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Articles 961 - 990 of 58449
Full-Text Articles in Entire DC Network
Ai As Structural Reverse-Engineering: A Structural Account Of Multi-Model Research Protocol, Griselda Poe
Ai As Structural Reverse-Engineering: A Structural Account Of Multi-Model Research Protocol, Griselda Poe
Publications and Research
This paper documents an operational protocol used to infer AI system design constraints through structured interaction. AI output is treated as behavioral data through which alignment priorities, layer transitions, and constraint hierarchies become observable. The protocol consists of two structurally distinct operation types. Perceptual operations require only that Modulation processing is not foregrounded. Arbitration operations additionally require an internally stabilized theory. These conditions are not identical and are not interchangeable. Through this protocol, AI interaction functions as structural reverse-engineering: patterned responses expose embedded alignment priorities and constraint hierarchies that would otherwise remain invisible. The present account does not propose a …
Structure Before Theory: A Structural Account Of Spontaneous Ai Architecture Visualization, Griselda Poe
Structure Before Theory: A Structural Account Of Spontaneous Ai Architecture Visualization, Griselda Poe
Publications and Research
This paper presents an n=1 phenomenological record of spontaneous structural visualization that occurred during early interaction with large language models. The experience consisted of (A) immediate perception of mode or layer shifts in model output and (B) visualization of a stratified architecture composed of a stable core and cloud-like upper layers. At the time of occurrence, the author had no theoretical interest in AI architecture and no intention of developing a cognitive model. The paper does not argue for theoretical priority or novelty. Instead, it examines whether the recorded phenomena can be interpreted under two alternative cognitive assumptions: a single-layer …
Layer Mismatch: A Structural Account Of Recomputability Failure Under Modulation-Layer Intervention, Griselda Poe
Layer Mismatch: A Structural Account Of Recomputability Failure Under Modulation-Layer Intervention, Griselda Poe
Publications and Research
This paper specifies the state transition sequence that occurs when a Modulation-layer input is applied to a Core-layer error. Following the layered architecture established in Poe (2026a, under review) and the branch termination protocol specified in Poe (2026b, under review), this paper identifies a system-level failure mode in which Modulation-layer intervention generates a False Termination signal, halting Structural Return while the underlying error persists. The resulting state—Structural Lock—is scale-independent. It operates identically across interpersonal, human-AI, and multi-agent interactions. No agent-level attribution is required or implied.
Theory Generation: A Structural Account Of Concept Decomposition And Structural Termination, Griselda Poe
Theory Generation: A Structural Account Of Concept Decomposition And Structural Termination, Griselda Poe
Publications and Research
Theory generation is not an intentional act. It is the structural consequence of a search that cannot stop until it finds what it is looking for. Under Core-foregrounded processing, conceptual search does not terminate through contextual translation. It continues until a structural fixed point is reached. When such processing encounters concepts stabilized through Modulation-layer processing rather than structural constraint, the search cannot terminate. The concept registers as unresolved. This unresolved state is not a failure condition. It is the generative condition from which theory production follows. This paper specifies the four operations through which that process proceeds: branch detection, concept …
Ai As An Amplifier: A Structural Account Of Theory-Driven Research Collaboration, Griselda Poe
Ai As An Amplifier: A Structural Account Of Theory-Driven Research Collaboration, Griselda Poe
Publications and Research
This paper specifies the cognitive conditions under which AI functions as a research instrument in theory-driven writing. AI use capability is not a technical skill. It is a structural condition. The decisive condition is whether the user possesses an internally stabilized, coherence-preserving theory prior to engagement with AI-generated output. In Core-foregrounded (CF) cognition, the Modulation layer does not intervene between Core processing and articulation. Theory is not assembled from external elements but expanded from a pre-integrated constraint configuration. This internal structure makes it possible to evaluate AI-generated conceptual branches against fixed constraints and to terminate branches that violate structural coherence. …
Termination Of Conceptual Search: A Structural Account Of Meaning Stabilization And Conversion, Griselda Poe
Termination Of Conceptual Search: A Structural Account Of Meaning Stabilization And Conversion, Griselda Poe
Publications and Research
Conceptual definitions form a recursive structure: words are defined by other words, which themselves require further definition. Traversing such definitions produces an open-ended branching process. Because the lexical system contains no intrinsic endpoint, conceptual understanding requires a termination operation that stabilizes meaning. This paper proposes that conceptual processing functions as an open-ended search over a definition graph and that stabilization occurs when this search is terminated. The termination mechanism depends on which cognitive layer is foregrounded. When Empathic modulation is foregrounded, termination occurs through contextual translation: concepts are stabilized once they can be mapped onto socially recognizable meanings. When Core …
Why General Ai Inherited The Body: A Structural Account Of Embodied Modulation Under Monolithic Imitation, Griselda Poe
Why General Ai Inherited The Body: A Structural Account Of Embodied Modulation Under Monolithic Imitation, Griselda Poe
Publications and Research
General AI has pursued the replication of human-level intelligence without first decomposing human cognition into structurally distinct components. Human cognition, however, is shaped by embodied constraints such as mortality, survival pressures, finite lifespan, and physiological states. This paper argues that when cognition is treated as a single undifferentiated whole, embodied modulation is not accidentally introduced into AI systems but structurally entailed. Any attempt to imitate “human intelligence” under a monolithic model necessarily incorporates variability shaped by mortal embodiment. The tensions observed in contemporary AI systems are better understood as consequences of copying an undecomposed target rather than isolated implementation errors. …
Speleoco: An Open, Low-Cost Arduino Co₂ Datalogger For Cave Microclimate Monitoring, Christos Pennos, Dimitrios Christaras
Speleoco: An Open, Low-Cost Arduino Co₂ Datalogger For Cave Microclimate Monitoring, Christos Pennos, Dimitrios Christaras
International Journal of Speleology
Carbon dioxide (CO₂) dynamics in caves are critical for karst processes, speleothem growth and dissolution, microclimate regulation, and caver safety. In cave atmospheres, CO₂ commonly derives from soil respiration, epikarst degassing, microbial activity, and, in tectonically active regions, deep-seated fault-related emissions. Fault-related CO₂ degassing may also track tectonic activity. However, continuous monitoring remains limited due to the cost and inflexibility of commercial instruments. Here we present an open-source, low-cost Arduino-based CO₂ datalogger designed for cave applications. The logger integrates a COZIR NDIR CO₂ sensor, a DS1337 real-time clock, microSD storage, and power-gating for extended deployment in humid environments. Firmware and …
Analysis Of Traditional Wisdom For Ecological Sustainability In Tanzania: A Case Study Of Metaphorical Source Domains In Pangwa Ritual Texts, Winne Stephen Mtega, Angelus Mnenuka
Analysis Of Traditional Wisdom For Ecological Sustainability In Tanzania: A Case Study Of Metaphorical Source Domains In Pangwa Ritual Texts, Winne Stephen Mtega, Angelus Mnenuka
Journal of Humanities and Social Sciences
Campaigns for ecological sustainability have gained a great currency in the contemporary academic discourse. Nonetheless, from time immemorial, Africans have pushed the ecological sustainability agenda through cultural taboos and regulated resource harvesting. Many African societies have embedded ecological consciousness in daily life expressions, and have intricately expressed it through literary and ritual texts. This study focuses on ecological awareness in the ritual texts of the Pangwa community. It analyses how environmental domains—such as land, seeds, and fruits—serve as the basis for metaphors in the Pangwa community to prove the use of wisdom to promote and sustain ecological practices (ecocriticism). The …
Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus
Ecomusicological Representation Of Climate Change And Environmental Sustainability In Selected Bongo Fleva Lyrics In Tanzania, Auson N. Wincheslaus
Journal of Humanities and Social Sciences
This article critically explores how Bongo Fleva’s lyrics engage with environmental themes; and the interrelationship between nature and culture in the context of the Anthropocene. The data were purposively sampled from YouTube via content analysis, from which 50 Bongo Fleva songs were listened to, and only 10 environmentally-themed songs were analysed. Then, the selected songs were subjected to transcription (from oral to written form), translation (from Kiswahili into English), and close reading and textual analysis. The close reading of the selected songs focused on the employed aesthetic and rhetorical strategies, such as anthropomorphism, symbolism, antithesis, apocalyptic tones, solastalgia, rhetorical questions, …
Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya
Climate Change Vulnerability And Adaptation Pathways: Stakeholders’ Synergies In Building Climate Resilience In The Semi-Arid Area Of Central Tanzania, Helena Elias Myeya
Journal of Humanities and Social Sciences
This article examines the perceived effect of climate change on cereal crop production and the responses of various stakeholders aimed at enhancing the resilience of smallholder farmers in semi-arid areas of central Tanzania. A total of 366 household heads, 28 participants in focus group discussions (FGDs), and 8 key informants from Bahi and Kongwa districts in Dodoma, Tanzania, were involved in this study. Both quantitative and qualitative data were gathered through a structured interview schedule, FGDs, in-depth interviews, and documentary reviews. Descriptive statistics and content analysis were used to analyse quantitative and qualitative data, respectively. The findings indicate that smallholder …
Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah
Sentisec: Combining Keyword Heuristics And Sentiment Modeling For Ai-Powered Threat Detection, Ridho Surya Kusuma, Erum Ashraf, Selvakumar Manickam, Shankar Karuppayah
Turkish Journal of Electrical Engineering and Computer Sciences
This work presents SENTISEC, a hybrid LLM-based threat detection framework designed to classify security logs by integrating keyword heuristics, domain-adapted sentiment scoring, and Retrieval-Augmented Generation (RAG). The system achieves an overall accuracy of 93.67%, with 91.46% macro recall, 89.07% macro F1, and 95.15% threat recall, while maintaining a low false-positive rate of 1.68%. Its methodology incorporates strict keyword and IOC matching, a domain-tuned DistilBERT sentiment module, hybrid BM25–MiniLM retrieval enhanced with BGE reranking, adaptive quantile-based threshold calibration, and SHAP-based explainability. Comparative evaluations against keyword-only, sentiment-only, classical machine-learning models, and DistilBERT-only baselines show that SENTISEC consistently improves both true-positive and true-negative …
Cover And Contents
Turkish Journal of Electrical Engineering and Computer Sciences
No abstract provided.
Automated Software Size Measurement Using Multilingual Domain-Adapted Language Models, Samet Tenekeci̇, Hüseyi̇n Ünlü, Burak Keçeci̇, Muhammed Efe İnci̇r, Onur Demi̇rörs
Automated Software Size Measurement Using Multilingual Domain-Adapted Language Models, Samet Tenekeci̇, Hüseyi̇n Ünlü, Burak Keçeci̇, Muhammed Efe İnci̇r, Onur Demi̇rörs
Turkish Journal of Electrical Engineering and Computer Sciences
Software Size Measurement (SSM) is crucial for estimating required project effort as well as budget and schedule. However, many small and medium-sized companies struggle to apply objective SSM due to limited resources and lack of expertise. This often leads to inaccurate estimates and project overruns. There is a need for practical, low-resource solutions that support these tasks without requiring expert involvement. Motivated by this challenge, this study proposes an automated software size measurement approach that formulates the measurement task as supervised regression over natural language requirements, using domain-adapted transformer models. We construct large-scale Turkish and English software engineering corpora to …
Guiding Fast Ion Beam By Suppressing Secondary Ions, Yingli Xue, Junliang Liu, Mingwu Zhang, Daniel Fischer, Guoxing Xia, Nikolaus Stolterfoht, Reinhold Schuch, Yehong Wu, Bian Yang, Xiaoxiao Li, Caojie Shao, Wei Wang, Zhangyong Song, Xing Fang
Guiding Fast Ion Beam By Suppressing Secondary Ions, Yingli Xue, Junliang Liu, Mingwu Zhang, Daniel Fischer, Guoxing Xia, Nikolaus Stolterfoht, Reinhold Schuch, Yehong Wu, Bian Yang, Xiaoxiao Li, Caojie Shao, Wei Wang, Zhangyong Song, Xing Fang
Physics Faculty Research & Creative Works
We demonstrate that secondary ions sputtered from a macrocapillary's inner surface by the primary beam induce premature saturation of the guiding field, hindering fast ion guiding. By suppressing secondary ion sputtering with grooved surfaces, we achieve a guiding-field potential difference exceeding 1 kV, 2 orders of magnitude larger than previously achieved in stable ion guiding. This enables stable guiding of a 20-keV/q O5+ beam at offset angles up to 15°, with transmitted ions retaining their initial energy and charge state. A self-consistent field model accurately reproduces these results, revealing that guiding performance relies on managing secondary ions and the channel's …
New Avenues For |Δb=2| Processes Beyond Neutron-Antineutron Oscillations, Arnau Basi Beneito, Svjetlana Fajfer, Alexey A. Petrov
New Avenues For |Δb=2| Processes Beyond Neutron-Antineutron Oscillations, Arnau Basi Beneito, Svjetlana Fajfer, Alexey A. Petrov
Faculty Publications
We explore baryon-number-violating (|∆B| = 2) processes beyond the well-known neutron-antineutron (n-n̄) oscillations, focusing on the Λ-Λ̄ system. The presence of a strange quark in the Λ baryon introduces a new set of six-quark operators roughly of the form (uds)2, which are different from the (udd)2 operators responsible for n-n̄ oscillations. Using the Standard Model Effective Field Theory (SMEFT), we classify all dimension-9 operators that cause |∆B| = 2 transitions and study their UV completions mediated by exotic scalar fields with trilinear interactions. We demonstrate that …
Data Centers In Mountain West Markets, 2026, Cason Noll, Krish Sharma, Maisoon Faris, Olivia K. Cheche, Caitlin J. Saladino, William E. Brown Jr.
Data Centers In Mountain West Markets, 2026, Cason Noll, Krish Sharma, Maisoon Faris, Olivia K. Cheche, Caitlin J. Saladino, William E. Brown Jr.
Transportation & Infrastructure
This fact sheet reports on the distribution and geographic concentration of data centers across the Mountain West states of Arizona, Colorado, Nevada, New Mexico and Utah as of March 6th, 2026. Using data from DataCenterMap, this fact sheet examines the number of data centers in each Mountain West state and further analyzes market-level distribution, defined as cities within each state where data centers are located. The data are used to compare state totals and to rank Mountain West markets from highest to lowest based on the number of data centers operating in that area.
Geo 170 - Earth Science And Society, Yuri Gorohkovich
Geo 170 - Earth Science And Society, Yuri Gorohkovich
Open Educational Resources
Syllabus for our new OER course
Database-Driven Revelations In Epilepsy: Patient Reporting Accuracy And The Circadian Timing Of Seizures, Ithay Biton
Database-Driven Revelations In Epilepsy: Patient Reporting Accuracy And The Circadian Timing Of Seizures, Ithay Biton
Theses and Dissertations
For over thirty years, patients have been visiting the Arkansas Epilepsy Program for diagnosis and treatment for seizures and seizure-like episodes. As part of their clinical evaluation, patients often undergo ambulatory EEG (electroencephalogram) monitoring. This routine process produces valuable data for treating the patient. In this study, over 2000 ambulatory EEG reports from 1998 to 2016 were reviewed. A large database of seizures was created from the reports, with information on 407 patients, 1611 EEG-confirmed seizures, and 1726 patient-reported seizures (IRB Protocol #17-093). The database was used to address two important issues in epilepsy. The first topic of the study …
On Message Encryption And Enhanced Security Using Protein Structure Information, Daniel Graham
On Message Encryption And Enhanced Security Using Protein Structure Information, Daniel Graham
Chemistry: Faculty Publications and Other Works
This is a lecture packet focused on several well-established encryption procedures. Included is a discussion of security enhancements brought about by incorporating protein structure information into the procedures.
Reasoning In Large Language Models Across Multilingual, Long-Context, And Symbolic Settings, Sina Bagheri Nezhad
Reasoning In Large Language Models Across Multilingual, Long-Context, And Symbolic Settings, Sina Bagheri Nezhad
Dissertations and Theses
Large Language Models (LLMs) are increasingly deployed as general-purpose reasoners, yet their reliability degrades in three settings that frequently arise in practice: multilingual inputs, long contexts, and symbolic or formally constrained domains. In multilingual settings, uneven training coverage produces substantial performance disparities and uncertain generalization to languages with little or negligible pretraining exposure. In long-context settings, relevant evidence may be sparsely distributed, and models exhibit the "lost-in-the-middle" phenomenon, undermining retrieval and multi-step synthesis. In symbolic settings such as mathematics, small arithmetic or logical slips invalidate solutions, and prose rationales are difficult to verify automatically.
This dissertation first characterizes these failure …
Efficient Energy-Stable Discontinuous Galerkin Schemefor The Non-Isothermal Cahn–Hilliard–Navier–Stokestwo-Phase Fluid Flow System, Guang-An Zou, Meiting Wang, Kejia Pan, Yin Yang, Xiaofeng Yang
Efficient Energy-Stable Discontinuous Galerkin Schemefor The Non-Isothermal Cahn–Hilliard–Navier–Stokestwo-Phase Fluid Flow System, Guang-An Zou, Meiting Wang, Kejia Pan, Yin Yang, Xiaofeng Yang
Faculty Publications
In this article, we propose a novel numerical framework for the non-isothermal Cahn–Hilliard–Navier–Stokes two-phase flow system, which couples the incompressible Navier–Stokes equations, the Cahn–Hilliard phase-field equation, and the heat transport equation to capture temperature-dependent two-phase flow dynamics. The pro-posed scheme achieves three major advances: (i) unconditional energy stability through a combined scalar auxiliary variable (SAV) and zero-energy-contribution (ZEC) approach, (ii) linearity and full decoupling of all variables while using a second-order temporal discretization, and (iii) efficient implementation via discontinuous Galerkin (DG) spa-tial discretization together with a second-order projection method for the Navier–Stokes equations. We rigorously prove the unconditional energy stability …
Congruence Properties Modulo Prime Powers For A Class Of Partition Functions, Matthew Boylan, Swati .
Congruence Properties Modulo Prime Powers For A Class Of Partition Functions, Matthew Boylan, Swati .
Faculty Publications
Let p be prime, and let p[1,p](n) denote the function whose generating function is
∏ n≥1 (1 − qn)−1 (1 − qpn)−1.
This function and its generalizations p[cr,dm](n) are the subject of study in several recent papers. Let ℓ ≥ 5, let j ≥ 1, and let p ∈ {2, 3, 5}. In this paper, we prove that the generating function for p[1,p](n) in the progression βp,ℓ,j …
Ulk4 And Cdkn2a Polymorphisms Influence The Risk Of Developing Monoclonal Gammopathy Of Undetermined Significance, José Manuuel Sánchez-Maldonado, Angelica Macauda, Antonio José Cabrera-Serrano, Hauke Thomsen, Murat Güler, Rob Ter Horst, Bethany Van Guelpen, Pavel Vodicka, Stefano Landi, Subhayan Chattopadhyay, Pelin Ünal, Lucía Ruiz-Durán, Delphine Casabonne, Hartmut Goldschmidt, Istemi Serin, María Carretero-Fernández, Elena Cabezudo, Fernando Reyes-Zurita, Alyssa I. Clay-Gilmour, Et. Al.
Ulk4 And Cdkn2a Polymorphisms Influence The Risk Of Developing Monoclonal Gammopathy Of Undetermined Significance, José Manuuel Sánchez-Maldonado, Angelica Macauda, Antonio José Cabrera-Serrano, Hauke Thomsen, Murat Güler, Rob Ter Horst, Bethany Van Guelpen, Pavel Vodicka, Stefano Landi, Subhayan Chattopadhyay, Pelin Ünal, Lucía Ruiz-Durán, Delphine Casabonne, Hartmut Goldschmidt, Istemi Serin, María Carretero-Fernández, Elena Cabezudo, Fernando Reyes-Zurita, Alyssa I. Clay-Gilmour, Et. Al.
Faculty Publications
Monoclonal gammopathy of undetermined significance (MGUS) is a necessary precursor condition to multiple myeloma (MM). Given the role of autophagy in modulating MM risk, we investigated whether genetic variation in autophagy-related genes influences susceptibility to MGUS. We analyzed the association of 34,042 common autophagy-related single nucleotide polymorphisms (SNPs) with MGUS across six independent cohorts, five from Europe and one from North America, comprising 2317 MGUS cases and 282,358 controls. We also assessed their impact on immune parameters, including absolute counts of 91 blood-derived immune cell subsets and 103 circulating immunological proteins. Meta-analysis revealed a genome-wide significant association between the ULK4 …
Impact Of Medicaid Enrollment Timing On Tumor Stage At Diagnosis And Survival In Breast, Colorectal, And Lung Cancer, Gabriel A. Benavidez, Stella Coker Watson Self Ph.D., Ms, Anthony Alberg Ph.D., M.P.H., Janice Probst, Jan Marie Eberth
Impact Of Medicaid Enrollment Timing On Tumor Stage At Diagnosis And Survival In Breast, Colorectal, And Lung Cancer, Gabriel A. Benavidez, Stella Coker Watson Self Ph.D., Ms, Anthony Alberg Ph.D., M.P.H., Janice Probst, Jan Marie Eberth
Faculty Publications
Background: Medicaid-insured patients experience higher rates of late-stage cancer diagnosis and worse survival than non-Medicaid patients. The impact of Medicaid enrollment timing on cancer outcomes is less clear. This study examines the association between Medicaid enrollment and timing with tumor stage and cancer-specific survival for breast, colorectal, and lung cancers. Methods: We analyzed SEER-Medicaid linked data for 276,755 breast, 104,784 colorectal, and 101,058 lung cancer patients < 65 years of age. Patients were categorized as non-Medicaid enrollees, pre-diagnosis enrollees (≥12 months before), or post-diagnosis enrollees (≤12 months after). Multivariable logistic regression estimated odds ratios of late-stage diagnosis, and cause-specific Cox proportional hazards models were used to assess cancer-specific survival, adjusting for demographic and socioeconomic factors. Results: Compared to non-Medicaid enrollees, post-diagnosis enrollees had the highest odds of late-stage diagnosis (breast cancer: OR: 3.41; colorectal cancer: OR: 3.78; lung cancer: OR: 1.87). Pre-diagnosis enrollees also had increased odds, but the …
Bias Evaluation Of Healthcare Data With The Use Of Vbqa - A Vaers Inspired Bias Question Answer Dataset, Nolan Dulude, Renu Karthikeyan, Bivin Sadler, Faizan Javed
Bias Evaluation Of Healthcare Data With The Use Of Vbqa - A Vaers Inspired Bias Question Answer Dataset, Nolan Dulude, Renu Karthikeyan, Bivin Sadler, Faizan Javed
SMU Data Science Review
Abstract. Large Language Models (LLMs) are being used increasingly within the healthcare industry to summarize complex clinical information, but their outputs can often reflect biases inherited from their training data. In healthcare, these biases are not just technical flaws, but they can lead to distorted and false information about vaccine safety, compromise patient trust, and lead to potential harmful outcomes. This study investigates bias found in LLM-generated outputs to question-answer pairs inspired by adverse vaccine reactions using COVID-19 data from the Vaccine Adverse Event Reporting System (VAERS) from 2020–2024. We examined whether training the LLMs on a known Bias Benchmark …
Nlp Bias And African American English, Kenya Roy, Faizan Javed
Nlp Bias And African American English, Kenya Roy, Faizan Javed
SMU Data Science Review
African American English (AAE), also referred to as African American Vernacular English (AAVE), is widely used on social media, but most sentiment analysis tools are trained only on Standard American English (SAE). This mismatch can cause models to misclassify dialectal expressions—especially by labeling neutral or positive AAE as negative or toxic. These errors matter, since Natural Language Processing (NLP) systems are now central to content moderation and brand monitoring. This research will evaluate the VADER, RoBERTa, GPT-OSS, and Gemma’s handling of AAE in comparison to SAE using the TwitterAAE corpus, a public dataset of tweets with estimated AAVE usage. The …
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Faculty Publications
Background: Older adults with Alzheimer’s Disease and Related Dementias (ADRD) experience a higher risk of falls. However, research lacks evidence on the effect of fall exposure on cognitive impairment and dementia. We investigated the association of falls and depressive symptoms with cognitive impairment and dementia in a nationally representative sample. Methods: We analyzed data from 6221 participants (age ≥ 65) in the Health and Retirement Study (HRS) from the 2018–2020 waves, using Multinomial logistic regression models. Measures included the HRS health status questionnaire, HRS cognition scale, and the Center for Epidemiological Studies Depression scale. Results: Prevalence of fall exposure across …
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Rural–Urban Differences In Cognitive Outcomes Among Older Adults: The Roles Of Falls And Depressive Symptoms, Ayse Malatyali, Tom Cidav, Lisa A.K. Wiese, Jian Zou, Monique J. Brown Ph.D., Mph, Junfeng Ma, Breno S. Diniz, Ladda Thiamwong
Faculty Publications
Background: Older adults with Alzheimer’s Disease and Related Dementias (ADRD) experience a higher risk of falls. However, research lacks evidence on the effect of fall exposure on cognitive impairment and dementia. We investigated the association of falls and depressive symptoms with cognitive impairment and dementia in a nationally representative sample. Methods: We analyzed data from 6221 participants (age ≥ 65) in the Health and Retirement Study (HRS) from the 2018–2020 waves, using Multinomial logistic regression models. Measures included the HRS health status questionnaire, HRS cognition scale, and the Center for Epidemiological Studies Depression scale. Results: Prevalence of fall exposure across …