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This paper aims to concentrate on recent innovations in flexible wearable sensor technology tailored for monitoring vital signals within the contexts of wearable sensors and systems developed specifically for monitoring health and fitness metrics.

In recent decades, wearable sensors for monitoring vital signals in sports and health have advanced greatly. Vital signals include electrocardiogram, electroencephalogram, electromyography, inertial data, body motions, cardiac rate and bodily fluids like blood and sweating, making them a good choice for sensing devices.

This report reviewed reputable journal articles on wearable sensors for vital signal monitoring, focusing on multimode and integrated multi-dimensional capabilities like structure, accuracy and nature of the devices, which may offer a more versatile and comprehensive solution.

The paper provides essential information on the present obstacles and challenges in this domain and provide a glimpse into the future directions of wearable sensors for the detection of these crucial signals. Importantly, it is evident that the integration of modern fabricating techniques, stretchable electronic devices, the Internet of Things and the application of artificial intelligence algorithms has significantly improved the capacity to efficiently monitor and leverage these signals for human health monitoring, including disease prediction.

This research focuses on the work–family facilitation process to theorize and examine the potential positive impact of perceived overqualification (POQ) on an individual’s work–family interface. Drawing on social cognitive theory of self-regulation, this research identifies work–family balance self-efficacy (WFBSE) as a motivational mechanism through which POQ affects work engagement. Additionally, it proposes flexibility human resource (HR) practices as a key moderator of this process.

This research collected multi-wave time-lagged data from 342 managers in the hospitality industry. The research focused on managers with the title of headwaiter and above, while front-line service personnel were not included.

The results showed that POQ had an indirect positive relationship with work engagement via WFBSE. The results also showed that employee-experienced flexibility HR practices moderated the effectiveness of WFBSE in translating POQ into work engagement.

This research provides guidance and insights into how HRM systems can be customized to sustain positive outcomes in situations of overqualification. It is crucial that hotels offer flexibility options or individualization of work arrangements for overqualified employees.

The potential positive impact of POQ on employees’ work–family interface has been neglected. In addition, prior research has devoted little attention to potential organizational factors that enhance the positive effects of POQ. By examining the mediating and moderating effects, this research aims to explain how and under what conditions POQ facilitates work engagement.

The objective of this paper is to develop a condition-based maintenance (CBM) scheme for pneumatic cylinders. The CBM scheme will detect two common types of air leaking failure modes and identify the leaky/faulty cylinder. The successful implementation of the proposed scheme will reduce energy consumption, scrap and rework, and time to repair.

Effective implementation of maintenance is important to reduce operation cost, improve productivity and enhance quality performance at the same time. Condition-based monitoring is an effective maintenance scheme where maintenance is triggered based on the condition of the equipment monitored either real time or at certain intervals. Pneumatic air systems are commonly used in many industries for packaging, sorting and powering air tools among others. A common failure mode of pneumatic cylinders is air leaks which is difficult to detect for complex systems with many connections. The proposed method consists of monitoring the stroke speed profile of the piston inside the pneumatic cylinder using hall effect sensors. Statistical features are extracted from the speed profiles and used to develop a fault detection machine learning model. The proposed method is demonstrated using a real-life case of tea packaging machines.

Based on the limited data collected, the ensemble machine learning algorithm resulted in 88.4% accuracy. The algorithm can detect failures as soon as they occur based on majority vote rule of three machine learning models.

Early air leak detection will improve quality of packaged tea bags and provide annual savings due to time to repair and energy waste reduction. The average annual estimated savings due to the implementation of the new CBM method is $229,200 with a payback period of less than two years.

To the best of the authors’ knowledge, this paper is the first in terms of proposing a CBM for pneumatic systems air leaks using piston speed. Majority, if not all, current detection methods rely on expensive equipment such as infrared or ultrasonic sensors. This paper also contributes to the research gap of economic justification of using CBM.

The prevalence of exposure to adversity is elevated in autistic populations, compared to neurotypical peers. Despite this, the frequency and nature of early adverse experiences are not well understood in autistic adults, with several underlying methodological limitations in the available literature. The purpose of this study is to systematically synthesise and analyse the prevalence of childhood adversity in this marginalised population, in accordance with the adverse childhood experiences (ACEs) framework.

Peer-reviewed empirical research articles were systematically searched for from electronic databases and screened against established inclusion criteria. Pooled prevalence rates for individual ACE types were calculated.

Four papers were included (N = 732), all of which used a predominantly or exclusively female sample. Only sexual abuse was reported in all papers, with a pooled prevalence rate of 38%. Physical abuse and emotional abuse were less frequently explored, with two papers reporting on these ACEs, though obtained comparable and higher pooled prevalence rates (39% and 49%, respectively). Pooled prevalence rates could be calculated for neither neglect nor “household” ACEs because of insufficient data. The limited state of the evidence, in conjunction with high levels of heterogeneity and poor sample representativeness found, positions the ACEs of autistic adults as a critical research priority.

To the best of the authors’ knowledge, this study is the first to systematically synthesise the prevalence of early childhood adversities, as conceptualised in accordance with the ACEs framework, in adults with autistic traits.

The purpose of this paper is to assess sub-national business cycle (BC) synchronization's impact on national cycles in four emerging markets economies with inflation targeting (IT-EMEs): Brazil, Colombia, South Korea and Mexico.

The authors use panel data models with fixed-effects and distributed lags.

The authors disclosed that sub-national synchronization increased national cycle amplitudes during expansion and recession phases. The authors also noticed that South Korea exhibited a more pronounced effect compared to Latin American countries, and this seemed to be associated with differences in the homogeneity of the production structures in the regions of these countries.

The authors cautioned that contrasting the findings with prior research on the effects of regional BC synchronization in IT-EMEs or with studies in different geographical contexts, is not possible due to the absence of prior research endeavors with this specific focus.

This study constitutes a first attempt to explain the impact of subnational cycle synchronization on the magnitude of national cycles in four IT-EMEs.