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Integrating frailty interventions into existing care models: a comprehensive approach to enhancing patient outcomes in chronic disease management
Get PDFFrailty syndrome (FS) is a complex and multifaceted condition commonly observed in old adults patients with chronic diseases, often accompanied by cognitive impairments. This review explores the integration of frailty interventions into existing care models to improve patient outcomes, focusing on four key areas. First, it emphasizes the importance of comprehensive assessment tools to identify frailty and cognitive impairments early, facilitating targeted care planning. Second, it highlights the value of personalized interventions, such as dietary modifications, exercise programs, and cognitive training, tailored to individual patient needs and preferences. Third, the review underscores the critical role of multidisciplinary care teams in providing holistic and coordinated care, leveraging the expertise of diverse healthcare professionals. Finally, it examines the potential of technological innovations and caregiver support systems in enhancing frailty management and addressing the challenges posed by cognitive impairments. By integrating these approaches, this review presents a patient-centered framework aimed at mitigating the impact of frailty and improving long-term outcomes. The findings emphasize the need for a unified strategy that combines personalized care, interdisciplinary collaboration, and technological advancements to address the multifaceted challenges of frailty in chronic disease management
Prescribed Performance-Based Switching Tracking Algorithm for DC–DC Buck Power Converter With Nonaffine Input and Stochastic Disturbance
No full textThis article explores the tracking issue for dc–dc buck power converter with stochastic disturbance, specifically focusing on how output voltage tracks to a desired voltage in a finite-time when the load changes. Meanwhile, considering unmodeled dynamics and nonaffine inputs, we propose an innovative finite-time fuzzy prescribed performance switching tracking algorithm to achieve tracking goal. For realizing the requirements of performance, the algorithm converts the tracking error to a new state by means of a coordinate transformation via the tangent function. In addition, the universal approximation capacity of the fuzzy-logic system is utilized to estimate the unknown nonlinear term effectively. On this basis, the designed adaptive dynamic event-triggered controller can not only ensure that all the signals for the closed-loop system remain bounded in probability but also guarantee that the tracking error will converge to a predetermined small neighborhood. Meanwhile, different piecewise functions are added into the controller to characterize prescribed performance and avoid singularity problems, respectively. Finally, the effectiveness of the tracking control algorithm is fully demonstrated by the simulations of the dc–dc buck power converter
Mechanical and thermal properties of polylactic acid blended with recycled polymethyl methacrylate
Get PDFThis study investigates the effect of incorporating recycled polymethyl methacrylate (r-PMMA) into polylactic acid (PLA) and further modifications with a bio-based compatibilizer (epoxidized soybean oil [ESO]). Various PLA:r-PMMA ratios were evaluated, with and without ESO. Blending r-PMMA into PLA significantly influenced mechanical properties. The 10PLA90r-PMMA blend showed enhanced elongation at break (6.10%) and tensile toughness (1686 kJ/m3) compared to pure PLA (3.34% and 737 kJ/m3, respectively), addressing PLA's inherent brittleness. The 30PLA70r-PMMA composition exhibited a tensile strength (TS) of 51.44 MPa and significant tensile toughness (1237 kJ/m3). Thermal analysis revealed an increase in the glass transition temperature (Tg) with higher r-PMMA content, reaching 124°C for 100r-PMMA, and a decrease in crystallinity percentage from 68.17% (pure PLA) to 30.43% (50PLA50r-PMMA). Incorporating ESO into a 50 PLA50r-PMMA blend modified its properties. Adding 3 parts per hundred resins (phr) ESO improved elongation at break (5.68%) and tensile toughness (1302 kJ/m3) while reducing TS (35.03 MPa). At 6 phr ESO, flexibility was maximized with an elongation of 6.37%, but TS decreased to 26.89 MPa. These findings highlight the synergy between r-PMMA and ESO in enhancing PLA's performance for sustainable applications and balancing mechanical and thermal properties while addressing environmental challenges
Special Issue: Scientific Advances in River Restoration
Get PDFIn September 2023, the River Restoration Centre (RRC) hosted the inaugural Scientific Advances in River Restoration (SARR) conference in collaboration with the University of Liverpool, UK. As we confront the twin crises of climate change and biodiversity loss, this event underscored the importance of global collaboration among river restoration scientists to help inform evidence-led solutions. Fluvial systems are particularly vulnerable to global climatic pressures, with droughts and floods exacerbating the impacts of human-induced river modifications. River restoration is a crucial tool in addressing these pervasive challenges, capable of benefiting both people (e.g., flood mitigation, community engagement) and nature (e.g., ecological recovery, ecosystem functionality). The SARR conference aimed to unite scientists from various disciplines and countries, foster collaborations, and highlight new advancements to enhance global progress in river restoration science. This river restoration special issue features a diverse selection of papers presented at the SARR conference, showcasing the multidisciplinary nature of contemporary river restoration
A decade review on hardwood composites and their research developments
Get PDFComposite materials, such as engineered wood products (EWPs), are favored for their stability, durability, and uniform mechanical properties, making them a potential way to valorize hardwood species. Therefore, this article aims to present a decade review of hardwood composites and their developments. The methodology of this review was divided into three main parts. First, a search for peer-reviewed articles on EWPs published between 2012 and 2023 was conducted using the Web of Science (WOS) database. Second, the data extracted from the WOS database were analyzed using the Virtual Operating System (VOS) viewer and a bibliometric approach. Third, selected peer-reviewed articles were systematically reviewed and included in this study, and their main findings were presented. The reviewed documents showed that hardwood composites are favored for their stability, durability, and uniform mechanical properties, which make them attractive for various engineering applications. Some key findings from the review include the potential of Yellow Birch to enhance wood-plastic composites by improving flexural strength and reducing flammability. Eucalyptus nanofibers have shown promise in enhancing the mechanical performance of composite mixtures. Hybrid poplar has been identified for its suitability in cross-laminated timber (CLT) products as they meet and exceed the shears and bending strength required by ANSI/APA PRG-320. Moreover, I-joists made from hardwood residues exhibit comparable mechanical performance to commercial counterparts. The review underscores the need for continued research and development to foster wider adoption of these valuable materials
Reevaluating Intermarket Connectedness: The Impact of Monday Return Calculations on Cryptocurrencies and Traditional Assets
Get PDFCryptocurrencies trade continuously, unlike traditional assets limited to weekdays, creating challenges in calculating Monday returns. This paper investigates the impact of four benchmark closing prices—Friday, Saturday, Sunday, and a weekend average—on intermarket connectedness. Analyzing 72 cryptocurrencies (2018–2024) and their relation to the S&P500 using the TVPVAR model, we find significant variations in economic and statistical outcomes, influencing both the magnitude and direction of spillovers. Mixed log- and non-log-based return methods yield inconsistent results for specific cryptocurrencies like THETA, GNO, GLM, and WAVES. These findings highlight the critical importance of consistent return methodologies in cryptocurrency market analysis
Wireless Rechargeable Sensor Networks: Energy Provisioning Technologies, Charging Scheduling Schemes, and Challenges
Get PDFRecently, a plethora of promising green energy provisioning technologies has been discussed in the orientation of prolonging the lifetime of energy-limited devices (e.g., sensor nodes). Wireless rechargeable sensor networks (WRSNs) have emerged among other fields that could greatly benefit from such technologies. Such an ad-hoc network comprises a base station(s) and multiple sensor nodes, which are primarily deployed in harsh environments, meeting the requirements of transmitting, receiving, collecting, and processing data. Unlike existing works, this survey paper focuses on energy provisioning technologies within the context of WRSNs by reviewing two interrelated domains. First, we introduce various energy provisioning techniques and their associated challenges, including conventional energy harvesting methods (e.g., solar, thermal, and mechanical). We highlight wireless power transfer (WPT) as one of the most applicable technologies for WRSNs, covering both radiative and non-radiative WPT. Additionally, we present radio frequency (RF) energy harvesting, including simultaneous wireless information and power transfer (SWIPT) and wireless powered communication networks (WPCNs), as well as backscatter communications. Furthermore, we compare hybrid energy harvesting techniques (e.g., solar-RF, vibro-acoustic, solar-thermal, etc.). Second, we introduce the fundamentals of wireless charging, reviewing various charger types (static and mobile), charging policies (including full and partial charging), charging modes (offline and online), and charging schemes (periodic and on-demand). We also present the collaborative charging mechanisms. Additionally, we address several key challenges facing WRSNs, such as energy consumption, multi-charger coordination, dynamic network recharging, monitoring & security threats, vehicle-to-vehicle (V2V) charging, and hybrid WRSNs Finally, we highlight trends and future directions for integrating advanced artificial intelligence (AI) technologies into WRSNs
Written evidence submitted by the research team of the following project: “Investigating the use of temporary accommodation for housing asylum seekers and refugees during the COVID-19 outbreak”
No full textWritten evidence submitted to Home Affairs Committee inquir
Large language models for pattern recognition in text data
Get PDFLarge language models (LLMs) are widely deployed in settings where both reliability and efficiency matter. We present a calibrated, seed‑robust empirical comparison of an encoder fine‑tuned model (bidirectional encoder representations from transformers (BERT)‑base) and a decoder in‑context model (generative pre-trained transformer (GPT)‑2 small) across Stanford question answering dataset v2.0 (SQuAD v2.0) and general language understanding evaluation (GLUE)-multi-genre natural language inference (MNLI), Stanford sentiment treebank 2 (SST‑2). Beyond accuracy, we assess reliability (expected calibration error with reliability diagrams and confidence–coverage analysis) and efficiency (latency, memory, throughput) under matched conditions and three fixed seeds. BERT‑base yields higher accuracy and lower calibration error, while GPT‑2 narrows gaps under few‑shot prompting but remains more sensitive to prompt design and context length. Efficiency benchmarks show that decoder‑only prompting incurs near‑linear latency/memory growth with k‑shot exemplars, whereas fine‑tuned encoders maintain stable per‑example cost. These findings offer practical guidance on when to prefer fine‑tuning versus prompting and demonstrate that reliability must be evaluated alongside accuracy for risk‑aware deployment
Prehabilitaiton for people with cancer clinical and implementation guidelines
No full textPolicy recommendations for prehabiitation for people with cancer - implementation and clinical guideline
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