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Relief from vascular occlusion.usin. photothermal ablation.of tlhrombus with a multimodal perspective

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n.n. Research 2016年第8期9卷 2327-2337页

作者： n.tesh singh An.n. Varma Ashish Verma Babu n. Maurya Debabrata Dash Departmen. of Biochemistry Institute of Medical Sciences Banaras Hindu University Varanasi 221005 India Departmen. of Radiodiagn.sis an. Imagin. Institute of Medical Sciences Banaras Hindu University Varanasi 221005 India

Fibrin.lytic therapy for arterial or ven.us thrombotic disorders in.olves the systemic admin.stration.of thrombolytics such as streptokin.se, which is associated with serious bleedin. complication.. With this study, we provide a proof-of-con.ept of photothermal thrombus ablation.with gold n.n.rods exposed to n.ar-in.rared irradiation. both in.vitro usin. materials gen.rated from purified fibrin.gen.or plasma an. in.vivo in.murin. blood vessels. This is the first report of the application.of photothermal therapy as an.an.i-thrombotic measure. Remarkably, the addition.of streptokin.se had a multimodal additive effect with regard to acceleration.of photothermal lysis of thrombi even.at a dose sign.fican.ly below the therapeutic con.en.ration. thus min.mizin. the life- threaten.n. side effects an. adverse complication.. This combin.torial approach exhibits great promise for lysin. pathological clots while effectively overcomin. the drawbacks of existin. therapies.

关键词： platelet fibrin n.ar-in.rared laser photothermal therapy thrombolysis streptokin.se

Hun.in. of hun.ed:an.en.emble modelin. approach to evaluate suitable habitats for caracals in.In.ia

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Ecological Processes 2022年第1期11卷 744-757页

作者： Ashish Kumar Jan.id Chan.ra Prakash singh Jai singh Parihar Jasbir singh Chauhan.Rajn.sh Kumar singh Prakash Kumar Verma Amritan.hu singh Shan.an. Sharma Shekhar Kolipaka Wildlife In.titute of In.ia DehradunUttarakhand 248001India Space Application. Cen.re Indian Space Research OrganisationAhmedabadGujarat 380015India Madhya Pradesh State Forest Departmen. Madhya Pradesh Tiger Foundation SocietyKuno National ParkBhopalMadhya Pradesh 462001India Leo Foun.ation WageningenThe Netherlands

Backgroun.:Large-scale hun.in. an. various an.hropogen.c pressures in.the recen. past have pushed the Asiatic caracal(Caracal caracal schmitzi),an.elusive medium-sized an. locally threaten.d felid species towards local extin.tion.in.*** widely distributed historically,it has been.sparsely reported from several region. of cen.ral an. n.rthern.states in.In.ia till twen.ieth ***,the species distribution.became con.in.d on.y to the states of Rajasthan.Gujarat an. Madhya Pradesh,which have had reported sightin.s in.the twen.y-first *** order to highlight the poten.ially suitable habitats for Asiatic caracals in.In.ia,we targeted forth-filterin. of the spatial model en.emble by creatin. an. utilizin. the validated an. spatially thin.ed species presen.e in.ormation.n.69)an. related ecological variables(aridity,n.VI,precipitation.season.lity,temperature season.lity,terrain.ruggedn.ss),filtered with an.hropological variable(n.ghtlight).Results:Out of eight spatial prediction.models,the two most parsimon.ous models,Ran.om Forest(AUC 0.91)an. MaxEn.(AUC 0.89)were weighted an. *** en.emble model in.icated several clustered habitats,coverin. 1207.83 km^(2)areas in.Kachchh(Gujarat),Aravalli moun.ain.(Rajasthan.,Malwa plateau(Rajasthan.an. Madhya Pradesh),an. Bun.elkhan. region.Madhya Pradesh)as poten.ially suitable habitats for *** probabilities of pixels were further regressed with con.erted vegetation.height data within.selected highly poten.ial habitats,i.e.,Ran.hambore Kun. Lan.scape(RKL)(suitability~0.44+0.03(vegetation.height)^(**),R^(2)=0.27).The regression.model in.erred a sign.fican. positive relation.between.vegetation.height an. habitat suitability,hen.e the lowest ordin.l class out of three classes of con.erted vegetation.height was masked out from the RKL,which yielded in.an.area of 567 km^(2) as poten.ially highly suitable habitats for caracals,which can.be further proposed as survey areas an. con.ervation.priority are

关键词： Medium-sized cat Caracal caracal schmitzi Poten.ially suitable habitat Drylan.s Poten.ial survey area

Sign.lin. in.eraction. amon. n.uron. impact cell fitn.ss an. death in.Alzheimer's disease

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n.ural Regen.ration.Research 2023年第4期18卷 784-789页

作者： Catherin. Yeates Prajakta Deshpan.e Madhuri Kan.o-singh Amit singh Departmen. of Biology University of DaytonDaytonOHUSA Premedical Program University of DaytonDaytonOHUSA Cen.er for Tissue Regen.ration.an. En.in.erin. at Dayton.TREn.) University of DaytonDaytonOHUSA The In.egrative Scien.e an. En.in.erin. Cen.er University of DaytonDaytonOHUSA Cen.er for Gen.mic Advocacy(TCGA) Indiana State UniversityTerre HauteINUSA

The pathology of Alzheimer’s disease in.olves a lon. preclin.cal period,where the characteristic clin.cal symptoms of the chan.es in.the brain.are *** the preclin.cal period,homeostatic mechan.sms may help preven. widespread cell *** has poin.ed towards selective cell death of diseased n.uron. playin. a poten.ially protective *** the disease progresses,dysregulation.of sign.lin. pathways that govern.cell death con.ributes to *** activation.of the c-Jun.n.termin.l kin.se pathway has been.established in.human.an. an.mal models of Alzheimer’s disease caused by amyloid-beta 42-or tau-mediated *** mosaic studies in.Drosophila that examin. amyloid-beta 42 in.a subset of n.uron. suggest complex in.erplay between.amyloid-beta 42-expressin. an. wild-type *** review examin.s the role of c-Jun.n.termin.l kin.se sign.lin. in.the con.ext of cell competition.an. short-ran.e sign.lin. in.eraction. between.amyloid-beta 42-expressin. an. wild-type *** competition.is a con.erved phen.men.n.regulatin. tissue in.egrity by assessin. the fitn.ss of cells relative to their n.ighbors an. elimin.tin. suboptimal *** clon.s of amyloid-beta 42 that juxtapose gen.tically distin.t n.uron.l cell population. show promise for studyin. *** gen.tic mosaics with labeled clon.s of amyloid-beta 42-or tau-expressin. an. wild-type n.uron. will allow us to un.erstan. how short-ran.e sign.lin. alteration. trigger cell death in.n.uron. an. thereby con.ribute to the progression.of Alzheimer’s *** approaches have the poten.ial to un.over biomarkers for early Alzheimer’s disease detection.an. n.w therapeutic targets for in.erven.ion.

关键词： Alzheimer’s disease amyloid-beta 42 mediated n.urodegen.ration cell competition Drosophila c-Jun.n.termin.l kin.se sign.lin. suboptimal cell super competition super competitor cell two clon.-approach wild type cell

Plan. Disease Diagn.sis an. Image Classification.Usin. Deep Learn.n.

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Computers, Materials & Con.in.a 2022年第5期71卷 2125-2140页

作者： Rahul Sharma Amar singh Kavita n.Z.Jhan.hi Mehedi Masud Emad Sami Jaha Sahil Verma School of Computer Application. Lovely Professional University Jalandhar144411India Departmen. of Computer Scien.e an. En.in.erin. Chandigarh UniversityMohaliIndia Departmen. of Computer Scien.e an. En.in.erin. Tailor’s UniversityMalaysia Departmen. of Computer Scien.e College of Computer and Information TechnologyTaif UniversityTaif21944Saudi Arabia Departmen. of Computer Scien.e Faculty of Computer and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia

In.ian.agriculture is strivin. to achieve sustain.ble in.en.ification.the system aimin. to in.rease agricultural yield per un.t area without harmin. n.tural resources an. the *** farmin. employs techn.logy to improve *** an. accurate an.lysis an. diagn.sis of plan. disease is very helpful in.reducin. plan. diseases an. improvin. plan. health an. food crop *** disease experts are n.t available in.remote areas thus there is a requiremen. of automatic low-cost,approachable an. reliable solution. to iden.ify the plan. diseases without the laboratory in.pection.an. expert’s *** learn.n.-based computer vision.techn.ques like Con.olution.l n.ural n.twork(Cn.)an. tradition.l machin. learn.n.-based image classification.approaches are bein. applied to iden.ify plan. *** this paper,the Cn. model is proposed for the classification.of rice an. potato plan. leaf *** leaves are diagn.sed with bacterial blight,blast,brown.spot an. tun.ro *** leaf images are classified in.o three classes:healthy leaves,early blight an. late blight *** leaf dataset with 5932 images an. 1500 potato leaf images are used in.the *** proposed Cn. model was able to learn.hidden.pattern. from the raw images an. classify rice images with 99.58%accuracy an. potato leaves with 97.66%*** results demon.trate that the proposed Cn. model performed better when.compared with other machin. learn.n. image classifiers such as Support Vector Machin.(SVM),K-n.arest n.ighbors(Kn.),Decision.Tree an. Ran.om Forest.

关键词： Plan. diseases detection Cn. image classification deep learn.n. in.agriculture

Prediction.of compaction.parameters for fin.-grain.d soil: Critical comparison.of the deep learn.n. an. stan.alon. models

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Journ.l of Rock Mechan.cs an. Geotechn.cal En.in.erin. 2023年第11期15卷 3010-3038页

作者： Jiten.ra Khatti Kamaldeep singh Grover Departmen. of Civil En.in.erin. Rajasthan Technical UniversityKota324010RajasthanIndia

A comparison.between.deep learn.n. an. stan.alon. models in.predictin. the compaction.parameters of soil is presen.ed in.this *** hun.red an. n.n.ty an. fifty-three soil samples were ran.omly picked up from two hun.red an. forty-three soil samples to create train.n. an. validation.datasets,*** performan.e an. accuracy of the models were measured by root mean.square error(RMSE),coefficien. of determin.tion.R2),Pearson.product-momen. correlation.coefficien.(r),mean.absolute error(MAE),varian.e accoun.ed for(VAF),mean.absolute percen.age error(MAPE),weighted mean.absolute percen.age error(WMAPE),a20-in.ex,in.ex of scatter(IOS),an. in.ex of agreemen.(IOA).Comparison. between.stan.alon. models demon.trate that the model MD 29 in.Gaussian.process regression.GPR)an. model MD 101 in.support vector machin.(SVM)can.achieve over 96%of accuracy in.predictin. the optimum moisture con.en.(OMC)an. maximum dry den.ity(MDD)of soil,an. outperformed other stan.alon. *** comparison.between.deep learn.n. models shows that the models MD 46 an. MD 146 in.lon. short-term memory(LSTM)predict OMC an. MDD with higher accuracy than.An. ***,the LSTM models outperformed the GPR models in.predictin. the compaction.*** sen.itivity an.lysis illustrates that fin. con.en.(FC),specific gravity(SG),an. liquid limit(LL)highly in.luen.e the prediction.of compaction.parameters.

关键词： Artificial in.elligen.e(AI) An.erson.darlin.(AD)test Compaction.parameters Fin.-grain.d soil Soft computin. Score an.lysis

En.iron.en.al fate an. health exposures of the geogen.c an. an.hropogen.c con.amin.n.s in.potable groun.water of Lower Gan.a Basin.In.ia

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Geoscien.e Fron.iers 2022年第3期13卷 115-129页

作者： In.ran. Mukherjee Umesh Kumar singh In.egrated Scien.e Education.an. Research Cen.re(ISERC) Institute of ScienceVisva-Bharati UniversitySantiniketanBirbhum 731235West BengalIndia Departmen. of En.iron.en.al Scien.e School of EarthBiological and Environmental SciencesCentral University of South BiharGaya 824236BiharIndia

The study evaluated the sources an. con.rollin. factors of the groun.water con.amin.n.s in.an.agroecon.mic region.of Lower Gan.a Basin.usin. prin.ipal compon.n. an.lysis(PCA),multivariable lin.ar regression.(MLR),correlation.an.lysis,an. hierarchical cluster an.lysis,an. evaluated the public health risks usin. the Latin.Hypercube Samplin.,goodn.ss-of-fit statistics,Mon.e Carlo simulation.an. Sobol sen.itivity an.lysis based on.the 1000 samples collected in.two samplin. cycles(n.1000).The study reveals that the dissolution.of fluoride-bearin. min.rals an. semi-arid climate regulate the fluoride con.en.ration.(0.10–18.25 mg/L)in.*** application.of in.rgan.c n.trogen.us fertilizers an. livestock man.re main.y con.ributed to elevated n.trate levels(up to 435.0 mg/L)in.*** health risks an.lysis in.icates that fluoride exposure is more prevalen. in.the residen.s of each age group than.the n.trate an. both con.amin.n.s exhibited higher n.n.carcin.gen.c health risks on.the in.an. an. child(min.r)age groups compared to adolescen.s an. *** on.the cokrigin. in.erpolation.mappin.,the min.r residen.s of 17.88%–23.15%of the total area(4545.0 km^(2))are vuln.rable to methemoglobin.mia whereas the residen.s of all age-groups in.38.47%–44.45%of the total area are susceptible to mild to severe den.al/skeletal fluorosis owin. to con.umption.of un.reated n.trate an. fluoride en.iched *** Sobol sen.itivity in.ices revealed con.amin.n. levels,groun.water in.ake rate an. their collective effects are the most in.luen.ial factors to pose poten.ial health risks on.the *** recharge an. rain.ater harvestin. practices should be adopted to improve the groun.water quality an. the residen.s are advised to drin. purified groun.water.

关键词： Cokrigin. Health risks Prin.ipal compon.n. an.lysis Cluster an.lysis n.trate con.amin.tion Fluoride con.amin.tion

Biomass-derived bifun.tion.l electrocatalysts for oxygen.reduction.an. evolution.reaction. A review

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Journ.l of En.rgy Chemistry 2022年第2期31卷 149-172页

作者： Satpal singh Sekhon.Jaeyoun. Lee Jin.Soo Park Future En.iron.en. an. En.rgy Research In.titute Sangmyung UniversityCheonan 31066Republic of Korea Departmen. of Physics Guru Nanak Dev UniversityAmritsar 143005India Ertl Cen.er for Electrochemistry an. Catalysis Gwangju Institute of Science and Technology123 Cheomdangwagi-roBuk-guGwangju 61005Republic of Korea Departmen. of Green.Chemical En.in.erin. College of EngineeringSangmyung UniversityCheonan 31066Republic of Korea

Oxygen.electrode catalysts are importan. as in.er-con.ersion.of O_(2) an. H_(2)O is crucial for en.rgy ***,the sluggish kin.tics of oxygen.reduction.an. evolution.reaction.(ORR an. OER)are a hin.ran.e to their scalable production.whereas scarce an. costly Pt an. Ir/Ru-based catalysts with the highest electrocatalytic activity are commercially *** good ORR catalysts are n.t always efficien. for OER an. vice versa,so bifun.tion.l catalysts on.which OER an. ORR occurs on.the same electrode are very *** catalysts based on.heteroatom-doped carbon.n.n.materials,though showed good electrocatalytic activity yet their high cost an. complex syn.hesis is n.t viable for scalable *** overcome these drawbacks,biomass-derived heteroatom-doped porous carbon. have recen.ly emerged as low-cost,earth-abun.an.,ren.wable an. sustain.ble en.iron.en.-frien.ly materials for bifun.tion.l oxygen.*** tun.ble morphology,mesoporous structure an. high con.en.ration.of catalytic active sites of these materials due to heteroatom(n.-dopin. could further en.an.e their ORR an. OER activity,alon. with toleran.e to methan.l crossover an. good ***,biomassderived heteroatom-doped porous carbon. with large surface area,rich edge defects,n.merous micropores an. thin.2 D n.n.architecture could be suitable as efficien. bifun.tion.l oxygen.*** the presen. article,syn.hesis,n.dopin.,ORR/OER mechan.sm an. electrocatalytic performan.e of biomassderived bifun.tion.l catalysts has been.*** selected biomass(chitin.eggs,euon.mus japon.cas,tobacco,lysin. an. plan. residue)except wood,act as both C an. n.precursor,resultin. in.n.selfdopin. of porous carbon. that avoids the use of toxic chemicals,thus makin. the syn.hesis a facile an. en.iron.en.-frien.ly green.*** syn.hetic strategy could be further optimized to develop future biomass-based n.self-doped porous carbon. as metal-free high performan.e bifun.tion.l oxy

关键词： Bifun.tion.l catalysts Biomass ORR OER n.dopin. Porous carbon.

Systematic study of the(n.2n.reaction.cross section.for^(121)Sb an.^(123)Sb isotopes

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Chin.se Physics C 2022年第5期46卷 77-94页

作者： R.K.singh n.L.singh R.D.Chauhan.Mayur Mehta S.V.Suryan.rayan. Rajn.kan. Makwan. B.K.n.yak H.n.ik Tarak n.th n.g K.Katovsky Departmen. of Physics Faculty of Sciencethe M.S.University of BarodaVadodara-390002INDIA Departmen. of Physics Netaji Subhas University of TechnologyDwarkaNew Delhi-110078INDIA In.titute for Plasma Research Gandhinagar-382428INDIA n.clear Physics Division Bhabha Atomic Research CentreMumbaiINDIA Radiochemistry Division Bhabha Atomic Research CentreMumbaiINDIA Departmen. of Electrical Power En.in.erin. Brno University of TechnologyBrno-61600Czech Republic

The cross section. of the^(121)Sb(n.2n.^(120)Sb^(m) an. ^(123)Sb(n.2n.^(122)Sb reaction. were measured at 12.50,15.79 an. 18.87 MeV n.utron.en.rgies relative to the stan.ard ^(27)Al(n.α)^(24)n. mon.tor reaction.usin. n.utron.activation.an. offlin. γ-ray *** of the samples was performed at the BARC-TIFR Pelletron.Lin.c Facility,Mumbai,*** quasi-mon.en.rgetic n.utron. were gen.rated via the ^(7)Li(p,n.*** model calculation. were performed by n.clear reaction.codes TALYS(ver.1.9)an. EMPIRE(ver.3.2.2)usin. various in.ut parameters an. n.clear level den.ity *** cross section. of the groun. an. the isomeric state as well as the isomeric cross section.ratio were studied theoretically from reaction.threshold to 26 MeV *** effect of pre-equilibrium emission.is also discussed in.detail usin. differen. theoretical *** presen. measured cross section. were discussed an. compared with the reported experimen.al data an. evaluation.data of the JEFF-3.3,En.F/B-VIII.0,JEn.L/AD-2017 an. TEn.L-2019 libraries.A detailed an.lysis of the un.ertain.ies in.the measured cross section.data was performed usin. the covarian.e an.lysis ***,a systematic study of the(n.2n.reaction.cross section.for^(121)Sb an.^(123)Sb isotopes was also performed within.14-15 MeV n.utron.en.rgies usin. various systematic *** work helps to overcome discrepan.ies in.Sb data an. illustrate a better un.erstan.in. of pre-equilibrium emission.in.the(n.2n.reaction.chan.el.

关键词： an.imon. (n.2n.reaction.cross section 7Li(p,n.reaction.n.utron.source n.utron.activation.an. offlin.γ-ray spectrometry systematic formulae covarian.e an.lysis TALYS(ver.1.9)an. EMPIRE(ver.3.2.2)codes

Deep learn.n. based computer vision.approaches for smart agricultural application.

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Artificial In.elligen.e in.Agriculture 2022年第1期6卷 211-229页

作者： V.G.Dhan.a A.Subeesh n.L.Kushwaha Din.sh Kumar Vishwakarma T.n.gesh Kumar G.Ritika A.n.singh ICAR-In.ian.In.titute of Seed Scien.e MauUttar Pradesh 275101India ICAR-Cen.ral In.titute of Agricultural En.in.erin. BhopalMadhya Pradesh 462038India ICAR-In.ian.Agricultural Research In.titute New Delhi 110012India Govin. Ballabh Pan. Un.versity of Agriculture an. Techn.logy PantnagarUttarakhand 263145India ICAR-n.tion.l In.titute of n.tural Fibre En.in.erin. an. Techn.logy Kolkata 700040India

The agriculture in.ustry is un.ergoin. a rapid digital tran.formation.an. is growin. powerful by the pillars of cuttin.-edge approaches like artificial in.elligen.e an. allied *** the core of artificial in.elligen.e,deep learn.n.-based computer vision.en.bles various agriculture activities to be performed automatically with utmost precision.en.blin. smart agriculture in.o *** vision.techn.ques,in.con.un.tion.with high-quality image acquisition.usin. remote cameras,en.ble n.n.con.act an. efficien. techn.logy-driven.solution. in.*** review con.ributes to providin. state-of-the-art computer vision.techn.logies based on.deep learn.n. that can.assist farmers in.operation. startin. from lan. preparation.to *** works in.the area of computer vision.were an.lyzed in.this paper an. categorized in.o(a)seed quality an.lysis,(b)soil an.lysis,(c)irrigation.water man.gemen.,(d)plan. health an.lysis,(e)weed man.gemen.(f)livestock man.gemen. an.(g)yield *** paper also discusses recen. tren.s in.computer vision.such as gen.rative adversarial n.tworks(GAn.,vision.tran.formers(ViT)an. other popular deep learn.n. ***,this study pin.oin.s the challen.es in.implemen.in. the solution. in.the farmer’s field in.*** overall fin.in. in.icates that con.olution.l n.ural n.tworks are the corn.r ston. of modern.computer vision.approaches an. their various architectures provide high-quality solution. across various agriculture activities in.terms of precision.an. ***,the success of the computer vision.approach lies in.buildin. the model on.a quality dataset an. providin. real-time solution..

关键词： Agriculture automation Computer vision Deep learn.n. Machin. learn.n. Smart agriculture Vision.tran.formers