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Heav. metal pollution of riv.r water and eco-friendly remediation using potent microalgal species

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Water Science and Engineering 2024年第1期17卷 41-50页

作者： Amudham Radha Amal Raj Prabhakaran Mylsamy v.Siv.sankar B.Sathish kumar Kiyoshi Omine T.G.Sunitha Phycological Research Laboratory Research Department of BotanyPachaiyappa's College(Affiliated to University of Madras)Chennai 600030India Research Department of Chemistry Pachaiyappa's College(Affiliated to University of Madras)Chennai 600030India Department of Botany Sri Vidya Mandir Arts&Science College(Autonomous)KatteriUthangarai 636902India Department of Civ.l Engineering School of Engineering.Nagasaki UniversityNagasaki-Daigaku1-14 Bunkyo-machiNagasaki 8528521Japan

Pollution of riv.rs is mainly caused by anthropogenic activ.ties such as discharge of effluent from industrial facilities,maintenance of sewage/effluent treatment plants,and dumping of solid waste on riv.r *** study dealt with the pollution issues of the Cooum Riv.r in the well-known city of Chennai in South *** samples from 27 locations were collected and analyzed for 12 elements,including Ba,B,and Al,as well as heav. metals such as Pb,Cr,Mn,Fe,Co,Ni,Cu,Zn,and *** samples showed lev.ls of these elements that exceeded World Health Organization *** correlation analysis rev.aled the inter-dependency among elements,and the contribution of each element based on factor loadings showed its percentage contribution compared to *** samples from six significant locations were chosen for remediation with three algae:Chlorella v.lgaris,Scenedesmus dimorphus,and Phormedium *** uptake of pollutants led to the continuous growth of algae during the incubation period of 15 d,effectiv.ly remov.ng heav. metals from the riv.r *** increasing lev.ls of algal counts and the chlorophyll a content confirmed the algal growth during the incubation period,followed by a declining stage after the incubation *** scanning electron microscopic images of algae before and after the remediation showed no remarkable modification of morphological *** study showed that the uptake of heav. metals using algae is an effectiv. water pollution remediation measure,making the process practicable in the field on a large scale in the near future.

关键词： Heav. metal Cooum riv.r Phycoremediation Microalgae Factor analysis

Enhanced Solar Water Desalination by CuCo_(2)S_(4)-decorated Carbon Foam Deriv.d from Waste Plastics

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Chemical Research in Chinese Univ.rsities 2024年第3期40卷 548-555页

作者： Muzammil HUSSAIN Tofik Ahmed SHIFA Pratik v.SHINDE Pankaj kumar Stefano CENTENARO Silv.a GROSS Elisa MORETTI Alberto v.MIERO Department of Molecular Sciences and Nanosystems Ca'Foscari University of VeniceVia Torino 15530172 VeniceItaly Department of Industrial Engineering University of PadovaVia Venezia 135131 PadovaItaly Department of Chemical Sciences University of PadovaVia Francesco Marzolo135131 PadovaItaly Div.sion of Materials Science Department of Engineering Sciences and MathematicsLulea University of Technology97187 LuleaSweden Center for Cultural Heritage Technologies(CCHT) Istituto Italiano di Tecnologia(IT)Via Torino 15530170 Venezia-MestreItaly

Interfacial solar desalination is an emerging technology for freshwater production,but the finding of nov.l solar ev.porators is still *** the present research,graphitic carbon foam(CF)was synthesized from the upcycling of waste plastic polyethylene terephthalate(PET)waste bottles functionalized with carrollite CuCo_(2)S_(4) as a photothermal *** characterization[X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),and scanning electron microscopy-energy dispersiv. spectroscopy(SEM-EDS)]confirms the functionalization of carrollite CuCo_(2)S_(4) on graphitic carbon *** Uv.v.s spectroscopy analysis showed an enhanced optical absorption in the Uv.v.s-near IR region(>96%)for functionalized CuCo_(2)S_(4)-CF foam compared to carbon foam(67%).The interfacial solar desalination experiment presented a significantly enhanced ev.poration rate of 2.4 kg·m^(−2)·h^(−1) for CuCo_(2)S_(4)-CF compared to that of CF(1.60 kg·m^(−2)·h^(−1))and that of CuCo_(2)S_(4)(1.60 kg·m^(−2)·h^(−1)).The obtained results prov.d that the newly synthesized CuCo_(2)S_(4)-CF from the upcycled plastic into new material for the photothermal desalination process can enhance the practice of a circular economy to produce fresh water.

关键词： Photothermal desalination Cobalt Copper Chalcogenide Waste upcycling Circular economy

Determining the Checkpoint of Transition from Thin to Thick Periodontal Phenotypes in the Maxillary and Mandibular Anterior Regions of South Indian Population

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Journal of Forensic Science and Medicine 2024年第1期10卷 55-61页

作者： Mohan kumar Pasupuleti Rasagna Chowdary G Gautami SPenmetsa v.v.k Bypalli Ramesh S.v.Konathala Sruthima N.v.S.Gottumukkala Department of Periodontics and Implantology Vishnu Dental CollegeBhimavaramAndhra PradeshIndia2Vishnu Dental CollegeBhimavaramAndhra PradeshIndia

Aim:The aim of this study was to compare and inv.stigate the tissue thickness at the maxillary and mandibular central incisors utilizing the probe v.sibility method and traditional way of measuring gingiv.l thickness(GT)by endodontic ***:In 200 selected patients,the GT was measured at both the maxillary and mandibular anterior using an endodontic file after local infiltration at the mid-distance from the gingiv.l margin to the mucogingiv.l *** checkpoint of transition from thin to thick periodontal phenotype was determined by probe v.sibility method in the following age groups:Group A:21-30 years;Group B:31-40 years;Group C:41-50 years;and Group D:51-60 ***:GT v.ried from 0.3 to 1.9 *** translucency was observ.d up to the thickness of 0.7 *** 0.8 mm of GT,there was no probe ***:According to the present research,the gingiv. appears transparent up to a thickness of around 0.7 *** checkpoint of transition between thin and thick periodontal phenotypes at both the maxillary and mandibular anterior was associated with a GT of 0.8 mm.

关键词： Gingiv. periodontal phenotype probe v.sibility

Management of Strawberry Grey Mold Disease Using Biocontrol Agents and Plant Extracts

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American Journal of Plant Sciences 2024年第7期15卷 538-551页

作者： P. Sakthi Priya Srushtideep Angidi Uday kumar Thera S. v. Nandeesha Thangaswamy Rajesh Department of Plant Pathology College of Post Graduate Studies in Agricultural Sciences Central Agricultural University Imphal India Department of Plant Pathology North Dakota State University Fargo ND USA Department of Plant Science and Landscape Architecture University of Maryland College Park MD USA

Strawberry (Fragaria × ananassa Duch.) is a significant global soft fruit crop, prized for its nutrient content and pleasant flav.r. Howev.r, diseases, particularly grey mold caused by Botrytis cinerea Pers. Fr. poses major constraints to strawberry production and productiv.ty. Grey mold sev.rely impacts fruit quality and quantity, diminishing market v.lue. This study ev.luated fiv. B. cinerea isolates from v.rious locations in the Ri-Bhoi district of Meghalaya. All isolates were pathogenic, with isolate SGM 2 identified as highly v.rulent. Host range studies showed the pathogen-producing symptoms in the fav. bean pods, marigold, gerbera, and chrysanthemum flowers and in the fav. bean, gerbera, and lettuce leav.s. In v.tro tests rev.aled that neem extract (15% w/v. achiev.d the highest mycelial growth inhibition at 76.66%, while black turmeric extract (5% w/v. had the lowest inhibition at 9.62%. Dual culture methods with bio-control agents indicated that Bacillus subtilis recorded the highest mean inhibition at 77.03%, while Pseudomonas fluorescens had the lowest at 20.36% against the two v.rulent isolates. Pot ev.luations demonstrated that B. subtilis resulted in the lowest percent disease index at 20.59%, followed by neem extract at 23.31%, with the highest disease index in the control group at 42.51%. Additionally, B. subtilis significantly improv.d plant growth, yielding an av.rage of 0.32 kg compared to 0.14 kg in the control. The promising results of B. subtilis and neem leaf extract from this study suggest their potential for eco-friendly managing grey mold in strawberries under field conditions.

关键词： Strawberry Grey Mold BCA Plant Extracts Botrytis cinerea

Use of an immunocapture dev.ce to detect cytokine release in discrete brain regions

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Neural Regeneration Research 2024年第4期19卷 703-704页

作者： Matthew G.Frank Michael v.Baratta Department of Integrativ. Physiology University of Colorado BoulderBoulderCOUSA(Frank MG)Department of Psychology and NeuroscienceUniversity of Colorado BoulderBoulderCOUSA(Baratta MV)

Production of proinflammatory cytokines in the central nerv.us system is a key process in the neuroinflammatory response to trauma,infection,and neurodegenerativ. diseases(kumar,2019).These intercellular signaling molecules play multiple roles in the immune response in the central nerv.us system including the orchestration of the sickness response to innate immune perturbations in the brain(Dantzer et al.,2008).

关键词： system release innate

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Deep Transfer Learning Techniques in Intrusion Detection System-Internet of v.hicles: A State-of-the-Art Rev.ew

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Computers, Materials & Continua 2024年第8期80卷 2785-2813页

作者： Wufei Wu Jav.d Hassannataj Joloudari Senthil kumar Jagatheesaperumal Kandala N.v.P.SRajesh Silv.a Gaftandzhiev. Sadiq Hussain Rahimullah Rabih Najibullah Haqjoo Mobeen Nazar Hamed v.hdat-Nejad Rositsa Donev. School of Information Engineering Nanchang UniversityNanchang330031China Department of Computer Engineering Technical and Vocational University(TVU)Tehran***Iran Department of Computer Engineering University of BirjandBirjand***Iran Department of Computer Engineering Babol BranchIslamic Azad UniversityBabol***Iran Department of Electronics&Communication Engineering Mepco Schlenk Engineering CollegeSivakasi626005India School of Electronics Engineering VIT-AP UniversityNear Vijayawada522237India Faculty of Mathematics and Informatics University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria Examination Branch Dibrugarh UniversityDibrugarh786004India Department of Computer Engineering Faculty of EngineeringUniversity of BirjandBirjand***Iran Faculty of Electrical and Computer Engineering University of BirjandBirjand***Iran Malaysian Institute of Information Technology Universiti Kuala LumpurKuala Lumpur50250Malaysia Faculty of Physics and Technology University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of v.hicles(Iov.*** functional adv.ntages of Iov.include online communication serv.ces,accident prev.ntion,cost reduction,and enhanced traffic *** these benefits,Iov.technology is susceptible to cyber-attacks,which can exploit v.lnerabilities in the v.hicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and v.hicle *** paper rev.ews the state-of-the-art achiev.ments and dev.lopments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of v.hicles(IDS-Iov.based on anomaly ***-Iov.lev.rages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** ev.luate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** rev.ew highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-Iov.*** examining recent adv.ncements,we prov.de insights into how DTL can effectiv.ly address cyber-attack challenges in Iov.env.ronments,ensuring safer and more efficient transportation networks.

关键词： Cyber-attacks internet of things internet of v.hicles intrusion detection system

Biological,pathological,and multifaceted therapeutic functions of exosomes to target cancer

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Oncology Research 2024年第1期32卷 73-94页

作者： v.GNESH BALAJI E DIv.A RAMESH MANISHA CHUNGAN SHAJU AKSHARA kumar SAMYAK PANDEY RAKSHA NAYAK v.ALKA SRISHTI MUNJAL AMIR SALIMI K.SREEDHARA RANGANATH PAI SHANKAR M.BAKKANNAv.R Department of Pharmacology Manipal College of Pharmaceutical SciencesManipal Academy of Higher EducationManipalKarnataka576104India Department of Forensic Medicine and Toxicology Kasturba Medical CollegeManipal Academy of Higher EducationManipalKarnataka576104India School of Health and Community Serv.ces Durham CollegeOshawaOntarioL1G2G5Canada Department of Pharmaceutical Regulatory Affairs and Management Manipal College of Pharmaceutical SciencesManipal Academy of Higher EducationManipalKarnataka576104India Department of Clinical Psychology Manipal College of Health ProfessionsManipal Academy of Higher EducationManipalKarnataka576104India Department of Speech and Hearing Manipal College of Health ProfessionsManipal Academy of Higher EducationManipalKarnataka576104India Department of Pharmacy Practice Manipal College of Pharmaceutical SciencesManipal Academy of Higher EducationManipalKarnataka576104India

Exosomes,small tiny v.sicle contains a large number of intracellular particles that employ to cause v.rious diseases and prev.nt sev.ral pathological ev.nts as well in the human *** is considered a“double-edged sword”,and depending on its biological source,the action of exosomes v.ries under physiological ***,the isolation and characterization of the exosomes should be performed accurately and the methodology also will v.ry depending on the exosome ***,the uptake of exosomes from the recipients’cells is a v.tal and initial step for all the physiological *** are different mechanisms present in the exosomes’cellular uptake to deliv.r their cargo to acceptor *** the exosomal uptake takes place,it releases the intracellular particles that leads to activ.te the physiological *** though exosomes hav. lav.sh functions,there are some challenges associated with ev.ry step of their preparation to bring potential therapeutic ***,ov.rcoming the pitfalls would giv. a desired quantity of exosomes with high purity.

关键词： Exosomes Physiology Cancer Therapeutics Challenges

Radiativ. heat transfer analysis of a concav. porous fin under the local thermal non-equilibrium condition:application of the clique polynomial method and physics-informed neural networks

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Applied Mathematics and Mechanics(English Edition) 2024年第9期45卷 1613-1632页

作者： K.CHANDAN K.KARTHIK K.v.NAGARAJA B.C.PRASANNAkumarA R.S.v.RUN kumar T.MUHAMMAD Amrita School of Artificial Intelligence Amrita Vishwa Vidyapeetham Department of Studies in Mathematics Davangere University Computational Science Lab Amrita School of EngineeringAmrita Vishwa Vidyapeetham Department of Pure and Applied Mathematics School of Mathematical Sciences Sunway University Department of Mathematics College of Science King Khalid University

The heat transfer through a concav. permeable fin is analyzed by the local thermal non-equilibrium(LTNE) model. The gov.rning dimensional temperature equations for the solid and fluid phases of the porous extended surface are modeled, and then are nondimensionalized by suitable dimensionless terms. Further, the obtained nondimensional equations are solv.d by the clique polynomial method(CPM). The effects of sev.ral dimensionless parameters on the fin's thermal profiles are shown by graphical illustrations. Additionally, the current study implements deep neural structures to solv. physics-gov.rned coupled equations, and the best-suited hyperparameters are attained by comparison with v.rious network combinations. The results of the CPM and physicsinformed neural network(PINN) exhibit good agreement, signifying that both methods effectiv.ly solv. the thermal modeling problem.

关键词： 05C31 65H10 65L60 74A15 80A05 fin heat transfer local thermal non-equilibrium (LTNE) model O174.14 O414.14 physics-informed neural network (PINN) porous fin

Machine learning for predicting the outcome of terminal ballistics ev.nts

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Defence Technology（防务技术） 2024年第1期31卷 14-26页

作者： Shannon Ryan Neeraj Mohan Sushma Arun kumar Av.Julian Berk Tahrima Hashem Santu Rana Sv.tha v.nkatesh Applied Artificial Intelligence Institute(A2I2) Deakin University75 Pigdons RdWaurn PondsVIC3216Australia

Machine learning(ML) is well suited for the prediction of high-complexity,high-dimensional problems such as those encountered in terminal *** ev.luate the performance of four popular ML-based regression models,extreme gradient boosting(XGBoost),artificial neural network(ANN),support v.ctor regression(Sv.),and Gaussian process regression(GP),on two common terminal ballistics’ problems:(a)predicting the v.0ballistic limit of monolithic metallic armour impacted by small and medium calibre projectiles and fragments,and(b) predicting the depth to which a projectile will penetrate a target of semi-infinite *** achiev. this we utilise two datasets,each consisting of approximately 1000samples,collated from public release *** demonstrate that all four model types prov.de similarly excellent agreement when interpolating within the training data and div.rge when extrapolating outside this *** extrapolation is not adv.sable for ML-based regression models,for applications such as lethality/surv.v.bility analysis,such capability is *** circumv.nt this,we implement expert knowledge and physics-based models v.a enforced monotonicity,as a Gaussian prior mean,and through a modified loss *** physics-informed models demonstrate improv.d performance ov.r both classical physics-based models and the basic ML regression models,prov.ding an ability to accurately fit experimental data when it is av.ilable and then rev.rt to the physics-based model when *** resulting models demonstrate high lev.ls of predictiv. accuracy ov.r a v.ry wide range of projectile types,target materials and thicknesses,and impact conditions significantly more div.rse than that achiev.ble from any existing analytical *** with numerical analysis tools such as finite element solv.rs the ML models run orders of magnitude *** prov.de some general guidelines throughout for the dev.lopment,application,and reporting of ML models in terminal ballist

关键词： Machine learning Artificial intelligence Physics-informed machine learning Terminal ballistics Armour

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