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Interactions between maternal parity and feed additives drive the composition of pig gut microbiomes in the post‑weaning period

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Journal of Animal Science and Biotechnology 2024年第3期15卷 1241-1257页

作者： Kayla Law Eduardo Rosa Medina Garcia Chad Hastad Deborah Murray Pedro E.Urriola Andres Gomez department of Animal Science University of Minnesota1364 Eckles AvenueSaint PaulMN 55108USA New Fashion Pork 164 Industrial ParkwayJacksonMN 56143USA

Background Nursery pigs undergo stressors in the post-weaning period that result in production and welfare *** challenges disproportionately impact the offspring of primiparous sows compared to those of mul-tiparous *** is known regarding potential interactions between parity and feed additives in the post-weaning period and their effects on nursery pig ***,the objective of this study was to investigate the effects of maternal parity on sow and offspring microbiomes and the influence of sow parity on pig fecal microbi-ome and performance in response to a prebiotic *** weaning,piglets were allotted into three treat-ment groups:a standard nursery diet including pharmacological doses of Zn and Cu(Con),a group fed a commercial prebiotic only(Preb)based on an Aspergillus oryzae fermentation extract,and a group fed the same prebiotic plus Zn and Cu(Preb+ZnCu).Results Although there were no differences in vaginal microbiome composition between primiparous and mul-tiparous sows,fecal microbiome composition was different(R^(2)=0.02,P=0.03).The fecal microbiomes of primiparous offspring displayed significantly higher bacterial diversity compared to multiparous offspring at d 0 and d 21 post-weaning(P<0.01),with differences in community composition observed at d 21(R^(2)=0.03,P=0.04).When analyzing the effects of maternal parity within each treatment,only the Preb diet triggered significant microbiome distinc-tions between primiparous and multiparous offspring(d 21:R^(2)=0.13,P=0.01;d 42:R^(2)=0.19,P=0.001).Composi-tional differences in pig fecal microbiomes between treatments were observed only at d 21(R^(2)=0.12,P=0.001).Pigs in the Con group gained significantly more weight throughout the nursery period when compared to those in the Preb+ZnCu *** Nursery pig gut microbiome composition was influenced by supplementation with an Aspergillus oryzae fermentation extract,with varying effects on performance

关键词： Aspergillus prebiotic Copper Feed additives Maternal Nursery pig microbiome Parity Swine microbiome Trace minerals Zinc

Development of a Novel Noise Reduction Algorithm for Smart Checkout RFID System in Retail Stores

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Computers, Materials & Continua 2024年第7期80卷 1277-1304页

作者： Shazielya Shamsul Mohammed A.H.Ali Salwa Hanim Abdul-Rashid Atef M.Ghaleb Fahad M.Alqahtani department of Mechanical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia Centre for Sustainable and Smart Manufacturing(CSSM) Faculty of EngineeringUniversiti MalayaKuala Lumpur50603Malaysia department of industrial Engineering College of EngineeringAlfaisal UniversityRiyadh11533Saudi Arabia department of industrial Engineering College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia

This paper presents a smart checkout system designed to mitigate the issues of noise and errors present in the existing barcode and RFID-based systems used at retail stores’checkout *** is achieved by integrating a novel AI algorithm,called Improved Laser Simulator Logic(ILSL)into the RFID *** enhanced RFID system was able to improve the accuracy of item identification,reduce noise interference,and streamline the overall checkout *** potential of the systemfor noise detection and elimination was initially investigated through a simulation study usingMATLAB and ILSL ***,it was deployed in a small-scale environment to validate its real-world *** show that RFID with the proposed new algorithm ILSL and AI basket is capable of accurately detecting the related itemswhile eliminating noise originating fromunrelated objects,achieving an accuracy rate of 88%.

关键词： Smart checkout system RFID technology improved laser simulator logic(ILSL) reduce noise checkout process

Predicting the Risk of Arterial Stiffness in Coal Miners Based on Different Machine Learning Models

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Biomedical and Environmental Sciences 2024年第1期37卷 108-111页

作者： CHEN Qian Wei HUANG Xue Zan DING Yu ZHU Feng Ren WANG Jia ZOU Yuan Jie DU Yuan Zhen ZHANG Ya Jun HUI Zi Wen ZHU Feng Lin MU Min The Project was supported by Open Research Grant of Joint National-Local Engineering Research Centre for Safe and Precise Coal Mining Anhui University of Science and TechnologyHefei 232001AnhuiChina School of Public Health Anhui University of Science and TechnologyHefei 232001AnhuiChina Key Laboratory of industrial Dust Prevention and Control Occupational Safety and HealthMinistry of EducationAnhui University of Science and TechnologyHefei 232001AnhuiChina Anhui Institute of occupational Safety and Health Anhui University of Science and TechnologyHefei 232001AnhuiChina Joint Research Center of occupational Medicine and Health Institute of Grand HealthHefei Comprehensive National Science CenterAnhui University of Science and TechnologyHefei 232001AnhuiChina department of occupational&Environmental Health School of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030HubeiChina Key Laboratory of Environment and Health Ministry of Education&Ministry of Environmental Protectionand State Key Laboratory of Environmental Health(Incubating)School of Public HealthTongji Medical CollegeHuazhong University of Science and TechnologyWuhan 430030HubeiChina

Coal is one of the world’s main energy resources,accounting for approximately 68%of China’s current total power ***,several studies have demonstrated that dust,exhaust fumes,and other harmful factors in coal mines increase the risk of cardiovascular disease(CVD)among miners^([1]).Arterial stiffness(AS)is an independent risk factor of CVD,and epidemiological studies have shown that AS plays a vital role in assessing the risk of CVD^([2]).

关键词： Arterial cardiovascular assessing

Combining Deep Learning with Knowledge Graph for Design Knowledge Acquisition in Conceptual Product Design

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工程与科学中的计算机建模(英文) 2024年第1期138卷 167-200页

作者： Yuexin Huang Suihuai Yu Jianjie Chu Zhaojing Su Yangfan Cong Hanyu Wang Hao Fan Key Laboratory of industrial Design and Ergonomics Ministry of Industry and Information TechnologyNorthwestern Polytechnical UniversityXi’an710072China School of industrial Design Engineering Delft University of TechnologyDelft2628 CEThe Netherlands department of industrial Design College of ArtsShandong University of Science and TechnologyTsingtao266590China College of Computer Science and Technology Zhejiang UniversityHangzhou310027China

The acquisition of valuable design knowledge from massive fragmentary data is challenging for designers in conceptual product *** study proposes a novel method for acquiring design knowledge by combining deep learning with knowledge ***,the design knowledge acquisition method utilises the knowledge extraction model to extract design-related entities and relations from fragmentary data,and further constructs the knowledge graph to support design knowledge acquisition for conceptual product ***,the knowledge extraction model introduces ALBERT to solve memory limitation and communication overhead in the entity extraction module,and uses multi-granularity information to overcome segmentation errors and polysemy ambiguity in the relation extraction *** comparison verified the effectiveness and accuracy of the proposed knowledge extraction *** case study demonstrated the feasibility of the knowledge graph construction with real fragmentary porcelain data and showed the capability to provide designers with interconnected and visualised design knowledge.

关键词： Conceptual product design design knowledge acquisition knowledge graph entity extraction relation extraction

Enhancing Hyper-Spectral Image Classification with Reinforcement Learning and Advanced Multi-Objective Binary Grey Wolf Optimization

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Computers, Materials & Continua 2024年第6期79卷 3469-3493页

作者： Mehrdad Shoeibi Mohammad Mehdi Sharifi Nevisi Reza Salehi Diego Martín Zahra Halimi Sahba Baniasadi TheWPI Business School Worcester Polytechnic InstituteWorcesterMassachusetts01609-2280USA department of industrial Engineering Iran University of Science and TechnologyNarmakTehran16846-13114Iran ETSI de Telecomunicación Universidad Politécnica de MadridAv.Complutense 30Madrid28040Spain department of Civil and Environmental Engineering University of MarylandCollege ParkMaryland20742USA department of industrial Engineering College of EngineeringUniversity of HoustonHoustonTexas77204USA

Hyperspectral(HS)image classification plays a crucial role in numerous areas including remote sensing(RS),agriculture,and the monitoring of the *** band selection in HS images is crucial for improving the efficiency and accuracy of image *** process involves selecting the most informative spectral bands,which leads to a reduction in data *** on these key bands also enhances the accuracy of classification algorithms,as redundant or irrelevant bands,which can introduce noise and lower model performance,are *** this paper,we propose an approach for HS image classification using deep Q learning(DQL)and a novel multi-objective binary grey wolf optimizer(MOBGWO).We investigate the MOBGWO for optimal band selection to further enhance the accuracy of HS image *** the suggested MOBGWO,a new sigmoid function is introduced as a transfer function to modify the wolves’*** primary objective of this classification is to reduce the number of bands while maximizing classification *** evaluate the effectiveness of our approach,we conducted experiments on publicly available HS image datasets,including Pavia University,Washington Mall,and Indian Pines *** compared the performance of our proposed method with several state-of-the-art deep learning(DL)and machine learning(ML)algorithms,including long short-term memory(LSTM),deep neural network(DNN),recurrent neural network(RNN),support vector machine(SVM),and random forest(RF).Our experimental results demonstrate that the Hybrid MOBGWO-DQL significantly improves classification accuracy compared to traditional optimization and DL ***-DQL shows greater accuracy in classifying most categories in both datasets *** the Indian Pine dataset,the MOBGWO-DQL architecture achieved a kappa coefficient(KC)of 97.68%and an overall accuracy(OA)of 94.32%.This was accompanied by the lowest root mean square error(RMSE)of 0.94,indicating very precise

关键词： Hyperspectral image classification reinforcement learning multi-objective binary grey wolf optimizer band selection

High-temperature tribological performance of functionally graded Stellite 6/WC metal matrix composite coatings manufactured by laser-directed energy deposition

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Friction 2024年第3期12卷 522-538页

作者： Marta OSTOLAZA Alaitz ZABALA Jon Inaki ARRIZUBIETA Iñigo LLAVORI Nagore OTEGI Aitzol LAMIKIZ department of Mechanical Engineering University of the Basque Country UPV/EHUPlaza Torres Quevedo 1Bilbo 48013Spain Faculty of Engineering Mechanics and Industrial ProductionMondragon UnibertsitateaLoramendi 4Mondragon 20500Spain

Wear-driven tool failure is one of the main hurdles in the *** issue can be addressed through surface coating with ceramic-reinforced metal matrix ***,the maximum ceramic content is limited by *** this work,the tribological behaviour of the functionally graded WC-ceramic-particlereinforced Stellite 6 coatings is *** that end,the wear resistance at room temperature and 400°C is ***,the tribological analysis is supported by crack sensitivity and hardness evaluation,which is of utmost importance in the processing of composite materials with *** indicate that functionally graded materials can be employed to increase the maximum admissible WC content,hence improving the tribological behaviour,most notably at high ***,a shift from abrasive to oxidative wear is observed in high-temperature wear testing.

关键词： friction coating metal matrix composite functionally graded materials high temperature laserdirected energy deposition

A whole-building data-driven fault detection and diagnosis approach for public buildings in hot climate regions

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Energy and Built Environment 2024年第6期5卷 911-932页

作者： Ashraf Alghanmi Akilu Yunusa-Kaltungo department of Mechanical Aerospace and Civil Engineering(MACE)University of ManchesterM139PLUK department of Mechanical Engineering Technology Yanbu Industrial CollegeYanbu Al-Sinaiyah City 41912Saudi Arabia

Fault detection and diagnosis(FDD)approaches comprise three main pillars:model-based,knowledge-based,and data-driven ***-driven approaches prioritise operational data and do not necessitate in-depth understanding of the system’s background;yet,significant amounts of data is required,which often poses challenges to *** simulated data is inexpensive and can run numerous faults types with varying severities and time periods,it has been used in data-driven FDD ***,the majority of FDD approaches are implemented at the system level of ***,most buildings have numerous systems with distinct ***,using individualised system-level analysis makes it difficult to see system-to-system ***,there is a significant underrepresentation of research that investigate the applications of FDD models under whole-building scenarios,so as to identify a wider range of energy consumption related faults in ***,since data-driven approaches significantly depend on the quantities of training data,it becomes challenging to diagnose faults that have limited *** a result,this study diagnoses numerous building systems faults,including single and simultaneous faults with limited *** is implemented within the context of the whole-building energy performance of religious buildings in hot climatic areas,employing data-driven FDD *** multi-class classification approaches were investigated to classify both the normal condition and faulty ***,feature extraction methodologies were compared to quantify their potential for improving the *** addition to the classification evaluation metrics,one-way ANOVA and Tukey-Kramer tests were implemented to examine the significance of the reported performance *** classifier obtained highest classification accuracy during validation and testing with about 90%,indicating a promising performance in w

关键词： Building energy performance Building maintenance Fault detection and diagnosis(FDD) Multi-class classification Feature extraction

Appraisal of pollution levels and non-carcinogenic health risks associated with the emergence of heavy metals in Indonesian community water for sanitation,hygiene,and consumption

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Emerging Contaminants 2024年第3期10卷 230-249页

作者： Nurul Fahimah Indah Rachmatiah Siti Salami Katharina Oginawati Haryo Mubiarto department of Environmental Engineering Faculty of Civil and Environmental EngineeringInstitut Teknologi BandungJl.Ganesha 10Bandung40132West JavaIndonesia Environmental Management Technology Research Group Department of Environmental EngineeringFaculty of Civil and Environmental EngineeringInstitut Teknologi BandungJl.Ganesha 10Bandung40132West JavaIndonesia industrial hygiene and Toxicology Laboratory Faculty of Civil and Environmental EngineeringInstitut Teknologi BandungJl.Ganesha 10Bandung40132West JavaIndonesia

Excessive heavy metal concentrations in water can pose a threat to human *** research analyzed 160 groundwater samples used for hygiene and sanitation,of which 62 were used for consumption,and 98 other types of drinking water were *** research findings indicate that 6%of groundwater for hygiene and sanitation and 13%of drinking water(7.8%groundwater,5.2%refill water)were deemed unfit for use due to elevated concentrations of certain heavy metals surpassing the maximum ***,Cd,Co,Hg,Mn,and Pb were detected in several drinking water samples deemed unsuitable for *** heavy metals suspected to originate from natural sources are Co,Fe,Mn,As,and Zn,while Pb,Cd,Hg,and Co are suspected to have anthropogenic *** arsenic exposure through the ingestion pathway posed a non-carcinogenic health risk to the local *** were found to be more susceptible than adult males and *** estimated average non-carcinogenic risk levels based on the water sources were refill water>well water>rainwater>spring ***,it is essential to monitor raw water sources at refill water depots in the study area and implement policies related to the quality of raw water sources,technology maintenance processes,and the quality of processed water from refill water ***,the community should be educated about householdscale water treatment to minimize health risks and consider using untreated well water and rainwater for consumption.

关键词： Bandung regency Groundwater Heavy metal Human health risk Water quality Refill water

Preventive effects of Bifidobacterium lactis Probio-M8 on ovalbumin-induced food allergy in mice

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Food Science and Human Wellness 2024年第4期13卷 2346-2352页

作者： Jialu Shi Yan Xu Cheng Liu Shizhi Wang Jin Wang Vijaya Raghavan Key Laboratory of Environmental Medicine and Engineering Ministry of Educationand Department of Nutrition and Food HygieneSchool of Public HealthSoutheast UniversityNanjing 210009China department of Bioresource Engineering Faculty of Agricultural and Environmental SciencesMcGill UniversitySainte-Anne-de-BellevueQC H9X3V9Canada

Food allergy is a significant public health concern *** probiotics have been found to enhance food allergy by regulating immune-microbe interactions in animal models and ***,the effects of Bifidobacterium lactis Probio-M8 on food allergy have not been thoroughly *** present study examined the anti-allergic properties of Probio-M8,particularly in relation to immune response and gut microbiota *** demonstrate that oral administration of Probio-M8 effectively mitigated the allergy symptoms triggered by ovalbumin(OVA)by ameliorating the morphological damage in the jejunum,reducing OVA-specific IgE and histamine levels in the serum,and suppressing Th2 cytokines(interleukin(IL)4 and IL-13)while increasing Th1 cytokines(interferon(IFN)γ)and regulatory T(Treg)cytokines(IL-10 and transforming growth factor(TGF)β1)in the culture supernatants of splenic ***,Probio-M8 effectively altered the diversity and composition of gut microbiota,particularly the relative abundances of Akkermansia_muciniphila in OVA-induced *** to the OVA group,the Probio-M8 group showed a decrease in the relative abundance of Akkermansia_*** conclusion,Probio-M8 demonstrates the potential to alleviate food allergy by regulating the Th1/Th2 response and modulating gut microbiota,thereby offering a novel therapeutic strategy for patients with food allergy.

关键词： Food allergy Bifidobacterium lactis Probio-M8 T cell immune response Gut microbiota