Journal Articles, Multidisciplinary Digital Publishing Institute (MDPI)

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Effects of Supplementation with Rumen-Protected Fats and Thermally Processed Soybean on Intake, Nutrient Digestibility, and Milk Composition of Pantaneiras Ewes
Chagas, Renata Alves das; Fernandes, Tatiane; Leonardo, Ariadne Patrícia; Valério, Agda Costa; da Silva, Núbia Michelle Vieira; Cardoso, Cláudia Andrea Lima; de Bessa, Rui José Branquinho; de Vargas Junior, Fernando Miranda (MDPI, 2026-01-07)
This study aimed to evaluate the effect of the supplementation with rumen-protected fat from soybean or palm and thermally processed soybean on the feed intake, digestibility of nutrients, milk production, and milk content of ewes. Twenty-five Pantaneiras ewes, 3–6 years old, 39.8 ± 3.51 kg body weight, and 65 ± 4 days in milk, were distributed into five treatments (5 ewes in each) in a completely randomized design continuous trial, over 56 days. The treatments consisted of daily supplementation with soybean-based rumen-protected fat (SPF; 30 g/d), palm-based rumen-protected fat (PPF; 30 g/d), a blend of soybean and palm rumen-protected fats (Blend; 30 g/d), thermally processed soybean (TPS; 124 g/d), and a control without supplementation. We performed a daily evaluation of feed intake and milk production, and every 14 days, we evaluated the nutrient digestibility, milk composition, and fatty acid profile. The protein and casein content were lower in the SPF treatment. Supplementation with PPF resulted in a higher saturated fatty acid content, while supplementation with TPS resulted in higher monounsaturated and polyunsaturated fatty acid contents. The supplementation with SPF resulted in higher milk fatty acid functionality. Feeding ewes SPF or TPS enhanced nutrient intake and digestibility, leading to increased milk production and an improved milk fatty acid profile. In contrast, supplementation with PPF resulted in a less favorable fatty acid composition.
A Feasibility Study of Real-Time FMRI with Neurofeedback of Motor Performance in Cerebellar Ataxia
Berenbaum, Joshua G.; Marvel, Cherie L.; Lisinski, Jonathan M.; Soldate, Jeffrey S.; Morgan, Owen P.; Kucharski, Ashley N.; Lutzel, Luca P.; Ecker, Jonathan A.; Rice, Laura C.; Mistri, Amy; Nadkarni, Prianca A.; Rosenthal, Liana S.; LaConte, Stephen M. (MDPI, 2026-01-23)
Background/Objectives: Neurodegenerative cerebellar ataxia (CA) is a movement disorder caused by progressive cell death in the cerebellum. Motor imagery represents a potential therapeutic tool to improve motor function by “exercising” brain regions associated with movement, without the need for overt activity. This study assessed the feasibility of combining motor imagery with real-time functional magnetic resonance imaging neurofeedback (rt-fMRI-NF) to improve motor function in CA. Methods: During finger tapping conditions, 16 participants with CA pushed a button at the same frequency in time with cross flashing at 1 Hz or 4 Hz, and this information was used to train the model. During motor imagery, participants imagined finger tapping while undergoing rt-fMRI-NF with visual feedback, steering them toward activating their motor circuit. Afterwards, they completed finger tapping again. FMRI analysis compared successful motor imagery trials versus all other imagery events. Brain activity on successful trials was covaried with pre–post rt-fMRI-NF tapping improvement scores. Results: Tapping was more accurate at 1 Hz than 4 Hz, and larger tapping error rates correlated with greater movement impairments. While not significant at the group level, 9 of the 16 participants improved tapping accuracy following rt-fMRI-NF. The size of motor improvements correlated with successful motor imagery activity at 1 Hz in the frontal lobe, insula, parietal lobe, basal ganglia, and cerebellum. Motor improvements were not associated with neurological impairment severity, mood, cognition, or imagery vividness. Conclusions: Feasibility was demonstrated for motor imagery therapy with neurofeedback to potentially improve fine motor precision in people with CA. Brain regions relevant to this process may be considered for targets of non-invasive therapeutic interventions.
Assessing the Efficacy of Artificial Intelligence Platforms in Answering Dental Caries Multiple-Choice Questions: A Comparative Study of ChatGPT and Google Gemini Language Models
Azhari, Amr Ahmed; Ahmed, Walaa Magdy; Alhamadani, Abdulaziz; Alfaraj, Amal; Zhang, Min; Lu, Chang-Tien (MDPI, 2026-01-27)
Objective: This study aimed to compare the accuracy of two large language models (LLMs)—ChatGPT (version 3.5) and Google Gemini (formerly Bard)—in answering dental caries-related multiple-choice questions (MCQs) using a simulated student examination framework across seven examination lengths. Materials and Methods: A total of 125 validated dental caries MCQs were extracted from Dental Decks and Oxford University Press question banks. Seven examination groups were constructed with varying question counts (25, 35, 45, 55, 65, 75, and 85 questions). For each group, 100 simulations were generated per LLM (ChatGPT and Gemini), resulting in 1400 simulated examinations. Each simulated student received a unique randomized subset of questions. MCQs were answered by each LLM using a standardized prompt to minimize ambiguity. Outcomes included mean score, passing rate (≥60%), and performance differences between LLMs. Statistical analyses included independent t-tests, one-way ANOVA within each LLM, and two-way ANOVA examining interactions between LLM type and question count. Results: Across all seven examination formats, Gemini significantly outperformed ChatGPT (p < 0.001). Gemini achieved higher passing rates and higher mean scores in every examination length. One-way ANOVA revealed significant score variation with increasing exam length for both LLMs (p < 0.05). Two-way ANOVA demonstrated significant main effects of LLM type and question count, with no significant interaction. Randomization had no measurable effect on Gemini performance but influenced ChatGPT scores. Conclusions: Gemini demonstrated superior accuracy and higher passing rates compared to ChatGPT in all simulated examination formats. While both LLMs struggled with complex caries-related content, Gemini provided more reliable performance across question quantities. Educators should exercise caution in relying on LLMs for automated assessment or self-study, and future research should evaluate human–AI hybrid models and LLM performance across broader dental domains.
Child Advocacy Workers’ Accounts of the Connections Between Pornography and Child Sexual Abuse
Ezzell, Matthew B.; Aadahl, Sarah; Bridges, Ana J.; Johnson, Jennifer A.; Hodges, Elizabeth; Sun, Chyng-Feng (MDPI, 2026-01-30)
This study analyzes the perspectives of support providers to survivors of child sexual abuse (CSA) on the potential links between pornography and the sexual abuse of children. Drawing from fifty interviews, eight focus group discussions, and post-interview surveys with frontline child advocacy support professionals from various backgrounds and settings, each with at least five years of experience in the field, this paper presents a conceptual model that situates pornography and CSA within interconnected “zones of violence” across digital, institutional, and community environments. Participants identified overlapping risk factors that can heighten pornography exposure and CSA vulnerability, including strained guardian–child relationships, inadequate supervision and digital literacy, socioeconomic precarity, limited access to services, and restrictive or patriarchal sexual norms. They described mediating processes linking pornography to abuse—social modeling, normalization of coercive and violent sexual scripts, grooming, power/threat dynamics (including sextortion and blackmail), and the production and circulation of child sexual abuse material (CSAM). Respondents perceived pornography as pervasive in young people’s lives, reported that it contributes to perceived shifts in CSA patterns, and emphasized the absence of best practices. They advocated comprehensive, digitally literate sex education; routine, developmentally appropriate screening; trauma-informed responses that avoid labeling and criminalizing children; and coordinated, multidisciplinary reforms.
Blood Pressure Variability (BPV) as a Novel Digital Biomarker of Multisystem Risk and Diagnostic Insight: Measurement, Mechanisms, and Emerging Artificial Intelligence Methods
Pugalenthi, Lakshmi Sree; Senapati, Sidhartha Gautam; Gohri, Jay; Anam, Hema Latha; Madan, Hritik; Arora, Adi; Arora, Avni; Lee, Jieun; Yerrapragada, Gayathri; Elangovan, Poonguzhali; Shariff, Mohammed Naveed; Natarajan, Thangeswaran; Janarthanan, Jayarajasekaran; Agarwal, Shreshta; Karuppiah, Shiva Sankari; Sood, Divyanshi; Rapolu, Swetha; Iyer, Vivek N.; Helgeson, Scott A.; Arunachalam, Shivaram P. (MDPI, 2026-01-30)
Hypertension has been traditionally known to be highlighted by mean blood pressure; however, emerging evidence exhibits that blood pressure variability (BPV), including short-term, day-to-day, and visit-to-visit fluctuations can have an implication across multiple body systems. Elevated BPV reflects repetitive hemodynamic stress, affecting the physiologic hemostasis contributing to vascular injury and end organ damage. This narrative review is a compilation of recent evidence on the prognostic value of BPV, explained by pathophysiology, various devices with its measurement approaches, and, essentially, the clinical implication of BPV and the use of such devices utilizing artificial intelligence. A comprehensive literature search across PubMed, Cochrane Library, Scopus, and Web of Science were conducted, focusing on observational studies, cohorts, randomized trials, and meta-analyses. Higher BPV has been associated with an increased risk of cardiovascular mortality, stroke, coronary events, and heart failure, the progression of chronic kidney disease, cognitive decline, and preeclampsia, among other end organ damage, despite mean blood pressure. The various pathophysiologic mechanisms include autonomic dysregulation, arterial stiffness, endothelial dysfunction, circadian rhythm alteration, and systemic inflammation, which result in vascular remodeling and multisystem damage. Antihypertensive medications such as calcium channel blockers and renin–angiotensin–aldosterone system inhibitors seem to reduce BPV; randomized trials have not specifically investigated their BPV-reducing effects. The aim of this review is to highlight that BPV is a dynamic marker of multisystem risk, and question how various AI-based devices can aid continuous BPV monitoring and patient specific risk stratification.
Design, Manufacturing, and Analysis of a Carbon Fiber Reinforced Polymer Crash Box
Engul, Mehmet; Demir, Serdar; Ersoy, Nuri (MDPI, 2026-02-06)
This paper presents a novel carbon fiber reinforced polymer (CFRP) crash box design, incorporating numerical analysis and manufacturing aspects. Within the design and analysis phases, a novel numerical methodology is employed to mitigate computational costs in estimating specific energy absorption (SEA). The proposed approach involves a reduction in ply interfaces and modification of pertinent material properties to optimize energy dissipation, achieving more than 50% reduction in simulation time. This methodology is applied to the design of a composite crash box made of unidirectional (UD) carbon/epoxy prepregs, resulting in a new geometry: sun-like shape featuring four sinusoidal arms connected to a central circular core. Subsequent manufacturing and testing reveal a SEA value of 79.46 J/g for designed geometry, surpassing metallic counterparts by a factor of 3 to 4. Furthermore, this study conducts a comparative analysis of energy absorption performance between unidirectional and woven fabric prepregs for the same geometry. Utilizing carbon/epoxy woven fabric (WF) prepregs further enhances the SEA to 89.26 J/g. Finally, the application of edge tapering to the crash box structure is shown to eliminate initial peak loads, thereby preventing excessive deceleration.
Equity Leadership in K–12 Online Communities Under Democratic Duress
Mullen, Carol A. (MDPI, 2026-02-06)
To understand virtual leaders’ work at the intersection of equity and community, virtual school leadership (VSL) was examined with relevance to preparation and research. Research questions were: How is VSL described in extant literature? How is VSL applicable to leaders’ preparation and development? An integrative review approach was applied to online learning and virtual leadership linked to community and equity concepts. Document analysis was used to qualitatively code 34 (of 132) studies. Despite the demand for cyber schooling, some US preservice programs may lack training on leading equitably and collaboratively in virtual environments. Five findings address what virtual school leaders (aspire to) do in their jobs. Community and equity were leadership orientations as well as concerns discerned from perceptions of virtual schooling. Online public education is ensnared in global democratic backsliding for 82 countries, yet VSL remains underexplored in research. This literature review/conceptual work introduces Equity and Community in K–12 Online Leadership, an original conceptual framework informed by professional standards, virtual learning theories, and factors central to leadership. A critique of findings, along with recommendations for leadership preparation and practice, responds to the call for better preparing preservice leaders for the demands of K–12 online learning.
Venezuelan Equine Encephalitis Virus Antagonizes the cGAS-STING Pathway
Heath, Brittany N.; Akhrymuk, Maryna; Jamiu, Abdullahi T.; Akhrymuk, Ivan; Pickrell, Alicia M.; Kehn-Hall, Kylene (MDPI, 2026-02-10)
Venezuelan equine encephalitis virus (VEEV) is a mosquito-borne pathogen causing low mortality but high morbidity in humans, with 4–14% cases exhibiting neurological complications. While the cyclic GMP-AMP synthase–stimulator of interferon genes (cGAS–STING) pathway is canonically associated with double-stranded DNA (dsDNA) detection, it has been shown to respond to RNA viruses and subsequently limit viral pathogenesis. Several viruses antagonize this signaling cascade, underscoring the importance that cGAS–STING plays in host immunity. Previous studies regarding single-stranded RNA viruses revealed that cGAS–STING limits viral replication in Old World alphavirus chikungunya virus infections, but little is known about New World alphaviruses such as VEEV. Here, we investigate the impact that STING activation has on VEEV infection as a potential prophylactic and therapeutic intervention. VEEV infection alone did not induce STING phosphorylation at Ser366, but interferon-stimulated genes (ISGs) were upregulated during the late phase of infection. Loss of STING through siRNA showed a partial dependency on STING for ISG transcription, suggesting that STING activation may occur through a noncanonical process. Priming of the STING pathway prior to infection was found to be critical in limiting viral replication; however, targeting STING activation post-infection abrogated the antiviral effects that dsDNA had on VEEV. VEEV suppressed STING phosphorylation in a multiplicity of infection (MOI)-dependent manner with the most robust pSTING (Ser366) inhibition observed at an MOI of 10. Collectively, our results suggest that VEEV antagonizes canonical STING activation.
A Two-Stage Generative Design Process for Lightweight Additively Manufactured High-Performance Cooling Manifolds for Power Electronics
Arriola, Emmanuel; Ignacio, Jose Emmanuel; Untalan, Ren Andrew; Arroyo, Abrey Angelo; Lopez, Toni Beth; Advincula, Rigoberto; Lu, Guo-Quan (MDPI, 2026-02-11)
The study presents a novel process to design lightweight, high-performance cooling manifolds for power electronics using generative design. The process begins with a baseline design that defines the constraints of the manifold with regard to the target cooling geometry and flow path. A flow optimization is then performed to optimize flow distribution and maximize convective efficiency. Once a final fluid volume is obtained, a structural optimization is conducted to minimize weight and material usage. The simulation results for the final design demonstrated a 40.1% increase in the average heat transfer coefficient, a 7.5% decrease in average chip temperature, a 76.6% improvement in temperature uniformity, and a 63.3% reduction in weight at the expense of a minimal 5.1% increase in pressure drop compared to the baseline design.
Operationalizing the Mind–Body Connection: Interoception via the Autonomic Nervous System
Nackley, Brittany; Friedman, Bruce H. (MDPI, 2026-02-12)
Traditional interoception research investigates cardioception, respiroception, or gastroception as a proxy for the sense of the body as a whole. These single-organ tasks sacrifice construct and ecological validity for a content validity that has been elusive. We propose that interoception is better captured by one’s sense of their own autonomic nervous system, or ANSception. The ANS integrates multimodal signals via lesser-myelinated neurons, making it an integral part of the interoceptive nervous system. Thirty-four participants moved a slider to reflect their perceived sympathetic activation (ANSception) while their physiology was monitored. Most participants reported integrating information from two or more organ systems during ANSception. The relationship between ANSception and physiology showed unique but often robust responses by condition and physiological measure. For example, one participant had a negative-to-positive-to-negative pattern for ANSception-EDA correlations from baseline to stimulus to recovery (r = −0.677; 0.657; −0.507, p < 0.001). Another participant had a strong positive correlation between their ANSception and blood pressure (r = 0.601, p < 0.001) during a five-minute reportedly meditative state. We propose that the role of interoception is to scan, integrate and manage information across organ systems, and we conclude that ANSception better captures this role than traditional single-organ tasks.
Reservoir Computing: Foundations, Advances, and Challenges Toward Neuromorphic Intelligence
Liu, Andrew; Azmine, Muhammad Farhan; Lin, Chunxiao; Yi, Yang (MDPI, 2026-02-13)
Reservoir computing (RC) has emerged as an energy-efficient paradigm for temporal information processing, offering reduced training complexity by fixing recurrent dynamics and training only a simple readout layer. Among RC models, Echo State Networks (ESNs) and Liquid State Machines (LSMs) represent two distinct approaches based on continuous-valued and spiking neural dynamics, respectively. In this work, we present a comparative evaluation of ESNs and LSMs on the Mackey–Glass chaotic time-series prediction task, with emphasis on scalability, overfitting behavior, and robustness to reduced numerical error precision. Experimental results show that ESNs achieve lower prediction error with relatively small reservoirs but exhibit early performance saturation and signs of overfitting as reservoir size increases. In contrast, LSMs demonstrate more consistent generalization with increasing reservoir size and maintain stable performance under aggressive reservoir quantization. These findings highlight fundamental trade-offs between accuracy and hardware efficiency, and suggest that spiking RC models are well suited for energy-constrained and neuromorphic computing applications.
Privacy Risks of Cybersquatting Attacks
Kolenbrander, Jack; Rheault, Elliott; Michaels, Alan J. (MDPI, 2026-02-19)
Cybersquatting is a collection of methods commonly used by malicious actors to mislead or trick internet users into accessing fraudulent or malicious content. Much of the current research has concentrated on the specific techniques used by attackers in this domain, such as typosquatting, combosquatting, and sound squatting. Some research has explored the financial and time impacts of cybersquatting; however, an understanding of user privacy impacts is limited. Prior research into privacy implications has primarily relied on passive techniques such as analyzing DNS records, HTML content, and domain registrations. These passive approaches limit the ability to interact with these domains and track the downstream impact of sharing personally identifiable information (PII). This research develops an active open-source intelligence (OSINT) collection system capable of rapidly collecting and analyzing squatting domains through both passive and active techniques, with a particular emphasis on identifying those that solicit user information. Synthetic identities are then registered with these domains, and their associated communications are collected and analyzed to identify privacy-related risks and determine whether shared PII propagates.
Agroclimatic Sensing, Communication, and Computational Systems-Based Methods and Technologies for Precision Irrigation Management: Current State and Prospects
Sarr, Aminata; Chandel, Abhilash K.; Diop, Lamine; Soro, Yrébégnan Moussa; Tossa, Alain K.; Hota, Smrutilipi; Manimozhian, Arunachalam (MDPI, 2026-02-23)
Agriculture uses most of the world’s fresh water. Given that the worldwide population is expanding at an alarming rate, more land cultivation is apparently in demand. As a result, much more water would be required to irrigate cultivable lands. However, fresh water is becoming scarce at a faster rate due to climate uncertainties and over-exploitation. Several controlled irrigation techniques, such as drip and sprinkler irrigation, have been introduced to safeguard water resources. However, these techniques do not readily meet crop water demands and often end up causing overapplication of water. Under these circumstances, smart precision irrigation is the best solution. Smart irrigation techniques facilitate delivery of water in an amount that is required by the crop as per site/location and temporal requirements. Several studies have been carried out in this area, and remarkable progress has been observed. These studies range from making use of in situ sophisticated sensors that are low-cost and consume minimum energy up to the use of small unmanned aerial systems (SUAS) and satellite imagery for irrigation management. This review summarizes research studies that highlight the components of developing and deploying various precision irrigation technologies, their benefits, and their limitations. Specifically, the scientific value of this study lies in outlining implications of using different sensors, parameters, and equipment, the agroclimatic models, communication technologies, artificial intelligence, and the energy sources to implement automated irrigation systems. A future scope of precision irrigation is also discussed in accordance with cost-effectiveness and sustainability. This study should also act as a referring guideline for new researchers as well as technology manufacturers who seek to design and develop a futuristic yet efficient irrigation system. Overall, this review is aimed at contributing to the understanding of automated irrigation systems for their effective deployment towards enhanced agricultural production, conserved water resources, and sustainable use of energy sources.
Energy Storage Systems for AI Data Centers: A Review of Technologies, Characteristics, and Applicability
Rahman, Saifur; Khan, Tafsir Ahmed (MDPI, 2026-01-26)
The fastest growth in electricity demand in the industrialized world will likely come from the broad adoption of artificial intelligence (AI)—accelerated by the rise of generative AI models such as OpenAI’s ChatGPT. The global “data center arms race” is driving up power demand and grid stress, which creates local and regional challenges because people in the area understand that the additional data center-related electricity demand is coming from faraway places, and they will have to support the additional infrastructure while not directly benefiting from it. So, there is an incentive for the data center operators to manage the fast and unpredictable power surges internally so that their loads appear like a constant baseload to the electricity grid. Such high-intensity and short-duration loads can be served by hybrid energy storage systems (HESSs) that combine multiple storage technologies operating across different timescales. This review presents an overview of energy storage technologies, their classifications, and recent performance data, with a focus on their applicability to AI-driven computing. Technical requirements of storage systems, such as fast response, long cycle life, low degradation under frequent micro-cycling, and high ramping capability—which are critical for sustainable and reliable data center operations—are discussed. Based on these requirements, this review identifies lithium titanate oxide (LTO) and lithium iron phosphate (LFP) batteries paired with supercapacitors, flywheels, or superconducting magnetic energy storage (SMES) as the most suitable HESS configurations for AI data centers. This review also proposes AI-specific evaluation criteria, defines key performance metrics, and provides semi-quantitative guidance on power–energy partitioning for HESSs in AI data centers. This review concludes by identifying key challenges, AI-specific research gaps, and future directions for integrating HESSs with on-site generation to optimally manage the high variability in the data center load and build sustainable, low-carbon, and intelligent AI data centers.
The Use of Digital Neurocognitive Assessments to Assess Traumatic Brain Injury and Dementia in Older Trauma Patients: An Emergency Department Feasibility Study
Weppner, Justin; Gray, Justin; Kuehl, Damon; Sandsmark, Danielle; Mirshahi, Nazanin; Diaz-Arrastia, Ramon; Rascovsky, Katya; Peacock, W. Frank; Van Meter, Timothy E. (MDPI, 2026-01-27)
Background/Objectives: Older adults are disproportionately affected by traumatic brain injuries (TBIs), representing a significant portion of TBI-related hospitalizations and deaths. The objective of this study was to evaluate the feasibility and effectiveness of BrainCheck (Braincheck, Inc., Austin, TX, USA), a digital cognitive assessment tool, in detecting acute TBI-related cognitive deficits in the context of dementia-related cognitive impairment in older adult emergency department (ED) patients. Methods: From March 2020 to November 2023, participants aged 65+ with mild TBI, as defined by the American College of Rehabilitation Medicine (ACRM) diagnostic criteria, and individuals with isolated orthopedic injuries were recruited from 14 U.S. type 1 and 2 trauma centers. After informed consent, each subject was assessed by well-validated neurocognitive tests to characterize pre- and postinjury cognitive status. The Clinical Dementia Rating (CDR) and Functional Activities Questionnaire (FAQ) were used to assess cognitive impairment, with the informant sections used to classify preinjury status. The Rivermead Post-Concussion Symptoms Questionnaire (RPQ16) was used to assess injury-related symptoms, and the tablet-based BrainCheck Battery was tested as a diagnostic platform for injury-related deficits across several functional domains. Spearman's correlation was used to assess BrainCheck's internal validity and its relationship with self-reported cognitive symptoms. Technology familiarity was self-reported on a 1 (lowest) to 5 (highest) Likert scale. ROC curves evaluated the tool’s accuracy in identifying cognitive impairment associated with TBI in the context of pre-existing cognitive impairment. Results: For the 101 mTBI and 52 orthopedic trauma control patients, BrainCheck demonstrated strong internal validity, with significant correlations among its component tests, indicating its effectiveness in assessing cognitive impairment. However, low correlations with RPQ16 self-reported symptoms suggest that BrainCheck and the self-reported questionnaire assess different aspects of cognitive functions. Conclusions: While BrainCheck effectively identified cognitive impairment, the composite battery and scoring did not differentiate TBI and dementia. Technology familiarity did not affect test outcomes. BrainCheck is a useful tool for evaluating cognitive function in adults aged ≥ 65 years with and without TBI in ED settings.
Flow Control of a Rim-Driven Propeller Using Vortex Generators for Enhanced Open-Water Performance
Bang, Ju Seong; Yoon, Seok Pyo; Brizzolara, Stefano; Kinnas, Spyros A.; Ahn, Hyung Taek (MDPI, 2026-01-28)
Rim-driven propellers (RDPs) have attracted renewed attention as an efficient propulsion concept for integrated electric propulsion systems, yet their structural configuration inherently limits duct geometry modification, and viscous losses associated with boundary layer separation near the duct trailing edge remain a key performance constraint. In this study, a vortex generator-based flow control strategy is proposed as a practical means of improving RDP performance without altering the duct geometry. Reynolds-averaged Navier–Stokes (RANS) simulations were conducted to examine the effects of vortex generators installed on the outer surface of the duct, with numerical reliability ensured through a grid convergence index (GCI) analysis. A steady-state multiple reference frame (MRF) approach was employed, and the resulting flow characteristics were analyzed using velocity profiles, line integral convolution (LIC) visualization, pressure field analysis, and distribution of the flow field in the wake. The results show that the vortex generators effectively delay boundary layer separation near the duct trailing edge by re-energizing the near-wall flow, thereby enhancing flow attachment and pressure recovery. Consequently, consistent improvements in thrust coefficient and propulsive efficiency are achieved over the entire range of advance ratios, while the increase in torque coefficient remains negligible. These findings demonstrate that vortex generator-based flow control offers a practical and effective approach for enhancing the open-water performance of rim-driven propellers under structural constraints.
Environmental and Economic Analysis of Repurposed Wind Turbine Blades for Recreational Trail Bridges
Silverman, Aeva G.; Ackall, Gabriel P.; Johansen, G. Eric; Gentry, T. Russell; Bank, Lawrence C. (MDPI, 2026-02-01)
A two-parameter environmental (measured in CO2eq—CO₂ is used in this paper to represent the carbon dioxide molecule as opposed to the chemical formula CO₂ as is common practice in LCA studies; CO2eq is an abbreviation for CO₂ equivalent and may be written as CO2e in the literature) and economic (measured in USD) analysis using life cycle analysis (LCA) and techno-economic analysis (TEA) of repurposed wind turbine blades for structural use in recreational trail bridges (e.g., on hiking trails and golf courses) is described in this paper. The US Department of Energy’s TECHTEST TEA/LCA software (v1.0) platform was used to compare three commercially available trail bridges (a steel truss bridge, an FRP pultruded truss bridge, and a glulam stringer bridge) with a bridge made from retired wind turbine blades (known as a BladeBridge). All bridges had a 50 ft (15.24 m) long by 6 ft (1.83 m) wide deck and were designed for a 90 psf (4.3 kN/m²) live load. The LCA functional unit was the assembled bridge, which was made ready to be shipped from the fabricator. Cradle-to-gate (A1–A3, i.e., raw material extraction, transportation, and manufacturing) system boundaries were used. For the BladeBridge, no embodied carbon was attributed to the blade itself (cut-off system allocation). For the TEA, a USD 660/tonne credit was attributed to the blade. The raw materials for each bridge were determined from detailed construction documents. Manufacturing and transportation energy were determined based on the equipment used for fabrication and geographical location. Direct labor for fabrication was calculated based on a weighted average of salaries taken from the US Bureau of Labor Statistics. The results indicate that raw materials had the biggest effect on embodied CO2eq and that labor had the largest impact on cost for all bridges. The results indicate that the BladeBridge is significantly less expensive to produce and releases less CO2eq into the environment (less Global Warming Potential (GWP)) than the three commercially available bridges. Additional TEA metrics for the BladeBridge, including Technology Readiness Level (TRL) and future market potential, were also evaluated and found to be positive for the BladeBridge technology.
The Role of Climate-Induced Disaster in Multidimensional Poverty: A Systematic Review and the Multidimensional Climate-Poverty Dynamics (MCPD) Framework
Nurullah, A B M; Ritchie, Liesel A.; Islam, Shammy; Roshid, Harun-Or-; Sultana, Nahida (MDPI, 2026-02-06)
Climate change is a pressing issue that has far-reaching effects on the global ecosystem, societies, and economies. Climate-induced disasters exacerbate multidimensional poverty through economic, social, and environmental pathways. This study examines the relationship between climate-induced disasters and multidimensional poverty, applying a mixed-method design comprising a PRISMA-guided systematic review and thematic analysis. Articles published between 1999 and 2025 were retrieved from Scopus and Web of Science, yielding 3587 articles. After reference checking and screening for relevance and availability, we finally reviewed 17 articles. The results highlight that climate-induced disasters disrupt economic and livelihood activities, negatively impact GDP, slow financial development, reduce per capita expenditure ability, and harm agricultural production. Disasters also have negative impacts on health and well-being, education, gender, the natural environment, and culture; these disasters promote intergenerational poverty. Among all stressors, floods and droughts are the most pervasive, and they have different magnitudes and durations of impacts. The assessment identifies governance quality, gender inequality, education, social positions, and environmental degradation as the significant mediating systems influencing vulnerability and recovery. To cope with vulnerabilities, individuals employ a variety of strategies based on their socioeconomic status. Building on these insights, the study develops the Multidimensional Climate–Poverty Dynamics (MCPD) Framework to conceptually capture climate–poverty as a socially constructed and institutionally mediated process. The study contributes theoretically to environmental sociology and empirically to climate policy by framing adaptation as a social process of transformation rather than as solely a survival mechanism.
The Species-Specific Inversion Polymorphism of the X Chromosome in Anopheles messeae and Anopheles daciae Is Based on the Common Ancestral Variant X1
Soboleva, Evgeniya S.; Sharakhova, Maria V.; Sharakhov, Igor V.; Artemov, Gleb N. (MDPI, 2025-12-19)
Background/Objectives: Chromosomal inversions play an important role in the evolution of insects by forming genetic barriers between closely related species and facilitating local adaptation. Polymorphic inversions in malaria mosquitoes of the Maculipennis subgroup have been studied for over 50 years, yet the evolutionary ancestry of the gene orders remains unknown. In this study, we mapped the genes flanking the breakpoints of two polymorphic X-chromosome inversions in the cryptic species Anopheles messeae and Anopheles daciae of the Maculipennis subgroup. Methods: We used an iterative mapping approach to define the breakpoint regions, selecting flanking markers based on the genome assembly of the reference species, Anopheles atroparvus. To identify the ancestral X chromosomal arrangement in An. messeae and An. daciae, we developed and implemented the genomic inversion calculator (GIC), which uses greedy heuristics to determine the shortest evolutionary scenario of rearrangements. Results: Our knowledge of the relative genomic positions of the inversion breakpoints in An. daciae and An. messeae enabled us to use the An. atroparvus genome as an outgroup and the GIC tool to show that the X0 and X2 arrangements emerged independently along the evolutionary lineages of An. daciae and An. messeae, respectively, based on the X1 arrangement. Conclusions: These results refine the structure and boundaries of the X chromosome rearrangements and reconstruct the sequence of evolutionary events in the cryptic complex An. messeae–An. daciae, demonstrating that the X1 arrangement is ancestral. This study lays the groundwork for analyzing the molecular organization of breakpoints, the mechanisms of inversion formation, and their role in speciation.
Integrating Pavement Friction and Macrotexture into a Speed-Dependent Pavement Safety Metric for Safety Performance Modeling
Bazmara, Behrokh; Izeppi, Edgar de León; Katicha, Samer W.; McCarthy, Ross; Flintsch, Gerardo W. (MDPI, 2025-12-20)
The paper proposes a pavement safety index, the estimated available friction at the expected travel speed, FRS(v), to model the composed effect of low-slip speed friction and macrotexture on roadway crashes. This index seems to capture the relative contributions of microtexture and macrotexture across different operating speeds. Speed-dependent available friction at 40, 55, and 70 mph was estimated using the speed-correction procedure in ASTM E1960-07 and integrated into Safety Performance Function (SPF) development. Comparison of the resulting SPF models suggests that FRS values corresponding to typical operating speeds can capture the combined influence of SFN (40) and macrotexture on expected crashes for freeways and rural two-lane, two-way highways. For freeways, the estimated available friction at 70 mph (FRS113) produced the most appropriate SPF, evidenced by the lowest AIC. For rural two-lane, two-way highways, the estimated available friction at 40 mph (FRS65) resulted in the lowest AIC value, consistent with the typical operating speeds on these facilities. In contrast, none of the speed-specific friction estimates produced satisfactory model performance for urban and suburban arterials, likely due to the wide variation in traveling speeds and geometric characteristics on these facilities. The applicability of the proposed metric was demonstrated through the development of illustrative investigatory friction levels based on observed crash data, and the identification of candidate roadway segments for friction improvement interventions, and the estimation of the corresponding return on investment for these interventions.

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