The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
Major solar plasma disturbances are subjected to Lomb-Scargle periodogram and wavelet analysis to determine the occurrence frequency.These disruptions include interplanetary coronal mass ejection,sudden storm commence...Major solar plasma disturbances are subjected to Lomb-Scargle periodogram and wavelet analysis to determine the occurrence frequency.These disruptions include interplanetary coronal mass ejection,sudden storm commencement,high-speed streams,corotating interaction regions,interplanetary shocks and Forbush decreases.We included information on all of the aforementioned solar disturbances for the last six solar cycles,from 1965 to 2023,for this study.Our findings reveal some intriguing and noteworthy results that clearly distinguish between even and odd-numbered solar cycles.The study suggests that the Sun behaves differently in odd and even-numbered solar cycles as it comes from the massive solar eruptions.During even-numbered solar cycles,variations with a period of∼44 days are prominently observed in addition to solar rotation(∼27 days)and extended solar(∼36 days)rotation.However,in addition to solar rotation,prolonged solar rotation,and periods of around 44 days,we also detect a number of intermittent changes with nearly comparable amplitude during the oddnumbered solar cycles.The findings also demonstrate that,in contrast to odd-numbered solar cycles,the emissions rate of these disruptions is more distinct and predictable during even-numbered solar cycles.展开更多
In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial...In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.展开更多
BACKGROUND A recently developed method enables automated measurement of the hallux valgus angle(HVA)and the first intermetatarsal angle(IMA)from weightbearing foot radiographs.This approach employs bone segmentation t...BACKGROUND A recently developed method enables automated measurement of the hallux valgus angle(HVA)and the first intermetatarsal angle(IMA)from weightbearing foot radiographs.This approach employs bone segmentation to identify anatomical landmarks and provides standardized angle measurements based on established guidelines.While effective for HVA and IMA,preoperative radiograph analysis remains complex and requires additional measurements,such as the hallux interphalangeal angle(IPA),which has received limited research attention.AIM To expand the previous method,which measured HVA and IMA,by incorporating the automatic measurement of IPA,evaluating its accuracy and clinical relevance.METHODS A preexisting database of manually labeled foot radiographs was used to train a U-Net neural network for segmenting bones and identifying landmarks necessary for IPA measurement.Of the 265 radiographs in the dataset,161 were selected for training and 20 for validation.The U-Net neural network achieves a high mean Sørensen-Dice index(>0.97).The remaining 84 radiographs were used to assess the reliability of automated IPA measurements against those taken manually by two orthopedic surgeons(OA and OB)using computer-based tools.Each measurement was repeated to assess intraobserver(OA1 and OA2)and interobserver(O_(A2) and O_(B))reliability.Agreement between automated and manual methods was evaluated using the Intraclass Correlation Coefficient(ICC),and Bland-Altman analysis identified systematic differences.Standard error of measurement(SEM)and Pearson correlation coefficients quantified precision and linearity,and measurement times were recorded to evaluate efficiency.RESULTS The artificial intelligence(AI)-based system demonstrated excellent reliability,with ICC3.1 values of 0.92(AI vs OA2)and 0.88(AI vs O_(B)),both statistically significant(P<0.001).For manual measurements,ICC values were 0.95(OA2 vs OA1)and 0.95(OA2 vs OB),supporting both intraobserver and interobserver reliability.Bland-Altman analysis revealed minimal biases of:(1)1.61°(AI vs O_(A2));and(2)2.54°(AI vs O_(B)),with clinically acceptable limits of agreement.The AI system also showed high precision,as evidenced by low SEM values:(1)1.22°(O_(A2) vs O_(B));(2)1.77°(AI vs O_(A2));and(3)2.09°(AI vs O_(B)).Furthermore,Pearson correlation coefficients confirmed strong linear relationships between automated and manual measurements,with r=0.85(AI vs O_(A2))and r=0.90(AI vs O_(B)).The AI method significantly improved efficiency,completing all 84 measurements 8 times faster than manual methods,reducing the time required from an average 36 minutes to just 4.5 minutes.CONCLUSION The proposed AI-assisted IPA measurement method shows strong clinical potential,effectively corresponding with manual measurements.Integrating IPA with HVA and IMA assessments provides a comprehensive tool for automated forefoot deformity analysis,supporting hallux valgus severity classification and preoperative planning,while offering substantial time savings in high-volume clinical settings.展开更多
The Suizhou meteorite is a heavily shock-met-amorphosed L6 chondrite which contains thin shock melt veins.So far,26 high-pressure phases have been identified from the meteorite.Among the high-pressure phases,ten of th...The Suizhou meteorite is a heavily shock-met-amorphosed L6 chondrite which contains thin shock melt veins.So far,26 high-pressure phases have been identified from the meteorite.Among the high-pressure phases,ten of them were approved as new minerals which include tuite,xieite,wangdaodeite,chenmingite,hemleyite,poirierite,asimowite,hiroseite,elgoresyite,and ohtaniite,by the Commission on New Minerals,Nomenclature and Classification of the International Mineralogical Association.Other high-pressure phases identified from the meteorite are ahrensite,akimotoite,bridgmanite,lingunite,magnesiowüstite,majorite,majorite-pyrope_(ss),maskelynite,riesite,ringwoodite,wadsleyite,and 5 other phases including phase A,vitrified phase B and phase C,phase D(Ca-rich majorite),and partly inverted ringwoodite.The occurrence and abundance of high-pressure phases makes this meteorite the one with the richest variety of high-pressure minerals to date.展开更多
Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numeri...Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numerical approach.However,the material assumptions for past computational human femur simulations were mainly homogeneous.Thus,this study aimed to design and analyze scaffolds for reconstructing the distal femur defect using a patient-specific finite element modeling technique.A three-dimensional finite element model of the human femur with accurate geometry and material distribution was developed using the finite element method and material mapping technique.An intact femur and a distal femur defect model treated with nine microstructure scaffolds and two solid scaffolds were investigated and compared under a single-leg stance loading.The results showed that the metal solid scaffold design could provide the most stable fixation for reconstructing the distal femur defect.However,the fixation stability was affected by various microstructure designs and pillar diameters.A microstructure scaffold can be designed to satisfy all the biomechanical indexes,opening up future possibilities for more stable reconstructions.A three-dimensional finite element model of the femur with real bone geometry and bone material distribution can be developed,and this patient-specific femur model can be used for studying other femoral fractures or injuries,paving the way for more comprehensive research in the field.Besides,this patient-specific finite element modeling technique can also be applied to developing other human or animal bone models,expanding the scope of biomechanical research.展开更多
Complex oxides are an important class of materials with enormous potential for electrochemical appli-cations.Depending on their composition and structure,such complex oxides can exhibit either a single conductivity(ox...Complex oxides are an important class of materials with enormous potential for electrochemical appli-cations.Depending on their composition and structure,such complex oxides can exhibit either a single conductivity(oxygen-ionic or protonic,or n-type,or p-type electronic)or a combination thereof gener-ating distinct dual-conducting or even triple-conducting materials.These properties enable their use as diverse functional materials for solid oxide fuel cells,solid oxide electrolysis cells,permeable membranes,and gas sensors.The literature review shows that the field of solid oxide materials and related electro-chemical cells has a significant level of research engagement,with over 8,000 publications published since 2020.The manual analysis of such a large volume of material is challenging.However,by examining the review articles,it is possible to identify key patterns,recent achievements,prospects,and remaining obstacles.To perform such an analysis,the present article provides,for the first time,a comprehensive summary of previous review publications that have been published since 2020,with a special focus on solid oxide materials and electrochemical systems.Thus,this study provides an important reference for researchers specializing in the fields of solid state ionics,high-temperature electrochemistry,and energyconversiontechnologies.展开更多
In order to take into account the uncertainties linked to the variables in the evaluation of the statistical properties of structural response, a reliability approach with probabilistic aspect was considered. This is ...In order to take into account the uncertainties linked to the variables in the evaluation of the statistical properties of structural response, a reliability approach with probabilistic aspect was considered. This is called the Probabilistic Transformation Method (PTM). This method is readily applicable when the function between the input and the output of the system is explicit. However, the situation is much more involved when it is necessary to perform the evaluation of implicit function between the input and the output of the system through numerical models. In this work, we propose a technique that combines Finite Element Analysis (FEA) and Probabilistic Transformation Method (PTM) to evaluate the Probability Density Function (PDF) of response where the function between the input and the output of the system is implicit. This technique is based on the numerical simulations of the Finite Element Analysis (FEA) and the Probabilistic Transformation Method (PTM) using an interface between Finite Element software and Matlab. Some problems of structures are treated in order to prove the applicability of the proposed technique. Moreover, the obtained results are compared to those obtained by the reference method of Monte Carlo. A second aim of this work is to develop an algorithm of global optimization using the local method SQP, because of its effectiveness and its rapidity of convergence. For this reason, we have combined the method SQP with the Multi start method. This developed algorithm is tested on test functions comparing with other methods such as the method of Particle Swarm Optimization (PSO). In order to test the applicability of the proposed approach, a structure is optimized under reliability constraints.展开更多
The formation of spatial patterns is an important issue in reaction–diffusion systems.Previous studies have mainly focused on the spatial patterns in reaction–diffusion models equipped with symmetric diffusion(such ...The formation of spatial patterns is an important issue in reaction–diffusion systems.Previous studies have mainly focused on the spatial patterns in reaction–diffusion models equipped with symmetric diffusion(such as normal or fractional Laplace diffusion),namely,assuming that spatial environments of the systems are homogeneous.However,the complexity and heterogeneity of spatial environments of biochemical reactions in vivo can lead to asymmetric diffusion of reactants.Naturally,there arises an open question of how the asymmetric diffusion affects dynamical behaviors of biochemical reaction systems.To answer this,we build a general asymmetric L´evy diffusion model based on the theory of a continuous time random walk.In addition,we investigate the two-species Brusselator model with asymmetric L´evy diffusion,and obtain a general condition for the formation of Turing and wave patterns.More interestingly,we find that even though the Brusselator model with symmetric diffusion cannot produce steady spatial patterns for some parameters,the asymmetry of L´evy diffusion for this model can produce wave patterns.This is different from the previous result that wave instability requires at least a three-species model.In addition,the asymmetry of L´evy diffusion can significantly affect the amplitude and frequency of the spatial patterns.Our results enrich our knowledge of the mechanisms of pattern formation.展开更多
Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentime...Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.展开更多
This study focuses on the improvement of the thermal stability and flame-retardant performance of polyurethane(PU)foam by using effective flame-retardant additives and nano silica(nSiO_(2))particles from rice husk.The...This study focuses on the improvement of the thermal stability and flame-retardant performance of polyurethane(PU)foam by using effective flame-retardant additives and nano silica(nSiO_(2))particles from rice husk.The addition of non-halogen flame retardants(FRs)including aluminum trihydroxide(ATH),triphenyl phosphate(TPP),and diammonium phosphate(DAP)leads to markedly enhanced thermal sta-bility and fire resistance of the PU/nSiO_(2)/FRs nanocomposites,resulting in achieving UL-94 HB standard.In particular,the nanocomposites met the UL-94 V-0 criteria thanks to the inclusion of DAP at 25 phr.The LOI value of the nanocomposites reached 26%which is much higher than that of PU/nSiO_(2)nanocompos-ite,about 20%.In order to further understand the fire-proof mechanism,the residue char layer remaining of the PU/nSiO_(2)/FRs nanocomposites after being burned was also investigated by scanning electron mi-croscopy(SEM)and Fourier transform infrared(FTIR).In addition,the microstructure,thermal stability,thermal conductivity,and mechanical properties of nanocomposites were also evaluated in this study.展开更多
The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human re...The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional requirements.To address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human effort.However,existing techniques often struggle with complex instructions and large-scale projects.In our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer trees.Experimental results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT dataset.Both datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse scenarios.These findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.展开更多
In this study, aluminum-doped zinc oxide(AZO) thin films were deposited onto a low-temperature polyethylene terephthalate(PET) substrate using DC magnetron sputtering. Deposition parameters included power range of 100...In this study, aluminum-doped zinc oxide(AZO) thin films were deposited onto a low-temperature polyethylene terephthalate(PET) substrate using DC magnetron sputtering. Deposition parameters included power range of 100-300 W, a working pressure of 15 mTorr, and a substrate temperature of 50 ℃. Post-deposition, flash lamp annealing(FLA) was employed as a rapid thermal processing method with a pulse duration of 1.7 ms and energy density of 7 J·cm-2, aimed at enhancing the film's quality while preserving the temperature-sensitive PET substrate. FLA offers advantages over conventional annealing,including shorter processing times and improved material properties. The structural, optical, and electrical characteristics of the AZO films were assessed using X-ray diffraction, field emission scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy, ultraviolet-visible spectroscopy, and Hall effect measurements. The results demonstrated that properties of AZO films varied with deposition and annealing conditions. Films deposited at 200 W and subjected to FLA exhibited superior crystallinity, with average visible light transmittance exceeding 80% and resistivity as low as 0.38 Ω·cm representing 95%improvement in transmittance. Electrical analysis revealed that carrier concentration, mobility, and resistivity were influenced by both sputtering and annealing parameters. These findings underscore the effectiveness of FLA in optimizing AZO thin film properties, highlighting potential in optoelectronics applications.展开更多
The World Health Organization states that foodborne diseases are a worldwide public health issue. Although street foods can provide nutritious and affordable ready-to-eat meals for city dwellers, their health risks ca...The World Health Organization states that foodborne diseases are a worldwide public health issue. Although street foods can provide nutritious and affordable ready-to-eat meals for city dwellers, their health risks can outweigh the benefits. A cross-sectional study was conducted in the Bamako district, focusing on street food vendors near schools, universities, extensive markets, administrative centers, and major roads. We aimed to sample fifty (50) sellers per municipality, making 300 sellers for the Bamako district. We developed a survey sheet to collect data, and six teams rotated between the municipalities each month. Before starting the collection, the teams were provided administrative papers approved by the municipal authority. The survey revealed three types of sales sites: fixed (65%), semi-fixed (30%), and mobile (4.40%). The proportion of sellers was 26.8%, 23.2%, 19.7%, and 4.2% in municipalities III, IV, and I. In municipalities I, II, III, IV, and VI, respectively, 92%, 95.70%, 93%, 87.2%, and 100% of the sellers were female. The age distribution of sellers was 65.63%, 46.81%, 40.82%, 38.30%, 36.17%, 36%, and 32% in the 25-34 and 35 - 44 age groups. Illiteracy rates were 59.20%, 61.70%, 55.30%, 75%, and 56% in municipalities I, II, III, IV, and VI, respectively. The study identified two categories of sellers: 48.3% in type 1 and 51.7% in type 2. The first category comprised 154 sellers, and the second 165 sellers. The survey found that 66.00%, 56.00%, 48.90%, 44.90%, 38.30%, and 34.40% of municipal V, VI, III, I, II, and IV sales sites were open-air. In municipality I, 63.30% of the sites were under hangars, while in municipalities II and IV, the corresponding percentages were 51.10% and 59.40%, respectively. Moreover, 46.00%, 31.90%, 31.30%, 30.60%, and 27.70% of the sites in municipalities VI, II, IV, I, and III were located next to gutters. In conclusion, this study identified several factors that could compromise the quality of street foods sold in the six municipalities of Bamako.展开更多
Various important medicines make use of secondary metabolites that are produced by plants.Medicinal plants,such as Withania somnifera and Tinospora cordifolia,are rich sources of chemically active compounds and are re...Various important medicines make use of secondary metabolites that are produced by plants.Medicinal plants,such as Withania somnifera and Tinospora cordifolia,are rich sources of chemically active compounds and are reported to have numerous therapeutic applications.The therapeutic use of medicinal plants is widely mentioned in Ayurveda and has folkloric importance in different parts of the world.The aim of this review is to summarize the phytochemical profiles,folkloric importance,and primary pharmacological activity of W.somnifera and T.cordifolia with emphasis on their action against the novel coronavirus.展开更多
Yogurt is a traditional dairy product well known in all the regions of the world. In Cameroon, the most popularly known type is “kossam” also called curdled milk. Kossam is a set of milk based beverage from northern...Yogurt is a traditional dairy product well known in all the regions of the world. In Cameroon, the most popularly known type is “kossam” also called curdled milk. Kossam is a set of milk based beverage from northern Cameroon presenting great symbolic, economic and social values for local population [1]. 150 Kossam samples were collected from neighborhoods of PK8, Bonamoussadi, Nyalla, cite des palmier, Deido and Bedi community and later on reconstituted into 50 different samples of 350 mL, each containing 1/3 of 3 individual samples. They were analyzed for their physiochemical properties such as: PH, titratable acidity, density, brix and dry matter using most at times the standard Association of Official Analytical Chemists (AOAC) methods with slight modifications and results compared to a licensed brand sold in the Cameroonian market. The results of the study showed that, the physico-chemical properties of the locally made yogurts were different within the different samples. Analysis of variance revealed a significant difference in the levels of the parameters analyzed in the different yogurt samples (p −1 Kg/L), Brix (8˚ - 24˚B), Dornic (23˚ - 160˚D). others contents per 100 g fresh matter are as follows: dry matter (average mean of 16.54%). Hence, the significant variations in the physico-chemical properties of kossam are a call for concern since as it impacts on the health of the population consuming this product.展开更多
Background: Hemolytic Disease of the Fetus and Newborn (HDFN) arises from blood group incompatibility, especially the RhD antigen. In Benin, systematic ABO RhD blood grouping is poorly understood by many midwives and ...Background: Hemolytic Disease of the Fetus and Newborn (HDFN) arises from blood group incompatibility, especially the RhD antigen. In Benin, systematic ABO RhD blood grouping is poorly understood by many midwives and nurses. Nearly one in ten women risk having children with HDFN. This study aimed to determine the level of knowledge of the Beninese population on HDFN. Methods: Data were collected from June 2023 to March 2024. Participants completed a Kobotoolbox questionnaire on WhatsApp, with in-person assistance for illiterate participants. The study involved 521 participants from across Benin. Data were analyzed using SigmaPlot version 14.0. Results: Among the 521 participants, 298 were women (57.20%) aged 18 to 77 years. The majority (40.69%) were aged 26 - 35. Over a third (35.51%) did not know their RhD blood group. Most (59.12%) were unaware of the risks for RhD discordant couples. Among those with a partner, 25.16% were in at-risk couples for HDFN, and over half (59.12%) were unaware of this risk. There was no significant association between being in a high-risk union and knowledge of the risk or education level. Conclusion: Only 40.88% of the Beninese population are aware of HDFN, indicating a low level of knowledge.展开更多
Information security and quality management are often considered two different fields. However, organizations must be mindful of how software security may affect quality control. This paper examines and promotes metho...Information security and quality management are often considered two different fields. However, organizations must be mindful of how software security may affect quality control. This paper examines and promotes methods through which secure software development processes can be integrated into the Systems Software Development Life-cycle (SDLC) to improve system quality. Cyber-security and quality assurance are both involved in reducing risk. Software security teams work to reduce security risks, whereas quality assurance teams work to decrease risks to quality. There is a need for clear standards, frameworks, processes, and procedures to be followed by organizations to ensure high-level quality while reducing security risks. This research uses a survey of industry professionals to help identify best practices for developing software with fewer defects from the early stages of the SDLC to improve both the quality and security of software. Results show that there is a need for better security awareness among all members of software development teams.展开更多
The high-water content of tomato predisposes it to spoilage by microorganisms and led producers to carry out traditional processing of tomatoes in the form of pasteurized tomato puree. However, rapid acidification of ...The high-water content of tomato predisposes it to spoilage by microorganisms and led producers to carry out traditional processing of tomatoes in the form of pasteurized tomato puree. However, rapid acidification of these traditional tomato purees is often observed. Then, the aim of this study was to evaluate the efficacy of the essential oil extracted from Clove (Syzygium aromaticum L.) in the improvement of traditional tomato puree producing technology. Essential oil of Clove (Syzygium aromaticum L.) was extracted by hydrodistillation and its chemical composition was determined by GC and GC/MS. Different types of traditional tomato puree were produced by the modification of the traditional processing technology and the addition of the essential oil introduction step, followed by manual stirring during the process. Based on previous studies, two different essential oil concentrations (5.0 and 7.5 μL∙g−1) were investigated. Physicochemical, microbiological and nutritional analyzes were performed in order to evaluate the quality of the traditional tomato puree produced. Results obtained revealed that the essential oil of Syzygium aromaticum investigated has a chemical composition characterized by the presence of eugenol (59.11%) and eugenol acetate (33.73%). Good stabilization of the physicochemical, microbiological and nutritional parameters in traditional tomato puree samples preserved with essential oil of Syzygium aromaticum were observed when compared to control. The essential oil of Clove, with his biological property, offers a novel approach to the management of traditional tomato puree during storage.展开更多
There is an urgent need for preventive and therapeutic drugs to effectively treat and prevent viral diseases from resurfacing as they emerge during the COVID-19 pandemic.This study aims to assess the antiviral effects...There is an urgent need for preventive and therapeutic drugs to effectively treat and prevent viral diseases from resurfacing as they emerge during the COVID-19 pandemic.This study aims to assess the antiviral effects of four natural compounds commonly used in traditional medicine to treat SARS-CoV-2 infection.A cytotoxicity,dose-dependent,and plaque reduction assay was performed on Vero CCL-81 cells to figure out their effects on the cells.Quantification of cytokines was assessed.In silico analysis for the selected compound was also evaluated.Results revealed that the compounds could disrupt the viral replication cycle through direct inhibition of the virus or immune system stimulation.The cytotoxicity assay results revealed that the compounds were well tolerated by the cells,indicating that the compounds were not toxic to the cells.This study evaluated the antioxidant capacities of propolis,curcumin,quercetin,and ginseng using ABTS,FRAP,and CUPRAC assays,revealing that propolis exhibited the highest antioxidant activity of ABTS with 1250.40±17.10μmol Trolox eq/g,with FRAP values reaching 1200.55±15.90μmol Fe2⁺eq/g and CUPRAC values of 1150.80±14.20μmol Trolox eq/g at 1000μg/mL,highlighting its potential as a potent natural antioxidant.The results of the plaque reduction assay revealed that the compounds could reduce the size and number of plaques,indicating that the compounds could inhibit the virus replication cycle.Subsequently,using molecular docking to analyze the effect of propolis,curcumin,quercetin,and ginseng as inhibitors,it was unveiled that the four compounds are likely to have the potential to inhibit the protease activity,spike protein S1,and RNA polymerase of SARS-CoV-2 and the virus titer was reduced by 100%after post-infection using propolis as an inhibitor control.展开更多
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
文摘Major solar plasma disturbances are subjected to Lomb-Scargle periodogram and wavelet analysis to determine the occurrence frequency.These disruptions include interplanetary coronal mass ejection,sudden storm commencement,high-speed streams,corotating interaction regions,interplanetary shocks and Forbush decreases.We included information on all of the aforementioned solar disturbances for the last six solar cycles,from 1965 to 2023,for this study.Our findings reveal some intriguing and noteworthy results that clearly distinguish between even and odd-numbered solar cycles.The study suggests that the Sun behaves differently in odd and even-numbered solar cycles as it comes from the massive solar eruptions.During even-numbered solar cycles,variations with a period of∼44 days are prominently observed in addition to solar rotation(∼27 days)and extended solar(∼36 days)rotation.However,in addition to solar rotation,prolonged solar rotation,and periods of around 44 days,we also detect a number of intermittent changes with nearly comparable amplitude during the oddnumbered solar cycles.The findings also demonstrate that,in contrast to odd-numbered solar cycles,the emissions rate of these disruptions is more distinct and predictable during even-numbered solar cycles.
文摘In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.
文摘BACKGROUND A recently developed method enables automated measurement of the hallux valgus angle(HVA)and the first intermetatarsal angle(IMA)from weightbearing foot radiographs.This approach employs bone segmentation to identify anatomical landmarks and provides standardized angle measurements based on established guidelines.While effective for HVA and IMA,preoperative radiograph analysis remains complex and requires additional measurements,such as the hallux interphalangeal angle(IPA),which has received limited research attention.AIM To expand the previous method,which measured HVA and IMA,by incorporating the automatic measurement of IPA,evaluating its accuracy and clinical relevance.METHODS A preexisting database of manually labeled foot radiographs was used to train a U-Net neural network for segmenting bones and identifying landmarks necessary for IPA measurement.Of the 265 radiographs in the dataset,161 were selected for training and 20 for validation.The U-Net neural network achieves a high mean Sørensen-Dice index(>0.97).The remaining 84 radiographs were used to assess the reliability of automated IPA measurements against those taken manually by two orthopedic surgeons(OA and OB)using computer-based tools.Each measurement was repeated to assess intraobserver(OA1 and OA2)and interobserver(O_(A2) and O_(B))reliability.Agreement between automated and manual methods was evaluated using the Intraclass Correlation Coefficient(ICC),and Bland-Altman analysis identified systematic differences.Standard error of measurement(SEM)and Pearson correlation coefficients quantified precision and linearity,and measurement times were recorded to evaluate efficiency.RESULTS The artificial intelligence(AI)-based system demonstrated excellent reliability,with ICC3.1 values of 0.92(AI vs OA2)and 0.88(AI vs O_(B)),both statistically significant(P<0.001).For manual measurements,ICC values were 0.95(OA2 vs OA1)and 0.95(OA2 vs OB),supporting both intraobserver and interobserver reliability.Bland-Altman analysis revealed minimal biases of:(1)1.61°(AI vs O_(A2));and(2)2.54°(AI vs O_(B)),with clinically acceptable limits of agreement.The AI system also showed high precision,as evidenced by low SEM values:(1)1.22°(O_(A2) vs O_(B));(2)1.77°(AI vs O_(A2));and(3)2.09°(AI vs O_(B)).Furthermore,Pearson correlation coefficients confirmed strong linear relationships between automated and manual measurements,with r=0.85(AI vs O_(A2))and r=0.90(AI vs O_(B)).The AI method significantly improved efficiency,completing all 84 measurements 8 times faster than manual methods,reducing the time required from an average 36 minutes to just 4.5 minutes.CONCLUSION The proposed AI-assisted IPA measurement method shows strong clinical potential,effectively corresponding with manual measurements.Integrating IPA with HVA and IMA assessments provides a comprehensive tool for automated forefoot deformity analysis,supporting hallux valgus severity classification and preoperative planning,while offering substantial time savings in high-volume clinical settings.
基金Science and Technology Planning Project of Guangdong Province(2023B1212060048).
文摘The Suizhou meteorite is a heavily shock-met-amorphosed L6 chondrite which contains thin shock melt veins.So far,26 high-pressure phases have been identified from the meteorite.Among the high-pressure phases,ten of them were approved as new minerals which include tuite,xieite,wangdaodeite,chenmingite,hemleyite,poirierite,asimowite,hiroseite,elgoresyite,and ohtaniite,by the Commission on New Minerals,Nomenclature and Classification of the International Mineralogical Association.Other high-pressure phases identified from the meteorite are ahrensite,akimotoite,bridgmanite,lingunite,magnesiowüstite,majorite,majorite-pyrope_(ss),maskelynite,riesite,ringwoodite,wadsleyite,and 5 other phases including phase A,vitrified phase B and phase C,phase D(Ca-rich majorite),and partly inverted ringwoodite.The occurrence and abundance of high-pressure phases makes this meteorite the one with the richest variety of high-pressure minerals to date.
基金funded by the TaipeiMedical University-National Taiwan University of Science and Technology joint research program under Grant No.TMU-NTUST-109-09.
文摘Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numerical approach.However,the material assumptions for past computational human femur simulations were mainly homogeneous.Thus,this study aimed to design and analyze scaffolds for reconstructing the distal femur defect using a patient-specific finite element modeling technique.A three-dimensional finite element model of the human femur with accurate geometry and material distribution was developed using the finite element method and material mapping technique.An intact femur and a distal femur defect model treated with nine microstructure scaffolds and two solid scaffolds were investigated and compared under a single-leg stance loading.The results showed that the metal solid scaffold design could provide the most stable fixation for reconstructing the distal femur defect.However,the fixation stability was affected by various microstructure designs and pillar diameters.A microstructure scaffold can be designed to satisfy all the biomechanical indexes,opening up future possibilities for more stable reconstructions.A three-dimensional finite element model of the femur with real bone geometry and bone material distribution can be developed,and this patient-specific femur model can be used for studying other femoral fractures or injuries,paving the way for more comprehensive research in the field.Besides,this patient-specific finite element modeling technique can also be applied to developing other human or animal bone models,expanding the scope of biomechanical research.
文摘Complex oxides are an important class of materials with enormous potential for electrochemical appli-cations.Depending on their composition and structure,such complex oxides can exhibit either a single conductivity(oxygen-ionic or protonic,or n-type,or p-type electronic)or a combination thereof gener-ating distinct dual-conducting or even triple-conducting materials.These properties enable their use as diverse functional materials for solid oxide fuel cells,solid oxide electrolysis cells,permeable membranes,and gas sensors.The literature review shows that the field of solid oxide materials and related electro-chemical cells has a significant level of research engagement,with over 8,000 publications published since 2020.The manual analysis of such a large volume of material is challenging.However,by examining the review articles,it is possible to identify key patterns,recent achievements,prospects,and remaining obstacles.To perform such an analysis,the present article provides,for the first time,a comprehensive summary of previous review publications that have been published since 2020,with a special focus on solid oxide materials and electrochemical systems.Thus,this study provides an important reference for researchers specializing in the fields of solid state ionics,high-temperature electrochemistry,and energyconversiontechnologies.
文摘In order to take into account the uncertainties linked to the variables in the evaluation of the statistical properties of structural response, a reliability approach with probabilistic aspect was considered. This is called the Probabilistic Transformation Method (PTM). This method is readily applicable when the function between the input and the output of the system is explicit. However, the situation is much more involved when it is necessary to perform the evaluation of implicit function between the input and the output of the system through numerical models. In this work, we propose a technique that combines Finite Element Analysis (FEA) and Probabilistic Transformation Method (PTM) to evaluate the Probability Density Function (PDF) of response where the function between the input and the output of the system is implicit. This technique is based on the numerical simulations of the Finite Element Analysis (FEA) and the Probabilistic Transformation Method (PTM) using an interface between Finite Element software and Matlab. Some problems of structures are treated in order to prove the applicability of the proposed technique. Moreover, the obtained results are compared to those obtained by the reference method of Monte Carlo. A second aim of this work is to develop an algorithm of global optimization using the local method SQP, because of its effectiveness and its rapidity of convergence. For this reason, we have combined the method SQP with the Multi start method. This developed algorithm is tested on test functions comparing with other methods such as the method of Particle Swarm Optimization (PSO). In order to test the applicability of the proposed approach, a structure is optimized under reliability constraints.
基金supported by the National Natural Science Foundation of China(Grant Nos.62066026,62363027,and 12071408)PhD program of Entrepreneurship and Innovation of Jiangsu Province,Jiangsu University’Blue Project’,the Natural Science Foundation of Jiangxi Province(Grant No.20224BAB202026)the Science and Technology Research Project of Jiangxi Provincial Department of Education(Grant No.GJJ2203316).
文摘The formation of spatial patterns is an important issue in reaction–diffusion systems.Previous studies have mainly focused on the spatial patterns in reaction–diffusion models equipped with symmetric diffusion(such as normal or fractional Laplace diffusion),namely,assuming that spatial environments of the systems are homogeneous.However,the complexity and heterogeneity of spatial environments of biochemical reactions in vivo can lead to asymmetric diffusion of reactants.Naturally,there arises an open question of how the asymmetric diffusion affects dynamical behaviors of biochemical reaction systems.To answer this,we build a general asymmetric L´evy diffusion model based on the theory of a continuous time random walk.In addition,we investigate the two-species Brusselator model with asymmetric L´evy diffusion,and obtain a general condition for the formation of Turing and wave patterns.More interestingly,we find that even though the Brusselator model with symmetric diffusion cannot produce steady spatial patterns for some parameters,the asymmetry of L´evy diffusion for this model can produce wave patterns.This is different from the previous result that wave instability requires at least a three-species model.In addition,the asymmetry of L´evy diffusion can significantly affect the amplitude and frequency of the spatial patterns.Our results enrich our knowledge of the mechanisms of pattern formation.
文摘Sentiment analysis, a crucial task in discerning emotional tones within the text, plays a pivotal role in understandingpublic opinion and user sentiment across diverse languages.While numerous scholars conduct sentiment analysisin widely spoken languages such as English, Chinese, Arabic, Roman Arabic, and more, we come to grapplingwith resource-poor languages like Urdu literature which becomes a challenge. Urdu is a uniquely crafted language,characterized by a script that amalgamates elements from diverse languages, including Arabic, Parsi, Pashtu,Turkish, Punjabi, Saraiki, and more. As Urdu literature, characterized by distinct character sets and linguisticfeatures, presents an additional hurdle due to the lack of accessible datasets, rendering sentiment analysis aformidable undertaking. The limited availability of resources has fueled increased interest among researchers,prompting a deeper exploration into Urdu sentiment analysis. This research is dedicated to Urdu languagesentiment analysis, employing sophisticated deep learning models on an extensive dataset categorized into fivelabels: Positive, Negative, Neutral, Mixed, and Ambiguous. The primary objective is to discern sentiments andemotions within the Urdu language, despite the absence of well-curated datasets. To tackle this challenge, theinitial step involves the creation of a comprehensive Urdu dataset by aggregating data from various sources such asnewspapers, articles, and socialmedia comments. Subsequent to this data collection, a thorough process of cleaningand preprocessing is implemented to ensure the quality of the data. The study leverages two well-known deeplearningmodels, namely Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), for bothtraining and evaluating sentiment analysis performance. Additionally, the study explores hyperparameter tuning tooptimize the models’ efficacy. Evaluation metrics such as precision, recall, and the F1-score are employed to assessthe effectiveness of the models. The research findings reveal that RNN surpasses CNN in Urdu sentiment analysis,gaining a significantly higher accuracy rate of 91%. This result accentuates the exceptional performance of RNN,solidifying its status as a compelling option for conducting sentiment analysis tasks in the Urdu language.
基金funded by the Vietnam National University Ho Chi Minh City(VNU-HCM)under grant number C2022-18-41.
文摘This study focuses on the improvement of the thermal stability and flame-retardant performance of polyurethane(PU)foam by using effective flame-retardant additives and nano silica(nSiO_(2))particles from rice husk.The addition of non-halogen flame retardants(FRs)including aluminum trihydroxide(ATH),triphenyl phosphate(TPP),and diammonium phosphate(DAP)leads to markedly enhanced thermal sta-bility and fire resistance of the PU/nSiO_(2)/FRs nanocomposites,resulting in achieving UL-94 HB standard.In particular,the nanocomposites met the UL-94 V-0 criteria thanks to the inclusion of DAP at 25 phr.The LOI value of the nanocomposites reached 26%which is much higher than that of PU/nSiO_(2)nanocompos-ite,about 20%.In order to further understand the fire-proof mechanism,the residue char layer remaining of the PU/nSiO_(2)/FRs nanocomposites after being burned was also investigated by scanning electron mi-croscopy(SEM)and Fourier transform infrared(FTIR).In addition,the microstructure,thermal stability,thermal conductivity,and mechanical properties of nanocomposites were also evaluated in this study.
基金This work is supported by EIAS(Emerging Intelligent Autonomous Systems)Data Science Lab,Prince Sultan University,Kingdom of Saudi Arabia,by paying the APC.
文摘The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional requirements.To address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human effort.However,existing techniques often struggle with complex instructions and large-scale projects.In our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer trees.Experimental results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT dataset.Both datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse scenarios.These findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.
基金supported by the MOTIE (Ministry of Trade,Industry,and Energy)in Korea,under the Fostering Global Talents for Innovative Growth Program (P0017308)supervised by the Korea Institute for Advancement of Technology (KIAT)+1 种基金supported by the MSIT (Ministry of Science and ICT),Korea,under the ITRC (Information Technology Research Center)support program (IITP-2024-2020-0-01655)supervised by the IITP (Institute of Information and Communications Technology Planning and Evaluation).
文摘In this study, aluminum-doped zinc oxide(AZO) thin films were deposited onto a low-temperature polyethylene terephthalate(PET) substrate using DC magnetron sputtering. Deposition parameters included power range of 100-300 W, a working pressure of 15 mTorr, and a substrate temperature of 50 ℃. Post-deposition, flash lamp annealing(FLA) was employed as a rapid thermal processing method with a pulse duration of 1.7 ms and energy density of 7 J·cm-2, aimed at enhancing the film's quality while preserving the temperature-sensitive PET substrate. FLA offers advantages over conventional annealing,including shorter processing times and improved material properties. The structural, optical, and electrical characteristics of the AZO films were assessed using X-ray diffraction, field emission scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy, ultraviolet-visible spectroscopy, and Hall effect measurements. The results demonstrated that properties of AZO films varied with deposition and annealing conditions. Films deposited at 200 W and subjected to FLA exhibited superior crystallinity, with average visible light transmittance exceeding 80% and resistivity as low as 0.38 Ω·cm representing 95%improvement in transmittance. Electrical analysis revealed that carrier concentration, mobility, and resistivity were influenced by both sputtering and annealing parameters. These findings underscore the effectiveness of FLA in optimizing AZO thin film properties, highlighting potential in optoelectronics applications.
文摘The World Health Organization states that foodborne diseases are a worldwide public health issue. Although street foods can provide nutritious and affordable ready-to-eat meals for city dwellers, their health risks can outweigh the benefits. A cross-sectional study was conducted in the Bamako district, focusing on street food vendors near schools, universities, extensive markets, administrative centers, and major roads. We aimed to sample fifty (50) sellers per municipality, making 300 sellers for the Bamako district. We developed a survey sheet to collect data, and six teams rotated between the municipalities each month. Before starting the collection, the teams were provided administrative papers approved by the municipal authority. The survey revealed three types of sales sites: fixed (65%), semi-fixed (30%), and mobile (4.40%). The proportion of sellers was 26.8%, 23.2%, 19.7%, and 4.2% in municipalities III, IV, and I. In municipalities I, II, III, IV, and VI, respectively, 92%, 95.70%, 93%, 87.2%, and 100% of the sellers were female. The age distribution of sellers was 65.63%, 46.81%, 40.82%, 38.30%, 36.17%, 36%, and 32% in the 25-34 and 35 - 44 age groups. Illiteracy rates were 59.20%, 61.70%, 55.30%, 75%, and 56% in municipalities I, II, III, IV, and VI, respectively. The study identified two categories of sellers: 48.3% in type 1 and 51.7% in type 2. The first category comprised 154 sellers, and the second 165 sellers. The survey found that 66.00%, 56.00%, 48.90%, 44.90%, 38.30%, and 34.40% of municipal V, VI, III, I, II, and IV sales sites were open-air. In municipality I, 63.30% of the sites were under hangars, while in municipalities II and IV, the corresponding percentages were 51.10% and 59.40%, respectively. Moreover, 46.00%, 31.90%, 31.30%, 30.60%, and 27.70% of the sites in municipalities VI, II, IV, I, and III were located next to gutters. In conclusion, this study identified several factors that could compromise the quality of street foods sold in the six municipalities of Bamako.
文摘Various important medicines make use of secondary metabolites that are produced by plants.Medicinal plants,such as Withania somnifera and Tinospora cordifolia,are rich sources of chemically active compounds and are reported to have numerous therapeutic applications.The therapeutic use of medicinal plants is widely mentioned in Ayurveda and has folkloric importance in different parts of the world.The aim of this review is to summarize the phytochemical profiles,folkloric importance,and primary pharmacological activity of W.somnifera and T.cordifolia with emphasis on their action against the novel coronavirus.
文摘Yogurt is a traditional dairy product well known in all the regions of the world. In Cameroon, the most popularly known type is “kossam” also called curdled milk. Kossam is a set of milk based beverage from northern Cameroon presenting great symbolic, economic and social values for local population [1]. 150 Kossam samples were collected from neighborhoods of PK8, Bonamoussadi, Nyalla, cite des palmier, Deido and Bedi community and later on reconstituted into 50 different samples of 350 mL, each containing 1/3 of 3 individual samples. They were analyzed for their physiochemical properties such as: PH, titratable acidity, density, brix and dry matter using most at times the standard Association of Official Analytical Chemists (AOAC) methods with slight modifications and results compared to a licensed brand sold in the Cameroonian market. The results of the study showed that, the physico-chemical properties of the locally made yogurts were different within the different samples. Analysis of variance revealed a significant difference in the levels of the parameters analyzed in the different yogurt samples (p −1 Kg/L), Brix (8˚ - 24˚B), Dornic (23˚ - 160˚D). others contents per 100 g fresh matter are as follows: dry matter (average mean of 16.54%). Hence, the significant variations in the physico-chemical properties of kossam are a call for concern since as it impacts on the health of the population consuming this product.
文摘Background: Hemolytic Disease of the Fetus and Newborn (HDFN) arises from blood group incompatibility, especially the RhD antigen. In Benin, systematic ABO RhD blood grouping is poorly understood by many midwives and nurses. Nearly one in ten women risk having children with HDFN. This study aimed to determine the level of knowledge of the Beninese population on HDFN. Methods: Data were collected from June 2023 to March 2024. Participants completed a Kobotoolbox questionnaire on WhatsApp, with in-person assistance for illiterate participants. The study involved 521 participants from across Benin. Data were analyzed using SigmaPlot version 14.0. Results: Among the 521 participants, 298 were women (57.20%) aged 18 to 77 years. The majority (40.69%) were aged 26 - 35. Over a third (35.51%) did not know their RhD blood group. Most (59.12%) were unaware of the risks for RhD discordant couples. Among those with a partner, 25.16% were in at-risk couples for HDFN, and over half (59.12%) were unaware of this risk. There was no significant association between being in a high-risk union and knowledge of the risk or education level. Conclusion: Only 40.88% of the Beninese population are aware of HDFN, indicating a low level of knowledge.
文摘Information security and quality management are often considered two different fields. However, organizations must be mindful of how software security may affect quality control. This paper examines and promotes methods through which secure software development processes can be integrated into the Systems Software Development Life-cycle (SDLC) to improve system quality. Cyber-security and quality assurance are both involved in reducing risk. Software security teams work to reduce security risks, whereas quality assurance teams work to decrease risks to quality. There is a need for clear standards, frameworks, processes, and procedures to be followed by organizations to ensure high-level quality while reducing security risks. This research uses a survey of industry professionals to help identify best practices for developing software with fewer defects from the early stages of the SDLC to improve both the quality and security of software. Results show that there is a need for better security awareness among all members of software development teams.
文摘The high-water content of tomato predisposes it to spoilage by microorganisms and led producers to carry out traditional processing of tomatoes in the form of pasteurized tomato puree. However, rapid acidification of these traditional tomato purees is often observed. Then, the aim of this study was to evaluate the efficacy of the essential oil extracted from Clove (Syzygium aromaticum L.) in the improvement of traditional tomato puree producing technology. Essential oil of Clove (Syzygium aromaticum L.) was extracted by hydrodistillation and its chemical composition was determined by GC and GC/MS. Different types of traditional tomato puree were produced by the modification of the traditional processing technology and the addition of the essential oil introduction step, followed by manual stirring during the process. Based on previous studies, two different essential oil concentrations (5.0 and 7.5 μL∙g−1) were investigated. Physicochemical, microbiological and nutritional analyzes were performed in order to evaluate the quality of the traditional tomato puree produced. Results obtained revealed that the essential oil of Syzygium aromaticum investigated has a chemical composition characterized by the presence of eugenol (59.11%) and eugenol acetate (33.73%). Good stabilization of the physicochemical, microbiological and nutritional parameters in traditional tomato puree samples preserved with essential oil of Syzygium aromaticum were observed when compared to control. The essential oil of Clove, with his biological property, offers a novel approach to the management of traditional tomato puree during storage.
基金The Deanship of Scientific Research at the University of Tabuk funded this work through Research Project No.S-1442-0077.
文摘There is an urgent need for preventive and therapeutic drugs to effectively treat and prevent viral diseases from resurfacing as they emerge during the COVID-19 pandemic.This study aims to assess the antiviral effects of four natural compounds commonly used in traditional medicine to treat SARS-CoV-2 infection.A cytotoxicity,dose-dependent,and plaque reduction assay was performed on Vero CCL-81 cells to figure out their effects on the cells.Quantification of cytokines was assessed.In silico analysis for the selected compound was also evaluated.Results revealed that the compounds could disrupt the viral replication cycle through direct inhibition of the virus or immune system stimulation.The cytotoxicity assay results revealed that the compounds were well tolerated by the cells,indicating that the compounds were not toxic to the cells.This study evaluated the antioxidant capacities of propolis,curcumin,quercetin,and ginseng using ABTS,FRAP,and CUPRAC assays,revealing that propolis exhibited the highest antioxidant activity of ABTS with 1250.40±17.10μmol Trolox eq/g,with FRAP values reaching 1200.55±15.90μmol Fe2⁺eq/g and CUPRAC values of 1150.80±14.20μmol Trolox eq/g at 1000μg/mL,highlighting its potential as a potent natural antioxidant.The results of the plaque reduction assay revealed that the compounds could reduce the size and number of plaques,indicating that the compounds could inhibit the virus replication cycle.Subsequently,using molecular docking to analyze the effect of propolis,curcumin,quercetin,and ginseng as inhibitors,it was unveiled that the four compounds are likely to have the potential to inhibit the protease activity,spike protein S1,and RNA polymerase of SARS-CoV-2 and the virus titer was reduced by 100%after post-infection using propolis as an inhibitor control.
