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Pre‑hatch thermal manipulation of embryos and post‑hatch baicalein supplementation mitigated heat stress in broiler chickens

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Journal of Animal Science and Biotechnology 2024年第3期15卷 1071-1085页

作者： Sadid Al Amaz Ajay Chaudhary Prem Lal Mahato rajesh Jha Birendra Mishra Department of Human Nutrition Food and Animal SciencesCollege of Tropical Agriculture and Human ResourcesUniversity of Hawai’i at ManoaAgSci 2161955 East‑West RdHonoluluHI 96822USA

Background High environmental temperatures induce heat stress in broiler chickens,affecting their health and pro-duction *** dietary,managerial,and genetics strategies have been tested with some success in mitigating heat stress(HS)in *** novel HS mitigation strategies for sustaining broiler production is critically *** study investigated the effects of pre-hatch thermal manipulation(TM)and post-hatch baica-lein supplementation on growth performance and health parameters in heat-stressed *** Six hundred fertile Cobb 500 eggs were incubated for 21 *** candling on embryonic day(ED)10,238 eggs were thermally manipulated at 38.5℃ with 55%relative humidity(RH)from ED 12 to 18,then transferred to the hatcher(ED 19 to 21,standard temperature)and 236 eggs were incubated at a controlled temperature(37.5℃)till *** hatch,180-day-old chicks from both groups were raised in 36 pens(n=10 birds/pen,6 replicates per treatment).The treatments were:1)Control,2)TM,3)control heat stress(CHS),4)thermal manipulation heat stress(TMHS),5)control heat stress supplement(CHSS),and 6)thermal manipulation heat stress supplement(TMHSS).All birds were raised under the standard environment for 21 d,followed by chronic heat stress from d 22 to 35(32–33℃ for 8 h)in the CHS,TMHS,CHSS,and TMHSS groups.A thermoneutral(22–24℃)environment was maintained in the Control and TM *** was constant(50%±5%)throughout the *** the data were analyzed using one-way ANOVA in R and GraphPad software at P<0.05 and are presented as mean±*** stress significantly decreased(P<0.05)the final body weight and ADG in CHS and TMHS groups compared to the other *** TM significantly increased(P<0.05)the expression of heat shock protein-related genes(HSP70,HSP90,and HSPH1)and antioxidant-related genes(GPX1 and TXN).TMHS birds showed a significant increment(P<0.05)in total cecal volatile fatty acid(VFA)concentration compared to the CHS bird

关键词： Baicalein Growth performance Gut microbiota Heat stress Thermal manipulation

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Effects of Enteromorpha prolifera polysaccharides on growth performance,intestinal barrier function and cecal microbiota in yellow-feathered broilers under heat stress

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Journal of Animal Science and Biotechnology 2024年第1期15卷 344-361页

作者： Wenchao Liu Huimei Liu Yaoyao Wang Zhongxiang Zhao Balamuralikrishnan Balasubramanian rajesh Jha Department of Animal Science College of Coastal Agricultural SciencesGuangdong Ocean UniversityZhanjiangGuangdong 524088People’s Republic of China Department of Food Science and Biotechnology College of Life ScienceSejong UniversitySeoul 05006South Korea Department of Human Nutrition Food and Animal SciencesCollege of Tropical Agriculture and Human ResourcesUniversity of Hawaii at ManoaHonoluluHI 96822USA

Background Global warming leading to heat stress(HS)is becoming a major challenge for broiler *** study aimed to explore the protective effects of seaweed(Enteromorpha prolifera)polysaccharides(EPS)on the intestinal barrier function,microbial ecology,and performance of broilers under HS.A total of 144 yellow-feathered broilers(male,56 days old)with 682.59±7.38 g were randomly assigned to 3 groups:1)TN(thermal neutral zone,23.6±1.8℃),2)HS(heat stress,33.2±1.5℃ for 10 h/d),and 3)HSE(HS+0.1%EPS).Each group contained 6 replicates with 8 broilers per *** study was conducted for 4 weeks;feed intake and body weights were measured at the end of weeks 2 and *** the end of the feeding trial,small intestine samples were collected for histomorphology,antioxidant,secretory immunoglobulin A(s Ig A)content,apoptosis,gene and protein expression analysis;cecal contents were also collected for microbiota analysis based on 16S r DNA *** Dietary EPS promoted the average daily gain(ADG)of broilers during 3–4 weeks of HS(P<0.05).At the end of HS on broilers,the activity of total superoxide dismutase(T-SOD),glutathione S-transferase(GST),and the content of s Ig A in jejunum were improved by EPS supplementation(P<0.05).Besides,dietary EPS reduced the epithelial cell apoptosis of jejunum and ileum in heat-stressed broilers(P<0.05).Addition of EPS in HS group broilers'diet upregulated the relative m RNA expression of Occludin,ZO-1,γ-GCLc and IL-10 of the jejunum(P<0.05),whereas downregulated the relative m RNA expression of NF-κB p65,TNF-αand IL-1βof the jejunum(P<0.05).Dietary EPS increased the protein expression of Occludin and ZO-1,whereas it reduced the protein expression of NF-κB p65 and MLCK(P<0.01)and tended to decrease the protein expression of TNF-α(P=0.094)in heat-stressed ***,the proportions of Bacteroides and Oscillospira among the three groups were positively associated with jejunal apoptosis and pro-inflammatory cytokine ex

关键词： Broilers Cecal microbiota Heat stress Intestinal barrier function Seaweed polysaccharides

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Modified Black Widow Optimization-Based Enhanced Threshold Energy Detection Technique for Spectrum Sensing in Cognitive Radio Networks

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Computer Modeling in Engineering & Sciences 2024年第3期138卷 2339-2356页

作者： R.Saravanan R.Muthaiah A.rajesh School of Computing SASTRA Deemed UniversityThanjavur613401India School of Electrical&Electronics Engineering SASTRA Deemed UniversityThanjavur613401India

This study develops an Enhanced Threshold Based Energy Detection approach(ETBED)for spectrum sensing in a cognitive radio *** threshold identification method is implemented in the received signal at the secondary user based on the square *** proposed method is implemented with the signal transmission of multiple outputs-orthogonal frequency division ***,the proposed method is considered the dynamic detection threshold adjustments and energy identification spectrum sensing technique in cognitive radio *** the dynamic threshold,the signal ratio-based threshold is *** threshold is computed by considering the Modified Black Widow Optimization Algorithm(MBWO).So,the proposed methodology is a combination of dynamic threshold detection and *** general threshold-based detection technique has different limitations such as the inability optimal signal threshold for determining the presence of the primary user *** limitations undermine the sensing accuracy of the energy identification ***,the ETBED technique is developed to enhance the energy efficiency of cognitive radio *** projected approach is executed and analyzed with performance and comparison *** proposed method is contrasted with the conventional techniques of theWhale Optimization Algorithm(WOA)and GreyWolf Optimization(GWO).It indicated superior results,achieving a high average throughput of 2.2 Mbps and an energy efficiency of 3.8,outperforming conventional techniques.

关键词： Cognitive radio network spectrum sensing noise uncertainty modified black widow optimization algorithm energy detection technique

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An Assisted Diagnosis of Alzheimer’s Disease Incorporating Attention Mechanisms Med-3D Transfer Modeling

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Computers, Materials & Continua 2024年第1期78卷 713-733页

作者： Yanmei Li Jinghong Tang Weiwu Ding Jian Luo Naveed Ahmad rajesh Kumar School of Artificial Intelligence Chongqing University of TechnologyChongqing400054China Computer School China West Normal UniversityNanchong637009China Department of Computer Science Prince Sultan UniversityRiyadh11586Saudi Arabia Yangtze Delta Region Institute(Huzhou) University of Electronic Science and Technology of ChinaHuzhou313001China

Alzheimer’s disease(AD)is a complex,progressive neurodegenerative *** subtle and insidious onset of its pathogenesis makes early detection of a formidable challenge in both contemporary neuroscience and clinical *** this study,we introduce an advanced diagnostic methodology rooted in theMed-3D transfermodel and enhanced with an attention *** aim to improve the precision of AD diagnosis and facilitate its early ***,we employ a spatial normalization technique to address challenges like clarity degradation and unsaturation,which are commonly observed in imaging ***,an attention mechanism is incorporated to selectively focus on the salient features within the imaging *** upon this foundation,we present the novelMed-3D transfermodel,designed to further elucidate and amplify the intricate features associated *** proposedmodel has demonstrated promising results,achieving a classification accuracy of 92%.To emphasize the robustness and practicality of our approach,we introduce an adaptive‘hot-updating’auxiliary diagnostic *** system not only enables continuous model training and optimization but also provides a dynamic platform to meet the real-time diagnostic and therapeutic demands of AD.

关键词： Alzheimer’s disease channel attention Med-3D hot update

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Machine learning modeling for fuel cell-battery hybrid power system dynamics in a Toyota Mirai 2 vehicle under various drive cycles

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Energy and AI 2024年第3期17卷 406-418页

作者： Adithya Legala Matthew Kubesh Venkata rajesh Chundru Graham Conway Xianguo Li Southwest Research Institute San AntonioTXUSA Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooOntarioCanada

Electrification is considered essential for the decarbonization of mobility sector, and understanding and modeling the complex behavior of modern fuel cell-battery electric-electric hybrid power systems is challenging, especially for product development and diagnostics requiring quick turnaround and fast computation. In this study, a novel modeling approach is developed, utilizing supervised machine learning algorithms, to replicate the dynamic characteristics of the fuel cell-battery hybrid power system in a 2021 Toyota Mirai 2nd generation (Mirai 2) vehicle under various drive cycles. The entire data for this study is collected by instrumenting the Mirai vehicle with in-house data acquisition devices and tapping into the Mirai controller area network bus during chassis dynamometer tests. A multi-input - multi-output, feed-forward artificial neural network architecture is designed to predict not only the fuel cell attributes, such as average minimum cell voltage, coolant and cathode air outlet temperatures, but also the battery hybrid system attributes, including lithium-ion battery pack voltage and temperature with the help of 15 system operating parameters. Over 21,0000 data points on various drive cycles having combinations of transient and near steady-state driving conditions are collected, out of which around 15,000 points are used for training the network and 6,000 for the evaluation of the model performance. Various data filtration techniques and neural network calibration processes are explored to condition the data and understand the impact on model performance. The calibrated neural network accurately predicts the hybrid power system dynamics with an R-squared value greater than 0.98, demonstrating the potential of machine learning algorithms for system development and diagnostics.

关键词： Artificial neural network(ANN) Proton exchange membrane fuel cell(PEMFC) Fuel cell electric vehicle(FCEV) Fuel cell-battery electric-electric hybrid power system Data based models Lithium-ion battery(LiB)

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Depression and anxiety among cancer patients visiting a tertiary care cancer hospital

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World Journal of Psychiatry 2024年第2期14卷 287-295页

作者： Maheshor Kaphle Diya Bajracharya Nirmala Regmi Dipsikha Aryal rajesh Karki Department of Public Health Peoples Dental College and HospitalTribhuvan UniversityKathmandu 44600BagmatiNepal Department of Public Health CiST CollegePokhara UniversityKathmandu 44600BagmatiNepal Department of Oncology Kanti HospitalMaharajgunjKathmandu 44600Nepal Central Department of Public Health Institute of MedicineTribhuvan UniversityMaharajgunjKathmandu 44600BagmatiNepal

BACKGROUND Cancer patients frequently experience psychological problems related to reactions to cancer diagnosis,cancer type and stage,treatment effects,recurrence,fear of end-of-life,survivorship,and financial *** and anxiety are both psychological and physiological disturbances among cancer *** To assess the prevalence of depression and anxiety among cancer patients attending a tertiary care cancer *** A cross-sectional study was conducted at Bhaktapur Cancer Hospital in Kathmandu Valley among 220 cancer patients aged from 18 years to 70 *** approval was taken from the Institutional Review Committee of CiST *** sampling was used to interview patients with the standardized Patient-Health Questionnaire(PHQ-9)for Depression and Hospital Anxiety and Depression sub-scale(HADS-A)for ***-Data was used for data entry and transferred to SPSS Version 25 for *** The study revealed that of 220 patients,most of the respondents belonged to the age group 51-60 *** than half 131(59.6%)of the respondents were female,most of them had depression,and one-third had *** the respondents,124(56.4%)had mild depression,70(31.8%)had moderate depression,and 3(1.3%)had severe depression;79(35.9%)had mild anxiety,64(29.1%)had moderate anxiety,and 4(1.8%)had severe *** Most respondents were depressed and one-third had *** than half and nearly one-third had mild and moderate depression,respectively,and nearly one-third had mild and moderate anxiety,which is higher than other studies.

关键词： Anxiety Cancer patients Depression Nepal Prevalence

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Multimodality Medical Image Fusion Based on Pixel Significance with Edge-Preserving Processing for Clinical Applications

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Computers, Materials & Continua 2024年第3期78卷 4317-4342页

作者： Bhawna Goyal Ayush Dogra Dawa Chyophel Lepcha rajesh Singh Hemant Sharma Ahmed Alkhayyat Manob Jyoti Saikia Department of ECE and UCRD Chandigarh UniversityMohaliPunjab140413India Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India Department of ECE Uttaranchal Institute of TechnologyUttaranchal UniversityDehradun248007India IES College of Technology IES UniversityBhopal462044India College of Technical Engineering The Islamic UniversityNajaf54001Iraq Department of Electrical Engineering University of North FloridaJacksonvilleFL32224USA

Multimodal medical image fusion has attained immense popularity in recent years due to its robust technology for clinical *** fuses multiple images into a single image to improve the quality of images by retaining significant information and aiding diagnostic practitioners in diagnosing and treating many ***,recent image fusion techniques have encountered several challenges,including fusion artifacts,algorithm complexity,and high computing *** solve these problems,this study presents a novel medical image fusion strategy by combining the benefits of pixel significance with edge-preserving processing to achieve the best fusion ***,the method employs a cross-bilateral filter(CBF)that utilizes one image to determine the kernel and the other for filtering,and vice versa,by considering both geometric closeness and the gray-level similarities of neighboring pixels of the images without smoothing *** outputs of CBF are then subtracted from the original images to obtain detailed *** further proposes to use edge-preserving processing that combines linear lowpass filtering with a non-linear technique that enables the selection of relevant regions in detailed images while maintaining structural *** regions are selected using morphologically processed linear filter residuals to identify the significant regions with high-amplitude edges and adequate *** outputs of low-pass filtering are fused with meaningfully restored regions to reconstruct the original shape of the *** addition,weight computations are performed using these reconstructed images,and these weights are then fused with the original input images to produce a final fusion result by estimating the strength of horizontal and vertical *** standard quality evaluation metrics with complementary properties are used for comparison with existing,well-known algorithms objectively to validate the fusion *** results from th

关键词： Image fusion fractal data analysis biomedical diseases research multiresolution analysis numerical analysis

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Cr-induced fusion reactions to synthesize superheavy elements

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Nuclear Science and Techniques 2024年第5期35卷 122-130页

作者： S.Madhu H.C.Manjunatha N.Sowmya B.M.rajesh L.Seenappa R.S.Susheela Department of Physics R V College of EngineeringBangalore 560074India Visvesvaraya Technological University BelagaviKarnataka 590018India Department of Physics Government First Grade CollegeSrinivasapurKarnataka 563135India Department of Physics Government First Grade CollegeDevanahallyKarnataka 562110India Department of Physics Government First Grade CollegeMulbagalKarnataka 563131India Department of Physics Government First Grade collegeNanjangudOoty RoadMysore 571301India

We investigated ^(50,52-54)Cr-induced fusion reactions for the synthesis of the superheavy element in the 104≤Z≤122 *** cross sections produced in this investigation using ^(54)Cr projectiles were compared with those obtained in prior *** estimated cross sections from this analysis are consistent with the findings of prior *** the current study,the predicted cross section was found to be 42fb at 236 MeV for ^(53)Cr+^(243)Am,23.2 fb at 236 MeV for ^(54)Cr+^(247)Cm,95.6 fb at 240 MeV for ^(53)Cr+248Bk,and 1.33 fb at 242 MeV for ^(53)Cr+***,these projected cross sections with excitation energy and beam energy will be useful in future Cr-induced fusion reaction investigations.

关键词： Fusion cross sections Compound nucleus formation probability Survival probability Evaporation residue cross sections

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Role of artificial intelligence in gastrointestinal surgery

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Artificial Intelligence in Cancer 2024年第2期5卷 1-9页

作者： Ankit Shukla rajesh Chaudhary Nishant Nayyar Department of Surgery Dr Rajendra Prasad Government Medical CollegeKangra 176001Himachal PradeshIndia Department of Renal Transplantation Dr Rajendra Prasad Government Medical CollegeKangra 176001India Department of Radiology Dr Rajendra Prasad Government Medical CollegeKangra 176001Himachal PradeshIndia

Artificial intelligence is rapidly evolving and its application is increasing day-byday in the medical *** application of artificial intelligence is also valuable in gastrointestinal diseases,by calculating various scoring systems,evaluating radiological images,preoperative and intraoperative assistance,processing pathological slides,prognosticating,and in treatment *** field has a promising future and can have an impact on many management *** this minireview,we aimed to determine the basics of artificial intelligence,the role that artificial intelligence may play in gastrointestinal surgeries and malignancies,and the limitations thereof.

关键词： Machine learning Gastrointestinal surgery Radiology Artificial neural network Deep learning

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Improved neurological diagnoses and treatment strategies via automated human brain tissue segmentation from clinical magnetic resonance imaging

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Intelligent Medicine 2024年第3期4卷 161-169页

作者： Puranam Revanth Kumar rajesh Kumar Jha P Akhendra Kumar B Deevena Raju Department of Electronics and Communication Engineering Faculty of Science and TechnologyICFAI Foundation for Higher EducationHyderabadIndia Department of Data Science&AI Faculty of Science and TechnologyICFAI Foundation for Higher EducationHyderabadIndia

Objective Segmentation of medical images is a crucial process in various image analysis *** segmentation methods excel in accuracy when compared to manual segmentation in the context of medical image *** of the essential phases in the quantitative analysis of the brain is automated brain tissue segmentation using clinically obtained magnetic resonance imaging(MRI)*** allows for precise quantitative examination of the brain,which aids in diagnosis,identification,and classification of ***,the efficacy of the segmentation approach is crucial to disease diagnosis and treatment *** This study presented a hybrid optimization method for segmenting brain tissue in clinical MRI scans us-ing a fractional Henry horse herd gas optimization-based Shepard convolutional neural network(FrHHGO-based ShCNN).To segment the clinical brain MRI images into white matter(WM),grey matter(GM),and cerebrospinal fluid(CSF)tissues,the proposed framework was evaluated on the Lifespan Human Connectome Projects(HCP)*** hybrid optimization algorithm,FrHHGO,integrates the fractional Henry gas optimization(FHGO)and horse herd optimization(HHO)*** required 30 min,whereas testing and segmentation of brain tissues from an unseen image required an average of 12 *** Compared to the results obtained with no refinements,the Skull stripping refinement showed significant *** the method included a preprocessing stage,it was flexible enough to enhance image quality,allowing for better results even with low-resolution *** precision of 93.2%,recall of 91.5%,Dice score of 91.1%,and F1-score of 90.5% were achieved using the proposed FrHHGO-based ShCNN,which was superior to all other approaches.

关键词： Brain tissue segmentation Deep learning Magnetic resonance imaging Optimization technique Shepard convolutional neural network

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