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Elevators, escalators and travelators have been developed to enable people to save time and physical strength when traveling. As places such as shopping malls, hotels and airports have become dependent on these transportation technologies, major problems can occur when they stop working. This paper reviews the historical steps used to address the reliability and safety of these human transportations – technologies and how fault diagnosis, fault detection and health monitoring, and maintenance forecasting are now being implemented, as well as the potential for further advancements.

Eddy current testing (ECT) is an established non-destructive evaluation (NDE) technique to evaluate materials. In last decade, machine learning (ML) has revolutionized many areas and ECT is not an exception. The focus of ML in ECT system is to automate some of its analyses for the possible in-situ monitoring of the process and to alleviate the interpretation burden on the operator. The fusion of ML and ECT is not new, however, due to recent advancements in machine learning, there is a need to assess the current potential of ML for ECT systems and identify any gaps and shortcomings for automated data analysis. Thus, this article discusses the findings of a literature survey about the contemporary methods of using machine learning for the automatic analysis of ECT data. The application of machine learning for the ECT system is described in a general workflow manner that begins with data collection and ends with the verification and validation of the performance of ML models. Findings on potential areas of application of the fusion of ML and ECT along with limitations and potential gaps are discussed. This study also identifies the need for common datasets, sample size determination and uncertainty quantification of ML models.

Abstract BackgroundCOVID-19 ended on May 5, 2023, and since then Hong Kong reported increased mental distress, which was speculated to be from the policies implemented during the pandemic. Despite this, longitudinal surveillance of deliberate self-harm (DSH) incidences throughout the pandemic in Hong Kong remained insufficient. ObjectiveThe objective of this study was to outline the changes in DSH incidences before and during the COVID-19 pandemic in Hong Kong, with respect to sex, age, and co-occurring mental health issues. MethodsA quasi-experiment was conducted using an interrupted time series design to estimate the impact of the pandemic on DSH-related emergency department (ED) visits. This design enabled the estimation of DSH-related ED visits based on prepandemic data from 2016 to 2019, assuming the pandemic had not occurred, and allowed for a comparison with observed DSH-related ED visits during the pandemic. The descriptive results were reported as the observed monthly DSH-related ED visits and observed incidence ratios during the pandemic. Afterwards, a negative binomial model was fitted to the prepandemic data (2016‐2019) and adjusted for temporal trends, seasonality, and population variation to estimate the expected monthly DSH-related ED visits and adjusted incidence ratios (aIRs). ResultsBetween January 2016 and December 2022, a total of 31,893 DSH episodes were identified. Initial descriptive analysis showed a significant difference in demographic characteristics (sex) and clinical characteristics (death within 28 d, diagnoses of co-occurring mental health issues, public assistance pay code, and triage level). Subsequent interrupted time-series analysis demonstrated significantly increasing trends in comparison with the prepandemic period. As reported in the aIRs among young adult males (aIR in 2020=1.34, PPPPPPPPPPPP ConclusionsThe average annual DSH-related ED visits increased during the pandemic period. Therefore, there is a need to raise awareness for such vulnerable groups in Hong Kong to prepare for postpandemic spillover.

Objective Disease activity both between and within patients with SLE is highly variable, yet factors driving this variability remain unclear. This study aimed to identify predictors of variability in SLE disease activity over time.Methods We analysed data from 2930 patients with SLE across 13 countries, collected over 38 754 clinic visits between 2013 and 2020. Clinic visit records were converted to panel data with 1-year intervals. The time-adjusted mean disease activity, termed AMS, was calculated. The yearly change in AMS, denoted as ΔAMSt, was regressed onto AMSt−1 and other potential predictors using random-effects models. Some variables were split into a person-mean component to assess between-patient differences and a demeaned component to assess within-patient variability.Results Overall, variability in SLE disease activity exhibited stabilisation over time. A significant inverse relationship emerged between a patient’s disease activity in a given year and variability in disease activity in the subsequent year: a 1-point increase in person-mean disease activity was associated with a 0.27-point decrease (95% CI −0.29 to –0.26, p

Summary: Background: Genome sequencing (GS) has revolutionised the diagnostic odyssey of patients with rare genetic diseases (RDs) and accelerated large-scale genome projects globally. However, the impact of GS on patients with RDs is yet to be investigated among genome projects in Asia. The Hong Kong Genome Project (HKGP) was implemented to benefit patients and families with RDs in Hong Kong, and to increase the inclusiveness of Chinese genomic data. This study evaluated the impact of short read GS (srGS), complemented by long read GS (lrGS) in a subset, on individuals recruited in the pilot phase of the HKGP. Methods: GS was performed on a prospective cohort of patients with suspected genetic disease recruited by territory-wide referrals to the HKGP. All participants received srGS, while lrGS was applied to a subset to resolve technically challenging regions unclear from srGS and provide phasing information for potential compound heterozygous variants. A phenotypic-driven diagnostic workflow was implemented to filter and prioritise rare and likely disease-causing variants. The primary outcome was diagnostic yield. The impact on the diagnostic odyssey and clinical management was also assessed. Findings: A total of 1264 individuals from 520 families with a broad spectrum of RDs were recruited, with 94% of probands being Chinese. srGS was performed for all individuals and lrGS was performed in 21 individuals. The use of srGS achieved a molecular diagnosis in 24% (125/520) of probands, and an additional 4% (21/520) with the assistance from lrGS. Approximately one-third of the identified diagnostic variants being novel. Diagnostic yield was found to be significantly higher among adult probands compared to paediatric probands (32% vs 24%; p = 0.025). The diagnostic yield was significantly higher in probands without prior genetic testing (37%; n = 185) compared to those previously tested, including exome and genome sequencing (23%; n = 335) (p = 0.001). GS ended diagnostic odysseys with an average length of 15 years (0.5–59), and potentially impacted clinical management in 77% (113/146) of diagnosed probands. Interpretation: This population-based genome project shed light on the consideration of integrating srGS and lrGS in clinical workflows for RDs. The identification of unique and prevalent variants from Southeast Asia increased the inclusiveness of Chinese genomic data, contributing to greater representation and genomic diversity. Funding: The HKGP is a publicly funded genome sequencing initiative commissioned by the Health Bureau of the HKSAR Government.

ChestVolume is an R package and Shiny web application developed to facilitate the analysis of chest expansion using three-dimensional (3D) coordinate data obtained from optical motion capture systems. This software provides an end-to-end solution for respiratory analysis, including data preprocessing, marker position adjustment, volume calculation, and interactive visualization. The package includes functions for reformating marker data, adjusting marker positions, and calculating chest segment volumes using convex hull algorithms. Visualization tools allow users to explore chest expansion across time, providing a dynamic view of respiratory motion. The interactive Shiny app integrated with ChestVolume offers a user-friendly interface for individuals without advanced programming expertise, making chest volume analysis accessible to a wider audience. Users can upload 3D motion capture data, define custom chest segments, select specific time ranges, and visualize chest expansion patterns in both static and animated formats. These features enable researchers and clinicians to assess regional chest expansion and detect asymmetries in respiratory motion, which are crucial for understanding respiratory mechanics and evaluating conditions such as chronic obstructive pulmonary disease and spinal deformities. ChestVolume advances respiratory health research by providing an open-source, customizable, and accessible tool for the quantitative assessment of chest wall movement. The package supports personalized rehabilitation strategies by enabling the identification of asymmetric respiratory motion, facilitating targeted interventions to improve respiratory function, and ultimately contributing to enhanced clinical assessments and health outcomes.

BackgroundFostering a strong professional identity (PI) enhances career fulfillment. In China, therapy education is undergoing development, integrating both Western and traditional health concepts, causing inconsistent PI among therapy students. To date, no validated tools exist to measure and monitor PI of Chinese therapy students. This study aimed to translate and validate the 9-item MacLeod Clark Professional Identity Scale (MCPIS-9) for this purpose.DesignThis study involved translation and cultural adaptation of the MCPIS-9, followed by a rigorous assessment of its model fit and psychometric properties using data collected via an online questionnaire.MethodsA forward- and backward- translation process was conducted. Content validity was evaluated using item-level content validity index (I-CVI) and scale level content validity index average method (S-CVI/Ave). Therapy students across all grades at undergraduate and postgraduate levels in China were eligible. Exploratory factor analysis (EFA) examined the underlying factor structure. Model fit was evaluated through confirmatory factor analysis (CFA) using the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Standardized Root Mean Square Residual (SRMR) and Root Mean Square of Error of Approximation (RMSEA). Convergent validity was assessed through Pearson's correlations coefficient (r) with the Professional Identity Scale for Health Students and Professionals (PISHSP). Internal consistency was examined using Cronbach's Alpha (Cα) and McDonald's Omega (ω).ResultsA total of 1054 students participated. Content validity was excellent (I-CVI = 0.86-1.0, S-CVI/Ave = 0.98). EFA indicated a two-factor structure with acceptable model fit (CFI = 0.978; TLI = 0.968; SRMR = 0.033; RMSEA = 0.063). Reliability was strong (Cα = 0.835; ω = 0.817). Convergent validity demonstrated a strong correlation (r = 0.75) with the PISHSP.ConclusionsThe Chinese MCPIS-9 is a reliable and valid tool for assessing PI among therapy students. Future research could focus on refining item 4 of this tool, potentially through further exploration of therapy students' perceptions of PI within the unique context of the Chinese healthcare system.

Introduction COVID-19 infection is associated with post-acute adverse outcomes affecting multiple organ systems. Although preliminary studies have suggested that COVID-19 re-infection may have a cumulative effect on long-term outcome, differential effects of COVID-19 re-infection severe enough to be hospitalised on post-acute sequelae compared with hospitalised first-time infection have not been explored.Methods Retrospective cohort study using territory-wide electronic medical records databases in Hong Kong. Adults hospitalised with COVID-19 between 1 January and 30 November 2022, who survived the first 28 days after infection and was discharged, were categorised into re-infection and first-time infection groups. Individuals with reinfection were compared with those with first-time infection for all-cause mortality, all-cause hospital readmission, attendance to the emergency department and complications during the post-acute period using propensity-score-weighted Cox regression. Subgroup analyses were conducted by age (

Objective To estimate the prevalence of organ damage (damage) and flare and to examine longitudinal associations between flares and subsequent damage accrual, in patients with systemic lupus erythematosus (SLE).Methods Patients enrolled in the Asia Pacific Lupus Collaboration cohort with ≥3 years of prospectively captured data were studied. Flares were assessed at routine visits, while damage ((Systemic Lupus International Collaborating Clinics/American College of Rheumatology) Damage Index) was assessed annually. Multivariable, multifailure survival analyses were carried out to quantify the association between flares and damage accrual.Results 1556 patients with SLE with a median (IQR) of 5.7 (3.9, 7.0) years of follow-up were studied. 39.5% (n=614) of patients had damage at enrolment, and 31.9% (n=496) accrued damage during the study observation period. The incidence of damage accrual during observation was ~58/1000 person-years. Overall, 74.1% (n=1153) of patients experienced a flare of any severity (mild/moderate or severe) at least once; 56.9% (n=885) experienced recurrent (≥2) flares. The risk of subsequent damage accrual in patients who experienced mild-to-moderate flare, after controlling for confounders, was 32% greater than in patients without flares (adjusted HR) (95% CI 1.32 (1.17 to 1.72)). The risk of damage accrual was greater if patients had severe flares (HR (95% CI) 1.58 (1.18 to 2.11)). For each additional flare, the risk of damage accrual increased by 7% (HR (95% CI) 1.07 (1.02 to 1.13)).Conclusions Flares independently increased the risk of damage accrual. Prevention of flares should be considered a necessary goal of SLE disease management to minimise permanent damage.

BackgroundPerceived pain intensity is an important determinant of health-related quality of life. A lack of studies has investigated the co-influences of physical and psychosocial risk factors on perceived pain intensity and the shifts in effects after pandemic. As a post-COVID symptom, it is important to re-assess the risk factors for post-COVID heath care.MethodsFour dimensions of physical/psychosocial risk factors were assessed: medical history, personal wellbeing and psychological distress, lifestyle, and socio-demographic characteristics. We first identified subgroups with significant increase in perceived pain intensity after pandemic by a comparison with the baseline group (all participants). Based on the variables associated with a severe increase in pain score (NRS), multivariate regression models were applied to identify risk factors on perceived pain intensity.ResultsAmong 3,237 urban individuals in Hong Kong, 20.95 and 30.58% were with severe pain (NRS > = 4) before and after pandemic. Participants with respiratory disease had the most significant increase in perceived pain intensity (increase in NRS: 1.29 [0.65, 1.93]), seconded by those with known psychiatric diseases and living with special needs. After pandemic, insomnia, known psychiatric diseases, female, and low household income remained as significant risk factors, and insomnia remained as the most significant (estimate: 1.018 [CI: 0.814, 1.221]). The effect sizes of these factors were increased after pandemic. Respiratory disease, cardiovascular disease, and low education (secondary school or below) were additional risk factors.ConclusionIt is necessary to develop up-to-date interventions targeting vulnerable populations, particularly individuals with known psychiatric diseases and insomnia, for pain reduction.

The optical excitation and applications of molybdenum disulfide (MoS₂) is critical due to its limited thickness and susceptibility to damage from high-intensity laser illumination, which can cause significant local heating and structural degradation. To mitigate this issue, protective layers made from materials with high thermal conductivity and transparency, such as graphene (Gr), hexagonal boron nitride (h-BN), and Gr/h-BN heterostructure, have been explored. This study utilizes Raman and photoluminescence (PL) spectroscopy to assess the stability of both bare MoS₂ flakes and MoS₂ flakes covered with different protecting layers under varying laser power levels. When exposed to 13 mW/μm2 laser for 30 min, bare MoS₂ undergoes considerable structural degradation, characterized by the formation of protrusions and a reduction in the Raman signal to just 10 % of its original intensity. In contrast, the Gr/MoS₂ heterostructure maintains the stability of both the Raman fingerprint peaks and PL intensity, with only a 0–15 % decrease. The h-BN/MoS₂ system also shows improved stability, with the Raman signal decreasing to around 30 % of its initial intensity. Gr/h-BN/MoS₂ exhibits similar stability to Gr/MoS₂. These findings indicate that the Gr/MoS₂ system provides the highest stability under laser illumination, followed by the Gr/h-BN/MoS₂ system and the h-BN/MoS₂ system, while bare MoS₂ demonstrates the lowest stability. The combined effects of efficient thermal dissipation and isolation from ambient oxygen offer significant protection to MoS₂ under high-power illumination.

We administered both maximum-performance and typical-performance assessments of cultural intelligence to 114 undergraduates in a selective university in the Northeast of the United States. We found that cultural intelligence could be measured by both maximum-performance and typical-performance tests of cultural intelligence. Cultural intelligence as assessed by a maximum-performance measure is largely distinct from the construct as assessed by a typical-performance measure. The maximum-performance test, the Sternberg Test of Cultural Intelligence (SCIT), showed high internal consistency and inter-rater reliability. Sections with problems from two content domains--Business (SCIT-B) and Leisure (SCIT-L) activities--were highly intercorrelated, suggesting they measured largely the same construct. The SCIT showed substantial correlations with another maximum-performance measure of cultural intelligence, Views-on-Culture. It also was correlated, at more modest levels, with fluid intelligence and personal intelligence tests. Factorially, the (a) maximum-performance cultural intelligence tests, (b) typical-performance cultural intelligence test and a test of openness to experience, and (c) fluid intelligence tests formed three separate factors.

The editors of the journal focus on publication barriers in Academy of Management Review by conducting informal interviews with scholars from locations not currently represented in top management journals. These interviews provide key challenges in relation to patterns of training and national culture. The editors then propose solutions to these challenges including theory development as well as inclusive training and publishing opportunities.

The waste condenser heat from chiller systems in hotels is typically discharged into the environment, leading to energy waste and plume generation. However, the recovery of this waste heat is not common. Therefore, this study presents a time series analysis to evaluate the potential for waste heat recovery for sustainable hotel operations. The case study focuses on a prototype hotel in subtropical Hong Kong and its engineering systems are modeled using EnergyPlus. By incorporating heat exchangers and thermal storage systems, waste condenser heat can be recovered to fully meet the heating demand for daily service water, which was originally supplied by boilers for 79.32 % of the total time. This application offers several benefits. Firstly, it reduces annual carbon emissions by 40.23 kgCO2e/m2 (equal to 27.36 % of the baseline emissions) associated with water-cooled chiller systems by maximizing energy efficiency and minimizing waste heat. Secondly, it decreases the operating capacity of cooling towers at high heat rejection, which reduces the chance of plume emissions by 30.9 %. Finally, it lowers the annual gas consumption of boilers by 153.11 MJ/m2 (equal to 79.32 % of the baseline consumption) and can serve as an alternative to renewable solar thermal systems. Challenges and opportunities for recovering waste condenser heat are also discussed in detail. Notably, this study introduces a new approach of using outdoor enthalpy to normalize the cooling demand for improved energy management. Overall, this study provides a comprehensive assessment of waste condenser heat from chiller systems to promote sustainable development.

The IMPACC cohort, composed of >1,000 hospitalized COVID-19 participants, contains five illness trajectory groups (TGs) during acute infection (first 28 days), ranging from milder (TG1-3) to more severe disease course (TG4) and death (TG5). Here, we report deep immunophenotyping, profiling of >15,000 longitudinal blood and nasal samples from 540 participants of the IMPACC cohort, using 14 distinct assays. These unbiased analyses identify cellular and molecular signatures present within 72 h of hospital admission that distinguish moderate from severe and fatal COVID-19 disease. Importantly, cellular and molecular states also distinguish participants with more severe disease that recover or stabilize within 28 days from those that progress to fatal outcomes (TG4 vs. TG5). Furthermore, our longitudinal design reveals that these biologic states display distinct temporal patterns associated with clinical outcomes. Characterizing host immune responses in relation to heterogeneity in disease course may inform clinical prognosis and opportunities for intervention.