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Chinese Journal of Chemistry 2012年第3期30卷 547-556页

作者： Issa,Raafat Mostafa Gaber,Mohammed al-wakiel,nadia abd-elhamed Fathalla,Shaimaa Kamal Chemistry Department Faculty of ScienceTanta University31527 TantaEgypt

Mn（Ⅱ）, Co（Ⅱ）, Ni（Ⅱ） and Cu（Ⅱ） complexes of 5-mercapto-1,2,4-triazol-3-imine-2＇-hydroxynaphthaline have been synthesized and characterized by elemental analysis, IR, IH NMR, EI-mass, UV-Vis, and ESR （electron spin resonance） spectra, molar conductance, magnetic moment measurements, DC conductivity and thermogravimetric analysis. IR spectra confirm that the ligand molecule existed in both thione and thiole forms. The molar conduc- tance values indicate the complexes are nonelectrolyte. The magnetic moment values of the complexes display paramagnetic behavior. all studies confirm the formation of an octahedral geometry for complex 1 and the other complexes have tetrahedral geometrical structures. The structures of the complexes have also been theoretically studied by using the molecular mechanic calculations by the hyperchem. 8.03 molecular modeling program which confirm the proposed structures. The Schiff-base ligand and its metal complexes have also been screened for their antimicrobial activities.

关键词： inorganic chemistry spectral thermal biological studies conductance triazole Schiffbase

Enhancing the Decomposition of Paper Cups Using Galleria Mellonella and Eisenia Fetida

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Journal of Renewable Materials 2024年第2期12卷 349-367页

作者： Shadi Moqbel Habib al-Ghoul abd al-Majeed al-Ghzawi Rami Mukbel Civil Engineering Department The University of JordanAmman11942Jordan Department of Chemistry Technical University of MunichMunichGermany Plant Production Jordan University of Science and TechnologyIrbid22110Jordan Basic Medical Veterinary Sciences Jordan University of Science and TechnologyIrbid22110Jordan

The composition of paper cups creates a challenge for the recycling industry,as the paperboard–plastic film composite is hard to ***,paper cups are sent to landfills or waste *** study explores the combined use of red worms(Eisenia fetida)and Greater wax moth(Galleria mellonella)in the biodegradation of paper *** study investigates the conditions and combinations that promote using Eisenia fetida and Galleria mellonella for degrading paper *** study considered the influence of environmental temperature,the presence of food waste,varying the number of Eisenia fetida worms,and the presence of a Galleria mellonella growth-slowing agent on the degradation *** achieve the study objectives,the study followed a quantitative *** study monitored the degradation of paper cup cuts that were placed in jars containing different combinations of Eisenia fetida worms,Galleria mellonella larvae,food waste,bedding material,and Galleria mellonella growth-slowing *** study found that the best operating temperature is *** study found that using food waste improves the performance of Eisenia fetida worms and Galleria mellonella larvae *** study found that adding a Galleria mellonella growth-slowing agent slightly enhances the degradation of the paper ***,a numerical model was obtained to simulate the paper cup degradation efficiency.

关键词： Paper cups resource recovery recycling circular economy Galleria mellonella Eisenia fetida

Phytochemical analysis, antioxidant, acetylcholinesterase, and α-amylase inhibitors from Hippeastrum hybridum extract

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Journal of Traditional Chinese Medicine 2024年第3期44卷 496-504页

作者： Naila Sher Mushtaq Ahmed nadia Mushtaq Department of Biotechnology University of Science and Technology Department of Botany University of Science and Technology

OBJECTIVE:To investigate the effects of Hippeastrum hybridum（HH） as a free radical scavenger,and an inhibitor of the two enzymes i-e alpha-amylase（α-amylase） and acetylcholinesterase（AChE）.METHODS:In this study,HH plant was preliminary analyzed for phytochemical screening and then tested for its antioxidant,anti-α-amylase,and anti-AChE efficiency via standard ***:Phytochemical analysis shows the existence of different compounds;while Coumarins and quinones were *** total phenolic,flavonoid,and tannins content were found to be（78.52±0.69） mg GAE/g,（2.01±0.04） mg RUE/g,and（58.12±0.23） mg TAE/g of plant extract respectively.28.02%±0.02% alkaloid and 2.02%±0.05% saponins were present in the HH *** HH extract showed the anti-oxidant property with IC50（50%inhibition） of（151.01±0.13）(HH),（79.01±0.04）(Ascorbic acid) for ferric reducing,（91.48±0.13）(HH),（48.02±0.11）(Ascorbic acid) against Ammonium molybdenum,（156.02±0.31）(HH),（52.38±0.21）(Ascorbic acid) against DPPH,136.01±0.21（HH）,52.02±0.31（Ascorbic acid） against H2O2,and 154.12±0.03（HH）,（40.05±0.15）(Ascorbic acid)μg/mL against ABTS *** analysis indicated that HH caused a competitive type of inhibition of α-amylase(Vmaxremained constant and Km increases from 10.65 to84.37%) while Glucophage caused the un-competitive type of inhibition i-e both Km and Vmaxdecreased from40.49 to 69.15%and 38.86 to 69.61%*** Ki,（inhibition constant）;KI,（dissociation constant）,Km,（Michaelis-Menten constant）,and IC50 were found to be62,364,68.1,and 38.08±0.22 for HH and 12,101.05,195,34.01±0.21 for ***,HH causes an anon-competitive type of inhibition of AChE i-e Km remains constant while Vmaxdecreases from 60.5%to74.1%.The calculated Ki,KI,Km,and IC50 were found to be 32,36.2,0.05,and 18.117±***:From the current results,it is concluded that HH extract contains bioactive compounds,and could be a good alternative to controlling oxidants,alzheimer‘s and T

关键词： Hippeastrum hybridum acetylcholinesterase alpha-amylase antioxidant phytochemicals

ANonmonotone Projected Gradient Method for Multiobjective Problems on Convex Sets

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Journal of the Operations Research Society of China 2024年第2期12卷 410-427页

作者： Gabrie Anibal Carrizo nadia Soledad Fazzio Maria Laura Schuverdt Department of Mathematics National University of the SouthBahia BlancaArgentina Department of Mathematics University of La PlataLa PlataArgentina

In this work we consider an extension of the classical scalar-valued projected gradient method for multiobjective problems on convex *** in Fazzio et al.(Optim Lett 13:1365-1379,2019)a parameter which controls the step length is considered and an updating rule based on the spectral gradient method from the scalar case is *** the present paper,we consider an extension of the traditional nonmonotone approach of Grippo et al.(SIAM J Numer Anal 23:707-716,1986)based on the maximum of some previous function values as suggested in Mita et al.(J Glob Optim 75:539-559,2019)for unconstrained multiobjective optimization *** prove the accumulation points of sequences generated by the proposed algorithm,if they exist,are stationary points of the original *** experiments are reported.

关键词： Multiobjective optimization Projected gradient methods Nonmonotone line search Global convergence

Privacy-preserved learning from non-i.i.d data in fog-assisted IoT:A federated learning approach

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Digital Communications and Networks 2024年第2期10卷 404-415页

作者： Mohamed abdel-Basset Hossam Hawash Nour Moustafa Imran Razzak Mohamed abd Elfattah Faculty of Computers and Informatics Zagazig UniversityZagazigSharqiyah44519Egypt School of Engineering and Information Technology University of New South Wales@ADFACanberraACT2600Australia Deakin University Geelong Waurn Ponds CampusAustralia Computer Science Department Misr Higher Institute for Commerce and ComputersMansoura35511Egypt

With the prevalence of the Internet of Things(IoT)systems,smart cities comprise complex networks,including sensors,actuators,appliances,and cyber *** complexity and heterogeneity of smart cities have become vulnerable to sophisticated cyber-attacks,especially privacy-related attacks such as inference and data poisoning *** Learning(FL)has been regarded as a hopeful method to enable distributed learning with privacypreserved intelligence in IoT *** though the significance of developing privacy-preserving FL has drawn as a great research interest,the current research only concentrates on FL with independent identically distributed(i.i.d)data and few studies have addressed the non-i.i.d *** is known to be vulnerable to Generative Adversarial Network(GAN)attacks,where an adversary can presume to act as a contributor participating in the training process to acquire the private data of other *** paper proposes an innovative Privacy Protection-based Federated Deep Learning(PP-FDL)framework,which accomplishes data protection against privacy-related GAN attacks,along with high classification rates from non-i.i.d ***-FDL is designed to enable fog nodes to cooperate to train the FDL model in a way that ensures contributors have no access to the data of each other,where class probabilities are protected utilizing a private identifier generated for each *** PP-FDL framework is evaluated for image classification using simple convolutional networks which are trained using MNIST and CIFAR-10 *** empirical results have revealed that PF-DFL can achieve data protection and the framework outperforms the other three state-of-the-art models with 3%–8%as accuracy improvements.

关键词： Privacy preservation Federated learning Deep learning Fog computing Smart cities

Sexual dimorphism of G protein-coupled receptor signaling in the brain

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Neural Regeneration Research 2024年第8期19卷 1635-1636页

作者： Sara aljoudi Hamdan Hamdan Khaled S.abd-Elrahman Department of Physiology and Immunology College of Medicine and Health SciencesKhalifa UniversityAbu DhabiUnited Arab Emirates Healthcare Engineering Innovation Center(HEIC) Khalifa UniversityAbu DhabiUnited Arab Emirates Department of Anesthesiology Pharmacology and Therapeuticsand Djavad Mowafaghian Center for Brain HealthUniversity of British ColumbiaVancouverBCCanada Department of Pharmacology and Therapeutics College of Medicine and Health ScienceKhalifa UniversityAbu DhabiUnited Arab Emirates Department of Pharmacology and Toxicology Faculty of PharmacyAlexandria UniversityAlexandriaEgypt

G protein-coupled receptors(GPCRs)represent the most substantial family of membrane receptors that are targeted by *** and Drug Administration-approved *** of the preclinical research to understand the pharmacology of... 详细信息

关键词： drugs clinical targeted

Nutritional and therapeutic benefits of coconut milk and its potential as a plant-based functional yogurt alternative: a review

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Food Science and Human Wellness 2024年

作者： Gengghatarani Gengan Nurul Solehah Mohd Zaini Nazamid Saari Anis Shobirin Meor Hussin Ahmad Haniff Jaafar Hanan Hasan Elicia Jitming Lim Wan abd al Qadr Imad Wan-Mohtar Muhamad Hafiz abd Rahim Functional Omics and Bioprocess Development Laboratory Institute of Biological Sciences Faculty of Science Universiti Malaya Faculty of Food Science and Technology Universiti Putra Malaysia School of Life and Environmental Sciences The University of Sydney

Plant-based milks are on the rise due to an increased awareness of their sustainability and health benefits. Currently， dairy milk is the most nutritionally complete beverage， but it suffers from the presence of indigestible lactose and allergenic proteins. Coconut milk has been around for a long time， but its application is limited due to a perceived lack of specific nutrients， high saturated fat levels， and low acceptability. Recent evidence indicates， however， that the saturated fat and other plant-based components found in coconut milk are good for metabolic outcomes and brain health. The conversion of coconut milk to yoghurt will further improve its functionality by boosting its existing nutritional qualities. In this article， the nutritional value of coconut milk， as well as its potential downsides， its application as yoghurt， and suggestions for enhancing its nutritional functionality will be examined.

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Single image super-resolution:a comprehensive review and recent insight

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Frontiers of Computer Science 2024年第1期18卷 139-156页

作者： Hanadi al-MEKHLAFI Shiguang LIU College of Intelligence and Computing Tianjin UniversityTianjin 300350China

Super-resolution(SR)is a long-standing problem in image processing and computer vision and has attracted great attention from researchers over the *** main concept of SR is to reconstruct images from low-resolution(LR)to high-resolution(HR).It is an ongoing process in image technology,through up-sampling,de-blurring,and *** neural network(CNN)has been widely used to enhance the resolution of images in recent *** alternative methods use deep learning to improve the progress of image super-resolution based on ***,we review the recent findings of single image super-resolution using deep learning with an emphasis on distillation knowledge used to enhance image super-resolution.,it is also to highlight the potential applications of image super-resolution in security monitoring,medical diagnosis,microscopy image processing,satellite remote sensing,communication transmission,the digital multimedia industry and video ***,we present the challenges and assess future trends in super-resolution based on deep learning.

关键词： super-resolution deep learning single-image interpolation-based learning-based reconstruction-based

RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad al-Ahmadi Jalal al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

Developing a Model for Parkinson’s Disease Detection Using Machine Learning algorithms

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Computers, Materials & Continua 2024年第6期79卷 4945-4962页

作者： Naif al Mudawi Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia

Parkinson’s disease(PD)is a chronic neurological condition that progresses over *** start to have trouble speaking,writing,walking,or performing other basic skills as dopamine-generating neurons in some brain regions are injured or *** patient’s symptoms become more severe due to the worsening of their signs over *** this study,we applied state-of-the-art machine learning algorithms to diagnose Parkinson’s disease and identify related risk *** research worked on the publicly available dataset on PD,and the dataset consists of a set of significant characteristics of *** aim to apply soft computing techniques and provide an effective solution for medical professionals to diagnose PD *** research methodology involves developing a model using a machine learning *** the model selection,eight different machine learning techniques were adopted:Namely,Random Forest(RF),Decision Tree(DT),Support Vector Machine(SVM),Naïve Bayes(NB),Light Gradient Boosting Machine(LightGBM),K-Nearest Neighbours(KNN),Extreme Gradient Boosting(XGBoost),and Logistic Regression(LR).Subsequently,the concentrated models were validated through 10-fold Cross-Validation and Receiver Operating Characteristic(ROC)—Area Under the Curve(AUC).In addition,GridSearchCV was utilised to measure each algorithm’s best parameter;eventually,the models were trained through the hyperparameter tuning *** 98%accuracy,LightGBM had the highest accuracy in this ***,KNN,and SVM came in second with 96%***,the performance scores of NB and LR were recorded to be 76%and 83%,*** is to be mentioned that after applying 10-fold cross-validation,the average performance score of LightGBM accounted for 93%.At the same time,the percentage of ROC-AUC appeared at 0.92,which indicates that this LightGBM model reached a satisfactory ***,we extracted meaningful insights and figured out potential gaps on top of *** extracting meaningful in

关键词： Light GBM cross-validation ROC-AUC Parkinson’s disease(PD) SVM and XGBoost