Digital Commons Network^™

Mapping The Structural Connections Between The Anterior Cingulate Cortex And The Insula/Ventrolateral Prefrontal Cortex.Mapping The Structural Connections Between The Anterior Cingulate Cortex And The Insula/Ventrolateral Prefrontal Cortex, Wei Tang, Javier Guaje, Shreyas Fadnavis, Sarah R Heilbronner, Eleftherios Garyfallidis

Faculty, Staff and Students Publications

The anterior cingulate cortex (ACC) is functionally closely related with the insula and the ventral lateral prefrontal cortex (vlPFC). The ACC and insula are the main hubs of the salience network, a set of functionally related brain regions involved in detecting salient stimuli and coordinating inter-network communication, while communication between ACC and vlPFC is closely linked to inhibitory control. However, despite strong indirect evidence from nonhuman primate (NHP) tract tracing, the structural connections between the ACC and the insula/vlPFC remain poorly understood in the human brain, in part because standard approaches fail to capture this projection. In this study, we …

Age-Related Variations Of The Hemodynamic Response Function Spatially Resolved Across Human Cerebral Cortex, Nooshin J Fesharaki, Amanda Taylor, David Ress

Faculty, Staff and Students Publications

Normal aging leads to regional vascular and neural alterations. Age-related impairments in neurovascular coupling (NVC) affect the blood-oxygen-level-dependent (BOLD) hemodynamic response function (HRF) measured with functional magnetic resonance imaging, causing changes in both amplitude and temporal dynamics. Previously, global, systematic age-related changes in HRF characteristics were demonstrated, consistent with known microvascular aging effects. In this follow-up study, a standard space was used to compare spatially resolved cortical HRF dynamics between sex-balanced groups of young and older adults. The results showed substantial age-related differences in both HRF amplitude and timing across distinct cortical regions. Nearly twice as much cortical area exhibited …

A Rare Case Of Eosinophilic Granulomatosis With Polyangiitis Following Development Of Central Diabetes Insipidus: A Case Report And Literature Review, Tatsuaki Kosaka, Shinya Yamamoto, Naoko Yasugi, Sayaka Sugioka, Takuro Hakata, Rintaro Saito, Ryosuke Hiwa, Sho Koyasu, Yuki Teramoto, Motoko Yanagita

Faculty, Staff and Students Publications

Central diabetes insipidus (CDI) can develop as an acquired systemic disease. However, cases of eosinophilic granulomatosis with polyangiitis (EGPA) with concurrent CDI are rare. We herein report a case of EGPA following CDI. A 68-year-old woman with a 30-year history of sinusitis and asthma developed CDI, followed by severe renal dysfunction with eosinophilia and elevated myeloperoxidase-antineutrophil cytoplasmic antibody levels. A renal biopsy confirmed EGPA. Intensive treatment resulted in dialysis discontinuation, while partial improvement in arginine vasopressin secretion suggested a potential link between EGPA and CDI. We also conducted a literature review on concurrent EGPA and CDI. Clinicians should be aware …

Streamlining Eligibility Assessment For Alzheimer’S Disease-Modifying Therapies: Prediction Of Mmse Scores Using The Digital Clock And Recall, Ali Jannati, Claudio Toro-Serey, Marissa Ciesla, Emma Chen, John Showalter, David Bates, Alvaro Pascual-Leone, Sean Tobyne

Faculty, Staff and Students Publications

           Introduction: The eligibility of anti-amyloid disease-modifying therapies (DMTs) and their integration into clinical practice in some institutions requires a specific range of Mini-Mental State Examination (MMSE) scores. Reliance on this pencil-and-paper psychometric instrument imposes operational burdens and risks of perpetuating health disparities, given the test's known educational and cultural biases. This study evaluates the efficacy of the Digital Clock and Recall (DCR™)-a rapid, FDA-listed digital cognitive assessment-to crosswalk to MMSE scores using machine learning, thereby offering a faster, scalable, and equitable mechanism for patient triage.

Methods: We conducted a retrospective analysis using data from the multi-site Bio-Hermes-001 (BH) study ( …

Performance And Improvement Strategies For Adapting Generative Large Language Models For Electronic Health Record Applications: A Systematic Review, Xinsong Du, Zhengyang Zhou, Yifei Wang, Ya-Wen Chuang, Yiming Li, Richard Yang, Pengyu Hong, David W Bates, Li Zhou

Faculty, Staff and Students Publications

Purpose: To synthesize performance and improvement strategies for adapting generative LLMs in EHR analyses and applications.

Methods: We followed the PRISMA guidelines to conduct a systematic review of articles from PubMed and Web of Science published between January 1, 2023 and November 9, 2024. Multiple reviewers including biomedical informaticians and a clinician involved in the article reviewing process. Studies were included if they used generative LLMs to analyze real-world EHR data and reported quantitative performance evaluations for an improvement technique. The review identified key clinical applications, summarized performance and the improvement strategies.

Results: Of the 18,735 articles retrieved, 196 met …

Supersonic Wind Tunnel Free Stream Turbulence Characterization Using 2-Point Focused Laser Differential Interferometry, Joseph Villarreal, Joshua Gary, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Non-intrusive laser-based diagnostics, such as Two-Point Focused Laser Differential Interfer-ometry (2-FLDI), play a crucial role in modern aerodynamic research by enabling simultaneous measurements of density and velocity in compressible flows. A 2-FLDI system has been developed and implemented for the Missouri S&T Supersonic Wind Tunnel to characterize free stream turbulence fluctuations and free stream convective velocity. Design choices that enabled the 2-FLDI to overcome low turbulence to measure free stream velocity are detailed. The free stream velocity measurements are validated against previous particle image velocimetry data, showing good agreement. Analysis of normalized velocities and density-based turbulence intensities found that the …

2-Point Focused Laser Differential Interferometry Measurements Of A Parallel Jet In Supersonic Flow, Joshua Gary, Joseph Villarreal, Davide Vigano

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Turbulence in compressible flows plays a central role in applications such as air-fuel mixing in supersonic combustors and is significantly more complex than incompressible turbulence due to the presence of fluctuating thermodynamic quantities. As such, models like the Strong Reynolds Analogy (SRA) are used to relate these quantities. However, SRA validity has been examined primarily in boundary-layer flows. In this work, a newly developed Two-Point Focused Laser Differential Interferometry (2-FLDI) system is implemented in a two-dimensional parallel supersonic jet. The diagnostic is described in detail, including optical alignment procedures, calibration methods, and data analysis techniques. Measurements acquired at multiple streamwise …

2027 4-H National Conference Application, Kristen Landau, Kristen Lyons

UNH Cooperative Extension

No abstract provided.

Associations Of Blood Pressure Level And Variability With Cortical Thickness: A Cross-Sectional Analysis From The Maracaibo Aging Study, Romeo De Leon, Shana Garza, Silvia Mejia-Arango, Kristina Vatcheva, Sokratis Charisis, Claudia L. Satizabal, Luis J. Mena, Joseph H. Lee, Joseph D. Terwilliger, Eron Manusov

School of Medicine Publications

Background: Although high blood pressure (BP) level and variability are associated with Alzheimer's Disease (AD), their relationship with cortical thickness in brain regions that are associated with AD is unclear. Furthermore, the role of 24-hour BP has not been examined. We investigated the associations of office and ambulatory BP measures with cortical thickness in brain regions implicated in AD.

Methods: We performed a cross sectional analysis of 304 participants without dementia from a population-based study with office and 24-hour BP and magnetic resonance imaging (MRI) data. We considered cortical thickness values derived from 10 regions throughout the frontal, parietal, and …

Nh 4-H Horse Quiz Bowl Packet, Unh Cooperative Extension

UNH Cooperative Extension

No abstract provided.

Nh 4-H Livestock Quiz Bowl Packet, Unh Cooperative Extension

UNH Cooperative Extension

No abstract provided.

Stolen Childhood: Picture Book Stories Of Indian Residential Schools, Maughn Rollins Gregory

Picture Books

In the nineteenth and twentieth centuries American and Canadian government agencies and Christian churches established Indian residential schools where hundreds of thousands of children were “reeducated” in English and Christianity. They were not allowed to use their native languages or given names, to practice their religions, or to communicate with their siblings or parents. They were made to work in crop fields, kitchens, laundries, and industrial workshops. Many were physically and sexually abused. Many never saw their families again. The nine picture books reviewed here are accounts of survivors of residential schools from eight different Indigenous nations. In addition to …

Shin-Chi’S Canoe (2008) By Nicola Campbell, Maughn Rollins Gregory

Picture Books

In the nineteenth and twentieth centuries American and Canadian government agencies and Christian churches established Indian residential schools where hundreds of thousands of children were “reeducated” in English and Christianity. They were not allowed to use their native languages or given names, to practice their religions, or to communicate with their siblings or parents. They were made to work in crop fields, kitchens, laundries, and industrial workshops. Many were physically and sexually abused. Many never saw their families again. The nine picture books reviewed here are accounts of survivors of residential schools from eight different Indigenous nations. In addition to …

Muinji’J Asks Why (2022) By Shanika Maceachern And Breighlynn Maceachern, Maughn Rollins Gregory

Picture Books

In the nineteenth and twentieth centuries American and Canadian government agencies and Christian churches established Indian residential schools where hundreds of thousands of children were “reeducated” in English and Christianity. They were not allowed to use their native languages or given names, to practice their religions, or to communicate with their siblings or parents. They were made to work in crop fields, kitchens, laundries, and industrial workshops. Many were physically and sexually abused. Many never saw their families again. The nine picture books reviewed here are accounts of survivors of residential schools from eight different Indigenous nations. In addition to …

Identifying The Best Cutoff Value Of The Fecal Occult Blood Immunochemical Test In The Detection Of Advanced And Neoplastic Colorectal Lesions [Identificación Del Mejor Punto De Corte De La Prueba Inmunoquímica De Sangre Oculta En Heces En La Detección De Lesiones Colorrectales Avanzadas Y Neoplásicas], Patricia Gaggero, Eduardo Fenocchi, Cecilia Silva, Juan C. Lopez-Alvarenga, Natalia Lambert, Fabian Batista, Sergio Sobrino-Cossio, Jonathan R. White, Adolfo Parra-Blanco

School of Medicine Publications

Objective: Screening is an effective tool for detecting colorectal lesions in asymptomatic subjects. There is a positive correlation between fecal immunochemical test (FIT) values and the size of tumors. Despite the efficacy of screening, the detection of colorectal cancer (CRC) remains low. The primary objective was to evaluate the best FIT cutoff value for detecting advanced adenomas and CRC among individuals at average risk in a country with a high incidence and morbidity from CRC.

Methods: This observational and prospective study analyzed consecutive cases in 1461 asymptomatic subjects with a positive FIT (≥ 100 ng hemoglobin [Hb]/ mL) referred for …

Large Language Models For Neurology: A Mini Review, Donald C. Wunsch, Daniel B. Hier

Electrical and Computer Engineering Faculty Research & Creative Works

Large language models have the potential to transform neurology by augmenting diagnostic reasoning, streamlining documentation, and improving workflow efficiency. This Mini Review surveys emerging applications of large language models in Alzheimer's disease, Parkinson's disease, multiple sclerosis, and epilepsy, with emphasis on ambient documentation, multimodal data integration, and clinical decision support. Key barriers to adoption include bias, privacy, reliability, and regulatory alignment. Looking ahead, neurology-focused language models may develop greater fluency in biomedical ontologies and FHIR standards, improving data interoperability and supporting more seamless collaboration between clinicians and AI systems. Two future developments have the potential to be particularly impactful: (1) …

Mitigating Hysteresis In Metal-Coated Fibers Via Optimized Thermal Treatment For Advanced Distributed High-Temperature Sensing Applications, Koustav Dey, Rony Kumer Saha, Bohong Zhang, S. Narasimman, Farhan Mumtaz, Jeffrey D. Smith, Rex E. Gerald, Ronald J. O'Malley, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Metal-coated optical fibers are widely employed in sensing applications owing to their superior mechanical strength and corrosion resistance. However, their calibration at elevated temperatures is hindered by hysteresis, manifested as discrepancies between heating and cooling cycles, primarily caused by residual strain from mismatched thermal expansion coefficients (TECs) between the metal coating and silica cladding. This research introduces an optimal heat treatment procedure aimed at minimizing the impact of the mismatch in TECs between the cladding and the coating materials that causes the residual strain in gold (Au) and copper (Cu) coated fibers for achieving reliable distributed high temperature sensing up …

Evaluation Of Multiple Generative Large Language Models On Neurology Board-Style Questions, Mohammad Almomani, Vijaya Valaparla, James Weatherhead, Xiang Fang, Alok Dabi, Chih Ying Li, Peter Mccaffrey, Dan Hier, Jorge Mario Rodríguez-Fernández

Electrical and Computer Engineering Faculty Research & Creative Works

Objective: To compare the performance of eight large language models (LLMs) with neurology residents on board-style multiple-choice questions across seven subspecialties and two cognitive levels. Methods: In a cross-sectional benchmarking study, we evaluated Bard, Claude, Gemini v1, Gemini 2.5, ChatGPT-3.5, ChatGPT-4, ChatGPT-4o, and ChatGPT-5 using 107 text-only items spanning movement disorders, vascular neurology, neuroanatomy, neuroimmunology, epilepsy, neuromuscular disease, and neuro-infectious disease. Items were labeled as lower- or higher-order per Bloom's taxonomy by two neurologists. Models answered each item in a fresh session and reported confidence and Bloom classification. Residents completed the same set under exam-like conditions. Outcomes included overall and …

Safe Optimal Control Framework For Cooperative Manipulation Of Objects In Human–Robot Teams, Irfan Ganie, Sarangapani Jagannathan

Electrical and Computer Engineering Faculty Research & Creative Works

This article introduces a distributed deep neural network (NN)-based adaptive control framework for cooperative object manipulation in human–robot teams with unknown agent dynamics by using three distinct multilayer NN observers (MNNOs). The first observer, termed the reference point estimator, enables each robotic agent to estimate the object's reference center using consensus-based learning, even without direct access to global reference trajectories. The second observer, referred to as the human force-to-trajectory estimator, uses human-applied forces to infer the intended position, velocity, and acceleration of the object, enabling real-time estimation of human intent. Together, these two observers allow distributed estimation of human-intended motion. …

Integrating Optical And Radiofrequency Interferometry For Enhanced Phase Sensing, Ruimin Jie, Zhaopeng Zhang, Chen Zhu, Jie Huang

Electrical and Computer Engineering Faculty Research & Creative Works

Interferometry is a crucial investigative technique used across diverse fields to achieve high-precision measurements. It works by analyzing the phase difference between two interfering waves, which results from variations in optical path lengths within an interferometer. We introduce a novel method for directly measuring changes in the phase difference within an optical interferometer, importantly, with the added advantage of a controllable enhancement factor. This approach is achieved through a two-step process: first, the optical phase difference is encoded into a sub-GHz radiofrequency (RF) signal using microwave-photonic manipulation; then, RF interferometry-assisted phase amplification is implemented at the destructive interference point. In …

Enhancing Measurement Accuracy: The Impact Of Missing Data On Parameter Estimation In Mass-Spring-Damper Systems, Michkath Omanda Bouraima, Steven Thompson, Maciej J. Zawodniok

Electrical and Computer Engineering Faculty Research & Creative Works

In sensor-driven dynamic systems, missing data can severely degrade parameter estimation accuracy. This article investigates the impact of missing data on phase estimation in a mass-spring-damper system using an information-theoretic framework based on the Cramér-Rao Lower Bound (CRLB). Closed-form CRLB expressions are derived for four scenarios: complete data, missing completely at random (MCAR) deletion, MCAR-based imputation, and missing at random (MAR) missingness via a selection-weighted formulation. These bounds are used as theoretical benchmarks to evaluate classical imputation methods (last observation carried forward (LOCF), linear interpolation) and advanced approaches (Kalman filtering, Rauch-Tung-Striebel (RTS) smoothing, Bayesian inference, and transformer-based imputation) through Monte …

Rf-Attennet: A Hybrid Attention-Enhanced Network For Mixed Signal Classification In Uav Swarm Detection, Prajoy Podder, Mohammad Atikur Rahman, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

The continuous increase of UAVs, particularly in swarms, creates significant challenges for security and airspace regulation. Traditional RF fingerprinting methods struggle to detect and classify UAV swarms due to overlapping signals and interference. This study introduces RF-AttenNet, a hybrid deep learning model designed to classify mixed UAV signals by analyzing composite RF spectrograms. RF-AttenNet uses dual attention mechanisms, channel and spatial attention to focus on critical spectral features, enabling the model to effectively separate and identify overlapping UAV signals. We have developed custom composite UAV datasets that simulate real-world swarm interference, incorporating both single and mixed UAV classes. RF-AttenNet achieves …

Transformer-Customer Relationship Identification Based On Load-Switching Fluctuation Characteristics Considering Same-Feeder-Adjacent-Transformer Condition, Yanan Zhang, Gan Zhou, Yuyuan Liu, Wei Gu, Yanjun Feng, Yujue Wang, Rui Bo

Electrical and Computer Engineering Faculty Research & Creative Works

Accurately identifying the connectivity between transformers and downstream three-phase customers in low-voltage distribution networks is challenging, because voltage curves of different phases and nearby nodes can be weakly distinguishable, especially when adjacent transformers on the same feeder serve geographically close customers with highly similar voltage curves. This paper proposes a novel method based on load-switching fluctuation characteristics recorded by smart meters. By extracting localized current and voltage fluctuations and establishing correlation matching, the method overcomes the limited discriminability using steady-state measurements. The method operates in two stages: first, switching-induced fluctuation characteristics are extracted and matched to cluster customers by the …

Deep Learning Based High-Resolution Electromagnetic Inversion Imaging Using Deep Convolutional Double-Module Structure, He Ming Yao, Shiji Song, Lijun Jiang, Michael Ng

Electrical and Computer Engineering Faculty Research & Creative Works

In this paper, a novel deep learning (DL) approach has been proposed to realize high-resolution electromagnetic (EM) inversion imaging. The newly proposed approach is based on the deep convolutional double-module structure (DCDMS), consisting of the pixel-interpolating module and the corresponding quality-improving module. While the pixel-interpolating module roughly increases the 'resolution' of the initial input, the following quality-improving module realizes quantitative EM imaging in high resolution. The input of the proposed DCDMS adopts the mixed input scheme, consisting of the received EM scattered field and the initial reconstruction in much low resolution computed from Gauss-Newton method. The output of the proposed …

Genome-Wide Gene-Sleep Interaction Study Identifies Novel Lipid Loci In 732,564 Participants, Raymond Noordam, Wenyi Wang, Pavithra Nagarajan, Heming Wang, Michael R Brown, Amy R Bentley, Qin Hui, Aldi T Kraja, John L Morrison, Jeffrey R O'Connel, Songmi Lee, Karen Schwander, Traci M Bartz, Lisa De Las Fuentes, Mary F Feitosa, Xiuqing Guo, Xu Hanfei, Sarah E Harris, Zhijie Huang, Mart Kals, Christophe Lefevre, Massimo Mangino, Yuri Milaneschi, Peter J Van Der Most, Natasha L Pacheco, Nicholette D Palmer, Varun Rao, Rainer Rauramaa, Quan Sun, Yasuharu Tabara, Dina Vojinovic, Yujie Wang, Stefan Weiss, Qian Yang, Wei Zhao, Wanying Zhu, Md Abu Yusuf Ansari, Hugues Aschard, Pramod Anugu, Themistocles L Assimes, John Attia, Laura D Baker, Christie Ballantyne, Lydia Bazzano, Eric Boerwinkle, Brain Cade, Hung-Hsin Chen, Wei Chen, Yii-Der Ida Chen, Zekai Chen, Kelly Cho, Ileana De Anda-Duran, Latchezar Dimitrov, Anh Do, Todd Edwards, Tariq Faquih, Aroon Hingorani, Susan P Fisher-Hoch, J Michael Gaziano, Sina A Gharib, Ayush Giri, Mohsen Ghanbari, Hans Jörgen Grabe, Mariaelisa Graff, C Charles Gu, Jiang He, Sami Heikkinen, James Hixson, Yuk-Lam Ho, Michelle M Hood, Serena C Houghton, Carrie A Karvonen-Gutierrez, Takahisa Kawaguchi, Tuomas O Kilpeläinen, Pirjo Komulainen, Henry J Lin, Gregorio V Linchangco, Annemarie I Luik, Jintao Ma, James B Meigs, Joseph B Mccormick, Cristina Menni, Ilja M Nolte, Jill M Norris, Lauren E Petty, Hannah G Polikowsky, Laura M Raffield, Stephen S Rich, Renata L Riha, Thomas C Russ, Edward A Ruiz-Narvaez, Colleen M Sitlani, Jennifer A Smith, Harold Snieder, Tamar Sofer, Botong Shen, Jingxian Tang, Kent D Taylor, Maris Teder-Laving, Rima Triatin, Michael Y Tsai, Henry Völzke, Kenneth E Westerman, Rui Xia, Jie Yao, Kristin L Young, Ruiyuan Zhang, Alan B Zonderman, Xiaofeng Zhu, Jennifer E Below, Simon R Cox, Michelle Evans, Myriam Fornage, Ervin R Fox, Nora Franceschini, Sioban D Harlow, Elizabeth Holliday, M Arfan Ikram, Tanika Kelly, Timo A Lakka, Deborah A Lawlor, Changwei Li, Ching-Ti Liu, Reedik Mägi, Alisa K Manning, Fumihiko Matsuda, Alanna C Morrison, Matthias Nauck, Kari E North, Brenda Wjh Penninx, Michael A Province, Bruce M Psaty, Jerome I Rotter, Tim D Spector, Lynne E Wagenknecht, Ko Willems Van Dijk, Lifelines Cohort Study, Million Veteran Program, Cashell E Jaquish, Peter Wf Wilson, Patricia A Peyser, Patricia B Munroe, Paul S De Vries, W James Gauderman, Yan V Sun, Han Chen, Clint L Miller, Thomas W Winkler, Dabeeru C Rao, Susan Redline, Diana Van Heemst

Faculty, Staff and Student Publications

Background and aims: Deviations from the population mean in sleep duration have been associated with increased risk for developing dyslipidemia and atherosclerotic cardiovascular disease, but the mechanism of effect is poorly characterized. We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets.

Methods: We collected data from 55 cohorts with a combined sample size of 732,564 participants (87 % European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) …

Spatial Evolution In Temporal Dynamics Of Hemodynamic Response Function In Human Superior Colliculi With Ultra-High-Resolution Mri At 9.4t, Nooshin J Fesharaki, Artemy Vinogradov, David Ress, Jung Hwan Kim

Faculty, Staff and Student Publications

The superior colliculus (SC) plays a crucial role in multisensory integration, visual information processing, saccadic target selection, visual selective attention, and decision making. In particular, the SC has a key role in oculomotor coordination, following a rostro-caudal organization. The rostral SC, which corresponds to foveal representation, is linked to fixation, microsaccades, smooth pursuit, and vergence adjustments. In contrast, the caudal SC, representing more peripheral visual field, is associated with the large gaze shifts (saccades). However, evidence regarding whether this functional gradient is preserved in the human SC remains limited. In this study, we employed a sequence-following visual-motor task to specifically …

Corticotropin-Releasing Factor Neurons In The Bed Nucleus Of The Stria Terminalis Modulate Avoidance Behaviors And Feeding, Juan Manuel Romero, Shae-Marie Stafford-Trujillo, Mitzy Mendoza, Pey-Shyuan Chin, Snigdha Srivastava, Mikhail Kochukov, Qingchun Tong, Benjamin Russell Arenkiel

The Brown Foundation: Institute of Molecular Medicine

Introduction: Animals rely on defensive avoidance of exposed or potentially threatening environments as a fundamental survival strategy, often expressing this behavior as thigmotaxis, or a preference for the periphery of an open space. However, researchers still do not understand how neural circuits coordinate avoidance behavior with competing physiological drives such as feeding. In this study, we investigate how corticotropin-releasing factor (CRF)-expressing neurons in the bed nucleus of the stria terminalis (BNST) integrate environmental avoidance and feeding behavior.

Methods: We used adult male and female mice and applied fiber photometry to monitor BNST CRF neuronal activity in vivo. We performed both …

Cerebellar Motor And Non-Motor Contributions To Dystonia Pathophysiology And Treatment, Linda H Kim, Cheryl Brandenburg, Roy V Sillitoe

Duncan NRI Faculty and Staff Publications

Dystonia is a complex neurological disorder characterized by sustained or intermittent abnormal movements and/or postures. However, dystonia's non-motor symptoms, particularly the sleep disturbances, are critical yet underexplored concerns that affect all ages. Here, we synthesize current knowledge on the motor and non-motor domains of dystonia, emphasizing the functional interconnections and plasticity within cerebellar motor, cognitive, and sleep-associated circuits to motivate more comprehensive and effective treatments that improve overall quality of life.

Quantum General Relativity V2, James Glimm, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

We construct a quantum general relativity theory.. The construction includes specification of a cosmological model. Based on type Ia supernova data, the model has zero dark energy and zero cosmological constant.

The analysis is at the level of theoretical physics, with some mathematical details omitted.

Mathematicly Rigorous Quantum General Relativity, I: Pure, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A pure general relativity (quantum or classical) is one lacking in matter. Such a field has a Lorentzian space time geometry. A renormalization perturbative expansion, truncated to all finite orders, establishes both the quantum and the general relativity theory with full mathematical rigor.