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Sample records for modified deep sclerectomy

  1. Bleeding during gonioscopy after deep sclerectomy.

    Science.gov (United States)

    Moreno-Montañés, Javier; Rodríguez-Conde, Rosa

    2003-10-01

    To show a new complication after deep sclerectomy (DS). We described two eyes of two patients with open-angle glaucoma and cataract who were operated on of an uneventful phacoemulsification and DS with SK-gel implantation. Bleeding during gonioscopic examination occurred in both eyes 7 and 8 months after combined surgery. The blood originated from the vessels around the Descemet window, and was probably due to manipulation or rocking of the goniolens. Pressure was immediately applied to the gonioscopic lens and the hyphema was interrupted. These cases show the presence of new vessels around the Descemet window after DS with SK-gel. Bleeding from the Descemet window vessels can occur during gonioscopy even months after DS. We recommend conducting a careful gonioscopic examination in patients who have undergone DS to avoid this complication.

  2. Prognostic value of gonioscopy after deep sclerectomy.

    Science.gov (United States)

    Moreno-Montañés, J; Rebolleda, G; Muñoz-Negrete, F J

    2007-01-01

    To ascertain gonioscopic characteristics and identify prognostic indicators related to intraocular pressure (IOP) after deep sclerectomy (DS). A transversal, prospective, and nonselected study was performed in 106 eyes (95 patients) after DS. Three surgeons performed all the surgeries and the gonioscopic examination, using the same protocol including 13 gonioscopic data. These data were evaluated for an association with postoperative IOP and time after surgery. A subscleral space was found in 91 eyes (85.8%), with visualization of the line of scleral flap in 48 eyes (45.3%). The trabeculo-Descemet membrane (TDM) was transparent in 46 eyes (43.4%), opaque in 4 cases, and pigmented in 18 eyes. This TDM was broken using Nd:YAG laser goniopuncture in 38 eyes(35.8%). Thin vessels around TDM were found in 58 eyes (54.7%), and blood remained in 25 eyes (23.5%). Gonioscopic variables significantly positively related with postoperative IOP were as follows: presence of subscleral space, scleral flap line view, and a Schwalbe line depressed. A narrow anterior chamber angle and iris synechia in TDM had a statistically significant negative effect on the postoperative IOP control. Similarly, eyes requiring Nd:YAG goniopuncture had a worse IOP control. The frequency of eyes with visible subscleral space and transparent TDM decreases with time after surgery (p=0.001). A visible subscleral space was a gonioscopic sign positively related to IOP control after surgery, although it decreased with follow-up. Eyes with goniopuncture, postoperative narrow angle, and iris synechia had worse postoperative IOP control. Although new vessels in TDM were a common finding after DS, the authors did not find any association with postoperative IOP.

  3. Subconjunctival PRGF Fibrin Membrane as an Adjuvant to Nonpenetrating Deep Sclerectomy: A 2-Year Pilot Study.

    Science.gov (United States)

    Rodríguez-Agirretxe, Iñaki; Freire, Vanesa; Muruzabal, Francisco; Orive, Gorka; Anitua, Eduardo; Díez-Feijóo, Elio; Acera, Arantxa

    2018-01-01

    To evaluate the potential role of the autologous PRGF (plasma rich in growth factors) fibrin membrane in tissue regeneration after glaucoma filtering surgery. Ten patients with medically uncontrolled primary open-angle glaucoma underwent nonpenetrating deep sclerectomy and were treated with PRGF fibrin membrane as adjuvant. Intraocular pressure reduction was the primary outcome. This variable was measured preoperatively and also at each follow-up visit. Secondary outcomes included the number of antiglaucoma medications, anterior segment optical coherence tomography bleb examination, photographic bleb evaluation, and subjective clinical symptomatology evaluation. The surgical technique showed a significant reduction (p PRGF-Endoret treatment could promote ocular surface regeneration after glaucoma surgery, enhancing the surgery success rates and reducing the need for postoperative medications. It is important to highlight that this is a preliminary study and some large clinical studies are necessary to verify these results. © 2017 S. Karger AG, Basel.

  4. Outcome of Primary Nonpenetrating Deep Sclerectomy in Patients with Steroid-Induced Glaucoma

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    Abdelhamid Elhofi

    2018-01-01

    Full Text Available Purpose. To evaluate the outcome of primary nonpenetrating deep sclerectomy (NPDS in patients with steroid-induced glaucoma. Methods. This was a retrospective interventional clinical study that included 60 eyes of 60 steroid-induced glaucoma patients that had undergone NPDS. Patients were followed up for 4 years. Data from the records was retrieved as regards corrected distance visual acuity (CDVA, intraocular pressure (IOP, visual field mean defect (dB, and number of antiglaucoma medications needed if any. Complete success of the surgical outcome was considered an IOP ≤ 21 mmHg with no antiglaucoma medications. Qualified success was considered an IOP ≤ 21 mmHg using antiglaucoma medications. Results. The mean age was 21.2 ± 8.5 years (ranged from 12 to 35 years. At 48 months, mean IOP was 13.6 ± 2.8 mmHg (range 11–23 mmHg. This represented 60% reduction of mean IOP from preoperative levels. One case had YAG laser goniopuncture. Three cases required needling followed by ab interno revision. Using ANOVA test, there was a statistically significant difference between preoperative and postoperative mean IOP values (P=0.032. Twelve, 16, and 20 patients required topical antiglaucoma medications at 24, 26, and 48 months postoperative, respectively. Conclusion. Primary nonpenetrating deep sclerectomy is a safe and an effective method of treating eyes with steroid-induced glaucoma. No major complications were encountered. After 4 years of follow-up, complete success rate was 56.7% and qualified success rate was 70%.

  5. Changes in anterior ocular structures and macula following deep sclerectomy with collagen implant.

    Science.gov (United States)

    Suominen, Sakari M A; Harju, Mika P; Hautamäki, Asta M E; Vesti, Eija T

    2018-01-01

    To determine the effect of intraocular pressure (IOP) lowering with deep sclerectomy (DS) on visual acuity, macular structures, and anterior ocular dimensions during the early postoperative period. We prospectively analyzed 35 eyes of 35 patients scheduled for DS. Our focus with the measurements was on early postoperative changes in anterior ocular and macular structures related to IOP lowering during the first month after DS. In addition to a clinical ophthalmologic examination, our measurements included corneal topography, measurement of ocular dimensions with optical biometry, and examination of macular structure with optical coherence tomography. These measurements were repeated 1, 2, and 4 weeks postoperatively. Best-corrected visual acuity (BCVA) decreased 1 week postoperatively to 0.22 (0.20) LogMAR (p = 0.006). The BCVA then increased to its preoperative level, 0.17 (0.18) (p = 0.28), after 4 weeks. Axial length decreased from 24.12 (1.81) mm to 24.04 (1.81) (p<0.001) 4 weeks postoperatively. The steeper meridian of corneal curvature and average corneal power increased postoperatively; central corneal thickness was decreased. No significant change appeared in other measurements. We found changes in corneal curvature and ocular dimensions after DS. These changes were relatively small and do not completely explain the decrease in visual acuity postoperatively. Macular structures showed no changes.

  6. Histopathological Evaluation of a Hydrophobic Terpolymer (PTFE-PVD-PP) as an Implant Material for Nonpenetrating Very Deep Sclerectomy.

    Science.gov (United States)

    Leszczynski, Rafal; Gumula, Teresa; Stodolak-Zych, Ewa; Pawlicki, Krzysztof; Wieczorek, Jaroslaw; Kajor, Maciej; Blazewicz, Stanislaw

    2015-08-01

    The purpose of the study was to assess the biocompatibility of porous terpolymer (polytetrafluoroethylene-co-polyvinylidene fluoride-co-polypropylene, PTFE-PVDF-PP) membranes as an implant material to be placed during nonpenetrating very deep sclerectomy (NPVDS). Another study objective was to determine whether the polymer membrane under investigation could be used to manufacture a new-generation implant, which would actively delay the process of fistula closure and facilitate aqueous humor drainage. Histological response and tissue tolerance of the implant material were assessed. The study was performed on 38 eyeballs of 19 New Zealand white rabbits (19 implanted, 19 control). Histological assessment was carried out between 2 and 52 weeks after surgery. We routinely assessed inflammatory infiltrate, neovascularization, hemorrhage, and stromal edema as well as connective tissue attachment to the implant and adjacent tissues. At 52 weeks of observation, a statistically significant difference was revealed between the study and control groups in terms of resorptive granulation, tissue, and the inflammatory infiltrate. No features of acute inflammatory response to the implant were observed, and there was an absence of histological features of acute inflammatory infiltrates and subsidence of chronic inflammatory infiltrates and resorptive granulation over time. Slight fibrotic response and insignificant changes in neighboring eye tissues all indicate good tolerance to bioimplant materials. This allows for some optimism regarding the use of hydrophobic terpolymer in the construction of new intrascleral implants. However, the ultimate decision regarding its usefulness and safety in the treatment of glaucoma requires further investigation.

  7. Mitomycin-augmented non-penetrating deep sclerectomy: preoperative gonioscopy and postoperative perimetric, tonometric and medication trends.

    Science.gov (United States)

    Sponsel, William Eric; Groth, Sylvia Linner

    2013-03-01

    Non-penetrating deep sclerectomy (NPDS) can enhance drainage of aqueous humour without disrupting the trabecular endothelial layer, reducing risks of postoperative hypotony and hyphema. This study explores associations of angle morphology with surgical efficacy in eyes with open and obstructed angles. Eighty-nine consecutive eyes undergoing successful NPDS (non-implant, with 0.4 mg/ml mitomycin C and limbus-based two-layer closure) were studied in this institutional review board-approved retrospective quality assurance study. Postoperative complication frequency, intraocular pressure (IOP), glaucoma medications required and acuity were monitored (baseline vs 3, 6, 9, 12 and 18-month postoperative levels), along with 30-2 Humphrey MD and corrected pattern standard deviation (CPSD) (baseline vs 6, 12 and 18-month postoperative values). Preoperative gonioscopy was compared with the subsequent requirement for specific postoperative interventions. IOP at all five postoperative intervals was reduced (22 ± 0.9 to 12 ± 0.5 mm Hg; p<0.0001). No hyphema were observed. Postoperative hypotony (IOP < 4 mm Hg) occurred rarely (8/445; 1.8%). Mean glaucoma medication use dropped from 3.1 ± 0.1 to 0.23 ± 0.1 at 18 months (p<0.0001). Mean 30-2 MD improved by approximately 1.4 dB at 6, 12 and 18 months (p<0.002); CPSD remained stable. Following NPDS, a sustained IOP decrease of 10 mm Hg (45%) was attained, with stable acuity, increased perimetric generalised light sensitivity and 90% reduction in medical therapy requirement. Morbidity risk was associated with narrow gonioscopic angle insertion and synechia, but not with shallow approach or trabecular pigmentation.

  8. Resultados pressóricos da esclerectomia profunda não penetrante no tratamento do glaucoma primário de ângulo aberto Tensional results of non-penetrating deep sclerectomy in the treatment of primary open-angle glaucoma

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    Ricardo Augusto Paletta Guedes

    2004-08-01

    Full Text Available OBJETIVO: O presente estudo tem como objetivo avaliar a eficácia, por meio da análise de seus resultados pressóricos, da esclerectomia profunda não penetrante para tratamento cirúrgico do glaucoma primário de ângulo aberto. MÉTODOS: Estudo retrospectivo de 104 olhos operados pela técnica de esclerectomia profunda não penetrante de 1999 a 2002. Nos casos em que havia risco para falência da bolsa filtrante (idade inferior a 45 anos, negros, cirurgia ocular prévia a mitomicina C foi utilizada. A análise dos resultados foi feita avaliando-se a pressão intra-ocular final. A taxa de sucesso foi calculada para toda a população e separando os grupos com e sem utilização de mitomicina C. RESULTADO: Para uma pressão intra-ocular pré-operatória média de 22,57±4,92 mmHg, os autores encontraram uma pressão intra-ocular pós-operatória média de 14,22±2,89 mmHg com tempo médio de acompanhamento de 19,4 meses. A mitomicina C foi utilizada em 80 olhos. O sucesso absoluto (pressão PURPOSE: The aim of this study is to assess the efficacy, of the non-penetrating procedure for surgical treatment of primary open-angle glaucoma, by the analysis of its tensional results. METHODS: Retrospective study of 104 eyes with primary open-angle glaucoma submitted to a non-penetrating deep sclerectomy from 1999 to 2002. Mitomycin C was used in cases with high risk for bleb failure, such as, age under 45 years, blacks, previous ocular surgery. Final mean intraocular pressure was observed and success rate was calculated for the whole population and for each group (with and without mitomycin C RESULTS: For a mean preoperative intraocular pressure of 22.57±4.92 mmHg, the authors found a mean final intraocular pressure of 14.22±2.89 mmHg. Mitomycin C was used in 80 eyes. Absolute success (intraocular pressure <18mmHg without medication for the entire group was 82.7%, with a follow-up of 19.4 months on average. Success rate after 3 years of follow-up, by

  9. Hydrocarbon accumulation in deep fluid modified carbonate rock in the Tarim Basin

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    The activities of deep fluid are regionalized in the Tarim Basin. By analyzing the REE in core samples and crude oil, carbon isotope of carbon dioxide and inclusion temperature measurement in the west of the Tazhong Uplift in the western Tarim Basin, all the evidence confirms the existence of deep fluid. The deep fluid below the basin floor moved up into the basin through discordogenic fauit and volcanicity to cause corrosion and metaaomatosis of carbonate rock by exchange of matter and energy. The pore structure and permeability of the carbonate reservoirs were improved, making the carbonate reservoirs an excellent type of deeply buried modification. The fluorite ore belts discovered along the large fault and the volcanic area in the west of the Tazhong Uplift are the outcome of deep fluid action. Such carbonate reservoirs are the main type of reservoirs in the Tazhong 45 oilfield. The carbonate reservoirs in well YM 7 are improved obviously by thermal fluid dolomitization. The origin and territory of deep fluid are associated with the discordogenic fault and volcanicity in the basin. The discordogenic fault and volcanic area may be the pointer of looking for the deep fluid modified reservoirs. The primary characteristics of hydrocarbon accumulation in deep fluid reconstructed carbonate rock are summarized as accumulation near the large fault and volcano passage, late-period hydrocarbon accumulation after volcanic activity, and subtle trap reservoirs controlled by lithology.

  10. Multiple limbal haemangiosarcomas in a border collie dog: management by lamellar keratectomy/sclerectomy and strontium-90 beta plesiotherapy.

    Science.gov (United States)

    Donaldson, D; Sansom, J; Murphy, S; Scase, T

    2006-09-01

    An eight-year-old, neutered, male border collie dog was presented with a six-week history of left ocular discomfort and a raised, red mass at the lateral limbus. The right eye had been enucleated approximately 12 months previously following suspected trauma when the eye had become red and painful. The mass was excised using superficial keratectomy/sclerectomy and the surgery site was treated with strontium-90 beta radiation. Histopathological findings were consistent with a diagnosis of haemangiosarcoma. Immunohistochemical staining showed uniform expression of CD31 in neoplastic cells, confirming their endothelial origin. Two further treatments with strontium-90 beta radiation were applied to the surgical site at weekly intervals. Twenty-six weeks after surgery, a second, raised, red limbal mass became apparent at the medial limbus of the left eye. Surgical excision and adjuvant strontium-90 beta plesiotherapy were performed as described for the initial tumour. Routine histopathological analysis confirmed haemangiosarcoma at this site. Eighty-six weeks following the initial presentation, no recurrence of ocular haemangiosarcoma was evident.

  11. Image-guided modified deep anterior lamellar keratoplasty (DALK) corneal transplant using intraoperative optical coherence tomography

    Science.gov (United States)

    Tao, Yuankai K.; LaBarbera, Michael; Ehlers, Justis P.; Srivastava, Sunil K.; Dupps, William J.

    2015-03-01

    Deep anterior lamellar keratoplasty (DALK) is an alternative to full-thickness corneal transplant and has advantages including the absence of allograft rejection; shortened duration of topical corticosteroid treatment and reduced associated risk of glaucoma, cataract, or infection; and enables use of grafts with poor endothelial quality. DALK begins by performing a trephination of approximately 80% stromal thickness, as measured by pachymetry. After removal of the anterior stoma, a needle is inserted into the residual stroma to inject air or viscoelastic to dissect Descemet's membrane. These procedures are inherently difficult and intraoperative rates of Descemet's membrane perforation between 4-39% have been reported. Optical coherence tomography (OCT) provides high-resolution images of tissue microstructures in the cornea, including Descemet's membrane, and allows quantitation of corneal layer thicknesses. Here, we use crosssectional intraoperative OCT (iOCT) measurements of corneal thickness during surgery and a novel micrometeradjustable biopsy punch to precision-cut the stroma down to Descemet's membrane. Our prototype cutting tool allows us to establish a dissection plane at the corneal endothelium interface, mitigates variability in cut-depths as a result of tremor, reduces procedure complexity, and reduces complication rates. iOCT-guided modified DALK procedures were performed on 47 cadaveric porcine eyes by non-experts and achieved a perforation rate of ~5% with a mean corneal dissection time care.

  12. Design of a Small Modified Minkowski Fractal Antenna for Passive Deep Brain Stimulation Implants

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    Sara Manafi

    2014-01-01

    Full Text Available A small planar modified Minkowski fractal antenna is designed and simulated in dual frequency bands (2.4 and 5.8 GHz for wireless energy harvesting by deep brain stimulation (DBS devices. The designed antenna, physically being confined inside a miniaturized structure, can efficiently convert the wireless signals in dual ISM frequency bands to the energy source to recharge the DBS battery or power the pulse generator directly. The performance metrics such as the return loss, the specific absorption rate (SAR, and the radiation pattern within skin and muscle-fat-skin tissues are evaluated for the designed antenna. The gain of the proposed antenna is 3.2 dBi at 2.4 GHz and 4.7 dBi at 5.8 GHz; also the averaged SAR of the antenna in human body tissue is found to be well below the legally allowed limit at both frequency bands. The link budget shows the received power at the distance of 25 cm at 2.4 GHz and 5.8 GHz are around 0.4 mW and 0.04 mW, which can empower the DBS implant. The large operational bandwidth, the physical compactness, and the efficiency in wireless signal reception make this antenna suitable in being used in implanted biomedical devices such as DBS pulse generators.

  13. Tensional results of non-penetrating deep sclerectomy in the treatment of primary open-angle glaucoma

    OpenAIRE

    Guedes, Ricardo Augusto Paletta; Guedes, Vanessa Maria Paletta

    2004-01-01

    OBJETIVO: O presente estudo tem como objetivo avaliar a eficácia, por meio da análise de seus resultados pressóricos, da esclerectomia profunda não penetrante para tratamento cirúrgico do glaucoma primário de ângulo aberto. MÉTODOS: Estudo retrospectivo de 104 olhos operados pela técnica de esclerectomia profunda não penetrante de 1999 a 2002. Nos casos em que havia risco para falência da bolsa filtrante (idade inferior a 45 anos, negros, cirurgia ocular prévia) a mitomicina C foi utilizada. ...

  14. Efficiency analyses of the CANDU spent fuel repository using modified disposal canisters for a deep geological disposal system design

    International Nuclear Information System (INIS)

    Lee, J.Y.; Cho, D.K.; Lee, M.S.; Kook, D.H.; Choi, H.J.; Choi, J.W.; Wang, L.M.

    2012-01-01

    Highlights: ► A reference disposal concept for spent nuclear fuels in Korea has been reviewed. ► To enhance the disposal efficiency, alternative disposal concepts were developed. ► Thermal analyses for alternative disposal concepts were performed. ► From the result of the analyses, the disposal efficiency of the concepts was reviewed. ► The most effective concept was suggested. - Abstract: Deep geological disposal concept is considered to be the most preferable for isolating high-level radioactive waste (HLW), including nuclear spent fuels, from the biosphere in a safe manner. The purpose of deep geological disposal of HLW is to isolate radioactive waste and to inhibit its release of for a long time, so that its toxicity does not affect the human beings and the biosphere. One of the most important requirements of HLW repository design for a deep geological disposal system is to keep the buffer temperature below 100 °C in order to maintain the integrity of the engineered barrier system. In this study, a reference disposal concept for spent nuclear fuels in Korea has been reviewed, and based on this concept, efficient alternative concepts that consider modified CANDU spent fuels disposal canister, were developed. To meet the thermal requirement of the disposal system, the spacing of the disposal tunnels and that of the disposal pits for each alternative concept, were drawn following heat transfer analyses. From the result of the thermal analyses, the disposal efficiency of the alternative concepts was reviewed and the most effective concept suggested. The results of these analyses can be used for a deep geological repository design and detailed analyses, based on exact site characteristics data, will reduce the uncertainty of the results.

  15. Dynamic Analysis of Thick Plates Including Deep Beams on Elastic Foundations Using Modified Vlasov Model

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    Korhan Ozgan

    2013-01-01

    Full Text Available Dynamic analysis of foundation plate-beam systems with transverse shear deformation is presented using modified Vlasov foundation model. Finite element formulation of the problem is derived by using an 8-node (PBQ8 finite element based on Mindlin plate theory for the plate and a 2-node Hughes element based on Timoshenko beam theory for the beam. Selective reduced integration technique is used to avoid shear locking problem for the evaluation of the stiffness matrices for both the elements. The effect of beam thickness, the aspect ratio of the plate and subsoil depth on the response of plate-beam-soil system is analyzed. Numerical examples show that the displacement, bending moments and shear forces are changed significantly by adding the beams.

  16. Modified big-bubble technique compared to manual dissection deep anterior lamellar keratoplasty in the treatment of keratoconus.

    Science.gov (United States)

    Knutsson, Karl Anders; Rama, Paolo; Paganoni, Giorgio

    2015-08-01

    To evaluate the clinical findings and results of manual dissection deep anterior lamellar keratoplasty (DALK) compared to a modified big-bubble DALK technique in eyes affected by keratoconus. Sixty eyes of 60 patients with keratoconus were treated with one of the two surgical techniques manual DALK (n = 30); big-bubble DALK (n = 30). The main outcomes measured were visual acuity, corneal topographic parameters, thickness of residual stroma and endothelial cell density (ECD). Patients were examined postoperatively at 1 month, 6 months, 1 year and 1 month after suture removal. Final best spectacle-corrected visual acuity (BSCVA) measured 1 month after suture removal was 0.11 ± 0.08 LogMAR in the big-bubble group compared to 0.13 ± 0.08 in the manual DALK group (p = 0.227). In patients treated with the big-bubble technique without complications (Descemet's membrane completely bared), the stromal residue was not measureable. Mean stromal residual thickness in the manual DALK group was 30.50 ± 27.60 μm. Data analysis of the manual DALK group demonstrated a significant correlation between BSCVA and residual stromal thickness; lower residual stromal thickness correlated with better BSCVA values (Spearman ρ = 0.509, p = 0.018). Postoperative ECD was similar in both groups at all intervals, with no statistically significant differences. In both groups, ECD loss was only significant during the 1- to 6-month interval (p = 0.001 and p big-bubble DALK and manual DALK groups, respectively). Manual DALK provides comparable results to big-bubble DALK. Big-bubble DALK permits faster visual recovery and is a surgical technique, which can be easily converted to manual DALK in cases of unsuccessful 'big-bubble' formation. © 2015 Acta Ophthalmologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

  17. Magnetic graphene oxide modified with choline chloride-based deep eutectic solvent for the solid-phase extraction of protein

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Yanhua; Wang, Yuzhi, E-mail: wyzss@hnu.edu.cn; Pan, Qi; Wang, Ying; Ding, Xueqin; Xu, Kaijia; Li, Na; Wen, Qian

    2015-06-02

    Highlights: • A strategy for extraction of protein based on DES-coated magnetic graphene oxide. • The deep eutectic solvents were based on choline chloride. • Bovine serum albumin was used as the analyte. • The material prepared works for the acidic but not the basic or the neutral proteins. - Abstract: Four kinds of green deep eutectic solvents (DESs) based on choline chloride (ChCl) have been synthesized and coated on the surface of magnetic graphene oxide (Fe{sub 3}O{sub 4}@GO) to form Fe{sub 3}O{sub 4}@GO-DES for the magnetic solid-phase extraction of protein. X-ray diffraction (XRD), vibrating sample magnetometer (VSM), Fourier transform infrared spectrometry (FTIR), field emission scanning electron microscopy (FESEM) and thermal gravimetric analysis (TGA) were employed to characterize Fe{sub 3}O{sub 4}@GO-DES, and the results indicated the successful preparation of Fe{sub 3}O{sub 4}@GO-DES. The UV–vis spectrophotometer was used to measure the concentration of protein after extraction. Single factor experiments proved that the extraction amount was influenced by the types of DESs, solution temperature, solution ionic strength, extraction time, protein concentration and the amount of Fe{sub 3}O{sub 4}@GO-DES. Comparison of Fe{sub 3}O{sub 4}@GO and Fe{sub 3}O{sub 4}@GO-DES was carried out by extracting bovine serum albumin, ovalbumin, bovine hemoglobin and lysozyme. The experimental results showed that the proposed Fe{sub 3}O{sub 4}@GO-DES performs better than Fe{sub 3}O{sub 4}@GO in the extraction of acidic protein. Desorption of protein was carried out by eluting the solid extractant with 0.005 mol L{sup −1} Na{sub 2}HPO{sub 4} contained 1 mol L{sup −1} NaCl. The obtained elution efficiency was about 90.9%. Attributed to the convenient magnetic separation, the solid extractant could be easily recycled.

  18. Compositional Bias in Naïve and Chemically-modified Phage-Displayed Libraries uncovered by Paired-end Deep Sequencing.

    Science.gov (United States)

    He, Bifang; Tjhung, Katrina F; Bennett, Nicholas J; Chou, Ying; Rau, Andrea; Huang, Jian; Derda, Ratmir

    2018-01-19

    Understanding the composition of a genetically-encoded (GE) library is instrumental to the success of ligand discovery. In this manuscript, we investigate the bias in GE-libraries of linear, macrocyclic and chemically post-translationally modified (cPTM) tetrapeptides displayed on the M13KE platform, which are produced via trinucleotide cassette synthesis (19 codons) and NNK-randomized codon. Differential enrichment of synthetic DNA {S}, ligated vector {L} (extension and ligation of synthetic DNA into the vector), naïve libraries {N} (transformation of the ligated vector into the bacteria followed by expression of the library for 4.5 hours to yield a "naïve" library), and libraries chemically modified by aldehyde ligation and cysteine macrocyclization {M} characterized by paired-end deep sequencing, detected a significant drop in diversity in {L} → {N}, but only a minor compositional difference in {S} → {L} and {N} → {M}. Libraries expressed at the N-terminus of phage protein pIII censored positively charged amino acids Arg and Lys; libraries expressed between pIII domains N1 and N2 overcame Arg/Lys-censorship but introduced new bias towards Gly and Ser. Interrogation of biases arising from cPTM by aldehyde ligation and cysteine macrocyclization unveiled censorship of sequences with Ser/Phe. Analogous analysis can be used to explore library diversity in new display platforms and optimize cPTM of these libraries.

  19. Graphene and graphene oxide modified by deep eutectic solvents and ionic liquids supported on silica as adsorbents for solid-phase extraction

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Xiaoqin; Li, Guizhen; Row, Kyung Ho [Dept. of Chemistry and Chemical Engineering, Inha University, Incheon (Korea, Republic of)

    2017-02-15

    A novel deep eutectic solvent (DES) and ionic liquid (IL)-modified graphene (G) and graphene oxide (GO) were synthesized and used as effective adsorbents for the preconcentration of three chlorophenols (CPs), 4-chlorophenol (4-CP), 2,4-dichlorophenol (2,4-DCP), and 2,4,6-trichlorophenol (2,4,6-TCP), in environmental water samples prior to high-performance liquid chromatography (HPLC). The new materials were characterized by scanning electron microscopy (S-4200) and Fourier-transform infrared spectrometry. The prepared functionalized GO@silica shows remarkable adsorption capacity toward CPs. When used as solid-phase extraction (SPE) sorbents, a superior recovery (88.49–89.70%) could be obtained compared to commercial sorbents, such as silica and aminosilica. Based on this, a method for the analysis of CPs in water samples was established by coupling SPE with HPLC. These results highlight the potential new role of DES and IL-modified GO in the preparation of analytical samples.

  20. Magnetic graphene oxide modified with choline chloride-based deep eutectic solvent for the solid-phase extraction of protein.

    Science.gov (United States)

    Huang, Yanhua; Wang, Yuzhi; Pan, Qi; Wang, Ying; Ding, Xueqin; Xu, Kaijia; Li, Na; Wen, Qian

    2015-06-02

    Four kinds of green deep eutectic solvents (DESs) based on choline chloride (ChCl) have been synthesized and coated on the surface of magnetic graphene oxide (Fe3O4@GO) to form Fe3O4@GO-DES for the magnetic solid-phase extraction of protein. X-ray diffraction (XRD), vibrating sample magnetometer (VSM), Fourier transform infrared spectrometry (FTIR), field emission scanning electron microscopy (FESEM) and thermal gravimetric analysis (TGA) were employed to characterize Fe3O4@GO-DES, and the results indicated the successful preparation of Fe3O4@GO-DES. The UV-vis spectrophotometer was used to measure the concentration of protein after extraction. Single factor experiments proved that the extraction amount was influenced by the types of DESs, solution temperature, solution ionic strength, extraction time, protein concentration and the amount of Fe3O4@GO-DES. Comparison of Fe3O4@GO and Fe3O4@GO-DES was carried out by extracting bovine serum albumin, ovalbumin, bovine hemoglobin and lysozyme. The experimental results showed that the proposed Fe3O4@GO-DES performs better than Fe3O4@GO in the extraction of acidic protein. Desorption of protein was carried out by eluting the solid extractant with 0.005 mol L(-1) Na2HPO4 contained 1 mol L(-1) NaCl. The obtained elution efficiency was about 90.9%. Attributed to the convenient magnetic separation, the solid extractant could be easily recycled. Copyright © 2015 Elsevier B.V. All rights reserved.

  1. La modified TiO{sub 2} photoanode and its effect on DSSC performance: A comparative study of doping and surface treatment on deep and surface charge trapping

    Energy Technology Data Exchange (ETDEWEB)

    Ako, Rajour Tanyi [Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, BE1410, Negara Brunei Darussalam (Brunei Darussalam); Ekanayake, Piyasiri, E-mail: piyasiri.ekanayake@ubd.edu.bn [Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, BE1410, Negara Brunei Darussalam (Brunei Darussalam); Centre for Advanced Material and Energy Sciences (CAMES), Universiti Brunei Darussalam, Jalan Tungku Link, BE1410, Negara Brunei Darussalam (Brunei Darussalam); Tan, Ai Ling [Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, BE1410, Negara Brunei Darussalam (Brunei Darussalam); Young, David James [Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, BE1410, Negara Brunei Darussalam (Brunei Darussalam); Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Maroochydore DC, Queensland, 4558 (Australia); Institute of Materials Research and Engineering (IMRE), Agency for Science, Technology and Research - A*STAR, #08-03, 2 Fusionopolis Way, Innovis, 138634 (Singapore)

    2016-04-01

    The effect of Lanthanum ions (La{sup 3+}) on charge trapping in dye-sensitized solar cell (DSSC) photoanodes has been investigated with doped and surface-treated TiO{sub 2} nanoparticles. Doped nanoparticles consisting of 0.5 mol.% Mg and La co-doped TiO{sub 2}, 0.5 mol.% Mg doped TiO{sub 2} and pure TiO{sub 2} were synthesized by the sol gel method. Surface-treated nanoparticles of Mg doped TiO{sub 2} and pure TiO{sub 2} were prepared by ball milling in 0.05 M aqueous La{sup 3+} solution. All materials were analyzed by XRD, XPS and UV–Vis DRS. Cell performance, surface free energy state changes and electron injection efficiency of DSSCs based on these nanoparticles were evaluated using current –voltage measurements, EIS and Incident photon to current conversion efficiency. Doped materials had La and Mg ions incorporated into the TiO{sub 2} lattice, while no lattice changes were observed for the surface-treated materials. Less visible light was absorbed by treated oxides compared with doped oxide samples. The overall power conversion efficiencies (PCE) of DSSC photoanodes based on doped materials were twice those of photoanodes fabricated from treated nanoparticles. Doping establishes deep traps that reduce the recombination of electron–hole (e–h) pairs. Conversely, the presence of absorbed oxygen in treated materials enhances e–h recombination with electrolyte at surface trap sites. - Highlights: • DSSC performance is investigated using photoanodes of doped and La{sup 3+} surface treated TiO{sub 2}. • TiO{sub 2} and Mg–TiO{sub 2} treated with La{sup 3+} absorbed less visible light. • A high concentration of absorbed oxygen on surface treated oxides reduced band bending. • Increased surface free energy in the modified DSSC anodes is caused more by Mg{sup 2+} at Ti{sup 4+} than by La{sup 3+} at the surfaces. • Near surface charge traps due to La{sup 3+} treatment promotes e–h recombination.

  2. Transforniceal Lateral Deep Bone Decompression—A Modified Technique to Prevent Postoperative Diplopia in Patients with Disfiguring Exophthalmos Due to Dysthyroid Orbitopathy

    Directory of Open Access Journals (Sweden)

    Shu-Lang Liao

    2006-01-01

    Conclusion: Transforniceal lateral deep bone decompression produces less new-onset, persistent diplopia than traditional inferomedial wall decompression, and provides good cosmesis by using a hidden small incisional wound. This approach appears to be a safe and effective procedure for patients with disfiguring exophthalmos, especially for Asian patients without crease fold.

  3. Magnetic molecularly imprinted polymers based on silica modified by deep eutectic solvents for the rapid simultaneous magnetic-based solid-phase extraction of Salvia miltiorrhiza bunge, Glycine max (Linn.) Merr and green tea.

    Science.gov (United States)

    Li, Guizhen; Wang, Xiaoqin; Row, Kyung Ho

    2018-04-01

    Novel magnetic molecularly imprinted polymers (MMIPs) with multiple-template based on silica were modified by four types of deep eutectic solvents (DESs) for the rapid simultaneous magnetic solid-phase extraction (MSPE) of tanshinone Ⅰ, tanshinone ⅡA, and cryptotanshinone from Salvia miltiorrhiza bunge; glycitein, genistein, and daidzein from Glycine max (Linn.) Merr; and epicatechin, epigallocatechin gallate, and epicatechin gallate from green tea, respectively. The synthesized materials were characterized by Fourier transform infrared spectroscopy and field emission scanning electron microscopy. Single factor experiments were to explore the relationship between the extraction efficiency and four factors (the sample solution pH, amount of DESs for modification, amount of adsorbent, and extraction time). It was showed that the DES4-MMIPs have better extraction ability than the MMIPs without DESs and the other three DESs-modified MMIPs. The best extraction recoveries with DES4-MMIP were tanshinone Ⅰ (85.57%), tanshinone ⅡA (80.58%), cryptotanshinone (92.12%), glycitein (81.65%), genistein (87.72%), daidzein (92.24%), epicatechin (86.43%), epigallocatechin gallate (80.92%), and epicatechin gallate (93.64%), respectively. The novel multiple-template MMIPs materials modified by DES for the rapid simultaneous MSPE of active compounds were proved to reduce the experimental steps than single-template technique, and increase the extraction efficiency. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  4. 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...

  5. 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

  6. 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...

  7. Magnetic Solid-phase Extraction with Fe3O4/Molecularly Imprinted Polymers Modified by Deep Eutectic Solvents and Ionic Liquids for the Rapid Purification of Alkaloid Isomers (Theobromine and Theophylline from Green Tea

    Directory of Open Access Journals (Sweden)

    Guizhen Li

    2017-06-01

    Full Text Available Different kinds of deep eutectic solvents (DES based on choline chloride (ChCl and ionic liquids (ILs based on 1-methylimidazole were used to modify Fe3O4/molecularly imprinted polymers (Fe3O4/MIPs, and the resulting materials were applied for the rapid purification of alkaloid isomers (theobromine and theophylline from green tea with magnetic solid-phase extraction (M-SPE. The M-SPE procedure was optimized using the response surface methodology (RSM to analyze the maximum conditions. The materials were characterized by Fourier transform infrared spectroscopy (FI-IR and field emission scanning electron microscopy (FE-SEM. Compared to the ILs-Fe3O4/MIPs, the DESs-Fe3O4/MIPs were developed for the stronger recognition and higher recoveries of the isomers (theophylline and theobromine from green tea, particularly DES-7-Fe3O4/MIPs. With RSM, the optimal recovery condition for theobromine and theophylline in the M-SPE were observed with ratio of methanol (80% as the washing solution, methanol/acetic acid (HAc (8:2 as the eluent at pH 3, and an eluent volume of 4 mL. The practical recoveries of theobromine and theophylline in green tea were 92.27% and 87.51%, respectively, with a corresponding actual extraction amount of 4.87 mg•g−1 and 5.07 mg•g−1. Overall, the proposed approach with the high affinity of Fe3O4/MIPs might offer a novel method for the purification of complex isomer samples.

  8. Magnetic Solid-phase Extraction with Fe₃O₄/Molecularly Imprinted Polymers Modified by Deep Eutectic Solvents and Ionic Liquids for the Rapid Purification of Alkaloid Isomers (Theobromine and Theophylline) from Green Tea.

    Science.gov (United States)

    Li, Guizhen; Wang, Xiaoqin; Row, Kyung Ho

    2017-06-25

    Different kinds of deep eutectic solvents (DES) based on choline chloride (ChCl) and ionic liquids (ILs) based on 1-methylimidazole were used to modify Fe3O4/molecularly imprinted polymers (Fe3O4/MIPs), and the resulting materials were applied for the rapid purification of alkaloid isomers (theobromine and theophylline) from green tea with magnetic solid-phase extraction (M-SPE). The M-SPE procedure was optimized using the response surface methodology (RSM) to analyze the maximum conditions. The materials were characterized by Fourier transform infrared spectroscopy (FI-IR) and field emission scanning electron microscopy (FE-SEM). Compared to the ILs-Fe3O4/MIPs, the DESs-Fe3O4/MIPs were developed for the stronger recognition and higher recoveries of the isomers (theophylline and theobromine) from green tea, particularly DES-7-Fe3O4/MIPs. With RSM, the optimal recovery condition for theobromine and theophylline in the M-SPE were observed with ratio of methanol (80%) as the washing solution, methanol/acetic acid (HAc) (8:2) as the eluent at pH 3, and an eluent volume of 4 mL. The practical recoveries of theobromine and theophylline in green tea were 92.27% and 87.51%, respectively, with a corresponding actual extraction amount of 4.87 mg•g-1 and 5.07 mg•g-1. Overall, the proposed approach with the high affinity of Fe3O4/MIPs might offer a novel method for the purification of complex isomer samples.

  9. 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....

  10. 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

  11. Modified cyanobacteria

    Science.gov (United States)

    Vermaas, Willem F J.

    2014-06-17

    Disclosed is a modified photoautotrophic bacterium comprising genes of interest that are modified in terms of their expression and/or coding region sequence, wherein modification of the genes of interest increases production of a desired product in the bacterium relative to the amount of the desired product production in a photoautotrophic bacterium that is not modified with respect to the genes of interest.

  12. 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.

  13. 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.

  14. 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...

  15. Modified SEAGULL

    Science.gov (United States)

    Salas, M. D.; Kuehn, M. S.

    1994-01-01

    Original version of program incorporated into program SRGULL (LEW-15093) for use on National Aero-Space Plane project, its duty being to model forebody, inlet, and nozzle portions of vehicle. However, real-gas chemistry effects in hypersonic flow fields limited accuracy of that version, because it assumed perfect-gas properties. As a result, SEAGULL modified according to real-gas equilibrium-chemistry methodology. This program analyzes two-dimensional, hypersonic flows of real gases. Modified version of SEAGULL maintains as much of original program as possible, and retains ability to execute original perfect-gas version.

  16. The deep cerebral stimulation of the under thalamic nucleus modifies the cerebral metabolism in {sup 18}FDG-Tep of obsessive compulsive patients; La stimulation cerebrale profonde du noyau sous thalamique modifie le metabolisme cerebral en 18FDG-TEP des patients obsessionnels compulsifs

    Energy Technology Data Exchange (ETDEWEB)

    Le Jeune, F.; Garin, E. [Service de medecine nucleaire, centre Eugene-Marquis, Rennes, (France); Verin, M.; Peron, J. [service de neurologie, CHU Pontchaillou, Rennes, (France); Mallet, L.; Yelnik, J. [Inserm, Avenir Team, Behavior, Emotion and Basal Ganglia, IFR 70, Pitie-Salpetriere, Paris, (France); Kreps, M.O. [Inserm U796, service de psychiatrie, hopital Sainte-Anne, Paris, (France); Drapier, D.; Millet, B. [service de psychiatrie adulte, centre hospitalier Guillaume-Regnier, Rennes, (France)

    2009-05-15

    The aim of this work was to find again this orbito-frontal hyper metabolism among the resistant obsessive compulsive disorder patients that are going to benefit of a deep cerebral stimulation of the under thalamus nucleus and to demonstrate that this new therapy approach leads a reduction of the metabolism in this area in correlation with the clinical improvement. It is about the first study realized in isotopic functional imaging on ten resistant compulsive disorder patients treated by bilateral deep cerebral stimulation of the under thalamus nucleus. It shows that the treatment efficiency is in relation with a reduction of the glucide metabolism in the right orbito-frontal cortex. It suggests equally that the under thalamus nucleus would be functionally linked to the orbito-frontal cortex. (N.C.)

  17. 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...

  18. Evaluating the Use of a Negative D-Dimer and Modified Low Wells Score in Excluding above Knee Deep Venous Thrombosis in an Outpatient Population, Assessing Need for Diagnostic Ultrasound

    International Nuclear Information System (INIS)

    Rahiminejad, Maryam; Rastogi, Anshul; Prabhudesai, Shirish; Mcclinton, David; MacCallum, Peter; Platton, Sean; Friedman, Emma

    2014-01-01

    Aims. Colour doppler ultrasonography (CDUS) is widely used in the diagnosis of deep venous thrombosis (DVT); however, the number of scans positive for above knee DVT is low. The present study evaluates the reliability of the D-dimer test combined with a clinical probability score (Wells score) in ruling out an above knee DVT and identifying patients who do not need a CDUS. Materials and Method. This study is a retrospective audit and reaudit of a total of 816 outpatients presenting with suspected lower limb DVT from March 2009 to March 2010 and from September 2011 to February 2012. Following the initial audit, a revised clinical diagnostic pathway was implemented. Results. In our initial audit, seven patients (4.9%) with a negative D-dimer and a low Wells score had a DVT. On review, all seven had a risk factor identified that was not included in the Wells score. No patient with negative D-dimer and low Wells score with no extra clinical risk factor had a DVT on CDUS (negative predictive value 100%). A reaudit confirmed adherence to our revised clinical diagnostic pathway. Conclusions. A negative D-dimer together with a low Wells score and no risk factors effectively excludes a lower limb DVT and an ultrasound is unnecessary in these patients

  19. 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)

  20. 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...

  1. Interfacial Modifiers

    Energy Technology Data Exchange (ETDEWEB)

    Martin, Ina; French, Roger H.

    2018-03-19

    Our project objective in the first and only Budget Period was to demonstrate the potential of nm-scale organofunctional silane coatings as a method of extending the lifetime of PV materials and devices. Specifically, the target was to double the lifetime performance of a laminated Cu(In,Ga)Se2 (CIGS) cell under real-world and accelerated aging exposure conditions. Key findings are that modification of aluminum-doped zinc oxide (AZO) films (materials used as transparent conductive oxide (TCO) top contacts) resulted in decreased degradation of optical and electrical properties under damp heat (DH) exposure compared to un-modified AZO. The most significant finding is that modification of the AZO top contact of full CIGS devices resulted in significantly improved properties under DH exposure compared to un-modified devices, by a factor of 4 after 1000 h. Results of this one-year project have demonstrated that surface functionalization is a viable pathway for extending the lifetime of state-of-the-art CIGS devices.

  2. 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.

  3. 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 ...

  4. 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 ...

  5. 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....

  6. Excess plutonium disposition: The deep borehole option

    International Nuclear Information System (INIS)

    Ferguson, K.L.

    1994-01-01

    This report reviews the current status of technologies required for the disposition of plutonium in Very Deep Holes (VDH). It is in response to a recent National Academy of Sciences (NAS) report which addressed the management of excess weapons plutonium and recommended three approaches to the ultimate disposition of excess plutonium: (1) fabrication and use as a fuel in existing or modified reactors in a once-through cycle, (2) vitrification with high-level radioactive waste for repository disposition, (3) burial in deep boreholes. As indicated in the NAS report, substantial effort would be required to address the broad range of issues related to deep bore-hole emplacement. Subjects reviewed in this report include geology and hydrology, design and engineering, safety and licensing, policy decisions that can impact the viability of the concept, and applicable international programs. Key technical areas that would require attention should decisions be made to further develop the borehole emplacement option are identified

  7. 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.

  8. 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 ...

  9. 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.

  10. Auditory processing during deep propofol sedation and recovery from unconsciousness

    OpenAIRE

    Koelsch, Stefan; Heinke, Wolfgang; Sammler, Daniela; Olthoff, Derk

    2006-01-01

    Objective Using evoked potentials, this study investigated effects of deep propofol sedation, and effects of recovery from unconsciousness, on the processing of auditory information with stimuli suited to elicit a physical MMN, and a (music-syntactic) ERAN. Methods Levels of sedation were assessed using the Bispectral Index (BIS) and the Modified Observer's Assessment of Alertness and Sedation Scale (MOAAS). EEG-measurements were performed during wakefulness, deep propofol sedation (MOAAS 2–3...

  11. 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

  12. 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...

  13. 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...

  14. 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.

  15. 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

  16. 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...

  17. 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.

  18. 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...

  19. 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....

  20. 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...

  1. 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.

  2. 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

  3. An interactive end-user software application for a deep-sea photographic database

    Digital Repository Service at National Institute of Oceanography (India)

    Jaisankar, S.; Sharma, R.

    . The software is the first of its kind in deep-sea applications and it also attempts to educate the user about deep-sea photography. The application software is developed by modifying established routines and by creating new routines to save the retrieved...

  4. 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

  5. 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.

  6. 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...

  7. 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

  8. 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.

  9. 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

  10. 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.

  11. 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…

  12. 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...

  13. [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.

  14. Characterization of modified clinoptilolite

    International Nuclear Information System (INIS)

    Novosad, J.; Jandl, J.; Woollins, J.D.

    1992-01-01

    Samples of clinoptilolite were modified using insoluble hexacyanoferrate from aqueous solution. The modified samples were characterized by elemental analysis, powder X-ray diffraction, solid state NMR and vibrational spectroscopy. The sorption properties of modified clinoptilolite were studied, too. Higher affinity for 137 Cs sorption in comparison with the natural clinoptilolite has been proved. (author) 5 refs.; 3 figs.; 2 tabs

  15. Deep Belief Networks for Electroencephalography: A Review of Recent Contributions and Future Outlooks.

    Science.gov (United States)

    Movahedi, Faezeh; Coyle, James L; Sejdic, Ervin

    2018-05-01

    Deep learning, a relatively new branch of machine learning, has been investigated for use in a variety of biomedical applications. Deep learning algorithms have been used to analyze different physiological signals and gain a better understanding of human physiology for automated diagnosis of abnormal conditions. In this paper, we provide an overview of deep learning approaches with a focus on deep belief networks in electroencephalography applications. We investigate the state-of-the-art algorithms for deep belief networks and then cover the application of these algorithms and their performances in electroencephalographic applications. We covered various applications of electroencephalography in medicine, including emotion recognition, sleep stage classification, and seizure detection, in order to understand how deep learning algorithms could be modified to better suit the tasks desired. This review is intended to provide researchers with a broad overview of the currently existing deep belief network methodology for electroencephalography signals, as well as to highlight potential challenges for future research.

  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 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.

  20. On Modified Bar recursion

    DEFF Research Database (Denmark)

    Oliva, Paulo Borges

    2002-01-01

    Modified bar recursion is a variant of Spector's bar recursion which can be used to give a realizability interpretation of the classical axiom of dependent choice. This realizability allows for the extraction of witnesses from proofs of forall-exists-formulas in classical analysis. In this talk I...... shall report on results regarding the relationship between modified and Spector's bar recursion. I shall also show that a seemingly weak form of modified bar recursion is as strong as "full" modified bar recursion in higher types....

  1. 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

  2. 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.)

  3. 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.)

  4. [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.

  5. 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

  6. 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...

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. Modified Allergens for Immunotherapy.

    Science.gov (United States)

    Satitsuksanoa, Pattraporn; Głobińska, Anna; Jansen, Kirstin; van de Veen, Willem; Akdis, Mübeccel

    2018-02-16

    During the past few decades, modified allergens have been developed for use in allergen-specific immunotherapy (AIT) with the aim to improve efficacy and reduce adverse effects. This review aims to provide an overview of the different types of modified allergens, their mechanism of action and their potential for improving AIT. In-depth research in the field of allergen modifications as well as the advance of recombinant DNA technology have paved the way for improved diagnosis and research on human allergic diseases. A wide range of structurally modified allergens has been generated including allergen peptides, chemically altered allergoids, adjuvant-coupled allergens, and nanoparticle-based allergy vaccines. These modified allergens show promise for the development of AIT regimens with improved safety and long-term efficacy. Certain modifications ensure reduced IgE reactivity and retained T cell reactivity, which facilities induction of immune tolerance to the allergen. To date, multiple clinical trials have been performed using modified allergens. Promising results were obtained for the modified cat, grass and birch pollen, and house dust mite allergens. The use of modified allergens holds promise for improving AIT efficacy and safety. There is however a need for larger clinical studies to reliably assess the added benefit for the patient of using modified allergens for AIT.

  12. 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...

  13. 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...

  14. 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.

  15. 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 ...

  16. 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

  17. 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

  18. Outcomes of the DeepWind Conceptual Design

    DEFF Research Database (Denmark)

    Schmidt Paulsen, Uwe; Borg, Michael; Aagaard Madsen, Helge

    2015-01-01

    DeepWind has been presented as a novel floating offshore wind turbine concept with cost reduction potentials. Twelve international partners developed a Darrieus type floating turbine with new materials and technologies for deep-sea offshore environment. This paper summarizes results of the 5 MW...... the Deepwind floating 1 kW demonstrator. The 5 MW simulation results, loading and performance are compared to the OC3-NREL 5 MW wind turbine. Finally the paper elaborates the conceptual design on cost modelling....... DeepWind conceptual design. The concept was evaluated at the Hywind test site, described on its few components, in particular on the modified Troposkien blade shape and airfoil design. The feasibility of upscaling from 5 MW to 20 MW is discussed, taking into account the results from testing...

  19. Modified Nance palatal button

    Directory of Open Access Journals (Sweden)

    Nitin Arora

    2015-01-01

    Full Text Available This paper describes modified Nance palatal button by which problems encountered in the palatal region around the acrylic button during space closure and molar distalization can be minimized.

  20. Modified microdissection electrocautery needle

    OpenAIRE

    Singh, Virendra; Kumar, Pramod

    2014-01-01

    Electrocautery is routinely used in surgical procedures. The commercially available microdissection electrocautery needles are costly. To overcome this disadvantage, we have modified monopolar electrocautery tip to function as well as commercially available systems.

  1. 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…

  2. Biological response modifiers

    Energy Technology Data Exchange (ETDEWEB)

    Weller, R.E.

    1991-10-01

    Much of what used to be called immunotherapy is now included in the term biological response modifiers. Biological response modifiers (BRMs) are defined as those agents or approaches that modify the relationship between the tumor and host by modifying the host's biological response to tumor cells with resultant therapeutic effects.'' Most of the early work with BRMs centered around observations of spontaneous tumor regression and the association of tumor regression with concurrent bacterial infections. The BRM can modify the host response in the following ways: Increase the host's antitumor responses through augmentation and/or restoration of effector mechanisms or mediators of the host's defense or decrease the deleterious component by the host's reaction; Increase the host's defenses by the administration of natural biologics (or the synthetic derivatives thereof) as effectors or mediators of an antitumor response; Augment the host's response to modified tumor cells or vaccines, which might stimulate a greater response by the host or increase tumor-cell sensitivity to an existing response; Decrease the transformation and/or increase differentiation (maturation) of tumor cells; or Increase the ability of the host to tolerate damage by cytotoxic modalities of cancer treatment.

  3. On the dragnosis of deep vein thrombosis

    International Nuclear Information System (INIS)

    Olsson, C.-G.

    1979-01-01

    Clinical and laboratory diagnostic methods were studied in 301 consecutive patients with suspected deep vein thrombosis (DVT). Unexpectedly, phlebography (the reference method) was found to cause DVT in estimated 48 % of patients without initial DVT. Using a new type of contrast medium, however, no thrombotic complications were found. - Neither clinical examination nor plethysmography were found to give reliable results. Using a modified technique for radioisotope detection, high sensitivity to DVT was found with the 125 I-fibrinogen uptake test (within 2 days) and a newly developed 99 Tcsup(m)-plasmin test (within one hour). Since both tests showed low specificity, they are reliable as screening tests to exclude DVT, but not as independent diagnostic methods. (author)

  4. 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.

  5. 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.

  6. 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...

  7. 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

  8. 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.

  9. Modified blank ammunition injuries.

    Science.gov (United States)

    Ogunc, Gokhan I; Ozer, M Tahir; Coskun, Kagan; Uzar, Ali Ihsan

    2009-12-15

    Blank firing weapons are designed only for discharging blank ammunition cartridges. Because they are cost-effective, are easily accessible and can be modified to live firearms plus their unclear legal situation in Turkish Law makes them very popular in Turkey. 2004 through 2008, a total of 1115 modified blank weapons were seized in Turkey. Blank firing weapons are easily modified by owners, making them suitable for discharging live firearm ammunition or modified blank ammunitions. Two common methods are used for modification of blank weapons. After the modification, these weapons can discharge the live ammunition. However, due to compositional durability problems with these types of weapons; the main trend is to use the modified blank ammunitions rather than live firearm ammunition fired from modified blank firing weapons. In this study, two types of modified blank weapons and two types of modified blank cartridges were tested on three different target models. Each of the models' shooting side was coated with 1.3+/-2 mm thickness chrome tanned cowhide as a skin simulant. The first model was only coated with skin simulant. The second model was coated with skin simulant and 100% cotton police shirt. The third model was coated with skin simulant and jean denim. After the literature evaluation four high risky anatomic locations (the neck area; the eyes; the thorax area and inguinal area) were pointed out for the steel and lead projectiles are discharged from the modified blank weapons especially in close range (0-50 cm). The target models were designed for these anatomic locations. For the target models six Transparent Ballistic Candle blocks (TCB) were prepared and divided into two test groups. The first group tests were performed with lead projectiles and second group with steel projectile. The shortest penetration depth (lead projectile: 4.358 cm; steel projectile 8.032 cm) was recorded in the skin simulant and jean denim coated block for both groups. In both groups

  10. Auditory processing during deep propofol sedation and recovery from unconsciousness.

    Science.gov (United States)

    Koelsch, Stefan; Heinke, Wolfgang; Sammler, Daniela; Olthoff, Derk

    2006-08-01

    Using evoked potentials, this study investigated effects of deep propofol sedation, and effects of recovery from unconsciousness, on the processing of auditory information with stimuli suited to elicit a physical MMN, and a (music-syntactic) ERAN. Levels of sedation were assessed using the Bispectral Index (BIS) and the Modified Observer's Assessment of Alertness and Sedation Scale (MOAAS). EEG-measurements were performed during wakefulness, deep propofol sedation (MOAAS 2-3, mean BIS=68), and a recovery period. Between deep sedation and recovery period, the infusion rate of propofol was increased to achieve unconsciousness (MOAAS 0-1, mean BIS=35); EEG measurements of recovery period were performed after subjects regained consciousness. During deep sedation, the physical MMN was markedly reduced, but still significant. No ERAN was observed in this level. A clear P3a was elicited during deep sedation by those deviants, which were task-relevant during the awake state. As soon as subjects regained consciousness during the recovery period, a normal MMN was elicited. By contrast, the P3a was absent in the recovery period, and the P3b was markedly reduced. Results indicate that the auditory sensory memory (as indexed by the physical MMN) is still active, although strongly reduced, during deep sedation (MOAAS 2-3). The presence of the P3a indicates that attention-related processes are still operating during this level. Processes of syntactic analysis appear to be abolished during deep sedation. After propofol-induced anesthesia, the auditory sensory memory appears to operate normal as soon as subjects regain consciousness, whereas the attention-related processes indexed by P3a and P3b are markedly impaired. Results inform about effects of sedative drugs on auditory and attention-related mechanisms. The findings are important because these mechanisms are prerequisites for auditory awareness, auditory learning and memory, as well as language perception during anesthesia.

  11. 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.

  12. 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.

  13. 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

  14. Modified nasolacrimal duct stenting

    International Nuclear Information System (INIS)

    Tian Min; Jin Mei; Chen Huanjun; Li Yi

    2008-01-01

    Objective: Traditional nasolacrimal duct stenting possesses some shortcoming including difficulty of pulling ball head guide wire from the nasal cavity with turbinate hypertrophy and nasal septal deviation. The new method of nose-oral tube track establishment can overcome the forementioned and increase the successful rate. Methods: 5 F catheter and arterial sheath were modified to be nasolacrimal duct stent delivery device respectively. Antegrade dacryocystography was taken firstly to display the obstructed site and followed by the modified protocol of inserting the guide wire through nasolacrimal duct and nasal cavity, and establishing the stent delivery track for retrograde stent placement. Results: 5 epiphora patients with failure implantation by traditional method were all succeeded through the modified stenting (100%). During 6-mouth follow-up, no serious complications and reocclusion occurred. Conclusion: The establishment of eye-nose-mouth-nose of external nasal guide wire track can improve the successful rate of nasolacrimal duct stenting. (authors)

  15. 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

  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. Normal modified stable processes

    DEFF Research Database (Denmark)

    Barndorff-Nielsen, Ole Eiler; Shephard, N.

    2002-01-01

    Gaussian (NGIG) laws. The wider framework thus established provides, in particular, for added flexibility in the modelling of the dynamics of financial time series, of importance especially as regards OU based stochastic volatility models for equities. In the special case of the tempered stable OU process......This paper discusses two classes of distributions, and stochastic processes derived from them: modified stable (MS) laws and normal modified stable (NMS) laws. This extends corresponding results for the generalised inverse Gaussian (GIG) and generalised hyperbolic (GH) or normal generalised inverse...

  18. 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...

  19. 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

  20. 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...

  1. 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 ...

  2. 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.

  3. EAMJ Modifiable 10.indd

    African Journals Online (AJOL)

    2010-02-02

    Feb 2, 2010 ... MODIFIABLE FACTORS ASSOCIATED WITH ACTIVE PULMONARY TUBERCULOSIS IN A KENYAN PRISON. A. S. Amwayi, MBChB, MSc., ... University of Agriculture and Technology, P.O. Box 62000- 0200, Nairobi, Kenya and E. M. Muchiri, MSc, PhD., Division ..... Diabetes and low BMI. 223452.81.

  4. Isotopically modified compounds

    International Nuclear Information System (INIS)

    Kuruc, J.

    2009-01-01

    In this chapter the nomenclature of isotopically modified compounds in Slovak language is described. This chapter consists of following parts: (1) Isotopically substituted compounds; (2) Specifically isotopically labelled compounds; (3) Selectively isotopically labelled compounds; (4) Non-selectively isotopically labelled compounds; (5) Isotopically deficient compounds.

  5. Modifiable Combining Functions

    OpenAIRE

    Cohen, Paul; Shafer, Glenn; Shenoy, Prakash P.

    2013-01-01

    Modifiable combining functions are a synthesis of two common approaches to combining evidence. They offer many of the advantages of these approaches and avoid some disadvantages. Because they facilitate the acquisition, representation, explanation, and modification of knowledge about combinations of evidence, they are proposed as a tool for knowledge engineers who build systems that reason under uncertainty, not as a normative theory of evidence.

  6. Modifying Cookbook Labs.

    Science.gov (United States)

    Clark, Robert, L.; Clough, Michael P.; Berg, Craig A.

    2000-01-01

    Modifies an extended lab activity from a cookbook approach for determining the percent mass of water in copper sulfate pentahydrate crystals to one which incorporates students' prior knowledge, engenders active mental struggling with prior knowledge and new experiences, and encourages metacognition. (Contains 12 references.) (ASK)

  7. 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.

  8. 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.

  9. Modified Faraday cup

    Science.gov (United States)

    Elmer, John W.; Teruya, Alan T.; O'Brien, Dennis W.

    1996-01-01

    A tomographic technique for measuring the current density distribution in electron beams using electron beam profile data acquired from a modified Faraday cup to create an image of the current density in high and low power beams. The modified Faraday cup includes a narrow slit and is rotated by a stepper motor and can be moved in the x, y and z directions. The beam is swept across the slit perpendicular thereto and controlled by deflection coils, and the slit rotated such that waveforms are taken every few degrees form 0.degree. to 360.degree. and the waveforms are recorded by a digitizing storage oscilloscope. Two-din-tensional and three-dimensional images of the current density distribution in the beam can be reconstructed by computer tomography from this information, providing quantitative information about the beam focus and alignment.

  10. Tip-modified Propellers

    DEFF Research Database (Denmark)

    Andersen, Poul

    1999-01-01

    The paper deals with tip-modified propellers and the methods which, over a period of two decades, have been applied to develop such propellers. The development is driven by the urge to increase the efficiency of propellers and can be seen as analogous to fitting end plates and winglets to aircraft...... propeller, have efficiency increases of a reasonable magnitude in both open-water and behind-ship conditions....

  11. Modified Firefly Algorithm

    Directory of Open Access Journals (Sweden)

    Surafel Luleseged Tilahun

    2012-01-01

    Full Text Available Firefly algorithm is one of the new metaheuristic algorithms for optimization problems. The algorithm is inspired by the flashing behavior of fireflies. In the algorithm, randomly generated solutions will be considered as fireflies, and brightness is assigned depending on their performance on the objective function. One of the rules used to construct the algorithm is, a firefly will be attracted to a brighter firefly, and if there is no brighter firefly, it will move randomly. In this paper we modify this random movement of the brighter firefly by generating random directions in order to determine the best direction in which the brightness increases. If such a direction is not generated, it will remain in its current position. Furthermore the assignment of attractiveness is modified in such a way that the effect of the objective function is magnified. From the simulation result it is shown that the modified firefly algorithm performs better than the standard one in finding the best solution with smaller CPU time.

  12. Genetically Modified Organisms

    Directory of Open Access Journals (Sweden)

    Claro Llaguno

    2001-06-01

    Full Text Available Recent reports have brought to public attention concerns about Bt corn and genetically modified organisms (GMO in general. The timing, it seems, is most appropriate considering two related developments early this year: the final approval of the Cartagena Protocol on Biosafety in Montreal on January 29, 2001, and the OECD Edinburgh Conference on GM food safety last February 28- March 1, 2001. The protocol makes clear that GMOs include all living modified organisms (LMO defined as "any living organism that possesses a novel combination of genetic material obtained through the use of modern biotechnology". This includes seeds, live fish, and other organisms intentionally obtained for release to the environment. It would seem that the common understanding about GMOs as referring to farm-to-table products is perforce expanded to embrace genetically modified farm animals and aquatic resources. Being a trade agreement, the Montreal accord primarily deals with the safety issues related to the transboundary movement of LMOs around the globe. The OECD conference on the other hand, called for an international body "to address all sides of the GM debate" in response to the public outcry, particularly in Western Europe, regarding the risks the new products pose to human health and the environment. Some points of contention, which remain unresolved, include issues such as whether countries should be allowed to develop their own GM food based on their needs, and whether a global moratorium on GMOs and mandatory labeling should be enforced worldwide.

  13. 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...

  14. 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...

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Deep brain stimulation for phantom limb pain.

    Science.gov (United States)

    Bittar, Richard G; Otero, Sofia; Carter, Helen; Aziz, Tipu Z

    2005-05-01

    Phantom limb pain is an often severe and debilitating phenomenon that has been reported in up to 85% of amputees. Its pathophysiology is poorly understood. Peripheral and spinal mechanisms are thought to play a role in pain modulation in affected individuals; however central mechanisms are also likely to be of importance. The neuromatrix theory postulates a genetically determined representation of body image, which is modified by sensory input to create a neurosignature. Persistence of the neurosignature may be responsible for painless phantom limb sensations, whereas phantom limb pain may be due to abnormal reorganisation within the neuromatrix. This study assessed the clinical outcome of deep brain stimulation of the periventricular grey matter and somatosensory thalamus for the relief of chronic neuropathic pain associated with phantom limb in three patients. These patients were assessed preoperatively and at 3 month intervals postoperatively. Self-rated visual analogue scale pain scores assessed pain intensity, and the McGill Pain Questionnaire assessed the quality of the pain. Quality of life was assessed using the EUROQOL EQ-5D scale. Periventricular gray stimulation alone was optimal in two patients, whilst a combination of periventricular gray and thalamic stimulation produced the greatest degree of relief in one patient. At follow-up (mean 13.3 months) the intensity of pain was reduced by 62% (range 55-70%). In all three patients, the burning component of the pain was completely alleviated. Opiate intake was reduced in the two patients requiring morphine sulphate pre-operatively. Quality of life measures indicated a statistically significant improvement. This data supports the role for deep brain stimulation in patients with phantom limb pain. The medical literature relating to the epidemiology, pathogenesis, and treatment of this clinical entity is reviewed in detail.

  20. 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.

  1. 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.

  2. 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

  3. Putting the Deep Biosphere on the Map for Oceanography Courses: Gas Hydrates As a Case Study for the Deep Biosphere

    Science.gov (United States)

    Sikorski, J. J.; Briggs, B. R.

    2014-12-01

    The ocean is essential for life on our planet. It covers 71% of the Earth's surface, is the source of the water we drink, the air we breathe, and the food we eat. Yet, the exponential growth in human population is putting the ocean and thus life on our planet at risk. However, based on student evaluations from our introductory oceanography course it is clear that our students have deficiencies in ocean literacy that impact their ability to recognize that the ocean and humans are inextricably connected. Furthermore, life present in deep subsurface marine environments is also interconnected to the study of the ocean, yet the deep biosphere is not typically covered in undergraduate oceanography courses. In an effort to improve student ocean literacy we developed an instructional module on the deep biosphere focused on gas hydrate deposits. Specifically, our module utilizes Google Earth and cutting edge research about microbial life in the ocean to support three inquiry-based activities that each explore different facets of gas hydrates (i.e. environmental controls, biologic controls, and societal implications). The relevant nature of the proposed module also makes it possible for instructors of introductory geology courses to modify module components to discuss related topics, such as climate, energy, and geologic hazards. This work, which will be available online as a free download, is a solid contribution toward increasing the available teaching resources focused on the deep biosphere for geoscience educators.

  4. 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.

  5. 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.

  6. Deep learning and data assimilation for real-time production prediction in natural gas wells

    NARCIS (Netherlands)

    Loh, K.K.L.; Shoeibi Omrani, P.S.; Linden, R.J.P. van der

    2018-01-01

    The prediction of the gas production from mature gas wells, due to their complex end-of-life behavior, is challenging and crucial for operational decision making. In this paper, we apply a modified deep LSTM model for prediction of the gas flow rates in mature gas wells, including the uncertainties

  7. 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.

  8. Modified harmony search

    Science.gov (United States)

    Mohamed, Najihah; Lutfi Amri Ramli, Ahmad; Majid, Ahmad Abd; Piah, Abd Rahni Mt

    2017-09-01

    A metaheuristic algorithm, called Harmony Search is quite highly applied in optimizing parameters in many areas. HS is a derivative-free real parameter optimization algorithm, and draws an inspiration from the musical improvisation process of searching for a perfect state of harmony. Propose in this paper Modified Harmony Search for solving optimization problems, which employs a concept from genetic algorithm method and particle swarm optimization for generating new solution vectors that enhances the performance of HS algorithm. The performances of MHS and HS are investigated on ten benchmark optimization problems in order to make a comparison to reflect the efficiency of the MHS in terms of final accuracy, convergence speed and robustness.

  9. Modified puestow lateral pancreaticojejunostomy.

    Science.gov (United States)

    Ceppa, Eugene P; Pappas, Theodore N

    2009-05-01

    There are various surgical options for the treatment of pain associated with chronic pancreatitis. The modified Puestow lateral pancreaticojejunostomy has been proven to be effective in ameliorating symptoms and expediting return to normal lifestyle while maintaining a low rate of morbidity and mortality. However, the debate regarding which surgical treatment provides the best outcomes is controversial. The aims of this manuscript are to identify the patient population for which the Puestow benefits the most and discuss the pertinent technical aspects of the surgical procedure.

  10. [A modified technique of liposuction with excision for gynecomastia].

    Science.gov (United States)

    Yang, Hong-Yan; Xu, Jun; Yan, Xiao-Qing; You, Lei

    2007-11-20

    To introduce a modified technique of liposuction with excision for gynecomastia. From 2003 to 2007, 32 cases of gynecomastia were treated with the modified technique: the operative region was divided into central and periphery parts, liposuction was performed only in the periphery part and the deep layer of the central part, while the breast gland in the superficial layer of the central part underwent sharp dissection, the subcutaneous tissue of the central part was conserved, and blood supply was reserved and saucer deformity was avoided. Follow-up was conducted for 3.0 - 18.5 months. Normal men breast appearance was achieved. No complication happened such as hematoma, seroma, saucer deformity, and necrosis in nipple and areola. This modified operative technique for gynecomastia proves to be an excellent and effective technique.

  11. 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...

  12. 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 ...

  13. 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.

  14. 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.

  15. 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)

  16. 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,

  17. 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,

  18. 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

  19. 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.

  20. 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.

  1. 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…

  2. 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...

  3. 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.

  4. Figure-Ground Organization Emerges in a Deep Net with a Feedback Loop

    OpenAIRE

    Zipser, Karl

    2015-01-01

    We used a deep net to model how object-specific activation at the high levels of a hierarchical neural network could be fed back to modify representations at lower levels. We first identified a subset of nodes in the uppermost hidden layer that were preferentially activated by images of people. We then ran a procedure to recursively modify an image so as to increase activation of the 'person-selective' nodes. The image was modified by choosing a rectangular region (of random size and position...

  5. Deep Joint Rain Detection and Removal from a Single Image

    OpenAIRE

    Yang, Wenhan; Tan, Robby T.; Feng, Jiashi; Liu, Jiaying; Guo, Zongming; Yan, Shuicheng

    2016-01-01

    In this paper, we address a rain removal problem from a single image, even in the presence of heavy rain and rain streak accumulation. Our core ideas lie in the new rain image models and a novel deep learning architecture. We first modify an existing model comprising a rain streak layer and a background layer, by adding a binary map that locates rain streak regions. Second, we create a new model consisting of a component representing rain streak accumulation (where individual streaks cannot b...

  6. Discovery deep space optical communications (DSOC) transceiver

    Science.gov (United States)

    Roberts, W. Thomas

    2017-02-01

    NASA's 22 cm diameter Deep Space Optical Communications (DSOC) Transceiver is designed to provide a bidirectional optical link between a spacecraft in the inner solar system and an Earth-based optical ground station. This design, optimized for operation across a wide range of illumination conditions, is focused on minimizing blinding from stray light, and providing reliable, accurate attitude information to point its narrow communication beam accurately to the future location of the ground terminal. Though our transceiver will transmit in the 1550 nm waveband and receive in the 1064 nm waveband, the system design relies heavily on reflective optical elements, extending flexibility to be modified for use at different wavebands. The design makes use of common path propagation among transmit, receive and pointing verification optical channels to maintain precise alignment among its components, and to naturally correct for element misalignment resulting from launch or thermal element perturbations. This paper presents the results of trade studies showing the evolution of the design, unique operational characteristics of the design, elements that help to maintain minimal stray light contamination, and preliminary results from development and initial testing of a functional aluminum test model.

  7. 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.

  8. Deep Brain Electrical Stimulation in Epilepsy

    Science.gov (United States)

    Rocha, Luisa L.

    2008-11-01

    The deep brain electrical stimulation has been used for the treatment of neurological disorders such as Parkinson's disease, chronic pain, depression and epilepsy. Studies carried out in human brain indicate that the application of high frequency electrical stimulation (HFS) at 130 Hz in limbic structures of patients with intractable temporal lobe epilepsy abolished clinical seizures and significantly decreased the number of interictal spikes at focus. The anticonvulsant effects of HFS seem to be more effective in patients with less severe epilepsy, an effect associated with a high GABA tissue content and a low rate of cell loss. In addition, experiments using models of epilepsy indicate that HFS (pulses of 60 μs width at 130 Hz at subthreshold current intensity) of specific brain areas avoids the acquisition of generalized seizures and enhances the postictal seizure suppression. HFS is also able to modify the status epilepticus. It is concluded that the effects of HFS may be a good strategy to reduce or avoid the epileptic activity.

  9. Obstetrical complications of endometriosis, particularly deep endometriosis.

    Science.gov (United States)

    Leone Roberti Maggiore, Umberto; Inversetti, Annalisa; Schimberni, Matteo; Viganò, Paola; Giorgione, Veronica; Candiani, Massimo

    2017-12-01

    Over the past few years, a new topic in the field of endometriosis has emerged: the potential impact of the disease on pregnancy outcomes. This review aims to summarize in detail the available evidence on the relationship between endometriosis, particularly deep endometriosis (DE), and obstetrical outcomes. Acute complications of DE, such as spontaneous hemoperitoneum, bowel perforation, and uterine rupture, may occur during pregnancy. Although these events represent life-threatening conditions, they are rare and unpredictable. Therefore, the current literature does not support any kind of prophylactic surgery before pregnancy to prevent such complications. Results on the impact of DE on obstetrical outcomes are debatable and characterized by several limitations, including small sample size, lack of adjustment for confounders, lack of adequate control subjects, and other methodologic flaws. For these reasons, it is not possible to draw conclusions on this topic. The strongest evidence shows that DE is associated with higher rates of placenta previa; for other obstetrical outcomes, such as miscarriage, intrauterine growth restriction, preterm birth and hypertensive disorders, results are controversial. Although it is unlikely that surgery of DE may modify the impact of the disease on the course of pregnancy, no study has yet investigated this issue. Copyright © 2017 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.

  10. 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...

  11. 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.

  12. 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...

  13. Bitumen based modified substance

    International Nuclear Information System (INIS)

    Kostolanyi, P.

    1987-01-01

    The necessary amounts of tetrahydrosilicic acid and methyl phenyl silicon oil are added to molten bitumen heated to temperatures of 50 to 200 degC. The mixture is thoroughly mixed and let to cool. The structure of the product comes close to gel and its properties (penetration, softening point, workability time, penetration index) may be changed in dependence on the amount of additions and on the time and temperature of heating. The advantage of the thus prepared modified material is its shorter workability time, its ability to bind materials with a certain water content, and its relatively low price. It may be used for fixing and storing low-and medium-level radioactive organic and thickened waste waters. (E.S.)

  14. Biodegradable modified Phba systems

    International Nuclear Information System (INIS)

    Aniscenko, L.; Dzenis, M.; Erkske, D.; Tupureina, V.; Savenkova, L.; Muizniece - Braslava, S.

    2004-01-01

    Compositions as well as production technology of ecologically sound biodegradable multicomponent polymer systems were developed. Our objective was to design some bio plastic based composites with required mechanical properties and biodegradability intended for use as biodegradable packaging. Significant characteristics required for food packaging such as barrier properties (water and oxygen permeability) and influence of γ-radiation on the structure and changes of main characteristics of some modified PHB matrices was evaluated. It was found that barrier properties were plasticizers chemical nature and sterilization with γ-radiation dependent and were comparable with corresponding values of typical polymeric packaging films. Low γ-radiation levels (25 kGy) can be recommended as an effective sterilization method of PHB based packaging materials. Purposely designed bio plastic packaging may provide an alternative to traditional synthetic packaging materials without reducing the comfort of the end-user due to specific qualities of PHB - biodegradability, Biocompatibility and hydrophobic nature

  15. Modified Clipped LMS Algorithm

    Directory of Open Access Journals (Sweden)

    Lotfizad Mojtaba

    2005-01-01

    Full Text Available Abstract A new algorithm is proposed for updating the weights of an adaptive filter. The proposed algorithm is a modification of an existing method, namely, the clipped LMS, and uses a three-level quantization ( scheme that involves the threshold clipping of the input signals in the filter weight update formula. Mathematical analysis shows the convergence of the filter weights to the optimum Wiener filter weights. Also, it can be proved that the proposed modified clipped LMS (MCLMS algorithm has better tracking than the LMS algorithm. In addition, this algorithm has reduced computational complexity relative to the unmodified one. By using a suitable threshold, it is possible to increase the tracking capability of the MCLMS algorithm compared to the LMS algorithm, but this causes slower convergence. Computer simulations confirm the mathematical analysis presented.

  16. Modified arthroscopic Brostrom procedure.

    Science.gov (United States)

    Lui, Tun Hing

    2015-09-01

    The open modified Brostrom anatomic repair technique is widely accepted as the reference standard for lateral ankle stabilization. However, there is high incidence of intra-articular pathologies associated with chronic lateral ankle instability which may not be addressed by an isolated open Brostrom procedure. Arthroscopic Brostrom procedure with suture anchor has been described for anatomic repair of chronic lateral ankle instability and management of intra-articular lesions. However, the complication rates seemed to be higher than open Brostrom procedure. Modification of the arthroscopic Brostrom procedure with the use of bone tunnel may reduce the risk of certain complications. Copyright © 2015 European Foot and Ankle Society. Published by Elsevier Ltd. All rights reserved.

  17. Modified circular velocity law

    Science.gov (United States)

    Djeghloul, Nazim

    2018-05-01

    A modified circular velocity law is presented for a test body orbiting around a spherically symmetric mass. This law exhibits a distance scale parameter and allows to recover both usual Newtonian behaviour for lower distances and a constant velocity limit at large scale. Application to the Galaxy predicts the known behaviour and also leads to a galactic mass in accordance with the measured visible stellar mass so that additional dark matter inside the Galaxy can be avoided. It is also shown that this circular velocity law can be embedded in a geometrical description of spacetime within the standard general relativity framework upon relaxing the usual asymptotic flatness condition. This formulation allows to redefine the introduced Newtonian scale limit in term of the central mass exclusively. Moreover, a satisfactory answer to the galactic escape speed problem can be provided indicating the possibility that one can also get rid of dark matter halo outside the Galaxy.

  18. 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...

  19. 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.

  20. Genetically modified foods and social concerns.

    Science.gov (United States)

    Maghari, Behrokh Mohajer; Ardekani, Ali M

    2011-07-01

    Biotechnology is providing us with a wide range of options for how we can use agricultural and commercial forestry lands. The cultivation of genetically modified (GM) crops on millions of hectares of lands and their injection into our food chain is a huge global genetic experiment involving all living beings. Considering the fast pace of new advances in production of genetically modified crops, consumers, farmers and policymakers worldwide are challenged to reach a consensus on a clear vision for the future of world food supply. The current food biotechnology debate illustrates the serious conflict between two groups: 1) Agri-biotech investors and their affiliated scientists who consider agricultural biotechnology as a solution to food shortage, the scarcity of environmental resources and weeds and pests infestations; and 2) independent scientists, environmentalists, farmers and consumers who warn that genetically modified food introduces new risks to food security, the environment and human health such as loss of biodiversity; the emergence of superweeds and superpests; the increase of antibiotic resistance, food allergies and other unintended effects. This article reviews major viewpoints which are currently debated in the food biotechnology sector in the world. It also lays the ground-work for deep debate on benefits and risks of Biotech-crops for human health, ecosystems and biodiversity. In this context, although some regulations exist, there is a need for continuous vigilance for all countries involved in producing genetically engineered food to follow the international scientific bio-safety testing guidelines containing reliable pre-release experiments and post-release track of transgenic plants to protect public health and avoid future environmental harm.

  1. 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...

  2. 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.

  3. 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...

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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...

  12. 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.

  13. 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.

  14. 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.

  15. 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

  16. 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

  17. Distinguishing modified gravity models

    International Nuclear Information System (INIS)

    Brax, Philippe; Davis, Anne-Christine

    2015-01-01

    Modified gravity models with screening in local environments appear in three different guises: chameleon, K-mouflage and Vainshtein mechanisms. We propose to look for differences between these classes of models by considering cosmological observations at low redshift. In particular, we analyse the redshift dependence of the fine structure constant and the proton to electron mass ratio in each of these scenarios. When the absorption lines belong to unscreened regions of space such as dwarf galaxies, a time variation would be present for chameleons. For both K-mouflage and Vainshtein mechanisms, the cosmological time variation of the scalar field is not suppressed in both unscreened and screened environments, therefore enhancing the variation of constants and their detection prospect. We also consider the time variation of the redshift of distant objects using their spectrocopic velocities. We find that models of the K-mouflage and Vainshtein types have very different spectroscopic velocities as a function of redshift and that their differences with the Λ-CDM template should be within reach of the future ELT-HIRES observations

  18. MODIFIED GYPSUM BINDER

    Directory of Open Access Journals (Sweden)

    KONDRATEVA N. V.

    2017-02-01

    Full Text Available Summary. Statement of the problem. A disadvantage of the gypsum binder is the limited water resistance of products that historically led to the use of gypsum products mostly for internal construction and finishing works. To regulate the process of hydration and structure formation of the use of chemical additives that are introduced with the mixing water or in the production of the binder. As a rule, substances that increase the solubility of the gypsum binder referred to as the hardening accelerator, and substances which retard the solubility of the inhibitors of hardening of the mixture. Most accelerators and retarders hardening affect adversely on the final strength of the mixture. More effective impact on gypsum binder additives have plasticizers. The purpose of the article. Getting gypsum binder modified with the aim of improving its water resistance and improvement of some technological factors (the time of hardening, water gypsum ratio, etc. would reduce its shortcomings and expand the scope of application of the binder. Conclusion. The result of the research reviewed changes in the basic properties of the gypsum binder with the introduction of additives, plasticizers, and selected the most effective supplements to significantly reduce water gypsum ratio, to improve strength properties and to obtain gypsum binder more dense structure.

  19. Distinguishing modified gravity models

    Energy Technology Data Exchange (ETDEWEB)

    Brax, Philippe [Institut de Physique Théorique, Université Paris-Saclay, CEA, CNRS, F-91191 Gif/Yvette Cedex (France); Davis, Anne-Christine, E-mail: philippe.brax@cea.fr, E-mail: A.C.Davis@damtp.cam.ac.uk [DAMTP, Centre for Mathematical Sciences, University of Cambridge, Cambridge, CB3 0WA (United Kingdom)

    2015-10-01

    Modified gravity models with screening in local environments appear in three different guises: chameleon, K-mouflage and Vainshtein mechanisms. We propose to look for differences between these classes of models by considering cosmological observations at low redshift. In particular, we analyse the redshift dependence of the fine structure constant and the proton to electron mass ratio in each of these scenarios. When the absorption lines belong to unscreened regions of space such as dwarf galaxies, a time variation would be present for chameleons. For both K-mouflage and Vainshtein mechanisms, the cosmological time variation of the scalar field is not suppressed in both unscreened and screened environments, therefore enhancing the variation of constants and their detection prospect. We also consider the time variation of the redshift of distant objects using their spectrocopic velocities. We find that models of the K-mouflage and Vainshtein types have very different spectroscopic velocities as a function of redshift and that their differences with the Λ-CDM template should be within reach of the future ELT-HIRES observations.

  20. Shifted-modified Chebyshev filters

    OpenAIRE

    ŞENGÜL, Metin

    2013-01-01

    This paper introduces a new type of filter approximation method that utilizes shifted-modified Chebyshev filters. Construction of the new filters involves the use of shifted-modified Chebyshev polynomials that are formed using the roots of conventional Chebyshev polynomials. The study also includes 2 tables containing the shifted-modified Chebyshev polynomials and the normalized element values for the low-pass prototype filters up to degree 6. The transducer power gain, group dela...

  1. 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...

  2. 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.

  3. 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...

  4. 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.

  5. Horseshoes in modified Chen's attractors

    International Nuclear Information System (INIS)

    Huang Yan; Yang Xiaosong

    2005-01-01

    In this paper we study dynamics of a class of modified Chen's attractors, we show that these attractors are chaotic by giving a rigorous verification for existence of horseshoes in these systems. We prove that the Poincare maps derived from these modified Chen's attractors are semi-conjugate to the 2-shift map

  6. Surface-modified electrodes (SME)

    NARCIS (Netherlands)

    Schreurs, J.P.G.M.; Barendrecht, E.

    1984-01-01

    This review deals with the literature (covered up to August 1983), the characterization and the applications of Surface-Modified Electrodes (SME). As a special class of SME's, the Enzyme-Modified Electrode (EME) is introduced. Three types of modification procedures are distinguished; i.e. covalent

  7. Genetically modified foods and allergy.

    Science.gov (United States)

    Lee, T H; Ho, H K; Leung, T F

    2017-06-01

    2015 marked the 25th anniversary of the commercial use and availability of genetically modified crops. The area of planted biotech crops cultivated globally occupies a cumulative two billion hectares, equivalent to twice the land size of China or the United States. Foods derived from genetically modified plants are widely consumed in many countries and genetically modified soybean protein is extensively used in processed foods throughout the industrialised countries. Genetically modified food technology offers a possible solution to meet current and future challenges in food and medicine. Yet there is a strong undercurrent of anxiety that genetically modified foods are unsafe for human consumption, sometimes fuelled by criticisms based on little or no firm evidence. This has resulted in some countries turning away food destined for famine relief because of the perceived health risks of genetically modified foods. The major concerns include their possible allergenicity and toxicity despite the vigorous testing of genetically modified foods prior to marketing approval. It is imperative that scientists engage the public in a constructive evidence-based dialogue to address these concerns. At the same time, improved validated ways to test the safety of new foods should be developed. A post-launch strategy should be established routinely to allay concerns. Mandatory labelling of genetically modified ingredients should be adopted for the sake of transparency. Such ingredient listing and information facilitate tracing and recall if required.

  8. Modified General Relativity and Cosmology

    Science.gov (United States)

    Abdel-Rahman, A.-M. M.

    1997-10-01

    Aspects of the modified general relativity theory of Rastall, Al-Rawaf and Taha are discussed in both the radiation- and matter-dominated flat cosmological models. A nucleosynthesis constraint on the theory's free parameter is obtained and the implication for the age of the Universe is discussed. The consistency of the modified matter- dominated model with the neoclassical cosmological tests is demonstrated.

  9. 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

  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. Modified Nanodiamonds for Detoxification

    Science.gov (United States)

    Gibson, Natalie Marie

    essential for interacting with charged molecules, like OTA. Furthermore, the increased ZPs lead to improved colloidal stabilities over a wide range of pH, which is important for their interaction in the GI tract. While the dyes and OTA illustrated primarily electrostatic adsorption mechanisms, neutrally charged AfB1's adsorption was predominantly based upon the aggregate size of the ND substrate. In addition to mycotoxins, fluorescent dyes, including propidium iodide, pyranine and 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS), were initially utilized during methodological development. Fluorescent dye investigations helped assesses the adsorption mechanisms of NDs and demonstrated the significance of electrostatic interactions. Beyond electrostatic adsorption mechanisms, surface functional groups were also responsible for the amount of dye adsorbed, as was also true in OTA adsorption. Therefore, surface characterization was carried out for several ND samples by FTIR, TOF-SIMS and TDMS analysis. Final results of our studies show that our modified NDs perform better than yeast cells walls and other NDs but comparable to activated charcoal in the adsorption of AfB1, and outperform clay minerals in OTA studies. Moreover, it was demonstrated that adsorption can be maintained in a wide range of pH, thereby, increasing the possibility of NDs use in mycotoxins enterosorbent applications.

  14. 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...

  15. 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

  16. 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

  17. 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

  18. 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...

  19. 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.)

  20. 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.

  1. 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.

  2. 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 ...

  3. 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 ...

  4. 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

  5. Deep drilling KLX 02. Drilling and documentation of a 1700 m deep borehole at Laxemar, Sweden

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, O [VBB VIAK AB, Malmoe (Sweden)

    1994-08-01

    In this report the preparation and execution of the deep core drilling KLX 02 is described. The hole was drilled with the wireline methods, NQ dimension (diameter 76 mm), to a final depth of 1700.5 m. Prior to core drilling a diameter 215 mm pilot hole was pre drilled to 200 m with controlled hammer drilling (DTH). In this hole casing and air-lift equipment was installed with the aim to support the circulation of drilling fluid. During core drilling there was a measurement of major drilling parameters and drilling fluid in and out of hole. As a fluid tracer uranine was used. Each 300 m of core drilling air-lift pump tests were performed. After completion a flow-meter log was run to finalize the project phase. It can be concluded that both the pre drilling and core drilling methods used proved to be successful. No severe technical problem occurred. However, potential risks have been pointed at in the report. The air-lift system functioned only partly and has to be modified for further use. Also the technique for monitoring of drilling parameters needs improvement as does the method for air-lift pump tests with packer. The organisation model for planning and realization functioned satisfactory and can be recommended for similar future projects. 9 refs, numerous tabs and figs.

  6. Deep drilling KLX 02. Drilling and documentation of a 1700 m deep borehole at Laxemar, Sweden

    International Nuclear Information System (INIS)

    Andersson, O.

    1994-08-01

    In this report the preparation and execution of the deep core drilling KLX 02 is described. The hole was drilled with the wireline methods, NQ dimension (diameter 76 mm), to a final depth of 1700.5 m. Prior to core drilling a diameter 215 mm pilot hole was pre drilled to 200 m with controlled hammer drilling (DTH). In this hole casing and air-lift equipment was installed with the aim to support the circulation of drilling fluid. During core drilling there was a measurement of major drilling parameters and drilling fluid in and out of hole. As a fluid tracer uranine was used. Each 300 m of core drilling air-lift pump tests were performed. After completion a flow-meter log was run to finalize the project phase. It can be concluded that both the pre drilling and core drilling methods used proved to be successful. No severe technical problem occurred. However, potential risks have been pointed at in the report. The air-lift system functioned only partly and has to be modified for further use. Also the technique for monitoring of drilling parameters needs improvement as does the method for air-lift pump tests with packer. The organisation model for planning and realization functioned satisfactory and can be recommended for similar future projects. 9 refs, numerous tabs and figs

  7. Deep intronic mutation and pseudo exon activation as a novel muscular hypertrophy modifier in cattle.

    Directory of Open Access Journals (Sweden)

    Claire Bouyer

    Full Text Available Myostatin is essential for proper regulation of myogenesis, and inactivation of Myostatin results in muscle hypertrophy. Here, we identified an unexpected mutation in the myostatin gene which is almost fixed in Blonde d'Aquitaine cattle. In skeletal muscle, the mutant allele was highly expressed leading to an abnormal transcript consisting of a 41-bp inclusion and premature termination codons and to residual levels of a correctly spliced transcript. This expression pattern, caused by a leaky intronic mutation with regard to spliceosome activity and its apparent stability with regard to surveillance mechanisms, could contribute to the moderate muscle hypertrophy in this cattle breed. This finding is of importance for genetic counseling for meat quantity and quality in livestock production and possibly to manipulate myostatin pre-mRNA in human muscle diseases.

  8. STELLAR STRUCTURE AND TESTS OF MODIFIED GRAVITY

    International Nuclear Information System (INIS)

    Chang, Philip; Hui, Lam

    2011-01-01

    Theories that attempt to explain cosmic acceleration by modifying gravity typically introduces a long-range scalar force that needs to be screened on small scales. One common screening mechanism is the chameleon, where the scalar force is screened in environments with a sufficiently deep gravitational potential, but acts unimpeded in regions with a shallow gravitational potential. This leads to a variation in the overall gravitational G with environment. We show that such a variation can occur within a star itself, significantly affecting its evolution and structure, provided that the host galaxy is unscreened. The effect is most pronounced for red giants, which would be smaller by a factor of tens of percent and thus hotter by hundreds of Kelvin, depending on the parameters of the underlying scalar-tensor theory. Careful measurements of these stars in suitable environments (nearby dwarf galaxies not associated with groups or clusters) would provide constraints on the chameleon mechanism that are four orders of magnitude better than current large-scale structure limits and two orders of magnitude better than present solar system tests.

  9. Efficacy of two types of palliative sedation therapy defined using intervention protocols: proportional vs. deep sedation.

    Science.gov (United States)

    Imai, Kengo; Morita, Tatsuya; Yokomichi, Naosuke; Mori, Masanori; Naito, Akemi Shirado; Tsukuura, Hiroaki; Yamauchi, Toshihiro; Kawaguchi, Takashi; Fukuta, Kaori; Inoue, Satoshi

    2018-06-01

    This study investigated the effect of two types of palliative sedation defined using intervention protocols: proportional and deep sedation. We retrospectively analyzed prospectively recorded data of consecutive cancer patients who received the continuous infusion of midazolam in a palliative care unit. Attending physicians chose the sedation protocol based on each patient's wish, symptom severity, prognosis, and refractoriness of suffering. The primary endpoint was a treatment goal achievement at 4 h: in proportional sedation, the achievement of symptom relief (Support Team Assessment Schedule (STAS) ≤ 1) and absence of agitation (modified Richmond Agitation-Sedation Scale (RASS) ≤ 0) and in deep sedation, the achievement of deep sedation (RASS ≤ - 4). Secondary endpoints included mean scores of STAS and RASS, deep sedation as a result, and adverse events. Among 398 patients who died during the period, 32 received proportional and 18 received deep sedation. The treatment goal achievement rate was 68.8% (22/32, 95% confidence interval 52.7-84.9) in the proportional sedation group vs. 83.3% (15/18, 66.1-100) in the deep sedation group. STAS decreased from 3.8 to 0.8 with proportional sedation at 4 h vs. 3.7 to 0.3 with deep sedation; RASS decreased from + 1.2 to - 1.7 vs. + 1.4 to - 3.7, respectively. Deep sedation was needed as a result in 31.3% (10/32) of the proportional sedation group. No fatal events that were considered as probably or definitely related to the intervention occurred. The two types of intervention protocol well reflected the treatment intention and expected outcomes. Further, large-scale cohort studies are promising.

  10. 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)

  11. 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

  12. 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)

  13. 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.

  14. 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)

  15. 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

  16. 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.

  17. MS Disease-Modifying Medications

    Science.gov (United States)

    ... disease-modifying therapies Approval: 2014 US; 2014 CAN Pregnancy Category C (see footnote, page 11) Rash, headache, fever, nasal congestion, nausea, urinary tract infection, fatigue, insomnia, upper respiratory tract infection, herpes viral ...

  18. Value Modifier Public Use File

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Center for Medicare (CM) has created a standard analytical file intended to promote transparency. For each Value Modifier performance year, CM will publish a...

  19. 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...

  20. Complex approach mechanical properties and formability assessment of selected deep-drawing steels

    OpenAIRE

    J. Štaba; M. Buršák

    2009-01-01

    The paper analyses the properties of deep-drawing sheets of three grades (Re = 320 to 475 MPa), surface-treated with hot-dip galvanizing, made of microalloyed steels. Deformation properties are assessed using tensile tests, technological Erichsen or cupping tests. These characteristics, as well as the behaviour of the surface layer, are also investigated under dynamic conditions (modified Erichsen test using a drop tester), or using flat bending fatigue tests. Using microscopic analysis the d...

  1. Performance Analysis of High-Speed Deep/Shallow Recessed Hybrid Bearing

    OpenAIRE

    Lei Wang; Shuyun Jiang

    2013-01-01

    The present paper proposes a theoretical analysis of the performance of deep/shallow recessed hybrid bearing. It is intended that, on the basis of the numerical results drawn from this study, appropriate shallow recess depth and width can be determined for use in the bearing design process. By adopting bulk flow theory, the turbulent Reynolds equation and energy equation are modified and solved numerically including concentrated inertia effects at the recess edge with different depth and widt...

  2. Offline High pH Reversed-Phase Peptide Fractionation for Deep Phosphoproteome Coverage

    DEFF Research Database (Denmark)

    Batth, Tanveer S; Olsen, Jesper V

    2016-01-01

    Protein phosphorylation, a process in which kinases modify serines, threonines, and tyrosines with phosphoryl groups is of major importance in eukaryotic biology. Protein phosphorylation events are key initiators of signaling responses which determine cellular outcomes after environmental...... and metabolic stimuli, and are thus highly regulated. Therefore, studying the mechanism of regulation by phosphorylation, and pinpointing the exact site of phosphorylation on proteins is of high importance. This protocol describes in detail a phosphoproteomics workflow for ultra-deep coverage by fractionating...

  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. Hardness in high temperature of steels ABNT H11 and ABNT H11 modified with niobium

    International Nuclear Information System (INIS)

    Goncalves, R.A.

    1984-01-01

    A method to measure the hardness of metallic materials was developed. The heating was done by the Joule effect heat dissipation in the sample, that is like an electrical resistor. A diamond penetrator with a revolution paraboloid format was used, that assure a linear relation between the load applyed and the penetration deep. Hardness tests were make in the range of 25 - 600 0 C, in the steels ABNT H11 and ABNT H11 modified with niobium, with the simultaneous register of the applied force, penetration deep and temperature. (E.G.) [pt

  11. 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.

  12. Scaled momentum spectra in deep inelastic scattering at HERA

    International Nuclear Information System (INIS)

    Abramowicz, H.; Abt, I.; Adamczyk, L.

    2009-12-01

    Charged particle production has been studied in neutral current deep inelastic ep scattering with the ZEUS detector at HERA using an integrated luminosity of 0.44 fb -1 . Distributions of scaled momenta in the Breit frame are presented for particles in the current fragmentation region. The evolution of these spectra with the photon virtuality, Q 2 , is described in the kinematic region 10 2 2 . Next-to-leading-order and modified leading-log-approximation QCD calculations as well as predictions from Monte Carlo models are compared to the data. The results are also compared to e + e - annihilation data. The dependences of the pseudorapidity distribution of the particles on Q 2 and on the energy in the γp system, W, are presented and interpreted in the context of the hypothesis of limiting fragmentation. (orig.)

  13. Scaled momentum spectra in deep inelastic scattering at HERA

    Energy Technology Data Exchange (ETDEWEB)

    Abramowicz, H. [Tel Aviv Univ. (Israel). Raymond and Beverly Sackler Faculty of Exact Sciences; University College London (United Kingdom); Max Planck Inst., Munich (Germany); Abt, I. [Max-Planck-Inst. fuer Physik, Muenchen (Germany); Adamczyk, L. [AGH-Univ. of Science and Technology, Cracow (PL). Faculty of Physics and Applied Computer Science] (and others)

    2009-12-15

    Charged particle production has been studied in neutral current deep inelastic ep scattering with the ZEUS detector at HERA using an integrated luminosity of 0.44 fb{sup -1}. Distributions of scaled momenta in the Breit frame are presented for particles in the current fragmentation region. The evolution of these spectra with the photon virtuality, Q{sup 2}, is described in the kinematic region 10modified leading-log-approximation QCD calculations as well as predictions from Monte Carlo models are compared to the data. The results are also compared to e{sup +}e{sup -} annihilation data. The dependences of the pseudorapidity distribution of the particles on Q{sup 2} and on the energy in the {gamma}p system, W, are presented and interpreted in the context of the hypothesis of limiting fragmentation. (orig.)

  14. 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.

  15. Implant materials modified by colloids

    Directory of Open Access Journals (Sweden)

    Zboromirska-Wnukiewicz Beata

    2016-03-01

    Full Text Available Recent advances in general medicine led to the development of biomaterials. Implant material should be characterized by a high biocompatibility to the tissue and appropriate functionality, i.e. to have high mechanical and electrical strength and be stable in an electrolyte environment – these are the most important properties of bioceramic materials. Considerations of biomaterials design embrace also electrical properties occurring on the implant-body fluid interface and consequently the electrokinetic potential, which can be altered by modifying the surface of the implant. In this work, the surface of the implants was modified to decrease the risk of infection by using metal colloids. Nanocolloids were obtained using different chemical and electrical methods. It was found that the colloids obtained by physical and electrical methods are more stable than colloids obtained by chemical route. In this work the surface of modified corundum implants was investigated. The implant modified by nanosilver, obtained by electrical method was selected. The in vivo research on animals was carried out. Clinical observations showed that the implants with modified surface could be applied to wounds caused by atherosclerotic skeleton, for curing the chronic and bacterial inflammations as well as for skeletal reconstruction surgery.

  16. 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

  17. Magnetically tunable oil droplet lens of deep-sea shrimp

    Science.gov (United States)

    Iwasaka, M.; Hirota, N.; Oba, Y.

    2018-05-01

    In this study, the tunable properties of a bio-lens from a deep-sea shrimp were investigated for the first time using magnetic fields. The skin of the shrimp exhibited a brilliantly colored reflection of incident white light. The light reflecting parts and the oil droplets in the shrimp's skin were observed in a glass slide sample cell using a digital microscope that operated in the bore of two superconducting magnets (maximum strengths of 5 and 13 T). In the ventral skin of the shrimp, which contained many oil droplets, some comparatively large oil droplets (50 to 150 μm in diameter) were present. A distinct response to magnetic fields was found in these large oil droplets. Further, the application of the magnetic fields to the sample cell caused a change in the size of the oil droplets. The phenomena observed in this work indicate that the oil droplets of deep sea shrimp can act as lenses in which the optical focusing can be modified via the application of external magnetic fields. The results of this study will make it possible to fabricate bio-inspired soft optical devices in future.

  18. Photobiology of the deep twilight zone and beyond

    Science.gov (United States)

    Waterman, Talbot H.

    1997-02-01

    Photobiology in the twilight zone of the deep sea depends on faint light of two, or possibly three, origins: sunlight, bioluminescence and some visible radiation near the bottom associated with hydrothermal vents. The deep twilight zone also contains two quite distinct ecosystems: the vast open ocean pelagic regime far from the shore and the bottom as well as the far less expansive benthic regime with quite different characteristic animals that live on, in or near the sea bo10 Most of the whole ocean's benthic regime with a mean depth over 3000m is well below the twilight zone, which eliminates sunlight as a light source there. Many of the most familiar deepsea animals with their spectacular arrays of dennal light organs and remarkable eyes are from the pelagic 19, 25 The less familiar benthic fishes and crustaceans sometimes have curious internal light organs powered by bacteria13 and occasional incredibly modified eyes.30 With the exception of those on the fishing rods of most female deepsea anglerfish, where the light is produced by symbiotic bacteria, all the numerous light organs of pelagic deepsea fishes are generally believed to manage their own chemiluminescence independent of luminous bacteria.17

  19. IMPROVEMENT OF RECOGNITION QUALITY IN DEEP LEARNING NETWORKS BY SIMULATED ANNEALING METHOD

    Directory of Open Access Journals (Sweden)

    A. S. Potapov

    2014-09-01

    Full Text Available The subject of this research is deep learning methods, in which automatic construction of feature transforms is taken place in tasks of pattern recognition. Multilayer autoencoders have been taken as the considered type of deep learning networks. Autoencoders perform nonlinear feature transform with logistic regression as an upper classification layer. In order to verify the hypothesis of possibility to improve recognition rate by global optimization of parameters for deep learning networks, which are traditionally trained layer-by-layer by gradient descent, a new method has been designed and implemented. The method applies simulated annealing for tuning connection weights of autoencoders while regression layer is simultaneously trained by stochastic gradient descent. Experiments held by means of standard MNIST handwritten digit database have shown the decrease of recognition error rate from 1.1 to 1.5 times in case of the modified method comparing to the traditional method, which is based on local optimization. Thus, overfitting effect doesn’t appear and the possibility to improve learning rate is confirmed in deep learning networks by global optimization methods (in terms of increasing recognition probability. Research results can be applied for improving the probability of pattern recognition in the fields, which require automatic construction of nonlinear feature transforms, in particular, in the image recognition. Keywords: pattern recognition, deep learning, autoencoder, logistic regression, simulated annealing.

  20. Modifying Knowledge, Emotions, and Attitudes Regarding Genetically Modified Foods

    Science.gov (United States)

    Heddy, Benjamin C.; Danielson, Robert W.; Sinatra, Gale M.; Graham, Jesse

    2017-01-01

    The purpose of this study was to explore whether conceptual change predicted emotional and attitudinal change while learning about genetically modified foods (GMFs). Participants were 322 college students; half read a refutation text designed to shift conceptual knowledge, emotions, and attitudes, while the other half served as a control group.…

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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...

  6. 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...

  7. 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

  8. 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).

  9. 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

  10. Applying artificial intelligence to disease staging: Deep learning for improved staging of diabetic retinopathy.

    Science.gov (United States)

    Takahashi, Hidenori; Tampo, Hironobu; Arai, Yusuke; Inoue, Yuji; Kawashima, Hidetoshi

    2017-01-01

    Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, disease staging using a wide area is more desirable than that using a limited area. We investigated if deep learning artificial intelligence (AI) could be used to grade diabetic retinopathy and determine treatment and prognosis. The retrospective study analyzed 9,939 posterior pole photographs of 2,740 patients with diabetes. Nonmydriatic 45° field color fundus photographs were taken of four fields in each eye annually at Jichi Medical University between May 2011 and June 2015. A modified fully randomly initialized GoogLeNet deep learning neural network was trained on 95% of the photographs using manual modified Davis grading of three additional adjacent photographs. We graded 4,709 of the 9,939 posterior pole fundus photographs using real prognoses. In addition, 95% of the photographs were learned by the modified GoogLeNet. Main outcome measures were prevalence and bias-adjusted Fleiss' kappa (PABAK) of AI staging of the remaining 5% of the photographs. The PABAK to modified Davis grading was 0.64 (accuracy, 81%; correct answer in 402 of 496 photographs). The PABAK to real prognosis grading was 0.37 (accuracy, 96%). We propose a novel AI disease-staging system for grading diabetic retinopathy that involves a retinal area not typically visualized on fundoscopy and another AI that directly suggests treatments and determines prognoses.

  11. 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

  12. 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

  13. Modified Steiner functional string action

    International Nuclear Information System (INIS)

    Baillie, C.F.; Johnston, D.A.

    1992-01-01

    It has recently been suggested by Ambartzumian et al. that the modified Steiner functional has desirable properties as an action for random surfaces and hence string world sheets. We perform a simulation of this action on a dynamically triangulated random surface to investigate this claim and find that the surfaces are in a flat phase

  14. Modified gravity without dark matter

    NARCIS (Netherlands)

    Sanders, Robert; Papantonopoulos, L

    2007-01-01

    On an empirical level, the most successful alternative to dark matter in bound gravitational systems is the modified Newtonian dynamics, or MOND, proposed by Milgrom. Here I discuss the attempts to formulate MOND as a modification of General Relativity. I begin with a summary of the phenomenological

  15. MODIFIED TECHNIQUE OF TOTAL LARYNGECTOMY

    Directory of Open Access Journals (Sweden)

    Predrag Spirić

    2010-12-01

    Full Text Available Surgical technique of total laryngectomy is well presented in many surgical textbooks. Essentially, it has remained the same since Gluck an Soerensen in 1922 described all its details. Generally, it stresses the U shape skin incision with releasing laryngeal structures and removing larynx from up to down. Further, pharyngeal reconstruction is performed with different kinds of sutures in two or more layers and is finished with skin suture and suction drainage. One of worst complications following this surgery is pharyngocutaneous fistula (PF. Modifications proposed in this this article suggests vertical skin incision with larynx removal from below upwards. In pharyngeal reconstruction we used the running locked suture in submucosal plan with „tobacco sac“ at the end on the tongue base instead of traditional T shaped suture. Suction drains were not used.The aim of study was to present the modified surgical technique of total laryingectomy and its impact on hospital stay duration and pharyngocutanous fistula formation. In this randomized study we analyzed 49 patients operated with modified surgical technique compared to 49 patient operated with traditional surgical technique of total laryngectomy. The modified technique of total laryngectomy was presented. Using modified technique we managed to decrease the PF percentage from previous 20,41% to acceptable 8,16% (p=0,0334. Also, the average hospital stay was shortened from 14,96 to 10,63 days (t =-2.9850; p=0.0358.The modified technique of total laryngectomy is safe, short and efficient surgical intervention which decreases the number of pharyngocutaneos fistulas and shortens the hospital stay.

  16. 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.

  17. 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.

  18. 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'

  19. 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.

  20. 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.

  1. 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

  2. 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...

  3. 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.

  4. 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...

  5. 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...

  6. 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.

  7. 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,...

  8. 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

  9. 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.

  10. 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

  11. 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,...

  12. 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

  13. 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

  14. 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.

  15. 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...

  16. 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...

  17. 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...

  18. 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

  19. 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

  20. 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 ...

  1. 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...

  2. 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.

  3. 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...

  4. 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...

  5. 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...

  6. 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

  7. 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...

  8. Modified Method of Simplest Equation Applied to the Nonlinear Schrödinger Equation

    Directory of Open Access Journals (Sweden)

    Vitanov Nikolay K.

    2018-03-01

    Full Text Available We consider an extension of the methodology of the modified method of simplest equation to the case of use of two simplest equations. The extended methodology is applied for obtaining exact solutions of model nonlinear partial differential equations for deep water waves: the nonlinear Schrödinger equation. It is shown that the methodology works also for other equations of the nonlinear Schrödinger kind.

  9. Modified Method of Simplest Equation Applied to the Nonlinear Schrödinger Equation

    Science.gov (United States)

    Vitanov, Nikolay K.; Dimitrova, Zlatinka I.

    2018-03-01

    We consider an extension of the methodology of the modified method of simplest equation to the case of use of two simplest equations. The extended methodology is applied for obtaining exact solutions of model nonlinear partial differential equations for deep water waves: the nonlinear Schrödinger equation. It is shown that the methodology works also for other equations of the nonlinear Schrödinger kind.

  10. 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...

  11. 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.

  12. 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.

  13. 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

  14. 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.

  15. Complexation thermodynamics of modified cyclodextrins

    DEFF Research Database (Denmark)

    Schönbeck, Jens Christian Sidney; Westh, Peter; Holm, Rene

    2014-01-01

    Inclusion complexes between two bile salts and a range of differently methylated β-cyclodextrins were studied in an attempt to rationalize the complexation thermodynamics of modified cyclodextrins. Calorimetric titrations at a range of temperatures provided precise values of the enthalpies (ΔH......°), entropies (ΔS°), and heat capacities (ΔCp) of complexation, while molecular dynamics simulations assisted the interpretation of the obtained thermodynamic parameters. As previously observed for several types of modified cyclodextrins, the substituents at the rims of the cyclodextrin induced large changes......° and then a strong decrease when the degree of substitution exceeded some threshold. Exactly the same trend was observed for ΔCp. The dehydration of nonpolar surface, as quantified by the simulations, can to a large extent explain the variation in the thermodynamic parameters. The methyl substituents form additional...

  16. Generalized gravity from modified DFT

    International Nuclear Information System (INIS)

    Sakatani, Yuho; Uehara, Shozo; Yoshida, Kentaroh

    2017-01-01

    Recently, generalized equations of type IIB supergravity have been derived from the requirement of classical kappa-symmetry of type IIB superstring theory in the Green-Schwarz formulation. These equations are covariant under generalized T-duality transformations and hence one may expect a formulation similar to double field theory (DFT). In this paper, we consider a modification of the DFT equations of motion by relaxing a condition for the generalized covariant derivative with an extra generalized vector. In this modified double field theory (mDFT), we show that the flatness condition of the modified generalized Ricci tensor leads to the NS-NS part of the generalized equations of type IIB supergravity. In particular, the extra vector fields appearing in the generalized equations correspond to the extra generalized vector in mDFT. We also discuss duality symmetries and a modification of the string charge in mDFT.

  17. Generalized gravity from modified DFT

    Energy Technology Data Exchange (ETDEWEB)

    Sakatani, Yuho [Department of Physics, Kyoto Prefectural University of Medicine,Kyoto 606-0823 (Japan); Fields, Gravity and Strings, CTPU,Institute for Basic Sciences, Daejeon 34047 (Korea, Republic of); Uehara, Shozo [Department of Physics, Kyoto Prefectural University of Medicine,Kyoto 606-0823 (Japan); Yoshida, Kentaroh [Department of Physics, Kyoto University,Kitashirakawa Oiwake-cho, Kyoto 606-8502 (Japan)

    2017-04-20

    Recently, generalized equations of type IIB supergravity have been derived from the requirement of classical kappa-symmetry of type IIB superstring theory in the Green-Schwarz formulation. These equations are covariant under generalized T-duality transformations and hence one may expect a formulation similar to double field theory (DFT). In this paper, we consider a modification of the DFT equations of motion by relaxing a condition for the generalized covariant derivative with an extra generalized vector. In this modified double field theory (mDFT), we show that the flatness condition of the modified generalized Ricci tensor leads to the NS-NS part of the generalized equations of type IIB supergravity. In particular, the extra vector fields appearing in the generalized equations correspond to the extra generalized vector in mDFT. We also discuss duality symmetries and a modification of the string charge in mDFT.

  18. Disulfiram as a radiation modifier

    International Nuclear Information System (INIS)

    Taylor, R.D.; Maners, A.W.; Salari, H.; Baker, M.; Walker, E.M. Jr.

    1986-01-01

    The radiation modifying effect and toxicity of tetraethylthiuram disulfide (disulfiram) have been studied. Disulfiram (DSM) inhibits aldehyde dehydrogenase, dopamine-beta-oxygenase, microsomal mixed-function oxidases and cytochrome P-450 enzymes. It is widely used for aversion therapy in alcoholism. Disulfiram also inhibits tumor formation by several known carcinogens. A biphasic toxicity pattern of DSM is reported in the L-929 mouse fibroblast culture system. Disulfiram is 100 percent toxic at 2 X 10(-7) M (0.05 micrograms per ml), 23 percent toxic at 3 X 10(-7) M (0.1 microgram per ml), and 100 percent toxic again at 3.4 X 10(-6) M (1.0 microgram per ml). The pattern is similar to the biphasic toxicity pattern of DMS's major metabolite, sodium diethyldithiocarbamate (DTC). Reports of both radiation protection and radiation enhancement by DTC exist. Previously, a radioprotective effect by 2 X 10(-6) M DTC (dose modifying factor = 1.26) has been demonstrated in the L-929 cell system. To date, no radiation modifying properties of DSM have been reported. Our investigation of DSM as a radiation modifier at 3 X 10(-7) M (0.1 microgram per ml) did not show significant improvement in survival of irradiated cells treated with DSM relative to the irradiated control group, as determined by absence of a difference in the Do of the two groups. Considering DSM's close structural relationship to DTC, it is possible that DSM may exhibit a radioprotective effect when applied in a different concentration than what was used in our research

  19. QGP and Modified Jet Fragmentation

    International Nuclear Information System (INIS)

    Wang, Xin-Nian

    2005-01-01

    Recent progresses in the study of jet modification in hotmedium and their consequences in high-energy heavy-ion collisions are reviewed. In particular, I will discuss energy loss for propagating heavy quarks and the resulting modified fragmentation function. Medium modification of the parton fragmentation function due to quark recombination are formulated within finite temperature field theory and their implication on the search for deconfined quark-gluon plasma is also discussed

  20. 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).

  1. Constitutive Behavior and Deep Drawability of Three Aluminum Alloys Under Different Temperatures and Deformation Speeds

    Science.gov (United States)

    Panicker, Sudhy S.; Prasad, K. Sajun; Basak, Shamik; Panda, Sushanta Kumar

    2017-08-01

    In the present work, uniaxial tensile tests were carried out to evaluate the stress-strain response of AA2014, AA5052 and AA6082 aluminum alloys at four temperatures: 303, 423, 523 and 623 K, and three strain rates: 0.0022, 0.022 and 0.22 s-1. It was found that the Cowper-Symonds model was not a robust constitutive model, and it failed to predict the flow behavior, particularly the thermal softening at higher temperatures. Subsequently, a comparative study was made on the capability of Johnson-Cook (JC), modified Zerilli-Armstrong (m-ZA), modified Arrhenius (m-ARR) and artificial neural network (ANN) for modeling the constitutive behavior of all the three aluminum alloys under the mentioned strain rates and temperatures. Also, the improvement in formability of the materials was evaluated at an elevated temperature of 623 K in terms of cup height and maximum safe strains by conducting cylindrical cup deep drawing experiments under two different punch speeds of 4 and 400 mm/min. The cup heights increased during warm deep drawing due to thermal softening and increase in failure strains. Also, a small reduction in cup height was observed when the punch speed increased from 4 to 400 mm/min at 623 K. Hence, it was suggested to use high-speed deformation at elevated temperature to reduce both punch load and cycle time during the deep drawing process.

  2. Kelvin Wave Influence on the Shallow-to-Deep Transition Over the Amazon

    Science.gov (United States)

    Rowe, A.; Serra, Y. L.

    2017-12-01

    The suite of observations from GOAmazon and CHUVA offers a unique opportunity to examine land-based convective processes in the tropics, including the poorly represented shallow-to-deep transition. This study uses these data to investigate impacts of Kelvin waves on the the shallow-to-deep transition over the Central Amazon. The Kelvin waves that propagate over the region often originate over the tropical central and east Pacific, with local generation over the Andes also observed. The observed 15 m s-1 phase speed and 4500 km wave length during the two-year campaign are in agreement with previously published studies of these waves across the tropics. Also in agreement with previous studies, we find the waves are most active during the wet season (November-May) for this region. Using four separate convective event classes (clear-sky, nonprecipitating cumulus congestus, afternoon deep convection, and mesoscale convective systems), we examine how the convection preferentially develops for different phases of the Kelvin waves seen during GOAmazon. We additionally examine surface meteorological variables, the vertical thermodynamic and dynamic structure of the troposphere, vertical moist static stability, integrated column water vapor and liquid water, and surface energy fluxes within the context of these convective classes to identify the important environmental factors contributing to observed periods of enhanced deep convection related to the waves. Results suggest that the waves significantly modify the local environment, such as creating a deep layer of moisture throughout the troposphere, favoring more organized convection in the active than in the suppressed phase of the wave. The significance of wave-related environmental modifications are assessed by comparing local rainfall accumulations during Kelvin wave activity to that when the waves are not present. Future work will further explore the shallow-to-deep transition and its modulation by Kelvin wave activity

  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. 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

  5. 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

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. 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.

  12. Deep, diverse and definitely different: unique attributes of the world's largest ecosystem

    Directory of Open Access Journals (Sweden)

    E. Ramirez-Llodra

    2010-09-01

    -water corals have an increased productivity through specific physical processes, such as topographic modification of currents and enhanced transport of particles and detrital matter. Because of its unique abiotic attributes, the deep sea hosts a specialized fauna. Although there are no phyla unique to deep waters, at lower taxonomic levels the composition of the fauna is distinct from that found in the upper ocean. Amongst other characteristic patterns, deep-sea species may exhibit either gigantism or dwarfism, related to the decrease in food availability with depth. Food limitation on the seafloor and water column is also reflected in the trophic structure of heterotrophic deep-sea communities, which are adapted to low energy availability. In most of these heterotrophic habitats, the dominant megafauna is composed of detritivores, while filter feeders are abundant in habitats with hard substrata (e.g. mid-ocean ridges, seamounts, canyon walls and coral reefs. Chemoautotrophy through symbiotic relationships is dominant in reducing habitats.

    Deep-sea biodiversity is among of the highest on the planet, mainly composed of macro and meiofauna, with high evenness. This is true for most of the continental margins and abyssal plains with hot spots of diversity such as seamounts or cold-water corals. However, in some ecosystems with particularly "extreme" physicochemical processes (e.g. hydrothermal vents, biodiversity is low but abundance and biomass are high and the communities are dominated by a few species. Two large-scale diversity patterns have been discussed for deep-sea benthic communities. First, a unimodal relationship between diversity and depth is observed, with a peak at intermediate depths (2000–3000 m, although this is not universal and particular abiotic processes can modify the trend. Secondly, a poleward trend of decreasing diversity has been discussed, but this remains controversial and studies with larger and more robust data sets are needed. Because of

  13. Broad Learning System: An Effective and Efficient Incremental Learning System Without the Need for Deep Architecture.

    Science.gov (United States)

    Chen, C L Philip; Liu, Zhulin

    2018-01-01

    Broad Learning System (BLS) that aims to offer an alternative way of learning in deep structure is proposed in this paper. Deep structure and learning suffer from a time-consuming training process because of a large number of connecting parameters in filters and layers. Moreover, it encounters a complete retraining process if the structure is not sufficient to model the system. The BLS is established in the form of a flat network, where the original inputs are transferred and placed as "mapped features" in feature nodes and the structure is expanded in wide sense in the "enhancement nodes." The incremental learning algorithms are developed for fast remodeling in broad expansion without a retraining process if the network deems to be expanded. Two incremental learning algorithms are given for both the increment of the feature nodes (or filters in deep structure) and the increment of the enhancement nodes. The designed model and algorithms are very versatile for selecting a model rapidly. In addition, another incremental learning is developed for a system that has been modeled encounters a new incoming input. Specifically, the system can be remodeled in an incremental way without the entire retraining from the beginning. Satisfactory result for model reduction using singular value decomposition is conducted to simplify the final structure. Compared with existing deep neural networks, experimental results on the Modified National Institute of Standards and Technology database and NYU NORB object recognition dataset benchmark data demonstrate the effectiveness of the proposed BLS.

  14. Trace Fossil Evidence of Trematode-Bivalve Parasite-Host Interactions in Deep Time.

    Science.gov (United States)

    Huntley, John Warren; De Baets, Kenneth

    2015-01-01

    Parasitism is one of the most pervasive phenomena amongst modern eukaryotic life and yet, relative to other biotic interactions, almost nothing is known about its history in deep time. Digenean trematodes (Platyhelminthes) are complex life cycle parasites, which have practically no body fossil record, but induce the growth of characteristic malformations in the shells of their bivalve hosts. These malformations are readily preserved in the fossil record, but, until recently, have largely been overlooked by students of the fossil record. In this review, we present the various malformations induced by trematodes in bivalves, evaluate their distribution through deep time in the phylogenetic and ecological contexts of their bivalve hosts and explore how various taphonomic processes have likely biased our understanding of trematodes in deep time. Trematodes are known to negatively affect their bivalve hosts in a number of ways including castration, modifying growth rates, causing immobilization and, in some cases, altering host behaviour making the host more susceptible to their own predators. Digeneans are expected to be significant agents of natural selection. To that end, we discuss how bivalves may have adapted to their parasites via heterochrony and suggest a practical methodology for testing such hypotheses in deep time. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. 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.

  16. Cosmological tests of modified gravity.

    Science.gov (United States)

    Koyama, Kazuya

    2016-04-01

    We review recent progress in the construction of modified gravity models as alternatives to dark energy as well as the development of cosmological tests of gravity. Einstein's theory of general relativity (GR) has been tested accurately within the local universe i.e. the Solar System, but this leaves the possibility open that it is not a good description of gravity at the largest scales in the Universe. This being said, the standard model of cosmology assumes GR on all scales. In 1998, astronomers made the surprising discovery that the expansion of the Universe is accelerating, not slowing down. This late-time acceleration of the Universe has become the most challenging problem in theoretical physics. Within the framework of GR, the acceleration would originate from an unknown dark energy. Alternatively, it could be that there is no dark energy and GR itself is in error on cosmological scales. In this review, we first give an overview of recent developments in modified gravity theories including f(R) gravity, braneworld gravity, Horndeski theory and massive/bigravity theory. We then focus on common properties these models share, such as screening mechanisms they use to evade the stringent Solar System tests. Once armed with a theoretical knowledge of modified gravity models, we move on to discuss how we can test modifications of gravity on cosmological scales. We present tests of gravity using linear cosmological perturbations and review the latest constraints on deviations from the standard [Formula: see text]CDM model. Since screening mechanisms leave distinct signatures in the non-linear structure formation, we also review novel astrophysical tests of gravity using clusters, dwarf galaxies and stars. The last decade has seen a number of new constraints placed on gravity from astrophysical to cosmological scales. Thanks to on-going and future surveys, cosmological tests of gravity will enjoy another, possibly even more, exciting ten years.

  17. Observational tests of modified gravity

    International Nuclear Information System (INIS)

    Jain, Bhuvnesh; Zhang Pengjie

    2008-01-01

    Modifications of general relativity provide an alternative explanation to dark energy for the observed acceleration of the Universe. Modified gravity theories have richer observational consequences for large-scale structures than conventional dark energy models, in that different observables are not described by a single growth factor even in the linear regime. We examine the relationships between perturbations in the metric potentials, density and velocity fields, and discuss strategies for measuring them using gravitational lensing, galaxy cluster abundances, galaxy clustering/dynamics, and the integrated Sachs-Wolfe effect. We show how a broad class of gravity theories can be tested by combining these probes. A robust way to interpret observations is by constraining two key functions: the ratio of the two metric potentials, and the ratio of the gravitational 'constant' in the Poisson equation to Newton's constant. We also discuss quasilinear effects that carry signatures of gravity, such as through induced three-point correlations. Clustering of dark energy can mimic features of modified gravity theories and thus confuse the search for distinct signatures of such theories. It can produce pressure perturbations and anisotropic stresses, which break the equality between the two metric potentials even in general relativity. With these two extra degrees of freedom, can a clustered dark energy model mimic modified gravity models in all observational tests? We show with specific examples that observational constraints on both the metric potentials and density perturbations can in principle distinguish modifications of gravity from dark energy models. We compare our result with other recent studies that have slightly different assumptions (and apparently contradictory conclusions).

  18. Deep Learning in Open Source Learning Streams

    DEFF Research Database (Denmark)

    Kjærgaard, Thomas

    2016-01-01

    This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized...... and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group......, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared...

  19. 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.

  20. Deep-seated sarcomas of the penis

    Directory of Open Access Journals (Sweden)

    Alberto A. Antunes

    2005-06-01

    Full Text Available Mesenchymal neoplasias represent 5% of tumors affecting the penis. Due to the rarity of such tumors, there is no agreement concerning the best method for staging and managing these patients. Sarcomas of the penis can be classified as deep-seated if they derive from the structures forming the spongy body and the cavernous bodies. Superficial lesions are usually low-grade and show a small tendency towards distant metastasis. In contrast, deep-seated lesions usually show behavior that is more aggressive and have poorer prognosis. The authors report 3 cases of deep-seated primary sarcomas of the penis and review the literature on this rare and aggressive neoplasia.

  1. Strategic Technologies for Deep Space Transport

    Science.gov (United States)

    Litchford, Ronald J.

    2016-01-01

    Deep space transportation capability for science and exploration is fundamentally limited by available propulsion technologies. Traditional chemical systems are performance plateaued and require enormous Initial Mass in Low Earth Orbit (IMLEO) whereas solar electric propulsion systems are power limited and unable to execute rapid transits. Nuclear based propulsion and alternative energetic methods, on the other hand, represent potential avenues, perhaps the only viable avenues, to high specific power space transport evincing reduced trip time, reduced IMLEO, and expanded deep space reach. Here, key deep space transport mission capability objectives are reviewed in relation to STMD technology portfolio needs, and the advanced propulsion technology solution landscape is examined including open questions, technical challenges, and developmental prospects. Options for potential future investment across the full compliment of STMD programs are presented based on an informed awareness of complimentary activities in industry, academia, OGAs, and NASA mission directorates.

  2. 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

  3. Deep learning for SAR image formation

    Science.gov (United States)

    Mason, Eric; Yonel, Bariscan; Yazici, Birsen

    2017-04-01

    The recent success of deep learning has lead to growing interest in applying these methods to signal processing problems. This paper explores the applications of deep learning to synthetic aperture radar (SAR) image formation. We review deep learning from a perspective relevant to SAR image formation. Our objective is to address SAR image formation in the presence of uncertainties in the SAR forward model. We present a recurrent auto-encoder network architecture based on the iterative shrinkage thresholding algorithm (ISTA) that incorporates SAR modeling. We then present an off-line training method using stochastic gradient descent and discuss the challenges and key steps of learning. Lastly, we show experimentally that our method can be used to form focused images in the presence of phase uncertainties. We demonstrate that the resulting algorithm has faster convergence and decreased reconstruction error than that of ISTA.

  4. Oceanography related to deep sea waste disposal

    International Nuclear Information System (INIS)

    1978-09-01

    In connection with studies on the feasibility of the safe disposal of radioactive waste, from a large scale nuclear power programme, either on the bed of the deep ocean or within the deep ocean bed, preparation of the present document was commissioned by the (United Kingdom) Department of the Environment. It attempts (a) to summarize the present state of knowledge of the deep ocean environment relevant to the disposal options and assess the processes which could aid or hinder dispersal of material released from its container; (b) to identify areas of research in which more work is needed before the safety of disposal on, or beneath, the ocean bed can be assessed; and (c) to indicate which areas of research can or should be undertaken by British scientists. The programmes of international cooperation in this field are discussed. The report is divided into four chapters dealing respectively with geology and geophysics, geochemistry, physical oceanography and marine biology. (U.K.)

  5. In Brief: Deep-sea observatory

    Science.gov (United States)

    Showstack, Randy

    2008-11-01

    The first deep-sea ocean observatory offshore of the continental United States has begun operating in the waters off central California. The remotely operated Monterey Accelerated Research System (MARS) will allow scientists to monitor the deep sea continuously. Among the first devices to be hooked up to the observatory are instruments to monitor earthquakes, videotape deep-sea animals, and study the effects of acidification on seafloor animals. ``Some day we may look back at the first packets of data streaming in from the MARS observatory as the equivalent of those first words spoken by Alexander Graham Bell: `Watson, come here, I need you!','' commented Marcia McNutt, president and CEO of the Monterey Bay Aquarium Research Institute, which coordinated construction of the observatory. For more information, see http://www.mbari.org/news/news_releases/2008/mars-live/mars-live.html.

  6. 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.

  7. 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

  8. Deep Learning in Medical Image Analysis.

    Science.gov (United States)

    Shen, Dinggang; Wu, Guorong; Suk, Heung-Il

    2017-06-21

    This review covers computer-assisted analysis of images in the field of medical imaging. Recent advances in machine learning, especially with regard to deep learning, are helping to identify, classify, and quantify patterns in medical images. At the core of these advances is the ability to exploit hierarchical feature representations learned solely from data, instead of features designed by hand according to domain-specific knowledge. Deep learning is rapidly becoming the state of the art, leading to enhanced performance in various medical applications. We introduce the fundamentals of deep learning methods and review their successes in image registration, detection of anatomical and cellular structures, tissue segmentation, computer-aided disease diagnosis and prognosis, and so on. We conclude by discussing research issues and suggesting future directions for further improvement.

  9. Pathways to deep decarbonization - Interim 2014 Report

    International Nuclear Information System (INIS)

    2014-01-01

    The interim 2014 report by the Deep Decarbonization Pathways Project (DDPP), coordinated and published by IDDRI and the Sustainable Development Solutions Network (SDSN), presents preliminary findings of the pathways developed by the DDPP Country Research Teams with the objective of achieving emission reductions consistent with limiting global warming to less than 2 deg. C. The DDPP is a knowledge network comprising 15 Country Research Teams and several Partner Organizations who develop and share methods, assumptions, and findings related to deep decarbonization. Each DDPP Country Research Team has developed an illustrative road-map 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. The interim 2014 report focuses on technically feasible pathways to deep decarbonization

  10. 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.

  11. Adhesives from modified soy protein

    Science.gov (United States)

    Sun, Susan [Manhattan, KS; Wang, Donghai [Manhattan, KS; Zhong, Zhikai [Manhattan, KS; Yang, Guang [Shanghai, CN

    2008-08-26

    The present invention provides useful adhesive compositions having similar adhesive properties to conventional UF and PPF resins. The compositions generally include a protein portion and modifying ingredient portion selected from the group consisting of carboxyl-containing compounds, aldehyde-containing compounds, epoxy group-containing compounds, and mixtures thereof. The composition is preferably prepared at a pH level at or near the isoelectric point of the protein. In other preferred forms, the adhesive composition includes a protein portion and a carboxyl-containing group portion.

  12. Metabolomics of Genetically Modified Crops

    Directory of Open Access Journals (Sweden)

    Carolina Simó

    2014-10-01

    Full Text Available Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

  13. A New Modified Firefly Algorithm

    Directory of Open Access Journals (Sweden)

    Medha Gupta

    2016-07-01

    Full Text Available Nature inspired meta-heuristic algorithms studies the emergent collective intelligence of groups of simple agents. Firefly Algorithm is one of the new such swarm-based metaheuristic algorithm inspired by the flashing behavior of fireflies. The algorithm was first proposed in 2008 and since then has been successfully used for solving various optimization problems. In this work, we intend to propose a new modified version of Firefly algorithm (MoFA and later its performance is compared with the standard firefly algorithm along with various other meta-heuristic algorithms. Numerical studies and results demonstrate that the proposed algorithm is superior to existing algorithms.

  14. On the Modified Barkhausen Criterion

    DEFF Research Database (Denmark)

    Lindberg, Erik; Murali, K.

    2016-01-01

    Oscillators are normally designed according to the Modified Barkhausen Criterion i.e. the complex pole pair is moved out in RHP so that the linear circuit becomes unstable. By means of the Mancini Phaseshift Oscillator it is demonstrated that the distortion of the oscillator may be minimized by i...... by introducing a nonlinear ”Hewlett Resistor” so that the complex pole-pair is in the RHP for small signals and in the LHP for large signals i.e. the complex pole pair of the instant linearized small signal model is moving around the imaginary axis in the complex frequency plane....

  15. Metabolomics of Genetically Modified Crops

    Science.gov (United States)

    Simó, Carolina; Ibáñez, Clara; Valdés, Alberto; Cifuentes, Alejandro; García-Cañas, Virginia

    2014-01-01

    Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade. PMID:25334064

  16. Particle acceleration in modified shocks

    International Nuclear Information System (INIS)

    Drury, L.O'C.; Axford, W.I.; Summers, D.

    1982-01-01

    Efficient particle acceleration in shocks must modify the shock structure with consequent changes in the particle acceleration. This effect is studied and analytic solutions are found describing the diffusive acceleration of particles with momentum independent diffusion coefficients in hyperbolic tangent type velocity transitions. If the input particle spectrum is a delta function, the shock smoothing replaces the truncated power-law downstream particle spectrum by a more complicated form, but one which has a power-law tail at high momenta. For a cold plasma this solution can be made completely self-consistent. Some problems associated with momentum dependent diffusion coefficients are discussed. (author)

  17. Particle acceleration in modified shocks

    Energy Technology Data Exchange (ETDEWEB)

    Drury, L.O' C. (Max-Planck-Institut fuer Kernphysik, Heidelberg (Germany, F.R.)); Axford, W.I. (Max-Planck-Institut fuer Aeronomie, Katlenburg-Lindau (Germany, F.R.)); Summers, D. (Memorial Univ. of Newfoundland, St. John' s (Canada))

    1982-03-01

    Efficient particle acceleration in shocks must modify the shock structure with consequent changes in the particle acceleration. This effect is studied and analytic solutions are found describing the diffusive acceleration of particles with momentum independent diffusion coefficients in hyperbolic tangent type velocity transitions. If the input particle spectrum is a delta function, the shock smoothing replaces the truncated power-law downstream particle spectrum by a more complicated form, but one which has a power-law tail at high momenta. For a cold plasma this solution can be made completely self-consistent. Some problems associated with momentum dependent diffusion coefficients are discussed.

  18. Stable isotope geochemistry of deep sea cherts

    Energy Technology Data Exchange (ETDEWEB)

    Kolodny, Y; Epstein, S [California Inst. of Tech., Pasadena (USA). Div. of Geological Sciences

    1976-10-01

    Seventy four samples of DSDP (Deep Sea Drilling Project) recovered cherts of Jurassic to Miocene age from varying locations, and 27 samples of on-land exposed cherts were analyzed for the isotopic composition of their oxygen and hydrogen. These studies were accompanied by mineralogical analyses and some isotopic analyses of the coexisting carbonates. delta/sup 18/0 of chert ranges between 27 and 39 parts per thousand relative to SMOW, delta/sup 18/0 of porcellanite - between 30 and 42 parts per thousand. The consistent enrichment of opal-CT in porcellanites in /sup 18/0 with respect to coexisting microcrystalline quartz in chert is probably a reflection of a different temperature (depth) of diagenesis of the two phases. delta/sup 18/0 of deep sea cherts generally decrease with increasing age, indicating an overall cooling of the ocean bottom during the last 150 m.y. A comparison of this trend with that recorded by benthonic foraminifera (Douglas et al., Initial Reports of the Deep Sea Drilling Project; 32:509(1975)) indicates the possibility of delta/sup 18/0 in deep sea cherts not being frozen in until several tens of millions of years after deposition. Cherts of any Age show a spread of delta/sup 18/0 values, increasing diagenesis being reflected in a lowering of delta/sup 18/0. Drusy quartz has the lowest delta/sup 18/0 values. On land exposed cherts are consistently depleted in /sup 18/0 in comparison to their deep sea time equivalent cherts. Water extracted from deep sea cherts ranges between 0.5 and 1.4 wt%. deltaD of this water ranges between -78 and -95 parts per thousand and is not a function of delta/sup 18/0 of the cherts (or the temperature of their formation).

  19. Deep Space Detection of Oriented Ice Crystals

    Science.gov (United States)

    Marshak, A.; Varnai, T.; Kostinski, A. B.

    2017-12-01

    The deep space climate observatory (DSCOVR) spacecraft resides at the first Lagrangian point about one million miles from Earth. A polychromatic imaging camera onboard delivers nearly hourly observations of the entire sun-lit face of the Earth. Many images contain unexpected bright flashes of light over both ocean and land. We constructed a yearlong time series of flash latitudes, scattering angles and oxygen absorption to demonstrate conclusively that the flashes over land are specular reflections off tiny ice crystals floating in the air nearly horizontally. Such deep space detection of tropospheric ice can be used to constrain the likelihood of oriented crystals and their contribution to Earth albedo.

  20. A clinical study on deep neck abscess

    International Nuclear Information System (INIS)

    Ota, Yumi; Ogawa, Yoshiko; Takemura, Teiji; Sawada, Toru

    2007-01-01

    Although various effective antibiotics have been synthesized, deep neck abscess is still a serious and life-threatening infection. It is important to diagnose promptly and treat adequately, and contrast-enhanced CT is useful and indispensable for diagnosis. We reviewed our patients with deep neck abscess, and analyzed the location by reviewing CT images, and discussed the treatment. Surgical drainage is a fundamental treatment for abscess but if it exists in only one area such as the parotid gland space, it can be cured with needle aspiration and suitable antibiotics. (author)

  1. Approximate Inference and Deep Generative Models

    CERN Multimedia

    CERN. Geneva

    2018-01-01

    Advances in deep generative models are at the forefront of deep learning research because of the promise they offer for allowing data-efficient learning, and for model-based reinforcement learning. In this talk I'll review a few standard methods for approximate inference and introduce modern approximations which allow for efficient large-scale training of a wide variety of generative models. Finally, I'll demonstrate several important application of these models to density estimation, missing data imputation, data compression and planning.

  2. Deep Belief Nets for Topic Modeling

    DEFF Research Database (Denmark)

    Maaløe, Lars; Arngren, Morten; Winther, Ole

    2015-01-01

    -formative. In this paper we describe large-scale content based collaborative filtering for digital publishing. To solve the digital publishing recommender problem we compare two approaches: latent Dirichlet allocation (LDA) and deep be-lief nets (DBN) that both find low-dimensional latent representations for documents....... Efficient retrieval can be carried out in the latent representation. We work both on public benchmarks and digital media content provided by Issuu, an on-line publishing platform. This article also comes with a newly developed deep belief nets toolbox for topic modeling tailored towards performance...

  3. Un paseo por la Deep Web

    OpenAIRE

    Ortega Castillo, Carlos

    2018-01-01

    Este documento busca presentar una mirada técnica e inclusiva a algunas de las tecnologías de interconexión desarrolladas en la DeepWeb, primero desde un punto de vista teórico y después con una breve introducción práctica. La desmitificación de los procesos desarrollados bajo la DeepWeb, brinda herramientas a los usuarios para esclarecer y construir nuevos paradigmas de sociedad, conocimiento y tecnología que aporten al desarrollo responsable de este tipo de redes y contribuyan al crecimi...

  4. Deep fracturation of granitic rock mass

    International Nuclear Information System (INIS)

    Bles, J.L.; Blanchin, R.; Bonijoly, D.; Dutartre, P.; Feybesse, J.L.; Gros, Y.; Landry, J.; Martin, P.

    1986-01-01

    This documentary study realized with the financial support of the European Communities and the CEA aims at the utilization of available data for the understanding of the evolution of natural fractures in granitic rocks from the surface to deep underground, in various feasibility studies dealing with radioactive wastes disposal. The Mont Blanc road tunnel, the EDF Arc-Isere gallerie, the Auriat deep borehole and the Pyrenean rock mass of Bassies are studied. In this study are more particularly analyzed the relationship between small fractures and large faults, evolution with depth of fracture density and direction, consequences of rock decompression and relationship between fracturation and groundwater [fr

  5. Gamma-rays from deep inelastic collisions

    International Nuclear Information System (INIS)

    Stephens, F.S.

    1979-01-01

    The γ-rays associated with deep inelastic collisions can give information about the magnitude and orientation of the angular momentum transferred in these events. In this review, special emphasis is placed on understanding the origin and nature of these γ-rays in order to avoid some of the ambiguities that can arise. The experimental information coming from these γ-ray studies is reviewed, and compared briefly with that obtained by other methods and also with the expectations from current models for deep inelastic collisions. 15 figures

  6. Fractal measures in a deep penetration problem

    International Nuclear Information System (INIS)

    Murthy, K.P.N.; Indira, R.; John, T.M.

    1993-01-01

    In the Monte Carlo simulation of a deep penetration problem the parameter, say b in the importance function must be assigned a value b' such that variance is minimum. If b b' the sample mean is still not reliable; but the sample fluctuations would be small and misleading, though the actual fluctuations are quite large. This is because the distribution of transmission has a tail which becomes prominent when b > b'. Considering a model deep penetration problem, and employing exact enumeration techniques, it is shown that in the limit of large biasing the long tailed distribution to the transmission is multifractal. (author). 5 refs., 3 figs

  7. La deep web : el mercado negro global

    OpenAIRE

    Gay Fernández, José

    2015-01-01

    La deep web es un espacio oculto de internet donde la primera garantía es el anonimato. En líneas generales, la deep web contiene todo aquello que los buscadores convencionales no pueden localizar. Esta garantía sirve para albergar una vasta red de servicios ilegales, como el narcotráfico, la trata de blancas, la contratación de sicarios, la compra-venta de pasaportes y cuentas bancarias, o la pornografía infantil, entre otros muchos. Pero el anonimato también posibilita que activ...

  8. Quantitative phase microscopy using deep neural networks

    Science.gov (United States)

    Li, Shuai; Sinha, Ayan; Lee, Justin; Barbastathis, George

    2018-02-01

    Deep learning has been proven to achieve ground-breaking accuracy in various tasks. In this paper, we implemented a deep neural network (DNN) to achieve phase retrieval in a wide-field microscope. Our DNN utilized the residual neural network (ResNet) architecture and was trained using the data generated by a phase SLM. The results showed that our DNN was able to reconstruct the profile of the phase target qualitatively. In the meantime, large error still existed, which indicated that our approach still need to be improved.

  9. Nuclear structure in deep-inelastic reactions

    International Nuclear Information System (INIS)

    Rehm, K.E.

    1986-01-01

    The paper concentrates on recent deep inelastic experiments conducted at Argonne National Laboratory and the nuclear structure effects evident in reactions between super heavy nuclei. Experiments indicate that these reactions evolve gradually from simple transfer processes which have been studied extensively for lighter nuclei such as 16 O, suggesting a theoretical approach connecting the one-step DWBA theory to the multistep statistical models of nuclear reactions. This transition between quasi-elastic and deep inelastic reactions is achieved by a simple random walk model. Some typical examples of nuclear structure effects are shown. 24 refs., 9 figs

  10. Deep Learning For Sequential Pattern Recognition

    OpenAIRE

    Safari, Pooyan

    2013-01-01

    Projecte realitzat en el marc d’un programa de mobilitat amb la Technische Universität München (TUM) In recent years, deep learning has opened a new research line in pattern recognition tasks. It has been hypothesized that this kind of learning would capture more abstract patterns concealed in data. It is motivated by the new findings both in biological aspects of the brain and hardware developments which have made the parallel processing possible. Deep learning methods come along with ...

  11. Environmental challenges of deep water activities

    International Nuclear Information System (INIS)

    Sande, Arvid

    1998-01-01

    In this presentation there are discussed the experiences of petroleum industry, and the projects that have been conducted in connection with the planning and drilling of the first deep water wells in Norway. There are also presented views on where to put more effort in the years to come, so as to increase the knowledge of deep water areas. Attention is laid on exploration drilling as this is the only activity with environmental potential that will take place during the next five years or so. The challenges for future field developments in these water depths are briefly discussed. 7 refs

  12. Complex approach mechanical properties and formability assessment of selected deep-drawing steels

    Directory of Open Access Journals (Sweden)

    J. Štaba

    2009-07-01

    Full Text Available The paper analyses the properties of deep-drawing sheets of three grades (Re = 320 to 475 MPa, surface-treated with hot-dip galvanizing, made of microalloyed steels. Deformation properties are assessed using tensile tests, technological Erichsen or cupping tests. These characteristics, as well as the behaviour of the surface layer, are also investigated under dynamic conditions (modified Erichsen test using a drop tester, or using flat bending fatigue tests. Using microscopic analysis the deformation properties of the surface layer are evaluated. The results show the compactness of the surface layer, high deformation characteristics, as well as fatigue properties of the investigated deep-drawing materials, suitable for application in the automotive industry.

  13. Modified Approach for Optimization of Real Life Transportation Problem in Neutrosophic Environment

    Directory of Open Access Journals (Sweden)

    Akanksha Singh

    2017-01-01

    Full Text Available To the best of our knowledge, there is only one approach for solving neutrosophic cost minimization transportation problems. Since neutrosophic transportation problems are a new area of research, other researchers may be attracted to extend this approach for solving other types of neutrosophic transportation problems like neutrosophic solid transportation problems, neutrosophic time minimization transportation problems, neutrosophic transshipment problems, and so on. However, after a deep study of the existing approach, it is noticed that a mathematical incorrect assumption has been used in these existing approaches; therefore there is a need to modify these existing approaches. Keeping the same in mind, in this paper, the existing approach is modified. Furthermore, the exact results of some existing transportation problems are obtained by the modified approach.

  14. Modified Multi Prime RSA Cryptosystem

    Science.gov (United States)

    Ghazali Kamardan, M.; Aminudin, N.; Che-Him, Norziha; Sufahani, Suliadi; Khalid, Kamil; Roslan, Rozaini

    2018-04-01

    RSA [1] is one of the mostly used cryptosystem in securing data and information. Though, it has been recently discovered that RSA has some weaknesses and in advance technology, RSA is believed to be inefficient especially when it comes to decryption. Thus, a new algorithm called Multi prime RSA, an extended version of the standard RSA is studied. Then, a modification is made to the Multi prime RSA where another keys is shared secretly between the receiver and the sender to increase the securerity. As in RSA, the methodology used for modified Multi-prime RSA also consists of three phases; 1. Key Generation in which the secret and public keys are generated and published. In this phase, the secrecy is improved by adding more prime numbers and addition of secret keys. 2. Encryption of the message using the public and secret keys given. 3. Decryption of the secret message using the secret key generated. For the decryption phase, a method called Chinese Remainder Theorem is used which helps to fasten the computation. Since Multi prime RSA use more than two prime numbers, the algorithm is more efficient and secure when compared to the standard RSA. Furthermore, in modified Multi prime RSA another secret key is introduced to increase the obstacle to the attacker. Therefore, it is strongly believed that this new algorithm is better and can be an alternative to the RSA.

  15. Modified Synthesis of Erlotinib Hydrochloride

    Directory of Open Access Journals (Sweden)

    Leila Barghi

    2012-06-01

    Full Text Available Purpose: An improved and economical method has been described for the synthesis of erlotinib hydrochloride, as a useful drug in treatment of non-small-cell lung cancer. Methods: Erlotinib hydrochloride was synthesized in seven steps starting from 3, 4-dihydroxy benzoic acid. In this study, we were able to modify one of the key steps which involved the reduction of the 6-nitrobenzoic acid derivative to 6-aminobenzoic acid derivative. An inexpensive reagent such as ammonium formate was used as an in situ hydrogen donor in the presence of palladium/charcoal (Pd/C instead of hydrogen gas at high pressure. Results: This proposed method proceeded with 92% yield at room temperature. Synthesis of erlotinib was completed in 7 steps with overall yield of 44%.Conclusion: From the results obtained it can be concluded that the modified method eliminated the potential danger associated with the use of hydrogen gas in the presence of flammable catalysts. It should be mentioned that the catalyst was recovered after the reaction and could be used again.

  16. Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentation

    Science.gov (United States)

    Karargyros, Alex; Syeda-Mahmood, Tanveer

    2018-02-01

    Deep learning networks are gaining popularity in many medical image analysis tasks due to their generalized ability to automatically extract relevant features from raw images. However, this can make the learning problem unnecessarily harder requiring network architectures of high complexity. In case of anomaly detection, in particular, there is often sufficient regional difference between the anomaly and the surrounding parenchyma that could be easily highlighted through bottom-up saliency operators. In this paper we propose a new hybrid deep learning network using a combination of raw image and such regional maps to more accurately learn the anomalies using simpler network architectures. Specifically, we modify a deep learning network called U-Net using both the raw and pre-segmented images as input to produce joint encoding (contraction) and expansion paths (decoding) in the U-Net. We present results of successfully delineating subdural and epidural hematomas in brain CT imaging and liver hemangioma in abdominal CT images using such network.

  17. DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks.

    Science.gov (United States)

    Li, Chao; Wang, Xinggang; Liu, Wenyu; Latecki, Longin Jan

    2018-04-01

    Mitotic count is a critical predictor of tumor aggressiveness in the breast cancer diagnosis. Nowadays mitosis counting is mainly performed by pathologists manually, which is extremely arduous and time-consuming. In this paper, we propose an accurate method for detecting the mitotic cells from histopathological slides using a novel multi-stage deep learning framework. Our method consists of a deep segmentation network for generating mitosis region when only a weak label is given (i.e., only the centroid pixel of mitosis is annotated), an elaborately designed deep detection network for localizing mitosis by using contextual region information, and a deep verification network for improving detection accuracy by removing false positives. We validate the proposed deep learning method on two widely used Mitosis Detection in Breast Cancer Histological Images (MITOSIS) datasets. Experimental results show that we can achieve the highest F-score on the MITOSIS dataset from ICPR 2012 grand challenge merely using the deep detection network. For the ICPR 2014 MITOSIS dataset that only provides the centroid location of mitosis, we employ the segmentation model to estimate the bounding box annotation for training the deep detection network. We also apply the verification model to eliminate some false positives produced from the detection model. By fusing scores of the detection and verification models, we achieve the state-of-the-art results. Moreover, our method is very fast with GPU computing, which makes it feasible for clinical practice. Copyright © 2018 Elsevier B.V. All rights reserved.

  18. Deep Seawater Intrusion Enhanced by Geothermal Through Deep Faults in Xinzhou Geothermal Field in Guangdong, China

    Science.gov (United States)

    Lu, G.; Ou, H.; Hu, B. X.; Wang, X.

    2017-12-01

    This study investigates abnormal sea water intrusion from deep depth, riding an inland-ward deep groundwater flow, which is enhanced by deep faults and geothermal processes. The study site Xinzhou geothermal field is 20 km from the coast line. It is in southern China's Guangdong coast, a part of China's long coastal geothermal belt. The geothermal water is salty, having fueled an speculation that it was ancient sea water retained. However, the perpetual "pumping" of the self-flowing outflow of geothermal waters might alter the deep underground flow to favor large-scale or long distant sea water intrusion. We studied geochemical characteristics of the geothermal water and found it as a mixture of the sea water with rain water or pore water, with no indication of dilution involved. And we conducted numerical studies of the buoyancy-driven geothermal flow in the deep ground and find that deep down in thousand meters there is favorable hydraulic gradient favoring inland-ward groundwater flow, allowing seawater intrude inland for an unusually long tens of kilometers in a granitic groundwater flow system. This work formed the first in understanding geo-environment for deep ground water flow.

  19. DeepBipolar: Identifying genomic mutations for bipolar disorder via deep learning.

    Science.gov (United States)

    Laksshman, Sundaram; Bhat, Rajendra Rana; Viswanath, Vivek; Li, Xiaolin

    2017-09-01

    Bipolar disorder, also known as manic depression, is a brain disorder that affects the brain structure of a patient. It results in extreme mood swings, severe states of depression, and overexcitement simultaneously. It is estimated that roughly 3% of the population of the United States (about 5.3 million adults) suffers from bipolar disorder. Recent research efforts like the Twin studies have demonstrated a high heritability factor for the disorder, making genomics a viable alternative for detecting and treating bipolar disorder, in addition to the conventional lengthy and costly postsymptom clinical diagnosis. Motivated by this study, leveraging several emerging deep learning algorithms, we design an end-to-end deep learning architecture (called DeepBipolar) to predict bipolar disorder based on limited genomic data. DeepBipolar adopts the Deep Convolutional Neural Network (DCNN) architecture that automatically extracts features from genotype information to predict the bipolar phenotype. We participated in the Critical Assessment of Genome Interpretation (CAGI) bipolar disorder challenge and DeepBipolar was considered the most successful by the independent assessor. In this work, we thoroughly evaluate the performance of DeepBipolar and analyze the type of signals we believe could have affected the classifier in distinguishing the case samples from the control set. © 2017 Wiley Periodicals, Inc.

  20. 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.

  1. DeepQA: improving the estimation of single protein model quality with deep belief networks.

    Science.gov (United States)

    Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

    2016-12-05

    Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. We introduce a novel single-model quality assessment method DeepQA based on deep belief network that utilizes a number of selected features describing the quality of a model from different perspectives, such as energy, physio-chemical characteristics, and structural information. The deep belief network is trained on several large datasets consisting of models from the Critical Assessment of Protein Structure Prediction (CASP) experiments, several publicly available datasets, and models generated by our in-house ab initio method. Our experiments demonstrate that deep belief network has better performance compared to Support Vector Machines and Neural Networks on the protein model quality assessment problem, and our method DeepQA achieves the state-of-the-art performance on CASP11 dataset. It also outperformed two well-established methods in selecting good outlier models from a large set of models of mostly low quality generated by ab initio modeling methods. DeepQA is a useful deep learning tool for protein single model quality assessment and protein structure prediction. The source code, executable, document and training/test datasets of DeepQA for Linux is freely available to non-commercial users at http://cactus.rnet.missouri.edu/DeepQA/ .

  2. Development of Deep-tow Autonomous Cable Seismic (ACS) for Seafloor Massive Sulfides (SMSs) Exploration.

    Science.gov (United States)

    Asakawa, Eiichi; Murakami, Fumitoshi; Tsukahara, Hitoshi; Saito, Shutaro; Lee, Sangkyun; Tara, Kenji; Kato, Masafumi; Jamali Hondori, Ehsan; Sumi, Tomonori; Kadoshima, Kazuyuki; Kose, Masami

    2017-04-01

    Within the EEZ of Japan, numerous surveys exploring ocean floor resources have been conducted. The exploration targets are gas hydrates, mineral resources (manganese, cobalt or rare earth) and especially seafloor massive sulphide (SMS) deposits. These resources exist in shallow subsurface areas in deep waters (>1500m). For seismic explorations very high resolution images are required. These cannot be effectively obtained with conventional marine seismic techniques. Therefore we have been developing autonomous seismic survey systems which record the data close to the seafloor to preserve high frequency seismic energy. Very high sampling rate (10kHz) and high accurate synchronization between recording systems and shot time are necessary. We adopted Cs-base atomic clock considering its power consumption. At first, we developed a Vertical Cable Seismic (VCS) system that uses hydrophone arrays moored vertically from the ocean bottom to record close to the target area. This system has been successfully applied to SMS exploration. Specifically it fixed over known sites to assess the amount of reserves with the resultant 3D volume. Based on the success of VCS, we modified the VCS system to use as a more efficient deep-tow seismic survey system. Although there are other examples of deep-tow seismic systems, signal transmission cables present challenges in deep waters. We use our autonomous recording system to avoid these problems. Combining a high frequency piezoelectric source (Sub Bottom Profiler:SBP) that automatically shots with a constant interval, we achieve the high resolution deep-tow seismic without data transmission/power cable to the board. Although the data cannot be monitored in real-time, the towing system becomes very simple. We have carried out survey trial, which showed the systems utility as a high-resolution deep-tow seismic survey system. Furthermore, the frequency ranges of deep-towed source (SBP) and surface towed sparker are 700-2300Hz and 10-200Hz

  3. The routine use of modified Borelli's lactritmel agar (MBLA).

    Science.gov (United States)

    Kaminski, G W

    1985-07-01

    The original formula of Borelli's lactritmel agar (BLA)(3) which contains wheat flour, milk and honey, has been modified by replacing the wheat flour with dehydrated Bacto Corn Meal Agar (Difco) and by slightly altering the concentrations of the milk and honey. The modified medium (MBLA) is less turbid, less particulate, and easier to prepare than BLA. Although Trichophyton rubrum usually produces a wine-red pigment with BLA, most strains initially produce a yellow pigment, with the red pigment developing later. The corn meal in MBLA reduces this tendency and stimulates the early formation of deep wine red pigment, MBLA enhances sporulation of dermatophytes and various fungi which fail to sporulate on other media, and maintains characteristic growth without developing pleomorphic degeneration. It has been used routinely since 1972 as a reliable aid to the differentiation of T. rubrum and T. mentagrophytes. Since 1975 selective MBLA has been used as a routine primary isolation medium for dermatophytes, and has proved to be most useful.

  4. Deep sedation during pneumatic reduction of intussusception.

    Science.gov (United States)

    Ilivitzki, Anat; Shtark, Luda Glozman; Arish, Karin; Engel, Ahuva

    2012-05-01

    Pneumatic reduction of intussusception under fluoroscopic guidance is a routine procedure. The unsedated child may resist the procedure, which may lengthen its duration and increase the radiation dose. We use deep sedation during the procedure to overcome these difficulties. The purpose of this study was to summarize our experience with deep sedation during fluoroscopic reduction of intussusception and assess the added value and complication rate of deep sedation. All children with intussusception who underwent pneumatic reduction in our hospital between January 2004 and June 2011 were included in this retrospective study. Anesthetists sedated the children using propofol. The fluoroscopic studies, ultrasound (US) studies and the childrens' charts were reviewed. One hundred thirty-one attempted reductions were performed in 119 children, of which 121 (92%) were successful and 10 (8%) failed. Two perforations (1.5%) occurred during attempted reduction. Average fluoroscopic time was 1.5 minutes. No complication to sedation was recorded. Deep sedation with propofol did not add any complication to the pneumatic reduction. The fluoroscopic time was short. The success rate of reduction was high,raising the possibility that sedation is beneficial, possibly by smooth muscle relaxation.

  5. Evaluation of Deep Discount Fare Strategies

    Science.gov (United States)

    1995-08-01

    This report evaluates the success of a fare pricing strategy known as deep discounting, that entails the bulk sale of transit tickets or tokens to customers at a significant discount compared to the full fare single ticket price. This market-driven s...

  6. Parity violation in deep inelastic scattering

    Energy Technology Data Exchange (ETDEWEB)

    Souder, P. [Syracuse Univ., NY (United States)

    1994-04-01

    AA beam of polarized electrons at CEBAF with an energy of 8 GeV or more will be useful for performing precision measurements of parity violation in deep inelastic scattering. Possible applications include precision tests of the Standard Model, model-independent measurements of parton distribution functions, and studies of quark correlations.

  7. Into the depths of deep eutectic solvents

    NARCIS (Netherlands)

    Rodriguez, N.; Alves da Rocha, M.A.; Kroon, M.C.

    2015-01-01

    Ionic liquids (ILs) have been successfully tested in a wide range of applications; however, their high price and complicated synthesis make them infeasible for large scale implementation. A decade ago, a new generation of solvents so called deep eutectic solvents (DESs) was reported for the first

  8. Modern problems of deep processing of coal

    International Nuclear Information System (INIS)

    Ismagilov, Z.R.

    2013-01-01

    Present article is devoted to modern problems of deep processing of coal. The history and development of new Institute of Coal Chemistry and Material Sciences of Siberian Branch of Russian Academy of Science was described. The aims and purposes of new institute were discussed.

  9. Case Studies and Monitoring of Deep Excavations

    NARCIS (Netherlands)

    Korff, M.

    2017-01-01

    Several case histories from Dutch underground deep excavation projects are presented in this paper, including the lessons learned and the learning processes involved. The focus of the paper is on how the learning takes places and how it is documented. It is necessary to learn in a systematic and

  10. Performance of deep geothermal energy systems

    Science.gov (United States)

    Manikonda, Nikhil

    Geothermal energy is an important source of clean and renewable energy. This project deals with the study of deep geothermal power plants for the generation of electricity. The design involves the extraction of heat from the Earth and its conversion into electricity. This is performed by allowing fluid deep into the Earth where it gets heated due to the surrounding rock. The fluid gets vaporized and returns to the surface in a heat pipe. Finally, the energy of the fluid is converted into electricity using turbine or organic rankine cycle (ORC). The main feature of the system is the employment of side channels to increase the amount of thermal energy extracted. A finite difference computer model is developed to solve the heat transport equation. The numerical model was employed to evaluate the performance of the design. The major goal was to optimize the output power as a function of parameters such as thermal diffusivity of the rock, depth of the main well, number and length of lateral channels. The sustainable lifetime of the system for a target output power of 2 MW has been calculated for deep geothermal systems with drilling depths of 8000 and 10000 meters, and a financial analysis has been performed to evaluate the economic feasibility of the system for a practical range of geothermal parameters. Results show promising an outlook for deep geothermal systems for practical applications.

  11. Fingerprint Minutiae Extraction using Deep Learning

    CSIR Research Space (South Africa)

    Darlow, Luke Nicholas

    2017-10-01

    Full Text Available components, such as image enhancement. We pose minutiae extraction as a machine learning problem and propose a deep neural network – MENet, for Minutiae Extraction Network – to learn a data-driven representation of minutiae points. By using the existing...

  12. Evolutionary Scheduler for the Deep Space Network

    Science.gov (United States)

    Guillaume, Alexandre; Lee, Seungwon; Wang, Yeou-Fang; Zheng, Hua; Chau, Savio; Tung, Yu-Wen; Terrile, Richard J.; Hovden, Robert

    2010-01-01

    A computer program assists human schedulers in satisfying, to the maximum extent possible, competing demands from multiple spacecraft missions for utilization of the transmitting/receiving Earth stations of NASA s Deep Space Network. The program embodies a concept of optimal scheduling to attain multiple objectives in the presence of multiple constraints.

  13. Deep Water Coral (HB1402, EK60)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The cruise will survey and collect samples of deep-sea corals and related marine life in the canyons in the northern Gulf of Maine in U.S. and Canadian waters. The...

  14. Particle Production in Deep Inelastic Muon Scattering

    Energy Technology Data Exchange (ETDEWEB)

    Ryan, John James [MIT

    1991-01-01

    The E665 spectrometer at Fermila.b measured Deep-Inelastic Scattering of 490 GeV /c muons off several targets: Hydrogen, Deuterium, and Xenon. Events were selected from the Xenon and Deuterium targets, with a range of energy exchange, $\

  15. Influence functionals in deep inelastic reactions

    International Nuclear Information System (INIS)

    Avishai, Y.

    1978-01-01

    It is suggested that the concept of influence functionals introduced by Feynman and Vernon could be applied to the study of deep inelastic reactions among heavy ions if the coupling between the relative motion and the internal degrees of freedom has a separable form as suggested by Hofmann and Siemens. (Auth.)

  16. Optimizing interplanetary trajectories with deep space maneuvers

    Science.gov (United States)

    Navagh, John

    1993-09-01

    Analysis of interplanetary trajectories is a crucial area for both manned and unmanned missions of the Space Exploration Initiative. A deep space maneuver (DSM) can improve a trajectory in much the same way as a planetary swingby. However, instead of using a gravitational field to alter the trajectory, the on-board propulsion system of the spacecraft is used when the vehicle is not near a planet. The purpose is to develop an algorithm to determine where and when to use deep space maneuvers to reduce the cost of a trajectory. The approach taken to solve this problem uses primer vector theory in combination with a non-linear optimizing program to minimize Delta(V). A set of necessary conditions on the primer vector is shown to indicate whether a deep space maneuver will be beneficial. Deep space maneuvers are applied to a round trip mission to Mars to determine their effect on the launch opportunities. Other studies which were performed include cycler trajectories and Mars mission abort scenarios. It was found that the software developed was able to locate quickly DSM's which lower the total Delta(V) on these trajectories.

  17. Deep learning for studies of galaxy morphology

    Science.gov (United States)

    Tuccillo, D.; Huertas-Company, M.; Decencière, E.; Velasco-Forero, S.

    2017-06-01

    Establishing accurate morphological measurements of galaxies in a reasonable amount of time for future big-data surveys such as EUCLID, the Large Synoptic Survey Telescope or the Wide Field Infrared Survey Telescope is a challenge. Because of its high level of abstraction with little human intervention, deep learning appears to be a promising approach. Deep learning is a rapidly growing discipline that models high-level patterns in data as complex multilayered networks. In this work we test the ability of deep convolutional networks to provide parametric properties of Hubble Space Telescope like galaxies (half-light radii, Sérsic indices, total flux etc..). We simulate a set of galaxies including point spread function and realistic noise from the CANDELS survey and try to recover the main galaxy parameters using deep-learning. We compare the results with the ones obtained with the commonly used profile fitting based software GALFIT. This way showing that with our method we obtain results at least equally good as the ones obtained with GALFIT but, once trained, with a factor 5 hundred time faster.

  18. Pre-cementation of deep shaft

    Science.gov (United States)

    Heinz, W. F.

    1988-12-01

    Pre-cementation or pre-grouting of deep shafts in South Africa is an established technique to improve safety and reduce water ingress during shaft sinking. The recent completion of several pre-cementation projects for shafts deeper than 1000m has once again highlighted the effectiveness of pre-grouting of shafts utilizing deep slimline boreholes and incorporating wireline technique for drilling and conventional deep borehole grouting techniques for pre-cementation. Pre-cementation of deep shaft will: (i) Increase the safety of shaft sinking operation (ii) Minimize water and gas inflow during shaft sinking (iii) Minimize the time lost due to additional grouting operations during sinking of the shaft and hence minimize costly delays and standing time of shaft sinking crews and equipment. (iv) Provide detailed information of the geology of the proposed shaft site. Informations on anomalies, dykes, faults as well as reef (gold bearing conglomerates) intersections can be obtained from the evaluation of cores of the pre-cementation boreholes. (v) Provide improved rock strength for excavations in the immediate vicinity of the shaft area. The paper describes pre-cementation techniques recently applied successfully from surface and some conclusions drawn for further considerations.

  19. Should deep seabed mining be allowed?

    NARCIS (Netherlands)

    Kim, Rak

    2017-01-01

    Abstract Commercial interest in deep sea minerals in the area beyond the limits of national jurisdiction has rapidly increased in recent years. The International Seabed Authority has already given out 26 exploration contracts and it is currently in the process of developing the Mining Code for

  20. Dust Measurements Onboard the Deep Space Gateway

    Science.gov (United States)

    Horanyi, M.; Kempf, S.; Malaspina, D.; Poppe, A.; Srama, R.; Sternovsky, Z.; Szalay, J.

    2018-02-01

    A dust instrument onboard the Deep Space Gateway will revolutionize our understanding of the dust environment at 1 AU, help our understanding of the evolution of the solar system, and improve dust hazard models for the safety of crewed and robotic missions.

  1. A quantitative lubricant test for deep drawing

    DEFF Research Database (Denmark)

    Olsson, David Dam; Bay, Niels; Andreasen, Jan L.

    2010-01-01

    A tribological test for deep drawing has been developed by which the performance of lubricants may be evaluated quantitatively measuring the maximum backstroke force on the punch owing to friction between tool and workpiece surface. The forming force is found not to give useful information...

  2. Deep underground disposal facility and the public

    International Nuclear Information System (INIS)

    Sumberova, V.

    1997-01-01

    Factors arousing public anxiety in relation to the deep burial of radioactive wastes are highlighted based on Czech and foreign analyses, and guidelines are presented to minimize public opposition when planning a geologic disposal site in the Czech Republic. (P.A.)

  3. Emotional arousal and memory after deep encoding.

    Science.gov (United States)

    Leventon, Jacqueline S; Camacho, Gabriela L; Ramos Rojas, Maria D; Ruedas, Angelica

    2018-05-22

    Emotion often enhances long-term memory. One mechanism for this enhancement is heightened arousal during encoding. However, reducing arousal, via emotion regulation (ER) instructions, has not been associated with reduced memory. In fact, the opposite pattern has been observed: stronger memory for emotional stimuli encoded with an ER instruction to reduce arousal. This pattern may be due to deeper encoding required by ER instructions. In the current research, we examine the effects of emotional arousal and deep-encoding on memory across three studies. In Study 1, adult participants completed a writing task (deep-encoding) for encoding negative, neutral, and positive picture stimuli, whereby half the emotion stimuli had the ER instruction to reduce the emotion. Memory was strong across conditions, and no memory enhancement was observed for any condition. In Study 2, adult participants completed the same writing task as Study 1, as well as a shallow-encoding task for one-third of negative, neutral, and positive trials. Memory was strongest for deep vs. shallow encoding trials, with no effects of emotion or ER instruction. In Study 3, adult participants completed a shallow-encoding task for negative, neutral, and positive stimuli, with findings indicating enhanced memory for negative emotional stimuli. Findings suggest that deep encoding must be acknowledged as a source of memory enhancement when examining manipulations of emotion-related arousal. Copyright © 2018. Published by Elsevier B.V.

  4. Coherence effects in deep inelastic scattering

    International Nuclear Information System (INIS)

    Andersson, B.; Gustafson, G.; Loennblad, L.; Pettersson, U.

    1988-09-01

    We present a framework for deep inelastic scattering, with bound state properties in accordance with a QCD force field acting like a vortex line in a colour superconducting vacuum, which implies some simple coherence effects. Within this scheme one may describe the results of present energies very well, but one obtains an appreciable depletion of gluon radiation in the HERA energy regime. (authors)

  5. Regulatory issues for deep borehole plutonium disposition

    International Nuclear Information System (INIS)

    Halsey, W.G.

    1995-03-01

    As a result of recent changes throughout the world, a substantial inventory of excess separated plutonium is expected to result from dismantlement of US nuclear weapons. The safe and secure management and eventual disposition of this plutonium, and of a similar inventory in Russia, is a high priority. A variety of options (both interim and permanent) are under consideration to manage this material. The permanent solutions can be categorized into two broad groups: direct disposal and utilization. The deep borehole disposition concept involves placing excess plutonium deep into old stable rock formations with little free water present. Issues of concern include the regulatory, statutory and policy status of such a facility, the availability of sites with desirable characteristics and the technologies required for drilling deep holes, characterizing them, emplacing excess plutonium and sealing the holes. This white paper discusses the regulatory issues. Regulatory issues concerning construction, operation and decommissioning of the surface facility do not appear to be controversial, with existing regulations providing adequate coverage. It is in the areas of siting, licensing and long term environmental protection that current regulations may be inappropriate. This is because many current regulations are by intent or by default specific to waste forms, facilities or missions significantly different from deep borehole disposition of excess weapons usable fissile material. It is expected that custom regulations can be evolved in the context of this mission

  6. Deep Reflection on My Pedagogical Transformations

    Science.gov (United States)

    Suzawa, Gilbert S.

    2014-01-01

    This retrospective essay contains my reflection on the deep concept of ambiguity (uncertainty) and a concomitant epistemological theory that all of our human knowledge is ultimately self-referential in nature. This new epistemological perspective is subsequently utilized as a platform for gaining insights into my experiences in conjunction with…

  7. North Jamaican Deep Fore-Reef Sponges

    NARCIS (Netherlands)

    Lehnert, Helmut; Soest, van R.W.M.

    1996-01-01

    An unexpectedly high amount of new species, revealed within only one hour of summarized bottom time, leads to the conclusion that the sponge fauna of the steep slopes of the deep fore-reef is still largely unknown. Four mixed gas dives at depths between 70 and 90 m, performed in May and June, 1993,

  8. Top Tagging by Deep Learning Algorithm

    CERN Document Server

    Akil, Ali

    2015-01-01

    In this report I will show the application of a deep learning algorithm on a Monte Carlo simulation sample to test its performance in tagging hadronic decays of boosted top quarks and compare what we get with the results of the application of some other algorithms.

  9. Semantic Tagging with Deep Residual Networks

    NARCIS (Netherlands)

    Bjerva, Johannes; Plank, Barbara; Bos, Johan

    2016-01-01

    We propose a novel semantic tagging task, semtagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets). Our tagger uses both word and character representations and includes a novel residual bypass architecture. We evaluate

  10. Priapulus from the deep sea (Vermes, Priapulida)

    NARCIS (Netherlands)

    Land, van der J.

    1972-01-01

    INTRODUCTION The species of the genus Priapulus occur in rather cold water. Hence, their shallow-water distribution is restricted to northern and southern waters (fig. 1); there are only a few isolated records from sub-tropical localities. However, in deep water the genus apparently has a world-wide

  11. Gamma-rays from deep inelastic collisions

    International Nuclear Information System (INIS)

    Stephens, F.S.

    1981-01-01

    My objective in this talk is to consider the question: 'What can be learned about deep inelastic collisions (DIC) from studying the associated gamma-rays'. First, I discuss the origin and nature of the gamma-rays from DIC, then the kinds of information gamma-ray spectra contain, and finally come to the combination of these two subjects. (orig./HSI)

  12. Deep Support Vector Machines for Regression Problems

    NARCIS (Netherlands)

    Wiering, Marco; Schutten, Marten; Millea, Adrian; Meijster, Arnold; Schomaker, Lambertus

    2013-01-01

    In this paper we describe a novel extension of the support vector machine, called the deep support vector machine (DSVM). The original SVM has a single layer with kernel functions and is therefore a shallow model. The DSVM can use an arbitrary number of layers, in which lower-level layers contain

  13. Using Cooperative Structures to Promote Deep Learning

    Science.gov (United States)

    Millis, Barbara J.

    2014-01-01

    The author explores concrete ways to help students learn more and have fun doing it while they support each other's learning. The article specifically shows the relationships between cooperative learning and deep learning. Readers will become familiar with the tenets of cooperative learning and its power to enhance learning--even more so when…

  14. Stimulating Deep Learning Using Active Learning Techniques

    Science.gov (United States)

    Yew, Tee Meng; Dawood, Fauziah K. P.; a/p S. Narayansany, Kannaki; a/p Palaniappa Manickam, M. Kamala; Jen, Leong Siok; Hoay, Kuan Chin

    2016-01-01

    When students and teachers behave in ways that reinforce learning as a spectator sport, the result can often be a classroom and overall learning environment that is mostly limited to transmission of information and rote learning rather than deep approaches towards meaningful construction and application of knowledge. A group of college instructors…

  15. Survey on deep learning for radiotherapy.

    Science.gov (United States)

    Meyer, Philippe; Noblet, Vincent; Mazzara, Christophe; Lallement, Alex

    2018-05-17

    More than 50% of cancer patients are treated with radiotherapy, either exclusively or in combination with other methods. The planning and delivery of radiotherapy treatment is a complex process, but can now be greatly facilitated by artificial intelligence technology. Deep learning is the fastest-growing field in artificial intelligence and has been successfully used in recent years in many domains, including medicine. In this article, we first explain the concept of deep learning, addressing it in the broader context of machine learning. The most common network architectures are presented, with a more specific focus on convolutional neural networks. We then present a review of the published works on deep learning methods that can be applied to radiotherapy, which are classified into seven categories related to the patient workflow, and can provide some insights of potential future applications. We have attempted to make this paper accessible to both radiotherapy and deep learning communities, and hope that it will inspire new collaborations between these two communities to develop dedicated radiotherapy applications. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. Pathways to deep decarbonization in India

    DEFF Research Database (Denmark)

    Shukla, P.; Dhar, Subash; Pathak, Minal

    This report is a part of the global Deep Decarbonisation Pathways (DDP) Project. The analysis consider two development scenarios for India and assess alternate roadmaps for transiting to a low carbon economy consistent with the globally agreed 2°C stabilization target. The report does not conside...

  17. Pressure induced deep tissue injury explained

    NARCIS (Netherlands)

    Oomens, C.W.J.; Bader, D.L.; Loerakker, S.; Baaijens, F.P.T.

    The paper describes the current views on the cause of a sub-class of pressure ulcers known as pressure induced deep tissue injury (DTI). A multi-scale approach was adopted using model systems ranging from single cells in culture, tissue engineered muscle to animal studies with small animals. This

  18. 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

  19. Mean associated multiplicities in deep inelastic processes

    International Nuclear Information System (INIS)

    Dzhaparidze, G.Sh.; Kiselev, A.V.; Petrov, V.A.

    1982-01-01

    A formula is derived for the mean hadron multiplicity in the target fragmentation range of deep inelastic scattering processes. It is shown that in the high-x region the ratio of the mean multiplicities in the current fragmentation region and in the target fragmentation region tends to unity at high energies. The mean multiplicity for the Drell-Yan process is considered

  20. 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.

  1. Predicting galling behaviour in deep drawing processes

    NARCIS (Netherlands)

    van der Linde, G.

    2011-01-01

    Deep drawing is a sheet metal forming process which is widely used in, for example, the automotive industry. With this process it is possible to form complex shaped parts of sheet metal and it is suitable for products that have to be produced in large numbers. The tools for this process are required

  2. Deep Belief Networks for dimensionality reduction

    NARCIS (Netherlands)

    Noulas, A.K.; Kröse, B.J.A.

    2008-01-01

    Deep Belief Networks are probabilistic generative models which are composed by multiple layers of latent stochastic variables. The top two layers have symmetric undirected connections, while the lower layers receive directed top-down connections from the layer above. The current state-of-the-art

  3. On mechanism of metals modifying

    International Nuclear Information System (INIS)

    Chernov, V.S.; Busol, F.I.

    1975-01-01

    Data from the literature are cited to show that in several cases, the mechanism of modification of metals and alloys by additives soluble in the melt cannot be explained by the adsorption hypothesis based on the surface activity of these additives. It is suggested that the mechanism of modification by soluble additives can be explained by the presence of a layer of liquid enriched (or depleted) in the additives preceding the crystallization front (densification by concentration), formed under actual conditions of crystallization as a result of the different solubilities of the additive in the solid and liquid phases of the base metal, regardless of its surface activity. This densification by concentration leads to the inhibition of crystal growth in the base metal (barrier action) and to concentration overcooling. On the basis of this theory it is suggested that the modifying action of additives can be predicted from some parameters of the phase diagrams. (author)

  4. Modified Aggressive Packet Combining Scheme

    International Nuclear Information System (INIS)

    Bhunia, C.T.

    2010-06-01

    In this letter, a few schemes are presented to improve the performance of aggressive packet combining scheme (APC). To combat error in computer/data communication networks, ARQ (Automatic Repeat Request) techniques are used. Several modifications to improve the performance of ARQ are suggested by recent research and are found in literature. The important modifications are majority packet combining scheme (MjPC proposed by Wicker), packet combining scheme (PC proposed by Chakraborty), modified packet combining scheme (MPC proposed by Bhunia), and packet reversed packet combining (PRPC proposed by Bhunia) scheme. These modifications are appropriate for improving throughput of conventional ARQ protocols. Leung proposed an idea of APC for error control in wireless networks with the basic objective of error control in uplink wireless data network. We suggest a few modifications of APC to improve its performance in terms of higher throughput, lower delay and higher error correction capability. (author)

  5. Genetically Modified Foods and Nutrition

    Directory of Open Access Journals (Sweden)

    Reci MESERI

    2008-10-01

    Full Text Available To consume a balanced diet may prevent many illnesses. After the Second World War the “Green Revolution” was conducted to increase efficiency in agriculture. After its harmful effects on environment were understood genetically modified foods (GMO were served to combat hunger in the world. Today insufficiency in food product is not the main problem; imbalanced food distribution is the problem. In addition, GMO’s might be harmful for health and environment. Moreover economical dependency to industrialized countries will carry on. If the community tends to use up all the sources and the population increases steadily hunger will not be the only scarcity that the human population would face. There will also be shortage in energy and clean water resources. In conclusion combating just with hunger using high technology will only postpone the problems for a short period of time. [TAF Prev Med Bull 2008; 7(5.000: 455-460

  6. The Modified Embedded Atom Method

    Energy Technology Data Exchange (ETDEWEB)

    Baskes, M.I.

    1994-08-01

    Recent modifications have been made to generalize the Embedded Atom Method (EAM) to describe bonding in diverse materials. By including angular dependence of the electron density in an empirical way, the Modified Embedded Atom Method (MEAM) has been able to reproduce the basic energetic and structural properties of 45 elements. This method is ideal for examining interfacial behavior of dissimilar materials. This paper explains in detail the derivation of the method, shows how parameters of MEAM are determined directly from experiment or first principles calculations, and examine the quality of the reproduction of the database. Materials with fcc, bcc, hcp, and diamond cubic crystal structure are discussed. A few simple examples of the application of the MEAM to surfaces and interfaces are presented. Calculations of pullout of a SiC fiber in a diamond matrix as a function of applied stress show nonuniform deformation of the fiber.

  7. DRREP: deep ridge regressed epitope predictor.

    Science.gov (United States)

    Sher, Gene; Zhi, Degui; Zhang, Shaojie

    2017-10-03

    The ability to predict epitopes plays an enormous role in vaccine development in terms of our ability to zero in on where to do a more thorough in-vivo analysis of the protein in question. Though for the past decade there have been numerous advancements and improvements in epitope prediction, on average the best benchmark prediction accuracies are still only around 60%. New machine learning algorithms have arisen within the domain of deep learning, text mining, and convolutional networks. This paper presents a novel analytically trained and string kernel using deep neural network, which is tailored for continuous epitope prediction, called: Deep Ridge Regressed Epitope Predictor (DRREP). DRREP was tested on long protein sequences from the following datasets: SARS, Pellequer, HIV, AntiJen, and SEQ194. DRREP was compared to numerous state of the art epitope predictors, including the most recently published predictors called LBtope and DMNLBE. Using area under ROC curve (AUC), DRREP achieved a performance improvement over the best performing predictors on SARS (13.7%), HIV (8.9%), Pellequer (1.5%), and SEQ194 (3.1%), with its performance being matched only on the AntiJen dataset, by the LBtope predictor, where both DRREP and LBtope achieved an AUC of 0.702. DRREP is an analytically trained deep neural network, thus capable of learning in a single step through regression. By combining the features of deep learning, string kernels, and convolutional networks, the system is able to perform residue-by-residue prediction of continues epitopes with higher accuracy than the current state of the art predictors.

  8. Linking white matter and deep gray matter alterations in premanifest Huntington disease

    Directory of Open Access Journals (Sweden)

    Andreia V. Faria

    2016-01-01

    Full Text Available Huntington disease (HD is a fatal progressive neurodegenerative disorder for which only symptomatic treatment is available. A better understanding of the pathology, and identification of biomarkers will facilitate the development of disease-modifying treatments. HD is potentially a good model of a neurodegenerative disease for development of biomarkers because it is an autosomal-dominant disease with complete penetrance, caused by a single gene mutation, in which the neurodegenerative process can be assessed many years before onset of signs and symptoms of manifest disease. Previous MRI studies have detected abnormalities in gray and white matter starting in premanifest stages. However, the understanding of how these abnormalities are related, both in time and space, is still incomplete. In this study, we combined deep gray matter shape diffeomorphometry and white matter DTI analysis in order to provide a better mapping of pathology in the deep gray matter and subcortical white matter in premanifest HD. We used 296 MRI scans from the PREDICT-HD database. Atrophy in the deep gray matter, thalamus, hippocampus, and nucleus accumbens was analyzed by surface based morphometry, and while white matter abnormalities were analyzed in (i regions of interest surrounding these structures, using (ii tractography-based analysis, and using (iii whole brain atlas-based analysis. We detected atrophy in the deep gray matter, particularly in putamen, from early premanifest stages. The atrophy was greater both in extent and effect size in cases with longer exposure to the effects of the CAG expansion mutation (as assessed by greater CAP-scores, and preceded detectible abnormalities in the white matter. Near the predicted onset of manifest HD, the MD increase was widespread, with highest indices in the deep and posterior white matter. This type of in-vivo macroscopic mapping of HD brain abnormalities can potentially indicate when and where therapeutics could be

  9. DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

    Science.gov (United States)

    Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

    2018-02-01

    Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The

  10. DeepQA: Improving the estimation of single protein model quality with deep belief networks

    OpenAIRE

    Cao, Renzhi; Bhattacharya, Debswapna; Hou, Jie; Cheng, Jianlin

    2016-01-01

    Background Protein quality assessment (QA) useful for ranking and selecting protein models has long been viewed as one of the major challenges for protein tertiary structure prediction. Especially, estimating the quality of a single protein model, which is important for selecting a few good models out of a large model pool consisting of mostly low-quality models, is still a largely unsolved problem. Results We introduce a novel single-model quality assessment method DeepQA based on deep belie...

  11. Deep Galaxy: Classification of Galaxies based on Deep Convolutional Neural Networks

    OpenAIRE

    Khalifa, Nour Eldeen M.; Taha, Mohamed Hamed N.; Hassanien, Aboul Ella; Selim, I. M.

    2017-01-01

    In this paper, a deep convolutional neural network architecture for galaxies classification is presented. The galaxy can be classified based on its features into main three categories Elliptical, Spiral, and Irregular. The proposed deep galaxies architecture consists of 8 layers, one main convolutional layer for features extraction with 96 filters, followed by two principles fully connected layers for classification. It is trained over 1356 images and achieved 97.272% in testing accuracy. A c...

  12. Combining shallow and deep processing for a robust, fast, deep-linguistic dependency parser

    OpenAIRE

    Schneider, G

    2004-01-01

    This paper describes Pro3Gres, a fast, robust, broad-coverage parser that delivers deep-linguistic grammatical relation structures as output, which are closer to predicate-argument structures and more informative than pure constituency structures. The parser stays as shallow as is possible for each task, combining shallow and deep-linguistic methods by integrating chunking and by expressing the majority of long-distance dependencies in a context-free way. It combines statistical and rule-base...

  13. New optimized drill pipe size for deep-water, extended reach and ultra-deep drilling

    Energy Technology Data Exchange (ETDEWEB)

    Jellison, Michael J.; Delgado, Ivanni [Grant Prideco, Inc., Hoston, TX (United States); Falcao, Jose Luiz; Sato, Ademar Takashi [PETROBRAS, Rio de Janeiro, RJ (Brazil); Moura, Carlos Amsler [Comercial Perfuradora Delba Baiana Ltda., Rio de Janeiro, RJ (Brazil)

    2004-07-01

    A new drill pipe size, 5-7/8 in. OD, represents enabling technology for Extended Reach Drilling (ERD), deep water and other deep well applications. Most world-class ERD and deep water wells have traditionally been drilled with 5-1/2 in. drill pipe or a combination of 6-5/8 in. and 5-1/2 in. drill pipe. The hydraulic performance of 5-1/2 in. drill pipe can be a major limitation in substantial ERD and deep water wells resulting in poor cuttings removal, slower penetration rates, diminished control over well trajectory and more tendency for drill pipe sticking. The 5-7/8 in. drill pipe provides a significant improvement in hydraulic efficiency compared to 5-1/2 in. drill pipe and does not suffer from the disadvantages associated with use of 6-5/8 in. drill pipe. It represents a drill pipe assembly that is optimized dimensionally and on a performance basis for casing and bit programs that are commonly used for ERD, deep water and ultra-deep wells. The paper discusses the engineering philosophy behind 5-7/8 in. drill pipe, the design challenges associated with development of the product and reviews the features and capabilities of the second-generation double-shoulder connection. The paper provides drilling case history information on significant projects where the pipe has been used and details results achieved with the pipe. (author)

  14. The hadronic final state in deep inelastic scattering at HERA

    International Nuclear Information System (INIS)

    Lanius, P.

    1994-10-01

    Global properties of the hadronic final state of deep inelastic scattering events recorded in 1992 with the H1 detector at HERA, are investigated. The data are corrected for detector effects and can be compared directly with QCD phenomenology and calculations based on BFKL dynamics. The measurement of the energy flows in the laboratory frame and in the hadronic centre of mass system reveal large discrepancies between the data and the different model predictions, indicating the failure of models based on Altarelli-Parisi evolution at low χ. However, these energy flow results are found to agree fairly well with theoretical predictions derived from Lipatov (BFKL) evolution. In the hadronic centre of mass frame the longitudinal and transverse momentum components of charged particles are measured. The longitudinal component exhibits scaling with W and allows comparison with lower energy lepton-nucleon scattering data as well as with e + e - data from LEP. For the 1993 data, studies of the charged particle energy spectra in the Breit frame are undertaken. This measurement allows a first tentative look at predictions from the Modified Leading Logarithmic Approximation for the target region, a region that to-date unexplored has been unexplored. (orig.)

  15. Acrylamide in deep-fried snacks of India.

    Science.gov (United States)

    Shamla, L; Nisha, P

    2014-01-01

    Acrylamide content in deep-fried snacks from 20 different production sites of South Indian province of Kerala (80 samples representing 4 important product categories) were determined using a modified high performance liquid chromatography (HPLC)-diode array detector (DAD) method. The limit of detection and the limit of quantification for this method were 1.04 and 3.17 μg/kg, respectively. The mean recoveries of acrylamide obtained by using spiked samples ranged between 90% and 103%, which shows good extraction efficiency. Acrylamide concentrations in the four groups of snacks ranged from 82.0 to 4245.6 µg/kg for potato chips, 46.2-2431.4 µg/kg for jack chips, 24.8-1959.8 µg/kg for sweet plantain chips and 14.7-1690.5 µg/kg for plantain chips. These are the most widely consumed snacks in South India, and the results revealed reasonable levels of acrylamide in these foods, which indicated the general risk of consumer exposure.

  16. Deep-Sea Corals: A New Oceanic Archive

    National Research Council Canada - National Science Library

    Adkins, Jess

    1998-01-01

    Deep-sea corals are an extraordinary new archive of deep ocean behavior. The species Desmophyllum cristagalli is a solitary coral composed of uranium rich, density banded aragonite that I have calibrated for several paleoclimate tracers...

  17. The development of deep learning in synthetic aperture radar imagery

    CSIR Research Space (South Africa)

    Schwegmann, Colin P

    2017-05-01

    Full Text Available sensing techniques but comes at the price of additional complexities. To adequately cope with these, researchers have begun to employ advanced machine learning techniques known as deep learning to Synthetic Aperture Radar data. Deep learning represents...

  18. Minimally invasive trans-portal resection of deep intracranial lesions.

    NARCIS (Netherlands)

    Raza, S.M.; Recinos, P.F.; Avendano, J.; Adams, H.; Jallo, G.I.; Quinones-Hinojosa, A.

    2011-01-01

    BACKGROUND: The surgical management of deep intra-axial lesions still requires microsurgical approaches that utilize retraction of deep white matter to obtain adequate visualization. We report our experience with a new tubular retractor system, designed specifically for intracranial applications,

  19. Extreme Longevity in Proteinaceous Deep-Sea Corals

    Energy Technology Data Exchange (ETDEWEB)

    Roark, E B; Guilderson, T P; Dunbar, R B; Fallon, S J; Mucciarone, D A

    2009-02-09

    Deep-sea corals are found on hard substrates on seamounts and continental margins world-wide at depths of 300 to {approx}3000 meters. Deep-sea coral communities are hotspots of deep ocean biomass and biodiversity, providing critical habitat for fish and invertebrates. Newly applied radiocarbon age date from the deep water proteinaceous corals Gerardia sp. and Leiopathes glaberrima show that radial growth rates are as low as 4 to 35 {micro}m yr{sup -1} and that individual colony longevities are on the order of thousands of years. The management and conservation of deep sea coral communities is challenged by their commercial harvest for the jewelry trade and damage caused by deep water fishing practices. In light of their unusual longevity, a better understanding of deep sea coral ecology and their interrelationships with associated benthic communities is needed to inform coherent international conservation strategies for these important deep-sea ecosystems.

  20. Assessing Deep Sea Communities Through Seabed Imagery

    Science.gov (United States)

    Matkin, A. G.; Cross, K.; Milititsky, M.

    2016-02-01

    The deep sea still remains virtually unexplored. Human activity, such as oil and gas exploration and deep sea mining, is expanding further into the deep sea, increasing the need to survey and map extensive areas of this habitat in order to assess ecosystem health and value. The technology needed to explore this remote environment has been advancing. Seabed imagery can cover extensive areas of the seafloor and investigate areas where sampling with traditional coring methodologies is just not possible (e.g. cold water coral reefs). Remotely operated vehicles (ROVs) are an expensive option, so drop or towed camera systems can provide a more viable and affordable alternative, while still allowing for real-time control. Assessment of seabed imagery in terms of presence, abundance and density of particular species can be conducted by bringing together a variety of analytical tools for a holistic approach. Sixteen deep sea transects located offshore West Africa were investigated with a towed digital video telemetry system (DTS). Both digital stills and video footage were acquired. An extensive data set was obtained from over 13,000 usable photographs, allowing for characterisation of the different habitats present in terms of community composition and abundance. All observed fauna were identified to the lowest taxonomic level and enumerated when possible, with densities derived after the seabed area was calculated for each suitable photograph. This methodology allowed for consistent assessment of the different habitat types present, overcoming constraints, such as specific taxa that cannot be enumerated, such as sponges, corals or bryozoans, the presence of mobile and sessile species, or the level of taxonomic detail. Although this methodology will not enable a full characterisation of a deep sea community, in terms of species composition for instance, itt will allow a robust assessment of large areas of the deep sea in terms of sensitive habitats present and community

  1. Microbiological characterization of deep geological compartments

    International Nuclear Information System (INIS)

    Barsotti, V.; Sergeant, C.; Vesvres, M.H.; Coulon, S.; Joulian, C.; Garrido, F.; Ollivier, B.

    2012-01-01

    Document available in extended abstract form only. Microbial life in deep sediments and Earth's crust is now acknowledged by the scientific world. The deep subsurface biosphere contributes significantly to fundamental biogeochemical processes. However, despite great advances in geo-microbiological studies, deep terrestrial ecosystems are microbiologically poorly understood, mainly due to their inaccessibility. The drilling down to the base of the Triassic (1980 meters deep) in the geological formations of the eastern Paris Basin performed by ANDRA (EST433) in 2008 provides us a good opportunity to explore the deep biosphere. We conditioned the samples on the coring site, in as aseptic conditions as possible. In addition to storage at atmospheric pressure, a portion of the four Triassic samples was placed in a 190 bars pressurized chamber to investigate the influence of the conservation pressure factor on the found microflora. In parallel, in order to evaluate a potential bacterial contamination of the cores by the drilling fluids, samples of mud just before each sample drilling were taken and analyzed. The microbial exploration can be divided in two parts: - A cultural approach in different culture media for metabolic groups as methanogens, fermenters and sulphate reducing bacteria to stimulate their growth and to isolate microbial cells still viable. - A molecular approach by direct extraction of genomic DNA from the geological samples to explore a larger biodiversity. The limits are here the difficulties to extract DNA from these low biomass containing rocks. After comparison and optimization of several DNA extraction methods, the bacterial diversity present in rock cores was analyzed using DGGE (Denaturating Gel Gradient Electrophoresis) and cloning. The detailed results of all these investigations will be presented: - Despite all 400 cultural conditions experimented (with various media, salinities, temperatures, conservation pressure, agitation), no viable and

  2. Deep Recurrent Convolutional Neural Network: Improving Performance For Speech Recognition

    OpenAIRE

    Zhang, Zewang; Sun, Zheng; Liu, Jiaqi; Chen, Jingwen; Huo, Zhao; Zhang, Xiao

    2016-01-01

    A deep learning approach has been widely applied in sequence modeling problems. In terms of automatic speech recognition (ASR), its performance has significantly been improved by increasing large speech corpus and deeper neural network. Especially, recurrent neural network and deep convolutional neural network have been applied in ASR successfully. Given the arising problem of training speed, we build a novel deep recurrent convolutional network for acoustic modeling and then apply deep resid...

  3. How to study deep roots - and why it matters

    OpenAIRE

    Maeght, Jean-Luc; Rewald, B.; Pierret, Alain

    2013-01-01

    The drivers underlying the development of deep root systems, whether genetic or environmental, are poorly understood but evidence has accumulated that deep rooting could be a more widespread and important trait among plants than commonly anticipated from their share of root biomass. Even though a distinct classification of "deep roots" is missing to date, deep roots provide important functions for individual plants such as nutrient and water uptake but can also shape plant communities by hydr...

  4. Benchmarking State-of-the-Art Deep Learning Software Tools

    OpenAIRE

    Shi, Shaohuai; Wang, Qiang; Xu, Pengfei; Chu, Xiaowen

    2016-01-01

    Deep learning has been shown as a successful machine learning method for a variety of tasks, and its popularity results in numerous open-source deep learning software tools. Training a deep network is usually a very time-consuming process. To address the computational challenge in deep learning, many tools exploit hardware features such as multi-core CPUs and many-core GPUs to shorten the training time. However, different tools exhibit different features and running performance when training ...

  5. Deep Complementary Bottleneck Features for Visual Speech Recognition

    NARCIS (Netherlands)

    Petridis, Stavros; Pantic, Maja

    Deep bottleneck features (DBNFs) have been used successfully in the past for acoustic speech recognition from audio. However, research on extracting DBNFs for visual speech recognition is very limited. In this work, we present an approach to extract deep bottleneck visual features based on deep

  6. Automatic Segmentation and Deep Learning of Bird Sounds

    NARCIS (Netherlands)

    Koops, Hendrik Vincent; Van Balen, J.M.H.; Wiering, F.

    2015-01-01

    We present a study on automatic birdsong recognition with deep neural networks using the BIRDCLEF2014 dataset. Through deep learning, feature hierarchies are learned that represent the data on several levels of abstraction. Deep learning has been applied with success to problems in fields such as

  7. An Ensemble of Deep Support Vector Machines for Image Categorization

    NARCIS (Netherlands)

    Abdullah, Azizi; Veltkamp, Remco C.; Wiering, Marco

    2009-01-01

    This paper presents the deep support vector machine (D-SVM) inspired by the increasing popularity of deep belief networks for image recognition. Our deep SVM trains an SVM in the standard way and then uses the kernel activations of support vectors as inputs for training another SVM at the next

  8. Deep brain stimulation as a functional scalpel.

    Science.gov (United States)

    Broggi, G; Franzini, A; Tringali, G; Ferroli, P; Marras, C; Romito, L; Maccagnano, E

    2006-01-01

    Since 1995, at the Istituto Nazionale Neurologico "Carlo Besta" in Milan (INNCB,) 401 deep brain electrodes were implanted to treat several drug-resistant neurological syndromes (Fig. 1). More than 200 patients are still available for follow-up and therapeutical considerations. In this paper our experience is reviewed and pioneered fields are highlighted. The reported series of patients extends the use of deep brain stimulation beyond the field of Parkinson's disease to new fields such as cluster headache, disruptive behaviour, SUNCt, epilepsy and tardive dystonia. The low complication rate, the reversibility of the procedure and the available image guided surgery tools will further increase the therapeutic applications of DBS. New therapeutical applications are expected for this functional scalpel.

  9. Preliminary results from NOAMP deep drifting floats

    International Nuclear Information System (INIS)

    Ollitrault, M.

    1989-01-01

    This paper is a very brief and preliminary outline of first results obtained with deep SOFAR floats in the NOAMP area. The work is now going toward more precise statistical estimations of mean and variable currents, together with better tracking to resolve submesoscales and estimate diffusivities due to mesoscale and smaller scale motions. However the preliminary results confirm that the NOAMP region (and surroundings) has a deep mesoscale eddy field that is considerably more energetic that the mean field (r.m.s. velocities are of order 5 cm s -1 ), although both values are diminished compared to the western basin. A data report containing trajectories and statistics is scheduled to be published by IFREMER in the near future. The project main task is to especially study the dispersion of radioactive substances

  10. Ion transport in deep-sea sediments

    International Nuclear Information System (INIS)

    Heath, G.R.

    1979-01-01

    Initial assessment of the ability of deep-sea clays to contain nuclear waste is optimistic. Yet, the investigators have no delusions about the complexity of the natural geochemical system and the perturbations that may result from emplacement of thermally-hot waste cannisters. Even though they may never be able to predict the exact nature of all these perturbations, containment of the nuclides by the waste form/cannister system until most of the heat has decayed, and burial of the waste to a sufficient depth that the altered zone can be treated as a black box source of dissolved nuclides to the enclosing unperturbed sediment, encourage them to believe that ion migration in the deep seabed can be modeled accurately and that our preliminary estimates of migration rates are likely to be reasonably realistic

  11. Deep learning for automated drivetrain fault detection

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin; Rømer-Odgaard, Bo; Winther, Ole

    2018-01-01

    A novel data-driven deep-learning system for large-scale wind turbine drivetrain monitoring applications is presented. It uses convolutional neural network processing on complex vibration signal inputs. The system is demonstrated to learn successfully from the actions of human diagnostic experts...... the fleet-wide diagnostic model performance. The analysis also explores the time dependence of the diagnostic performance, providing a detailed view of the timeliness and accuracy of the diagnostic outputs across the different architectures. Deep architectures are shown to outperform the human analyst...... as well as shallow-learning architectures, and the results demonstrate that when applied in a large-scale monitoring system, machine intelligence is now able to handle some of the most challenging diagnostic tasks related to wind turbines....

  12. Jet-images — deep learning edition

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Luke de [Institute for Computational and Mathematical Engineering, Stanford University,Huang Building 475 Via Ortega, Stanford, CA 94305 (United States); Kagan, Michael [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States); Mackey, Lester [Department of Statistics, Stanford University,390 Serra Mall, Stanford, CA 94305 (United States); Nachman, Benjamin; Schwartzman, Ariel [SLAC National Accelerator Laboratory, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States)

    2016-07-13

    Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. This interplay between physically-motivated feature driven tools and supervised learning algorithms is general and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.

  13. JGR special issue on Deep Earthquakes

    Science.gov (United States)

    The editor and associate editors of the Journal of Geophysical Research—Solid Earth and Planets invite the submission of manuscripts for a special issue on the topic “Deep- and Intermediate-Focus Earthquakes, Phase Transitions, and the Mechanics of Deep Subduction.”Manuscripts should be submitted to JGR Editor Gerald Schubert (Department of Earth and Space Sciences, University of California, Los Angeles, Los Angeles, CA 90024) before July 1, 1986, in accordance with the usual rules for manuscript submission. Submitted papers will undergo the normal JGR review procedure. For more information, contact either Schubert or the special guest associate editor, Cliff Frohlich (Institute for Geophysics, University of Texas at Austin, 4920 North IH-35, Austin, TX 78751; telephone: 512-451-6223).

  14. Ensemble Network Architecture for Deep Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Xi-liang Chen

    2018-01-01

    Full Text Available The popular deep Q learning algorithm is known to be instability because of the Q-value’s shake and overestimation action values under certain conditions. These issues tend to adversely affect their performance. In this paper, we develop the ensemble network architecture for deep reinforcement learning which is based on value function approximation. The temporal ensemble stabilizes the training process by reducing the variance of target approximation error and the ensemble of target values reduces the overestimate and makes better performance by estimating more accurate Q-value. Our results show that this architecture leads to statistically significant better value evaluation and more stable and better performance on several classical control tasks at OpenAI Gym environment.

  15. DCMDN: Deep Convolutional Mixture Density Network

    Science.gov (United States)

    D'Isanto, Antonio; Polsterer, Kai Lars

    2017-09-01

    Deep Convolutional Mixture Density Network (DCMDN) estimates probabilistic photometric redshift directly from multi-band imaging data by combining a version of a deep convolutional network with a mixture density network. The estimates are expressed as Gaussian mixture models representing the probability density functions (PDFs) in the redshift space. In addition to the traditional scores, the continuous ranked probability score (CRPS) and the probability integral transform (PIT) are applied as performance criteria. DCMDN is able to predict redshift PDFs independently from the type of source, e.g. galaxies, quasars or stars and renders pre-classification of objects and feature extraction unnecessary; the method is extremely general and allows the solving of any kind of probabilistic regression problems based on imaging data, such as estimating metallicity or star formation rate in galaxies.

  16. An Introduction to Deep Learning with Keras

    CERN Multimedia

    CERN. Geneva

    2016-01-01

    Keras is a modular, powerful and intuitive open-source Deep Learning library built on Theano and TensorFlow. Thanks to its minimalist, user-friendly interface, it has become one of the most popular packages to build, train and test neural networks, for both beginners and experts. In this tutorial, we will start with an introduction of the basics of neural networks and will work through fully functioning examples, with an eye towards deployment strategies within the context of CERN. Fundamental steps and parameters in Deep Learning will be presented both from a conceptual and a practical standpoint, by looking at the way Keras implements them and exposes them to the users. Please visit the [Keras website][1] prior to the workshop for installation instructions and feel free to reach out for any issue. [1]: http://keras.io/#installation

  17. Deep space test bed for radiation studies

    International Nuclear Information System (INIS)

    Adams, James H.; Adcock, Leonard; Apple, Jeffery; Christl, Mark; Cleveand, William; Cox, Mark; Dietz, Kurt; Ferguson, Cynthia; Fountain, Walt; Ghita, Bogdan; Kuznetsov, Evgeny; Milton, Martha; Myers, Jeremy; O'Brien, Sue; Seaquist, Jim; Smith, Edward A.; Smith, Guy; Warden, Lance; Watts, John

    2007-01-01

    The Deep Space Test-Bed (DSTB) Facility is designed to investigate the effects of galactic cosmic rays on crews and systems during missions to the Moon or Mars. To gain access to the interplanetary ionizing radiation environment the DSTB uses high-altitude polar balloon flights. The DSTB provides a platform for measurements to validate the radiation transport codes that are used by NASA to calculate the radiation environment within crewed space systems. It is also designed to support other exploration related investigations such as measuring the shielding effectiveness of candidate spacecraft and habitat materials, testing new radiation monitoring instrumentation, flight avionics and investigating the biological effects of deep space radiation. We describe the work completed thus far in the development of the DSTB and its current status

  18. Nanostructured Deep Carbon: A Wealth of Possibilities

    Science.gov (United States)

    Navrotsky, A.

    2012-12-01

    The materials science community has been investigating novel forms of carbon including C60 buckyballs, nanodiamond, graphene, carbon "onion" structures with a mixture of sp2 and sp3 bonding , and multicomponent nanostructured Si-O-C-N polymer derived ceramics. Though such materials are generally viewed as metastable, recently measured energetics of several materials suggest that this may not always be the case in multicomponent systems. Finely disseminated carbon phases, including nanodiamonds, have been found in rocks from a variety of deep earth settings. The question then is whether some of the more exotic forms of carbon can also exist in the deep earth or other planetary interiors. This presentation discusses thermodynamic constraints related to surface and interface energies, nanodomain structures, and compositional effects on the possible existence of complex carbon, carbide and oxycarbide nanomaterials at high pressure.

  19. 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...

  20. Gas Classification Using Deep Convolutional Neural Networks

    Science.gov (United States)

    Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

    2018-01-01

    In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP). PMID:29316723

  1. Recanalization after acute deep vein thrombosis

    Directory of Open Access Journals (Sweden)

    Gustavo Mucoucah Sampaio Brandao

    2013-12-01

    Full Text Available The process of recanalization of the veins of the lower limbs after an episode of acute deep venous thrombosis is part of the natural evolution of the remodeling of the venous thrombus in patients on anticoagulation with heparin and vitamin K inhibitors. This remodeling involves the complex process of adhesion of thrombus to the wall of the vein, the inflammatory response of the vessel wall leading to organization and subsequent contraction of the thrombus, neovascularization and spontaneous lysis of areas within the thrombus. The occurrence of spontaneous arterial flow in recanalized thrombosed veins has been described as secondary to neovascularization and is characterized by the development of flow patterns characteristic of arteriovenous fistulae that can be identified by color duplex scanning. In this review, we discuss some controversial aspects of the natural history of deep vein thrombosis to provide a better understanding of its course and its impact on venous disease.

  2. Learning with hierarchical-deep models.

    Science.gov (United States)

    Salakhutdinov, Ruslan; Tenenbaum, Joshua B; Torralba, Antonio

    2013-08-01

    We introduce HD (or “Hierarchical-Deep”) models, a new compositional learning architecture that integrates deep learning models with structured hierarchical Bayesian (HB) models. Specifically, we show how we can learn a hierarchical Dirichlet process (HDP) prior over the activities of the top-level features in a deep Boltzmann machine (DBM). This compound HDP-DBM model learns to learn novel concepts from very few training example by learning low-level generic features, high-level features that capture correlations among low-level features, and a category hierarchy for sharing priors over the high-level features that are typical of different kinds of concepts. We present efficient learning and inference algorithms for the HDP-DBM model and show that it is able to learn new concepts from very few examples on CIFAR-100 object recognition, handwritten character recognition, and human motion capture datasets.

  3. Gas Classification Using Deep Convolutional Neural Networks.

    Science.gov (United States)

    Peng, Pai; Zhao, Xiaojin; Pan, Xiaofang; Ye, Wenbin

    2018-01-08

    In this work, we propose a novel Deep Convolutional Neural Network (DCNN) tailored for gas classification. Inspired by the great success of DCNN in the field of computer vision, we designed a DCNN with up to 38 layers. In general, the proposed gas neural network, named GasNet, consists of: six convolutional blocks, each block consist of six layers; a pooling layer; and a fully-connected layer. Together, these various layers make up a powerful deep model for gas classification. Experimental results show that the proposed DCNN method is an effective technique for classifying electronic nose data. We also demonstrate that the DCNN method can provide higher classification accuracy than comparable Support Vector Machine (SVM) methods and Multiple Layer Perceptron (MLP).

  4. Computational ghost imaging using deep learning

    Science.gov (United States)

    Shimobaba, Tomoyoshi; Endo, Yutaka; Nishitsuji, Takashi; Takahashi, Takayuki; Nagahama, Yuki; Hasegawa, Satoki; Sano, Marie; Hirayama, Ryuji; Kakue, Takashi; Shiraki, Atsushi; Ito, Tomoyoshi

    2018-04-01

    Computational ghost imaging (CGI) is a single-pixel imaging technique that exploits the correlation between known random patterns and the measured intensity of light transmitted (or reflected) by an object. Although CGI can obtain two- or three-dimensional images with a single or a few bucket detectors, the quality of the reconstructed images is reduced by noise due to the reconstruction of images from random patterns. In this study, we improve the quality of CGI images using deep learning. A deep neural network is used to automatically learn the features of noise-contaminated CGI images. After training, the network is able to predict low-noise images from new noise-contaminated CGI images.

  5. Jet-images — deep learning edition

    International Nuclear Information System (INIS)

    Oliveira, Luke de; Kagan, Michael; Mackey, Lester; Nachman, Benjamin; Schwartzman, Ariel

    2016-01-01

    Building on the notion of a particle physics detector as a camera and the collimated streams of high energy particles, or jets, it measures as an image, we investigate the potential of machine learning techniques based on deep learning architectures to identify highly boosted W bosons. Modern deep learning algorithms trained on jet images can out-perform standard physically-motivated feature driven approaches to jet tagging. We develop techniques for visualizing how these features are learned by the network and what additional information is used to improve performance. This interplay between physically-motivated feature driven tools and supervised learning algorithms is general and can be used to significantly increase the sensitivity to discover new particles and new forces, and gain a deeper understanding of the physics within jets.

  6. On deep inelastic lepton-nuclear interactions

    International Nuclear Information System (INIS)

    Garsevanishvili, V.R.; Darbaidze, Ya.Z.; Menteshashvili, Z.R.; Ehsakiya, Sh.M.

    1981-01-01

    The problem of building relativistic theory of nuclear reactions by way of involving relativistic methods, developed in the elementary particle theory, becomes rather actual at the time being. The paper presents some results of investigations into deep inelastic lepton-nuclear processes lA → l'(A-1)x, with the spectator nucleus-fragment in the finite state. To describe the reactions lA → l'(A-1)x (where l=an electron, muan, neutrino, antineutrino), the use is made of the self-similarity principle and multiparticle quasipotential formalism in the ''light front'' variables. The expressions are obtained for the differential cross-sections of lepton-nuclear processes and for the structure functions of deep inelastic scattering of neutrinos (antineutrinos) and charged leptons by nuclei

  7. 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.

  8. 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

    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. 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.' Successfully transition to a low-carbon economy will require unprecedented global cooperation, including a global cooperative effort to accelerate the development and diffusion of some key low carbon technologies. As underscored throughout this report, the results of the DDPP analyses remain preliminary and incomplete. The DDPP proceeds in two phases. This 2014 report describes the DDPP's approach to deep decarbonization at the country level and presents preliminary findings on technically feasible pathways to deep decarbonization, utilizing technology assumptions and timelines provided by the DDPP Secretariat. At this stage we have not yet considered the economic and social costs and benefits of deep decarbonization, which will be the topic for the next report. The DDPP is issuing this 2014 report to the UN Secretary-General Ban Ki-moon in support of the Climate Leaders' Summit at the United Nations on September 23, 2014. This 2014 report by the Deep Decarbonization Pathway Project (DDPP) summarizes preliminary findings of the technical pathways developed by the DDPP Country Research Partners with the objective of achieving emission reductions consistent with limiting global warming to less than 2 deg. C., without, at this stage, consideration of economic and social costs and benefits. The DDPP is a knowledge

  9. Modified tubularized incised plate urethroplasty

    Directory of Open Access Journals (Sweden)

    Shivaji Mane

    2013-01-01

    Full Text Available Aim: To share our experience of doing tubularized incised plate urethroplasty with modifications. Materials and Methods: This is a single surgeon personal series from 2004 to 2009. One hundred patients of distal hypospadias were subjected for Snodgrass urethroplasty with preputioplasty. The age range was 1 to 5 year with mean age of 2.7 years. Selection criteria were good urethral plate, without chordee and torsion needing complete degloving. Main technical modification from original Snodgrass procedure was spongioplasty, preputioplasty, and dorsal slit when inability to retract prepuce during surgery. Results: Average follow-up period is 23 months. Seven (7% patients developed fistula and one patient had complete preputial dehiscence. Phimosis developed in three (3% patients and required circumcision. Dorsal slit was required in seven patients. One patient developed meatal stenosis in postoperative period. All other patients are passing single urinary stream and have cosmesis that is acceptable. Conclusions: Modified tubularized incised plate urethroplasty with preputioplasty effectively gives cosmetically normal looking penis with low complications.

  10. Nonderivative Modified Gravity: a Classification

    CERN Document Server

    Comelli, Denis; Pilo, Luigi

    2014-01-01

    We analyze the theories of gravity modified by a generic nonderivative potential built from the metric, under the minimal requirement of unbroken spatial rotations. Using the canonical analysis, we classify the potentials $V$ according to the number of degrees of freedom (DoF) that propagate at the nonperturbative level. We then compare the nonperturbative results with the perturbative DoF propagating around Minkowski and FRW backgrounds. A generic $V$ implies 6 propagating DoF at the non-perturbative level, with a ghost on Minkowski background. There exist potentials which propagate 5 DoF, as already studied in previous works. Here, no $V$ with unbroken rotational invariance admitting 4 DoF is found. Theories with 3 DoF turn out to be strongly coupled on Minkowski background. Finally, potentials with only the 2 DoF of a massive graviton exist. Their effect on cosmology is simply equivalent to a cosmological constant. Potentials with 2 or 5 DoF and explicit time dependence appear to be a further viable possib...

  11. Solution properties of hydrophobically modified

    Directory of Open Access Journals (Sweden)

    A.M. Al-Sabagh

    2016-12-01

    Full Text Available We tested nine hydrophobically modified polyacrylamides with molecular weights situated between 1.58 and 0.89 × 106 g/mol for enhanced oil recovery applications. Their solution properties were investigated in the distilled water, brine solution, formation water and sea water. Their critical association concentrations were determined from the relationship between their concentrations and the corresponding apparent viscosities (ηapp at 30 °C at shear rate 6 s−1. They were between 0.4 and 0.5 g/dl. The brine solutions of 0.5 g/dl of HM-PAMs were investigated at different conditions regarding their apparent viscosities. Such conditions were mono and divalent cations, temperature ranging from 30 to 90 °C, the shear rate ranging from 6 to 30 s−1 and the aging time for 45 days. The surface and interfacial tensions for the HM-PAMs were measured for concentration range from 0.01 to 1 g/dl brine solutions at 30 °C and their emulsification efficiencies were investigated for 7 days. The discrepancy in the properties and efficiencies of the tested copolymers was discussed in the light of their chemical structure.

  12. Modified teleparallel gravity: Inflation without an inflaton

    International Nuclear Information System (INIS)

    Ferraro, Rafael; Fiorini, Franco

    2007-01-01

    The Born-Infeld strategy to smooth theories having divergent solutions is applied to the teleparallel equivalent of general relativity. Differing from other theories of modified gravity, modified teleparallelism leads to second order equations, since the teleparallel Lagrangian only contains first derivatives of the vierbein. We show that the Born-Infeld-modified teleparallelism solves the particle horizon problem in a spatially flat Friedmann-Robertson-Walker (FRW) universe by providing an initial exponential expansion without resorting to an inflaton field

  13. Genetically Modified Products – Contradictions and Challenges

    OpenAIRE

    Rodica Pamfilie; Lavinia-Alexandra Cristescu

    2011-01-01

    This paper aims to identify the perception that consumers have about GM products, also taking into consideration the evolution of consumption and production of products based on genetically modified organisms. Therefore, the paper presents both aspects to clarify the concept of genetically modified organism (GMO issues such as typology, national or international regulations regarding this area) and global market development of genetically modified organisms, evolution which is presented by st...

  14. Deep soft tissue leiomyoma of the thigh

    International Nuclear Information System (INIS)

    Watson, G.M.T.; Saifuddin, A.; Sandison, A.

    1999-01-01

    A case of ossified leiomyoma of the deep soft tissues of the left thigh is presented. The radiographic appearance suggested a low-grade chondrosarcoma. MRI of the lesion showed signal characteristics similar to muscle on both T1- and T2-weighted spin echo sequences with linear areas of high signal intensity on T1-weighted images consistent with medullary fat in metaplastic bone. Histopathological examination of the resected specimen revealed a benign ossified soft tissue leiomyoma. (orig.)

  15. Blind source deconvolution for deep Earth seismology

    Science.gov (United States)

    Stefan, W.; Renaut, R.; Garnero, E. J.; Lay, T.

    2007-12-01

    We present an approach to automatically estimate an empirical source characterization of deep earthquakes recorded teleseismically and subsequently remove the source from the recordings by applying regularized deconvolution. A principle goal in this work is to effectively deblur the seismograms, resulting in more impulsive and narrower pulses, permitting better constraints in high resolution waveform analyses. Our method consists of two stages: (1) we first estimate the empirical source by automatically registering traces to their 1st principal component with a weighting scheme based on their deviation from this shape, we then use this shape as an estimation of the earthquake source. (2) We compare different deconvolution techniques to remove the source characteristic from the trace. In particular Total Variation (TV) regularized deconvolution is used which utilizes the fact that most natural signals have an underlying spareness in an appropriate basis, in this case, impulsive onsets of seismic arrivals. We show several examples of deep focus Fiji-Tonga region earthquakes for the phases S and ScS, comparing source responses for the separate phases. TV deconvolution is compared to the water level deconvolution, Tikenov deconvolution, and L1 norm deconvolution, for both data and synthetics. This approach significantly improves our ability to study subtle waveform features that are commonly masked by either noise or the earthquake source. Eliminating source complexities improves our ability to resolve deep mantle triplications, waveform complexities associated with possible double crossings of the post-perovskite phase transition, as well as increasing stability in waveform analyses used for deep mantle anisotropy measurements.

  16. Tephrostratigraphy the DEEP site record, Lake Ohrid

    Science.gov (United States)

    Leicher, N.; Zanchetta, G.; Sulpizio, R.; Giaccio, B.; Wagner, B.; Francke, A.

    2016-12-01

    In the central Mediterranean region, tephrostratigraphy has been proofed to be a suitable and powerful tool for dating and correlating marine and terrestrial records. However, for the period older 200 ka, tephrostratigraphy is incomplete and restricted to some Italian continental basins (e.g. Sulmona, Acerno, Mercure), and continuous records downwind of the Italian volcanoes are rare. Lake Ohrid (Macedonia/Albania) in the eastern Mediterranean region fits this requisite and is assumed to be the oldest continuously existing lake of Europe. A continous record (DEEP) was recovered within the scope of the ICDP deep-drilling campaign SCOPSCO (Scientific Collaboration on Past Speciation Conditions in Lake Ohrid). In the uppermost 450 meters of the record, covering more than 1.2 Myrs of Italian volcanism, 54 tephra layers were identified during core-opening and description. A first tephrostratigraphic record was established for the uppermost 248 m ( 637 ka). Major element analyses (EDS/WDS) were carried out on juvenile glass fragments and 15 out of 35 tephra layers have been identified and correlated with known and dated eruptions of Italian volcanoes. Existing 40Ar/39Ar ages were re-calculated by using the same flux standard and used as first order tie points to develop a robust chronology for the DEEP site succession. Between 248 and 450 m of the DEEP site record, another 19 tephra horizons were identified and are subject of ongoing work. These deposits, once correlated with known and dated tephra, will hopefully enable dating this part of the succession, likely supported by major paleomagnetic events, such as the Brunhes-Matuyama boundary, or the Cobb-Mountain or the Jaramillo excursions. This makes the Lake Ohrid record a unique continuous, distal record of Italian volcanic activity, which is candidate to become the template for the central Mediterranean tephrostratigraphy, especially for the hitherto poorly known and explored lower Middle Pleistocene period.

  17. Uncertain Photometric Redshifts with Deep Learning Methods

    Science.gov (United States)

    D'Isanto, A.

    2017-06-01

    The need for accurate photometric redshifts estimation is a topic that has fundamental importance in Astronomy, due to the necessity of efficiently obtaining redshift information without the need of spectroscopic analysis. We propose a method for determining accurate multi-modal photo-z probability density functions (PDFs) using Mixture Density Networks (MDN) and Deep Convolutional Networks (DCN). A comparison with a Random Forest (RF) is performed.

  18. Brucellosis associated with deep vein thrombosis.

    Science.gov (United States)

    Tolaj, Ilir; Mehmeti, Murat; Ramadani, Hamdi; Tolaj, Jasmina; Dedushi, Kreshnike; Fejza, Hajrullah

    2014-11-19

    Over the past 10 years more than 700 cases of brucellosis have been reported in Kosovo, which is heavily oriented towards agriculture and animal husbandry. Here, brucellosis is still endemic and represents an uncontrolled public health problem. Human brucellosis may present with a broad spectrum of clinical manifestations; among them, vascular complications are uncommon. Hereby we describe the case of a 37-year-old male patient with brucellosis complicated by deep vein thrombosis on his left leg.

  19. Gene expression inference with deep learning.

    Science.gov (United States)

    Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

    2016-06-15

    Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  20. A Moessbauer study of deep sea sediments

    International Nuclear Information System (INIS)

    Minai, Y.; Tominaga, T.; Furuta, T.; Kobayashi, K.

    1981-01-01

    In order to determine the chemical states of iron in deep sea sediments, Moessbauer spectra of the sediments collected from various areas of the Pacific have been measured. The Moessbauer spectra were composed of paramagnetic ferric, high-spin ferrous, and magnetic components. The correlation of their relative abundance to the sampling location and the kind of sediments may afford clues to infer the origin of each iron-bearing phase. (author)

  1. Deep inelastic collisions viewed as Brownian motion

    International Nuclear Information System (INIS)

    Gross, D.H.E.; Freie Univ. Berlin

    1980-01-01

    Non-equilibrium transport processes like Brownian motion, are studied since perhaps 100 years and one should ask why does one not use these theories to explain deep inelastic collision data. These theories have reached a high standard of sophistication, experience, and precision that I believe them to be very usefull for our problem. I will try to sketch a possible form of an advanced theory of Brownian motion that seems to be suitable for low energy heavy ion collisions. (orig./FKS)

  2. Deep electroproduction of exotic hybrid mesons

    International Nuclear Information System (INIS)

    Anikin, I.V.; Pire, B.; Szymanowski, L.; Teryaev, O.V.; Wallon, S.

    2004-01-01

    We evaluate the leading order amplitude for the deep exclusive electroproduction of an exotic hybrid meson in the Bjorken regime. We show that, contrarily to naive expectation, this amplitude factorizes at the twist 2 level and thus scales like usual meson electroproduction when the virtual photon and the hybrid meson are longitudinally polarized. Exotic hybrid mesons may thus be studied in electroproduction experiments at JLAB, HERA (HERMES) or CERN (Compass)

  3. Deep primary production in coastal pelagic systems

    DEFF Research Database (Denmark)

    Lyngsgaard, Maren Moltke; Richardson, Katherine; Markager, Stiig

    2014-01-01

    produced. The primary production (PP) occurring below the surface layer, i.e. in the pycnocline-bottom layer (PBL), is shown to contribute significantly to total PP. Oxygen concentrations in the PBL are shown to correlate significantly with the deep primary production (DPP) as well as with salinity...... that eutrophication effects may include changes in the structure of planktonic food webs and element cycling in the water column, both brought about through an altered vertical distribution of PP....

  4. Environmental studies for deep seabed mining

    Digital Repository Service at National Institute of Oceanography (India)

    Sharma, R.

    tests of prototype mining systems and components in the Pacific Ocean in the seventies (DOMES, 1976). The subsequent progress in the development of mining technology for deep-sea minerals has been slow since 1980 due to unfavorable metal market... assume instead, because commercial system size and type are likely different depending upon the use of nodule elements and can vary with metal market situation. 2. How do we generalize the test parameters from the tow-sled collector and miner...

  5. Deep vein thrombosis: diagnosis, treatment, and prevention

    Energy Technology Data Exchange (ETDEWEB)

    Stewart, W.P.; Youngswick, F.D.

    Deep vein thrombosis (DVT) is a dangerous complication that may present after elective foot surgery. Because of the frequency with which DVT occurs in the elderly patient, as well as in the podiatric surgical population, the podiatrist should be acquainted with this entity. A review of the diagnosis, treatment, prevention, and the role of podiatry in the management of DVT is discussed in this paper.

  6. Deep Learning with Dynamic Computation Graphs

    OpenAIRE

    Looks, Moshe; Herreshoff, Marcello; Hutchins, DeLesley; Norvig, Peter

    2017-01-01

    Neural networks that compute over graph structures are a natural fit for problems in a variety of domains, including natural language (parse trees) and cheminformatics (molecular graphs). However, since the computation graph has a different shape and size for every input, such networks do not directly support batched training or inference. They are also difficult to implement in popular deep learning libraries, which are based on static data-flow graphs. We introduce a technique called dynami...

  7. Critical study of high efficiency deep grinding

    OpenAIRE

    Johnstone, lain

    2002-01-01

    The recent years, the aerospace industry in particular has embraced and actively pursued the development of stronger high performance materials, namely nickel based superalloys and hardwearing steels. This has resulted in a need for a more efficient method of machining, and this need was answered with the advent of High Efficiency Deep Grinding (HEDG). This relatively new process using Cubic Boron Nitride (CBN) electroplated grinding wheels has been investigated through experim...

  8. Young Children in Deep Poverty. Fact Sheet

    Science.gov (United States)

    Ekono, Mercedes; Jiang, Yang; Smith, Sheila

    2016-01-01

    A U.S. family of three living in deep poverty survives on an annual income below $9,276, or less than $9.00 a day per family member. The struggle to raise children on such a meager income is not a rare circumstance among U.S. families, especially those with young children. Currently, 11 percent of young children (0-9 years) live in households with…

  9. Deuteron structure in the deep inelastic regime

    Energy Technology Data Exchange (ETDEWEB)

    Garcia Canal, C.A.; Tarutina, T. [Universidad Nacional de La Plata, IFLP/CONICET y Departamento de Fisica, La Plata (Argentina); Vento, V. [Universidad de Valencia-CSIC, Departamento de Fisica Teorica-IFIC, Burjassot (Valencia) (Spain)

    2017-06-15

    We study nuclear effects in the deuteron in the deep inelastic regime using the newest available data. We put special emphasis on their Q{sup 2} dependence. The study is carried out using a scheme which parameterizes, in a simple manner, these effects by changing the proton and neutron stucture functions in medium. The result of our analysis is compared with other recent proposals. We conclude that precise EMC ratios cannot be obtained without considering the nuclear effects in the deuteron. (orig.)

  10. Deep Inelastic Scattering at the Amplitude Level

    International Nuclear Information System (INIS)

    Brodsky, Stanley J.

    2005-01-01

    The deep inelastic lepton scattering and deeply virtual Compton scattering cross sections can be interpreted in terms of the fundamental wavefunctions defined by the light-front Fock expansion, thus allowing tests of QCD at the amplitude level. The AdS/CFT correspondence between gauge theory and string theory provides remarkable new insights into QCD, including a model for hadronic wavefunctions which display conformal scaling at short distances and color confinement at large distances

  11. Mean associated multiplicities in deep inelastic processes

    International Nuclear Information System (INIS)

    Dzhaparidze, G.S.; Kiselev, A.V.; Petrov, V.A.

    1982-01-01

    A formula is derived for the mean multiplicity of hadrons in the target-fragmentation region in the process of deep inelastic scattering. It is shown that in the region of large x the ratio of the mean multiplicities in the current- and target-fragmentation regions tends to unity at high energies. The mean multiplicity in the Drell-Yan process is also discussed

  12. Microplastic pollution in deep-sea sediments

    International Nuclear Information System (INIS)

    Van Cauwenberghe, Lisbeth; Vanreusel, Ann; Mees, Jan; Janssen, Colin R.

    2013-01-01

    Microplastics are small plastic particles ( 3 was observed. •The depths from where these microplastics were recovered range from 1176 to 4843 m. •The sizes of the particles range from 75 to 161 μm at their largest cross-section. -- Here, we demonstrate that microplastics have invaded the marine environment to an extent that they appear to even be present in the remote deep sea

  13. Colour coherence in deep inelastic Compton scattering

    Energy Technology Data Exchange (ETDEWEB)

    Lebedev, A.I.; Vazdik, J.A. (Lebedev Physical Inst., Academy of Sciences, Moscow (USSR))

    1992-01-01

    MC simulation of Deep Inelastic Compton on proton - both QED and QCD - was performed on the basis of LUCIFER program for HERA energies. Charged hadron flow was calculated for string and independent fragmentation with different cuts on p{sub t} and x. It is shown that interjet colour coherence leads in the case of QCD Compton to the drag effects diminishing the hadron flow in the direction between quark jet and proton remnant jet. (orig.).

  14. Colour coherence in deep inelastic Compton scattering

    International Nuclear Information System (INIS)

    Lebedev, A.I.; Vazdik, J.A.

    1992-01-01

    MC simulation of Deep Inelastic Compton on proton - both QED and QCD - was performed on the basis of LUCIFER program for HERA energies. Charged hadron flow was calculated for string and independent fragmentation with different cuts on p t and x. It is shown that interjet colour coherence leads in the case of QCD Compton to the drag effects diminishing the hadron flow in the direction between quark jet and proton remnant jet. (orig.)

  15. Brucellosis associated with deep vein thrombosis

    Directory of Open Access Journals (Sweden)

    Ilir Tolaj

    2014-11-01

    Full Text Available Over the past 10 years more than 700 cases of brucellosis have been reported in Kosovo, which is heavily oriented towards agriculture and animal husbandry. Here, brucellosis is still endemic and represents an uncontrolled public health problem. Human brucellosis may present with a broad spectrum of clinical manifestations; among them, vascular complications are uncommon. Hereby we describe the case of a 37-year-old male patient with brucellosis complicated by deep vein thrombosis on his left leg.

  16. Brucellosis Associated with Deep Vein Thrombosis

    Science.gov (United States)

    Tolaj, Ilir; Mehmeti, Murat; Ramadani, Hamdi; Tolaj, Jasmina; Dedushi, Kreshnike; Fejza, Hajrullah

    2014-01-01

    Over the past 10 years more than 700 cases of brucellosis have been reported in Kosovo, which is heavily oriented towards agriculture and animal husbandry. Here, brucellosis is still endemic and represents an uncontrolled public health problem. Human brucellosis may present with a broad spectrum of clinical manifestations; among them, vascular complications are uncommon. Hereby we describe the case of a 37-year-old male patient with brucellosis complicated by deep vein thrombosis on his left leg. PMID:25568754

  17. Brucellosis Associated with Deep Vein Thrombosis

    OpenAIRE

    Tolaj, Ilir; Mehmeti, Murat; Ramadani, Hamdi; Tolaj, Jasmina; Dedushi, Kreshnike; Fejza, Hajrullah

    2014-01-01

    Over the past 10 years more than 700 cases of brucellosis have been reported in Kosovo, which is heavily oriented towards agriculture and animal husbandry. Here, brucellosis is still endemic and represents an uncontrolled public health problem. Human brucellosis may present with a broad spectrum of clinical manifestations; among them, vascular complications are uncommon. Hereby we describe the case of a 37-year-old male patient with brucellosis complicated by deep vein thrombosis on his left ...

  18. Study deep geothermal energy; Studie dypgeotermisk energi

    Energy Technology Data Exchange (ETDEWEB)

    Havellen, Vidar; Eri, Lars Sigurd; Andersen, Andreas; Tuttle, Kevin J.; Ruden, Dorottya Bartucz; Ruden, Fridtjof; Rigler, Balazs; Pascal, Christophe; Larsen, Bjoern Tore

    2012-07-01

    The study aims to analyze the potential energy with current technology, challenges, issues and opportunities for deep geothermal energy using quantitative analysis. It should especially be made to identify and investigate critical connections between geothermal potential, the size of the heating requirements and technical solutions. Examples of critical relationships may be acceptable cost of technology in relation to heating, local geothermal gradient / drilling depth / temperature levels and profitability. (eb)

  19. Clinical analysis of deep neck space infections

    International Nuclear Information System (INIS)

    Hatano, Atsushi; Ui, Naoya; Shigeta, Yasushi; Iimura, Jiro; Rikitake, Masahiro; Endo, Tomonori; Kimura, Akihiro

    2009-01-01

    Deep neck space infections, which affect soft tissues and fascial compartments of the head and neck, can lead to lethal complications unless treated carefully and quickly, even with the advanced antibiotics available. We reviewed our seventeen patients with deep neck abscesses, analyzed their location by reviewing CT images, and discussed the treatment. Deep neck space infections were classified according to the degree of diffusion of infection diagnosed by CT images. Neck space infection in two cases was localized to the upper neck space above the hyoid bone (Stage I). Neck space infection in 12 cases extended to the lower neck space (Stage II), and further extended to the mediastinum in one case (Stage III). The two cases of Stage I and the four cases of Stage II were managed with incision and drainage through a submental approach. The seven cases of Stage II were managed with incision and drainage parallel to the anterior border of the sternocleidomastoid muscle, the ''Dean'' approach. The one case of Stage III received treatment through transcervicotomy and anterior mediastinal drainage through a subxiphodal incision. The parapharyngeal space played an important role in that the inflammatory change can spread to the neck space inferiorly. The anterior cervical space in the infrahyoid neck was important for mediastinal extension of parapharyngeal abscesses. It is important to diagnose deep neck space infections promptly and treat them adequately, and contrast-enhanced CT is useful and indispensable for diagnosis. The point is which kind of drainage has to be performed. If the surgical method of drainage is chosen according to the level of involvement in the neck space and mediastinum, excellent results may be obtained in terms of survival and morbidity. (author)

  20. Disseminating genetically modified (GM) maize technology to ...

    African Journals Online (AJOL)

    Disseminating genetically modified (GM) maize technology to smallholder farmers in the Eastern Cape province of South Africa: extension personnel's awareness of stewardship requirements and dissemination practices.