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Multifaceted Disparities Associated with Translator Earnings: A Quantitative Study of Upwork Profiles

Journal of Social Computing 2024年第1期5卷 88-100页

作者： Tyler Horan Data Analytics and Computational Social Science Program University of Massachusetts AmherstAmherstMA 01003USA

This study aims to quantitatively explore the multifaceted determinants that influence earnings in the translation *** a dataset comprising 45000 translator profiles,the study focusses on delineating disparities correlated with demographic variables such as age,gender,home country wealth,and language *** study uses a random forest regression model to delineate the complex interaction between gender,the economic standing of a translator’s domicile country,age,and linguistic proficiency,as they relate to *** findings substantiate and,in many ways,extend existing qualitative and anecdotal evidence that has shaped the discourse in this *** rigorous empirical framework employed here can be replicated or adapted to study other sectors within the gig economy,thus contributing to a more comprehensive understanding of labour dynamics in the digital age.

关键词： translation online employment gig economy intercultural communication

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Assessment of CYP2D6 gene expression in liver tissue: Variability in CYP2D6 mRNA levels within genotype-predicted metabolizer phenotype groups

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Chemico-Biological Interactions 2025年 416卷

作者： Meaddough, Erika L. Sarasua, Sara M. Kunkel, Deborah Boccuto, Luigi Ganakammal, Satishkumar R. Moersen, Matt Farrell, Christopher L. School of Nursing Healthcare Genetics & Genomics Program College of Behavioral Social and Health Sciences Clemson University Clemson SC United States School of Mathematical and Statistical Sciences College of Science Clemson University Clemson SC United States Research Computing & Data Clemson Computing and Information Technology Clemson University Clemson SC United States

Pharmacogenetic (PGx) testing can be used to help guide drug therapy and decrease or avoid the risk of adverse drug reactions. CYP2D6 is an important pharmacogene in pharmacogenomics testing panels. However, phenoconversion, whereby an individual's ability to metabolize a drug does not match the genotype-predicted metabolizer status, is a confounding factor to the accurate application of PGx testing results to patient care. To address this issue, CYP2D6 expression between and within genotype-predicted CYP2D6 metabolizer phenotype groups was compared using WGS and RNA-Seq data from 134 normal liver tissue donors obtained from the GTEx program. Wide variability in CYP2D6 mRNA levels was observed within metabolizer phenotype groups. The median expression level for ultrarapid metabolizers (UMs) was 738.9 TPM (transcripts per million;196.8–778.9 TPM), 212.5 TPM (32.1–666.5 TPM) for normal metabolizers (NMs), 219.6 TPM for intermediate metabolizers (IMs) (22–389.8 TPM), and 121.2 TPM for poor metabolizers (PMs) (9.3–298.2 TPM). The PM and UM phenotypes were significant predictors of CYP2D6 expression (p = 0.0004 and p = 0.019, respectively). Interestingly, expression of the gene encoding human serum albumin (ALB) was also a significant predictor of CYP2D6 expression (p = 0.0003). data from 50 patients with hepatocellular carcinoma obtained from the TCGA program showed no significant difference in expression between tumor tissue (median = 119.7 TPM, range 0.16–817.7 TPM) and normal matched tissue (median = 143.3 TPM, range 26.2–810.7 TPM). Transcriptional regulation of CYP2D6 expression may contribute to differences in drug response and risk for CYP2D6 phenoconversion. Efforts to understand the role of gene expression to predict CYP2D6 phenoconversion may inform the use of PGx testing in the clinical setting. © 2025 The Authors

关键词： CYP2D6 Drug-metabolizing enzymes Gene expression Hepatocellular carcinoma Metabolizer phenotype Pharmacogenetics Phenoconversion

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Exploiting CotA laccase from Antarctic Bacillus sp. PAMC28748 for efficient mediator-assisted dye decolorization and ABTS regeneration

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Chemosphere 2025年 372卷 144137页

作者： Karmacharya, Jayram Shrestha, Prasansah Han, So-Ra Lee, Jun Hyuck Oh, Tae-Jin Department of Life Science and Biochemical Engineering SunMoon University Asan31460 Korea Republic of Genome-based Bio-IT Convergence Institute Asan31460 Korea Republic of Bio Big Data-based Chungnam Smart Clean Research Leader Training Program SunMoon University Asan31460 Korea Republic of Division of Life Sciences Korea Polar Research Institute Incheon21990 Korea Republic of Department of Pharmaceutical Engineering and Biotechnology SunMoon University Asan31460 Korea Republic of

Laccases are of particular interest in addressing environmental challenges, such as the degradation of triphenylmethane (TPM) dyes, including crystal violet (CV) and Coomassie Brilliant Blue (CBB), which are commonly used in SDS-PAGE for protein visualization. However, these dyes present significant environmental concerns due to their resistance to degradation, which makes their removal from industrial wastewater a major challenge. To address this, the current study investigates the potential of a novel CotA laccase derived from Bacillus sp. PAMC28748, an Antarctic bacterial isolate, for decolorizing these stubborn dyes. The CotA gene was successfully cloned and expressed, and the enzyme demonstrated optimal activity at pH 3 and 50 °C, which favors its maximum catalytic performance. The recombinant Bacillus sp. PAMC28748 rBCLac effectively decolorized CBB without additional mediators, whereas the degradation of CV required the use of the redox mediator ABTS. With ABTS, over 90 % decolorization was achieved at a 0.35 % concentration of CV after 240 min of incubation. Further investigation through molecular docking studies revealed that hydrogen bonding and hydrophobic interactions between the enzyme and the dye molecules are critical for effective degradation, highlighting the enzyme's specific interaction mechanisms. In addition to its catalytic effectiveness, the study also demonstrated the practical potential of the rBCLac system by recovering and reusing both ABTS and rBCLac through ultracentrifugation and acetone precipitation. The process maintained over 75 % efficiency across three cycles, despite a slight decline in enzyme activity, thus showcasing the system's sustainability and reusability. These findings collectively suggest that rBCLac, isolated from an extreme Antarctic environment, holds considerable promise as a candidate for the removal of industrial wastewater containing persistent dyes, with the added potential for cost-effective and sustainable wat

关键词： Hydrogen bonds

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Knowledge and information management: Is it possible to do interesting and important research, get funded, be useful and appreciated? 02

Knowledge and information management: Is it possible to do i...

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Proceedings of the Eleventh International Conference on Information and Knowledge Management (CIKM 2002)

作者： Zemankova, Maria Information and Data Management Program National Science Foundation

ISBN: (纸本)9781581134926

The survey of the CIKM Call for Papers for the period 1998-2002 demonstrates that the CIKM organizers very accurately "identify challenging problems facing the development of future knowledge and information systems [in] applied and theoretical research" and also play an important role fostering "bridging traditionally separated areas such as databases and information retrieval, or those that apply techniques from one area to another". The presented CIKM papers also indicate that researchers work on interesting problems. This paper discusses some additional research topics for future consideration by the CIKM community.

关键词： Information management

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Crack Catcher AI — Enabling Smart Fracture Mechanics Approach for Damage Control in Thin Silicon Wafers for 3D Semiconductor Integrated Devices/Packages

Crack Catcher AI — Enabling Smart Fracture Mechanics Approa...

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Annual International Symposium on Reliability Physics

作者： Gabriel Preston Greer Gonzolez Andrea S. Karnyoto Fitya S. Mozar Matthew M. Henry Mahmud Isnan Kuncahyo S. Nugroho Henry Candra Muhamad Doris Dianing N. N. Putri Tyas K Sari Bens Pardamean Endang Djuana Derrric Speaks Arief S. Budiman Oregon Renewable Energy Center (OREC) Oregon Institute of Technology (Oregon Tech) Klamath Falls OR USA Dept. of Manufacturing & Mechanical Eng. & Tech. (MMET) Oregon Institute of Technology Klamath Falls OR USA Bioinformatics & Data Science Research Center (BDSRC) Bina Nusantara University Jakarta Indonesia Computer Sci. Dept. BINUS Grad. Program - Master of Computer Sci. Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Center for Artificial Intelligence and Advanced Technology (CAPTIVATE) Universitas TRISAKTI Jakarta Indonesia Department of Electrical Engineering Faculty of Industrial Technology Universitas TRISAKTI Jakarta Indonesia Industrial Eng. Dept. BINUS Grad. Program – Master of Industrial Eng. Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

The importance of silicon cannot be undermined - in photovoltaics (PV) as well as in semiconductor industries. However, silicon is very brittle. Silicon cells/wafers crack easily during manufacturing assembly and/or during device operations. Crack Catcher AI uses novel smart fracture mechanics approach with Artificial Intelligence (AI) methodologies to predict and control crack/damage evolution in thin silicon cells/wafers. This is critical as semiconductor 3D integration technology calls for wafer-to-wafer bonding with utmost alignment accuracy and yield/reliability.

关键词： Semiconductor device measurement Three-dimensional displays Accuracy Semiconductor device reliability Silicon Artificial intelligence Bonding Stress Three-dimensional integrated circuits Stress measurement

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Bayesian Parameter Estimation for Partially Observed McKean-Vlasov Diffusions Using Multilevel Markov chain Monte Carlo

arXiv

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arXiv 2025年

作者： Jasra, Ajay Wu, Amin School of Data Science The Chinese University of Hong Kong Shenzhen Shenzhen China Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this article we consider Bayesian estimation of static parameters for a class of partially observed McKean-Vlasov diffusion processes with discrete-time observations over a fixed time interval. This problem features several obstacles to its solution, which include that the posterior density is numerically intractable in continuous-time, even if the transition probabilities are available and even when one uses a time-discretization, the posterior still cannot be used by adopting well-known computational methods such as Markov chain Monte Carlo (MCMC). In this paper we provide a solution to this problem by using new MCMC algorithms which can solve the aforementioned issues. This MCMC algorithm is extended to use multilevel Monte Carlo (MLMC) methods. We prove convergence bounds on our parameter estimators and show that the MLMC-based MCMC algorithm reduces the computational cost to achieve a mean square error versus ordinary MCMC by an order of magnitude. We numerically illustrate our results on two models. Copyright © 2025, The Authors. All rights reserved.

关键词： Channel estimation

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VeriFact: Verifying Facts in LLM-Generated Clinical Text with Electronic Health Records

arXiv

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arXiv 2025年

作者： Chung, Philip Swaminathan, Akshay Goodell, Alex J. Kim, Yeasul Reincke, S. Momsen Han, Lichy Deverett, Ben Sadeghi, Mohammad Amin Ariss, Abdel-Badih Ghanem, Marc Seong, David Lee, Andrew A. Coombes, Caitlin E. Bradshaw, Brad Sufian, Mahir A. Hong, Hyo Jung Nguyen, Teresa P. Rasouli, Mohammad R. Kamra, Komal Burbridge, Mark A. McAvoy, James C. Saffary, Roya Ma, Stephen P. Dash, Dev Xie, James Wang, Ellen Y. Schmiesing, Clifford A. Shah, Nigam Aghaeepour, Nima Department of Anesthesiology Perioperative and Pain Medicine Stanford Medicine United States Department of Biomedical Data Science Stanford Medicine United States Department of Pediatrics Stanford Medicine United States Department of Medicine Stanford Medicine United States Department of Emergency Medicine Stanford Medicine United States Immunology Program Stanford Medicine United States Medical Scientist Training Program Stanford Medicine United States Clinical Excellence Research Center Stanford Medicine United States Technology and Digital Solutions Stanford Health Care United States

Methods to ensure factual accuracy of text generated by large language models (LLM) in clinical medicine are lacking. VeriFact is an artificial intelligence system that combines retrieval-augmented generation and LLM-as-a-Judge to verify whether LLM-generated text is factually supported by a patient’s medical history based on their electronic health record (EHR). To evaluate this system, we introduce VeriFact-BHC, a new dataset that decomposes Brief Hospital Course narratives from discharge summaries into a set of simple statements with clinician annotations for whether each statement is supported by the patient’s EHR clinical notes. Whereas highest agreement between clinicians was 88.5%, VeriFact achieves up to 92.7% agreement when compared to a denoised and adjudicated average human clinician ground truth, suggesting that VeriFact exceeds the average clinician’s ability to fact-check text against a patient’s medical record. VeriFact may accelerate the development of LLM-based EHR applications by removing current evaluation bottlenecks. © 2025, CC BY.

关键词： Electronic health record

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Operative estimation of global horizontal irradiance using transfer functions through network types of artificial neural network in some selected sites in North-East Ethiopia: assessment and comparison

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Heliyon 2025年第10期11卷

作者： Woldegiyorgis, Tegenu Argaw Assamnew, Abera Debebe Benti, Natei Ermias Desalegn, Gezahegn Assefa Anose, Fikru Abiko Mossie, Sentayehu Yigzaw Department of Physics College of Natural Sciences Wollo University P.O. Box 1145 Dessie Ethiopia Computational Data Science Program College of Natural and Computational Sciences Addis Ababa University P. O. Box 1176 Addis Ababa Ethiopia Department of Physics College of Natural and Computational Sciences Wolkite University Wolkite Ethiopia

The estimation of global horizontal irradiance (GHI) for a specific location is crucial to the design, modeling, and effective operation of photovoltaic (PV) and solar thermal energy conversion systems. This study aims to predict the monthly average daily and monthly average GHI for three locations in Ethiopia (Kemissie, Haik, and Woldiya) using artificial neural networks (ANNs) with various activation functions. Days of the year, elevation, and average values (maximum and minimum temperatures, surface pressure, wind speed, relative humidity, wind direction, and precipitation) were fed into the ANN during training. For the prediction of monthly average daily GHI, the CFBP-tansig, FFBP-tansig, and FFBP-logsig networks proved to be the most accurate. Likewise, for monthly average GHI prediction, the FFBP-tansig, CFBP-tansig, and LR-tansig networks exhibited the best performance. The daily and monthly GHI predictions achieved RMSE values ranging from 0.00058 to 0.04042, with correlation coefficients (r) between 0.95417 and nearly 1.0. In comparison, traditional methods showed RMSE values between 0.1 and 0.2, indicating that the ANN models provided up to 80 % better accuracy. The EBP-purelin, CFBP-purelin, and LR-purelin models were less effective, with RMSE values between 0.13815 and 0.17307, and r from 0.91153 to 0.96719. Among the studied locations, Kemissie exhibited the highest GHI potential, emphasizing the region's significant capability for solar energy generation in Ethiopia. © 2025 The Authors

关键词： Activation function Artificial neural network Global horizontal irradiance Network types Prediction

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Uncovering Sentiments Expressed on GPT in Academic Papers 17

Uncovering Sentiments Expressed on GPT in Academic Papers

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17th International Conference on Open Source Systems and Technologies, ICOSST 2023

作者： Hong, Alicia Nwoji, Stanley C Murungi, Joyce K. Tatikonda, Pavan K. Kaluvakolli, Anandhakumar Harrisburg University of Science and Technology Data Science Program HarrisburgPA United States

ISBN: (纸本)9798350381320

The growing hype surrounding GPT models has generated both fear and excitement, with concerns about job replacement and admiration for its capabilities. This study investigated the prevailing sentiments within the academic field. The paper aimed to conduct a more comprehensive and objective analysis focusing on academia. We conducted sentiment analysis on a corpus of both peer-reviewed and preprinted article abstracts published between January 2022 and March 2023 to determine the early prevailing sentiments toward GPT models. We collected and processed 400+academic papers on GPT models, extracting the abstracts and keywords to gain insights into authors' perspectives. The study focused on identifying these articles' positive, negative, and neutral sentiments. The study considered various approaches, including RoBERTa, and traditional Machine Learning models such as Naïve Bayes, Random Forest, and Support Vector Machine, to analyze the collected data and compare performance results. The results demonstrated that the predominant sentiments expressed in scholarly paper abstracts toward GPT models are neutral (60.2% of the sample), instead of polarized. This observation holds even when the confidence score of the model output is limited to $\gt0.5$. The significance of this study lies in its novelty, as limited articles have examined these sentiments. Understanding the various sentiments expressed in scholarly discourse on GPT models can contribute to further research on the ethical implications of generative AI. © 2023 IEEE.

关键词： Sentiment analysis

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