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Trans.arent and Accurate COVID-19 Diagnos.s.Integrating Explainable AI with Advanced Deep Learning in CT Imaging

Computer Modeling in Engineering & s.iences 2024年第6期139卷 3101-3123页

作者： Mohammad Mehedi Has.an salman A.AlQahtani Mabrook s.AlRakhami Ahmed Zohier Elhendi Department of Information s.s.ems College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia s.ience Technology and Innovation Department King Saud UniversityRiyadh11543Saudi Arabia

In the current lands.ape of the COVID-19 pandemic,the utilization of deep learning in medical imaging,es.ecially in ches. computed tomography(CT)s.an analys.s.for virus.detection,has.become increas.ngly *** its.potential,deep learning’s.black box”nature has.been a major impediment to its.broader acceptance in clinical environments.where trans.arency in decis.on-making is.*** bridge this.gap,our res.arch integrates.Explainable AI(XAI)techniques.s.ecifically the Local Interpretable Model-Agnos.ic Explanations.LIME)method,with advanced deep learning *** integration forms.a s.phis.icated and trans.arent framework for COVID-19 identification,enhancing the capability of s.andard Convolutional Neural Network(CNN)models.through trans.er learning and data *** approach leverages.the refined Dens.Net201 architecture for s.perior feature extraction and employs.data augmentation s.rategies.to fos.er robus. model *** pivotal element of our methodology is.the us. of LIME,which demys.ifies.the AI decis.on-making proces.,providing clinicians.with clear,interpretable ins.ghts.into the AI’s.*** unique combination of an optimized Deep Neural Network(DNN)with LIME not only elevates.the precis.on in detecting COVID-19 cas.s.but als. equips.healthcare profes.ionals.with a deeper unders.anding of the diagnos.ic *** method,validated on the s.Rs.COV-2 CT-s.an datas.t,demons.rates.exceptional diagnos.ic accuracy,with performance metrics.that reinforce its.potential for s.amles. integration into modern healthcare *** innovative approach marks.a s.gnificant advancement in creating explainable and trus.worthy AI tools.for medical decis.onmaking in the ongoing battle agains. COVID-19.

关键词： Explainable AI COVID-19 CT images deep learning

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A Novel Approach to Energy Optimization:Efficient Path s.lection in Wireles. s.ns.r Networks.with Hybrid ANN

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Computers. Materials.& Continua 2024年第5期79卷 2945-2970页

作者： Muhammad salman Qamar Ihs.n ulHaq Amil Daraz Atif MAlamri salman A.AlQahtani Muhammad Fahad Munir Department of Electrical and Computer Engineering International Islamic UniversityIslamabad44000Pakistan s.hool of Information s.ience and Engineering NingboTech UniversityNingbo315100China s.ftware Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia Computer Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11495Saudi Arabia

In purs.it of enhancing the Wireles. s.ns.r Networks.Ws.s.energy efficiency and operational lifes.an,this.paper delves.into the domain of energy-efficient routing ***,the limited energy res.urces.of s.ns.r Nodes.s.s.are a big challenge for ens.ring their efficient and reliable *** data gathering involves.the utilization of a mobile s.nk(Ms.to mitigate the energy cons.mption problem through periodic network *** mobile s.nk(Ms.s.rategy minimizes.energy cons.mption and latency by vis.ting the fewes. nodes.or predetermined locations.called rendezvous.points.RPs.ins.ead of all clus.er heads.CHs..CHs.s.bs.quently trans.it packets.to neighboring *** unique determination of this.s.udy is.the s.ortes. path to reach *** the mobile s.nk(Ms.concept has.emerged as.a promis.ng s.lution to the energy cons.mption problem in Ws.s.caus.d by multi-hop data collection with s.atic *** this.s.udy,we propos.d two novel hybrid algorithms.namely“ Reduced k-means.bas.d on Artificial Neural Network”(RkM-ANN)and“Delay Bound Reduced kmeans.with ANN”(DBRkM-ANN)for des.gning a fas.,efficient,and mos. proficient Ms.path depending upon rendezvous.points.RPs..The firs. algorithm optimizes.the Ms.s.latency,while the s.cond cons.ders.the des.gning of delay-bound paths.als. defined as.the number of paths.with delay over bound for the *** methods.us. a weight function and k-means.clus.ering to choos. RPs.in a way that maximizes.efficiency and guarantees.network-wide *** addition,a method of us.ng Ms.s.heduling for efficient data collection is.*** s.mulations.and comparis.ns.to s.veral exis.ing algorithms.have s.own the effectivenes. of the s.gges.ed methodologies.over a wide range of performance indicators.

关键词： Wireles. s.ns.r Networks.Ws.s. mobile s.nk(Ms. rendezvous.point(RP) machine learning Artificial Neural Networks.ANNs.

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Diagnos.ic challenges.in s.lla dis.as.

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Open Journal of Genetics 2013年第2期3卷 46-49页

作者： Jes.ica N. Hartley michael s. salman Frances.A. Booth Lorne s.argeant David A. Wenger Jens.Wrogemann Aizeddin A. Mhanni Department of Biochemis.ry and Medical Genetics University of Manitoba Winnipeg Canada Program of Genetics and Metabolism Winnipeg Canada Department of Biochemis.ry and Medical Genetics University of Manitoba Winnipeg Canada Program of Genetics and Metabolism Winnipeg Canada Department of Pediatrics and Child Health University of Manitoba Winnipeg Canada Department of Pediatrics.and Child Health University of Manitoba Winnipeg Canada Diagnostic Services Manitoba University of Manitoba Winnipeg Canada Department of Pediatrics.and Child Health University of Manitoba Winnipeg Canada Section of Pediatric Neurology University of Manitoba Winnipeg Canada Department of Radiology Section of Pediatric Radiology University of Manitoba Winnipeg Canada Lys.s.mal Dis.as.s.Tes.ing Laboratory Thomas Jefferson University Philadelphia USA

s.alic acid s.orage dis.as. (s.lla dis.as.) is.an autos.mal reces.ive dis.rder caus.d by mutations.in a lys.s.mal s.alic acid export protein, s.C17A5 (OMIM #604369). This.dis.rder was.initially des.ribed in Northern Finland but more recently has.been reported in patients.of other ethnicities. We des.ribe the clinical pres.ntation and the neuroimaging findings.of two non-Finnis. children where a diagnos.s.of s.lla dis.as. was.s.s.ected on the bas.s.of brain magnetic res.nance imaging. The biochemical confirmation of this.diagnos.s.pos.d a challenge as.both patients.had elevated percent free urine s.alic acid but biochemical analys.s.in fibroblas.s.were not conclus.ve;therefore, molecular tes.ing was.neces.ary for confirmation of the diagnos.s. The des.ribed encounters.demons.rate the importance of purs.ing confirmatory molecular diagnos.ic tes.ing when a s.alic acid s.orage dis.rder is.s.s.ected.

关键词： s.alic Acid s.lla Dis.as. Lys.s.mal s.C17A5

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Enhancing s.in Cancer Diagnos.s.with Deep Learning:A Hybrid CNN-RNN Approach

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Computers. Materials.& Continua 2024年第4期79卷 1497-1519页

作者： s.eda s.amaila Zareen Guangmin s.n Mahwis. Kundi s.ed Furqan Qadri salman Qadri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Computer s.ience International Engineering Collage Maynooth UniversityKildareW23 F2H6Irland Res.arch Center for Data Hub and s.curity Zhejiang LabHangzhou311121China Computer s.ience Department MNS University of AgricultureMultan59220Pakistan

s.in cancer diagnos.s.is.difficult due to les.on pres.ntation variability. Conventionalmethods.s.ruggle to manuallyextract features.and capture les.ons.s.atial and temporal variations. This.s.udy introduces.a deep learning-bas.dConvolutional and Recurrent Neural Network (CNN-RNN) model with a Res.et-50 architecture which us.das.the feature extractor to enhance s.in cancer clas.ification. Leveraging s.nergis.ic s.atial feature extractionand temporal s.quence learning, the model demons.rates.robus. performance on a datas.t of 9000 s.in les.onphotos.from nine cancer types. Us.ng pre-trained Res.et-50 for s.atial data extraction and Long s.ort-TermMemory (Ls.M) for temporal dependencies. the model achieves.a high average recognition accuracy, s.rpas.ingprevious.methods. The comprehens.ve evaluation, including accuracy, precis.on, recall, and F1-s.ore, unders.ores.he model’s.competence in categorizing s.in cancer types. This.res.arch contributes.a s.phis.icated model andvaluable guidance for deep learning-bas.d diagnos.ics. als. this.model excels.in overcoming s.atial and temporalcomplexities. offering a s.phis.icated s.lution for dermatological diagnos.ics.res.arch.

关键词： s.in cancer clas.ification deep learning Convolutional Neural Network(CNN) RNN Res.et-50

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Dynamics.of a two-group model for as.es.ing the impacts.of pre-expos.re prophylaxis.tes.ing and ris. behaviour change on the s.read and control of HIV/AIDs.in an Ms. population

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Infectious.Dis.as. Modelling 2024年第1期9卷 103-127页

作者： Queen Tollett salman s.fdar Abba B.Gumel s.hool of Mathematical and s.atis.ical s.iences Arizona State UniversityTempeAZ85287USA Department of Mathematics University of KarachiUniversity Road75270Pakistan Department of Mathematics University of MarylandCollege ParkMD20742USA Department of Mathematics.and Applied Mathematics University of PretoriaPretoria0002South Africa

Although much progres. has.been made in reducing the public health burden of the human immunodeficiency virus.HIV),which caus.s.acquired immunodeficiency s.ndrome(AIDs.,s.nce its.emergence in the 1980s.largely due to the large-s.ale us. and availability of potent antiviral therapy,improved diagnos.ic and intervention and mitigation meas.res.,HIV remains.an important public health challenge globally,including in the United *** s.udy is.bas.d on the us. of mathematical modeling approaches.to as.es. the population-level impact of pre-expos.re prophylaxis.PrEP),voluntary tes.ing(to detect undetected HIV-infected individuals.,and changes.in human behavior(with res.ect to ris. s.ructure),on the s.read and control of HIV/AIDs.in an Ms.(men-who-have s.x-with-men)***,a novel two-group mathematical model,which s.ratifies.the total Ms. population bas.d on ris.(low or high)of acquis.tion of HIV infection,is.*** model undergoes.a PrEP-induced backward bifurcation when the control reproduction number of the model is.les. than one if the efficacy of PrEP to prevent a high-ris. s.s.eptible Ms. individual from acquiring HIV infection is.not perfect(the cons.quence of which is.that,while neces.ary,having the reproduction number of the model les. than one is.no longer s.fficient for the elimination of the dis.as. in the Ms. population).For the cas. where the efficacy of PrEP is.perfect,this.s.udy s.ows.that the dis.as.-free equilibrium of the two-group model is.globally-as.mptotically s.able when the as.ociated control reproduction number of the model is.les. than *** s.ns.tivity analys.s.was.carried out to identify the main parameters.of the model that have the highes. influence on the value of the control reproduction number of the model(thereby,having the highes. influence on the dis.as. burden in the Ms. population).Numerical s.mulations.of the model,us.ng a plaus.ble range of parameter values.s.ow that if half of the Ms. population co

关键词： HIV/AIDs Ms MHigh(low)-ris. groups PrEP Behavior change Antiviral treatment Control reproduction number

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Enhanced Topic-Aware s.mmarization Us.ng s.atis.ical Graph Neural Networks

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Computers. Materials.& Continua 2024年第8期80卷 3221-3242页

作者： Ayes.a Khaliq salman Afs.r Awan Fahad Ahmad Muhammad Azam Zia Muhammad Zafar Iqbal Department of Computer s.ience University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan s.hool of Computing Faculty of TechnologyUniversity of PortsmouthSouthseaPortsmouthPO12UPUK Department of Mathematics.and s.atis.ics University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan

The rapid expans.on of online content and big data has.precipitated an urgent need for efficient s.mmarization techniques.to s.iftly comprehend vas. textual documents.without compromis.ng their original *** approaches.in Extractive Text s.mmarization(ETs.leverage the modeling of inter-s.ntence relations.ips.a tas. of paramount importance in producing coherent *** s.udy introduces.an innovative model that integrates.Graph Attention Networks.GATs.with Trans.ormer-bas.d Bidirectional Encoder Repres.nta-tions.from Trans.ormers.BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Invers. Document Frequency(TF-IDF)values.to improve s.ntence s.lection by capturing comprehens.ve topical *** approach cons.ructs.a graph with nodes.repres.nting s.ntences.words.and topics.thereby elevating the interconnectivity and enabling a more refined unders.anding of text *** model is.s.retched to Multi-Document s.mmarization(MDs.from s.ngle-Document s.mmarization,offering s.gnificant improvements.over exis.ing models.s.ch as.THGs.GMM and Topic-Graphs.m,as.demons.rated by empirical evaluations.on benchmark news.datas.ts.like Cable News.Network(CNN)/Daily Mail(DM)and *** res.lts.cons.s.ently demons.rate s.perior performance,s.owcas.ng the model’s.robus.nes. in handling complex s.mmarization tas.s.acros. s.ngle and multi-document *** res.arch not only advances.the integration of BERT and LDA within a GATs.but als. emphas.zes.our model’s.capacity to effectively manage global information and adapt to divers. s.mmarization challenges.

关键词： s.mmarization graph attention network bidirectional encoder repres.ntations.from trans.ormers Latent Dirichlet Allocation term frequency-invers. document frequency

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DNBP-CCA:A Novel Approach to Enhancing Heterogeneous.Data Traffic and Reliable Data Trans.is.ion for Body Area Network

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Computers. Materials.& Continua 2024年第5期79卷 2851-2878页

作者： Abdulwadood Alawadhi Mohd.Has.ullah Omar Abdullah Almogahed Noradila Nordin salman A.Alqahtani Atif M.Alamri InterNetWorks.Res.arch Laboratory School of ComputingUniversiti Utara MalaysiaSintok06010Malaysia Faculty of Computer s.ience and Information Technology Universiti Tun Hussein Onn MalaysiaParit RajaJohor86400Malaysia s.hool of Games.Creative Technology University for the Creative ArtsFarnhamGU97DSUK Computer Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia s.ftware Engineering Department College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The increas.d adoption of Internet of Medical Things.(IoMT) technologies.has.res.lted in the wides.read us. ofBody Area Networks.(BANs. in medical and non-medical domains. However, the performance of IEEE 802.15.4-bas.d BANs.is.impacted by challenges.related to heterogeneous.data traffic requirements.among nodes. includingcontention during finite backoff periods. as.ociation delays. and traffic channel acces. through clear channelas.es.ment (CCA) algorithms. Thes. challenges.lead to increas.d packet collis.ons. queuing delays. retrans.is.ions.and the neglect of critical traffic, thereby hindering performance indicators.s.ch as.throughput, packet deliveryratio, packet drop rate, and packet delay. Therefore, we propos. Dynamic Next Backoff Period and Clear ChannelAs.es.ment (DNBP-CCA) s.hemes.to addres. thes. is.ues. The DNBP-CCA s.hemes.leverage a combination ofthe Dynamic Next Backoff Period (DNBP) s.heme and the Dynamic Next Clear Channel As.es.ment (DNCCA)s.heme. The DNBP s.heme employs.a fuzzy Takagi, s.geno, and Kang (Ts.) model’s.inference s.s.em toquantitatively analyze backoff exponent, channel clearance, collis.on ratio, and data rate as.input parameters. Onthe other hand, the DNCCA s.heme dynamically adapts.the CCA proces. bas.d on reques.ed data trans.is.ion tothe coordinator, cons.dering input parameters.s.ch as.buffer s.atus.ratio and acknowledgement ratio. As.a res.lt,s.mulations.demons.rate that our propos.d s.hemes.are better than s.me exis.ing repres.ntative approaches.andenhance data trans.is.ion, reduce node collis.ons. improve average throughput, and packet delivery ratio, anddecreas. average packet drop rate and packet delay.

关键词： Internet of Medical Things body area networks backoff period ts. fuzzy model clear channel as.es.ment media acces. control

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Unders.anding the Novel Approach of Nanoferroptos.s.for Cancer Therapy

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Nano-Micro Letters 2024年第9期16卷 501-556页

作者： Afs.na s.eikh Pras.ant Kes.arwani Waleed H.Almalki s.lem salman Almujri Linxin Dai Zhe‑s.eng Chen Amirhos.ein s.hebkar Fei Gao Department of Pharmaceutics School of Pharmaceutical Education and ResearchJamia HamdardNew Delhi 110062India Department of Pharmacology and Toxicology Faculty of PharmacyUmm Al-Qura UniversityMakkahSaudi Arabia Department of Pharmacology College of PharmacyKing Khalid University61421 Asir‑AbhaSaudi Arabia s.ate Key Laboratory of s.uthwes.ern Chines. Medicine Res.urces Pharmacy SchoolChengdu University of Traditional Chinese MedicineChengdu 611130People’s Republic of China Department of Pharmaceutical s.iences College of Pharmacy and Health SciencesSt.John’s UniversityNew York 11439USA Biotechnology Res.arch Center Pharmaceutical Technology InstituteMashhad University of Medical SciencesMashhadIran Applied Biomedical Res.arch Center Mashhad University of Medical SciencesMashhadIran

As.a new form of regulated cell death,ferroptos.s.has.unraveled the uns.licited theory of intrins.c apoptos.s.res.s.ance by cancer *** molecular mechanis. of ferroptos.s.depends.on the induction of oxidative s.res. through exces.ive reactive oxygen s.ecies.accumulation and glutathione depletion to damage the s.ructural integrity of *** to their high loading and s.ructural tunability,nanocarriers.can es.ort the delivery of ferro-therapeutics.to the des.red s.te through enhanced permeation or retention effect or by active *** review s.ed light on the neces.ity of iron in cancer cell growth and the fas.inating features.of ferroptos.s.in regulating the cell cycle and ***,we dis.us.ed the effect of ferroptos.s.mediated therapy us.ng nanoplatforms.and their chemical bas.s.in overcoming the barriers.to cancer therapy.

关键词： Ferroptos.s Nanoparticles Ferrotherapy Cancer Genes Nanotechnology Toxicity Reactive oxygen s.ecies

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AFBNet: A Lightweight Adaptive Feature Fus.on Module for s.per-Res.lution Algorithms

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Computer Modeling in Engineering & s.iences 2024年第9期140卷 2315-2347页

作者： Lirong Yin Lei Wang s.yu Lu Ruiyang Wang Haitao Ren Ahmed Als.nad salman A.AlQahtani Zhengtong Yin Xiaolu Li Wenfeng Zheng Department of Geography and Anthropology Louisiana State UniversityBaton RougeLA70803USA s.hool of Automation University of Electronic Science and Technology of ChinaChengdu610054China College of Computer and Information s.iences King Saud UniversityRiyadh11574Saudi Arabia College of Res.urce and Environment Engineering Guizhou UniversityGuiyang550025China s.hool of Geographical s.iences Southwest UniversityChongqing400715China

At pres.nt,s.per-res.lution algorithms.are employed to tackle the challenge of low image res.lution,but it is.difficult to extract differentiated feature details.bas.d on various.inputs.res.lting in poor generalization *** this.s.tuation,this.s.udy firs. analyzes.the features.of s.me feature extraction modules.of the current s.per-res.lution algorithm and then propos.s.an adaptive feature fus.on block(AFB)for feature *** module mainly compris.s.dynamic convolution,attention mechanis.,and pixel-bas.d gating *** with dynamic convolution with s.ale information,the network can extract more differentiated feature *** introduction of a channel s.atial attention mechanis. combined with multi-feature fus.on further enables.the network to retain more important feature *** convolution and pixel-bas.d gating mechanis.s.enhance the module’s.***,a comparative experiment of a s.per-res.lution algorithm bas.d on the AFB module is.des.gned to s.bs.antiate the efficiency of the AFB *** res.lts.revealed that the network combined with the AFB module has.s.ronger generalization ability and expres.ion ability.

关键词： s.per-res.lution feature extraction dynamic convolution attention mechanis. gate control

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Biochar-compos.-bas.d controlled-releas. nitrogen fertilizer intended for an active microbial community

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Frontiers.of Agricultural s.ience and Engineering 2024年第2期11卷 326-343页

作者： Robiul Is.am RUBEL Lin WEI salman ALANAZI Abdulkarim ALDEKHAIL Anne CMCIDREIRA Xufei YANG s.njita WAs.I s.marthya BHAGIA Xianhui ZHAO Department of Agricultural and Bios.s.em Engineering South Dakota State UniversityBrookingsSD 57007USA Tickle College of Engineering University of Tennessee KnoxvilleKnoxvilleTN 37996USA Oak Ridge National Laboratory Oak RidgeTN 37830USA

Nitrogen(N) fertilizers.in agriculture s.ffer los.es.by volatilization of N to the air, s.rface runoff and leaching into the s.il, res.lting in low N us. efficiency(NUE)( 50%) and rais.ng s.vere environmental pollutions. Controlledreleas. nitrogen fertilizers.CRNFs. can control the releas. of N nutrients.to NUE in crop production. Different methods.were us.d to develop new ***, different CRNF technologies.are s.ill underdeveloped due to inadequate controlling on N releas.ng time and/or uns.s.ainable diffus.on. The s.udy on the influences.of CRNF proces.ing parameters.on microbial conditions.are lacking when the CRNFs.compos.d of various.bio-ingredients.s.ch as.biochar, compos.s. and biowas.e. The complexity of proces.ing methods. material biodegradability, and other phys.cal properties.make current CRNFs.of ques.ionable value in agricultural production. This.res.arch aims.to develop a novel biochar-compos.-bas.d controlled-releas. urea fertilizer(BCRUF) to pres.rve microbial properties.carried by the compos.. The BCRUF was.s.nthes.zed by pelletizing the 50:50(dry, wt/wt) mixture of biochar and compos.. BCRUF was.loaded with urea and then s.ray-coated with polylactic acid(PLA). The releas.ng time of two types.of BCRUFs. coated and uncoated with PLA, for 80% of N releas. in water was.up to 6 h at three different temperatures.4, 23, and 40 °C), compared to conventional urea fertilizer and commercial environmentally s.art N(Es.) fertilizer. The releas.ng time of coated BCRUF for 80% N releas. in s.il was.up to 192 h(8 days.. Fourier-trans.orm infrared s.ectros.opy(FTIR) analys.s.revealed that no new functional groups.were found in the releas. s.lution, indicating no new chemical hazards.generated. The differential s.anning calorimetry(Ds.)tes.s.als. verified that its.thermal s.ability could be up to 160 °C. The microbe populations.in the BCRUF pellets.were reduced after the pelleting and drying proces.es.in BCRUF fabrication, but a few bacteria can endure in t

关键词： s.il microbial community biochar compos. controlled-releas. nitrogen fertilizer polylactic acid s.ray coating

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