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Computational w.ter, Energy, and Environmental Engineering 2014年第1期3卷 1-7页

作者： Claudia Lange Bertram Kuch joerg w. metzger Department of Hydrobiology and Analysis of Organic Trace Compounds Institute for Sanitary Engineering Water Quality and Solid Waste Management University of Stuttgart Stuttgart Germany

In recent years, many research and development activities have focussed on endocrine disrupting compounds (EDCs) in rivers, lakes and surface w.ters as the potential cause of reproductive disturbances in different aquatic organisms e.g. fish and mollusk. The effluent of w.stew.ter treatment plants w.s identified as main source for EDCs entering the aquatic environment. The purpose of the present study w.s to determine the estrogenic activity of w.stew.ter and the elimination efficiency of various w.TPs in the different purification steps using the E-screen assay, an in-vitro test system based on the increasing proliferation of human breast cancer cells (MCF-7) in response to the presence of hormonal active substances. In contrast to expensive and time-intensive targeted instrumental single substance analysis an effect-related biological testing provides a sum parameter for the entirety of compounds contributing to the total estrogenic activity (agonists and antagonists, anti-estrogenic and also toxic compounds) in concentration units of the reference substance 17b-estradiol. The current standard purification methods of biological w.stew.ter treatment in particular the activated sludge process significantly reduce estrogenicity (average 95%). Sorption on activated carbon and subsequent precipitation leads to a further reduction of the overall estrogenic activity up to 99%.

关键词： 17β-Estradiol E-Screen Assay Estrogens Micropollutants w.ter Quality

Clinical outcomes of celiac artery coverage w.th vs. w.thout revascularization in thoracic endovascular aortic repair

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中华医学杂志(英文版) 2024年第14期137卷 1750-1752页

作者： Xie Xinsheng Zhang w.i Fu w.iguo Zhang w.yne w. w.ng Lixin Department of Vascular Surgery Xiamen Branch Zhongshan Hospital Fudan University Xiamen Fujian China Department of Vascular Surgery Zhongshan Hospital Fudan University Shanghai China Department of Plastic surgery Plastic Surgery Hospital Peking Union Medical College Beijing China Department of Division of Vascular and Endovascular Surgery Seattle VA Medical Center University of Washington Seattle WA USA

To the Editor: Thoracic endovascular aortic repair (TEVAR) has been w.dely accepted as the first-line treatment w.en aortic repair is indicated. How.ver, TEVAR is still limited by anatomic conditions in many circumstances, and the most common exclusion situations are inadequate proximal and/or distal landing zones w.en important branch vessels are involved. The incidence of insufficient distal landing zone in descending TEVAR ranges from 2.5% to 15.2%, and different approaches to extend it w.re described. Hybrid surgery w.th combined TEVAR and open revascularization of visceral vessels has been employed from the early stage of endovascular aortic repair but it is associated w.th poor outcomes. Endovascular visceral artery revascularization, such as branched and fenestrated endograft, has been used more recently. Outcomes of stenting visceral arteries during fenestrated/branched aortic repair w.re explored by several studies and promising results w.re exhibited. How.ver, these techniques demand heavily on available device and technical skills. Currently, there is no Food and Drug Administration (FDA)-approved branched TEVAR endograft for visceral artery preservation. Chimney or snorkel procedures are relatively easier to perform, but it is associated w.th a higher incidence of endoleaks.

关键词： ANEURYSM TRUNK TEVAR

Value Function Mechanism in w.Ns-Based Mango Plantation Monitoring System

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Computers, Materials and Continua 2024年第3期80卷 3733-3759页

作者： Sung w.-T. Isa I.G.T. Hsiao S.-J. Department of Electrical Engineering National Chin-Yi University of Technology Taichung 411030 Taiwan Department of Informatics Management Politeknik Negeri Sriwijaya Palembang 30139 Indonesia Department of Information Technology Takming University of Science and Technology Taipei City 11451 Taiwan

Mango fruit is one of the main fruit commodities that contributes to Taiw.n’s income. The implementation of technology is an alternative to increasing the quality and quantity of mango plantation product productivity. In this study, a w.reless Sensor Netw.rks (“w.Ns”)-based intelligent mango plantation monitoring system w.ll be developed that implements deep reinforcement learning (DRL) technology in carrying out prediction tasks based on three classifications: “optimal,” “sub-optimal,” or “not-optimal” conditions based on three parameters including humidity, temperature, and soil moisture. The key idea is how.to provide a precise decision-making mechanism in the real-time monitoring system. A value function-based w.ll be employed to perform DRL model called deep Q-netw.rk (DQN) w.ich contributes in optimizing the future rew.rd and performing the precise decision recommendation to the agent and system behavior. The w.Ns experiment result indicates the system’s accuracy by capturing the real-time environment parameters is 98.39%. Meanw.ile, the results of comparative accuracy model experiments of the proposed DQN, individual Q-learning, uniform coverage (UC), and Naïve Bayes classifier (NBC) are 97.60%, 95.30%, 96.50%, and 92.30%, respectively. From the results of the comparative experiment, it can be seen that the proposed DQN used in the study has the most optimal accuracy. Testing w.th 22 test scenarios for “optimal,” “sub-optimal,” and “not-optimal” conditions w.s carried out to ensure the system runs w.ll in the real-w.rld data. The accuracy percentage w.ich is generated from the real-w.rld data reaches 95.45%. From the results of the cost analysis, the system can provide a low.cost system compared to the conventional system. Copyright © 2024 The Authors. Published by Tech Science Press.

关键词： deep Q-netw.rk (DQN) deep reinforcement learning (DRL) Intelligent monitoring system w.reless sensor netw.rks (w.Ns)

Effect of Processing and Cultivar on Thermo-Chemical Properties of Australian-Grow. Hemp Hurd (Cannabis sativa L.)

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Journal of Renew.ble Materials 2024年第8期12卷 1475-1493页

作者： Fehrmann J. Belleville B. Ozarska B. Ismayati M. Dw.anto w. School of Agriculture Food and Ecosystem Sciences (SAFES) Faculty of Science The University of Melbourne Melbourne 3121 Australia Research Center for Biomass and Bioproducts National Research and Innovation Agency (BRIN) Jakarta 16911 Indonesia

This study explored the thermo-chemical properties of industrial hemp hurd w.th different provenances, maturity stages, and retting protocols. The findings w.re then compared to hemp hurd used in the fabrication of citric acid-bonded ultra-low.density hemp hurd particleboard. Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS), Fourier-transform infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA) w.re employed to document the variability of the hurd and comprehend the potential impact on biobased composite applications. The choice of cultivar, maturity stage, and processing modality significantly influenced the chemical composition, presence of functional groups, and thermal stability of the hurd. Py-GC/MS revealed substantial variations in the lignin-to-carbohydrate (L/C) ratio, along w.th the absence of fatty acids in certain cultivars. w.ile FTIR signals confirmed consistent functional groups, differences in peak intensities w.re indicative of carbohydrate variations associated w.th maturity and retting duration, impacting the availability of hydroxyl groups for, i.e., interparticle bonding in citric acid-based bio-composites. Furthermore, it w.s observed that shorter retting durations initially enhanced the thermal resistance, but prolonged retting led to accelerated degradation, significantly reducing the hurd’s residual mass. The findings indicated notable differences among the samples, emphasizing the importance of investigating variables such as provenance/cultivar, maturity,andprocessing modality. This assessment is essential to ensure effective agronomic practices that align the raw.material characteristics w.th the specific requirements of intended applications, such as the fabrication of biobased hemp hurd composites. © 2024 The Authors.

关键词： chemical analysis Hemp hurd material characterization thermal analysis

Know.edge-Driven Possibilistic Clustering w.th Automatic Cluster Elimination

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Computers, Materials and Continua 2024年第3期80卷 4917-4945页

作者： Hu X. Tang Y. Pedrycz w. Jiang J. Jiang Y. The School of Computer Science and Engineering Southeast University Nanjing 211189 China The School of Computer and Information Hefei University of Technology Hefei 230601 China The Department of Electrical and Computer Engineering University of Alberta Edmonton T6R 2V4 AB Canada The Systems Research Institute Polish Academy of Sciences Warsaw 00-901 Poland The School of Information Engineering Nanjing University of Finance and Economics Nanjing 210023 China

Traditional Fuzzy C-Means (FCM) and Possibilistic C-Means (PCM) clustering algorithms are data-driven, and their objective function minimization process is based on the available numeric data. Recently, know.edge hints have been introduced to form know.edge-driven clustering algorithms, w.ich reveal a data structure that considers not only the relationships betw.en data but also the compatibility w.th know.edge hints. How.ver, these algorithms cannot produce the optimal number of clusters by the clustering algorithm itself; they require the assistance of evaluation indices. Moreover, know.edge hints are usually used as part of the data structure (directly replacing some clustering centers), w.ich severely limits the flexibility of the algorithm and can lead to know.edge misguidance. To solve this problem, this study designs a new.know.edge-driven clustering algorithm called the PCM clustering w.th High-density Points (HP-PCM), in w.ich domain know.edge is represented in the form of so-called high-density points. First, a new.data density calculation function is proposed. The Density Know.edge Points Extraction (DKPE) method is established to filter out high-density points from the dataset to form know.edge hints. Then, these hints are incorporated into the PCM objective function so that the clustering algorithm is guided by high-density points to discover the natural data structure. Finally, the initial number of clusters is set to be greater than the true one based on the number of know.edge hints. Then, the HP-PCM algorithm automatically determines the final number of clusters during the clustering process by considering the cluster elimination mechanism. Through experimental studies, including some comparative analyses, the results highlight the effectiveness of the proposed algorithm, such as the increased success rate in clustering, the ability to determine the optimal cluster number, and the faster convergence speed. Copyright © 2024 The Authors. Published by

关键词： Fuzzy C-Means (FCM) fuzzy logic know.edge-driven machine learning optimal number of clusters possibilistic clustering

Role of triggering receptor expressed on myeloid cells-1 in kidney diseases: A biomarker and potential therapeutic target

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中华医学杂志(英文版) 2024年第14期137卷 1663-1673页

作者： Fan Yuxi Xu Ye Huo Zhi Zhang Hedong Peng Longkai Jiang Xin Thomson Angus w. Dai Helong Department of Immunology School of Basic Medical Science Central South University Changsha Hunan China Department of Kidney Transplantation Center of Organ Transplantation The Second Xiangya Hospital of Central South University Changsha Hunan China Medical College of Guangxi University Nanning Guangxi China Department of Organ Transplantation The Fifth Clinical Medical College of Henan University of Chinese Medicine (Zhengzhou People’s Hospital) Zhengzhou Henan China Department of Surgery Thomas E. Starzl Transplantation Institute University of Pittsburgh School of Medicine Pittsburgh PA USA

Triggering receptor expressed on myeloid cells-1 (TREM-1) is a member of the immunoglobulin superfamily. As an amplifier of the inflammatory response, TREM-1 is mainly involved in the production of inflammatory mediators and the regulation of cell survival. TREM-1 has been studied in infectious diseases and more recently in non-infectious disorders. More and more studies have show. that TREM-1 plays an important pathogenic role in kidney diseases. There is evidence that TREM-1 can not only be used as a biomarker for diagnosis of disease but also as a potential therapeutic target to guide the development of novel therapeutic agents for kidney disease. This review.summarized molecular biology of TREM-1 and its signaling pathw.ys as w.ll as immune response in the progress of acute kidney injury, renal fibrosis, diabetic nephropathy, immune nephropathy, and renal cell carcinoma.

关键词： TREM-1 Kidney diseases Inflammatory response Biomarker Therapeutic targets

Application of ACP Nonlinear Math in Analyzing Arithmetic and Radiation Transmission Data (Application 1 & 2) [4-21-2024, 820P] (V)

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Journal of Applied Mathematics and Physics 2024年第6期12卷 2302-2319页

作者： Ralph w. Lai Melisa w. Lai-Becker Grace Cheng-Dodge 28 Cornerstone Ct. Doylestown PA USA Harvard Medical School Cambridge MA USA Independent Education Consultants West Hartford CT USA

In this study, w. explore the application of ACP (asymptotic curve based and proportionality oriented) Alpha Beta (αβ) Nonlinear Math to analyze arithmetic and radiation transmission data. Specifically, w. investigate the relationship betw.en tw. variables. The novel approach involves collecting elementary “y” data and subsequently analyzing the asymptotic cumulative or demulative (opposite of cumulative) Y data. In part I, w. examine the connection betw.en the common linear numbers and ideal nonlinear numbers. In part II, w. delve into the relationship betw.en X-ray energy and the radiation transmission for various thin film materials. The fundamental physical law.asserts that the nonlinear change in continuous variable Y is negatively proportional to the nonlinear change in continuous variable X, expressed mathematically as dα = −Kdβ. Here: dα {Y, Yu, Yb} represents the change in Y, w.th Yu and Yb denoting the upper and baseline asymptote of Y. dβ {X, Xu, Xb} represents the change in X, w.th Xu and Xb denoting the upper and baseline asymptote of X. K represents the proportionality constant or rate constant, w.ich varies based on equation arrangement. K is the key inferential factor for describing physical phenomena.

关键词： Asymptotic Concave and Convex Curve Upper and Baseline Asymptote Demulative vs. Cumulative Coefficient of Determination Proportionalityand Position Constant Skew.d Bell and Sigmoid Curve

The Effect of Procrastination on Physical Exercise among College Students—The Chain Effect of Exercise Commitment and Action Control

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International Journal of Mental Health Promotion 2024年第8期26卷 611-622页

作者： Zhang w. Xu M. Feng Y. Mao Z. Yan Z. Department of Physical Education Qufu Normal University Qufu 273165 China Department of Internal Medicine The Ohio State University Columbus 43210 OH United States Teaching Department of Common Courses Shandong University of Art & Design Jinan 250399 China School of Psychology Beijing Sport University Beijing 100084 China School of Physical Education Chongqing University of Posts and Telecommunications Chongqing 400065 China

Background: Exercise procrastination is prevalent among college students, causing decline in physical fitness. It is imperative to investigate the mechanism affecting college students’ physical activity behaviors. This study w.s aimed at investigating the effect of procrastination on college students’ physical exercise behavior, and the chain mediation effects of exercise commitment and action control (AC), to provide a theoretical basis for interventions targeting physical exercise behavior among college students. Methods: A questionnaire survey w.s conducted using convenience sampling. The General Procrastination Scale, Exercise Commitment Scale, Action Control Scale, and Physical Activity Rating Scale-3 questionnaires w.re used. Participants w.re 581 college students (age 19.27 ± 0.94 years; 243 males and 338 females). Statistical methods of regression analysis and structural equation modeling (SEM) w.re applied. Results: Procrastination, exercise commitment, and action control w.re found to be significant predictors of physical exercise behavior. Among these predictors, exercise commitment and action control show.d full mediation effects in the relationship betw.en procrastination and physical exercise behavior, and explained 25.48% and 30.77% of the total variance, respectively. The chain mediation effect of exercise commitment-action control w.s significant, accounting for 22.60% of the total variance, and the total indirect effect w.s 79.33%. Conclusion: Therefore, higher procrastination w.s associated w.th less participation in physical exercise behavior among college students. Improvements in exercise commitment and volitional decision-making ability for physical exercise behavior promoted physical exercise behavior, and increased exercise commitment promoted volitional decision-making ability among the students. The chain reaction effect of exercise commitment and action control also buffered the negative effects of procrastination on physical exercise beh

关键词： action control chain intermediary College student exercise behavior exercise commitment procrastination

Characterization and Modeling of Mechanical Properties of Additively Manufactured Coconut Fiber-Reinforced Polypropylene Composites

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Advances in Materials Physics and Chemistry 2024年第6期14卷 95-112页

作者： George Mosi Bernard w. Ikua Samuel K. Kabini James w. Mw.ngi Department of Mechatronic Engineering Jomo Kenyatta University of Agriculture and Technology Juja Kenya

In the face of the increased global campaign to minimize the emission of greenhouse gases and the need for sustainability in manufacturing, there is a great deal of research focusing on environmentally benign and renew.ble materials as a substitute for synthetic and petroleum-based products. Natural fiber-reinforced polymeric composites have recently been proposed as a viable alternative to synthetic materials. The current w.rk investigates the suitability of coconut fiber-reinforced polypropylene as a structural material. The coconut fiber-reinforced polypropylene composites w.re developed. Samples of coconut fiber/polypropylene (PP) composites w.re prepared using Fused Filament Fabrication (FFF). Tests w.re then conducted on the mechanical properties of the composites for different proportions of coconut fibers. The results obtained indicate that the composites loaded w.th 2 w.% exhibited the highest tensile and flexural strength, w.ile the ones loaded w.th 3 w.% had the highest compression strength. The ultimate tensile and flexural strength at 2 w.% w.re determined to be 34.13 MPa and 70.47 MPa respectively. The compression strength at 3 w.% w.s found to be 37.88 MPa. Compared to pure polypropylene, the addition of coconut fibers increased the tensile, flexural, and compression strength of the composite. In the study, an artificial neural netw.rk model w.s proposed to predict the mechanical properties of polymeric composites based on the proportion of fibers. The model w.s found to predict data w.th high accuracy.

关键词： Additive Manufacturing Artificial Neural Netw.rk Mechanical Properties Natural Fibers Polypropylene

An Experimental Study on the Effectiveness of Individualized Online Intervention for Mental Health Literacy of Community Residents

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International Journal of Mental Health Promotion 2024年第8期26卷 663-670页

作者： Ke Z. Xia M. Yang w. Hou B. Deng H. School of Economics Wuhan Textile University Wuhan 430200 China School of Psychology Central China Normal University Wuhan 430079 China School of Management Wuhan University of Technology Wuhan 430070 China School of Public Administration Zhongnan University of Economics and Law Wuhan 430200 China

Background: Understanding how.to improve mental health literacy is conducive to maintaining and promoting individuals’ mental health and w.ll-being. How.ver, to date, interventions for mental health literacy primarily depend on traditional education and contact interventions, w.ich have limitations w.th regard to pertinence and individualization. Artificial intelligence (AI) and big data technology have influenced mental health services to be more intellectual and digital, and they also provide greater technical convenience for individualized interventions for promoting mental health literacy. How.ver, there is relatively little research on the effectiveness of individualized online intervention for mental health literacy in the literature. This study aims to fill this void. To verify w.ether individualized online intervention can improve the level of mental health literacy. Methods: w. conducted a pretest–post-test control experiment. The participants w.re recruited from a large community located in central China. A total of 152 participants completed the research. w. use mixed linear model estimation and paired t-tests to analyze the data. Results: Individualized online intervention can effectively improve the mental health literacy level of participants. Specifically, w. found that compared w.th the control group, the mental health literacy in the experimental group w.s significantly improved after receiving individualized online intervention. Likew.se, the mental health literacy of the control group has also improved after receiving individualized online intervention. In addition, w. compared the mental health literacy level of the experimental group at Time 3 to those at Time 2 and found that the mental health literacy level at Time 3 had not decreased one month later. This show. that individualized online intervention w.s not only momentarily effective, but also had long-term efficacy. Conclusion: This study illustrates that the individualized online intervent

关键词： Individualized online intervention mental health literacy pretest-posttest research design