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Perceived stigma and quality of life in Parkinson’s disease with additional health conditions

General Psychiatry 2022年第3期35卷 192-200页

作者： samia s islam sandy Neargarder shraddha B Kinger Joshua T Fox-Fuller Robert D salazar Alice Cronin-Golomb Department of Psychological and Brain sciences Boston UniversityBostonMassachusettsUSA Department of Psychology Bridgewater State UniversityBridgewaterMassachusettsUSA

Background Parkinson’s disease(PD)is associated with perceived stigma and affects quality of life(QoL).Additional health conditions may influence these consequences of *** This study assessed the impact of health conditions on perceived stigma and QoL in persons with *** hypothesised that individuals with more health conditions would report more stigma and poorer *** also examined the contributions of demographic and clinical characteristics to the correlations between health conditions and perceived stigma/*** We identified 196 eligible participants from the Boston University Online survey study of Parkinson’s Disease and examined their health history,performance on multiple stigma measures,and scores on the 39-item Parkinson’s Disease Questionnaire assessing *** At least one health condition was reported by 79%of the sample,with a median of 2 and a range of 0–7 health *** perceived stigma and poorer QoL were associated with thyroid disease,depression,anxiety,and the total number of health *** correlations were related to younger age,less education,and earlier disease *** health conditions(high blood pressure,back/leg surgery,headache,cancer/tumours,and heart disease)were not significantly correlated with stigma or *** Having more health conditions,or thyroid disease,depression,or anxiety,was associated with more perceived stigma and poorer QoL,with younger age,less education,and earlier disease onset affecting the *** is important to consider the burden of health conditions and how they affect persons with PD with specific clinical characteristics.

关键词： younger life education

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A Robust Approach for Multi Classification-Based Intrusion Detection through stacking Deep Learning Models

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Computers, Materials & Continua 2024年第6期79卷 4845-4861页

作者： samia Allaoua Chelloug Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

Intrusion detection is a predominant task that monitors and protects the network ***,many datasets have been published and investigated by researchers to analyze and understand the problem of intrusion prediction and *** particular,the Network security Laboratory-Knowledge Discovery in Databases(NsL-KDD)is an extensively used benchmark dataset for evaluating intrusion detection systems(IDss)as it incorporates various network traffic *** is worth mentioning that a large number of studies have tackled the problem of intrusion detection using machine learning models,but the performance of these models often decreases when evaluated on new *** has led to the utilization of deep learning techniques,which have showcased significant potential for processing large datasets and therefore improving detection *** that reason,this paper focuses on the role of stacking deep learning models,including convolution neural network(CNN)and deep neural network(DNN)for improving the intrusion detection rate of the NsL-KDD *** base model is trained on the NsL-KDD dataset to extract significant *** the base models have been trained,the stacking process proceeds to the second stage,where a simple meta-model has been trained on the predictions generated from the proposed base *** combination of the predictions allows the meta-model to distinguish different classes of attacks and increase the detection *** experimental evaluations using the NsL-KDD dataset have shown the efficacy of stacking deep learning models for intrusion *** performance of the ensemble of base models,combined with the meta-model,exceeds the performance of individual *** stacking model has attained an accuracy of 99%and an average F1-score of 93%for the multi-classification ***,the training time of the proposed ensemble model is lower than the training time of benchmark techniques,demonstrating its efficien

关键词： Intrusion detection multi classification deep learning stacking NsL-KDD

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Polio in Gaza:Another disastrous outcome of the Gaza conflict,2023-2024

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Asian Pacific Journal of Tropical Medicine 2024年第9期17卷 381-383页

作者： Zuhair Dardona Mounia Amane samia Boussaa Microbial Biotechnologies Agro sciences and Environment Laboratory(BioMAgE)Faculty of Sciences SemlaliaCadi Ayyad UniversityMarrakeshMoroccoGovernmental Medical ServicesGazaPalestine IsPITs-Higher Institute of Nursing and Health Techniques Ministry of HealthMarrakechMorocco IsPITs-Higher Institute of Nursing and Health Techniques Ministry of HealthRabatMorocco

On October 7th,2023,a devastating conflict erupted between Gaza and Israel,causing around 40000 deaths and over 90000 *** war has displaced more than 1.9 million people,who now live in overcrowded tent camps facing severe shortages of clean water,sanitation,fuel,electricity,and *** rely on international aid and resort to unsafe methods for basic needs[1].The Gaza strip,a tiny coastal area of just 365 square kilometers with 2.3 million residents,is one of the world's most densely populated *** burdened by inadequate infrastructure,the ongoing war has worsened conditions,caused the collapse of sewage and water systems and severely disrupted daily *** devastation has created a breeding ground for infectious diseases,especially among the displaced people living in overcrowded camps[2,3].

关键词： injuries Israel resort

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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

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Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： Asifa Mehmood Qureshi Naif Al Mudawi Mohammed Alonazi samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,scale Invariant Feature Transform(sIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection sIFT VAID

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New-fashioned solitons of coupled nonlinear Maccari systems describing the motion of solitary waves in fluid flow

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Journal of Ocean Engineering and science 2024年第4期9卷 353-363页

作者： Tarikul islam Ali Akbar Hadi Rezazadeh Ahmet Bekir Department of Mathematics Hajee Mohammad Danesh Science and Technology UniversityDinajpurBangladesh Department of Applied Mathematics University of RajshahiBangladesh Faculty of Modern Technologies Engineering Amol University of Special Modern TechnologiesAmolIran Neighbourhood of Akcaglan Imarli StreetNo.28/4Eskisehir 26030Turkey

The schrodinger equation type nonlinear coupled Maccari system is a significant equation that flourished with the wide-ranging arena concerning fluid flow and the theory of deep-water waves,physics of plasma,nonlinear optics,*** exploit the enhanced tanh approach and the rational(G/G)-expansion process to retrieve the soliton and dissimilar soliton solutions to the Maccari system in this *** suggested systems of nonlinear equations turn into a differential equation of single variable through executing some operations of wave variable ***,with the successful implementation of the advised techniques,a lot of exact soliton solutions are *** obtained solutions are depicted in 2D,3D,and contour traces by assigning appropriate values of the allied unknown *** diverse graphical appearances assist the researchers to understand the underlying processes of intricate phenomena of the leading *** individual performances of the employed methods are praise-worthy which justify further application to unravel many other nonlinear evolution equations ascending in various branches of science and engineering.

关键词： Rational(G'/G)-expansion method Coupled nonlinear schrodinger equations soliton Improved tanh method Exact solutions

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self-supported copper-based gas diffusion electrodes improve the local CO_(2)concentration for efficient electrochemical CO_(2)reduction

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Frontiers of Chemical science and Engineering 2024年第3期18卷 51-62页

作者： Azeem Mustafa Bachirou Guene Lougou Yong shuai Zhijiang Wang Haseeb-ur-Rehman samia Razzaq Wei Wang Ruming Pan Jiupeng Zhao Key Laboratory of Aerospace Thermophysics of MIIT Harbin Institute of TechnologyHarbin150001China school of Energy science and Engineering Harbin Institute of TechnologyHarbin150001China MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and storage School of Chemistry and Chemical EngineeringHarbin Institute of TechnologyHarbin150001China Mechanical Engineering Department University of Engineering and TechnologyTaxila47050Pakistan school of Aerospace Mechanical and Mechatronics EngineeringUniversity of SydneySydney2006Australia

Electrochemical CO_(2)reduction is a sustainable approach in green chemistry that enables the production of valuable chemicals and fuels while mitigating the environmental impact associated with CO_(2)*** its several advantages,this technology suffers from an intrinsically low CO_(2)solubility in aqueous solutions,resulting in a lower local CO_(2)concentration near the electrode,which yields lower current densities and restricts product *** diffusion electrodes(GDEs),particularly those with tubular architectures,can solve these issues by increasing the local CO_(2)concentration and triple-phase interface,providing abundant electroactive sites to achieve superior reaction *** this study,robust and self-supported Cu flow-through gas diffusion electrodes(FTGDEs)were synthesized for efficient formate production via electrochemical CO_(2)*** were further compared with traditional Cu electrodes,and it was found that higher local CO_(2)concentration due to improved mass transfer,the abundant surface area available for the generation of the triple-phase interface,and the porous structure of Cu FTGDEs enabled high formate Faradaic efficiency(76%)and current density(265 mA¸cm^(−2))at–0.9 V *** hydrogen electrode(RHE)in 0.5 mol·L^(−1)*** combined phase inversion and calcination process of the Cu FTGDEs helped maintain a stable operation for several *** catalytic performance of the Cu FTGDEs was further investigated in a non-gas diffusion configuration to demonstrate the impact of local gas concentration on the activity and performance of electrochemical CO_(2)*** study demonstrates the potential of flow-through gas-diffusion electrodes to enhance reaction kinetics for the highly efficient and selective reduction of CO_(2),offering promising applications in sustainable electrochemical processes.

关键词： CO_(2)electroreduction flow-through delivery hollow fiber structure local concentration formate

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Attention,neighbors:Methyl salicylate mediates plant airborne defense

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Plant Communications 2024年第1期5卷 1-3页

作者： shan Liu Faisal islam Jianping Chen Zongtao sun Jian Chen International Genome Center Jiangsu UniversityZhenjiang 212013China state Key Laboratory for Managing Biotic and Chemical Threats to the Quality and safety of Agro-products Key Laboratory of Biotechnology in Plant Protection of Ministry of Agriculture and Zhejiang ProvinceInstitute of Plant VirologyNingbo UniversityNingboChina

Plants have evolved to generate and release a wide array of volatile organic compounds(VOCs)when challenged by environmental stimuli such as biotic and abiotic stresses,which facilitate their reproduction,defense responses,and plant-plant communication(Karban,2021).Once emitted,some VOCs can elicit defense signaling in neighboring plants by interacting with specific receptor(s),a phenomenon referred to as airborne defense(AD)(Loreto and D’Auria,2022).

关键词： neighboring neighbor media

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Vision Intelligence for smart sheep Farming: Applying Ensemble Learning to Detect sheep Breeds

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Artificial Intelligence in Agriculture 2024年第1期11卷 1-12页

作者： Galib Muhammad shahriar Himel Md Masudul islam Mijanur Rahaman Bangladesh University of Business and Technology DhakaBangladesh

The ability to automatically recognize sheep breeds holds significant value for the sheep *** farmers often require breed identification to assess the commercial worth of their ***,many farmers specifically the novice one encounter difficulties in accurately identifying sheep breeds without experts in the ***,there is a need for autonomous approaches that can effectively and precisely replicate the breed identification skills of a sheep breed expert while functioning within a farm environment,thus providing considerable benefits the industry-specific to the novice farmers in the *** achieve this objective,we suggest utilizing a model based on convolutional neural networks(CNNs)which can rapidly and efficiently identify the type of sheep based on their facial *** approach offers a cost-effective *** conduct our experiment,we utilized a dataset consisting of 1680 facial images which represented four distinct sheep *** paper proposes an ensemble method that combines Xception,VGG16,InceptionV3,InceptionResNetV2,and DenseNet121 *** the transfer learning using this pre-trained model,we applied several optimizers and loss functions and chose the best combinations out of *** classification model has the potential to aid sheep farmers in precisely and efficiently distinguishing between various breeds,enabling more precise assessments of sector-specific classification for different businesses。

关键词： Computer vision sheep breed classification Image processing Transfer learning Ensemble learning Meta learner

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Reservoir quality of the Late Cretaceous Volador Formation of the Latrobe group,Gippsland Basin,Australia:Implications from integrated analytical techniques

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Energy Geoscience 2024年第1期5卷 121-140页

作者： Kamalia Norjannah Kamalrulzaman Mohamed Ragab shalaby Md Aminul islam Department of Geosciences Faculty of ScienceUniversiti Brunei DarussalamBrunei Darussalam Geology Department Faculty of ScienceTanta UniversityTanta31527Egypt

Increasing demand for energy due to the populous Eastern Australia has driven oil and gas industries to find new sources of hydrocarbons as they are the primary energy *** study has been done on the Volador Formation in the Gippsland Basin by means of core-based petrophysical,sedimentological,and petrographic analyses as well as well log-based interpretation and capillary pressure *** wells from Kipper,Basker and Tuna fields with available dataset were investigated in this study:Kipper-1,Basker-1,Basker-2,Basker-5 and ***,the formation has good reservoir quality based on the high porosity and permeability values obtained through core and well log petrophysical *** formation made up of mostly moderate to coarse quartz grains that has experienced strong anti-compaction and is poorly *** and illite clays are seen dispersed in the rock formation,with the minority being mixed *** clays and diagenetic features including kaolinite cement and quartz overgrowth that can lead to porosity reduction only have insignificant impact on the overall reservoir *** addition,capillary pressure data shows that most samples are found in the transition to good reservoir zones(saturation).The results obtained from this study have shown that the Volador Formation in the Gippsland Basin is worth for hydrocarbon exploration.

关键词： Volador formation Reservoir rock characterization Core-based Petrographic Well log based Capillary pressure

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Robust Machine Learning Technique to Classify COVID-19 Using Fusion of Texture and Vesselness of X-Ray Images

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Computer Modeling in Engineering & sciences 2024年第2期138卷 1981-2004页

作者： shaik Mahaboob Basha Victor Hugo Cde Albuquerque samia Allaoua Chelloug Mohamed Abd Elaziz shaik Hashmitha Mohisin suhail Parvaze Pathan Department of Electronics and Communication Engineering N.B.K.R.Institute of Science&TechnologyVidyanagarAndhra Pradesh524413India Department of Teleinformatics Engineering Federal University of CearáFortaleza60455-970Brazil Information Technology Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Mathematics Faculty of ScienceZagazig UniversityZagazig44519Egypt Faculty of Computer science and Engineering Galala UniversitySuez435611Egypt Artificial Intelligence Research Center(AIRC) College of Engineering and Information TechnologyAjman UniversityAjmanUnited Arab Emirates Department of Electrical and Computer Engineering Lebanese American UniversityByblos13-5053Lebanon Department of Avionics Indian Institute of Space Science and TechnologyThiruvananthapuramKerala695547India Department of Veterinary Clinical sciences University of MinnesotaSt.PaulMinnesota55108USA

Manual investigation of chest radiography(CXR)images by physicians is crucial for effective decision-making in COVID-19 ***,the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning *** study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies,including normal *** information is extracted using gray co-occurrence matrix(GLCM)-based features,while vessel-like features are obtained using Frangi,sato,and Meijering *** learning models employing Decision Tree(DT)and RandomForest(RF)approaches are designed to categorize CXR images into common lung infections,lung opacity(LO),COVID-19,and viral pneumonia(VP).The results demonstrate that the fusion of texture and vesselbased features provides an effective ML model for aiding *** ML model validation using performance measures,including an accuracy of approximately 91.8%with an RF-based classifier,supports the usefulness of the feature set and classifier model in categorizing the four different ***,the study investigates the importance of the devised features in identifying the underlying pathology and incorporates histogrambased *** analysis reveals varying natural pixel distributions in CXR images belonging to the normal,COVID-19,LO,and VP groups,motivating the incorporation of additional features such as mean,standard deviation,skewness,and percentile based on the filtered ***,the study achieves a considerable improvement in categorizing COVID-19 from LO,with a true positive rate of 97%,further substantiating the effectiveness of the methodology implemented.

关键词： Chest radiography(CXR)image COVID-19 classifier machine learning random forest texture analysis

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