Digital Commons Network^™

Divergent Patterns Of Probabilistic Reasoning In Humans And Gpt-5, Pegah Imannezhad, Emmanuel M. Pothos, Andy J. Wills

School of Psychology

Large Language Models (LLMs) such as GPT‑5 are increasingly consulted for advice across a wide range of domains, yet little is known about how their probability judgments compare to those of humans. This study examined GPT‑5’s adherence to classical probability rules, focusing on conjunction fallacies, disjunction fallacies, and violations of binary complementarity. Using a large dataset on human probabilistic judgments, in which participants displayed multiple types of fallacies, we tested GPT‑5 on the same task and with matched participant profiles. GPT‑5 produced only single conjunction or disjunction fallacies and showed near‑perfect compliance with binary complementarity constraints. Its overall response pattern …

Ucc Minutes 3-3-26, Angela Brock

UCC Agendas/Minutes

No abstract provided.

Approved Courses 3-3-26, Angela Brock

Individual Course Committee (ICC)

No abstract provided.

Icc Agenda 3-3-26, Angela Brock

Individual Course Committee (ICC)

No abstract provided.

Walter Suarez Juarez V. Attorney General United States Of America

2026 Decisions

Agency

John Wayne V. John Wetzel

2026 Decisions

USDC for the Eastern District of Pennsylvania

The Prospector, March 3, 2026, Utep Student Publications

The Prospector

No abstract provided.

Harinder Singh V. Thomas Droppa

2026 Decisions

USDC for the District of New Jersey

Order Prohibiting Opt Out Releases

Catholic Dioceses in Bankruptcy

No abstract provided.

A New Strain-Crystallizable Rubber Via Neodymocene-Catalyzed Regio-, Stereo-, And Sequence-Selective Copolymerization Of Isoprene And Ethylene, Li Jia, Lei Zhu, Zhenxing Chen, Jingqing Lyu

University Research

An ansa-neodymocene catalyst previously reported in the literature has been identified to catalyze the title copolymerization to afford poly(1,4-trans-isoprene–ethylene) with 95% selectivity for the major microstructure. Such structural regularity is minimally required for the rubbery product, dubbed isoprene–ethylene rubber (IER), to exhibit prominent strain-induced crystallization (SIC) at 0 °C. The mechanical properties of IER rival those of natural rubber when SIC occurs. The unit cell of the strain-induced crystals is monoclinic with a = 2.21 nm, b = 0.72 nm, c = 1.30 nm, and β = 110.8°. Each unit cell is estimated to contain 12 chains in the ac …

Robots, Ledgers, And Revpar: A Blockchain-Enabled Ai–Robotics Conceptual Model For Sustainable Hotel Revenue And Asset Management, Leonard A. Jackson

Faculty Articles

Introduction: Robotics and artificial intelligence (AI) are rapidly reshaping hospitality by automating frontline and back-of-house processes, augmenting service encounters, and expanding the analytical scope of revenue management. Yet, existing research remains fragmented: service-robot studies largely emphasize adoption and human–robot interaction, while revenue-management research prioritizes pricing and distribution, sustainability research focuses on environmental practices, and hotel real-estate scholarship foregrounds governance and asset value. Meanwhile, blockchain technologies—through distributed ledgers, smart contracts, digital identity, and tokenization—offer a complementary trust and value-transfer layer that can address coordination and verification problems across hotel ecosystems (e.g., data sharing, sustainability claims, and owner–operator contracting).

Methods: Drawing on …

Influence Of Body Composition On The Efficacy Of Nivolumab Plus Ipilimumab For Metastatic Clear Cell Renal Cell Carcinoma, Kabir Grewal, Maria Julia Moura Nascimento Santos, Pankaj Kumar Chauhan, Kai Yu, Nizar M Tannir, Sagar S Mukhida, Neha Venkatesh, Amishi Y Shah, Amado J Zurita, Andrew C Johns, Matthew T Campbell, Sangeeta Goswami, Jianjun Gao, Eric Jonasch, Jennifer L Mcquade, Omar Alhalabi, Pavlos Msaouel, Andrew W Hahn

Faculty, Staff and Student Publications

Background: Immune checkpoint inhibitor therapy (ICI) with nivolumab+ipilimumab is a first-line (1L) standard for metastatic clear cell renal cell carcinoma (ccRCC), yet outcomes remain heterogeneous. Increasing evidence suggests that host factors influence the tumor microenvironment and response to ICI. Although higher body mass index (BMI) has been associated with improved outcomes in several malignancies, BMI is an imprecise surrogate for underlying adipose and muscle compartments. We evaluated the association between body composition and outcomes with 1L nivolumab+ipilimumab in metastatic ccRCC.

Methods: We retrospectively analyzed patients with mccRCC treated with 1L nivolumab+ipilimumab at MD Anderson Cancer Center between June 2015 and …

Inductive Transducers For Measuring Vibrations, S.F. Amirov, A.Kh. Sulliev, A.A. Shoimkulov

Chemical Technology, Control and Management

A new design of an induction transducer has been developed for measuring linear and torsional vibrations in different directions with high sensitivity by constructing an inertial element consisting of four mutually perpendicular sectors and making the masses of two adjacent sectors different from the masses of the other two adjacent sectors. By constructing an inertial element in the form of a sector with two mutually diametric magnetic cores and different masses, and placing it between the horizontal and vertical axes, a design of an induction transducer has been developed that highly sensitively measures linear and torsional vibrations in different directions, …

The Main Errors Of The Ultrasonic Sensor In Measuring Water Flow In Open Channels, Anvar Urolovich Djalilov

Chemical Technology, Control and Management

This article analyzes the use of ultrasonic sensors in measuring water flow and the main errors that may occur in this process. In the conducted scientific research, a time-pulse ultrasonic sensor was tested. The absolute, relative and repeatability errors of the sensor during water flow measurement were studied. The absolute error represents the largest difference between the value recorded by the sensor and the real value, affecting the overall accuracy of the measurement system. This error can vary depending on environmental factors, the design and operating principles of the sensor. During the experiment, the performance of this sensor was …

Proteomic Profiling Of Pulmonary Function And Cardiovascular Disease Risk In The Atherosclerosis Risk In Communities Study, Yura Lee, Astrid M Manuel, Ngoc Quynh H Nguyen, Christine Ladd-Acosta, Alanna C Morrison, Kari E North, Eric Boerwinkle, Amil M Shah, Zhongming Zhao, Stephanie J London, Bing Yu

Faculty, Staff and Student Publications

Background: Pulmonary function is linked to cardiovascular disease risk; however, the underlying mechanisms remain unclear. We aimed to identify protein biomarkers associated with pulmonary function and examine their impact on incident chronic obstructive pulmonary disease, coronary heart disease, heart failure, and all-cause mortality.

Methods: Data from White and Black Americans in the Atherosclerosis Risk in Communities study (visit 2: N=11 354, mean age=57 years; visit 5: N=3517, mean age=75 years), a prospective cohort, were analyzed. Linear regression assessed associations between protein levels and pulmonary function measures, including forced expiratory volume in 1 second and forced vital capacity. The impact of …

Spartan Daily, March 3, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 166, Issue 17

Clinical Validation Of Perfusion Imaging With Pulmonary Function Test Data Using Voronoi-Based Discretization, Jorge Cisneros, Caleb J. Herrera, Yi-Kuan Liu, Lisa V. Du, Yevgeniy Vinogradskiy, Richard Castillo, Girish Nair, Edward Castillo

Department of Medicine Faculty Papers

Objective.Accurate lung function assessment is essential for diagnosing and managing diseases like chronic obstructive pulmonary disorder, pulmonary emboli, and lung cancer. Single-photon emission computed tomography (SPECT) provides valuable 3D functional imaging of ventilation and perfusion, but is limited by low spatial resolution, availability, additional radiation, and cost. Alternative methods, including CT-based perfusion (CT-P) and deep learning models, require large datasets to validate results that are often scarce. Pulmonary function tests (PFTs) offer rapid and noninvasive global lung function measures and are clinically widely used. While ventilation correlates well with PFTs, perfusion imaging presents challenges due to complex blood flow and …

Association Between Functional Status And Cardiac Function In Chronic Heart Failure: Insights From The C-Mic Ii Trial., Marat Fudim, Tamara Kovacevic-Preradovic, Marija Zdravkovic, Sasko Jovev, Nermir Granov, Tanja Popov, Igor Rudez, Petar Vukovic, Velibor Ristic, Annette Holtdirk, Muhammad Shahzeb Khan, Faouzi Kallel, Miodrag Peric, Javed Butler, Stefan D. Anker, Dragana Kosevic, J. Eduardo Rame

Department of Medicine Faculty Papers

INTRODUCTION: Relationship between changes in cardiac function, functional capacity, and patient-reported health status in heart failure (HF) remains incompletely defined, which may help inform endpoint selection and clarify how distinct clinical domains reflect treatment response.

METHODS: This post hoc analysis of the randomized cardiac microcurrent (C-MIC) II trial, which evaluated the efficacy and safety of C-MIC therapy in patients with chronic HF with reduced ejection fraction on optimal guideline-directed medical therapy, included 65 ambulatory patients with non-ischaemic dilated cardiomyopathy, New York Heart Association (NYHA) Class III-IV symptoms, and baseline left ventricular ejection fraction (LVEF) 25-35%. Correlations between changes in Kansas …

Pharmacologic And Oncohistone Inhibition Of Setd2 Converge On Genomic Instability, Alyssa T Paparella, Ashley G Boice, In Young Park, Rajkishor Nishad, Durga Tripathi, Seth A Nelson, Edward W Pietryk, H Josh Jang, Ian J Frew, W Kimryn Rathmell, Frank M Mason, Cristian Coarfa, Ruhee Dere, Cheryl Lyn Walker

Faculty, Staff and Students Publications

Background/objectives: SETD2 is a dual-function methyltransferase important for methylation of histone H3 at lysine 36 and α-tubulin in spindle microtubules. Genetic inactivation of SETD2 during oncogenesis drives loss of H3K36me3, genomic instability, and cancer progression. This study asked if disruption of genomic stability was a canonical feature of SETD2 inactivation via different pathways.

Methods: We evaluated the impact of EPZ-719, a pharmacologic SETD2 inhibitor, and an H3.3K36M mutant histone ("oncohistone") that binds and sequesters SETD2, on methylation activity and genomic stability in human cell lines. SETD2 activity was measured using in vitro methylation assays, H3K36me3 loss confirmed by Western analysis, …

Self-Aware Quantum-Inspired Routing Framework For 6g And Quantum Networks, Haitham M. Abdelghany, Mohamed M. Ashour

Mansoura Engineering Journal

This paper introduces a quantum-hybrid-aware routing framework that incorporates the concepts of quantum computing with meta-cognitive learning to improve adaptability, reliability, and awareness in dynamic quantum networks. The proposed system accommodates a new IoT, edge computing and 6G system, where routing schemes should be flexible and robust and have cross-topology functionality. Conventional methods of quantum reinforcement learning can be characterized by a trade-off between exploration and decision stability. To cope with this, the proposed self-aware hybrid architecture is a combination of quantum-enhanced learning and a meta-cognitive awareness layer to allow autonomous agents to monitor performance and adjust routing strategies on …

Integrated Simulation-Based Optimisation Of Rocket Launch Dynamics For Enhanced Fuel Efficiency And Payload Precision, Syahir Amzar Zulkifli, Rizalman Mamat, Erdiwansyah Erdiwansyah, S. M. Rosdi, Ahmad Tamimi, Ahmad Fitri Yusop

Terra Joule Journal

Precision in launch dynamics and trajectory optimisation is critical for enhancing mission success, fuel efficiency, and payload capacity in modern aerospace operations. This study aims to develop and validate a high-fidelity, simulation-based framework for optimising rocket ascent trajectories, providing a cost-effective, scalable alternative to extensive physical testing. The methodology integrates ANSYS Fluent for aerodynamic and thermal load modelling, MATLAB/Simulink for dynamic control system simulation, and General Mission Analysis Tool (GMAT) for orbital trajectory planning, enabling a multi-domain approach that accounts for thrust vectoring, aerodynamic drag, stage separation, and environmental disturbances. Optimisation algorithms, the Genetic Algorithm (GA) and Particle Swarm Optimisation …

Cfd Simulation Of The Influence Of The Inflow Guided Baffles On Photovoltaic Cooling Thermal Performance, Hussein A. Jaffar, Ali A. Ismaeel, Ahlam Luaibi Shuraiji

Terra Joule Journal

This study presents a comprehensive investigation into enhancing the thermal performance of photovoltaic (PV) modules through the integration of inflow-guided cooling baffles, using a validated 3D CFD model developed in ANSYS Fluent 2020 R1. The simulations were performed under a solar heat flux of 850 W/m², an inlet air velocity of 2.5 m/s, and a Reynolds number of 1.2× 10⁴, while four configurations were examined: a baseline PV module without baffles, a vertical-guide model reported in previous studies, and three novel nozzle-type inflow guides positioned at 45°, 30°, and 25°. Experimental validation conducted under controlled environmental …

Intelligent Fault Diagnosis Of Ev Induction Motors Using Multi-Sensor Ann And Explainable Ai For Sustainable Transportation, Royal Madan, Ahmed Ali Farhan Ogaili

Terra Joule Journal

Maintaining the dependability and operational continuity of electric vehicle (EV) drivetrains has become crucial as the world's shift to electrified transportation picks up speed. This is a major obstacle for sustainable mobility. Using a high-capacity Artificial Neural Network (ANN), this study presents a data-driven multi-sensor framework for advanced fault diagnosis of induction motors in EV applications. The publicly available University of Ottawa dataset that encompasses nine distinct fault categories and 180 test samples was utilized to replicate both mechanical failure modes (e.g., broken rotor bars, bearing defects, rotor misalignment) and electrical anomalies (e.g., stator winding faults, voltage imbalance) under constant …

Reducing The Surface Roughness Of Curvature Surfaces By Electrical Discharge Machining With Magnetic Abrasive Finishing, Shahad Taqi, Saad Shather, Wisam Hamdan

Engineering and Technology Journal

This study presents an integrated work that combines unconventional machining and finishing techniques for complex geometric models. A Taguchi design investigated three electrical-discharge parameters—electric current, pulse duration, and gap—each at three levels; a multi-objective optimization matrix was then used to select the optimal conditions. The geometric models were designed using SolidWorks software and machined on a CNC machine to ensure maximum accuracy in the resulting samples. The samples were finished using the magnetic abrasive finishing technique, where the particle mixture was developed as a hybrid blend of two types of abrasive particles, tungsten carbide (WC) and silicon carbide (SiC). Among …

Parametric Evaluation And Biomechanical Assessment Of A Curved Biodegradable Zk60 Locking Plate For Femoral Shaft Fractures Using Finite Element Analysis, Ahmad Jasim, Jenan Kashan, Aseel Abed

Engineering and Technology Journal

This study evaluates the biomechanical performance of a novel curved biodegradable ZK60 magnesium alloy locking plate for plate osteosynthesis in midshaft femoral fractures classified as AO/ASIF 32-A3 (Arbeitsgemeinschaft für Osteosynthesefragen/Association for the Study of Internal Fixation). Current metallic implants are associated with complications such as stress shielding, the need for secondary surgery, and limited support for biological healing. Biodegradable options offer promising solutions but remain insufficiently studied, especially regarding curved plate designs. This work addresses that gap by systematically assessing how plate thickness and curvature influence fracture stability. Finite element analysis (FEA) was performed under physiological loading of 700 N …

A Segmentation Of Buildings From Multi-Scene Drone Images Using Deep Learning Models: Case Study- A Car Multi-Story Garage In The Camp Of The University Of Technology, Akram Jalil, Imzahim Alwan

Engineering and Technology Journal

Accurate building segmentation is essential for urban planning, monitoring, and mapping. Most deep learning approaches rely on single-view images, limiting segmentation accuracy due to the loss of spatial context. This re-search proposes a multi-view deep learning framework that integrates features extracted from four pre-trained CNN models—MobileNetV2, Res-Net50, VGG16, and InceptionV3—to capture multi-angle and multi-scale details. A vision transformer is employed to fuse and refine these features, enhancing global context and boundary precision. The proposed method was evaluated using UAV imagery of a multi-story garage at the University of Technology, captured by a DJI Mavic 2 Pro with a high-resolution Hasselblad …

Prediction Of Reconnaissance Drought Index And Standardized Precipitation Index For Drought Analysis, Zahraa Kadhum, Amjed Alhameedawi, Mustafa Hamoodi

Engineering and Technology Journal

Drought is a natural disaster characterized by its intensity, duration, and spatial extent. This research investigates meteorological drought in Babylon Province, Iraq, highlighting its significance in the local context, particularly given the region's vulnerability to climatic changes. Employing the Drought Index Calculator (Drin C), we evaluate drought indices, namely the Reconnaissance Drought Index (RDI) and the Standard Precipitation Index (SPI), from 1991 to 2021. This study underscores the imperative of assessing the accuracy of commonly used drought monitoring techniques due to their inherent uncertainties. This work highlights the importance of integrating advanced modelling tools, such as the integration of advanced …

An Artificial Neural Network Model Prediction Of Mortar Strengths Reinforced With Henequen And Sisal Fibres For Sustainable Construction, Akintayo Adeniji, Williams Kupolati, Everardt Burger, Mueez Are, Jacques Snyman, Julius Ndambuki, Chris Ackerman

Engineering and Technology Journal

The increasing demand for sustainable building materials has spurred interest in using natural fibers for construction. This study evaluates the performance of henequen and sisal fibers in mortar to enhance their tensile properties and provide alternatives to synthetic fibers. Mortar samples were prepared using a 1:3 mix ratio, with fibers introduced at 0%, 0.5%, 1%, 1.5%, and 2% by weight. The particle size distribution, setting times, consistency, and water ab-sorption and tensile strength of mortar constituents and fibers were determined. Compressive and splitting tensile strength tests were conducted on samples of 75 mm cubes and 50 × 100 mm cylinders …

Moment-Curvature Relations Of Fiber-Reinforced Concrete-Encased Cfst Beams, Raad Abdulkhudhur, Hussein Al-Quraishi, Mohammed Elwi

Engineering and Technology Journal

A concrete-filled steel tube surrounded by external concrete is a composite element known as a concrete-encased concrete-filled steel tube (CFST). This composite element is used in multi-story buildings, large-span constructions, bridges, and underground transit stations. This research examined the curvature behavior of fiber-reinforced concrete-encased CFST beams. Eight concrete-encased CFST beams and one conventional beam were subjected to four-point loads during testing. The factors examined were shear connection, section size, CFST ratio, outer concrete compressive strength, compressive strength of concrete inside the steel tube, steel fiber content, and unfilled steel tubes. Curvature is an important factor that determines the adequacy of …

The Effect Of Synthetic Minority Oversampling For Enhancing Brain Tumor Image Classification, Farah Fadhil, Zainab Sultani

Engineering and Technology Journal

Brain tumors are among the most serious neurological diseases, posing significant diagnostic challenges due to their diverse nature and complexity imbalance in medical imaging datasets. To address these challenges, machine learning (ML) has demonstrated high potential in brain tumor classification; nevertheless, its overall performance can suffer when minority classes are underrepresented. This study examines the impact of the Synthetic Minority Over-sampling Technique (SMOTE) on MRI brain tumor classification using handcrafted features, including Gray Level Co-occurence Matrix (GLCM), Histogram of Oriented Gradients (HOG), and their combination (HOG + GLCM), with three classifiers, namely, Logistic Regression (LR), Support Vector Machines (SVM), and …