Revisiting the Antecedents of Social Entrepreneurial Intentions in Hong Kong

This study examined how empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and prior experience with social problems are associated with social entrepreneurial intentions. Through a survey, a sample of 252 Hong Kong students was used for analyses. Factor analyses supported that the antecedents of social entrepreneurial intentions could be divided into dimensions of empathy, moral obligation, social entrepreneurial self-efficacy, perceived social support, and prior experience with social problems. Multiple regression analysis results indicated that perceived social support was the most prominent antecedent of social entrepreneurial intentions, followed by moral obligation, empathy, and prior experience with social problems. Notably, moral obligation was revealed to be negatively associated with social entrepreneurial intentions.

TCN AA: A Wi Fi based Temporal Convolution Network for Human to Human Interaction Recognition with Augmentation and Attention

The utilization of Wi-Fi-based human activity recognition (HAR) has gained considerable interest in recent times, primarily owing to its applications in various domains such as healthcare for monitoring breath and heart rate, security, elderly care, and others. These Wi-Fi-based methods exhibit several advantages over conventional state-of-the-art techniques that rely on cameras and sensors, including lower costs and ease of deployment. However, a significant challenge associated with Wi-Fi-based HAR is the significant decline in performance when the scene or subject changes. To mitigate this issue, it is imperative to train the model using an extensive dataset. In recent studies, the utilization of CNN-based models or sequence-to-sequence models such as LSTM, GRU, or Transformer has become prevalent. While sequence-to-sequence models can be more precise, they are also more computationally intensive and require a larger amount of training data. To tackle these limitations, we propose a novel approach that leverages a temporal convolution network with augmentations and attention, referred to as TCN-AA. Our proposed method is computationally efficient and exhibits improved accuracy even when the data size is increased threefold through our augmentation techniques. Our experiments on a publicly available dataset indicate that our approach outperforms existing state-of-the-art methods, with a final accuracy of 99.42%.Comment: Published to IEEE Internet of things Journal but haven't been accepted yet (under review

The Effects of Green Energy Production on Farmland: A Case Study in Yunlin County, Taiwan

Taiwan enacted the Act of Renewable Energy in the year 2009 which promotes energy safety, green economy, and a sustainable environment, and with that the government envisages a contribution of photovoltaic energy of up to 20% by the year 2025. In this study we look into the motivation and background of this energy policy, plans for implementation and associated challenges, and its actual consequences for farmland use and farmers. In addition, we take a look into the implementation of mixed-use farmland in which agricultural activity and photovoltaic installations are planned to coexist in order to increase land value and productivity. We furthermore report on some of our findings related to a field survey conducted in Taiwan’s corn chamber of Yunlin County which has been facing a number of socioeconomic challenges

Experiences with a simple laparoscopic gastric tube construction

BACKGROUND: Minimally invasive esophagectomy (MIE) is a complex operation, and the detailed optimal surgical procedure has not been well described. Our aim was to evaluate use of a simple method of laparoscopic gastric tube construction as minimally invasive surgery for patients with esophageal cancer. METHODS: We performed a retrospective review of 26 consecutive patients who underwent MIE for esophageal cancer in the Koo Foundation Sun Yat-Sen Cancer Center between September 2009 and August 2011. Perioperative data and postoperative complications were statistically analyzed. RESULTS: The patient group consisted of 22 men and 4 women. MIE was performed successfully in all patients. The mean operative time was 430.4 ± 60.6 minutes, and the mean estimated operative blood loss was 135.0 ± 97.8 mL. There were no cases of conversion to open surgery during the procedure. The postoperative complication rate was 53.8%, and there was no surgical mortality. CONCLUSIONS: We recommend this novel method of total laparoscopic staplized formation of gastric tube to facilitate gastric pull-up

The Clinical COPD Questionnaire Correlated with BODE Index-A Cross-Sectional Study

The Global initiative for Chronic Obstructive Lung Disease (GOLD) staging has widely used in the stratification of the severity of COPD, while BODE (body mass index, airflow obstruction, dyspnea, and exercise capacity) index was proven superior to FEV1 in predicting mortality, exacerbation and disease severity in patients with COPD. Clinical COPD Questionnaire (CCQ), a questionnaire with ten items categorized into three domains (symptoms, functional state and mental state) was developed to measure health status of COPD patients. However, little is known about the relationship between CCQ score and BODE index. We performed a prospective study with the inclusion of 89 patients who were clinically stable after a 6-week-therapy for COPD symptoms comparing their health status assessed by CCQ, BODE index and GOLD staging. We found that the total CCQ score was correlated with BODE score (P < 0.001) and GOLD staging (P < 0.001); of three CCQ domains, the functional status correlated the most with BODE index (rS = 0.670) and GOLD staging (rS = 0.531), followed by symptoms (rS = 0.482; rS = 0.346, respectively), and mental status (rS = 0.340; rS = 0.236, respectively). Our data suggest that CCQ is a reliable and convenient alternative tool to evaluate the severity of COPD

Crystallographic origin of cycle decay of the high-voltage LiNi\u3csub\u3e0.5\u3c/sub\u3eMn\u3csub\u3e1.5\u3c/sub\u3eO\u3csub\u3e4\u3c/sub\u3e spinel lithium-ion battery electrode

High-voltage spinel LiNi0.5Mn1.5O4 (LNMO) is considered a potential high-power-density positive electrode for lithium-ion batteries, however, it suffers from capacity decay after extended charge-discharge cycling, severely hindering commercial application. Capacity fade is thought to occur through the significant volume change of the LNMO electrode occurring on cycling, and in this work we use operando neutron powder diffraction to compare the structural evolution of the LNMO electrode in an as-assembled 18650-type battery containing a Li4Ti5O12 negative electrode with that in an identical battery following 1000 cycles at high-current. We reveal that the capacity reduction in the battery post cycling is directly proportional to the reduction in the maximum change of the LNMO lattice parameter during its evolution. This is correlated to a corresponding reduction in the MnO6 octahedral distortion in the spinel structure in the cycled battery. Further, we find that the rate of lattice evolution, which reflects the rate of lithium insertion and removal, is ∼9 and ∼10% slower in the cycled than in the as-assembled battery during the Ni2+/Ni3+ and Ni3+/Ni4+ transitions, respectively

Innovative digital technology adapted in nursing education between Eastern and Western countries: a mini-review

Advanced digital technologies have overcome the limitation of on-site teaching, especially after the COVID-19 epidemic. Various newly-developed digital technologies, such as e-learning, virtual reality, serious games, and podcasts, have gained renewed interest and come into the spotlight. Podcasts are becoming increasingly popular in nursing education as they provide a convenient and cost-effective way for students to access educational content. This mini-review article provides an overview of the development of podcasts in nursing education in Eastern and Western countries. It explores potential future trends in the use of this technology. The literature review demonstrates that nursing education in Western countries has already integrated podcasts into curriculum design, using the podcast to convey nursing education knowledge and skills and to improve students’ learning outcomes. However, few articles address nursing education in Eastern countries. The benefits of integrating podcasts into nursing education appear far greater than the limitations. In the future, the application of podcasts can serve not only as a supplement to instructional methodologies but also as a tool for clinical practicing students in nursing education. In addition, with the aging population increasing in both Eastern and Western countries, podcasts have the potential to serve as an effective delivery modality for health education in the future, particularly for the older adult, whose eyesight declines with age, and those populations with visual impairments