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Work re‐entry following maternity leave for first‐time mothers: An events, social identity and intersectional theories informed identity work framework
Get PDFMany first‐time mothers experience significant identity issues on work re‐entry following maternity leave, an important individual and life‐related event. Work re‐entry prompts significant identity tensions leading to identity work challenges and potential career changes. We address this significant life event and develop a subjective identity informed conceptual framework explaining its key components and outcomes. We propose that for first‐time mothers, re‐entry following maternity leave triggers a cognitive and subjective assessment of identity threat and opportunity leading to the use of multiple identity work strategies to address personal, role, and collective identities. We analyze the impacts of these reworked identities and identity work for career decision making and outcomes. We theoretically underpin our framework using event systems, a subjective perspective on social identity and intersectional theories and in doing so, propose future research questions and highlight implications for national policy and organizational practices
Material matters: recommendations for the analysis of relational spaces in sociotechnical transition studies
Get PDFThis Opinion Paper examines the interplay between materiality, relational spaces, and technological change dynamics. The objective is to introduce a novel theoretical perspective and a structured analytical process designed to enrich the investigation of relational spaces within the context of sociotechnical transitions. Our perspective aims to help transition scholars integrate the often-overlooked importance of material arrangements with the analyses of material flows and social components. We interpret this integration as a morphological approach to the analysis of relational spaces. The development of our perspective is grounded in a thorough review of existing literature on transition studies, complemented by the application of the theory of space constitution. Through our theoretical contribution, we advance the spatial discourse in transition studies, offering the means required to produce novel insights into how diverse social and material dimensions of spatial contexts affect, and are affected by, sociotechnical transition pathways and the technological change they produce
H∞ High-Order Repetitive Control for Functional Electrical Stimulation in Intention Tremor Suppression
No full textIntention tremor is a rhythmic and involuntary limb swing movement that causes significant inconvenience to the daily life of patients. Repetitive control is suitable for functional-electrical-stimulation-based intention tremor suppression because it can significantly attenuate the periodic signals. However, the performance of the repetitive controller may be weakened in tremor suppression due to uncertainties in the dynamics of the musculoskeletal model and the tremor frequency. In this paper, we propose an advanced methodology for tremor suppression by combining control with high-order repetitive control. The proposed controller can not only guarantee the robust stability of the system subjected to model uncertainty, but also effectively suppress tremors with varying frequency. Comparative experiments on the unimpaired subjects and intention tremor patients were carried out to verify the effectiveness of the proposed method. The experimental statistical analysis results show that the proposed high-order repetitive controller can suppress tremors by up to , which is about and higher than the single memory loop repetitive controller and the traditional filter-based controller, respectively. Note to Practitioners —Patients afflicted with wrist intention tremors encounter significant challenges while executing routine activities such as eating, writing, and dressing. Functional electrical stimulation for tremor suppression operates by generating electrical pulses that oppose the tremor motion, thereby inducing muscle contractions and diminishing tremor magnitude. Given the periodic nature of tremor signals acting as system disturbances, repetitive control emerges as an effective method for tremor suppression. However, the conventional repetitive controller cannot significantly improve the tremor suppression performance in practice due to the uncertain property of the musculoskeletal dynamics and the variation of tremor frequency. In this paper, a robust controller combining control with high-order repetitive control is proposed to address above issues. The high-order repetitive controller can effectively suppress the periodic tremor signals with varying frequency, and the controller can provide robust stability and the desired tracking performance by properly choosing of the weighting functions. The comparative experimental results, conducted on our self-built wrist tremor suppression experimental platform, involving unimpaired subjects and patients with intention tremors, validate that the proposed control approach enhances tremor suppression efficacy by 11% and 31%, compared to the traditional repetitive controller and the filter-based controller, respectively. The feasibility and effectiveness of the proposed approach is only initially verified by small scale test, and more clinical verifications will be carried out in tremor patients in the future
Towards sustainability: Examining financial, economic, and societal determinants of environmental degradation
Get PDFWe examine the determinants of environmental degradation, focusing on MENA economies from 1991 to 2020, with a particular focus on the role of sectoral composition. Specifically, we assess the contributions of the industrial, manufacturing, agricultural, and service sectors to GDP and their impact on environmental outcomes. Employing augmented mean group estimation, we evidence that technological advancements and renewable energy consumption significantly reduce environmental degradation, and that multinational corporations from developed countries transfer beneficial environmental practices to local firms in emerging regions. Results offer new insights into the impact of financial, economic, and societal factors on environmental outcomes
A non-linear Lasso and explainable LSTM approach for estimating tail risk interconnectedness
Get PDFTail risk inter-connectivity is a significant aspect and a risk indicator that should be focused on. Many of the previous works have shown potential non-linearity in tail risk contagion. With the recent advancements in deep learning, Long-Short Term Memory (LSTM) networks have played an important role in sequential data prediction. We experiment with LASSO-based neural networks and interpretative LSTM model along with other machine learning approaches for investigating tail risk interconnectedness among the public banks of Japan. We also investigate the risk reception from large overseas banks in United States finding that medium-sized banks are more likely to receive international risks. Our studies show that LSTM-based model is an excellent fit for the scenario and total connectedness goes up during an economic crisis. The banks having larger market capitalization are more prone to emission and reception of tail risks. This is accompanied by exhibiting the impact of some major economic distresses on Japanese banking system. These results provide important information to regulators and policy makers
Confucian Culture and Corporate Environmental Management: The Role of Innovation, Financing Constraints and Managerial Myopia
No full textThis paper explores the impact of Confucian culture on the environmental management practices of firms, utilizing data from A-share listed companies in China from 2009 to 2022. The study reveals several significant findings: (1) Firms in regions with a stronger presence of Confucian culture are more likely to adopt environmentally responsible management practices; (2) Confucian culture enhances firms' environmental management through three channels: promoting innovation, easing financing constraints, and reducing managerial myopia, with a particular emphasis on alleviating financing constraints; (3) Regional environmental regulations mitigate the positive influence of Confucian culture on firms' environmental management practices. This study contributes to the literature by elucidating the determinants of corporate environmental management and emphasizing the critical role of cultural factors, particularly in overcoming financial barriers, in corporate decision-making
Dynamic Caching Dependency-Aware Task Offloading in Mobile EdgeComputing
Get PDFMobile Edge Computing (MEC) is a distributed computing paradigm that provides computing capabilities at the periphery of mobile cellular networks. This architecture empowers Mobile Users (MUs) to offload computation-intensive applications to large-scale computing nodes near the edge side, reducing application latency for MUs. The resource allocation and task offloading in MEC has been widely studied. However, the burgeoning complexity inherent to modern applications, often represented as Directed Acyclic Graphs (DAGs) comprising a multitude of subtasks with interdependencies, poses huge challenges for application offloading and resource allocation. Meanwhile, previous work has neglected the impact of edge caching on the offloading execution of dependent tasks. Therefore, this paper introduces a novel dynamic caching dependency-aware task offloading (CachOf) scheme. First, to effectively enhance the rationality of cache and computing resource allocation, we develop a subtask priority computation scheme based on DAG dependencies. This scheme includes the execution sequence priority of subtasks on a single MU and the offloading sequence priority of subtasks from multiple MUs. Second, a dynamic caching scheme, designed to cater to dependent tasks, is proposed. This caching approach can not only assist offloading decisions, but also contribute to load balancing by harmonizing caching resources among edge servers. Finally, based on the task prioritization results and caching results, this paper presents a Deep Reinforcement Learning (DRL)-based offloading scheme to judiciously allocate resources and improve the execution efficiency of applications. Extensive simulation experiments demonstrate that CachOf outperforms other baseline schemes, achieving improved execution efficiency for applications
Digital credit and insurance: Improving economic well-being for rural households
Get PDFThe integration of digital technologies in credit and insurance services has important implications for the economic well-being of rural households. This paper utilizes cross-sectional data from a 2022 survey conducted with 476 rural households in China to explore the influence of digitally coordinated credit and insurance (DCCI) on economic well-being. Results indicate that DCCI significantly enhances both net incomes and farm incomes of rural households. Particularly, younger households, those engaged with digital technologies, and those facing high natural risks see greater benefits. Additionally, we find that reducing credit rationing and enhancing risk resilience are key mechanisms through which DCCI improves economic outcomes. The robustness of these results is confirmed through various analytical methods and measures. This study highlights the important role of digital transformation in the credit and insurance sectors for fostering economic growth in the rural sectors of emerging markets
A Pilot Randomized Controlled Trial Testing the Feasibility and Acceptability of Helping Ease Anxiety and Depression after Stroke (HEADS: UP): An Online Mindfulness-Based Intervention for Stroke Survivors
Get PDFObjectives: The purpose of this study was to assess feasibility and acceptability of a stroke-specific mindfulness-based intervention called Helping Ease Anxiety and Depression after Stroke (HEADS: UP). Method: This study was a mixed-methods pilot randomized controlled trial comparing HEADS: UP to treatment as usual (TAU). HEADS: UP is a 9-week mindfulness intervention for stroke survivors. UK (United Kingdon)-based stroke survivors were recruited and attended HEADS: UP Online. Psychological functioning outcomes measures and other data were collected online at pre-intervention (Week 0), post-intervention (Week 9), and follow-up (months 3 and 6). Participants were randomized 1:1 to either HEADS: UP or TAU. Results: Sixty-two participants completed baseline questionnaires and were randomized to HEADS: UP (n = 30) or TAU (n = 32). Retention rates were as follows: HEADS: UP (n = 25, 83.30%) versus TAU (n = 25, 78.10%) at post-intervention, HEADS: UP (n = 24, 80%) versus TAU (n = 26, 81.30%) at 3-month follow-up, and HEADS: UP (n = 20, 66.70%) versus TAU (n = 25, 78.10%) at 6-month follow-up. The mean age for HEADS: UP was 56.0 years versus 56.80 for TAU. The HEADS: UP group was 30% male, while the TAU group was 56% male. Depression Anxiety Stress Scales (DASS)-21 total mean score for HEADS: UP improved in the direction of expected effect (baseline 46.20, SD (standard deviation) = 24.00; post-intervention 24.00, SD = 16.10) indicating recovery versus no reliable change for TAU (baseline 36.10, SD = 18.70; post-intervention 31.60, SD = 20.40). HEADS: UP and TAU scores continued to improve over time. Between-group effect sizes (Cohen’s d) at post-intervention were large for BAI (Beck Anxiety Inventory) (d = 0.91), DASS-21 total (d = 0.89), and BDI (Beck Depression Inventory)-II (d = 0.86), highlighting the potential of HEADS: UP for improving depression and anxiety symptoms. At the six-month follow-up, the attrition rate was higher in the HEADS: UP group (33.30%) compared with TAU (21.90%). Conclusions: HEADS: UP is feasible and acceptable and has potential to improve depression and anxiety symptoms for stroke survivors. Preregistration: ClinicalTrials.gov: NCT04985838
Image De-noising Based on WMF Technique for Electrical Trees Structure in High Voltage Cable Insulation
Get PDFElectrical treeing is a common problem during the pre-breakdown phenomenon in solid insulations due to the damage caused by Partial Discharge (PD) that progresses through stressed insulation via chemical degradation, which resembles the shape of a tree root. This resulted in a decrease in performance through degrading the insulation, which became a serious problem while dealing with electrical equipment. Hence, a deep understanding of electrical tree structure is vital to improving the quality of solid insulations. Ergo, optical microscopy is primarily used to examine tree structures, shapes, and fractal dimensions to reconstruct electrical tree structures for morphological study. However, optical microscopy images are frequently degraded by noise from readout procedures or image data acquisition systems, noise caused by occlusion, illumination, non-uniform intensity, destroying potential tree pixels, and a critical loss of information about the electrical tree structures. Therefore, this research proposed the Wiener Median Fusion (WMF) filter for electrical tree study. The performance of the WMF de-noising technique improves the image quality for the precise portrayal of the electrical tree structure based on thresholding segmentation algorithm analysis in terms of accuracy, sensitivity, and false positive rate. Based on the analysis of the thresholding segmentation algorithm, Otsu's thresholding exhibits the highest result compared to Niblack. The Otsu's overall percentage in terms of accuracy is 80.2934%, the sensitivity is 99.1513%, and the false positive rate is 82.6265%
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