Polytechnic University

ABSTRACT Alzheimer’s disease (AD) is a neurodegenerative disorder and the most common cause of dementia in humans. The accumulation of abnormal protein aggregates, including extracellular amyloid plaques and intracellular neurofibrillary tangles, is considered a key pathological hallmark of AD. Currently, the primary approach for treating AD is pharmacological treatment, which is only symptomatic and unable to cure or reverse the progression of AD. Increasing evidence suggests that radiofrequency electromagnetic fields (RF-EMFs) may attenuate the progression of AD and improve memory function. This article reviews the studies related to the application of RF-EMFs in the field of AD, including investigations at the cellular and molecular levels, in animal models, and in clinical applications. The therapeutic potential of RF-EMFs as an intervention for AD is discussed in the present review, along with current challenges and future research directions.

A novel polarity-switching photoelectrochemical (PEC) sensing method was proposed for quantifying ochratoxin A (OTA). Aminated dendritic mesoporous silica nanoparticle (DMSN) with well-defined pores was synthesized to encapsulate hemin, and its pore channels were sealed by OTA-specific aptamers as gatekeepers. Specific binding of OTA to the aptamer induced conformational changes and aptamer dissociation, triggering the release of entrapped hemin. The released hemin was captured by a hydrogen-bonded organic framework (HOF-101) modified electrode, which switched the photocurrent polarity from cathodic to anodic, with the anodic signal linearly increasing with OTA concentration. Under optimized conditions, the method exhibited a linear range of 10 pg mL-1-10 μg mL-1 and a limit of detection (LOD) of 3.5 pg mL-1. Validated with camellia oil samples, its results were comparable to high-performance liquid chromatography (HPLC), verifying reliability for OTA detection in complex food matrices.

Purpose: This study evaluated the effectiveness of the online and face-to-face formats of a course-based Positive Youth Development (PYD) program, “Tomorrow's Leaders,” in promoting holistic development among university students in Hong Kong. Method: Utilizing a one-group pretest-posttest design, this study collected data from students who took the course “Tomorrow's Leaders” before and after the course, with 2,695 students enrolled online and 4,056 students enrolled face-to-face. Results: Students demonstrated enhanced PYD attributes, psychological well-being, and desired graduate qualities in both formats. Students in the face-to-face format showed greater improvement than those in online format in specific outcomes (e.g., self-determination, life satisfaction, and problem-solving ability). Discussion: The findings supported the effectiveness of the online PYD program but also highlighted the advantages of face-to-face learning. This disparity underscores the critical role of interpersonal engagement in nurturing leadership abilities and fostering a positive self-concept in young people, which is relevant to youth social workers.

Nontyphoidal Salmonella (NTS) is a major foodborne pathogen, and rising antimicrobial resistance (AMR) threatens treatment efficacy. Salmonella remained the leading cause of bacterial foodborne outbreaks in Hong Kong, but data regarding its prevalence in retail meats are limited. This study investigated the prevalence, serotype distribution, AMR patterns, and genetic relationships of Salmonella in retail pork, beef, and chicken collected across Hong Kong from July 2022 to June 2023. We found a high overall Salmonella prevalence (27.6%), particularly in pork (50.6%) and fresh, non-chilled meat (46.2%), suggesting potential contamination during slaughter, with the non-chilled conditions potentially promoting further bacterial growth. The dominant serotypes (S. typhimurium, S. Rissen, S. Derby, S. London), mainly from pork and beef, mirrored the top serotypes and key AMR profiles (ciprofloxacin, ceftriaxone) found in local human clinical cases, highlighting the food chain's relevance. High rates of multidrug non-susceptibility (68.7%) and non-susceptibility to critical antibiotics like ciprofloxacin (69.6%), ceftriaxone (7.8%), and azithromycin (8.3%) were observed. Phylogenetic analysis identified multiple genetically related clusters containing both human and food isolates, with clonal spread predominant in pork/beef serotypes and plasmid-mediated AMR determinants in chicken serotypes. Notably, several clusters showed non-susceptibility to multiple first-line antimicrobials, highlighting concerning transmission patterns from retail meats to clinical cases. This study provides crucial baseline data and identifies high-risk transmission pathways between food sources and clinical cases, underscoring the need for integrated genomic surveillance to combat AMR Salmonella in Hong Kong's food supply.

Low interfacial thermal conductance often emerges as a primary barrier to effective heat management in advanced nanodevices. This study examines how topological defects affect the interfacial thermal conductance of graphene/SiC lateral heterostructure, utilizing nonequilibrium molecular dynamics simulations. The significant lattice mismatch between graphene and SiC results in a pristine interface that experiences severe strain and structural distortion, ultimately reducing the level of phonon transmission. By introduction of 5|8|5 topological defects, the interfacial deformation is effectively alleviated, thereby improving phonon coupling across the boundary. The results reveal an unconventional increase in interfacial thermal conductance, with the maximal value achieved when three defects are incorporated, representing a 61% improvement compared with the pristine interface. However, an excessive number of defects can lead to a reduction in the thermal conductivity. These findings demonstrate that controlled defect engineering offers a tunable pathway to optimize interfacial heat transport in 2D heterostructures, providing valuable insights for thermal management in nanoscale devices.

. In this article, we consider the problem of parameter estimation for the Cox-Ingersoll-Ross model. The trajectory fitting estimation method is not directly applicable because it yields inconsistent estimators. Hence, the improved trajectory fitting estimation approach is used to obtain the consistency estimators for drift parameters based on continuous observation. We study the strong consistency and asymptotic behavior of the improved trajectory fitting estimators. Computer simulations are performed to illustrate our theory.

ABSTRACT This research investigates the fault detection for discrete‐time switched positive systems under unknown‐but‐bounded disturbances through a zonotope‐based residual evaluation methodology. Compared with the existing findings, the proposed framework introduces a dynamic threshold, thereby achieving an improvement in detection sensitivity while preserving robustness against disturbances. First, we develop a criterion to guarantee the stability and performance for the augmented system. Building upon the analysis results, a co‐design procedure is formulated to simultaneously optimize positive fault detection observers and switching signals for the underlying system. Furthermore, we construct a residual zonotope that geometrically encapsulates the admissible state trajectories of the fault‐free augmented system. The efficacy of the presented zonotopic fault detection scheme is substantiated through illustrative examples.

The study of the mental health of residents in the prosperous southern regions of China, which have experienced long-term rapid growth, is a very meaningful topic. Studies that approach the issue from the perspective of the relationship between environmental governance efficiency and residents' consumption level are quite rare. This study explores the nexus of environmental governance efficiency and residents' life satisfaction in Guangdong Province, China, through a psychological and public administration lens, using panel data from 21 cities (2001-2023). Life satisfaction, a critical indicator of mental health, is proxied by the ratio of consumption expenditure to disposable income, reflecting residents' economic behavior and wellbeing. Environmental governance efficiency, measured via the super-efficiency SBM model of Data Envelopment Analysis (DEA), captures the psychological benefits of effective public administration by improving living conditions through sustainable environmental policies. Two-way fixed effects models, validated by the Hausman test were employed. We find a significant positive relationship between governance efficiency and life satisfaction (FE1, FE2, and FE4, p < 0.001; FE3, p < 0.01), underscoring the role of high-quality governance in fostering mental wellbeing. Environmental governance efficiency, health insurance coverage, per capita GDP, fiscal self-sufficiency, and economic openness significantly enhance residents' life satisfaction in Guangdong by increasing consumption expenditure, though industrial production and government scale show negative effects, and regional disparities persist. The fixed-effect model, validated by the Hausman test, confirms these findings, highlighting the importance of high-quality governance and social services in supporting mental wellbeing. In Guangdong, a region marked by rapid urbanization and economic dynamism, efficient environmental governance mitigates pollution and enhances urban livability, positively impacting residents' mental health. This study demonstrates that efficient environmental governance in Guangdong Province significantly enhances residents' life satisfaction by improving living conditions and supporting mental wellbeing, offering a replicable model for sustainable development in rapidly growing economies.

Link prediction is a fundamental problem for graphs, which can reveal the potential relationships between users. Graph embedding can easily encode graph structural relations, and heterogeneous attribute features in a continuous vector space, which is effective in link prediction. However, graph embedding methods for large-scale graphs suffer high computation and space costs, and sampling enclosing subgraphs is a practical yet efficient way to obtain the most features at the least cost. Nevertheless, the existing sampling techniques may lose essential features when the random sampling number of nodes is not large, as node features are assumed to follow a uniform distribution. In this paper, we propose a novel large-scale graph sampling strategy for link prediction named Weighted Sampling Enclosing subgraphs-based Link prediction (WSEL) to resolve this issue, which maximumly preserves the structural and attribute features of enclosing subgraphs with less sampling. More specifically, we first extract the feature importance of each node in an enclosing subgraph and then take the node importance as node weight. Then, random walk node sequences are obtained by multiple weighted random walks from a target pair of nodes, generating a weighted sampling of enclosing subgraphs. By leveraging the weighted sampling enclosing subgraphs, WSEL can scale to larger graphs with much less overhead while maintaining some essential information of the original graph. Experiments on real-world datasets demonstrate that our model can scale to larger graphs while maintaining competitive link prediction performance under substantially reduced computational cost.

The craft beer market is continually expanding, driven by the consumers’ demand for product diversification, which leads to innovation in the brewing industry. While traditional brewing focuses on consistency and high-volume efficiency using standard yeasts, craft brewing prioritizes small-batch experimentation and flavor complexity. Traditionally, Saccharomyces cerevisiae (Ale beer) and Saccharomyces pastorianus (Lager beer) yeast are used in brewing. The craft brewing revolution introduced the use of non-conventional yeast. These yeasts possess distinct technological characteristics compared to commercial starters, such as a richer enzyme profile. This biological diversity produces beers with novel, complex aroma profiles, and opens exciting avenues for flavor creation. Recently, non-alcoholic beer and low-alcoholic beer (NABLAB), and functional beer have become the new horizons for the application of non-conventional yeasts. In recent years, the brewing potential of these alternative yeasts has been extensively explored. However, some aspects relating to the interactions between yeast and raw materials precursors involved in the aroma of the final beer, and the management of yeasts in fermentation, remain unexplored. This review systematically outlines the various innovative ways in which non-conventional yeasts are applied in brewing, including healthier beer. Here, we explore how these yeasts can foster innovation in the beer sector and provide the possibility for sustainable development in contemporary brewing.