In Whom We Trust, Linda W. Wagner

Ontario Review

LINDA W. WAGNER, a former contributor, teaches English at Michigan State University. She is the author of many critical essays, as well as The Poetry of William Carlos Williams (1964) and The Prose of William Carlos Williams (1970). She recently edited T. S. Eliot: A Collection of Criticism (McGraw-Hill, 1974) and Ernest Hemingway: Five Decades of Criticism (MSU ' Press, 1974).

Is Don Juan Alive And Well?, Arnold J. Mandell M.D.

Ontario Review

ARNOLD J. MANDELL, M.D. is Chairman of the Department of Psychiatry at the University of California at San Diego School of Medicine. His innumerable publications include such items as "A Psychiatric Personality Typology Replaced by One from the NFL - The Acceptability Rather than the Perfectability of Man" in The Saturday Rev iew/ World (1974); and "Redundant Macromolecular Mechanisms in Central Synaptic Regulation" in New Concepts in Neurotransmitter Regulation (1973) . He has served or is serving on numerous state and national committees, and is on the editorial boards of seven professional journals.

Wavelet-Based Mechanomyographic Intensity Responses To Sustained Tasks Anchored To Low Versus High Ratings Of Perceived Exertion, Dolores G. Ortega, Robert W. Smith, Jocelyn E. Arnett, Tyler J. Neltner, Trevor D. Roberts, Justin S. Pioske, Richard J. Schmidt, Terry J. Housh

Journal for Sports Neuroscience

Purpose: This study examined the effects of sustained, isometric forearm flexion tasks anchored to ratings of perceived exertion of 2 (RPE2_FT) versus 8 (RPE8_FT) on the wavelet-based mechanomyographic (MMG) intensity responses from pretest and posttest maximal voluntary isometric contractions (MVICs) as well as the time course of changes in the MMG intensity responses throughout the sustained tasks. Methods: Eleven men (mean±SD: age=20.9±2.3 yrs) performed MVICs before and after the sustained tasks. The wavelet analyses decomposed the MMG signals onto a set of 11 wavelet bands (WBs). Repeated measures ANOVAs were used to analyze the MMG intensity …

Analysis And Assessment Of Land-Cover Changes In Bisha Governorate (1985–2025) Using Remote Sensing And Geographic Information Systems (Gis) Techniques., Samar Saud Al-Duraibi

UB Journal for Humanities

This studying aims to analyze and assess land cover changes in Bisha Governorate during the period 1985–2025 by tracking transformations in vegetation cover (natural and agricultural), urban areas, dry valleys, rocky and desert lands, and water bodies. The study employed historical and analytical approaches, utilizing remote sensing and geographic information system (GIS) techniques to monitor spatial and temporal patterns of change. The results indicate that urban expansion and demographic growth contributed to a decline in vegetated areas, while vegetation cover was influenced by climatic factors, recording its highest extent of approximately 523 km² in 2005. The findings reveal that the …

Assessing The Student Awareness To Age Friendly Design: The Case Of Ain Shams University- Architecture Students, Shorouk Saleh Ali Kabel, Samah Mohamed Elsayed Atteia Elkhateb, Rowaida M. O. Mohamed Rashed, Wesam M. El-Bardisy

HBRC Journal

With Egypt’s rapid urbanization and projected demographic shift, where individuals aged 60 and above are expected to constitute more than 15% of the population by 2050, addressing the needs of older adults in urban design has become increasingly urgent. Despite global recognition of the importance of age-friendly design, its integration into Egyptian architectural education remains limited, particularly concerning accessibility, safety, and inclusivity.

This study evaluates the level of awareness of Age-Friendly Design (AFD) principles among architecture students at Ain Shams University using a mixed-methods approach. Quantitative data were collected through an online questionnaire assessing students’ familiarity with the concept, while …

Performance-Based Seismic Design And Retrofitting Via Drift And Strain Criteria, Tharwat A. Sakr, Hanaa E. Abd-El-Mottaleb, Shrouk S. Kamel

HBRC Journal

In recent decades, the demand for seismic code updates has significantly increased. Performance-based seismic design (PBSD) is a modern approach to earthquake-resistant building construction. By using this technique, the designers can establish performance targets that satisfy the owner. Most codes rely on strength design that utilizes a design response spectrum, highlighting serviceability without addressing performance levels. In this paper, an appraisal for the incorporation of PBSD into the Egyptian Code is proposed using nonlinear static and dynamic analysis. At first, response spectrum charts for 72, 475, and 2475 years return periods (RP) were developed based on the Egyptian seismicity information. …

Place Personality And User Behaviour: Insights From Cairo’S Streets, Sara Sabahy, Zeina Elzein, Doaa Abouelmagd

HBRC Journal

A place’s personality is beyond the sum of its characteristics. It’s how people perceive it on a human level, hoping for a better understanding and seeking connection. This study aims to understand how people connect with public spaces to enhance the quality of urban life.

A place’s personality extends beyond its physical attributes—it reflects how people emotionally perceive and connect with it. This study investigates the relationship between the perceived personality of urban streets and users’ behaviour to enhance the quality of urban life in Cairo. Focusing on Downtown Cairo and New Cairo, it addresses a gap in destination personality …

Automated Optimization Of Structured Large Language Model Prompts Via Iterative Evaluation, Hui Wu, Haoda Huang, Samuel Shen, Enrica Filippi, Imed Zitouni, Simon Zhao, Zach Fisher

Defensive Publications Series

Performance of generative models (GMs), such as Large Language Models (LLMs), is highly dependent on the quality of the input prompt that is processed using the GM. However, manual prompt engineering is often inefficient and requires specialized expertise. This disclosure describes a method for the automated optimization of structured prompts through an iterative evaluation process. A structured prompt template is initially populated using task descriptions and reference data to generate candidate seed prompts. These candidate seed prompts are executed against a targeted model, and the resulting responses are assessed by an automated evaluator. Based on performance metric(s), a refinement loop …

Rme-1: A Formal Specification For Geometric Semantic Refinement, Samuel J. Church

Defensive Publications Series

RME-1: A Formal Specification for Geometric Semantic Refinement

Document ID: RME-1-2026-PRIOR-ART-01

Status: Public Disclosure for Defensive Publication

Core Methodology: Non-Euclidean Mapping of Abstract Logic to Sensory-Grounded Vectors

I. Mathematical Framework: The RME Hilbert Space

The RME-1 engine operates by projecting linguistic units into a multi-axial Hilbert Space. Unlike standard token-probability models, RME-1 enforces a Geometric Constraint (GC) on the output, defined by the relationship between four primary variables:

1. Symbolic Density ($SD$): The concentration of domain-specific semantic tokens per unit of syntax.

2. Sensory Gravity ($SG$): The coefficient of tactile or physical-structural grounding in the output string.

3. Intent …

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A Full Educational Resource Review Of Grey Literature Resources For Vancomycin Dosing Tutorials, Emma S. Kuska, Jen Mlyniec, Kathleen L. Wantuch, Logan Brock, Kathryn E. Desear, Timothy P. Gauthier, Elizabeth B. Hirsch, Wesley D. Kufel, Taylor Morrisette, Matthew Pearsall, Bryan P. White, Joseph J. Carreno

Pharmacy Faculty Scholarship

Background: Optimized vancomycin dosing is associated with improved clinical outcomes, especially decreased acute kidney injury. Free, online, grey literature training materials are available for vancomycin dosing; however, their utility is unclear. Objectives: This study evaluates the utility of these tools for just-in-time (e.g. refresher courses) training for general clinicians dosing vancomycin. Methods: A structured grey literature review of websites was performed, and the Online Course Quality Review (OSCQR) rubric was modified for this study. Eligible resources included free, web-based tutorials aimed at general clinicians. The materials were evaluated using the rubric. Data were summarized as counts and proportions. Results: A …

Theoretical Analysis Of Mir-Based Differential Photoacoustic Spectroscopy For Noninvasive Glucose Sensing, Tasnim Ahmed, Khan Mahmud, Md Rejvi Kaysir, Shazzad Rassel, Dayan Ban

Electrical and Computer Engineering Faculty Research

Diabetes is a developing global health concern that cannot be cured, necessitating frequent blood glucose monitoring and dietary management. Photoacoustic Spectroscopy (PAS) in the mid-infrared (MIR) region has recently emerged as a viable noninvasive blood glucose monitoring technique. However, MIR-PAS confronts significant challenges: (i) Water absorption, which reduces light penetration, and (ii) interference from other blood components. This paper systematically analyzes the background of photoacoustic signal generation and proposes a differential PAS (DPAS) in the MIR region for removing the background signals arising from water and other interfering components of blood, which improves the overall detection sensitivity. A detailed mathematical …

Polystyrene Nanoplastics As Pfas Carriers And Their Interactions With Zwitterionic Phospholipid Membranes, Jiahuiyu Fang, Tongxuan Qiao, Pranab Sarker, Xiaoxue Qin, Size Zheng, Mark J. Uline, Tao Wei

Faculty Publications

The co-occurrence of per- and polyfluoroalkyl substances (PFAS) and nanoplastics (NPs) poses a synergistic threat to environmental and human health, yet the molecular mechanisms governing PFAS–NP complexation and membrane interactions remain unclear. Using atomistic molecular dynamics simulations, we investigated the adsorption of neutral polytetrafluoroethylene (PTFE) and anionic perfluorinated compounds (perfluorooctanoic acid, PFOA, and perfluorooctanesulfonic acid, PFOS) on polystyrene NPs (3.1 and 6.7 nm) and their interactions with 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) membranes. Polystyrene NPs act as carriers, transporting PFAS molecules to the lipid/water interface, where PFAS attachment modifies NP interfacial behavior. PFAS adsorption on the NP surface is driven by …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

Exploitation Prioritization And Residual Risk Assessment Based On Hybrid Mcdm Model, Zibo Wang, Yaofang Zhang, Sicai Lv, Yingzhou Wang, Hongri Liu, Bailing Wang

Turkish Journal of Electrical Engineering and Computer Sciences

Exploitation is one of the most significant ways to launch attacks using vulnerabilities. The increasing number of vulnerabilities and limited allocation of security resources make it impossible to eliminate all exploitations. Because not every vulnerability can be fixed, it is necessary to rank exploitations and subsequently assess the residual risk, which is defined as the remaining threat potential after each elimination. In this paper, a structured and flexible decision support framework based on a hybrid multicriteria decision-making model is proposed for prioritizing exploitations and assessing residual risk. Metrics are treated as criteria in the model. The hybrid model is developed …

A Deep Learning-Based Real-Time No-Reference Image Decolorization Network With Perceptual Preservation, Mengjuan Zhao, Yitao Liang, Weiya Shi, Juan Xia

Turkish Journal of Electrical Engineering and Computer Sciences

Currently, grayscale images are preferred as input data for some specific vision tasks. Decolorization is the transformation of a color image into a grayscale image. Efficient decolorization algorithms can improve the overall task efficiency, while perceptual preservation in decolorization can provide more information for further processing. In recent research, traditional methods focus on preserving contrast or detail information with little attention to perceptual features. Deep-learning methods are beginning to consider perceptual preservation, but they run inefficiently. In addition, the decolorization methods lack the optimal target grayscale images for reference. Therefore, we propose a new deep learning-based real-time no-reference decolorization network …

Noninvasive Condition Monitoring For Eccentricity Fault Detection In Large Hydro Generators, Atena Tazikeh Lemeski, Di̇dem Tekgün, Ozan Keysan, Kemal Leblebi̇ci̇oğlu, Murat Göl

Turkish Journal of Electrical Engineering and Computer Sciences

Eccentricity faults in electric machines remain a critical concern, as they generate uneven magnetic forces that increase vibration and noise, ultimately raising the risk of premature motor failure. This study proposes a method for the early detection of dynamic eccentricity (DE) faults in hydropower plants through an advanced optimization-based parameter identification technique integrated with finite element analysis (FEA). Finite element modeling (FEM) is first used to analyze an existing salient-pole synchronous generator (SPSG) from a hydroelectric power plant in Türkiye. The effects of DE faults on the SPSG’s magnetic equivalent circuit parameters are then examined under various fault severities. A …

A Deep Learning Model For Accurate Tomato Leaf Disease Identification, Maheen Shahzad, Muhammad Abdullah Javed, Erum Ashraf, Hafiz Ishfaq Ahmad, Sabeen Masood

Turkish Journal of Electrical Engineering and Computer Sciences

Recent advances in machine learning and deep learning have greatly improved how we detect plant diseases, making diagnoses more accurate, faster, and easier to scale. However, many existing solutions depend on large, pretrained models that need powerful hardware, which limits their use in the field, especially in areas with limited resources. To tackle this, we designed a custom lightweight convolutional neural network (CNN) built from scratch using 20,000 carefully selected images from the PlantVillage tomato dataset. Our model uses Squeeze-and-Excitation (SE) blocks and Swish activation functions to boost performance, reaching an accuracy of 97.7% while using far fewer computing resources …

Influence Of Sinr And Noise Variance On Outage Probability For Mimo-Noma System In 5g And Beyond, Sadiq Ur Rehman, Jawwad Ahmed, Muhammad Zubair, Syed Sajjad Hussain Rizvi

Turkish Journal of Electrical Engineering and Computer Sciences

Nonorthogonal multiple access (NOMA) communication presents a promising solution to the limitations of traditional orthogonal multiple access techniques, offering potential improvements in achievable rates. Multiple-input multiple-output (MIMO), when combined with NOMA (MIMO-NOMA), further enhances these benefits by leveraging the diversity advantages of multiple antennas. Looking ahead, the future of wireless communication hinges on deploying heterogeneous networks (HetNets), facilitating the coexistence of various wireless access networks in a hierarchical fashion. However, the advent of 5G and 6G communications brings shorter channel coherence times, rendering channel reciprocity unreliable. Consequently, conventional channel estimation methods relying on uplink (UL) pilots for downlink (DL) transmission …

A Novel Approach To Maximum Weighted Traffic Flow Method For Effective Signal Control, Zülal Hi̇lal Yildiz Budak, Seyi̇t Alperen Çeltek, Aki̇f Durdu

Turkish Journal of Electrical Engineering and Computer Sciences

Traffic signal management is a critical challenge due to its environmental, economic, and public health impacts. The maximum weighted flow method (MaxWeightedFlow) was developed to optimize traffic flow at isolated and coordinated urban intersections. This study proposes a new method, the novel MaxWeightedFlow, which includes two key strategies to enhance the classical approach. The first strategy reduces computational burden by estimating vehicle approach times based on instantaneous speeds, improving real-time performance. The second employs regression analysis to optimize the alpha parameter, representing the vehicle waiting coefficient. The proposed approach, the novel MaxWeightedFlow, was evaluated using real-world traffic data from Kilis, …

Improving Rail System Signaling Efficiency Through Ai-Based Driving Profile Generation: A Comparative Performance Analysis, Mehmet Taci̇ddi̇n Akçay, Abdurrahi̇m Akgündoğdu

Turkish Journal of Electrical Engineering and Computer Sciences

In this study, a dataset comprising 3600 discrete operational snapshots (rather than continuous time-series data) derived from real-field operations is used to obtain a high-accuracy driving profile equation using a second-degree Polynomial Regression method. This equation demonstrates the model’s interpretability. The performance metrics obtained with the second-degree polynomial regression model’s equation are as follows: a coefficient of determination (R2) of 0.84, a Pearson Correlation Coefficient of 0.91, and an RMSE of 11.13. These results indicate the effectiveness of artificial intelligence-based approaches in improving the efficiency of the railway signaling system. The same dataset is also utilized with other machine learning …

First Results On The Search For Lepton Number Violating Neutrinoless Double-Β Decay With The Legend-200 Experiment, H. Acharya, N. Ackermann, M. Agostini, A. Alexander, C. Andreoiu, G. R. Araujo, Frank Avignone Iii, M. Babicz, W. Bae, A. M. Bakalyarov, M. Balata, A. S. Barabash, C. J. Barton, L. Baudis, C. Bauer, E. Bernieri, L. Bezrukov, K. H. Bhimani, V. Biancaccu, E. Blalock, Et. Al.

Faculty Publications

The LEGEND Collaboration is searching for neutrinoless double-beta (0νββ) decay by operating high-purity germanium detectors enriched in ⁷⁶Ge in a low-background liquid argon environment. Building on key technological innovations from the GERmanium Detector Array (GERDA) experiment and the MAJORANA DEMONSTRATOR experiment, LEGEND-200 has performed a first 0νββ decay search based on 61.0 kg yr of data. Over half of this exposure comes from our highest performing detectors, including newly developed inverted-coaxial detectors, and is characterized by an estimated background level of 0.5^+0.3_−0.2 cts/(keV ton yr) in the 0νββ decay signal region. A combined …

Patent Pending: How The Current Patent Utility Requirement Hinders Biotechnological Innovation, Madison Drlik

Journal of Law and Health

The legal system is always playing catch up to adapt to new legal landscapes, doctrines, and technology; however, patent law needs help to compete with biotechnological research in the race towards innovation. Biotechnological research in the realm of human health and medicine often involves the use of therapeutic drugs. The field of healthcare biotechnology takes biological systems and processes and generates novel, creative solutions to a number of human health conditions. However, the translation process for a new drug, therapy, or process is long and expensive which requires investors to help the researchers and scientists move their creations from inception …

Evaluating The Fate And Variability Of Soil Organic Carbon And Nitrogen Species Under Conservation Practices In The Raccoon River Watershed, Zhonglong Zhang, May Wu

Civil and Environmental Engineering Faculty Publications and Presentations

This study evaluates the fate and variability of soil organic carbon (SOC) stocks and nitrogen species using the latest version of the Soil and Water Assessment Tool– Carbon (SWAT-C) and assesses how conservation practices influence their dynamics in the Raccoon River Watershed (RRW). Dominated by intensive agricultural pro- duction, the RRW is a significant contributor of sediment and nutrient loads to local rivers and the Mississippi River. This SWAT-C model simulates the export of SOC and nitrogen species and evaluates their responses under varying management scenarios. Model calibration was performed for streamflow, sediment, nitrate, total nitrogen, and organic carbon with …

Fort Hays State University Tiger Weekly, January 16, 2026, University Relations

Tiger Weekly Newsletters

No abstract provided.

Optimal Murine Cd4+ T Cell Priming By Mrna-Lipid Nanoparticle Vaccines Requires Endogenous Antigen Processing, Julia E. Rood, Suh Kyung Yoon, Mary K. Heard, Stephen D. Carro, Emma J. Hedgepeth, Mary E. O'Mara, Michael J. Hogan, Nhu Le, Hiromi Muramatsu, Kieu Lam, Petra Schreiner, Coral Kasden, Hansell H. Stedman, Ryan A. Langlois, James Heyes, Norbert Pardi, Laurence C. Eisenlohr

College of Life Sciences Faculty Papers

Lipid nanoparticle (LNP)-encapsulated nucleoside-modified mRNA vaccines elicit robust CD4+ T cell responses, yet the mechanisms underlying this T cell priming remain unknown. Antigens presented to CD4+ T cells on major histocompatibility complex class II (MHC II) are traditionally acquired by antigen presenting cells (APCs) from extracellular sources. Here we show that vaccine specific CD4+ T cell responses instead rely on antigen directly expressed within APCs, without extracellular transit. Murine APCs treated with mRNA-LNP vaccines activate T cells more efficiently when presenting antigen produced internally, rather than acquired externally. Immunization with mRNA-LNP vaccines engineered to inhibit antigen expression in APCs results …

Distribution System Reliability Evaluation Considering Protection Coordination Using Petri Nets, Rani Kumari, Bhukya Krishna Naick

Turkish Journal of Electrical Engineering and Computer Sciences

Maintaining reliable and high-quality power delivery becomes increasingly complex with expanding power grids. The lack of protection coordination poses a significant threat, compromising overall system reliability. This research addresses this challenge by proposing a method for coordinating protective devices within the distribution system, specifically during network faults. The proposed approach utilizes a stochastic timed Petri net (STPN) based methodology to model protective device coordination across various fault scenarios. This technique effectively captures the dynamic behavior and interactions of protective equipment, allowing for the anticipation of potential disturbances. This proactive insight facilitates preventative measures to address prewarning situations, thereby preventing cascading …

A Programmable Genetic Platform For Engineering Noninvasive Biosensors, Asish N Chacko, Kaamini M Dhanabalan, Jinyang Wan, Roy Chien, Nolan T Anderson, Binzhi Xu, Katie Pham, Ritu Tiwari, Arnab Mukherjee

Faculty, Staff and Student Publications

Creating genetic sensors for noninvasive visualization of biological activities in optically opaque tissues holds immense potential for basic research and the development of genetic and cell-based therapies. Magnetic resonance imaging (MRI) stands out among deep tissue imaging methods for its ability to generate high-resolution images without ionizing radiation. However, the adoption of MRI as a mainstream biomolecular technology has been hindered by the lack of adaptable methods to link molecular events with genetically encodable contrast. Here, we introduce modular aquaporin-based protease-activatable probes for enhanced reporting (MAPPER), a platform for the systematic creation of genetic sensors for MRI. To develop MAPPER, …

Ai-Enabled Decision-Support Systems In The Joint Targeting Cycle: Legal Challenges, Risks, And The Human(E) Dimension, Jessica Dorsey, Marta Bo

International Law Studies

Israel’s military campaign in Gaza as well as ongoing conflicts in Ukraine, Yemen, Iraq, and Syria include the reported military use of AI-enabled decision-support systems (AI-DSS) within the joint targeting cycle (JTC). These tools use AI techniques to collect and analyze data, provide information about the operational environment, and make actionable recommendations with the aim of aiding military decision-makers in evaluating factors relevant to legal compliance, such as taking precautions and ensuring proportionality in attacks. These systems are often touted as being simply a human aid and, as such, have flown largely under the radar regarding regulation as they are …

A Robust Deep Learning Ensemble Framework For Waterbody Detection Using High-Resolution X-Band Sar Under Data-Constrained Conditions, Soyeon Choi, Seung Hee Kim, Son V. Nghiem, Menas Kafatos, Minha Choi, Jinsoo Kim, Yangwon Lee

Institute for ECHO Articles and Research

Accurate delineation of inland waterbodies is critical for applications such as hydrological monitoring, disaster response preparedness and response, and environmental management. While optical satellite imagery is hindered by cloud cover or low-light conditions, Synthetic Aperture Radar (SAR) provides consistent surface observations regardless of weather or illumination. This study introduces a deep learning-based ensemble framework for precise inland waterbody detection using high-resolution X-band Capella SAR imagery. To improve the discrimination of water from spectrally similar non-water surfaces (e.g., roads and urban structures), an 8-channel input configuration was developed by incorporating auxiliary geospatial features such as height above nearest drainage (HAND), slope, …

Cold Atmospheric Plasma For Prostate Cancer Therapy—Potential For Clinical Translation, Shengxin Zhang, Janith Wanigasekara, Daniela Boehm, James F. Curtin, Paula Bourke, Tao Zhang, Gemma K. Kinsella

Research Outputs: 2025-Present

Cold atmospheric plasma (CAP) has potential as a new cancer treatment tool due to its room temperature biocompatibility and possible cancer cell selectivity with low side effects. This review examines the current research stage of CAP therapy for Prostate Cancer (PCa) treatment with a focus on CAP device standardization and CAP therapy clinical translation. The current CAP preclinical data is explored through the lens of PCa cellular response, PCa cells selectivity, CAP treatment type and CAP combination therapies. Finally, building on the current preclinical data, this review proposes the potential clinical application methods of CAP at different PCa stages to …