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Smart Healthcare Activity Recognition Using Statistical Regression and intelligent Learning

Computers, Materials & Continua 2024年第1期78卷 1189-1205页

作者： K.Akilandeswari Nithya Rekha Sivakumar hend Khalid Alkahtani Shakila Basheer Sara Abdelwahab Ghorashi Department of Computer Sciences Government Arts College(Autonomous)Salem636007India Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of information Systems College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia

in this present time,Human Activity Recognition(HAR)has been of considerable aid in the case of health monitoring and *** exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and *** many research works conducted on Smart Healthcare Monitoring,there remain a certain number of pitfalls such as time,overhead,and falsification involved during ***,this paper proposes a Statistical Partial Regression and Support Vector intelligent Agent Learning(SPR-SViAL)for Smart Healthcare *** first,the Statistical Partial Regression Feature Extraction model is used for data preprocessing along with the dimensionality-reduced features extraction ***,the input dataset the continuous beat-to-beat heart data,triaxial accelerometer data,and psychological characteristics were acquired from ioT wearable *** attain highly accurate Smart Healthcare Monitoring with less time,Partial Least Square helps extract the dimensionality-reduced *** that,with these resulting features,SViAL is proposed for Smart Healthcare Monitoring with the help of Machine Learning and intelligent Agents to minimize both analysis falsification and *** evaluation is carried out for factors such as time,overhead,and false positive rate accuracy concerning several *** quantitatively analyzed results indicate the better performance of our proposed SPR-SViAL method when compared with two state-of-the-art methods.

关键词： internet of Things smart health care monitoring human activity recognition intelligent agent learning statistical partial regression support vector

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Surface activation of viscose textiles via air,argon,and oxygen dielectric barrier discharge plasma:influence of peak voltage

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Plasma Science and Technology 2024年第7期26卷 134-147页

作者： Shrouk ELASHRY Usama M.RASHED Mostafa A.waHBA hend M.AHMED Nabil M.ELSiRAGY Plasma Laboratory Physics DepartmentFaculty of scienceTanta UniversityTanta 31527Egypt Physics Department Faculty of Science(Male)Al-Azhar UniversityCairo 11651Egypt Textile Research industrial Division National Research CentreDokkiGiza 12622Egypt

This paper discusses the use of atmospheric pressure dielectric barrier discharge(DBD)plasma treatment to enhance the surface qualities of viscose *** study explores the effects of different plasma gases,discharge voltages,and exposure times on the treated *** findings emphasize the importance of optimizing the plasma's peak voltage to achieve the desired surface treatment *** document also presents data on colour strength,wettability,colour fastness,and tensile strength of the treated fabrics,as well as scanning electron microscopy(SEM)analysis of surface morphology and chemical analysis using fouriertransition infrared spectroscopy(FTiR)and energy dispersive X-ray(EDX).The results show that treatment at a peak voltage of 11.83 k V is more efficient,except for the tensile strength which is enhanced at a peak voltage of 8.92 k *** oxygen plasma treatment significantly improves the colour strength,which exhibits an increase from 11 to *** intensified colour was attributed to the significant influence of electrostatic interactions between the charged hydroxyl groups of the oxygen plasma treated viscose textiles and the dye molecules,which enhance the *** oxygen DBD plasma exhibits a higher ability to enhance the properties of textiles when compared to air and argon *** study presents a sustainable,economical,secure,and ecologically friendly approach to explore new fabrics for specific uses.

关键词： Lissajous diagrams printability wettability tensile strength SEM EDX FTiR

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Added value of ratio of cross diameters of the appendix in ultrasound diagnosis of acute appendicitis

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World Journal of Gastrointestinal Surgery 2024年第1期16卷 21-28页

作者： Feng-wa Gu Si-Ze Wu Department of Ultrasound The First Affiliated Hospital of Hainan Medical UniversityHaikou 570102Hainan ProvinceChina

BACKGROUND The maximum outer diameter(MOD)of the appendix is an essential parameter for diagnosing acute appendicitis,but there is space for improvement in ultrasound(US)diagnostic *** To investigate whether combining the ratio of the cross diameters(RATiO)of the appendix with MOD of the appendix can enhance the diagnostic performance of acute *** A retrospective study was conducted,and medical records of 233 patients with acute appendicitis and 112 patients with a normal appendix were *** MOD and RATiO of the appendix were calculated and tested for their diagnostic performance of acute appendicitis,both individually and in *** The RATiO for a normal appendix was 1.32±0.16,while for acute appendicitis it was 1.09±*** cut-off value for RATiO was determined to be≤*** area under the receiver operating characteristic curve(AUC)for diagnosing acute appendicitis using RATiO≤1.18 and MOD>6 mm was 0.870 and 0.652,*** was a significant difference in AUC between RATiO≤1.18 and MOD>6 mm(Ping the combination of RATiO≤1.18 and MOD>6 mm with MOD>6 mm alone,the combination showed increased specificity,positive predictive value(PPV),and ***,the sensitivity and negative predictive value *** Combining RATiO of the appendix≤1.18 and MOD>6 mm can significantly improve the specificity,PPV,and AUC in the US diagnosis of acute appendicitis.

关键词： Acute appendicitis Diameter Ratio Diagnosis Ultrasound

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The earliest evidence for a microblade adaptation in the remote,high altitude regions of the Tibetan Plateau

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Science China Earth Sciences 2024年第5期67卷 1561-1573页

作者： Yingshuai JiN Xiaoling ZHANG Shejiang waNG Junyi GE Wei HE wa DA Yunyao TAN Ziyi YANG Christopher MORGAN Xing GAO institute of Vertebrate Paleontology and Paleoanthropology Chinese Academy of SciencesBeijing 100044China University of the Chinese Academy of Sciences Beijing 100049China Cultural Relics Conservation institute of the Xizang Autonomous Region Lhasa 850000China Nagqu Culture and Tourism Bureau Nagqu 852000China University of Nevada Reno 89557USA

Microblade assemblages are among the most common prehistoric archaeological materials found on the Tibetan Plateau(TP)and are thought to indicate large scale migration to and settlement of the *** microblade sites,however,have been systematically excavated,especially in the remotest,highest-elevation regions of the *** timing of the large-scale arrival,spread,and permanent settlement of people on the TP therefore remains *** this paper,we report on a recently excavated site,Locality 3 of the Nwya Devu Site(ND3),located at 4600 meters above sea level(masl),near the shore of Ngoin Lake,on the interior *** analyses reveal a fairly typical microblade technological orientation and two types of microblade cores:wedge-shaped and semi-conical,which are similar to those found throughout North *** Optically Stimulated Luminescence(OSL)dating and AMS^(14)C dating,the age of ND3 ranges from 11 to 10 *** date range indicates ND3 is the oldest microblade site yet recorded in the remote,high-elevation regions of the TP and thus provides important information about when and how hunter-gatherers using microblades began exploiting the higher altitudes of the *** together,studies at ND3 and throughout the TP suggest that a microblade adaptation is associated with the first prolonged human occupation of the plateau and that microblades played a significant role in mediating the risks and facilitating the mobility necessary to permanently inhabit the TP.

关键词： The interior of Tibetan Plateau Nwya Devu locality 3 Microblade Early Holocene High altitude adaption

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Strengthening and control of second-phase particle precipitation in ferritic/austenitic/martensitic heat-resistant alloys:a review

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Journal of iron and Steel Research international 2024年第1期31卷 3-23页

作者： Xue-cheng Peng Han-jie Guo Xin-fang Zhang Yi-wa Luo Ye Sun Jing Guo Rong-guang Yang Xiao-dan Zheng School of Metallurgical and Ecological Engineering University of Science and Technology Beijing(USTB)Beijing100083China Beijing Key Laboratory of Special Melting and Preparation of High-End Metal Materials University of Science and Technology Beijing(USTB)Beijing100083China Beijing Shougang Gitane New MATERiALS Co. Ltd.Beijing102206China

Heat-resistant alloys with excellent mechanical properties are widely used in various fields,and further improvement in their properties is essential to meet the requirements in new-generation advanced supercritical boilers,nuclear reactors,superheaters,and other new materials *** effectively enhance the comprehensive performance of heat-resistant alloys,second-phase particle strengthening has been widely studied,and in the face of different service envi-ronments of advanced heat-resistant steels,the selection of suitable second-phase particles is essential to maximize the performance of these *** this end,three major types of reinforcing phases in heat-resistant alloys such as carbides,rare earth oxides,and intermetallic compounds are summarized.A comparative analysis of the precipitation behavior of the reinforcing phases with different types as well as the risks and means of controlling their use in service,is *** parameters for the application of various types of second-phase particles in heat-resistant alloys are provided to support the design and preparation of new ultrahigh-performance heat-resistant alloys.

关键词： Heat-resistant alloy Second-phase particle Carbide Rare earth oxide intermetallic compound Strengthening

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Particle Swarm Optimization-Based Hyperparameters Tuning of Machine Learning Models for Big COViD-19 Data Analysis

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Journal of Computer and Communications 2024年第3期12卷 160-183页

作者： hend S. Salem Mohamed A. Mead Ghada S. El-Taweel Department of Computer Sciences Suez Canal University Ismailia Egypt

Analyzing big data, especially medical data, helps to provide good health care to patients and face the risks of death. The COViD-19 pandemic has had a significant impact on public health worldwide, emphasizing the need for effective risk prediction models. Machine learning (ML) techniques have shown promise in analyzing complex data patterns and predicting disease outcomes. The accuracy of these techniques is greatly affected by changing their parameters. Hyperparameter optimization plays a crucial role in improving model performance. in this work, the Particle Swarm Optimization (PSO) algorithm was used to effectively search the hyperparameter space and improve the predictive power of the machine learning models by identifying the optimal hyperparameters that can provide the highest accuracy. A dataset with a variety of clinical and epidemiological characteristics linked to COViD-19 cases was used in this study. Various machine learning models, including Random Forests, Decision Trees, Support Vector Machines, and Neural Networks, were utilized to capture the complex relationships present in the data. To evaluate the predictive performance of the models, the accuracy metric was employed. The experimental findings showed that the suggested method of estimating COViD-19 risk is effective. When compared to baseline models, the optimized machine learning models performed better and produced better results.

关键词： Big COViD-19 Data Machine Learning Hyperparameter Optimization Particle Swarm Optimization Computational intelligence

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Deuterium distribution and behavior of blisters in pre-damaged and undamaged tungsten

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Tungsten 2024年第3期6卷 647-656页

作者： Cong Li Xiao-wa wang Ran-Ran Su Xuan-Xin Hu Shu-Guang Wei Han-Jun Tu Li-Qun Shi Hong-Liang Zhang Key Laboratory of Nuclear Physics and ion-Beam Application Institute of Modern Physics Fudan University School of Mechanical Engineering Shanghai Jiao Tong University Department of Materials Science and Engineering University of Wisconsin

Tungsten(W),as a plasma-facing material,is subjected to high fluence plasma,resulting in both radiation damage and deuterium(D) *** study explores the blistering behavior and D supersaturated layers in both pre-damaged and undamaged W *** achieve a uniform damage profile similar to neutron irradiation,carbon(C) ions with multiple energies and angles were *** samples were further irradiated with low-energy D ions under two fluences at temperatures from ～380 to 640 *** various experimental techniques,we found that pre-damaged W samples can effectively suppress the formation of blistering and lower the threshold temperature at which the surface remains free of *** also observed the prominent D supersaturated peaks within the depth of 20 nm in both pre-damaged and undamaged ***,a close correlation between blistering and the D supersaturation was *** results suggest that neutron irradiation in the fusion reactors could increase the critical D concentration for blistering,while a greater depth of damage facilitated the inward diffusion of D,thereby reducing the D concentration gradient and alleviating surface blistering.

关键词： Tungsten Deuterium Supersaturated layer Blister ion irradiation Pre-damage

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Using fracture-based continuum modeling of coupled geomechanical-hydrological processes for numerical simulation of hydraulic fracturing

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第5期16卷 1582-1599页

作者： Goodluck i.Ofoegbu GNO Modeling Research LLC. San AntonioTX78253USA

This paper describes numerical simulation of hydraulic fracturing using fracture-based continuum modeling(FBCM)of coupled geomechanical-hydrological processes to evaluate a technique for high-density fracturing and fracture *** simulations are innovative because of modeling discrete fractures explicitly in continuum analysis.A key advantage of FBCM is that fracture initiation and propagation are modeled explicitly without changing the domain grid(*** re-meshing).Further,multiple realizations of a preexisting fracture distribution can be analyzed using the same domain *** simulated hydraulic fracturing technique consists of pressurizing multiple wells simultaneously:initially without permeating fluids into the rock,to seed fractures uniformly and at high density in the wall rock of the wells;followed by fluid injection to propagate the seeded fracture density *** combines the ease of continuum modeling with the potential accuracy of modeling discrete fractures and fracturing *** are modeled as piecewise planar based on intersections with domain elements;fracture geometry stored as continuum properties is used to calculate parameters needed to model individual fractures;and rock behavior is modeled through tensorial aggregation of the behavior of discrete fractures and unfractured *** are presented for previously unfractured rock and for rock with preexisting fractures of horizontal,shallow-dipping,steeply dipping,or vertical *** of a single-well model are used to determine the pattern and spacing for a multiple-well *** results illustrate high-density fracturing and fracture caging through simultaneous fluid injection in multiple wells:for previously unfractured rock or rock with preexisting shallow-dipping or horizontal fractures,and in situ vertical compressive stress greater than *** preexisting fractures are steeply dipping or vertical,and considering the same in situ

关键词： Discrete fracture Fracture-based continuum modeling Fracture caging High-density fracturing Hydraulic fracturing Preexisting fracture

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Supramolecular Manipulation of intracellular Acidic Vesicles to improve Cellular Self-Repair and Self-Defense

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CCS Chemistry 2024年第6期6卷 1487-1498页

作者： Ziyi wang Chen Sun Yu Dong Yuan-Fu Ding Chen Zhao ian wa Ho Jiahong Lu Ruibing wang State Key Laboratory of Quality Research in Chinese Medicine Institute of Chinese Medical SciencesUniversity of MacaoTaipaMacao 999078China

Lysosomes are the“cell stomach”that digests various species including macromolecules and pathogens for self-repair and self-defense upon fusion with endosomes,autophagosomes,and ***,artificially manipulating intracellular vesicles could potentially promote lysosome-mediated intracellular digestion for disease prevention and ***,a supramolecular strategy to efficiently tether and fuse acidic vesicles(i.e.,lysosomes,late endosomes,autolysosomes,and phagosomes)has been developed for the first time to enhance the digestion of cellular wastes and foreign matter,including pathogens.A linear polyethylene glycol(PEG)derivative dually tagged with morpholine(MOR)and adamantane(ADA)on the opposite side,namely,MOR-PEG-ADA,was designed to target intracellular acidic vesicles via MOR and to decorate their surfaces with ***,the addition of cucurbit[7]uril(CB[7])grafted hyaluronic acid(HA)induced supramolecular tethering and fusion of acidic vesicles via strong host-guest interactions between CB[7]of CB[7]-HA and ADA residing on the surface of acidic *** a proof-ofconcept,the overall cellular metabolism,including endogenous autophagy and the exogenous endocytosis and phagocytosis,was effectively upregulated,demonstrating that supramolecular regulation of the dynamics of intracellular acidic vesicles may promote the lysosome’s digestion to significantly improve cellular self-repair and self-defense.

关键词： supramolecular chemistry organelle regulation intracellular acidic vesicles lysosomes selfdefense self-repair

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Artificial intelligence system for outcome evaluations of human in vitro fertilization-derived embryos

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中华医学杂志(英文版) 2024年第16期137卷 1939-1949页

作者： Sun Ling Li Jiahui Zeng Simiao Luo Qiangxiang Miao Hanpei Liang Yunhao Cheng Linling Sun Zhuo Tai wa Hou Han Yibing Yin Yun Wu Keliang Zhang Kang Department of Reproductive Medicine Guangzhou Women and Children’s Medical Center Guangzhou Medical University Guangzhou Guangdong China Guangzhou National Laboratory Guangzhou Guangdong China Department of Reproductive Medicine Jiangmen Central Hospital Jiangmen Guangdong China Department of Ophthalmology Dongguan People’s Hospital The First School of Clinical Medicine Southern Medical University Dongguan Guangdong China institute for Artificial intelligence in Medicine Faculty of Medicine Macau University of Science and Technology Macau Special Administrative Region China Wenzhou Eye Hospital Institute for Advanced Studies on Eye Health and Diseases Wenzhou Medical University Wenzhou Zhejiang China Kiang Wu Hospital Macau Special Administrative Region China Faculty of Business City University of Macau Macau Special Administrative Region China State Key Laboratory of Reproductive Medicine and Offspring Health Center for Reproductive Medicine Institute of Women Children and Reproductive Health and Key laboratory of Reproductive Endocrinology of Ministry of Education Shandong University Jinan Shandong China

Background: in vitro fertilization (iVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical iVF practices in iVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos. However, traditional embryo selection methods, primarily reliant on visual inspection of morphology, exhibit variability and are contingent on the experience of practitioners. Therefore, an automated system that can evaluate heterogeneous embryo data to predict the final outcomes of live births is highly ***: We employed artificial intelligence (Ai) for embryo morphological grading, blastocyst embryo selection, aneuploidy prediction, and final live-birth outcome prediction. We developed and validated the Ai models using multitask learning for embryo morphological assessment, including pronucleus type on day 1 and the number of blastomeres, asymmetry, and fragmentation of blastomeres on day 3, using 19,201 embryo photographs from 8271 patients. A neural network was trained on embryo and clinical metadata to identify good-quality embryos for implantation on day 3 or day 5, and predict live-birth outcomes. Additionally, a 3D convolutional neural network was trained on 418 time-lapse videos of preimplantation genetic testing (PGT)-based ploidy outcomes for the prediction of aneuploidy and consequent live-birth ***: These two approaches enabled us to automatically assess the implantation potential. By combining embryo and maternal metrics in an ensemble Ai model, we evaluated live-birth outcomes in a prospective cohort that achieved higher accuracy than experienced embryologists (46.1%vs. 30.7% on day 3, 55.0%vs. 40.7% on day 5). Our results demonstrate the potential for Ai-based selection of embryos based on characteristics beyond the observational abilities of human clinicians (area under the curve: 0.769, 95% confidenc

关键词： Artificial intelligence Fertilizationin vitro Embryo implantation Blastocyst Aneuploidy Neural networks, computer Live birth

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