water (along with dissolved solutes) moves along open fractures (or man-made shortcuts) at relatively high velocity into adjacent, more permeable units. Groundwater volumes involved in this flow probably are small

  12. Impact disruption and recovery of the deep subsurface biosphere

    Science.gov (United States)

    Cockell, Charles S.; Voytek, Mary A.; Gronstal, Aaron L.; Finster, Kai; Kirshtein, Julie D.; Howard, Kieren; Reitner, Joachim; Gohn, Gregory S.; Sanford, Ward E.; Horton, J. Wright; Kallmeyer, Jens; Kelly, Laura; Powars, David S.

    2012-01-01

    Although a large fraction of the world's biomass resides in the subsurface, there has been no study of the effects of catastrophic disturbance on the deep biosphere and the rate of its subsequent recovery. We carried out an investigation of the microbiology of a 1.76 km drill core obtained from the ~35 million-year-old Chesapeake Bay impact structure, USA, with robust contamination control. Microbial enumerations displayed a logarithmic downward decline, but the different gradient, when compared to previously studied sites, and the scatter of the data are consistent with a microbiota influenced by the geological disturbances caused by the impact. Microbial abundance is low in buried crater-fill, ocean-resurge, and avalanche deposits despite the presence of redox couples for growth. Coupled with the low hydraulic conductivity, the data suggest the microbial community has not yet recovered from the impact ~35 million years ago. Microbial enumerations, molecular analysis of microbial enrichment cultures, and geochemical analysis showed recolonization of a deep region of impact-fractured rock that was heated to above the upper temperature limit for life at the time of impact. These results show how, by fracturing subsurface rocks, impacts can extend the depth of the biosphere. This phenomenon would have provided deep refugia for life on the more heavily bombarded early Earth, and it shows that the deeply fractured regions of impact craters are promising targets to study the past and present habitability of Mars.

  13. Applications of Deep Learning and Reinforcement Learning to Biological Data.

    Science.gov (United States)

    Mahmud, Mufti; Kaiser, Mohammed Shamim; Hussain, Amir; Vassanelli, Stefano

    2018-06-01

    Rapid advances in hardware-based technologies during the past decades have opened up new possibilities for life scientists to gather multimodal data in various application domains, such as omics, bioimaging, medical imaging, and (brain/body)-machine interfaces. These have generated novel opportunities for development of dedicated data-intensive machine learning techniques. In particular, recent research in deep learning (DL), reinforcement learning (RL), and their combination (deep RL) promise to revolutionize the future of artificial intelligence. The growth in computational power accompanied by faster and increased data storage, and declining computing costs have already allowed scientists in various fields to apply these techniques on data sets that were previously intractable owing to their size and complexity. This paper provides a comprehensive survey on the application of DL, RL, and deep RL techniques in mining biological data. In addition, we compare the performances of DL techniques when applied to different data sets across various application domains. Finally, we outline open issues in this challenging research area and discuss future development perspectives.

  14. Deep and shallow water effects on developing preschoolers' aquatic skills.

    Science.gov (United States)

    Costa, Aldo M; Marinho, Daniel A; Rocha, Helena; Silva, António J; Barbosa, Tiago M; Ferreira, Sandra S; Martins, Marta

    2012-05-01

    The aim of the study was to assess deep and shallow water teaching methods in swimming lessons for preschool children and identify variations in the basic aquatic skills acquired. The study sample included 32 swimming instructors (16 from deep water programs and 16 from shallow water programs) and 98 preschool children (50 from deep water swimming pool and 48 from shallow water swimming pool). The children were also studied regarding their previous experience in swimming (6, 12 and 18 months or practice). Chi-Square test and Fisher's exact test were used to compare the teaching methodology. A discriminant analysis was conducted with Λ wilk's method to predict under what conditions students are better or worse (aquatic competence). Results suggest that regardless of the non-significant variations found in teaching methods, the water depth can affect aquatic skill acquisition - shallow water lessons seem to impose greater water competence particularly after 6 months of practice. The discriminant function revealed a significant association between groups and all predictors for 6 months of swimming practice (pdeep and shallow water programs for preschoolers is not significantly different. However, shallow water lessons could be preferable for the development of basic aquatic skills.

  15. Towards deep learning with segregated dendrites.

    Science.gov (United States)

    Guerguiev, Jordan; Lillicrap, Timothy P; Richards, Blake A

    2017-12-05

    Deep learning has led to significant advances in artificial intelligence, in part, by adopting strategies motivated by neurophysiology. However, it is unclear whether deep learning could occur in the real brain. Here, we show that a deep learning algorithm that utilizes multi-compartment neurons might help us to understand how the neocortex optimizes cost functions. Like neocortical pyramidal neurons, neurons in our model receive sensory information and higher-order feedback in electrotonically segregated compartments. Thanks to this segregation, neurons in different layers of the network can coordinate synaptic weight updates. As a result, the network learns to categorize images better than a single layer network. Furthermore, we show that our algorithm takes advantage of multilayer architectures to identify useful higher-order representations-the hallmark of deep learning. This work demonstrates that deep learning can be achieved using segregated dendritic compartments, which may help to explain the morphology of neocortical pyramidal neurons.

  16. Deep down: Isopod biodiversity of the Kuril-Kamchatka abyssal area including a comparison with data of previous expeditions of the RV Vityaz

    Science.gov (United States)

    Elsner, Nikolaus O.; Malyutina, Marina V.; Golovan, Olga A.; Brenke, Nils; Riehl, Torben; Brandt, Angelika

    2015-01-01

    This study focusses on the isopod biodiversity in the abyssal area southeast of the Kuril-Kamchatka Trench. The KuramBio (Kuril-Kamchatka Biodiversity Studies) expedition in summer 2012 collected altogether 10,169 isopods from 21 C-EBS hauls at 12 stations, belonging to 19 families, 73 genera and 207 species from the depth range between 4830 and 5780 m. Munnopsidae and Desmosomatidae were the most abundant and species-rich families, Eurycope (Munnopsidae) and Macrostylis (Macrostylidae) the most abundant genera. An nMDS plot on the basis of the Cosine similarity index reveals no clear pattern and all hauls to be different from each other. We compared our data with 12 stations from the same depth range sampled by the Russian RV Vityaz about 50 years ago and were able to identify several species collected by the RV Vityaz. The identified isopod species belonged to the families Munnopsidae, Macrostylidae, Haploniscidae, Desmosomatidae, Ischnomesidae and Nannoniscidae. Of the 333 individuals collected by the RV Vityaz, Haploniscidae and Munnopsidae were the most abundant families. Desmosomatidae were only represented by rarefaction curves of both the KuramBio and the Vityaz samples are not approaching an asymptote, indicating that even after repeated sampling just a part of the local fauna has been recorded so far.

  17. Analyses of the deep borehole drilling status for a deep borehole disposal system

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jong Youl; Choi, Heui Joo; Lee, Min Soo; Kim, Geon Young; Kim, Kyung Su [KAERI, Daejeon (Korea, Republic of)

    2016-05-15

    The purpose of disposal for radioactive wastes is not only to isolate them from humans, but also to inhibit leakage of any radioactive materials into the accessible environment. Because of the extremely high level and long-time scale radioactivity of HLW(High-level radioactive waste), a mined deep geological disposal concept, the disposal depth is about 500 m below ground, is considered as the safest method to isolate the spent fuels or high-level radioactive waste from the human environment with the best available technology at present time. Therefore, as an alternative disposal concept, i.e., deep borehole disposal technology is under consideration in number of countries in terms of its outstanding safety and cost effectiveness. In this paper, the general status of deep drilling technologies was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, very preliminary applicability of deep drilling technology for deep borehole disposal analyzed. In this paper, as one of key technologies of deep borehole disposal system, the general status of deep drilling technologies in oil industry, geothermal industry and geo scientific field was reviewed for deep borehole disposal of high level radioactive wastes. Based on the results of these review, the very preliminary applicability of deep drilling technology for deep borehole disposal such as relation between depth and diameter, drilling time and feasibility classification was analyzed.

  18. Sunnyvale Marine Climate Deep Retrofit

    Energy Technology Data Exchange (ETDEWEB)

    German, A.; Siddiqui, A.; Dakin, B.

    2014-11-01

    The Alliance for Residential Building Innovation (ARBI) and Allen Gilliland of One Sky Homes collaborated on a marine climate retrofit project designed to meet both Passive House (PH) and Building America (BA) program standards. The scope included sealing, installing wall, roof and floor insulation (previously lacking), replacing windows, upgrading the heating and cooling system, and installing.

  19. What Is Deep Vein Thrombosis?

    Science.gov (United States)

    ... the blood to trigger the activity of the enzyme thrombin. Active thrombin then forms long protein strands that clump together with platelets and red blood cells to form clots. Read less Risk Factors Risk factors for VTE include a history of a previous VTE event; surgery; medical conditions ...

  20. Sunnyvale Marine Climate Deep Retrofit

    Energy Technology Data Exchange (ETDEWEB)

    German, A. [Alliance for Residential Building Innovation (ARBI), Davis, CA (United States); Siddiqui, A. [Alliance for Residential Building Innovation (ARBI), Davis, CA (United States); Dakin, B. [Alliance for Residential Building Innovation (ARBI), Davis, CA (United States)

    2014-11-01

    The Alliance for Residential Building Innovation (ARBI) and Allen Gilliland of One Sky Homes collaborated on a marine climate retrofit project designed to meet both Passive House (PH) and Building America program standards. The scope included sealing, installing wall, roof and floor insulation (previously lacking), replacing windows, upgrading the heating and cooling system, and installing mechanical ventilation.

  1. Overview of deep learning in medical imaging.

    Science.gov (United States)

    Suzuki, Kenji

    2017-09-01

    The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field and became very popular in many fields. It started from an event in late 2012, when a deep-learning approach based on a convolutional neural network (CNN) won an overwhelming victory in the best-known worldwide computer vision competition, ImageNet Classification. Since then, researchers in virtually all fields, including medical imaging, have started actively participating in the explosively growing field of deep learning. In this paper, the area of deep learning in medical imaging is overviewed, including (1) what was changed in machine learning before and after the introduction of deep learning, (2) what is the source of the power of deep learning, (3) two major deep-learning models: a massive-training artificial neural network (MTANN) and a convolutional neural network (CNN), (4) similarities and differences between the two models, and (5) their applications to medical imaging. This review shows that ML with feature input (or feature-based ML) was dominant before the introduction of deep learning, and that the major and essential difference between ML before and after deep learning is the learning of image data directly without object segmentation or feature extraction; thus, it is the source of the power of deep learning, although the depth of the model is an important attribute. The class of ML with image input (or image-based ML) including deep learning has a long history, but recently gained popularity due to the use of the new terminology, deep learning. There are two major models in this class of ML in medical imaging, MTANN and CNN, which have similarities as well as several differences. In our experience, MTANNs were substantially more efficient in their development, had a higher performance, and required a

  2. Estimation of the Critical Temperatures of Some More Deep Eutectic Solvents from Their Surface Tensions

    Directory of Open Access Journals (Sweden)

    Yizhak Marcus

    2018-01-01

    Full Text Available The critical temperatures of two dozen deep eutectic solvents, for only some of which these have been estimated previously, were estimated from the temperature dependences of their surface tensions and densities available in the literature according to the Eötvös and the Guggenheim expressions.

  3. Seasonal copepod lipid pump promotes carbon sequestration in the deep North Atlantic

    DEFF Research Database (Denmark)

    Jonasdottir, Sigrun; Visser, Andre; Richardson, Katherine

    2015-01-01

    it is metabolized at a rate comparable to the carbon delivered by sinking detritus. This “lipid pump” has not been included in previous estimates of the deep-ocean carbon sequestration, which are based on either measurements of sinking fluxes of detritus, or estimates of new primary production. Unlike other...

  4. Efficient forward propagation of time-sequences in convolutional neural networks using Deep Shifting

    NARCIS (Netherlands)

    K.L. Groenland (Koen); S.M. Bohte (Sander)

    2016-01-01

    textabstractWhen a Convolutional Neural Network is used for on-the-fly evaluation of continuously updating time-sequences, many redundant convolution operations are performed. We propose the method of Deep Shifting, which remembers previously calculated results of convolution operations in order

  5. Limitations of microbial hydrocarbon degradation at the Amon mud volcano (Nile deep-sea fan)

    NARCIS (Netherlands)

    Felden, J.; Lichtschlag, A.; Wenzhöfer, F.; de Beer, D.; Feseker, T.; Pop Ristova, P.; de Lange, G.; Boetius, A.

    2013-01-01

    The Amon mud volcano (MV), located at 1250m water depth on the Nile deep-sea fan, is known for its active emission of methane and non-methane hydrocarbons into the hydrosphere. Previous investigations showed a low efficiency of hydrocarbon-degrading anaerobic microbial communities inhabiting the

  6. Three hitherto unreported macro-fungi from Kashmir Himalaya

    International Nuclear Information System (INIS)

    Pala, S.A.; Wana, A.H.; Boda, R.H.

    2012-01-01

    The Himalayan state, Jammu and Kashmir due to its climate ranging from tropical deciduous forests to temperate and coniferous forests provides congenial habitat for the growth of diverse macro fungal species which in turn gives it the status of 'hub' of macro-fungal species. The macro fungal species richness of the state is directly related to its expansive forest communities and diverse weather patterns, but all the regions of the state have not been extensively surveyed till now. In this backdrop, a systematic survey for exploration and inventorization of macro fungal species of Western Kashmir Himalaya was undertaken during the year 2009 and 2010, which in turn resulted identification of the three species viz., Thelephora caryophyllea (Schaeff.) Pers., Coltricia cinnamomea (Pers.) Murr., and Guepinia helvelloides Fr. as new reports from the Kashmir. These species were identified on the basis of macro and microscopic characters and also the aid of taxonomic keys, field manuals, mushroom herbaria and help from expert taxonomists in the related field was taken into account. (author)

  7. Iliotibial band syndrome following hip arthroscopy: An unreported complication

    Directory of Open Access Journals (Sweden)

    Roberto Seijas

    2016-01-01

    Conclusions: This is a newly described observation within followup of hip arthroscopy. These findings may help orthopedic surgeons when planning rehabilitation after hip arthroscopy, including stretching exercises to prevent this syndrome.

  8. Reported and Unreported Teacher-Student Sexual Harassment.

    Science.gov (United States)

    Wishnietsky, Dan H.

    1991-01-01

    Study surveyed North Carolina school superintendents (n=140) and high school seniors (n=300) on the extent of teacher-student sexual harassment. Data revealed discrepancies between the number of teachers disciplined for student sexual harassment and the number of students claiming harassment. Presents a structure for establishing guidelines to…

  9. Deep Learning and Its Applications in Biomedicine.

    Science.gov (United States)

    Cao, Chensi; Liu, Feng; Tan, Hai; Song, Deshou; Shu, Wenjie; Li, Weizhong; Zhou, Yiming; Bo, Xiaochen; Xie, Zhi

    2018-02-01

    Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of human health and disease. Developed from artificial neural networks, deep learning-based algorithms show great promise in extracting features and learning patterns from complex data. The aim of this paper is to provide an overview of deep learning techniques and some of the state-of-the-art applications in the biomedical field. We first introduce the development of artificial neural network and deep learning. We then describe two main components of deep learning, i.e., deep learning architectures and model optimization. Subsequently, some examples are demonstrated for deep learning applications, including medical image classification, genomic sequence analysis, as well as protein structure classification and prediction. Finally, we offer our perspectives for the future directions in the field of deep learning. Copyright © 2018. Production and hosting by Elsevier B.V.

  10. The deep lymphatic anatomy of the hand.

    Science.gov (United States)

    Ma, Chuan-Xiang; Pan, Wei-Ren; Liu, Zhi-An; Zeng, Fan-Qiang; Qiu, Zhi-Qiang

    2018-04-03

    The deep lymphatic anatomy of the hand still remains the least described in medical literature. Eight hands were harvested from four nonembalmed human cadavers amputated above the wrist. A small amount of 6% hydrogen peroxide was employed to detect the lymphatic vessels around the superficial and deep palmar vascular arches, in webs from the index to little fingers, the thenar and hypothenar areas. A 30-gauge needle was inserted into the vessels and injected with a barium sulphate compound. Each specimen was dissected, photographed and radiographed to demonstrate deep lymphatic distribution of the hand. Five groups of deep collecting lymph vessels were found in the hand: superficial palmar arch lymph vessel (SPALV); deep palmar arch lymph vessel (DPALV); thenar lymph vessel (TLV); hypothenar lymph vessel (HTLV); deep finger web lymph vessel (DFWLV). Each group of vessels drained in different directions first, then all turned and ran towards the wrist in different layers. The deep lymphatic drainage of the hand has been presented. The results will provide an anatomical basis for clinical management, educational reference and scientific research. Copyright © 2018 Elsevier GmbH. All rights reserved.

  11. Human-level control through deep reinforcement learning

    Science.gov (United States)

    Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

    2015-02-01

    The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

  12. Human-level control through deep reinforcement learning.

    Science.gov (United States)

    Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

    2015-02-26

    The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

  13. Automated embolic signal detection using Deep Convolutional Neural Network.

    Science.gov (United States)

    Sombune, Praotasna; Phienphanich, Phongphan; Phuechpanpaisal, Sutanya; Muengtaweepongsa, Sombat; Ruamthanthong, Anuchit; Tantibundhit, Charturong

    2017-07-01

    This work investigated the potential of Deep Neural Network in detection of cerebral embolic signal (ES) from transcranial Doppler ultrasound (TCD). The resulting system is aimed to couple with TCD devices in diagnosing a risk of stroke in real-time with high accuracy. The Adaptive Gain Control (AGC) approach developed in our previous study is employed to capture suspected ESs in real-time. By using spectrograms of the same TCD signal dataset as that of our previous work as inputs and the same experimental setup, Deep Convolutional Neural Network (CNN), which can learn features while training, was investigated for its ability to bypass the traditional handcrafted feature extraction and selection process. Extracted feature vectors from the suspected ESs are later determined whether they are of an ES, artifact (AF) or normal (NR) interval. The effectiveness of the developed system was evaluated over 19 subjects going under procedures generating emboli. The CNN-based system could achieve in average of 83.0% sensitivity, 80.1% specificity, and 81.4% accuracy, with considerably much less time consumption in development. The certainly growing set of training samples and computational resources will contribute to high performance. Besides having potential use in various clinical ES monitoring settings, continuation of this promising study will benefit developments of wearable applications by leveraging learnable features to serve demographic differentials.

  14. Hello World Deep Learning in Medical Imaging.

    Science.gov (United States)

    Lakhani, Paras; Gray, Daniel L; Pett, Carl R; Nagy, Paul; Shih, George

    2018-05-03

    There is recent popularity in applying machine learning to medical imaging, notably deep learning, which has achieved state-of-the-art performance in image analysis and processing. The rapid adoption of deep learning may be attributed to the availability of machine learning frameworks and libraries to simplify their use. In this tutorial, we provide a high-level overview of how to build a deep neural network for medical image classification, and provide code that can help those new to the field begin their informatics projects.

  15. Deep Generative Models for Molecular Science

    DEFF Research Database (Denmark)

    Jørgensen, Peter Bjørn; Schmidt, Mikkel Nørgaard; Winther, Ole

    2018-01-01

    Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep...... generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or...

  16. Harnessing the Deep Web: Present and Future

    OpenAIRE

    Madhavan, Jayant; Afanasiev, Loredana; Antova, Lyublena; Halevy, Alon

    2009-01-01

    Over the past few years, we have built a system that has exposed large volumes of Deep-Web content to Google.com users. The content that our system exposes contributes to more than 1000 search queries per-second and spans over 50 languages and hundreds of domains. The Deep Web has long been acknowledged to be a major source of structured data on the web, and hence accessing Deep-Web content has long been a problem of interest in the data management community. In this paper, we report on where...

  17. Desalination Economic Evaluation Program (DEEP). User's manual

    International Nuclear Information System (INIS)

    2000-01-01

    DEEP (formerly named ''Co-generation and Desalination Economic Evaluation'' Spreadsheet, CDEE) has been developed originally by General Atomics under contract, and has been used in the IAEA's feasibility studies. For further confidence in the software, it was validated in March 1998. After that, a user friendly version has been issued under the name of DEEP at the end of 1998. DEEP output includes the levelised cost of water and power, a breakdown of cost components, energy consumption and net saleable power for each selected option. Specific power plants can be modelled by adjustment of input data including design power, power cycle parameters and costs

  18. Zooplankton at deep Red Sea brine pools

    KAUST Repository

    Kaartvedt, Stein

    2016-03-02

    The deep-sea anoxic brines of the Red Sea comprise unique, complex and extreme habitats. These environments are too harsh for metazoans, while the brine–seawater interface harbors dense microbial populations. We investigated the adjacent pelagic fauna at two brine pools using net tows, video records from a remotely operated vehicle and submerged echosounders. Waters just above the brine pool of Atlantis II Deep (2000 m depth) appeared depleted of macrofauna. In contrast, the fauna appeared to be enriched at the Kebrit Deep brine–seawater interface (1466 m).

  19. NATURAL GAS RESOURCES IN DEEP SEDIMENTARY BASINS

    Energy Technology Data Exchange (ETDEWEB)

    Thaddeus S. Dyman; Troy Cook; Robert A. Crovelli; Allison A. Henry; Timothy C. Hester; Ronald C. Johnson; Michael D. Lewan; Vito F. Nuccio; James W. Schmoker; Dennis B. Riggin; Christopher J. Schenk

    2002-02-05

    From a geological perspective, deep natural gas resources are generally defined as resources occurring in reservoirs at or below 15,000 feet, whereas ultra-deep gas occurs below 25,000 feet. From an operational point of view, ''deep'' is often thought of in a relative sense based on the geologic and engineering knowledge of gas (and oil) resources in a particular area. Deep gas can be found in either conventionally-trapped or unconventional basin-center accumulations that are essentially large single fields having spatial dimensions often exceeding those of conventional fields. Exploration for deep conventional and unconventional basin-center natural gas resources deserves special attention because these resources are widespread and occur in diverse geologic environments. In 1995, the U.S. Geological Survey estimated that 939 TCF of technically recoverable natural gas remained to be discovered or was part of reserve appreciation from known fields in the onshore areas and State waters of the United. Of this USGS resource, nearly 114 trillion cubic feet (Tcf) of technically-recoverable gas remains to be discovered from deep sedimentary basins. Worldwide estimates of deep gas are also high. The U.S. Geological Survey World Petroleum Assessment 2000 Project recently estimated a world mean undiscovered conventional gas resource outside the U.S. of 844 Tcf below 4.5 km (about 15,000 feet). Less is known about the origins of deep gas than about the origins of gas at shallower depths because fewer wells have been drilled into the deeper portions of many basins. Some of the many factors contributing to the origin of deep gas include the thermal stability of methane, the role of water and non-hydrocarbon gases in natural gas generation, porosity loss with increasing thermal maturity, the kinetics of deep gas generation, thermal cracking of oil to gas, and source rock potential based on thermal maturity and kerogen type. Recent experimental simulations

  20. 75 FR 20933 - Airworthiness Directives; Arrow Falcon Exporters, Inc. (previously Utah State University...

    Science.gov (United States)

    2010-04-22

    ... Hawkins and Powers Aviation, Inc.); S.M.&T. Aircraft (previously US Helicopters, Inc., UNC Helicopter, Inc... Joaquin Helicopters (previously Hawkins and Powers Aviation, Inc.); S.M.&T. Aircraft (previously US...

  1. Discovery radiomics via evolutionary deep radiomic sequencer discovery for pathologically proven lung cancer detection.

    Science.gov (United States)

    Shafiee, Mohammad Javad; Chung, Audrey G; Khalvati, Farzad; Haider, Masoom A; Wong, Alexander

    2017-10-01

    While lung cancer is the second most diagnosed form of cancer in men and women, a sufficiently early diagnosis can be pivotal in patient survival rates. Imaging-based, or radiomics-driven, detection methods have been developed to aid diagnosticians, but largely rely on hand-crafted features that may not fully encapsulate the differences between cancerous and healthy tissue. Recently, the concept of discovery radiomics was introduced, where custom abstract features are discovered from readily available imaging data. We propose an evolutionary deep radiomic sequencer discovery approach based on evolutionary deep intelligence. Motivated by patient privacy concerns and the idea of operational artificial intelligence, the evolutionary deep radiomic sequencer discovery approach organically evolves increasingly more efficient deep radiomic sequencers that produce significantly more compact yet similarly descriptive radiomic sequences over multiple generations. As a result, this framework improves operational efficiency and enables diagnosis to be run locally at the radiologist's computer while maintaining detection accuracy. We evaluated the evolved deep radiomic sequencer (EDRS) discovered via the proposed evolutionary deep radiomic sequencer discovery framework against state-of-the-art radiomics-driven and discovery radiomics methods using clinical lung CT data with pathologically proven diagnostic data from the LIDC-IDRI dataset. The EDRS shows improved sensitivity (93.42%), specificity (82.39%), and diagnostic accuracy (88.78%) relative to previous radiomics approaches.

  2. Joint Segmentation of Multiple Thoracic Organs in CT Images with Two Collaborative Deep Architectures.

    Science.gov (United States)

    Trullo, Roger; Petitjean, Caroline; Nie, Dong; Shen, Dinggang; Ruan, Su

    2017-09-01

    Computed Tomography (CT) is the standard imaging technique for radiotherapy planning. The delineation of Organs at Risk (OAR) in thoracic CT images is a necessary step before radiotherapy, for preventing irradiation of healthy organs. However, due to low contrast, multi-organ segmentation is a challenge. In this paper, we focus on developing a novel framework for automatic delineation of OARs. Different from previous works in OAR segmentation where each organ is segmented separately, we propose two collaborative deep architectures to jointly segment all organs, including esophagus, heart, aorta and trachea. Since most of the organ borders are ill-defined, we believe spatial relationships must be taken into account to overcome the lack of contrast. The aim of combining two networks is to learn anatomical constraints with the first network, which will be used in the second network, when each OAR is segmented in turn. Specifically, we use the first deep architecture, a deep SharpMask architecture, for providing an effective combination of low-level representations with deep high-level features, and then take into account the spatial relationships between organs by the use of Conditional Random Fields (CRF). Next, the second deep architecture is employed to refine the segmentation of each organ by using the maps obtained on the first deep architecture to learn anatomical constraints for guiding and refining the segmentations. Experimental results show superior performance on 30 CT scans, comparing with other state-of-the-art methods.

  3. Deep Extragalactic VIsible Legacy Survey (DEVILS): Motivation, Design and Target Catalogue

    Science.gov (United States)

    Davies, L. J. M.; Robotham, A. S. G.; Driver, S. P.; Lagos, C. P.; Cortese, L.; Mannering, E.; Foster, C.; Lidman, C.; Hashemizadeh, A.; Koushan, S.; O'Toole, S.; Baldry, I. K.; Bilicki, M.; Bland-Hawthorn, J.; Bremer, M. N.; Brown, M. J. I.; Bryant, J. J.; Catinella, B.; Croom, S. M.; Grootes, M. W.; Holwerda, B. W.; Jarvis, M. J.; Maddox, N.; Meyer, M.; Moffett, A. J.; Phillipps, S.; Taylor, E. N.; Windhorst, R. A.; Wolf, C.

    2018-06-01

    The Deep Extragalactic VIsible Legacy Survey (DEVILS) is a large spectroscopic campaign at the Anglo-Australian Telescope (AAT) aimed at bridging the near and distant Universe by producing the highest completeness survey of galaxies and groups at intermediate redshifts (0.3 < z < 1.0). Our sample consists of ˜60,000 galaxies to Y<21.2 mag, over ˜6 deg2 in three well-studied deep extragalactic fields (Cosmic Origins Survey field, COSMOS, Extended Chandra Deep Field South, ECDFS and the X-ray Multi-Mirror Mission Large-Scale Structure region, XMM-LSS - all Large Synoptic Survey Telescope deep-drill fields). This paper presents the broad experimental design of DEVILS. Our target sample has been selected from deep Visible and Infrared Survey Telescope for Astronomy (VISTA) Y-band imaging (VISTA Deep Extragalactic Observations, VIDEO and UltraVISTA), with photometry measured by PROFOUND. Photometric star/galaxy separation is done on the basis of NIR colours, and has been validated by visual inspection. To maximise our observing efficiency for faint targets we employ a redshift feedback strategy, which continually updates our target lists, feeding back the results from the previous night's observations. We also present an overview of the initial spectroscopic observations undertaken in late 2017 and early 2018.

  4. PC operated acoustic transient spectroscopy of deep levels in MIS structures

    International Nuclear Information System (INIS)

    Bury, P.; Jamnicky, I.

    1996-01-01

    A new version of acoustic deep-level transient spectroscopy is presented to study the traps at the insulator-semiconductor interface. The acoustic deep-level transient spectroscopy uses an acoustoelectric response signal produced by the MIS structure interface when a longitudinal acoustic wave propagates through a structure. The acoustoelectric response signal is extremely sensitive to external conditions of the structure and reflects any changes in the charge distribution, connected also with charged traps. In comparison with previous version of acoustic deep-level transient spectroscopy that closely coincides with the principle of the original deep-level transient spectroscopy technique, the present technique is based on the computer-evaluated isothermal transients and represents an improved, more efficient and time saving technique. Many tests on the software used for calculation as well as on experimental setup have been performed. The improved acoustic deep-level transient spectroscopy method has been applied for the Si(p) MIS structures. The deep-level parameters as activation energy and capture cross-section have been determined. (authors)

  5. Comet Dust After Deep Impact

    Science.gov (United States)

    Wooden, Diane H.; Harker, David E.; Woodward, Charles E.

    2006-01-01

    When the Deep Impact Mission hit Jupiter Family comet 9P/Tempel 1, an ejecta crater was formed and an pocket of volatile gases and ices from 10-30 m below the surface was exposed (A Hearn et aI. 2005). This resulted in a gas geyser that persisted for a few hours (Sugita et al, 2005). The gas geyser pushed dust grains into the coma (Sugita et a1. 2005), as well as ice grains (Schulz et al. 2006). The smaller of the dust grains were submicron in radii (0-25.3 micron), and were primarily composed of highly refractory minerals including amorphous (non-graphitic) carbon, and silicate minerals including amorphous (disordered) olivine (Fe,Mg)2SiO4 and pyroxene (Fe,Mg)SiO3 and crystalline Mg-rich olivine. The smaller grains moved faster, as expected from the size-dependent velocity law produced by gas-drag on grains. The mineralogy evolved with time: progressively larger grains persisted in the near nuclear region, having been imparted with slower velocities, and the mineralogies of these larger grains appeared simpler and without crystals. The smaller 0.2-0.3 micron grains reached the coma in about 1.5 hours (1 arc sec = 740 km), were more diverse in mineralogy than the larger grains and contained crystals, and appeared to travel through the coma together. No smaller grains appeared at larger coma distances later (with slower velocities), implying that if grain fragmentation occurred, it happened within the gas acceleration zone. These results of the high spatial resolution spectroscopy (GEMINI+Michelle: Harker et 4. 2005, 2006; Subaru+COMICS: Sugita et al. 2005) revealed that the grains released from the interior were different from the nominally active areas of this comet by their: (a) crystalline content, (b) smaller size, (c) more diverse mineralogy. The temporal changes in the spectra, recorded by GEMIM+Michelle every 7 minutes, indicated that the dust mineralogy is inhomogeneous and, unexpectedly, the portion of the size distribution dominated by smaller grains has

  6. Anisotropy in the deep Earth

    Science.gov (United States)

    Romanowicz, Barbara; Wenk, Hans-Rudolf

    2017-08-01

    Seismic anisotropy has been found in many regions of the Earth's interior. Its presence in the Earth's crust has been known since the 19th century, and is due in part to the alignment of anisotropic crystals in rocks, and in part to patterns in the distribution of fractures and pores. In the upper mantle, seismic anisotropy was discovered 50 years ago, and can be attributed for the most part, to the alignment of intrinsically anisotropic olivine crystals during large scale deformation associated with convection. There is some indication for anisotropy in the transition zone, particularly in the vicinity of subducted slabs. Here we focus on the deep Earth - the lower mantle and core, where anisotropy is not yet mapped in detail, nor is there consensus on its origin. Most of the lower mantle appears largely isotropic, except in the last 200-300 km, in the D″ region, where evidence for seismic anisotropy has been accumulating since the late 1980s, mostly from shear wave splitting measurements. Recently, a picture has been emerging, where strong anisotropy is associated with high shear velocities at the edges of the large low shear velocity provinces (LLSVPs) in the central Pacific and under Africa. These observations are consistent with being due to the presence of highly anisotropic MgSiO3 post-perovskite crystals, aligned during the deformation of slabs impinging on the core-mantle boundary, and upwelling flow within the LLSVPs. We also discuss mineral physics aspects such as ultrahigh pressure deformation experiments, first principles calculations to obtain information about elastic properties, and derivation of dislocation activity based on bonding characteristics. Polycrystal plasticity simulations can predict anisotropy but models are still highly idealized and neglect the complex microstructure of polyphase aggregates with strong and weak components. A promising direction for future progress in understanding the origin of seismic anisotropy in the deep mantle

  7. A Pseudoaneurysm of the Deep Palmar Arch After Penetrating Trauma to the Hand: Successful Exclusion by Ultrasound Guided Percutaneous Thrombin Injection

    Directory of Open Access Journals (Sweden)

    A. Bosman

    Full Text Available : Introduction: Pseudoaneurysm of the hand is a rare condition; most are treated surgically. Ultrasound guided thrombin injection has not previously been reported as a treatment option for pseudoaneurysms of the deep palmar arch. Report: A man was referred to the emergency department with a swollen, painful hand after penetrating trauma. On physical examination, a pulsating tumor was found on the dorsum of the hand. Imaging revealed a pseudoaneurysm vascularized by the deep palmar arch. Ultrasound guided percutaneous thrombin injection was successfully performed. Conclusion: Thrombin injection might be a safe alternative option in the treatment of pseudoaneurysm of the deep palmar arch. Keywords: Deep palmar arch, Pseudoaneurysm, Thrombin injection

  8. DeepDive: Declarative Knowledge Base Construction.

    Science.gov (United States)

    De Sa, Christopher; Ratner, Alex; Ré, Christopher; Shin, Jaeho; Wang, Feiran; Wu, Sen; Zhang, Ce

    2016-03-01

    The dark data extraction or knowledge base construction (KBC) problem is to populate a SQL database with information from unstructured data sources including emails, webpages, and pdf reports. KBC is a long-standing problem in industry and research that encompasses problems of data extraction, cleaning, and integration. We describe DeepDive, a system that combines database and machine learning ideas to help develop KBC systems. The key idea in DeepDive is that statistical inference and machine learning are key tools to attack classical data problems in extraction, cleaning, and integration in a unified and more effective manner. DeepDive programs are declarative in that one cannot write probabilistic inference algorithms; instead, one interacts by defining features or rules about the domain. A key reason for this design choice is to enable domain experts to build their own KBC systems. We present the applications, abstractions, and techniques of DeepDive employed to accelerate construction of KBC systems.

  9. Variational inference & deep learning : A new synthesis

    NARCIS (Netherlands)

    Kingma, D.P.

    2017-01-01

    In this thesis, Variational Inference and Deep Learning: A New Synthesis, we propose novel solutions to the problems of variational (Bayesian) inference, generative modeling, representation learning, semi-supervised learning, and stochastic optimization.

  10. Pathways to deep decarbonization - 2015 report

    International Nuclear Information System (INIS)

    Ribera, Teresa; Colombier, Michel; Waisman, Henri; Bataille, Chris; Pierfederici, Roberta; Sachs, Jeffrey; Schmidt-Traub, Guido; Williams, Jim; Segafredo, Laura; Hamburg Coplan, Jill; Pharabod, Ivan; Oury, Christian

    2015-12-01

    In September 2015, the Deep Decarbonization Pathways Project published the Executive Summary of the Pathways to Deep Decarbonization: 2015 Synthesis Report. The full 2015 Synthesis Report was launched in Paris on December 3, 2015, at a technical workshop with the Mitigation Action Plans and Scenarios (MAPS) program. The Deep Decarbonization Pathways Project (DDPP) is a collaborative initiative to understand and show how individual countries can transition to a low-carbon economy and how the world can meet the internationally agreed target of limiting the increase in global mean surface temperature to less than 2 degrees Celsius (deg. C). Achieving the 2 deg. C limit will require that global net emissions of greenhouse gases (GHG) approach zero by the second half of the century. In turn, this will require a profound transformation of energy systems by mid-century through steep declines in carbon intensity in all sectors of the economy, a transition we call 'deep decarbonization'

  11. Variational inference & deep learning: A new synthesis

    OpenAIRE

    Kingma, D.P.

    2017-01-01

    In this thesis, Variational Inference and Deep Learning: A New Synthesis, we propose novel solutions to the problems of variational (Bayesian) inference, generative modeling, representation learning, semi-supervised learning, and stochastic optimization.

  12. DNA Replication Profiling Using Deep Sequencing.

    Science.gov (United States)

    Saayman, Xanita; Ramos-Pérez, Cristina; Brown, Grant W

    2018-01-01

    Profiling of DNA replication during progression through S phase allows a quantitative snap-shot of replication origin usage and DNA replication fork progression. We present a method for using deep sequencing data to profile DNA replication in S. cerevisiae.

  13. DAPs: Deep Action Proposals for Action Understanding

    KAUST Repository

    Escorcia, Victor; Caba Heilbron, Fabian; Niebles, Juan Carlos; Ghanem, Bernard

    2016-01-01

    action proposals from long videos. We show how to take advantage of the vast capacity of deep learning models and memory cells to retrieve from untrimmed videos temporal segments, which are likely to contain actions. A comprehensive evaluation indicates

  14. Evaluation of static resistance of deep foundations.

    Science.gov (United States)

    2017-05-01

    The focus of this research was to evaluate and improve Florida Department of Transportation (FDOT) FB-Deep software prediction of nominal resistance of H-piles, prestressed concrete piles in limestone, large diameter (> 36) open steel and concrete...

  15. The deep ocean under climate change.

    Science.gov (United States)

    Levin, Lisa A; Le Bris, Nadine

    2015-11-13

    The deep ocean absorbs vast amounts of heat and carbon dioxide, providing a critical buffer to climate change but exposing vulnerable ecosystems to combined stresses of warming, ocean acidification, deoxygenation, and altered food inputs. Resulting changes may threaten biodiversity and compromise key ocean services that maintain a healthy planet and human livelihoods. There exist large gaps in understanding of the physical and ecological feedbacks that will occur. Explicit recognition of deep-ocean climate mitigation and inclusion in adaptation planning by the United Nations Framework Convention on Climate Change (UNFCCC) could help to expand deep-ocean research and observation and to protect the integrity and functions of deep-ocean ecosystems. Copyright © 2015, American Association for the Advancement of Science.

  16. Deep gold mine fracture zone behaviour

    CSIR Research Space (South Africa)

    Napier, JAL

    1998-12-01

    Full Text Available The investigation of the behaviour of the fracture zone surrounding deep level gold mine stopes is detailed in three main sections of this report. Section 2 outlines the ongoing study of fundamental fracture process and their numerical...

  17. Deep Ultraviolet Macroporous Silicon Filters, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase I proposal describes a novel method to make deep and far UV optical filters from macroporous silicon. This type of filter consists of an array of...

  18. Toolkits and Libraries for Deep Learning.

    Science.gov (United States)

    Erickson, Bradley J; Korfiatis, Panagiotis; Akkus, Zeynettin; Kline, Timothy; Philbrick, Kenneth

    2017-08-01

    Deep learning is an important new area of machine learning which encompasses a wide range of neural network architectures designed to complete various tasks. In the medical imaging domain, example tasks include organ segmentation, lesion detection, and tumor classification. The most popular network architecture for deep learning for images is the convolutional neural network (CNN). Whereas traditional machine learning requires determination and calculation of features from which the algorithm learns, deep learning approaches learn the important features as well as the proper weighting of those features to make predictions for new data. In this paper, we will describe some of the libraries and tools that are available to aid in the construction and efficient execution of deep learning as applied to medical images.

  19. Deep-Sea Soft Coral Habitat Suitability

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Deep-sea corals, also known as cold water corals, create complex communities that provide habitat for a variety of invertebrate and fish species, such as grouper,...

  20. Photon diffractive dissociation in deep inelastic scattering

    International Nuclear Information System (INIS)

    Ryskin, M.G.

    1990-01-01

    The new ep-collider HERA gives us the possibility to study the diffractive dissociation of virtual photon in deep inelastic ep-collision. The process of photon dissociation in deep inelastic scattering is the most direct way to measure the value of triple-pomeron vertex G 3P . It was shown that the value of the correct bare vertex G 3P may more than 4 times exceeds its effective value measuring in the triple-reggeon region and reaches the value of about 40-50% of the elastic pp-pomeron vertex. On the contrary in deep inelastic processes the perpendicular momenta q t of the secondary particles are large enough. Thus in deep inelastic reactions one can measure the absolute value of G 3P vertex in the most direct way and compare its value and q t dependence with the leading log QCD predictions

  1. Applications of Deep Learning in Biomedicine.

    Science.gov (United States)

    Mamoshina, Polina; Vieira, Armando; Putin, Evgeny; Zhavoronkov, Alex

    2016-05-02

    Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.

  2. Mean associative multiplicities in deep inelastic processes

    International Nuclear Information System (INIS)

    Dzhaparidze, G.Sh.; Kiselev, A.V.; Petrov, V.A.

    1981-01-01

    The associative hadron multiplicities in deep inelastic and Drell--Yan processes are studied. In particular the mean multiplicities in different hard processes in QCD are found to be determined by the mean multiplicity in parton jet [ru

  3. Deep-Sea Stony Coral Habitat Suitability

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Deep-sea corals, also known as cold water corals, create complex communities that provide habitat for a variety of invertebrate and fish species, such as grouper,...

  4. Deep Learning and Applications in Computational Biology

    KAUST Repository

    Zeng, Jianyang

    2016-01-01

    In this work, we develop a general and flexible deep learning framework for modeling structural binding preferences and predicting binding sites of RBPs, which takes (predicted) RNA tertiary structural information

  5. Leading particle in deep inelastic scattering

    International Nuclear Information System (INIS)

    Petrov, V.A.

    1984-01-01

    The leading particle effect in deep inelastic scattering is considered. The change of the characteris cs shape of the leading particle inclusive spectrum with Q 2 is estimated to be rather significant at very high Q 2

  6. Progress in deep-UV photoresists

    Indian Academy of Sciences (India)

    Unknown

    This paper reviews the recent development and challenges of deep-UV photoresists and their ... small amount of acid, when exposed to light by photo- chemical ... anomalous insoluble skin and linewidth shift when the. PEB was delayed.

  7. Methods in mooring deep sea sediment traps

    Digital Repository Service at National Institute of Oceanography (India)

    Venkatesan, R.; Fernando, V.; Rajaraman, V.S.; Janakiraman, G.

    The experience gained during the process of deployment and retrieval of nearly 39 sets of deep sea sediment trap moorings on various ships like FS Sonne, ORV Sagarkanya and DSV Nand Rachit are outlined. The various problems encountered...

  8. Deep Water Horizon (HB1006, EK60)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monitor and measure the biological, chemical, and physical environment in the area of the oil spill from the deep water horizon oil rig in the Gulf of Mexico. A wide...

  9. Evidence for nitrite-dependent anaerobic methane oxidation as a previously overlooked microbial methane sink in wetlands

    Science.gov (United States)

    Hu, Bao-lan; Shen, Li-dong; Lian, Xu; Zhu, Qun; Liu, Shuai; Huang, Qian; He, Zhan-fei; Geng, Sha; Cheng, Dong-qing; Lou, Li-ping; Xu, Xiang-yang; Zheng, Ping; He, Yun-feng

    2014-01-01

    The process of nitrite-dependent anaerobic methane oxidation (n-damo) was recently discovered and shown to be mediated by “Candidatus Methylomirabilis oxyfera” (M. oxyfera). Here, evidence for n-damo in three different freshwater wetlands located in southeastern China was obtained using stable isotope measurements, quantitative PCR assays, and 16S rRNA and particulate methane monooxygenase gene clone library analyses. Stable isotope experiments confirmed the occurrence of n-damo in the examined wetlands, and the potential n-damo rates ranged from 0.31 to 5.43 nmol CO2 per gram of dry soil per day at different depths of soil cores. A combined analysis of 16S rRNA and particulate methane monooxygenase genes demonstrated that M. oxyfera-like bacteria were mainly present in the deep soil with a maximum abundance of 3.2 × 107 gene copies per gram of dry soil. It is estimated that ∼0.51 g of CH4 m−2 per year could be linked to the n-damo process in the examined wetlands based on the measured potential n-damo rates. This study presents previously unidentified confirmation that the n-damo process is a previously overlooked microbial methane sink in wetlands, and n-damo has the potential to be a globally important methane sink due to increasing nitrogen pollution. PMID:24616523

  10. Reduced vaginal elasticity, reduced lubrication, and deep and superficial dyspareunia in irradiated gynecological cancer survivors.

    Science.gov (United States)

    Stinesen Kollberg, Karin; Waldenström, Ann-Charlotte; Bergmark, Karin; Dunberger, Gail; Rossander, Anna; Wilderäng, Ulrica; Åvall-Lundqvist, Elisabeth; Steineck, Gunnar

    2015-05-01

    The purpose of this study was to examine whether or not vaginal elasticity or lack of lubrication is associated with deep or superficial dyspareunia. We investigated gynecological cancer survivors treated with radiation therapy. In a population-based study with 616 women answering a questionnaire (participation rate 78%) and who were treated with radiotherapy for gynecological cancer, we analyzed information from 243 women (39%) who reported that they had had intercourse during the previous six months. Analyses included log-binomial regression (relative risks) and multiple imputations by chained equations in combination with Bayesian Model Averaging, yielding a posterior probability value. Age range of this cancer recurrent-free group of women was 29-80. Dyspareunia affected 164 of 243 of the women (67%). One hundred thirty-four women (55%) reported superficial pain, 97 women (40%) reported deep pain, and 87 women (36%) reported both types of dyspareunia. The relative risk (RR) of deep dyspareunia was 1.87 (CI 1.41-2.49) with impaired vaginal elasticity compared to normal vaginal elasticity. Age and lower abdominal swelling were separate risk factors for deep dyspareunia. However, effects remain after adjusting for these factors. The relative risk of deep dyspareunia was almost twice as high with impaired vaginal elasticity compared to normal vaginal elasticity. If we wish to treat or even prevent deep dyspareunia in women with gynecological cancer, we may use our knowledge of the pathophysiology of deep dyspareunia and increasingly provide dilators together with instructions on how to use them for stretching exercises in order to retain vaginal elasticity. Results highlight the need for studies with more precise questions distinguishing superficial from deep dyspareunia so that in the future we may be able to primarily try to avoid reduced vaginal elasticity and secondarily reduce the symptoms.

  11. Exploring fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing

    Science.gov (United States)

    Zhang, Xiao-Yong; Wang, Guang-Hua; Xu, Xin-Ya; Nong, Xu-Hua; Wang, Jie; Amin, Muhammad; Qi, Shu-Hua

    2016-10-01

    The present study investigated the fungal diversity in four different deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing of the nuclear ribosomal internal transcribed spacer-1 (ITS1). A total of 40,297 fungal ITS1 sequences clustered into 420 operational taxonomic units (OTUs) with 97% sequence similarity and 170 taxa were recovered from these sediments. Most ITS1 sequences (78%) belonged to the phylum Ascomycota, followed by Basidiomycota (17.3%), Zygomycota (1.5%) and Chytridiomycota (0.8%), and a small proportion (2.4%) belonged to unassigned fungal phyla. Compared with previous studies on fungal diversity of sediments from deep-sea environments by culture-dependent approach and clone library analysis, the present result suggested that Illumina sequencing had been dramatically accelerating the discovery of fungal community of deep-sea sediments. Furthermore, our results revealed that Sordariomycetes was the most diverse and abundant fungal class in this study, challenging the traditional view that the diversity of Sordariomycetes phylotypes was low in the deep-sea environments. In addition, more than 12 taxa accounted for 21.5% sequences were found to be rarely reported as deep-sea fungi, suggesting the deep-sea sediments from Okinawa Trough harbored a plethora of different fungal communities compared with other deep-sea environments. To our knowledge, this study is the first exploration of the fungal diversity in deep-sea sediments from Okinawa Trough using high-throughput Illumina sequencing.

  12. Biodiversity loss from deep-sea mining

    OpenAIRE

    C. L. Van Dover; J. A. Ardron; E. Escobar; M. Gianni; K. M. Gjerde; A. Jaeckel; D. O. B. Jones; L. A. Levin; H. Niner; L. Pendleton; C. R. Smith; T. Thiele; P. J. Turner; L. Watling; P. P. E. Weaver

    2017-01-01

    The emerging deep-sea mining industry is seen by some to be an engine for economic development in the maritime sector. The International Seabed Authority (ISA) – the body that regulates mining activities on the seabed beyond national jurisdiction – must also protect the marine environment from harmful effects that arise from mining. The ISA is currently drafting a regulatory framework for deep-sea mining that includes measures for environmental protection. Responsible mining increasingly stri...

  13. DEEP VADOSE ZONE TREATABILITY TEST PLAN

    International Nuclear Information System (INIS)

    Chronister, G.B.; Truex, M.J.

    2009-01-01

    (sm b ullet) Treatability test plan published in 2008 (sm b ullet) Outlines technology treatability activities for evaluating application of in situ technologies and surface barriers to deep vadose zone contamination (technetium and uranium) (sm b ullet) Key elements - Desiccation testing - Testing of gas-delivered reactants for in situ treatment of uranium - Evaluating surface barrier application to deep vadose zone - Evaluating in situ grouting and soil flushing

  14. Deep inelastic inclusive weak and electromagnetic interactions

    International Nuclear Information System (INIS)

    Adler, S.L.

    1976-01-01

    The theory of deep inelastic inclusive interactions is reviewed, emphasizing applications to electromagnetic and weak charged current processes. The following reactions are considered: e + N → e + X, ν + N → μ - + X, anti ν + N → μ + + X where X denotes a summation over all final state hadrons and the ν's are muon neutrinos. After a discussion of scaling, the quark-parton model is invoked to explain the principle experimental features of deep inelastic inclusive reactions

  15. Short-term Memory of Deep RNN

    OpenAIRE

    Gallicchio, Claudio

    2018-01-01

    The extension of deep learning towards temporal data processing is gaining an increasing research interest. In this paper we investigate the properties of state dynamics developed in successive levels of deep recurrent neural networks (RNNs) in terms of short-term memory abilities. Our results reveal interesting insights that shed light on the nature of layering as a factor of RNN design. Noticeably, higher layers in a hierarchically organized RNN architecture results to be inherently biased ...

  16. Deep Learning for Video Game Playing

    OpenAIRE

    Justesen, Niels; Bontrager, Philip; Togelius, Julian; Risi, Sebastian

    2017-01-01

    In this article, we review recent Deep Learning advances in the context of how they have been applied to play different types of video games such as first-person shooters, arcade games, and real-time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces...

  17. Life Support for Deep Space and Mars

    Science.gov (United States)

    Jones, Harry W.; Hodgson, Edward W.; Kliss, Mark H.

    2014-01-01

    How should life support for deep space be developed? The International Space Station (ISS) life support system is the operational result of many decades of research and development. Long duration deep space missions such as Mars have been expected to use matured and upgraded versions of ISS life support. Deep space life support must use the knowledge base incorporated in ISS but it must also meet much more difficult requirements. The primary new requirement is that life support in deep space must be considerably more reliable than on ISS or anywhere in the Earth-Moon system, where emergency resupply and a quick return are possible. Due to the great distance from Earth and the long duration of deep space missions, if life support systems fail, the traditional approaches for emergency supply of oxygen and water, emergency supply of parts, and crew return to Earth or escape to a safe haven are likely infeasible. The Orbital Replacement Unit (ORU) maintenance approach used by ISS is unsuitable for deep space with ORU's as large and complex as those originally provided in ISS designs because it minimizes opportunities for commonality of spares, requires replacement of many functional parts with each failure, and results in substantial launch mass and volume penalties. It has become impractical even for ISS after the shuttle era, resulting in the need for ad hoc repair activity at lower assembly levels with consequent crew time penalties and extended repair timelines. Less complex, more robust technical approaches may be needed to meet the difficult deep space requirements for reliability, maintainability, and reparability. Developing an entirely new life support system would neglect what has been achieved. The suggested approach is use the ISS life support technologies as a platform to build on and to continue to improve ISS subsystems while also developing new subsystems where needed to meet deep space requirements.

  18. Deep Predictive Models in Interactive Music

    OpenAIRE

    Martin, Charles P.; Ellefsen, Kai Olav; Torresen, Jim

    2018-01-01

    Automatic music generation is a compelling task where much recent progress has been made with deep learning models. In this paper, we ask how these models can be integrated into interactive music systems; how can they encourage or enhance the music making of human users? Musical performance requires prediction to operate instruments, and perform in groups. We argue that predictive models could help interactive systems to understand their temporal context, and ensemble behaviour. Deep learning...

  19. Predicting Process Behaviour using Deep Learning

    OpenAIRE

    Evermann, Joerg; Rehse, Jana-Rebecca; Fettke, Peter

    2016-01-01

    Predicting business process behaviour is an important aspect of business process management. Motivated by research in natural language processing, this paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process. This is both a novel method in process prediction, which has largely relied on explicit process models, and also a novel application of deep learning methods. The approach is evaluated on two real da...

  20. A Deep Learning Approach to Drone Monitoring

    OpenAIRE

    Chen, Yueru; Aggarwal, Pranav; Choi, Jongmoo; Kuo, C. -C. Jay

    2017-01-01

    A drone monitoring system that integrates deep-learning-based detection and tracking modules is proposed in this work. The biggest challenge in adopting deep learning methods for drone detection is the limited amount of training drone images. To address this issue, we develop a model-based drone augmentation technique that automatically generates drone images with a bounding box label on drone's location. To track a small flying drone, we utilize the residual information between consecutive i...

  1. Bank of Weight Filters for Deep CNNs

    Science.gov (United States)

    2016-11-22

    very large even on the best available hardware . In some studies in transfer learning it has been observed that the network learnt on one task can be...CNNs. Keywords: CNN, deep learning , neural networks, transfer learning , bank of weigh filters, BWF 1. Introduction Object recognition is an important...of CNNs (or, in general, of deep neural networks) is that feature generation part is fused with the classifier part and both parts are learned together

  2. Leveraging multiple datasets for deep leaf counting

    OpenAIRE

    Dobrescu, Andrei; Giuffrida, Mario Valerio; Tsaftaris, Sotirios A

    2017-01-01

    The number of leaves a plant has is one of the key traits (phenotypes) describing its development and growth. Here, we propose an automated, deep learning based approach for counting leaves in model rosette plants. While state-of-the-art results on leaf counting with deep learning methods have recently been reported, they obtain the count as a result of leaf segmentation and thus require per-leaf (instance) segmentation to train the models (a rather strong annotation). Instead, our method tre...

  3. DeepSpark: A Spark-Based Distributed Deep Learning Framework for Commodity Clusters

    OpenAIRE

    Kim, Hanjoo; Park, Jaehong; Jang, Jaehee; Yoon, Sungroh

    2016-01-01

    The increasing complexity of deep neural networks (DNNs) has made it challenging to exploit existing large-scale data processing pipelines for handling massive data and parameters involved in DNN training. Distributed computing platforms and GPGPU-based acceleration provide a mainstream solution to this computational challenge. In this paper, we propose DeepSpark, a distributed and parallel deep learning framework that exploits Apache Spark on commodity clusters. To support parallel operation...

  4. DeepX: Deep Learning Accelerator for Restricted Boltzmann Machine Artificial Neural Networks.

    Science.gov (United States)

    Kim, Lok-Won

    2018-05-01

    Although there have been many decades of research and commercial presence on high performance general purpose processors, there are still many applications that require fully customized hardware architectures for further computational acceleration. Recently, deep learning has been successfully used to learn in a wide variety of applications, but their heavy computation demand has considerably limited their practical applications. This paper proposes a fully pipelined acceleration architecture to alleviate high computational demand of an artificial neural network (ANN) which is restricted Boltzmann machine (RBM) ANNs. The implemented RBM ANN accelerator (integrating network size, using 128 input cases per batch, and running at a 303-MHz clock frequency) integrated in a state-of-the art field-programmable gate array (FPGA) (Xilinx Virtex 7 XC7V-2000T) provides a computational performance of 301-billion connection-updates-per-second and about 193 times higher performance than a software solution running on general purpose processors. Most importantly, the architecture enables over 4 times (12 times in batch learning) higher performance compared with a previous work when both are implemented in an FPGA device (XC2VP70).

  5. Contemporary deep recurrent learning for recognition

    Science.gov (United States)

    Iftekharuddin, K. M.; Alam, M.; Vidyaratne, L.

    2017-05-01

    Large-scale feed-forward neural networks have seen intense application in many computer vision problems. However, these networks can get hefty and computationally intensive with increasing complexity of the task. Our work, for the first time in literature, introduces a Cellular Simultaneous Recurrent Network (CSRN) based hierarchical neural network for object detection. CSRN has shown to be more effective to solving complex tasks such as maze traversal and image processing when compared to generic feed forward networks. While deep neural networks (DNN) have exhibited excellent performance in object detection and recognition, such hierarchical structure has largely been absent in neural networks with recurrency. Further, our work introduces deep hierarchy in SRN for object recognition. The simultaneous recurrency results in an unfolding effect of the SRN through time, potentially enabling the design of an arbitrarily deep network. This paper shows experiments using face, facial expression and character recognition tasks using novel deep recurrent model and compares recognition performance with that of generic deep feed forward model. Finally, we demonstrate the flexibility of incorporating our proposed deep SRN based recognition framework in a humanoid robotic platform called NAO.

  6. Diabetic retinopathy screening using deep neural network.

    Science.gov (United States)

    Ramachandran, Nishanthan; Hong, Sheng Chiong; Sime, Mary J; Wilson, Graham A

    2017-09-07

    There is a burgeoning interest in the use of deep neural network in diabetic retinal screening. To determine whether a deep neural network could satisfactorily detect diabetic retinopathy that requires referral to an ophthalmologist from a local diabetic retinal screening programme and an international database. Retrospective audit. Diabetic retinal photos from Otago database photographed during October 2016 (485 photos), and 1200 photos from Messidor international database. Receiver operating characteristic curve to illustrate the ability of a deep neural network to identify referable diabetic retinopathy (moderate or worse diabetic retinopathy or exudates within one disc diameter of the fovea). Area under the receiver operating characteristic curve, sensitivity and specificity. For detecting referable diabetic retinopathy, the deep neural network had an area under receiver operating characteristic curve of 0.901 (95% confidence interval 0.807-0.995), with 84.6% sensitivity and 79.7% specificity for Otago and 0.980 (95% confidence interval 0.973-0.986), with 96.0% sensitivity and 90.0% specificity for Messidor. This study has shown that a deep neural network can detect referable diabetic retinopathy with sensitivities and specificities close to or better than 80% from both an international and a domestic (New Zealand) database. We believe that deep neural networks can be integrated into community screening once they can successfully detect both diabetic retinopathy and diabetic macular oedema. © 2017 Royal Australian and New Zealand College of Ophthalmologists.

  7. Some Challenges of Deep Mining†

    Directory of Open Access Journals (Sweden)

    Charles Fairhurst

    2017-08-01

    Full Text Available An increased global supply of minerals is essential to meet the needs and expectations of a rapidly rising world population. This implies extraction from greater depths. Autonomous mining systems, developed through sustained R&D by equipment suppliers, reduce miner exposure to hostile work environments and increase safety. This places increased focus on “ground control” and on rock mechanics to define the depth to which minerals may be extracted economically. Although significant efforts have been made since the end of World War II to apply mechanics to mine design, there have been both technological and organizational obstacles. Rock in situ is a more complex engineering material than is typically encountered in most other engineering disciplines. Mining engineering has relied heavily on empirical procedures in design for thousands of years. These are no longer adequate to address the challenges of the 21st century, as mines venture to increasingly greater depths. The development of the synthetic rock mass (SRM in 2008 provides researchers with the ability to analyze the deformational behavior of rock masses that are anisotropic and discontinuous—attributes that were described as the defining characteristics of in situ rock by Leopold Müller, the president and founder of the International Society for Rock Mechanics (ISRM, in 1966. Recent developments in the numerical modeling of large-scale mining operations (e.g., caving using the SRM reveal unanticipated deformational behavior of the rock. The application of massive parallelization and cloud computational techniques offers major opportunities: for example, to assess uncertainties in numerical predictions; to establish the mechanics basis for the empirical rules now used in rock engineering and their validity for the prediction of rock mass behavior beyond current experience; and to use the discrete element method (DEM in the optimization of deep mine design. For the first time, mining

  8. Objective aesthetic performance of Icon treatment by deep infiltration: a case report

    Directory of Open Access Journals (Sweden)

    Fabrizio Guerra

    2016-06-01

    Full Text Available Enamel hypomineralization is characterized by decreased refractive index of the lesion surface as compared to the surrounding sound enamel. Icon® treatment has been recently successfully used for the cosmetic treatment of enamel demineralizations seen in white spot lesions (WSLs and developmental defects of enamel (DDE. On the other hand, cases of molar incisal hypomineralization (MIH, deep lesions of traumatic origin, and those associated with severe fluorosis do not have the same response to this type of treatment. The application of a new deep Icon® infiltrative technique is proposed and the aesthetic results are validated by using a spectrophotometric approach as previously described by our group.

  9. ¿El Caballo Viejo? Latin Genre Recognition with Deep Learning and Spectral Periodicity

    DEFF Research Database (Denmark)

    Sturm, Bob L.; Kereliuk, Corey Mose; Larsen, Jan

    2015-01-01

    as BALLROOM. In this paper, we reproduce the “winning” deep learning system using LMD, and measure the effects of time dilation on its performance. We find that tempo changes of at most ±6 % greatly diminish and improve its performance. Interpreted with the low-level nature of the input features......The “winning” system in the 2013 MIREX Latin Genre Classification Task was a deep neural network trained with simple features. An explanation for its winning performance has yet to be found. In previous work, we built similar systems using the BALLROOM music dataset, and found their performances...

  10. Deep brain stimulation reveals emotional impact processing in ventromedial prefrontal cortex

    DEFF Research Database (Denmark)

    Gjedde, Albert; Geday, Jacob

    2009-01-01

    We tested the hypothesis that modulation of monoaminergic tone with deep-brain stimulation (DBS) of subthalamic nucleus would reveal a site of reactivity in the ventromedial prefrontal cortex that we previously identified by modulating serotonergic and noradrenergic mechanisms by blocking serotonin......-noradrenaline reuptake sites. We tested the hypothesis in patients with Parkinson's disease in whom we had measured the changes of blood flow everywhere in the brain associated with the deep brain stimulation of the subthalamic nucleus. We determined the emotional reactivity of the patients as the average impact...

  11. Malignant peritoneal mesothelioma associated with deep vein thrombosis following radiotherapy for seminoma of the testis

    International Nuclear Information System (INIS)

    Sato, Fuminori; Yamazaki, Hajime; Ataka, Ken; Mashima, Ichiro; Suzuki, Kenta; Takahashi, Toru; Umezu, Hajime; Gejyo, Fumitake

    2000-01-01

    A 52-year-old man developed malignant peritoneal mesothelioma 17 years after radiotherapy for seminoma of the testis. Although asbestos exposure is considered to be the major risk factor for the development of malignant mesothelioma, prior therapeutic radiation has also been postulated as a causative factor. The unexplained appearance of ascites or pleural effusion within a previously irradiated area should be considered suggestive of malignant mesothelioma in any long-term survivor of cancer. In addition, the patient suffered a deep vein thrombosis four years before the diagnosis of mesothelioma. Deep vein thrombosis is a common complication of malignant disease, and is often the first clue to occult malignancy. (author)

  12. Malignant peritoneal mesothelioma associated with deep vein thrombosis following radiotherapy for seminoma of the testis

    Energy Technology Data Exchange (ETDEWEB)

    Sato, Fuminori; Yamazaki, Hajime; Ataka, Ken; Mashima, Ichiro; Suzuki, Kenta; Takahashi, Toru; Umezu, Hajime; Gejyo, Fumitake [Niigata Univ. (Japan). School of Medicine

    2000-11-01

    A 52-year-old man developed malignant peritoneal mesothelioma 17 years after radiotherapy for seminoma of the testis. Although asbestos exposure is considered to be the major risk factor for the development of malignant mesothelioma, prior therapeutic radiation has also been postulated as a causative factor. The unexplained appearance of ascites or pleural effusion within a previously irradiated area should be considered suggestive of malignant mesothelioma in any long-term survivor of cancer. In addition, the patient suffered a deep vein thrombosis four years before the diagnosis of mesothelioma. Deep vein thrombosis is a common complication of malignant disease, and is often the first clue to occult malignancy. (author)

  13. Effectiveness of a second deep TMS in depression: a brief report.

    Science.gov (United States)

    Rosenberg, O; Isserles, M; Levkovitz, Y; Kotler, M; Zangen, A; Dannon, P N

    2011-06-01

    Deep transcranial magnetic stimulation (DTMS) is an emerging and promising treatment for major depression. In our study, we explored the effectiveness of a second antidepressant course of deep TMS in major depression. We enrolled eight patients who had previously responded well to DTMS but relapsed within 1 year in order to evaluate whether a second course of DTMS would still be effective. Eight depressive patients who relapsed after a previous successful deep TMS course expressed their wish to be treated again. Upon their request, they were recruited and treated with 20 daily sessions of DTMS at 20 Hz using the Brainsway's H1 coil. The Hamilton depression rating scale (HDRS), Hamilton anxiety rating scale (HARS) and the Beck depression inventory (BDI) were used weekly to evaluate the response to treatment. Similar to the results obtained in the first course of treatment, the second course of treatment (after relapse) induced significant reductions in HDRS, HARS and BDI scores, compared to the ratings measured prior to treatment. The magnitude of response in the second course was smaller relative to that obtained in the first course of treatment. Our results suggest that depressive patients who previously responded well to deep TMS treatment are likely to respond again. However, the slight reduction in the magnitude of the response in the second treatment raises the question of whether tolerance or resistance to this treatment may eventually develop. Copyright © 2011 Elsevier Inc. All rights reserved.

  14. 76 FR 1349 - Airworthiness Directives; Cessna Aircraft Company (Cessna) (Type Certificate A00003SE Previously...

    Science.gov (United States)

    2011-01-10

    ... Airworthiness Directives; Cessna Aircraft Company (Cessna) (Type Certificate A00003SE Previously Held by... Company (Type Certificate A00003SE previously held by Columbia Aircraft Manufacturing (previously The... Cessna Aircraft Company (Cessna) (Type Certificate A00003SE previously held by Columbia Aircraft...

  15. Improved Automated Detection of Diabetic Retinopathy on a Publicly Available Dataset Through Integration of Deep Learning.

    Science.gov (United States)

    Abràmoff, Michael David; Lou, Yiyue; Erginay, Ali; Clarida, Warren; Amelon, Ryan; Folk, James C; Niemeijer, Meindert

    2016-10-01

    To compare performance of a deep-learning enhanced algorithm for automated detection of diabetic retinopathy (DR), to the previously published performance of that algorithm, the Iowa Detection Program (IDP)-without deep learning components-on the same publicly available set of fundus images and previously reported consensus reference standard set, by three US Board certified retinal specialists. We used the previously reported consensus reference standard of referable DR (rDR), defined as International Clinical Classification of Diabetic Retinopathy moderate, severe nonproliferative (NPDR), proliferative DR, and/or macular edema (ME). Neither Messidor-2 images, nor the three retinal specialists setting the Messidor-2 reference standard were used for training IDx-DR version X2.1. Sensitivity, specificity, negative predictive value, area under the curve (AUC), and their confidence intervals (CIs) were calculated. Sensitivity was 96.8% (95% CI: 93.3%-98.8%), specificity was 87.0% (95% CI: 84.2%-89.4%), with 6/874 false negatives, resulting in a negative predictive value of 99.0% (95% CI: 97.8%-99.6%). No cases of severe NPDR, PDR, or ME were missed. The AUC was 0.980 (95% CI: 0.968-0.992). Sensitivity was not statistically different from published IDP sensitivity, which had a CI of 94.4% to 99.3%, but specificity was significantly better than the published IDP specificity CI of 55.7% to 63.0%. A deep-learning enhanced algorithm for the automated detection of DR, achieves significantly better performance than a previously reported, otherwise essentially identical, algorithm that does not employ deep learning. Deep learning enhanced algorithms have the potential to improve the efficiency of DR screening, and thereby to prevent visual loss and blindness from this devastating disease.

  16. Memo on Some Target of Previous Meeting in 2004 and Now

    International Nuclear Information System (INIS)

    Shibata, Heki

    2014-01-01

    The necessity of deep borehole observation was pointed out in a 2002 WS entitled 'Physics of Active Faults' organized by USGS and NIED, and discussion on the utilization of deep borehole observation for design basis ground motion development was then was deepened at the 2004 OECD/NEED Tsukuba WS. In addition to this study history, a series of WSs on Seismic Observation in Deep Boreholes and its Application organized by OECD, IAEA and JNES was planned. The author also explained that at the first SODB WS, he expected deep borehole observation to be used to observe the activity of specific faults with high accuracy, to detect the detailed structure of those specific faults, and to estimate the asperity distribution in order to establish a practical approach to design basis earthquakes for nuclear power plant design. Recently, however, he has come to think that SODB will help find hidden faults and help observe the conditions of old faults. He also mentioned that he believes that in the future SODB can be used for re-activity evaluation of tertiary faults and evaluation of the movement of local fracture zones

  17. Deep learning classification in asteroseismology

    Science.gov (United States)

    Hon, Marc; Stello, Dennis; Yu, Jie

    2017-08-01

    In the power spectra of oscillating red giants, there are visually distinct features defining stars ascending the red giant branch from those that have commenced helium core burning. We train a 1D convolutional neural network by supervised learning to automatically learn these visual features from images of folded oscillation spectra. By training and testing on Kepler red giants, we achieve an accuracy of up to 99 per cent in separating helium-burning red giants from those ascending the red giant branch. The convolutional neural network additionally shows capability in accurately predicting the evolutionary states of 5379 previously unclassified Kepler red giants, by which we now have greatly increased the number of classified stars.

  18. Ultra Deep Wave Equation Imaging and Illumination

    Energy Technology Data Exchange (ETDEWEB)

    Alexander M. Popovici; Sergey Fomel; Paul Sava; Sean Crawley; Yining Li; Cristian Lupascu

    2006-09-30

    In this project we developed and tested a novel technology, designed to enhance seismic resolution and imaging of ultra-deep complex geologic structures by using state-of-the-art wave-equation depth migration and wave-equation velocity model building technology for deeper data penetration and recovery, steeper dip and ultra-deep structure imaging, accurate velocity estimation for imaging and pore pressure prediction and accurate illumination and amplitude processing for extending the AVO prediction window. Ultra-deep wave-equation imaging provides greater resolution and accuracy under complex geologic structures where energy multipathing occurs, than what can be accomplished today with standard imaging technology. The objective of the research effort was to examine the feasibility of imaging ultra-deep structures onshore and offshore, by using (1) wave-equation migration, (2) angle-gathers velocity model building, and (3) wave-equation illumination and amplitude compensation. The effort consisted of answering critical technical questions that determine the feasibility of the proposed methodology, testing the theory on synthetic data, and finally applying the technology for imaging ultra-deep real data. Some of the questions answered by this research addressed: (1) the handling of true amplitudes in the downward continuation and imaging algorithm and the preservation of the amplitude with offset or amplitude with angle information required for AVO studies, (2) the effect of several imaging conditions on amplitudes, (3) non-elastic attenuation and approaches for recovering the amplitude and frequency, (4) the effect of aperture and illumination on imaging steep dips and on discriminating the velocities in the ultra-deep structures. All these effects were incorporated in the final imaging step of a real data set acquired specifically to address ultra-deep imaging issues, with large offsets (12,500 m) and long recording time (20 s).

  19. Large-eddy simulation of maritime deep tropical convection

    Directory of Open Access Journals (Sweden)

    Peter A Bogenschutz

    2009-12-01

    Full Text Available This study represents an attempt to apply Large-Eddy Simulation (LES resolution to simulate deep tropical convection in near equilibrium for 24 hours over an area of about 205 x 205 km2, which is comparable to that of a typical horizontal grid cell in a global climate model. The simulation is driven by large-scale thermodynamic tendencies derived from mean conditions during the GATE Phase III field experiment. The LES uses 2048 x 2048 x 256 grid points with horizontal grid spacing of 100 m and vertical grid spacing ranging from 50 m in the boundary layer to 100 m in the free troposphere. The simulation reaches a near equilibrium deep convection regime in 12 hours. The simulated vertical cloud distribution exhibits a trimodal vertical distribution of deep, middle and shallow clouds similar to that often observed in Tropics. A sensitivity experiment in which cold pools are suppressed by switching off the evaporation of precipitation results in much lower amounts of shallow and congestus clouds. Unlike the benchmark LES where the new deep clouds tend to appear along the edges of spreading cold pools, the deep clouds in the no-cold-pool experiment tend to reappear at the sites of the previous deep clouds and tend to be surrounded by extensive areas of sporadic shallow clouds. The vertical velocity statistics of updraft and downdraft cores below 6 km height are compared to aircraft observations made during GATE. The comparison shows generally good agreement, and strongly suggests that the LES simulation can be used as a benchmark to represent the dynamics of tropical deep convection on scales ranging from large turbulent eddies to mesoscale convective systems. The effect of horizontal grid resolution is examined by running the same case with progressively larger grid sizes of 200, 400, 800, and 1600 m. These runs show a reasonable agreement with the benchmark LES in statistics such as convective available potential energy, convective inhibition

  20. Deep ocean communities impacted by changing climate over 24 y in the abyssal northeast Pacific Ocean.

    Science.gov (United States)

    Smith, Kenneth L; Ruhl, Henry A; Kahru, Mati; Huffard, Christine L; Sherman, Alana D

    2013-12-03

    The deep ocean, covering a vast expanse of the globe, relies almost exclusively on a food supply originating from primary production in surface waters. With well-documented warming of oceanic surface waters and conflicting reports of increasing and decreasing primary production trends, questions persist about how such changes impact deep ocean communities. A 24-y time-series study of sinking particulate organic carbon (food) supply and its utilization by the benthic community was conducted in the abyssal northeast Pacific (~4,000-m depth). Here we show that previous findings of food deficits are now punctuated by large episodic surpluses of particulate organic carbon reaching the sea floor, which meet utilization. Changing surface ocean conditions are translated to the deep ocean, where decadal peaks in supply, remineralization, and sequestration of organic carbon have broad implications for global carbon budget projections.

  1. High efficacy with deep nurse-administered propofol sedation for advanced gastroenterologic endoscopic procedures

    DEFF Research Database (Denmark)

    Jensen, Jeppe Thue; Hornslet, Pernille; Konge, Lars

    2016-01-01

    was requested eight times (0.4 %). One patient was intubated due to suspected aspiration. CONCLUSIONS: Intermittent deep NAPS for advanced endoscopies in selected patients provided an almost 100 % success rate. However, the rate of hypoxia, hypotension and respiratory support was high compared with previously......BACKGROUND AND STUDY AIMS: Whereas data on moderate nurse-administered propofol sedation (NAPS) efficacy and safety for standard endoscopy is abundant, few reports on the use of deep sedation by endoscopy nurses during advanced endoscopy, such as Endoscopic Retrograde Cholangiopancreatography (ERCP......) and Endoscopic Ultrasound (EUS) are available and potential benefits or hazards remain unclear. The aims of this study were to investigate the efficacy of intermittent deep sedation with propofol for a large cohort of advanced endoscopies and to provide data on the safety. PATIENTS AND METHODS: All available...

  2. Seasonal copepod lipid pump promotes carbon sequestration in the deep North Atlantic.

    Science.gov (United States)

    Jónasdóttir, Sigrún Huld; Visser, André W; Richardson, Katherine; Heath, Michael R

    2015-09-29

    Estimates of carbon flux to the deep oceans are essential for our understanding of global carbon budgets. Sinking of detrital material ("biological pump") is usually thought to be the main biological component of this flux. Here, we identify an additional biological mechanism, the seasonal "lipid pump," which is highly efficient at sequestering carbon into the deep ocean. It involves the vertical transport and metabolism of carbon rich lipids by overwintering zooplankton. We show that one species, the copepod Calanus finmarchicus overwintering in the North Atlantic, sequesters an amount of carbon equivalent to the sinking flux of detrital material. The efficiency of the lipid pump derives from a near-complete decoupling between nutrient and carbon cycling—a "lipid shunt," and its direct transport of carbon through the mesopelagic zone to below the permanent thermocline with very little attenuation. Inclusion of the lipid pump almost doubles the previous estimates of deep-ocean carbon sequestration by biological processes in the North Atlantic.

  3. DeepPVP: phenotype-based prioritization of causative variants using deep learning

    KAUST Repository

    Boudellioua, Imene; Kulmanov, Maxat; Schofield, Paul N; Gkoutos, Georgios V; Hoehndorf, Robert

    2018-01-01

    phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp Conclusions: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well

  4. Deep-sea Lebensspuren of the Australian continental margins

    Science.gov (United States)

    Przeslawski, Rachel; Dundas, Kate; Radke, Lynda; Anderson, Tara J.

    Much of the deep sea comprises soft-sediment habitats dominated by comparatively low abundances of species-rich macrofauna and meiofauna. Although often not observed, these animals bioturbate the sediment during feeding and burrowing, leaving signs of their activities called Lebensspuren ('life traces'). In this study, we use still images to quantify Lebensspuren from the eastern (1921 images, 13 stations, 1300-2200 m depth) and western (1008 images, 11 stations, 1500-4400 m depth) Australian margins using a univariate measure of trace richness and a multivariate measure of Lebensspuren assemblages. A total of 46 Lebensspuren types were identified, including those matching named trace fossils and modern Lebensspuren found elsewhere in the world. Most traces could be associated with waste, crawling, dwellings, organism tests, feeding, or resting, but the origin of 15% of trace types remains unknown. Assemblages were significantly different between the two regions and depth profiles, with five Lebensspuren types accounting for over 95% of the differentiation (ovoid pinnate trace, crater row, spider trace, matchstick trace, mesh trace). Lebensspuren richness showed no strong relationships with depth, total organic carbon, or mud, although there was a positive correlation to chlorin index (i.e., organic freshness) in the eastern margin, with richness increasing with organic freshness. Lebensspuren richness was not related to epifauna either, indicating that epifauna may not be the primary source of Lebensspuren. Despite the abundance and distinctiveness of several traces both in the current and previous studies (e.g., ovoid pinnate, mesh, spider), their origin and distribution remains a mystery. We discuss this and several other considerations in the identification and quantification of Lebensspuren. This study represents the first comprehensive catalogue of deep-sea Lebensspuren in Australian waters and highlights the potential of Lebensspuren as valuable and often

  5. Deep learning for EEG-Based preference classification

    Science.gov (United States)

    Teo, Jason; Hou, Chew Lin; Mountstephens, James

    2017-10-01

    Electroencephalogram (EEG)-based emotion classification is rapidly becoming one of the most intensely studied areas of brain-computer interfacing (BCI). The ability to passively identify yet accurately correlate brainwaves with our immediate emotions opens up truly meaningful and previously unattainable human-computer interactions such as in forensic neuroscience, rehabilitative medicine, affective entertainment and neuro-marketing. One particularly useful yet rarely explored areas of EEG-based emotion classification is preference recognition [1], which is simply the detection of like versus dislike. Within the limited investigations into preference classification, all reported studies were based on musically-induced stimuli except for a single study which used 2D images. The main objective of this study is to apply deep learning, which has been shown to produce state-of-the-art results in diverse hard problems such as in computer vision, natural language processing and audio recognition, to 3D object preference classification over a larger group of test subjects. A cohort of 16 users was shown 60 bracelet-like objects as rotating visual stimuli on a computer display while their preferences and EEGs were recorded. After training a variety of machine learning approaches which included deep neural networks, we then attempted to classify the users' preferences for the 3D visual stimuli based on their EEGs. Here, we show that that deep learning outperforms a variety of other machine learning classifiers for this EEG-based preference classification task particularly in a highly challenging dataset with large inter- and intra-subject variability.

  6. Radiocarbon Based Ages and Growth Rates: Hawaiian Deep Sea Corals

    Energy Technology Data Exchange (ETDEWEB)

    Roark, E B; Guilderson, T P; Dunbar, R B; Ingram, B L

    2006-01-13

    The radial growth rates and ages of three different groups of Hawaiian deep-sea 'corals' were determined using radiocarbon measurements. Specimens of Corallium secundum, Gerardia sp., and Leiopathes glaberrima, were collected from 450 {+-} 40 m at the Makapuu deep-sea coral bed using a submersible (PISCES V). Specimens of Antipathes dichotoma were collected at 50 m off Lahaina, Maui. The primary source of carbon to the calcitic C. secundum skeleton is in situ dissolved inorganic carbon (DIC). Using bomb {sup 14}C time markers we calculate radial growth rates of {approx} 170 {micro}m y{sup -1} and ages of 68-75 years on specimens as tall as 28 cm of C. secundum. Gerardia sp., A. dichotoma, and L. glaberrima have proteinaceous skeletons and labile particulate organic carbon (POC) is their primary source of architectural carbon. Using {sup 14}C we calculate a radial growth rate of 15 {micro}m y{sup -1} and an age of 807 {+-} 30 years for a live collected Gerardia sp., showing that these organisms are extremely long lived. Inner and outer {sup 14}C measurements on four sub-fossil Gerardia spp. samples produce similar growth rate estimates (range 14-45 {micro}m y{sup -1}) and ages (range 450-2742 years) as observed for the live collected sample. Similarly, with a growth rate of < 10 {micro}m y{sup -1} and an age of {approx}2377 years, L. glaberrima at the Makapuu coral bed, is also extremely long lived. In contrast, the shallow-collected A. dichotoma samples yield growth rates ranging from 130 to 1,140 {micro}m y{sup -1}. These results show that Hawaiian deep-sea corals grow more slowly and are older than previously thought.

  7. Iodine-123 miniplasmin for the detection of deep venous thrombosis

    International Nuclear Information System (INIS)

    Schubiger, P.A.; Haeberli, A.; Gallino, A.; Straub, P.W.

    1989-09-01

    Human plasminogen (MW 90'000) is cleaved by elastase into several fragments, including one with a molecular weight of 38'000 (mini-plasminogen). This fragment retains sufficiently preserved fibrin binding sites but lacks the affinity for α 2 -antiplasmin. Therefore radiolabelled miniplasmin was tested in 21 patients with suspected deep venous thrombosis, in 5 patients with lymphedema and in 5 healthy controls for its potential use as fast marker of deep venous thrombosis. 250 μCi of Iodine-123 miniplasmin was given i.v. after previous activation with 3000 IU urokinase. The tracer distribution was measured 15, 30 and 60 minutes after injection at 10 points over each leg. The mean left/right ratio obtained in the 5 volunteers was 1.04 (range 0.89-1.12). In the patients the test was considered positive when the left/right ratio was greater than 1.15 or smaller than 0.85 at two adjacent locations and in two consecutive measuring times. In the 21 patients studied both tests gave concurrent results in 19, while in one patient with a positive and in one patient with a negative phlebography the miniplasmintest gave opposite results. In 4 of the 5 patients with edema and no thrombosis the miniplasmintest was negative. Most positive tests were conclusive as early as 15 minutes after injection of miniplasmin. The sensitivity was calculated to be 90% and the specificity 85%. Therefore Iodine-123 miniplasmin has been estimated as a fast, non invasive marker for the diagnosis of deep venous thrombosis and preliminary clinical studies with scintigraphy have been performed on over 50 patients. Evaluation gave a sensitivity between 40% and 86% and a specificity between 62% and 100%. Clinical studies have not been continued. Since I-123 miniplasmin is not available around the clock, it can't be used in emergency diagnosis. (author) 2 figs., 5 tabs., 30 refs

  8. Desalination Economic Evaluation Program (DEEP-3.0). User's manual

    International Nuclear Information System (INIS)

    2006-01-01

    DEEP is a Desalination Economic Evaluation Program developed by the International Atomic Energy Agency (IAEA) and made freely available for download, under a license agreement (www.iaea.org/nucleardesalination). The program is based on linked Microsoft Excel spreadsheets and can be useful for evaluating desalination strategies by calculating estimates of technical performance and costs for various alternative energy and desalination technology configurations. Desalination technology options modelled, include multi-stage flashing (MSF), multi-effect distillation (MED), reverse osmosis (RO) and hybrid options (RO-MSF, RO-MED) while energy source options include nuclear, fossil, renewables and grid electricity (stand-alone RO). Version 3 of DEEP (DEEP 3.0) features important changes from previous versions, including upgrades in thermal and membrane performance and costing models, the coupling configuration matrix and the user interface. Changes in the thermal performance model include a revision of the gain output ratio (GOR) calculation and its generalization to include thermal vapour compression effects. Since energy costs continue to represent an important fraction of seawater desalination costs, the lost shaft work model has been generalized to properly account for both backpressure and extraction systems. For RO systems, changes include improved modelling of system recovery, feed pressure and permeate salinity, taking into account temperature, feed salinity and fouling correction factors. The upgrade to the coupling technology configuration matrix includes a re-categorization of the energy sources to follow turbine design (steam vs. gas) and cogeneration features (dual-purpose vs. heat-only). In addition, cost data has also been updated to reflect current practice and the user interface has been refurbished and made user-friendlier

  9. Assessment of deep geological environment condition

    International Nuclear Information System (INIS)

    Bae, Dae Seok; Han, Kyung Won; Joen, Kwan Sik

    2003-05-01

    The main tasks of geoscientific study in the 2nd stage was characterized focusing mainly on a near-field condition of deep geologic environment, and aimed to generate the geologic input data for a Korean reference disposal system for high level radioactive wastes and to establish site characterization methodology, including neotectonic features, fracture systems and mechanical properties of plutonic rocks, and hydrogeochemical characteristics. The preliminary assessment of neotectonics in the Korean peninsula was performed on the basis of seismicity recorded, Quarternary faults investigated, uplift characteristics studied on limited areas, distribution of the major regional faults and their characteristics. The local fracture system was studied in detail from the data obtained from deep boreholes in granitic terrain. Through this deep drilling project, the geometrical and hydraulic properties of different fracture sets are statistically analysed on a block scale. The mechanical properties of intact rocks were evaluated from the core samples by laboratory testing and the in-situ stress conditions were estimated by a hydro fracturing test in the boreholes. The hydrogeochemical conditions in the deep boreholes were characterized based on hydrochemical composition and isotopic signatures and were attempted to assess the interrelation with a major fracture system. The residence time of deep groundwater was estimated by C-14 dating. For the travel time of groundwater between the boreholes, the methodology and equipment for tracer test were established

  10. Molecular analysis of deep subsurface bacteria

    International Nuclear Information System (INIS)

    Jimenez Baez, L.E.

    1989-09-01

    Deep sediments samples from site C10a, in Appleton, and sites, P24, P28, and P29, at the Savannah River Site (SRS), near Aiken, South Carolina were studied to determine their microbial community composition, DNA homology and mol %G+C. Different geological formations with great variability in hydrogeological parameters were found across the depth profile. Phenotypic identification of deep subsurface bacteria underestimated the bacterial diversity at the three SRS sites, since bacteria with the same phenotype have different DNA composition and less than 70% DNA homology. Total DNA hybridization and mol %G+C analysis of deep sediment bacterial isolates suggested that each formation is comprised of different microbial communities. Depositional environment was more important than site and geological formation on the DNA relatedness between deep subsurface bacteria, since more 70% of bacteria with 20% or more of DNA homology came from the same depositional environments. Based on phenotypic and genotypic tests Pseudomonas spp. and Acinetobacter spp.-like bacteria were identified in 85 million years old sediments. This suggests that these microbial communities might have been adapted during a long period of time to the environmental conditions of the deep subsurface

  11. Preface: Deep Slab and Mantle Dynamics

    Science.gov (United States)

    Suetsugu, Daisuke; Bina, Craig R.; Inoue, Toru; Wiens, Douglas A.

    2010-11-01

    We are pleased to publish this special issue of the journal Physics of the Earth and Planetary Interiors entitled "Deep Slab and Mantle Dynamics". This issue is an outgrowth of the international symposium "Deep Slab and Mantle Dynamics", which was held on February 25-27, 2009, in Kyoto, Japan. This symposium was organized by the "Stagnant Slab Project" (SSP) research group to present the results of the 5-year project and to facilitate intensive discussion with well-known international researchers in related fields. The SSP and the symposium were supported by a Grant-in-Aid for Scientific Research (16075101) from the Ministry of Education, Culture, Sports, Science and Technology of the Japanese Government. In the symposium, key issues discussed by participants included: transportation of water into the deep mantle and its role in slab-related dynamics; observational and experimental constraints on deep slab properties and the slab environment; modeling of slab stagnation to constrain its mechanisms in comparison with observational and experimental data; observational, experimental and modeling constraints on the fate of stagnant slabs; eventual accumulation of stagnant slabs on the core-mantle boundary and its geodynamic implications. This special issue is a collection of papers presented in the symposium and other papers related to the subject of the symposium. The collected papers provide an overview of the wide range of multidisciplinary studies of mantle dynamics, particularly in the context of subduction, stagnation, and the fate of deep slabs.

  12. Deep Ocean Contribution to Sea Level Rise

    Science.gov (United States)

    Chang, L.; Sun, W.; Tang, H.; Wang, Q.

    2017-12-01

    The ocean temperature and salinity change in the upper 2000m can be detected by Argo floats, so we can know the steric height change of the ocean. But the ocean layers above 2000m represent only 50% of the total ocean volume. Although the temperature and salinity change are small compared to the upper ocean, the deep ocean contribution to sea level might be significant because of its large volume. There has been some research on the deep ocean rely on the very sparse situ observation and are limited to decadal and longer-term rates of change. The available observational data in the deep ocean are too spares to determine the temporal variability, and the long-term changes may have a bias. We will use the Argo date and combine the situ data and topographic data to estimate the temperature and salinity of the sea water below 2000m, so we can obtain a monthly data. We will analyze the seasonal and annual change of the steric height change due to the deep ocean between 2005 and 2016. And we will evaluate the result combination the present-day satellite and in situ observing systems. The deep ocean contribution can be inferred indirectly as the difference between the altimetry minus GRACE and Argo-based steric sea level.

  13. Deep Learning: A Primer for Radiologists.

    Science.gov (United States)

    Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

    2017-01-01

    Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

  14. DeepPVP: phenotype-based prioritization of causative variants using deep learning

    KAUST Repository

    Boudellioua, Imene

    2018-05-02

    Background: Prioritization of variants in personal genomic data is a major challenge. Recently, computational methods that rely on comparing phenotype similarity have shown to be useful to identify causative variants. In these methods, pathogenicity prediction is combined with a semantic similarity measure to prioritize not only variants that are likely to be dysfunctional but those that are likely involved in the pathogenesis of a patient\\'s phenotype. Results: We have developed DeepPVP, a variant prioritization method that combined automated inference with deep neural networks to identify the likely causative variants in whole exome or whole genome sequence data. We demonstrate that DeepPVP performs significantly better than existing methods, including phenotype-based methods that use similar features. DeepPVP is freely available at https://github.com/bio-ontology-research-group/phenomenet-vp Conclusions: DeepPVP further improves on existing variant prioritization methods both in terms of speed as well as accuracy.

  15. Deep learning in TMVA Benchmarking Benchmarking TMVA DNN Integration of a Deep Autoencoder

    CERN Document Server

    Huwiler, Marc

    2017-01-01

    The TMVA library in ROOT is dedicated to multivariate analysis, and in partic- ular oers numerous machine learning algorithms in a standardized framework. It is widely used in High Energy Physics for data analysis, mainly to perform regression and classication. To keep up to date with the state of the art in deep learning, a new deep learning module was being developed this summer, oering deep neural net- work, convolutional neural network, and autoencoder. TMVA did not have yet any autoencoder method, and the present project consists in implementing the TMVA autoencoder class based on the deep learning module. It also includes some bench- marking performed on the actual deep neural network implementation, in comparison to the Keras framework with Tensorflow and Theano backend.

  16. DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network.

    Science.gov (United States)

    Katzman, Jared L; Shaham, Uri; Cloninger, Alexander; Bates, Jonathan; Jiang, Tingting; Kluger, Yuval

    2018-02-26

    Medical practitioners use survival models to explore and understand the relationships between patients' covariates (e.g. clinical and genetic features) and the effectiveness of various treatment options. Standard survival models like the linear Cox proportional hazards model require extensive feature engineering or prior medical knowledge to model treatment interaction at an individual level. While nonlinear survival methods, such as neural networks and survival forests, can inherently model these high-level interaction terms, they have yet to be shown as effective treatment recommender systems. We introduce DeepSurv, a Cox proportional hazards deep neural network and state-of-the-art survival method for modeling interactions between a patient's covariates and treatment effectiveness in order to provide personalized treatment recommendations. We perform a number of experiments training DeepSurv on simulated and real survival data. We demonstrate that DeepSurv performs as well as or better than other state-of-the-art survival models and validate that DeepSurv successfully models increasingly complex relationships between a patient's covariates and their risk of failure. We then show how DeepSurv models the relationship between a patient's features and effectiveness of different treatment options to show how DeepSurv can be used to provide individual treatment recommendations. Finally, we train DeepSurv on real clinical studies to demonstrate how it's personalized treatment recommendations would increase the survival time of a set of patients. The predictive and modeling capabilities of DeepSurv will enable medical researchers to use deep neural networks as a tool in their exploration, understanding, and prediction of the effects of a patient's characteristics on their risk of failure.

  17. Striations, duration, migration and tidal response in deep tremor.

    Science.gov (United States)

    Ide, Satoshi

    2010-07-15

    Deep tremor in subduction zones is thought to be caused by small repeating shear slip events on the plate interface with significant slow components. It occurs at a depth of about 30 kilometres and provides valuable information on deep plate motion and shallow stress accumulation on the fault plane of megathrust earthquakes. Tremor has been suggested to repeat at a regular interval, migrate at various velocities and be modulated by tidal stress. Here I show that some time-invariant interface property controls tremor behaviour, using precise location of tremor sources with event duration in western Shikoku in the Nankai subduction zone, Japan. In areas where tremor duration is short, tremor is more strongly affected by tidal stress and migration is inhibited. Where tremor lasts longer, diffusive migration occurs with a constant diffusivity of 10(4) m(2) s(-1). The control property may be the ratio of brittle to ductile areas, perhaps determined by the influence of mantle wedge serpentinization on the plate interface. The spatial variation of the controlling property seems to be characterized by striations in tremor source distribution, which follows either the current or previous plate subduction directions. This suggests that the striations and corresponding interface properties are formed through the subduction of inhomogeneous structure, such as seamounts, for periods as long as ten million years.

  18. Behaviour of Steel Fibre Reinforced Rubberized Continuous Deep Beams

    Science.gov (United States)

    Sandeep, MS; Nagarajan, Praveen; Shashikala, A. P.

    2018-03-01

    Transfer girders and pier caps, which are in fact deep beams, are critical structural elements present in high-rise buildings and bridges respectively. During an earthquake, failure of lifeline structures like bridges and critical structural members like transfer girders will result in severe catastrophes. Ductility is the key factor that influences the resistance of any structural member against seismic action. Structural members cast using materials having higher ductility will possess higher seismic resistance. Previous research shows that concrete having rubber particles (rubcrete) possess better ductility and low density in comparison to ordinary concrete. The main hindrance to the use of rubcrete is the reduction in compressive and tensile strength of concrete due to the presence of rubber. If these undesirable properties of rubcrete can be controlled, a new cementitious composite with better ductility, seismic performance and economy can be developed. A combination of rubber particles and steel fibre has the potential to reduce the undesirable effect of rubcrete. In this paper, the effect of rubber particles and steel fibre in the behaviour of two-span continuous deep beams is studied experimentally. Based on the results, optimum proportions of steel fibre and rubber particles for getting good ductile behaviour with less reduction in collapse load is found out.

  19. Desiccation-crack-induced salinization in deep clay sediment

    Directory of Open Access Journals (Sweden)

    S. Baram

    2013-04-01

    Full Text Available A study on water infiltration and solute transport in a clayey vadose zone underlying a dairy farm waste source was conducted to assess the impact of desiccation cracks on subsurface evaporation and salinization. The study is based on five years of continuous measurements of the temporal variation in the vadose zone water content and on the chemical and isotopic composition of the sediment and pore water in it. The isotopic composition of water stable isotopes (δ18O and δ2H in water and sediment samples, from the area where desiccation crack networks prevail, indicated subsurface evaporation down to ~ 3.5 m below land surface, and vertical and lateral preferential transport of water, following erratic preferential infiltration events. Chloride (Cl− concentrations in the vadose zone pore water substantially increased with depth, evidence of deep subsurface evaporation and down flushing of concentrated solutions from the evaporation zones during preferential infiltration events. These observations led to development of a desiccation-crack-induced salinization (DCIS conceptual model. DCIS suggests that thermally driven convective air flow in the desiccation cracks induces evaporation and salinization in relatively deep sections of the subsurface. This conceptual model supports previous conceptual models on vadose zone and groundwater salinization in fractured rock in arid environments and extends its validity to clayey soils in semi-arid environments.

  20. Nano-Satellite Secondary Spacecraft on Deep Space Missions

    Science.gov (United States)

    Klesh, Andrew T.; Castillo-Rogez, Julie C.

    2012-01-01

    NanoSat technology has opened Earth orbit to extremely low-cost science missions through a common interface that provides greater launch accessibility. They have also been used on interplanetary missions, but these missions have used one-off components and architectures so that the return on investment has been limited. A natural question is the role that CubeSat-derived NanoSats could play to increase the science return of deep space missions. We do not consider single instrument nano-satellites as likely to complete entire Discovery-class missions alone,but believe that nano-satellites could augment larger missions to significantly increase science return. The key advantages offered by these mini-spacecrafts over previous planetary probes is the common availability of advanced subsystems that open the door to a large variety of science experiments, including new guidance, navigation and control capabilities. In this paper, multiple NanoSat science applications are investigated, primarily for high risk/high return science areas. We also address the significant challenges and questions that remain as obstacles to the use of nano-satellites in deep space missions. Finally, we provide some thoughts on a development roadmap toward interplanetary usage of NanoSpacecraft.