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Bolstering integrity in environmental data science and machine learning requires understanding socioecological inequity

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Frontiers of Environmental Science & Engineering 2024年第5期18卷 171-179页

作者： joe F.Bozeman III School of Civil and Environmental Engineering Georgia Institute of TechnologyAtlantaGA30332USA School of Public Policy Georgia Institute of TechnologyAtlantaGA30332USA

Socioecological inequity in environmental data science—such as inequities deriving from data-driven approaches and machine learning(mL)—are current issues subject to debate and *** is growing consensus around embedding equity throughout all research and design domains—from inception to administration,while also addressing procedural,distributive,and recognitional ***,practically doing so may seem onerous or daunting to *** current perspective helps to alleviate these types of concerns by providing substantiation for the connection between environmental data science and socioecological inequity,using the Systemic Equity Framework,and provides the foundation for a paradigmatic shift toward normalizing the use of equity-centered approaches in environmental data science and mL *** the integrity of environmental data science and mL is just beginning from an equity-centered tool development and rigorous application *** this end,this perspective also provides relevant future directions and challenges by overviewing some meaningful tools and strategies—such as applying the Wells-Du Bois Protocol,employing fairness metrics,and systematically addressing irreproducibility;emerging needs and proposals—such as addressing data-proxy bias and supporting convergence research;and establishes a ten-step path ***,the work that environmental scientists and engineers do ultimately affect the well-being of us all.

关键词： Equity Bias machine Learning Data Science Justice Systemic Equity

Lightweight Super-Resolution model for Complete model Copyright Protection

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Tsinghua Science and Technology 2024年第4期29卷 1194-1205页

作者： Bingyi Xie Honghui Xu YongJoon joe Daehee Seo Zhipeng Cai Department of Computer Science Georgia State UniversityAtlantaGA 30303USA LSWare Inc. Seoul 08504Republic of Korea College of Intelligence Information Engineering Sangmyung UniversityRepublic of KoreaSeoul 03016

Deep learning based techniques are broadly used in various applications, which exhibit superior performance compared to traditional methods. One of the mainstream topics in computer vision is the image super-resolution task. In recent deep learning neural networks, the number of parameters in each convolution layer has increased along with more layers and feature maps, resulting in better image super-resolution performance. In today’s era, numerous service providers offer super-resolution services to users, providing them with remarkable convenience. However, the availability of open-source super-resolution services exposes service providers to the risk of copyright infringement, as the complete model could be vulnerable to leakage. Therefore, safeguarding the copyright of the complete model is a non-trivial concern. To tackle this issue, this paper presents a lightweight model as a substitute for the original complete model in image super-resolution. This research has identified smaller networks that can deliver impressive performance, while protecting the original model’s copyright. Finally, comprehensive experiments are conducted on multiple datasets to demonstrate the superiority of the proposed approach in generating super-resolution images even using lightweight neural networks.

关键词： lightweight adversarial learning image super-resolution copyright protection

Integrins and their potential roles in mammalian pregnancy

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Journal of Animal Science and Biotechnology 2024年第1期15卷 1-19页

作者： Gregory A.Johnson Robert C.Burghardt Fuller W.Bazer Heewon Seo joe W.Cain Department of Veterinary Integrative Biosciences School of Veterinary Medicine and Biomedical SciencesTexas A&M UniversityCollege StationTX 77843‑4459USA Department of Animal Science College of Agriculture and Life SciencesTexas A&M UniversityCollege StationTX 77843‑2471USA

Integrins are a highly complex family of receptors that, when expressed on the surface of cells, can mediate reciprocal cell-to-cell and cell-to-extracellular matrix(ECm) interactions leading to assembly of integrin adhesion complexes(IACs) that initiate many signaling functions both at the membrane and deeper within the cytoplasm to coordinate processes including cell adhesion, migration, proliferation, survival, differentiation, and metabolism. All metazoan organisms possess integrins, and it is generally agreed that integrins were associated with the evolution of multicellularity, being essential for the association of cells with their neighbors and surroundings, during embryonic development and many aspects of cellular and molecular biology. Integrins have important roles in many aspects of embryonic development, normal physiology, and disease processes with a multitude of functions discovered and elucidated for integrins that directly influence many areas of biology and medicine, including mammalian pregnancy, in particular implantation of the blastocyst to the uterine wall, subsequent placentation and conceptus(embryo/fetus and associated placental membranes) development. This review provides a succinct overview of integrin structure, ligand binding, and signaling followed with a concise overview of embryonic development, implantation, and early placentation in pigs, sheep, humans, and mice as an example for rodents. A brief timeline of the initial localization of integrin subunits to the uterine luminal epithelium(LE) and conceptus trophoblast is then presented, followed by sequential summaries of integrin expression and function during gestation in pigs, sheep, humans, and rodents. As appropriate for this journal, summaries of integrin expression and function during gestation in pigs and sheep are in depth, whereas summaries for humans and rodents are brief. Because similar models to those illustrated in Fig. 1, 2, 3, 4, 5 and 6 are present throughout the sc

关键词： Humans Implantation Integrins Pigs Pregnancy Rodents Sheep

Going deep:Roots,carbon,and analyzing subsoil carbon dynamics

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molecular Plant 2024年第1期17卷 1-3页

作者： Ezhilmathi Angela Joseph Fernando michael Selvaraj Yusaku Uga Wolfgang Busch Hunt Bowers joe Tohme Alliance of Bioversity International and CIAT Km 17 Recta Cali-PalmiraAprtado Aereo 6713Cali 763537Colombia National Institute of Agrobiological Sciences(NIAS) TsukubaIbaraki 305-0856Japan Salk Institute for Biological Studies 10010 N Torrey Pines RoadLa JollaCA 92037USA Earth Optics Suite 840ArlingtonVA 22202USA

Agricultural practices currently contribute to the emission of approximately 10%–12%atmospheric greenhouse gasses,with tillage agriculture accelerating soil disruption and carbon dioxide ***,various options exist,such as converting new lands for agriculture,promoting healthier plant-based diets,adopting advanced management technologies,and minimizing food ***,these measures alone are insufficient to ensure environmental sustainability within planetary boundaries.

关键词： soil measures carbon

The new era of cardiovascular research:revolutionizing cardiovascular research with 3D models in a dish

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medical Review 2024年第1期4卷 68-85页

作者： Yuan Yang Hao Yang Fedir N.Kiskin joe Z.Zhang Institute of Neurological and Psychiatric Disorders Shenzhen Bay LaboratoryShenzhenGuangdong ProvinceChina Institute of Neurological and Psychiatric Disorders Shenzhen Bay LaboratoryShenzhen 518132Guangdong ProvinceChina

Cardiovascular research has heavily relied on studies using patient samples and animal ***,patient studies often miss the data from the crucial early stage of cardiovascular diseases,as obtaining primary tissues at this stage is *** animal models can offer some insights into disease mechanisms,although they usually do not fully recapitulate the phenotype of cardiovascular diseases and their *** recent years,a promising breakthrough has emerged in the form of in vitro three-dimensional(3D)cardiovascular models utilizing human pluripotent stem *** innovative models recreate the intricate 3D structure of the human heart and vessels within a controlled *** advancement is pivotal as it addresses the existing gaps in cardiovascular research,allowing scientists to study different stages of cardiovascular diseases and specific drug responses using human-origin *** this review,we first outline various approaches employed to generate these *** then comprehensively discuss their applications in studying cardiovascular diseases by providing insights into molecular and cellular changes associated with cardiovascular condi***,we highlight the potential of these 3D models serving as a platform for drug testing to assess drug efficacy and *** their immense potential,challenges persist,particularly in maintaining the complex structure of 3D heart and vessel models and ensuring their function is comparable to real ***,overcoming these challenges could revolutionize cardiovascular *** has the potential to offer comprehensive mechanistic insights into human-specific disease processes,ultimately expediting the development of personalized therapies.

关键词： pluripotent stem cells three-dimensional(3D)models cardiac microtissues cardiac organoids vessel organoids organ-on-a-chip

Performance, Combustion and Emission Characteristics of Oxygenated Diesel in DI Engines: A Critical Review

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Journal of Power and Energy Engineering 2024年第6期12卷 16-49页

作者： Joseph Lungu Lennox Siwale Rudolph joe Kashinga School of Engineering The Copperbelt University Riverside Campus Kitwe Zambia

The transition from non-renewable to renewable energy sources is a significant challenge of our time. In the fuel industry, oxygenated additives such as butanol are transforming conventional fuels into renewable biofuels. This technology has been utilized in reciprocating engines for decades. This paper reviews the viability of using an n-butanol blend as a short-term replacement for diesel by analyzing its physical and chemical properties, combustion, performance, and emission characteristics in compression ignition (CI) engines under various conditions, including variable load, speed, acceleration, and both stationary and transient cycles. N-Butanol exhibits higher viscosity, better lubricity, higher heating value, improved blend stability, enhanced cold-flow properties, and higher density. These factors influence spray formation, injection timing, atomization, and combustion characteristics. Its higher oxygen content improves the diffusion combustion stage and efficiency. Adding 5% and 10% n-butanol to diesel increases pressure and apparent heat release rate, slightly reduces temperature, and improves thermal efficiency, with mixed effects on CO and THC emissions and a notable decrease in particulate matter emissions. Fuel consumption increases, while the impact on NOx emissions varies. A 10% butanol blend is considered optimal for enhancing performance and reducing particulate emissions without significantly affecting NOx emissions. Blending up to 40% butanol with diesel does not require engine modifications or ECU recalibrations in engines calibrated for pure diesel. Due to its advantageous properties and performance, n-butanol is recommended as a superior alcohol-diesel blend than ethanol for short-term diesel replacement.

关键词： Diesel Engine Alcohol Additives N-Butanol Combustion and Properties

Enhancing Patients Outcomes and Infection Control through Smart Indoor Air Quality monitoring Systems

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Journal of Computer and Communications 2024年第6期12卷 25-37页

作者： Othniel Ojochonu Abalaka joe Essien Calistus Chimezie martin Ogharandukun Department of Computer Science Veritas University Abuja Nigeria Department of Pure and Applied Physics Veritas University Abuja Nigeria

Air pollution poses a critical threat to public health and environmental sustainability globally, and Nigeria is no exception. Despite significant economic growth and urban development, Nigeria faces substantial air quality challenges, particularly in urban centers. While outdoor air pollution has received considerable attention, the issue of indoor air quality remains underexplored yet equally critical. This study aims to develop a reliable, cost-effective, and user-friendly solution for continuous monitoring and reporting of indoor air quality, accessible from anywhere via a web interface. Addressing the urgent need for effective indoor air quality monitoring in urban hospitals, the research focuses on designing and implementing a smart indoor air quality monitoring system using Arduino technology. Employing an Arduino Uno, ESP8266 Wi-Fi module, and mQ135 gas sensor, the system collects real-time air quality data, transmits it to the ThingSpeak cloud platform, and visualizes it through a user-friendly web interface. This project offers a cost-effective, portable, and reliable solution for monitoring indoor air quality, aiming to mitigate health risks and promote a healthier living environment.

关键词： Artificial Intelligence Air Pollution Infection Control Data Transmission Data Acquisition Sensors

machine Learning models for Heterogenous Network Security Anomaly Detection

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Journal of Computer and Communications 2024年第6期12卷 38-58页

作者： mercy Diligence Ogah joe Essien martin Ogharandukun monday Abdullahi Department of Computer Science Veritas University Abuja Nigeria Department of Pure and Applied Physics Veritas University Abuja Nigeria Department of Computer Science Air Force Institute of Technology Kaduna Nigeria

The increasing amount and intricacy of network traffic in the modern digital era have worsened the difficulty of identifying abnormal behaviours that may indicate potential security breaches or operational interruptions. Conventional detection approaches face challenges in keeping up with the ever-changing strategies of cyber-attacks, resulting in heightened susceptibility and significant harm to network infrastructures. In order to tackle this urgent issue, this project focused on developing an effective anomaly detection system that utilizes machine Learning technology. The suggested model utilizes contemporary machine learning algorithms and frameworks to autonomously detect deviations from typical network behaviour. It promptly identifies anomalous activities that may indicate security breaches or performance difficulties. The solution entails a multi-faceted approach encompassing data collection, preprocessing, feature engineering, model training, and evaluation. By utilizing machine learning methods, the model is trained on a wide range of datasets that include both regular and abnormal network traffic patterns. This training ensures that the model can adapt to numerous scenarios. The main priority is to ensure that the system is functional and efficient, with a particular emphasis on reducing false positives to avoid unwanted alerts. Additionally, efforts are directed on improving anomaly detection accuracy so that the model can consistently distinguish between potentially harmful and benign activity. This project aims to greatly strengthen network security by addressing emerging cyber threats and improving their resilience and reliability.

关键词： Cyber-Security Network Anomaly Detection machine Learning Random Forest Decision Tree Gaussian Naive Bayes

Crystal reconstruction of V2O3/carbon heterointerfaces via anodic hydration for ultrafast and reversible mg-ion battery cathodes

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Infomat 2024年第3期6卷 95-107页

作者： Gun Jang Yun Sang joe Sang Joon Lee Hyun Gyu Cho Sang Ha Baek Peixun Xiong Kang Ho Shin Jeong Seok Yeon min Su Kang Si Hyoung Oh Ho Seok Park School of Chemical Engineering Sungkyunkwan University(SKKU)SuwonRepublic of Korea Advanced Batteries Research Center Korea Electronics Technology InstituteSeongnamRepublic of Korea Korea Institute of Science and Technology SeoulRepublic of Korea SKKU Advanced Institute of Nano Technology(SAINT) Sungkyunkwan UniversitySuwonRepublic of Korea Department of Health Sciences and Technology Samsung Advanced Institute for Health Sciences and Technology(SAIHST)Sungkyunkwan UniversitySuwonRepublic of Korea SKKU Institute of Energy Science and Technology(SIEST) Sungkyunkwan UniversitySuwonRepublic of Korea

magnesium-ion batteries(mIBs)have promising applications because of their high theoretical capacity and the natural abundance of magnesium ***,the kinetic performance and cyclic stability of cathode materials are limited by the strong interactions between mg ions and the crystal ***,we demonstrate the unique mg^(2+)-ion storage mechanism of a hierarchical accordion-like vanadium oxide/carbon heterointerface(V2O3@C),where the V2O3 crystalline structure is reconstructed into a mgV_(3)O_(7)·H_(2)O phase through an anodic hydration reaction upon first cycle,for the improved kinetic and cyclic *** verified by in situ/ex situ spectroscopic and electrochemical analyses,the fast charge transfer kinetics of the V2O3@C cathode were due to the crystal-reconstruction and chemically coupled *** V2O3@C demonstrated an ultrahigh rate capacity of 130.4 mAh g^(-1)at 50000 mA g^(-1)and 1000 cycles,achieving a Coulombic efficiency of 99.6%.The high capacity of 381.0 mA h g^(-1)can be attributed to the reversible mg^(2+)-ion intercalation mechanism observed in the mgV_(3)O_(7)·H_(2)O phase using a 0.3 m mg(TFSI)2/ACN(H_(2)O)***,within the voltage range of 2.25 V versus mg/mg^(2+),the V2O3@C exhibited a capacity of 245.1 mAh g^(-1)when evaluated with magnesium metal in a 0.3 m mg(TFSI)^(2+)0.25 m mgCl_(2)/DmE *** research findings have important implications for understanding the relationship between the mg-ion storage mechanism and reconstructed crystal phase of vanadium oxides as well as the heterointerface reconstruction for the rational design of mIB cathode materials.

关键词： anodic hydration reaction magnesium ion battery nano crystal vanadium oxide