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A convolutional neural network to detect possible hidden data in spatial domain images

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Cybersecurity 2024年第1期7卷 37-52页

作者： Jean de la Croix Ntivuguruzwa Tohari Ahmad department of Informatics Institut Teknologi Sepuluh Nopember(ITS)Kampus ITS Keputih SukoliloSurabaya60111Indonesia African Center of Excellence in the Internet of Things College of Science and TechnologyUniversity of Rwanda3900KigaliRwanda

Hiding secret data in digital multimedia has been essential to protect the data.Nevertheless,attackers with a steganalysis technique may break them.Existing steganalysis methods have good results with conventional Machine Learning(ML)techniques;however,the introduction of Convolutional Neural Network(CNN),a deep learning paradigm,achieved better performance over the previously proposed ML-based techniques.Though the existing CNN-based approaches yield good results,they present performance issues in classification accuracy and stability in the network training phase.This research proposes a new method with a CNN architecture to improve the hidden data detection accuracy and the training phase stability in spatial domain images.The proposed method comprises three phases:pre-processing,feature extraction,and classification.firstly,in the pre-processing phase,we use spatial rich model filters to enhance the noise within images altered by data hiding;secondly,in the feature extraction phase,we use two-dimensional depthwise separable convolutions to improve the signal-to-noise and regular convolutions to model local features;and finally,in the classification,we use multi-scale average pooling for local features aggregation and representability enhancement regardless of the input size variation,followed by three fully connected layers to form the final feature maps that we transform into class probabilities using the softmax function.The results identify an improvement in the accuracy of the considered recent scheme ranging between 4.6 and 10.2%with reduced training time up to 30.81%.

关键词： Information security Spatial domain steganalysis deep learning Convolutional neural network Infrastructure

Survival effects of antibiotic exposure during the larval and adult stages in the West Nile virus vector Culex pipiens

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Insect Science 2024年第2期31卷 542-550页

作者： Marta Garrigos Mario Garrido Manuel Morales-Yuste JosuéMartinez-de la Puente Jesus Veiga faculty of Pharmacy Department of ParasitologyUniversity of GranadaGranadaSpain CIBER de Epidemiologia y Salud Publica(CIBERESP) MadridSpain

The ability of mosquitoes to transmit a pathogen is affected,among other factors,by their survival rate,which is partly modulated by their microbiota.Mosquito microbiota is acquired during the larval phase and modified during their development and adult feeding behavior,being highly dependent on environmental factors.Pharmaceutical residues including antibiotics are widespread pollutants potentially being present in mosquito breeding waters likely affecting their microbiota.Here,we used Culex pipiens mosquitoes to assess the impact of antibiotic exposure during the larval and adult stages on the survival rate of adult mosquitoes.Wild-collected larvae were randomly assigned to two treatments:larvae maintained in water supplemented with antibiotics and control larvae.Emerged adults were subsequently assigned to each of two treatments,fed with sugar solution with antibiotics and fed only with sugar solution(controls).larval exposure to antibiotics significantly increased the survival rate of adult females that received a control diet.In addition,the effect of adult exposure to antibiotics on the survival rate of both male and female mosquitoes depended on the number of days that larvae fed ad libitum in the laboratory before emergence.In particular,shorter larval ad libitum feeding periods reduced the survival rate of antibiotic-treated adult mosquitoes compared with those that emerged after a longer larval feeding period.These differences were not found in control adult mosquitoes.Our results extend the current understanding of the impact of antibiotic exposure of mosquitoes on a key component of vectorial capacity,that is the vector survival rate.

关键词： antibiotics avian malaria microbiota mosquitoes vector competence vector survival

Review of Networked Microgrid Protection:Architectures,Challenges,Solutions,and future Trends

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 448-467页

作者： Jorge de la Cruz Ying Wu John E.Candelo-Becerra Juan C.Vasquez Josep M.Guerrero Center for Research on Microgrids(CROM) Department of Energy TechnologyAalborg University9220 AalborgDenmark facultad de Minas Departamento de Energia Eléctrica y AutomaticaUniversidad Nacional de ColombiaSede MedellinCarrera 80 No.65-223RobledoMedellin 050041Colombia. Center for Research on Microgrids at UPC(UPC CROM) Department of Electronic EngineeringTechnical University of Catalonia(UPC)08019 Barcelona Spain ICREA Pg.Lluis Companys 2308010 BarcelonaSpain Center for Research on Microgrids at AAU(AAU CROM) AAU EnergyAalborg University(AAU)9220 Aalborg EastDenmark

design and selection of advanced protection schemes have become essential for reliable and secure operation of networked microgrids.Various protection schemes that allow correct operation of microgrids have been proposed for individual systems in different topologies and connections.Nevertheless,protection schemes for networked microgrids are still in devel-opment,and further research is required to design and operate advanced protection in interconnected systems.Interconnection of these microgrids in different nodes with various intercon-nection technologies increases fault occurrence and complicates protection operation.This paper aims to point out challenges in developing protection for networked microgrids,potential solutions,and research areas that need to be addressed for their development.first,this article presents a systematic analysis of different microgrid clusters proposed since 2016,including several architectures of networked microgrids,operation modes,components,and utilization of renewable sources,which have not been widely explored in previous review papers.Second,the paper presents a discussion on protection systems currently available for microgrid clusters,current challenges,and solutions that have been proposed for these systems.finally,it discusses the trend of protection schemes in networked microgrids and presents some conclusions related to implementation.IndexTerms—Adaptive eprotection,microgrid cluster,microgrid,multiple microgrid,networked microgrid,real-time simulation,smart grid.

关键词： Adaptive eprotection microgrid cluster microgrid multiple microgrid networked microgrid real-time simulation smart grid

Histopathological impact of SARS-CoV-2 on the liver:Cellular damage and long-term complications

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World Journal of Gastroenterology 2024年第22期30卷 2866-2880页

作者： Alfonso Rodriguez-Espada Moises Salgado-de la Mora Briana Mariette Rodriguez-Paniagua Nathaly Limonde la Rosa Monica Itzel Martinez-Gutierrez Santiago Pastrana-Brandes Nalu Navarro-Alvarez department of Molecular Biology Universidad Panamericana School of MedicineCampus MéxicoMexico 03920Mexico department of Internal Medicine Instituto Nacional de Ciencias Médicas y Nutrición Salvador ZubiránMexico 14080Mexico department of Surgery University of Colorado Anschutz Medical CampusDenverCO 80045United States PECEM Facultad de MedicinaUniversidad Nacional Autónoma de MéxicoMexico 04360Mexico department of Gastroenterology Instituto Nacional de Ciencias Médicas y Nutrición Salvador ZubiránMexico 14080Mexico

Coronavirus disease 2019(COVID-19),caused by the highly pathogenic severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),primarily impacts the respiratory tract and can lead to severe outcomes such as acute respiratory distress syndrome,multiple organ failure,and death.despite extensive studies on the pathogenicity of SARS-CoV-2,its impact on the hepatobiliary system remains unclear.While liver injury is commonly indicated by reduced albumin and elevated bilirubin and transaminase levels,the exact source of this damage is not fully understood.Proposed mechanisms for injury include direct cytotoxicity,collateral damage from inflammation,drug-induced liver injury,and ischemia/hypoxia.However,evidence often relies on blood tests with liver enzyme abnormalities.In this comprehensive review,we focused solely on the different histopathological manifestations of liver injury in COVID-19 patients,drawing from liver biopsies,complete autopsies,and in vitro liver analyses.We present evidence of the direct impact of SARS-CoV-2 on the liver,substantiated by in vitro observations of viral entry mechanisms and the actual presence of viral particles in liver samples resulting in a variety of cellular changes,including mitochondrial swelling,endoplasmic reticulum dilatation,and hepatocyte apoptosis.Additional ly,we describe the diverse liver pathology observed during COVID-19 infection,encompassing necrosis,steatosis,cholestasis,and lobular inflammation.We also discuss the emergence of long-term complications,notably COVID-19-related secondary sclerosing cholangitis.Recognizing the histopathological liver changes occurring during COVID-19 infection is pivotal for improving patient recovery and guiding decision-making.

关键词： Liver SARS-CoV-2 COVID-19 Angiotensin-converting enzyme 2 Histopathology Liver biopsies Liver autopsy In vitro

Kentish Plover(Charadrius alexandrinus) and Little Tern(Sternula albifrons) prefer shells for nesting:A field experiment

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Avian Research 2024年第1期15卷 55-59页

作者： Macarena Castro Andrés de la Cruz Nuria Martin-Sanjuan Alejandro Pérez-Hurtado Instituto Universitario de Investigacion Marina(INMAR) Campus de Excelencia Internacional del Mar(CEIMAR)Departamento de BiologíaUniversidad de CadizPuerto RealSpain Servicios centrales de Investigacion Salinas de la Esperanza Universidad de CadizPuerto RealSpain

Shorebird populations are declining worldwide,mainly due to human disturbances and loss of coastal wetlands.However,supratidal habitats as saltpans could play a role in buffering human impact.Saltpans have shown to be important as feeding or breeding sites of some shorebird species.A potential conservation strategy to increase shorebird populations in saltpans is to manipulate the cues that birds use to select optimal breeding habitat.Here it is hypothesized that shorebirds are attracted to bivalve shells due to the advantages they offer.following this hypothesis,we supplemented a restored saltpan in 2019 and 2021 with bivalve shells,expecting an increase in the number of breeding birds’ nests.More than 75% of Kentish Plover(Charadrius alexandrinus) and Little Tern(Sternula albifrons) nests were found in patches with shells in both years.The best model for both species indicates that the presence of shells is the factor that most correlates with the location of nests.The probability of choosing one place over another to settle their nest increases in areas with an abundance of shells,double in the case of the Kentish Plover and triple in the case of the Little Tern.The result of this study may constitute a valuable tool for attracting birds to restored saltpans and could contribute to the success of expensive restoration projects where time is usually a constraint.

关键词： Habitat management Nest site selection Saltpan restoration Shell supplementation Shorebirds

depression Intensity Classification from Tweets Using fast Text Based Weighted Soft Voting Ensemble

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Computers, Materials & Continua 2024年第2期78卷 2047-2066页

作者： Muhammad Rizwan Muhammad faheem Mushtaq Maryam Rafiq Arif Mehmood Isabel de la Torre Diez Monica Gracia Villar Helena Garay Imran Ashraf department of Artificial Intelligence The Islamia University of BahawalpurBahawalnagar63100Pakistan department of Information Technology Khwaja Fareed University of Engineering and ITRYKhan64200Pakistan department of Computer Science&Information Technology The Islamia University of BahawalpurBahawalnagar63100Pakistan department of Signal Theory and Communications and Telematic Engineering Unviersity of ValladolidPaseo de Belén 15Valladolid47011Spain faculty of Social Science and Humanities Universidad Europea del Atlántico Isabel Torres 21Santander39011Spain department of Project Management Universidad Internacional IberoamericanaCampeche24560México fundación Universitaria Internacional de Colombia Bogotá111611Colombia Universidad Internacional Iberoamericana AreciboPuerto Rico00613USA Universidade Internacional do Cuanza Cuito46703Angola department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541South Korea

Predicting depression intensity from microblogs and social media posts has numerous benefits and applications,including predicting early psychological disorders and stress in individuals or the general public.A major challenge in predicting depression using social media posts is that the existing studies do not focus on predicting the intensity of depression in social media texts but rather only perform the binary classification of depression and moreover noisy data makes it difficult to predict the true depression in the social media text.This study intends to begin by collecting relevant Tweets and generating a corpus of 210000 public tweets using Twitter public application programming interfaces(APIs).A strategy is devised to filter out only depression-related tweets by creating a list of relevant hashtags to reduce noise in the corpus.furthermore,an algorithm is developed to annotate the data into three depression classes:‘Mild,’‘Moderate,’and‘Severe,’based on International Classification of Diseases-10(ICD-10)depression diagnostic criteria.Different baseline classifiers are applied to the annotated dataset to get a preliminary idea of classification performance on the corpus.further fastText-based model is applied and fine-tuned with different preprocessing techniques and hyperparameter tuning to produce the tuned model,which significantly increases the depression classification performance to an 84%f1 score and 90%accuracy compared to baselines.finally,a fastText-based weighted soft voting ensemble(WSVE)is proposed to boost the model’s performance by combining several other classifiers and assigning weights to individual models according to their individual performances.The proposed WSVE outperformed all baselines as well as fastText alone,with an f1 of 89%,5%higher than fastText alone,and an accuracy of 93%,3%higher than fastText alone.The proposed model better captures the contextual features of the relatively small sample class and aids in the detection of early depression intensity prediction from tweet

关键词： depression classification deep learning fastText machine learning

Rice University Rule to determine the Number of Bins

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Open Journal of Statistics 2024年第1期14卷 119-149页

作者： José Moral de la Rubia School of Psychology Universidad Autónoma de Nuevo León Monterrey Mexico

This study aims to establish a rationale for the Rice University rule in determining the number of bins in a histogram. It is grounded in the Scott and freedman-Diaconis rules. Additionally, the accuracy of the empirical histogram in reproducing the shape of the distribution is assessed with respect to three factors: the rule for determining the number of bins (square root, Sturges, Doane, Scott, freedman-Diaconis, and Rice University), sample size, and distribution type. Three measures are utilized: the average distance between empirical and theoretical histograms, the level of recognition by an expert judge, and the accuracy index, which is composed of the two aforementioned measures. Mean comparisons are conducted with aligned rank transformation analysis of variance for three fixed-effects factors: sample size (20, 35, 50, 100, 200, 500, and 1000), distribution type (10 types), and empirical rule to determine the number of bins (6 rules). from the accuracy index, Rice’s rule improves with increasing sample size and is independent of distribution type. It outperforms the friedman-Diaconis rule but falls short of Scott’s rule, except with the arcsine distribution. Its profile of means resembles the square root rule concerning distributions and Doane’s rule concerning sample sizes. These profiles differ from those of the Scott and friedman-Diaconis rules, which resemble each other. Among the seven rules, Scott’s rule stands out in terms of accuracy, except for the arcsine distribution, and the square root rule is the least accurate.

关键词： Histogram Class Intervals Accuracy Distributions descriptive Statistics

Measures of Variability for Qualitative Variables Using the R Software

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Open Journal of Statistics 2024年第3期14卷 259-293页

作者： José Moral de la Rubia School of Psychology Universidad Autnoma de Nuevo Len Monterrey Mexico

Although there are many measures of variability for qualitative variables, they are little used in social research, nor are they included in statistical software. The aim of this article is to present six measures of variation for qualitative variables of simple calculation, as well as to facilitate their use by means of the R software. The measures considered are, on the one hand, freemans variation ratio, Morals universal variation ratio, Kvalseths standard deviation from the mode, and Wilcoxs variation ratio which are most affected by proximity to a constant random variable, where the measures of variability for qualitative variables reach their minimum value of 0. On the other hand, the Gibbs-Poston index of qualitative variation and Shannons relative entropy are included, which are more affected by the proximity to a uniform distribution, where the measures of variability for qualitative variables reach their maximum value of 1. Point and interval estimation are addressed. Bootstrap by the percentile and bias-corrected and accelerated percentile methods are used to obtain confidence intervals. Two calculation situations are presented: with a sample mode and with two or more modes. The standard deviation from the mode among the six considered measures, and the universal variation ratio among the three variation ratios, are particularly recommended for use.

关键词： Variation Ratio Relative Entropy Index of Qualitative Variation Standard deviation from Mode Bootstrap Confidence Interval

Calculation of Two-Tailed Exact Probability in the Wald-Wolfowitz One-Sample Runs Test

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Journal of Data Analysis and Information Processing 2024年第1期12卷 89-114页

作者： José Moral de la Rubia School of Psychology Universidad Autónoma de Nuevo León Monterrey Nuevo León México

The objectives of this paper are to demonstrate the algorithms employed by three statistical software programs (R, Real Statistics using Excel, and SPSS) for calculating the exact two-tailed probability of the Wald-Wolfowitz one-sample runs test for randomness, to present a novel approach for computing this probability, and to compare the four procedures by generating samples of 10 and 11 data points, varying the parameters n0 (number of zeros) and n1 (number of ones), as well as the number of runs. fifty-nine samples are created to replicate the behavior of the distribution of the number of runs with 10 and 11 data points. The exact two-tailed probabilities for the four procedures were compared using friedman’s test. Given the significant difference in central tendency, post-hoc comparisons were conducted using Conover’s test with Benjamini-Yekutielli correction. It is concluded that the procedures of Real Statistics using Excel and R exhibit some inadequacies in the calculation of the exact two-tailed probability, whereas the new proposal and the SPSS procedure are deemed more suitable. The proposed robust algorithm has a more transparent rationale than the SPSS one, albeit being somewhat more conservative. We recommend its implementation for this test and its application to others, such as the binomial and sign test.

关键词： Randomness Nonparametric Test Exact Probability Small Samples Quantiles