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Low-to-Moderate Arsenic Exposure and Urothelial Tract Cancers with a Long Latent Period of Follow-Up in an Arseniasis Area

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Journal of Epidemiology and Global Health 2023年第4期13卷 807-815页

作者： Liao, Pei-Ju Lee, Chih-Hung Wang, Shu-Li Chiou, Hung-Yi Chen, Chien-Jen Seak, Chen-June Wu, I-Wen Hsu, Kuang-Hung International Program of Health Informatics and Management Chang Gung University Taoyuan Taiwan Master Degree Program in Health and Long-Term Care Industry Chang Gung University Taoyuan Taiwan Division of Nephrology Chang Gung Memorial Hospital Keelung Taiwan Department of Dermatology Kaohsiung Chang Gung Memorial Hospital Kaohsiung Taiwan National Institute of Environmental Health Sciences National Health Research Institutes Miaoli Taiwan Institute of Population Health Sciences National Health Research Institutes Zhunan Miaoli County Taiwan Master Program in Applied Epidemiology College of Public Health Taipei Medical University Taipei Taiwan Genomics Research Center Academia Sinica Taipei Taiwan Department of Emergency Medicine New Taipei Municipal Tucheng Hospital New Taipei City Taiwan Department of Emergency Medicine Lin-Kou Medical Center Chang Gung Memorial Hospital Taoyuan Taiwan College of Medicine Chang Gung University Taoyuan Taiwan Laboratory for Epidemiology Department of Health Care Management and Healthy Aging Research Center Chang Gung University No. 259 Wen-Hwa 1St Road Kwei-Shan Taoyuan 333 Taiwan Research Center for Food and Cosmetic Safety College of Human Ecology Chang Gung University of Science and Technology Taoyuan Taiwan Department of Safety Health and Environmental Engineering Ming Chi University of Technology New Taipei City Taiwan

Background: Arsenic exposure can cause adverse health effects. The effects of long-term low-to-moderate exposure and methylations remain unclear. Objective: This study aims to examine the association between low-to-moderate arsenic exposure and urothelial tract cancers while considering the effects of methylation capacity. Methods: In this study, 5,811 participants were recruited from an arseniasis area in Taiwan for inorganic arsenic metabolite analysis. This follow-up study was conducted between August 1995 and December 2017. We identified 85 urothelial tract cancers in these participants, including 49 bladder and 36 upper urothelial tract cancer cases. A Cox proportional hazards model was employed. Results: The analyses revealed a significant association between concentrations of inorganic arsenic in water > 100 ug/L and bladder cancer occurrence, with a hazard ratio (HR) of 4.88 (95% CI 1.35–17.61). A monotonic trend was observed between concentrations of inorganic arsenic in water (from 0 to > 100 ug/L) and the incidence of urothelial tract cancer, including bladder cancer (p < 0.05) and upper urothelial tract cancers (p < 0.05). Participants with a lower primary methylation index or higher secondary methylation index had a prominent effect. Conclusions: Rigorous regulations and active interventions should be considered for populations with susceptible characteristics. © 2023, The Author(s).

关键词： Bladder cancer Dose–response relationship Long latency arsenic exposure Methylation capacity Upper urothelial tract cancers

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Multimodal Sentiment Analysis using Kernel Based Support Vector Machine

Multimodal Sentiment Analysis using Kernel Based Support Vec...

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Advanced Technologies in Intelligent Control, Environment, Computing & Communication engineering (ICATIECE), International Conference on

作者： V Sunil Kumar Piyush Kumar Pareek Victor Hugo Costa De Albuquerque Ashish Khanna Deepak Gupta Madhumala R B Department Artificial Intelligence & Machine Learning Nitte Meenakshi Institute of Technology Bengaluru Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceará Fortaleza Brazil Department of Teleinformatics Engineering Federal University of Ceará Brazil CSE Dept Maharaja Agrasen Institute of Technology GGSIPU Department of ISE Dayananda Sagar Academy of Technology and Management Bangalore

ISBN: (纸本)9781665493970

There has been a steady expansion in the number of social websites, electronic media outlets, and blogging services, all of which contribute a large number of user messages such as comments, reviews, and opinions from customers. The quantity of these signals, which are used to evaluate the quality of a wide variety of goods and services, is rather substantial. As a result, it is challenging to monitor and identify the feelings of customers. As a result, a method known as Sentiment Analysis (SA), also known as Opinion Mining (OM), was developed. This method gathers data from the internet by using Natural Language Processing (NLP) strategies and then analyses people's thoughts. It does this by extracting subjective information from the words, assessing opinions, and quantifying positive and negative evaluations. The end result is a conclusion about the specific entity, which may be an organisation, the public, or a product. The NLP first gathers the views, and then those opinions are sorted into positive, neutral, and negative categories. Both the marketing promotion and the customer's ability to choose the most appropriate product for their needs may be improved by doing an analysis. The purpose of this study is to evaluate the use of different machine learning and swarm intelligence optimization methods to perform sentiment analysis on data derived from movie reviews. This study helps many businesses increase their profits while simultaneously lowering the number of problems caused by a certain product. Within the scope of this investigation, three distinct models of sentiment analysis were investigated. An effective method for doing sentiment analysis known as a Hybrid Kernel based Support Vector Machine (HKSVM) has been presented. The preprocessing that is described here is meant to cut down on the data inconsistencies and get rid of the data that isn't needed. After that, the Expectation Maximization (EM) technique is used in order to identify an outlier. After t

关键词： Support vector machines Sentiment analysis Analytical models Sensitivity Veins Tagging Probabilistic logic

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The influence of preparation and pretreatment on the physicochemical properties and performance of plant-based biocoagulants in treating wastewater

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Environmental Advances 2023年 14卷

作者： Kurniawan, Setyo Budi Ahmad, Azmi Said, Nor Sakinah Mohd Gustinasari, Kiki Abdullah, Siti Rozaimah Sheikh Imron, Muhammad Fauzul Laboratory of Algal Biotechnology Centre Algatech Institute of Microbiology of the Czech Academy of Sciences Opatovický mlýn Novohradská 237 Třeboň 379 81 Czech Republic Department of Petrochemical Engineering Politeknik Tun Syed Nasir Syed Ismail Johor Pagoh 84600 Malaysia Department of Chemical and Process Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia (UKM) Selangor Bangi 43600 Malaysia Study Program of Environmental Engineering Department of Biosystem Engineering Faculty of Agricultural Engineering Universitas Brawijaya Malang 65145 Indonesia Study Program of Environmental Engineering Department of Biology Faculty of Science and Technology Universitas Airlangga Kampus C UNAIR Jalan Mulyorejo Surabaya 60115 Indonesia Department of Water Management Faculty of Civil Engineering and Geosciences Delft University of Technology Stevinweg 1 CN Delft 2628 Netherlands

Biocoagulants have gained attention as an alternative to chemical coagulants in water and wastewater treatment due to their ability to remove pollutant parameters such as turbidity, suspended solids, color, and organic compounds. Plant-based biocoagulants are currently the most promising due to their abundant availability and reliable performance. A proper preparation of plant-based biocoagulants is required to ensure the active compounds from the plants can be extracted. Plant raw materials are prepared into biocoagulants using drying and grinding, extraction, and purification. In mechanical preparation, drying and grinding exhibit great influence on the performance of plant-based biocoagulants due to the removal of moisture and higher contact with the carrier medium during dissolution. A smaller biocoagulant's size resulted in up to 78 % higher removal of turbidity. In chemical preparation, the oil needs to be removed before extracting the active ingredients to avoid low active compound extraction yields. The defatting of Moringa oleifera seeds showed an 18 % higher protein content. Salt and alcohol extractions were mentioned as superior extraction methods to obtain carbohydrate and protein from plant-based biocoagulants compared to water extraction, with up to a 5 % increment in turbidity removal. Preparation and pretreatment protocols have a great influence on the properties and performance of plant-based biocoagulants. Further extension of research on plant-based biocoagulants should address the problems in the initial characterization of plant material, standard pretreatment and preparation protocols, and real-scale application of plant-based biocoagulants. © 2023 The Author(s)

关键词： Biocoagulant Coagulant Environmental pollution Extraction Properties Synthesis

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Recover energy and materials from agricultural waste via thermalchemical conversion (vol 5, pg 1200, 2022)

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ONE EARTH 2022年第12期5卷 1404-1404页

作者： Lee, Kuan-Tieng Chen, Wei-Hsin Sarles, Paul Park, Young-Kwon Ok, Yong Sik Department of Aeronautics and Astronautics National Cheng Kung University Tainan 701 Taiwan Research Center for Smart Sustainable Circular Economy Tunghai University Taichung 407 Taiwan Department of Mechanical Engineering National Chin-Yi University of Technology Taichung 411 Taiwan International Master Degree Program on Energy National Cheng Kung University Tainan 701 Taiwan School of Environmental Engineering University of Seoul Seoul 02504 Republic of Korea Korea Biochar Research Center APRU Sustainable Waste Management Program & Division of Environmental Science and Ecological Engineering Korea University Seoul Republic of Korea

Every year, at least 1,300 million tons of agricultural waste is produced, and the amount is likely to expand further in a world with a growing population to feed. Our current linear approach to handling this vast amount of waste via landfills and incineration has already contributed to about 3% of global greenhouse gas emissions and also created various toxic pollutants. There is an urgent need to sustainably manage agricultural waste that can benefit both the environment and humans. Thermochemical conversion emerges as a promising technology that can convert agricultural waste into a variety of valuable products, creating circularity opportunities. In this primer, we explain the thermochemical conversion of agricultural waste by illustrating four mainstreaming processes. We further discuss the potential tradeoffs of these processes in terms of their environmental externalities and reflect upon the potential toward a circular and net-zero future.

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Reconciling regional nitrogen boundaries with global food security (Sep, 10.1038/s43016-021-00366-x, 2021)

NATURE FOOD

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NATURE FOOD 2022年第5期3卷 385-385页

作者： Chang, Jinfeng Havlik, Petr Leclere, David de Vries, Wim Valin, Hugo Deppermann, Andre Hasegawa, Tomoko Obersteiner, Michael College of Environmental and Resource Sciences Zhejiang University Hangzhou China Ecosystems Services and Management Program (ESM) International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria Environmental Systems Analysis Group Wageningen University and Research Wageningen the Netherlands College of Science and Engineering Ritsumeikan University Shiga Japan

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Smart Resource Allocation Advisor in the Cloud for COVID-19 and Other Pandemics

Smart Resource Allocation Advisor in the Cloud for COVID-19 ...

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IEEE Cloud Summit

作者： Ozlem Cosgun Amjad Umar Information Systems Engineering and Management Program Harrisburg University of Science and Technology Harrisburg PA USA

ISBN: (数字)9781728182667

ISBN: (纸本)9781728182674

Deployment of scarce resources is a critical issue for especially large-scale outbreaks of infectious diseases. During the COVID-19 pandemic, healthcare providers are facing the challenges of significant shortages of limited resources such as testing, personal protective equipment (PPE), hospital beds, ICU s, medications and ventilators because of the dramatic increase in the number of patients. Therefore, in this study, we develop “a general smart resource allocation advisor in the cloud” that determines the smart allocation of the scarce resources with respect to the pandemic severity level, from low to very severe, to mitigate and control the spread of the disease. Portfolio model of cost-benefit analysis is used to identify the low cost-high benefit allocations of the resources to focus on more and high cost-low benefit allocations to avoid as well. Therefore, this model provides healthcare providers useful insights about their resource allocations to be more responsive to their patients and control the transmission of the virus.

关键词： COVID-19 Personal protective equipment Pandemics Resource management Viruses (medical) Portfolios Testing

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Setting time and compressive strength of geopolymer concrete with variations in the addition of cement

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AIP Conference Proceedings 2024年第1期3098卷

作者： Yayan Adi Saputro Jati Widagdo Syamsul Arifin Sa’dullah Assa’idi Nimas Aulia Pambajeng Miftahunnajah Abdul Talib Bon Civil Engineering Program Study Faculty of Science and Technology Islamic University of Nahdlatul Ulama Jepara Jepara Indonesia Product Design Program Study Faculty of Science and Technology Islamic University of Nahdlatul Ulama Jepara Jepara Indonesia Management Program Study Faculty of Economics and Business Islamic University of Nahdlatul Ulama Jepara Jepara Indonesia Islamic Education Management Study Program Islamic University of Nahdlatul Ulama Jepara Jepara Indonesia Balekambang Polytechnic Jepara Jepara Indonesia Professor of Technology Management Faculty of Technology Management and Business Universiti Tun Hussein Onn Malaysia Parit Raja Johor Malaysia

The increasing demand for cement in the world of construction can have an extraordinary effect, especially in the production of cement which produces CO2. So we need an alternative material as a substitute and even replace the role of cement. Utilization of coal waste in the form of fly ash is in the spotlight to be maximized. Therefore this research was conducted as an alternative contribution to the solution using geopolymer concrete in terms of setting time and compressive strength with variations in the addition of cement. The method used is experimental in the laboratory which produces qualitative data for further numerical calculations. Tests focused on the setting time and compressive strength of concrete using 5 mix designs with cement variations ranging from 10%, 20%, 30%, 40% of the use of fly ash. The results of the setting time with the highest duration, namely 100% FA=1.5, 95 minutes initial setting time and 225 minutes final setting time, then decreased to the lowest duration, namely 60% FA: Pc 40%=1.5. The initial setting time is 15 minutes and the final setting time is 37 minutes. The highest concrete compressive strength results in the MD 4 mix design with 70% FA mixture: Pc 30%=1.5, which is 43.3 MPa. While the lowest compressive strength is the design mix MD 1 with a mixture of 100% FA=1.5 of 21.8 MPa.

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Industrial ergonomic work design to improve the employee quality of life and productivity at Pt Cita Rasa Palembang

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AIP Conference Proceedings 2023年第1期2680卷

作者： Micheline Rinamurti Heri Setiawan Management Study Program Business and Accounting Faculty Musi Charitas Catholic University Palembang Indonesia Industrial Engineering Study Program Science and Technology Faculty Musi Charitas Catholic University Palembang Indonesia

The physical environment of PT Cita Rasa Palembang before it was designed based on industrial ergonomics, it was found that the quality of life of worker was quite heavy and had an impact on productivity which was still not optimal. The main objective of this research is to find out that industrial ergonomic work design can improve the employee quality of life as assessed by decreasing musculoskeletal complaints, fatigue and workload of employees who make Pempek Belida at PT Cita Rasa Palembang, and increase productivity seen from the aspect of the number of Pempek Belida’s sales. This experimental study used a pre and posttest group design, treatment by subjects design and involved 45 samples who were randomly selected stratified with multistage random sampling. The independent variable was the implementation of the results of work design in the form of industrial ergonomic. The dependent variables are (a) the employee quality of life as assessed from indicators of musculoskeletal complaints, fatigue, and workload, and (b) increasing the percentage of employee productivity who make Pempek Belida at PT Cita Rasa Palembang. The data obtained between before and after the implementation of the results of industrial ergonomic work design will be analyzed using paired t test at a significance level of 5% (α=0.05). The results of the research on work design who made Pempek Belida at PT Cita Rasa Palembang through industrial ergonomic which: increased the percentage of employee quality of life significantly (p <0.05) seen from: decreased musculoskeletal complaints by 25.02%; decrease employee fatigue by 20.20%; and decrease in workload by 21.30%; and (b) increasing the percentage of employee productivity by 15.15%

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Overall mortality risk analysis for rectal cancer using deep learning-based fuzzy systems

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Computers in Biology and Medicine 2023年 157卷 106706-106706页

作者： Yang, Cheng-Hong Chen, Wen-Ching Chen, Jin-Bor Huang, Hsiu-Chen Chuang, Li-Yeh Department of Information Management Tainan University of Technology Tainan Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan Department of Internal Medicine Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine Kaohsiung Taiwan Department of Community Health Chia-Yi Christian Hospital Chia-Yi City Taiwan Department of Chemical Engineering & Institute of Biotechnology and Chemical Engineering I-Shou University Kaohsiung Taiwan

Colorectal cancer is a leading cause of cancer mortality worldwide, with an increasing incidence rate in developing countries. Integration of genetic information with cancer therapy guidance has shown promise in cancer treatment, indicating its potential as an essential tool in translation oncology. However, the high-throughput analysis and variability of genomic data poses a major challenge to conventional analytic approaches. In this study, we propose an advanced analytic approach, named "Fuzzy-based RNNCoxPH," incorporated fuzzy logic, recurrent neural networks (RNNs), and Cox proportional hazards regression (CoxPH) for detecting missense variants associated with high-risk of all-cause mortality in rectum adenocarcinoma. The test data set was downloaded from "Rectum adenocarcinoma, TCGA-READ" the Genomic Data Commons (GDC) portal. In this study, four model-based risk score models were derived using RNN, CoxPH, RNNCoxPHAddition, and RNNCoxPHMultiplication. The RNNCoxPHAddition and RNNCoxPHMultiplication models were obtained as the sum and product of the RNN risk degree matrix and the CoxPH risk degree matrix, respectively. Moreover, the fuzzy logic system was used to calculate the survival risk values of missense variants and classified their membership grade to improve the identification of high-risk gene variation locations associated with cancer mortality. The four models were integrated to develop an advanced risk estimation model. There were 20 028 variants associated with survival status, amongst 17 638 variants were associated with survival and 2390 variants associated with mortality. The proposed Fuzzy-based RNNCoxPH model obtained a balanced accuracy of 93.7%, which was significantly higher than that of the other four test methods. In particular, the CoxPH model is commonly used in medical researches and the XGBoost model is famous for its high accuracy in machine learning. The results suggest that the Fuzzy-based RNNCoxPH model exhibits a higher efficacy

关键词： Fuzzy logic

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Automatic rigging of 3D models with stacked hourglass networks and descriptors

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AIP Conference Proceedings 2024年第1期2919卷

作者： Ritika Verma Sarthak Mittal Siddharth Pawar Moolchand Sharma Shalini Goel Victor Hugo C. de Albuquerque Department of Computer Science & Engineering MAIT GGSIPU New Delhi India HMR Institute of Technology and Management New Delhi India Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceará Fortaleza/CE Brazil Department of Teleinformatics Engineering Federal University of Ceará Fortaleza/CE Brazil

We put forward an approach for automated skeleton rigging of 3D point cloud models of segmented characters. Unlike earlier systems that fit predetermined skeleton templates or forecast predetermined sets of joints, our approach generates an animation skeleton that is tuned to the structure and geometry of the input 3D model. Our architecture is built on a stack of hourglass models trained using a large dataset of 3D-rigged characters mined from the web. It works with a volumetric representation of the input 3D shapes enhanced with geometric shape elements that provide different indications for joint and bone positions. The proposed method also allows straightforward user customization of the output skeleton’s level of detail. Our study shows that, compared to many alternatives and baselines, our approach predicts animation skeletons that are significantly more comparable to those made by people.

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