Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

Discipline
Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 169471 - 169500 of 5150034

Full-Text Articles in Entire DC Network

Analyzing Option Chain Bid–Ask Spreads With Machine Learning, Brian Byrne, Qianru Shang Jun 2025

Analyzing Option Chain Bid–Ask Spreads With Machine Learning, Brian Byrne, Qianru Shang

SAML-25 Workshop on Statistical and Machine Learning

This paper investigates the determinants of option bid–ask spreads using machine learning techniques. We analyze a cross-sectional dataset of Apple Inc. (AAPL) call options, focusing on the relative bid–ask spread as the target variable. By comparing linear models with ensemble methods such as Random Forests and XGBoost, we find that nonlinear machine learning methods significantly outperform traditional OLS regression. The most influential factors are moneyness, implied volatility, and time to expiration, while volume and open interest have limited predictive power. Results suggest that spreads are driven by a mix of market microstructure dynamics, capital constraints, and regulatory requirements such as …

Go to article

Intention To Commute By Public Transportation And/Or By Foot: Findings From A Pls Structural Equation Model, Simona Balzano, Houyem Demni,, Edoardo Pascucci,, Luisa Natale, Giuseppe Cappelli, Sofia Nardoianni, Giovanni C. Porzio Jun 2025

Intention To Commute By Public Transportation And/Or By Foot: Findings From A Pls Structural Equation Model, Simona Balzano, Houyem Demni,, Edoardo Pascucci,, Luisa Natale, Giuseppe Cappelli, Sofia Nardoianni, Giovanni C. Porzio

SAML-25 Workshop on Statistical and Machine Learning

Sustainable mobility stands at the forefront of contemporary discussions, driven by the clear imperative to transition towards more environmentally friendly transportation and patterns. This shift is widely recognized as a crucial opportunity to address the challenges and inherent dangers posed by climate change. It is then crucial to introduce attitudes to encourage voluntary behavioral changes toward different sustainable solutions. In this perspective, to foster a future where sustainable personal mobility options are widely embraced and integrated, it is crucial to comprehend the inclination of younger generations to use them. For this reason, a survey on the use of sustainable mobility …

Go to article

Shedding Light On Cellular Glycolysis Pathway Kinetics Using A Spectralomics Approach, Integrating Multivariate Statistical And Machine Learning Analytical Approaches, Nitin Patil, Zohreh Mirveis, Hugh Byrne Jun 2025

Shedding Light On Cellular Glycolysis Pathway Kinetics Using A Spectralomics Approach, Integrating Multivariate Statistical And Machine Learning Analytical Approaches, Nitin Patil, Zohreh Mirveis, Hugh Byrne

SAML-25 Workshop on Statistical and Machine Learning

The potential of time resolved label-free Raman microspectroscopy to elucidate the kinetics of cellular and subcellular glycolysis pathway was explored in this study. A549, human lung cells were cultured in an unbuffered minimal medium with glucose as a sole carbon source under three different modulated conditions. Modulator drugs oligomycin and 2-deoxyglucose were used to stimulate and inhibit the glycolysis pathway. Initially the kinetic glycolysis assay was used to monitor the glycolysis end-point kinetics followed by development of a numerical model capable of simulating the end-point kinetics. For Raman spectroscopy, samples at different timepoints from the experiments with similar conditions as …

Go to article

Ai-Driven Personalized Radiotherapy Planning, Nithin Venkatesh, Marco Pota, Maged Shaban Jun 2025

Ai-Driven Personalized Radiotherapy Planning, Nithin Venkatesh, Marco Pota, Maged Shaban

SAML-25 Workshop on Statistical and Machine Learning

The planning of radiation oncology treatment is made more dynamic and individualized by Artificial Intelligence (AI). Routine radiotherapy practice applies normative procedures indifferent to patient-specific parameters such as tumor volume, patient anatomy, and heterogeneity in the delineation of treatment response. Inadequate and over-radiation treatment is the most prevalent outcome. Further, with the inclusion of AI, it can facilitate enhancing the healthcare industry through optimizing radiotherapy using an array of patient information such as molecular profiles and imaging data. The product offers an end-to-end AI-driven solution to all aspects of radiotherapy, from initial consultation (diagnosis) to adaptive treatment planning. All the …

Go to article

Early Lane Change Prediction For Mixed Traffic With V2x Communication, Muhammed Fatih Koc, Nouman Ashraf, Pramod Pathak, Sachin Sharma Jun 2025

Early Lane Change Prediction For Mixed Traffic With V2x Communication, Muhammed Fatih Koc, Nouman Ashraf, Pramod Pathak, Sachin Sharma

SAML-25 Workshop on Statistical and Machine Learning

Lane change prediction is essential for ensuring road safety and effective decision-making in autonomous vehicles (AVs). AVs will probably take several decades to penetrate new vehicle sales. As AVs and human-driven vehicles (HDVs) will coexist in traffic for the long term, AVs must understand the lane change intentions of surrounding HDVs. Lane changing is a critical manoeuvre that can cause a crash if it is performed late or if incorrect lane adjustments are made. Therefore, forecasting surrounding vehicles’ lane change intentions in advance is essential to ensure safe driving in mixed traffic environments having both AVs and HDVs. The unpredictability …

Go to article

A Machine Learning Approach To Improve Prediction In Chemical Exposure Risk Assessment, Michele Marro, Cédric Koller, Hasnaa Chettou, David Vernez Jun 2025

A Machine Learning Approach To Improve Prediction In Chemical Exposure Risk Assessment, Michele Marro, Cédric Koller, Hasnaa Chettou, David Vernez

SAML-25 Workshop on Statistical and Machine Learning

Exposure models play a crucial role in predicting chemical exposure in workplaces, offering an essential alternative to measurements, which are resource-intensive and time-consuming and sometimes not possible. Despite their widespread use and continuous development, significant challenges persist, including variability in predictions, limited model updates, and difficulties in accessing the required input data. In this study, we investigate how modern machine learning techniques can contribute to the improvement of exposure models by addressing these limitations. To overcome the frequent lack of data, we explore the use of synthetic datasets generated through existing exposure models. This approach allows for the study of …

Go to article

Interpretable Ai In Education: A Comparison Of Glass-Box Models For Predicting Student Success, Jan Glazenborg Jun 2025

Interpretable Ai In Education: A Comparison Of Glass-Box Models For Predicting Student Success, Jan Glazenborg

SAML-25 Workshop on Statistical and Machine Learning

This Master’s thesis addresses early identification of first-year Computer Science students at risk of underperformance by comparing inherently interpretable (“glass-box”) predictive models with the existing Naïve Bayes–based PreSS tool. The PreSS dataset was originally compiled by Quille & Bergin from 692 first-year CS1 students across eleven institutions in Ireland and Denmark, who completed surveys on programming and mathematics backgrounds, gaming habits and a short programming test four to six hours into the course. Seventeen normalized features capturing demographic, academic and behavioural factors were extracted. In this thesis, four machine learning models are evaluated: Naïve Bayes, explainable boosting machines, automatic piecewise …

Go to article

Pros & Cons Of Reinforcement Learning - Illustrated By The Problem Of Controlling Gantry Robots, Horst Zisgen Jun 2025

Pros & Cons Of Reinforcement Learning - Illustrated By The Problem Of Controlling Gantry Robots, Horst Zisgen

SAML-25 Workshop on Statistical and Machine Learning

In this talk a solution for the dynamic scheduling of flexible flow shop systems using gantry robots for material handling by means of simulation and Reinforcement Learning (RL) is presented. Subsequently the pros and cons of a RL approach are briefly discussed and illustrated at the robot control problem.

Go to article

Survival Predictions From Classification Algorithms – Concepts And Application To Graft And Patient Survival After Kidney Transplantation, Antje Jahn Jun 2025

Survival Predictions From Classification Algorithms – Concepts And Application To Graft And Patient Survival After Kidney Transplantation, Antje Jahn

SAML-25 Workshop on Statistical and Machine Learning

Clinical prediction models are developed to predict long-term patient outcomes following medical interventions. One example motivating this research is the prediction of graft and patient survival after kidney transplantation, using data from the German organ transplantation registry. A practical issue in this context is to deal with incomplete information due to right-censoring, which arises when patients are lost to follow-up or enter the study at different times, resulting in varying durations of observation. This is particularly relevant in the registry data, where follow-up is frequently incomplete or irregular. While traditional survival analysis methods handle censoring by modeling the hazard function, …

Go to article

Pathology’S Place In Understanding The Bias And Inequalities In Women’S Healthcare, Andrea Heaney, Eugene Hickey, Emma Murphy Jun 2025

Pathology’S Place In Understanding The Bias And Inequalities In Women’S Healthcare, Andrea Heaney, Eugene Hickey, Emma Murphy

SAML-25 Workshop on Statistical and Machine Learning

Women’s healthcare is a complex, multifaceted issue with both historic and implicit biases, along with biological differences between men and women. With the advancement of AI tools in healthcare and the potential for biased data to create biased models, it is vital to consider how women are represented in data. Previously conducted semi-structured semantic interviews with clinicians were analysed via Braun and Clark’s method of thematic analysis. The analysis of these interviews yielded the following themes: Gender Influencing Health, Pregnancy, Social Factors, General Health, Treatment, Training, and Research. These themes highlight that context is key to understanding the biases in …

Go to article

Impact Of Spatial Diversity And Subject Variability On Wifi-Based Human Activity Recognition, Amany Elkelany, Robert J. Ross, Susan Mckeever Jun 2025

Impact Of Spatial Diversity And Subject Variability On Wifi-Based Human Activity Recognition, Amany Elkelany, Robert J. Ross, Susan Mckeever

SAML-25 Workshop on Statistical and Machine Learning

In recent years, WiFi-based Human Activity Recognition (HAR) has gained substantial attention due to the ubiquity of WiFi infrastructure and advancements in wireless communication. Unlike camera-based systems that raise privacy concerns or wearable sensors that require user compliance, WiFi-based HAR provides a noninvasive and practical alternative that operates seamlessly with existing infrastructure. WiFi-based HAR leverages fluctuations in wireless signals, particularly Channel State Information (CSI), to passively detect and classify human activities. WiFi-based HAR models often achieve high accuracy in a single environment but suffer significant performance drops when applied to new environments due to variations in spatial settings, human movement, …

Go to article

Optimising Ai For Chemical Imaging: Benchmarking Performance Against Foundation Models For Task-Specific Applications In Histopathology, Rahul Suresh, Mohd Rifqi Rafsanjani, Karin Jirstrom, Arman Rahman, William M. Gallagher, Aidan Meade Jun 2025

Optimising Ai For Chemical Imaging: Benchmarking Performance Against Foundation Models For Task-Specific Applications In Histopathology, Rahul Suresh, Mohd Rifqi Rafsanjani, Karin Jirstrom, Arman Rahman, William M. Gallagher, Aidan Meade

SAML-25 Workshop on Statistical and Machine Learning

The integration of chemical imaging with artificial intelligence presents a compelling route toward fully digital, label-free histopathology, yet it also introduces notable challenges. While deep learning models from domains like machine vision, digital pathology, and remote sensing are readily accessible, they frequently struggle to generalize effectively to chemical imaging data, as highlighted in recent research [1]. Additionally, although foundational pathological models show potential for advancing AI-based histopathological diagnostics and prognostics, our preliminary assessments suggest they may fall short in addressing the broad spectrum of classification tasks encountered in clinical settings. In this presentation, we highlight some recent published work from …

Go to article

Transient Voltage Instability Identification Based On Koopman Operator In Power Grid With A High Proportion Of Renewables, Xiuqi Zhang, Hongqing Liu, Liqiang Wang, Yong Li, Han Gao Jun 2025

Transient Voltage Instability Identification Based On Koopman Operator In Power Grid With A High Proportion Of Renewables, Xiuqi Zhang, Hongqing Liu, Liqiang Wang, Yong Li, Han Gao

Journal of Electric Power Science and Technology

Transient voltage instability is one of the important factors that threaten the stability of power system. The dynamic reactive power reserve and supporting capacity of the power grid with a high proportion of renewables decrease sharply, and the control models and operation characteristics of grid-connected renewables are diverse. Thus, the reactive power voltage of the system often fluctuates rapidly after a fault occurs, which leads to a more prominent voltage stability problem. In response, a transient voltage instability identification method based on the Koopman operator is proposed in this paper to avoid power system outage accidents caused by voltage instability …

Go to article

Relay Protection Setting Calculation Method For Power Grid Based On Spark, Chuang Song, Wei Han, Xingwei Du, Jingjun Wang Jun 2025

Relay Protection Setting Calculation Method For Power Grid Based On Spark, Chuang Song, Wei Han, Xingwei Du, Jingjun Wang

Journal of Electric Power Science and Technology

To adapt the grid to the requirements of intelligentization and the dispatching and control cloud technology route, this paper proposes a relay protection setting calculation method for power grid based on distributed parallel computing. First, the cluster architecture of the Spark distributed computing platform is introduced, and the key issues of distributed parallel computing, such as load balancing, system fault tolerance, etc. are analyzed. On this basis, a computing system for relay protection setting calculation based on Spark is designed. Secondly, the extra-high-voltage power grid setting calculation in the computing system is analyzed, and the principles of protection and setting …

Go to article

A Novel Distance Protection Method For High‑Voltage Line In Substation With Integration Of Inverter‑Interfaced Distributed Generator, Zhengfei Lu, Minghao Wen, Yu Zhou, Longxing Jin, Shuai Ma Jun 2025

A Novel Distance Protection Method For High‑Voltage Line In Substation With Integration Of Inverter‑Interfaced Distributed Generator, Zhengfei Lu, Minghao Wen, Yu Zhou, Longxing Jin, Shuai Ma

Journal of Electric Power Science and Technology

The strong variability, spatiotemporal randomness, and nonlinear controlled characteristics during faults of inverter-interfaced distributed generators (IIDGs) such as direct-drive wind turbines and photovoltaic generators pose significant challenges to the existing relay protection systems in power grids. When faults occur in high-voltage lines of substations with integration of IIDGs, the fault characteristics are more complex compared to those in the case of the access of traditional synchronous machine sources to high-voltage lines, which makes it difficult for conventional positive-sequence voltage-polarized phase-comparison distance protection to adapt to. As a result, the performance of protection for power grids deteriorates. This paper analyzes the …

Go to article

Ultra‑Low Frequency Oscillation Control Method Considering Dead Zone And Limiting Optimization Of Hydraulic Turbine Governor, Jiawei Wang, De Zhang, Yuzheng Xie, Ancheng Xue Jun 2025

Ultra‑Low Frequency Oscillation Control Method Considering Dead Zone And Limiting Optimization Of Hydraulic Turbine Governor, Jiawei Wang, De Zhang, Yuzheng Xie, Ancheng Xue

Journal of Electric Power Science and Technology

The dead zone and limiting of a hydraulic turbine governor have a great influence on the characteristics of the ultra-low frequency oscillations (ULFOs), which can even lead to the oscillation of the positive damping system under large disturbance. However, the existing control methods for ULFOs mainly focus on optimizing proportional‑integral‑derivative (PID) control parameters of hydraulic turbine governors to improve system damping, without considering the dead zone and limiting parameters concurrently. This paper proposes a ULFO control method considering the dead zone and limiting optimization of the turbine governor and verifies its effectiveness and superiority. Firstly, in a non-smooth single hydro-generator …

Go to article

Fault Line Selection And Section Location Method For Asymmetric Distribution Network Based On Fast Switch Arc Suppression Device, Fangyu He, Yanru Ni, Xiangjun Zeng, Kun Yu, Chao Zeng Jun 2025

Fault Line Selection And Section Location Method For Asymmetric Distribution Network Based On Fast Switch Arc Suppression Device, Fangyu He, Yanru Ni, Xiangjun Zeng, Kun Yu, Chao Zeng

Journal of Electric Power Science and Technology

In consideration of the problem of high-resistance grounding fault line selection and section location in asymmetric distribution networks, a fault line selection and section location method for asymmetric distribution networks based on the fast switch arc suppression device is proposed. Firstly, the basic principle of the fast switch arc suppression device is analyzed. On this basis, the electrical quantity properties of each feeder in the distribution system prior to and following the operation of the device are analyzed in depth after the high-resistance grounding fault occurs in the system. Through theoretical derivation, it is found that the fault feeder and …

Go to article

A Two‑Stage Recovery Strategy For Damaged Distribution Networks Considering Cold Load Pick‑Up, Yongpeng Zhang, Lizhen Wu, Jianping Wei, Wei Chen Jun 2025

A Two‑Stage Recovery Strategy For Damaged Distribution Networks Considering Cold Load Pick‑Up, Yongpeng Zhang, Lizhen Wu, Jianping Wei, Wei Chen

Journal of Electric Power Science and Technology

The development of intelligent distribution networks has improved the self-healing ability and recovery speed of the power grid. However, when the system encounters large-scale power outages, the recovery process becomes more complex. Therefore, in response to the problem of power interruption in damaged distribution networks, this paper proposes a two-stage recovery strategy for damaged distribution networks that takes into account cold load pick-up (CLPU), aiming to generate a power restoration plan for distribution networks with switch control actions. The first stage generates traditional recovery and distributed power-assisted island power supply recovery plans that support feeder reconfiguration. In the second stage, …

Go to article

Optimal Business Expansion Model For Distribution Network Considering Load Timing And Power Source Matching, Fuhai Yu, Yongkuo Liu, Qiulin Ding, Chenglong Shen, Anqi Wang Jun 2025

Optimal Business Expansion Model For Distribution Network Considering Load Timing And Power Source Matching, Fuhai Yu, Yongkuo Liu, Qiulin Ding, Chenglong Shen, Anqi Wang

Journal of Electric Power Science and Technology

When business expansion plans of new access loads are formulated for traditional distribution networks, their timing and controllable and interruptible loads are not considered, which can easily cause loads with the same characteristics to be concentrated in the same power source. As a result, the peak and valley values of the power point are overlapped, and thus equipment utilization and business expansion capacity are lowered. In response, this paper proposes an optimal business expansion model for distribution networks, which considers load timing and power source matching. Firstly, the paper proposes a fuzzy C-means clustering method based on the improved nutcracker …

Go to article

Fault Detection In Switchgear Based On Rfid Sensors And Deep Learning, Zhen Wang, Ziquan Liu, Yongling Lu, Yujie Li Jun 2025

Fault Detection In Switchgear Based On Rfid Sensors And Deep Learning, Zhen Wang, Ziquan Liu, Yongling Lu, Yujie Li

Journal of Electric Power Science and Technology

In order to improve the accuracy of switchgear fault detection, this paper proposes a fault detection algorithm for switchgear based on RFID sensors and deep learning. Firstly, RFID sensing tags are designed to collect the current signals and temperature of the switchgear. Secondly, the collected signals are subjected to deep-level feature extraction through a deep belief network (DBN), and sparse coding (SC) is integrated into the DBN to improve its detection accuracy. Finally, in order to improve the detection speed, an extreme learning machine (ELM) is used to classify and recognize the signals extracted from the features. The experimental results …

Go to article

A Novel Reactive Power Support And Grounding Fault Control Composite Device Based On Station Resources, Lijun Tang, Xinjun Qian, Hongwen Liu, Chunming Tu, Zejun Huang, Qi Guo Jun 2025

A Novel Reactive Power Support And Grounding Fault Control Composite Device Based On Station Resources, Lijun Tang, Xinjun Qian, Hongwen Liu, Chunming Tu, Zejun Huang, Qi Guo

Journal of Electric Power Science and Technology

Owing to the ability of both reactive power support (RPS) and grounding fault control (GFC), composite devices have attracted extensive attention. However, most existing composite devices have some disadvantages, such as high capacity and the need for additional power supply devices. To address these problems, a novel RPS and GFC composite device (RGCD) is proposed in this paper from the idea of making full use of existing station resources. Firstly, the topology and the operation principle of RGCD are introduced. The RGCD is composed of the capacitor and the arc suppression coil in the station and the multi-functional converter (MC). …

Go to article

Comparison And Evaluation Of Grid‑Connected Performance Of Grid‑Following And Grid‑Forming Stations Based On Game Theory And Improved Topsis, Zhen'ao Yang, Junru Chen, Yushan Liu, Jiajun Guo, Xiqiang Chang Jun 2025

Comparison And Evaluation Of Grid‑Connected Performance Of Grid‑Following And Grid‑Forming Stations Based On Game Theory And Improved Topsis, Zhen'ao Yang, Junru Chen, Yushan Liu, Jiajun Guo, Xiqiang Chang

Journal of Electric Power Science and Technology

In order to quantitatively assess the frequency/voltage support effects of grid-following and grid-forming stations, an evaluation index system to quantify the performance of the stations is proposed, considering the power support density and energy support density. First, based on the output response characteristics of grid-following and grid-forming controlled generating units in renewable energy stations, the characteristic quantities of power, voltage, and frequency are observed over multiple time scales in terms of voltage and frequency stability. Second, the coupling relationship between the indicators is considered comprehensively, and the base weights of the indicators are derived using the best-worst method (BWM) and …

Go to article

Photovoltaic And Energy Storage Charging And Switching Station Siting And Capacity Determination Method Considering Ultra‑High Power, Xiaonan Liu, Jian Zhang, Zhida Zhang, Jianing Duo, Shan Cheng, Shuang Hao, Yue Zhao, Haojie Wang Jun 2025

Photovoltaic And Energy Storage Charging And Switching Station Siting And Capacity Determination Method Considering Ultra‑High Power, Xiaonan Liu, Jian Zhang, Zhida Zhang, Jianing Duo, Shan Cheng, Shuang Hao, Yue Zhao, Haojie Wang

Journal of Electric Power Science and Technology

Existing studies in the planning of ultra-high power charging and switching stations lack a comprehensive depiction of user behavioral variability and stochasticity and the consideration of collaborative planning of distributed flexible resources such as photovoltaic and energy storage in the station. To this end, a two-tier siting and capacity determination method for integrated photovoltaic and energy storage charging and switching power stations involving multiple coupling factors is proposed. First, an electric vehicle charging and switching load prediction model considering user travel characteristics, temperature, and real-time road conditions is constructed. Second, to take into account user charging and switching needs and …

Go to article

New Bypass Mmc Sub‑Module And Its Dc Fault Ride‑Through Strategy, Zhibo Wang, Ye Tian, Yidong Zhu Jun 2025

New Bypass Mmc Sub‑Module And Its Dc Fault Ride‑Through Strategy, Zhibo Wang, Ye Tian, Yidong Zhu

Journal of Electric Power Science and Technology

The DC short-circuit fault current cannot be blocked by the modular multilevel converter (MMC) with traditional half-bridge sub-module (HBSM), which reduces the reliability of MMC based high voltage direct current (MMC-HVDC) systems. In this paper, based on two HBSM systems, a new bypass sub-module named diode clamp dual-half-bridge sub-module (DCDHBSM) with DC fault current blocking capability is proposed. Compared with other sub-modules possessing DC short-circuit current blocking capability, the proposed DCDHBSM requires fewer power devices and has lower operation loss. Moreover, a DC fault ride-through strategy suitable for DCDHBSM is designed, and sorting algorithm is utilized to balance the post-fault …

Go to article

Study On Electrical Features Of Inter‑Turn Insulation Fault Of 10 Kv Dry‑Type Air‑Core Series Reactor By Field‑Circuit Coupling Method, Lizhi Zhang, Chengjun Cao, Wei Zhang, Kaida Chen, Shijie Lei Jun 2025

Study On Electrical Features Of Inter‑Turn Insulation Fault Of 10 Kv Dry‑Type Air‑Core Series Reactor By Field‑Circuit Coupling Method, Lizhi Zhang, Chengjun Cao, Wei Zhang, Kaida Chen, Shijie Lei

Journal of Electric Power Science and Technology

The frequent occurrence of inter-turn short circuit faults of dry-type air-core series reactors in shunt capacitor sets gravely imperils the secure and steady operation of the power system. It is extremely crucial to research the variations of characteristic quantities prior to and subsequent to inter-turn short circuits in dry-type air-core series reactors. In this paper, Maxwell is used to establish the field-circuit coupling model, and the model accuracy is verified by comparing the calculated value of the analytical method with the test value of the manufacturer. On this basis, the inter-turn short-circuit model is constructed, and the electrical quantities when …

Go to article

Vibration Characteristics And Signal Inversion Of Oil‑Immersed Transformer Based On Electromagnetic‑Structural Field, Feng Huang, Chun Guo, Bingbing Qiu, Xiaodan Qiu, Yi Yang, Fating Yuan, Ruiqing Ji Jun 2025

Vibration Characteristics And Signal Inversion Of Oil‑Immersed Transformer Based On Electromagnetic‑Structural Field, Feng Huang, Chun Guo, Bingbing Qiu, Xiaodan Qiu, Yi Yang, Fating Yuan, Ruiqing Ji

Journal of Electric Power Science and Technology

As critical equipment in the power system, the operation status of oil-immersed transformers directly affects the safety and stability of the power grid. Based on COMSOL, a finite element simulation software, a 10kV/400V oil-immersed transformer electromagnetic–structural multiphysics coupling calculation model is established to analyze the effect of added/unadded clamping devices on the core vibration displacement. On this basis, the vibration characteristics of the core, windings, and tank wall are analyzed, and their corresponding vibration acceleration signals are extracted. Subsequently, the Kendall and Spearman correlation coefficients are employed to calculate the correlation among the vibration signals of the core, windings, and …

Go to article

A Hormone-Dependent Trna Half Promotes Cell Cycle Progression Via Destabilization Of P21 Mrna, Takuya Kawamura, Megumi Shigematsu, Yohei Kirino Jun 2025

A Hormone-Dependent Trna Half Promotes Cell Cycle Progression Via Destabilization Of P21 Mrna, Takuya Kawamura, Megumi Shigematsu, Yohei Kirino

Department of Biochemistry and Molecular Biology Faculty Papers

tRNA halves are among the most abundant short non-coding RNAs in the cellular transcriptome. Here we report that in androgen receptor-positive LNCaP prostate cancer cells, the hormone-dependent 5'-tRNALysCUU half promoted cell proliferation by facilitating cell cycle progression. Global mRNA profiling upon the 5'-tRNALysCUU half depletion revealed that the mRNA of p21, a negative regulator of the cell cycle, is post-transcriptionally destabilized via a 5'-tRNALysCUU half-driven mechanism. YBX1, identified as a protein interacting with 5'-tRNALysCUU half in the cytosol, was shown to stabilize p21 mRNA. Specific sequences resembling the 5'-tRNALysCUU half, located in the 3'-UTR of p21 mRNA and termed LL588, …

Go to article

Local And Regional Pastors And Non-Profit Leaders Complete Gardner-Webb’S Searight Pace Grant Writing Course, Office Of University Communications Jun 2025

Local And Regional Pastors And Non-Profit Leaders Complete Gardner-Webb’S Searight Pace Grant Writing Course, Office Of University Communications

Gardner-Webb NewsCenter Archive

A group of ministers and non-profit leaders from local and regional ministries recently completed the Searight PACE course, “Grant Writing for Churches and Non- Profits.” Taught by Dr. Bobbie Cox, professor and chair of the Department of Public Service, the five-part series helped participants to develop the skills and resources needed to write successful grants.

Go to article

Beyond Barriers: Supporting Formerly Incarcerated Students In American Higher Education, Carly Jean Colbert Jun 2025

Beyond Barriers: Supporting Formerly Incarcerated Students In American Higher Education, Carly Jean Colbert

Journal of Prison Education Research

The United States prison industry is the largest in the world. With the reintroduction of Second Chance Pell in 2015, more people are starting their education while incarcerated, and some attempt to finish after release. However, they are faced with numerous barriers that may prevent graduation. Drawing on Astin’s theory of student involvement, this mixed-methods study examines the challenges that formerly incarcerated people face while pursuing college degrees. Rather than focusing on access, this research focuses on the supports that institutions of higher education can establish to help formerly incarcerated students persist and successfully complete their undergraduate degrees. The findings …

Go to article

Exploitation Of Plasma Treatment-Assisted Monocarboxylic Cobalt Phthalocyanine Nanorod Growth For High-Efficiency Photodetection Applications, Ahmed Ramzy, Ahmed M. El-Mahalawy, M A. Abd El Ghaffar, Wael A. Abbas Jun 2025

Exploitation Of Plasma Treatment-Assisted Monocarboxylic Cobalt Phthalocyanine Nanorod Growth For High-Efficiency Photodetection Applications, Ahmed Ramzy, Ahmed M. El-Mahalawy, M A. Abd El Ghaffar, Wael A. Abbas

Nanotechnology Research Centre

Here, the effect of cobalt phthalocyanine (CoPC) functionalization by a monocarboxylic group in the form of thermally evaporated thin films followed by plasma treatment for variable time intervals is introduced. The effect of plasma treatment on crystalline structure, molecular structure, and morphology was examined using the XRD, FT-IR, and FE-EEM techniques. Significant modifications were observed in the crystal structure and morphology with increasing plasma treatment time intervals. The plasma treatment for 5 min enhanced the formation of the nanorods along the deposited surface with improved crystallinity. Tracking the optical properties variation of the deposited MCCoPc thin films under plasma treatment …

Go to article

First Prev Next Last