Search

Background: Social innovation is often used as a mechanism to jump-start public–private partnerships to leverage resources to achieve social impact; the analysis of sustainability and the impact of corporate social responsibility (CSR) cannot be emphasized enough. Due to advances in the information and communication technology industry in Taiwan, this paper aims to explore whether these advancements drive CSR as a form of social innovation to meet health needs in Taiwan. Methodology: This paper uses a case study to look at CSR programs in the health sector in Taiwan. Corporations with diverse missions and different CSR approaches that are available on the internet are selected. The analysis of the case study takes a qualitative, exploratory approach to shed light on current initiatives. Results: The majority of CSR programs in Taiwan are private sector activities that emerged during the COVID-19 pandemic; current CSR activities in Taiwan are driven by awards, public relations, and external interests. Corporations in Taiwan have the potential to address the health care gaps of urban–rural health utilization among Taiwanese indigenous communities. It is recommended for corporations to (1) develop partnerships with public health experts or to (2) employ CSR personnel with health care backgrounds who can navigate the intersection between health, business, and policies to develop CSR strategies. Conclusions: Further evaluation of the projects mentioned in this paper to assess the direct and indirect impact on health outcomes could provide a more comprehensive understanding of the field of CSR in the health sector in Taiwan. [ABSTRACT FROM AUTHOR]

Energy justice remains relatively under-researched outside of the Western context, especially in Asia. This paper addresses that gap by investigating the process of energy transition in Taiwan through the socio-spatial lens and institutional points of view. The paper underscores the urgency of recognizing and addressing the overlooked social injustices across different territories, advocating an integrated planning approach that incorporates a just energy transition perspective to reduce the uneven negative impacts of deploying renewable energies across communities and regional territories. Drawing on a case study of the Changhua region, the paper identifies conflicts arising from the rapid deployment of renewable energy, such as land use changes that displace farming activities and negatively affect rural stakeholders. The findings suggest the need to urgently address the gap between top–down goals in energy transition and bottom–up considerations to raise awareness and prevent injustices that risk deepening the existing socio-economic inequities. This paper also proposes a new framework for both new research and policy for (just) energy transition, incorporating distributional, procedural, and recognitional concerns together with a critical view on the cross-scale and cross-sectoral integration as part of the spatial planning process. [ABSTRACT FROM AUTHOR]

This article explores the potential for collaboration between China and Pakistan in the healthcare field, specifically in terms of research and publications. While China has made significant progress in medical research and publications, there are concerns about unethical publication practices that regulatory bodies are addressing. The Pakistan Journal of Medical Sciences has been receiving research papers from China for the past twenty years, but the acceptance rate has remained low due to a commitment to maintaining standards and intellectual integrity. The author recently visited China to promote academic collaboration and met with faculty members from hospitals in Shanghai and Changsha. The article emphasizes the importance of following ethical guidelines and provides tips for Chinese researchers to improve their chances of acceptance. Overall, the article highlights the potential for collaboration while acknowledging the challenges and the importance of maintaining quality and ethical standards in research and publications. [Extracted from the article]

As the threat of global warming to human beings has gradually received attention, this article introduces the terror management theory to explain whether health risk awareness will affect their willingness to accept smart green buildings and that relationship is positively regulated by death anxiety. In addition, this article introduces the concept of materialismto propose that consumers will also accept smart green buildings due to the influence of materialism. This article interviewed two consumers and two professors in Taiwan, and verified the three hypotheses of this article through qualitative coding analysis. This article also used quantitative research methods to verify the theoretical model. This article not only introduces the cross-cutting contributions between terrormanagement theory, materialism and smart green buildings, but also helps the construction industry develop strategies to attract consumers. [ABSTRACT FROM AUTHOR]

This paper presents the results of an action research project investigating a Global Englishes course offered at a Taiwanese university, in the context of Taiwan’s Bilingual 2030 policy. The study aimed to address the issue of English being viewed as a foreign language in Taiwan, and native speakers being stereotypically considered as the custodians of the language and culture. To address these problems, the researcher implemented a course called Learning Englishes and Cultures Through Movies based on the Global Englishes paradigm. 14 secondyear undergraduate English majors fully participated in the course during the second semester of the 2020–2021 academic year. Qualitative data were collected from biweekly reflections provided by the students and analysed through content analysis. The findings showed that the course helped students develop more global attitudes and perceptions, and supported the effectiveness of the materials and tasks included in the course. The results offer guidance for future cycles of action research. [ABSTRACT FROM AUTHOR]

The investigation examines English proficiency levels across Taiwanese primary education, revealing a significant divergence in skills characterized by an M-shaped distribution among students in the fifth and sixth grades. To address this disparity, the study employs a performance evaluation method that combines importance–performance analysis (IPA) and the refined Kano model, aiming to identify and improve upon the current deficiencies in English language teaching. Further analytical depth is provided by applying a three-factor theory, which re-evaluates the traditional five-factor framework of the Kano model, informed by a survey of 443 respondents. The analysis identified that, out of twenty evaluative items, four are critical and demand targeted enhancement efforts. The paper has identified four items for enhancement to improve English language instruction quality. Specifically, it suggests that two items from the importance–performance analysis are critically under resourced and require immediate intervention. Additionally, the paper recognizes two items from the Kano model that also need focused improvement. The study recommends swift and targeted actions to address these areas, with the goal of raising the overall standard of teaching. Based on these findings, the study proposes a set of practical recommendations aimed at increasing the overall effectiveness of teaching and fostering an environment that enhances student motivation. The ultimate goal of this study is to support English teachers in primary schools by providing strategic insights that can lead to the enhancement of teaching practices and the amelioration of English language education deficiencies. [ABSTRACT FROM AUTHOR]

Systematic entomology as the study and ordering of insect biodiversity is a material-based practice that relies on insect bodies as a resource. Especially large amounts of insect specimens were collected and traded globally in the decades surrounding the turn of the twentieth century, often relying on colonial infrastructures. Taking colonial-era Taiwan as a case study, this paper asks under which circumstances specific places became collecting sites. It takes a series of articles on the insect fauna of the island as a point of departure, titled H. Sauter's Formosa-Ausbeute after the German naturalist who sent the specimens around the world in the early twentieth century. It explores how collecting specimens was entangled with colonial infrastructure projects, insect policies, and forest-based industries. After Taiwan became a Japanese colony in 1895, newly constructed railways, including push car lines and logging trains, gave naturalists access to inner frontiers. Conversely, insects moved into the spotlight by disrupting these same infrastructures. A rush into the mountains was brought on by the island's abundance in old growth forests, as evergreen trees such as camphor laurels became valuable export resources. The location of insect collecting sites was determined not just by ecological factors but by forest-based industries and colonial policies as well. As ancient trees were felled and aboriginal peoples violently displaced, insect collectors followed colonial infrastructures into the mountains, resulting in what a German entomologist called the "mass fabrication" of articles about Taiwan's insect fauna. [ABSTRACT FROM AUTHOR]

In this paper, an improved one-line evolution formulation is proposed and derived for the dynamic shoreline planforms of embayed beaches. Although embayed sandy beaches can perform several functions, serving as leisure spots and areas of coastal protection, shoreline advances and retreats occur continuously as a result of many natural forces, such as winds, waves, currents, tides, etc. The one-line evolution formulation for dynamic shoreline planforms based on the polar coordinate can be adopted to simulate high-planform-curvature shorelines and achieve better stability and simplicity in comparison with other description coordinates. While the polar coordinate and rectangular control volume are adopted to derive the one-line evolution formulation for dynamic shoreline planforms, the difference between the radial direction of the polar coordinate and the normal direction of the shoreline segment may result in inaccurate predictions of shoreline movements. In this study, a correction coefficient, which can adjust the influence of these two misaligned directions, is derived and included in the one-line evolution formulation, which is based on the polar coordinate. Thus, by considering the correction coefficient, an improved one-line evolution formulation for dynamic shoreline planforms of crenulate-shaped bays is proposed in this paper. Some numerical examples are provided to verify the merits of the proposed improved one-line evolution formulation. Moreover, the proposed numerical approach is applied to simulate the dynamic movements of the shoreline in Taitung—the southeastern part of Taiwan—and the effectiveness of the proposed formulation in solving realistic engineering applications is evidently verified. [ABSTRACT FROM AUTHOR]

Career building can be challenging for young surgeons, especially when topics such as lifestyle, work–life balance and subspecialization arise. Suggestions and advice from senior colleagues is very valuable but many young surgeons do not have such opportunities or are limited to a few senior surgeons. The International Microsurgery Club (IMC), in collaboration with the World Society of Reconstructive Microsurgery, organized a combined webinar for this topic and invited world renowned microsurgery masters polled by the IMC members to join, including Prof. Peter Neligan (Emeritus from University of Washington, United States), Prof. Raja Sabapathy (Ganga Hospital, India), Dr. Gregory Buncke (The Buncke Clinic, United States), Prof. Isao Koshima (Hiroshima University Hospital, Japan), Prof. David Chwei-Chin Chuang (Chang Gung Memorial Hospital, Taiwan), and Prof. Eric Santamaria (Hospital General Dr. Manuel Gea Gonzalez, Mexico) on May 1, 2022. Prof. Joon-Pio Hong (Asan Medical Center, South Korea) and Prof. Fu-Chan Wei (Chang Gung Memorial Hospital, Taiwan) were also selected but unfortunately could not make it and were therefore invited to another event in April 2023, summarized in a recently published paper. There is ample literature reporting on different aspects of developing a microsurgical career but the goal of this session was to offer an opportunity for direct exchange with experienced mentors. Moreover, insights from experienced microsurgeons from different part of the world were more likely to offer different perspectives on aspects such as career building, failure management, and team culture. This webinar event was moderated by Dr. Jung-Ju Huang (Taiwan), Dr. Susana Heredero (Spain), and Dr. Wei F. Chen (United States). [ABSTRACT FROM AUTHOR]

Societal Impact Statement: Multiple cropping, the cultivation of several crops on the same land in a year, occupied an important part of Taiwan's agricultural research from 1950 to 1970. This research originated in the context of Taiwan's land reform and diversification programs and their connections to the government's political ambition to maximize food production. The study of how multiple cropping was politicized and depoliticized by different actors helps to expand the narratives of the Green Revolution in Asia, analyze their legacies, and highlight Taiwan's role in the international exchange of visions of agricultural development during the Cold War. Summary: Scholars have recently expanded the history of the Green Revolution to move beyond the narrative of North–South technological diffusion. This article enriches the scholarship with the case of multiple cropping in Taiwan and its connection to Cold War geopolitics.Rice productivity in postwar Taiwan was boosted through a land reform launched by the Sino‐American Joint Commission on Rural Reconstruction (JCRR) in the 1950s. Backed by American aid and staffed by scientists from the Republic of China (ROC) government, the JCRR envisioned to turn tenant farmers into landowners so as to encourage labor input and adoption of seeds and fertilizers.By 1960, the JCRR presented its reform as a "bloodless social revolution" and extended its focus to multiple cropping through a diversification program. The JCRR further created the Asian Vegetable Research and Development Center (AVRDC) in 1971 to spread Taiwan's breeding and cropping techniques. The ROC's diplomatic isolation in the 1970s, however, prompted the center to reinterpret Taiwan's success in multiple cropping from a political achievement to a technological triumph, thus reinforcing the technology‐driven narrative used by the International Rice Research Institute (IRRI).Through Taiwan's influences on IRRI's rice breeding and multiple cropping research, this paper illustrates that the history of the Green Revolution requires more complex narratives. In addition, with Taiwan's political and economic transition since the 1980s, farmers began to reclaim their voice and influence agricultural policies. The case thus highlights the need of democratic participation in agricultural research, a concern that remains relevant today. [ABSTRACT FROM AUTHOR]

This paper proposes a novel censored autoregressive conditional Fréchet (CAcF) model with a flexible evolution scheme for the time-varying parameters, which allows deciphering tail risk dynamics constrained by price limits from the viewpoints of different risk preferences. The proposed model can well accommodate many important empirical characteristics of financial data, such as heavy-tailedness, volatility clustering, extreme event clustering, and price limits. We then investigate tail risk dynamics via the CAcF model in the price-limited stock markets, taking entropic value at risk (EVaR) as a risk measurement. Our findings suggest that tail risk will be seriously underestimated in price-limited stock markets when the censored property of limit prices is ignored. Additionally, the evidence from the Chinese Taiwan stock market shows that widening price limits would lead to a decrease in the incidence of extreme events (hitting limit-down) but a significant increase in tail risk. Moreover, we find that investors with different risk preferences may make opposing decisions about an extreme event. In summary, the empirical results reveal the effectiveness of our model in interpreting and predicting time-varying tail behaviors in price-limited stock markets, providing a new tool for financial risk management. [ABSTRACT FROM AUTHOR]

For the advancement of smart grids, solar power generation predictions have become an important research topic. In the case of using traditional modeling methods, excessive computational costs may be incurred and it is difficult for these methods to learn the multi-variable dependencies of the data. Therefore, in this paper, a deep learning model was used to combine convolutional neural networks and long short-term memory recurrent network predictions. This method enables hourly power generation one day into the future. Convolutional neural networks are used to extract the features of multiple time series, while long short-term memory neural networks predict multivariate outcomes simultaneously. In order to obtain more accurate prediction results, we performed feature selection on meteorological features and combined the selected weather features to train the prediction model. We further distinguished sunny- and rainy-day models according to the predicted daily rainfall conditions. In the experiment, it was shown that the method of combining meteorological features further reduced the error. Finally, taking into account the differences in climate conditions between the northern and southern regions of Taiwan, the experimental results of case studies involving multiple regions were evaluated to verify the proposed method. The results showed that training combined with selected meteorological features can be widely used in regions with different climates in Taiwan. [ABSTRACT FROM AUTHOR]

Background: Sciaenidae is one of the most important coastal fisheries in Taiwan, both in production and economic value. It is also significant as the main targetted diet of Chinese white dolphins, Sousa chinensis, especially for the genus Johnius, such as J. taiwanensis, J. belangerii and J. distinctus, which is primarily found in central-western Taiwan coastal waters. Despite an abundance of Johnius species occurrences reported in the Global Biodiversity Information Facility (GBIF) and the Taiwan Biodiversity Information Facility (TaiBIF) data portals (Mozambique, Australia, Taiwan, Korea, India, Indonesia, South Africa, Pakistan, Vietnam and China), there are no specific datasets that properly document the regional distribution of this genus, especially in Taiwanese waters. Thus, this paper describes a dataset of genus Johnius occurrences in waters on the central-western coast of Taiwan. The data collection for the present study was conducted from 2009 until 2020 and comprised 62 sampling events and 133 occurrence records. All fish specimens were collected by trawling in Miaoli, Changhwa and Yunlin Counties, Taiwan and brought back to the lab for identification, individual number count and body weight measurement. These processing data have been integrated and established in the Taiwan Fish Database and published in GBIF. This dataset contains six Johnius species and 2,566 specimens, making it comprehensive Johnius fish fauna and spatial distributional data on the coastal habitat in central-western Taiwanese waters. New information: This dataset contains 133 occurrence records of Johnius species (Sciaenidae) with 2,566 specimens, making it the most extensive public dataset of Johnius distribution records in Taiwan. The publication of this dataset through the TaiBIF and GBIF dataset platforms demonstrated that the number of Johnius spatial and temporal records in Taiwan waters is influenced by the topographical structure of the Changyun Rise (CYR) in combination with the cold current of the China Coastal currents and bound with the warm currents of the Kuroshio and the South China Sea on the central-western coast of Taiwan. The data serve as the foundation for understanding the biogeography and Johnius species ecology in Taiwan's coastal waters, which present a 2°C water temperature difference split at the CYR. [ABSTRACT FROM AUTHOR]

The ship tracking and mapping capabilities that geospatial technology provides create an opportunity to observe fishing vessels as they move through established maritime boundaries. This paper connects data availability to ground-truthing research and explores the limits of vessel movement mapping in representing worker abuse at sea through three related themes. First, a conceptual background links the advancements in maritime remote sensing to critical GIS scholarship and provides a background on worker abuse aboard Taiwanese fishing vessels. Second, the paper examines the potential of machine learning algorithms to represent worker abuse at sea, arguing that more extensive ground-truthing research with workers could help address variations in the data and limited data sets. Third, I use remote sensing data to identify and unpack Taiwanese fishing across the three EEZs with the most concentrated Taiwanese fishing activity: starting with Taiwan, followed by the Falkland Islands, and Seychelles. I argue that fishing activity and the digital representation of vessel movements are governed by terrestrial geopolitics and subject to manipulation by ship captains. Finally, the conclusion offers recommendations for how future research can capitalize on the capabilities of AIS, particularly with respect to addressing problems of working conditions and abuse at sea. [ABSTRACT FROM AUTHOR]

Bridges may undergo structural vibration responses when exposed to seismic waves. An analysis of structural vibration characteristics is essential for evaluating the safety and stability of a bridge. In this paper, a signal time-frequency feature extraction method (NTFT-ESVD) integrating standard time-frequency transformation, singular value decomposition, and information entropy is proposed to analyze the vibration characteristics of structures under seismic excitation. First, the experiment simulates the response signal of the structure when exposed to seismic waves. The results of the time-frequency analysis indicate a maximum relative error of only 1% in frequency detection, and the maximum relative errors in amplitude and time parameters are 5.9% and 6%, respectively. These simulation results demonstrate the reliability of the NTFT-ESVD method in extracting the time-frequency characteristics of the signal and its suitability for analyzing the seismic response of the structure. Then, a real seismic wave event of the Su-Tong Yangtze River Bridge during the Hengchun earthquake in Taiwan (2006) is analyzed. The results show that the seismic waves only have a short-term impact on the bridge, with the maximum amplitude of the vibration response no greater than 1 cm, and the maximum vibration frequency no greater than 0.2 Hz in the three-dimensional direction, indicating that the earthquake in Hengchun will not have any serious impact on the stability and security of the Su-Tong Yangtze River Bridge. Additionally, the reliability of determining the arrival time of seismic waves by extracting the time-frequency information from structural vibration response signals is validated by comparing it with results from seismic stations (SSE/WHN/QZN) at similar epicenter distances published by the USGS. The results of the case study show that the combination of dynamic GNSS monitoring technology and time-frequency analysis can be used to analyze the impact of seismic waves on the bridge, which is of great help to the manager in assessing structural seismic damage. [ABSTRACT FROM AUTHOR]

This paper discusses spatio-temporal metaphors in three regions in and around China from the perspective of language contact, looking for evidence of areal convergence or transfer of the conceptual metaphors. The approach fits broadly within the framework of Cognitive Contact Linguistics. After a review of spatio-temporal metaphors in the Sinitic languages, I sketch out the relevant metaphors in languages spoken in northwest China (Xinjiang and the Qinghai-Gansu Sprachbund), in and near northeast China, and in south China and Taiwan – many of which have not been discussed previously in the literature on conceptual metaphor. The study reveals evidence for metaphor transfer involving the up-down spatial dimension from Sinitic to Japanese and Korean, contact-facilitated extension of metaphor involving the front-back dimension in Tsou, and possible transfer of front-back metaphor to other languages of Taiwan. Several of the lexical items used in front-back metaphorical expressions in Santa, two Hmong varieties, Japanese, and Korean are borrowed from Sinitic, but these do not clearly represent transfer of the conceptual mapping. [ABSTRACT FROM AUTHOR]

Guided by entering the deep sea and achieving deep marine development in marine construction, the factors hindering marine construction cannot be ignored. Strong ocean winds have a devastating impact on tasks such as ship navigation, carrier aircraft take-off and landing, naval operations and military exercises, and affect the planning of sea routes and the development of the long-distance sea. This paper uses ERA5 wind field data and key climate indices to conduct a systematic analysis of catastrophic winds in the global ocean using methods such as climate statistical analysis, the Theil–Sen trend method, Pearson correlation and contribution rate calculation. It points out the spatiotemporal distribution, variation trend, climate index correlation and contribution rate characteristics of strong winds occurrence (SWO) and hopes that the results of this study can serve as a guide for maritime route planning and provide technical assistance and decision-making support for marine development and other needs. The results show the following: The high global SWO occurs in the Southern Ocean, the North Atlantic, the North Pacific, near Taiwan, China, the Arabian Sea and other locations, with the strongest SWO in summer. The growth trend of SWO in the Southern Ocean is strongest, with decreasing regions near the Arabian Sea and the Bay of Bengal, and the growth trend is reflected in all four seasons. The climate indices with the strongest correlation and highest contribution to the global SWO are AAO (Antarctic Oscillation) and EP–NP (East Pacific–North Pacific pattern) with a correlation between −0.5 and 0.5 and a contribution rate of up to −50%~50%. [ABSTRACT FROM AUTHOR]

This paper presents the verification results of an experimental site that employed a particle tracking algorithm to assess the transport of tracers through the composite formation of gravel and Cholan in northwest Taiwan. A suitable hydrogeological conceptual model that describes the flow characteristics of the gravel formation and Cholan formation is essential to evaluate groundwater flow and management at this site. Continuous porous medium (CPM) can be easily applied in the gravel formation, while the Cholan formation, characterized by argillaceous sandstone, is commonly treated as a porous medium. However, this study obtains its fracture distribution through geological surveys, and the key fracture parameters are also collected, analyzed, and incorporated into the model. Four hydrogeological conceptual models, including CPM, discrete fracture network (DFN), equivalent continuous porous medium (ECPM), and hybrid DFN/ECPM, are generated for this complex formation. This study combines the conceptual models of the gravel and Cholan formation into four cases to describe the characteristics of the composite formation. The groundwater flow field of four cases is simulated, and the particle tracking method is employed to model the tracer transport. Simulation results from the four hybrid models all yielded a breakthrough curve (BTC) for the first 15 h, indicating that the tracer arrived at the designated outlet within this timeframe and primarily flowed through the gravel formation, while long-time particle tracking revealed a possible flow path through the Cholan formation after 15 h. The breakthrough curve of the four cases shows that the ECPM model is more suitable for representing the heterogeneity of the Cholan formation than the common CPM model. This study provides a suitable numerical algorithm of the conceptual model of the Cholan formation based on strong evidence by considering different models and comparing them with in situ tracer tests. [ABSTRACT FROM AUTHOR]

In recent years, influencer marketing has taken over traditional brand advertisements on social media platforms, combining word-of-mouth marketing with celebrity endorsements. However, there has been limited academic research on the key success factors in influencer marketing. This paper used a hybrid MCDM model that integrates the Delphi method and the decision-making trial and evaluation laboratory (DEMATEL) approach. Through a two-stage empirical study, the research aims to explore the crucial success factors in influencer marketing. This study focuses on the Taiwanese market. The target respondents for the survey are consumers in Taiwan who have purchased products or services based on recommendations from key opinion leaders (KOLs) or internet celebrities. This systematic research framework not only pinpoints key factors that capture consumer attention towards influencers, but it also illustrates the inter-relationship of structure and improvement directions among these factors. According to results, the key factors include influencer reputation, credibility, degree of key opinion influence, attractiveness, popularity, consistency between influencers and brands, fan engagement level, and informativeness. Finally, businesses can consider five aspects to be the purpose of collaboration, product type, target audience for the product, characteristics of the influencer's creative content, and media attributes. By comprehensively considering these aspects, businesses can determine the appropriate format for collaborative content. This decision can then guide how influencers communicate with consumers, effectively conveying brand information to the relevant target audience. The research findings provide fresh and significant insights in the field of influencer marketing studies. [ABSTRACT FROM AUTHOR]

To achieve successful prevention of fire incidents originating from human activities, it is imperative to possess a thorough understanding. This paper introduces a machine learning approach, specifically utilizing deep neural networks (DNN), to develop predictive models for fire occurrence in Keelung City, Taiwan. It investigates ten factors across demographic, architectural, and economic domains through spatial analysis and thematic maps generated from geographic information system data. These factors are then integrated as inputs for the DNN model. Through 50 iterations, performance indices including the coefficient of determination (R2), root mean square error (RMSE), variance accounted for (VAF), prediction interval (PI), mean absolute error (MAE), weighted index (WI), weighted mean absolute percentage error (WMAPE), Nash–Sutcliffe efficiency (NS), and the ratio of performance to deviation (RPD) are computed, with average values of 0.89, 7.30 × 10−2, 89.21, 1.63, 4.90 × 10−2, 0.97, 2.92 × 10−1, 0.88, and 4.84, respectively. The model's predictions, compared with historical data, demonstrate its efficacy. Additionally, this study explores the impact of various urban renewal strategies using the DNN model, highlighting the significant influence of economic factors on fire incidence. This underscores the importance of economic factors in mitigating fire incidents and emphasizes their consideration in urban renewal planning. [ABSTRACT FROM AUTHOR]

The present study aims to identify the most productive countries, journals, authors, institutions and the most used keywords in the field of special education during 2011-2020, based on the WoS database. The widespread effects of the papers and how they are related were analyzed with the bibliometric analysis method. The findings of the study showed that the USA is inarguably the most productive country, followed by England and Australia. On the other hand, there was a very strong positive correlation (r = 0.929) between the number of papers published by countries and their h-index, a similar finding was also found to be present between the countries' h-index and GDP per capita (r = 0.790). Moreover, it was found that the journals with the highest quartile (Q1 and Q2) in the field of special education published significantly more papers than the journals with the lowest quartile (Q3 and Q4). Matson, JL (USA), Sigafoos, J (New Zealand) and Lancioni, GE (Italy) were determined as the most prolific authors, respectively. Autism, intellectual disability, and Down syndrome were the phrases most frequently used as keywords. Our findings provide key information regarding the developments that the research direction of special education field has recently taken. This study also serves a potential roadmap for future studies.

This paper presents an original wireless DYU Air Box of an environment-monitoring IoT (EMIoT) system on a campus to offer information on environmental conditions through the public ThingSpeak IoT platform for stakeholders including all the students and employees on the Da-Yeh University (DYU) campus in Taiwan. Firstly, the proposed wireless heterogeneous multi-sensor module aggregates BME680, SCD30, PMS7003, and BH1750 sensors with a TTGO ESP32 Wi-Fi device based on the I2C and UART interface standards of series communication. Through the DYU-802.1X Wi-Fi network with the WPA2 Enterprise security directly, the wireless multi-sensor monitoring module further forwards the observation data of environmental conditions on campus via the DYU-802.1X Wi-Fi network to the public ThingSpeak IoT platform, which is a cloud service platform to aggregate, visualize, and analyze live sensing data of air quality index (AQI), concentrations of PM1.0/2.5 and CO2, brightness, ambient temperature, and relative humidity (RH). The results illustrate the proposed DYU Air Box for monitoring the indoor environmental conditions on campus and validate them with sufficient accuracy and confidence with commercialized measurement instruments. In this work, the wireless smart environment-monitoring IoT system features monitoring and automatic alarm functions for monitoring AQI, CO2, and PM concentrations, as well as ambient illumination, temperature, and RH parameters and collaboration and interoperability through the Enterprise Intranet. All the organizational stakeholders interested in the environmental conditions of the DYU campus can openly access the information according to their interests. In the upcoming future, the information of the environmental conditions in the DYU campus will be developed to be simultaneously accessed by all the stakeholders through both the public ThingSpeak IoT platform and the private EMIoT system. [ABSTRACT FROM AUTHOR]

Over the last 50 years since Whittingham created the world's first lithium-ion battery (LIB) in 1970, LIBs have continued to develop and have become mainstream for electric vehicle (EV) batteries. However, when an LIB for an EV reaches 80% of its state of health (SOH), although it still retains about 80% of its capacity, it is no longer suitable for use in general EVs and must be retired. This is problematic because not only is a retired LIB still viable for use and not totally obsolete, if not properly disposed of, a retired LIB may cause environmental pollution on top of being a waste of resources. Therefore, the reuse of retired LIBs from EVs is increasingly important. This paper uses circular economy (CE) and extended producer responsibility (EPR) as a theoretical basis to deal with the disposal of retired LIBs from EVs in Taiwan from legal, technical, and economic perspectives, and hopes to provide suggestions for the reuse of retired LIBs from EVs in Taiwan. [ABSTRACT FROM AUTHOR]

Under net-zero objectives, the development of electric vehicle (EV) charging infrastructure on a densely populated island can be achieved by repurposing existing facilities, such as rooftops of wholesale stores and parking areas, into charging stations to accelerate transport electrification. For facility owners, this transformation could enable the showcasing of carbon reduction efforts through the self-use of renewable energy while simultaneously gaining charging revenue. In this paper, we propose a dynamic energy management system (EMS) for a solar-and-energy storage-integrated charging station, taking into consideration EV charging demand, solar power generation, status of energy storage system (ESS), contract capacity, and the electricity price of EV charging in real-time to optimize economic efficiency, based on a real-world situation in Taiwan. This study confirms the benefits of ESS in contracted capacity management, peak shaving, valley filling, and price arbitrage. The result shows that the incorporation of dynamic EMS with solar-and-energy storage-integrated charging stations effectively reduces electricity costs and the required electricity contract capacity. Moreover, it leads to an augmentation in the overall operational profitability of the charging station. This increase contains not only the revenue generated from electricity sales at the charging station but also the additional income from surplus solar energy sales. From a comprehensive cost–benefit perspective, introducing this solar-and-energy storage-integrated EMS can increase facility owners' net income by 1.25 times compared to merely installing charging infrastructure. [ABSTRACT FROM AUTHOR]

This paper investigates a wind speed oscillation event that occurred near the coastline of central Taiwan in the afternoon of 17 February 2018, using data from observations and numerical simulations. The observed wind speeds at 100-m altitude displayed a fast-oscillating pattern of about 6 cycles between strong winds of approximately 21 m s−1 and weak winds of around 2 m s−1, with periods of about 10 min. The pressure anomalies fluctuated in antiphase with the wind speed anomalies. The synoptic analysis revealed the influence of a continental high pressure system, resulting in a cold-air outbreak over Taiwan. The cold north-northeasterly winds split into two branches upon encountering Taiwan's topography, with ridging off the east coast and a lee trough off the west coast of Taiwan. Wind oscillations were detected in the low-level cold air offshore the west coast of Taiwan, depicted by wavelike structures in wind speeds, sea level pressure, and potential temperature. The perturbations were identified as Kelvin-Helmholtz billows characterized by regions of strong wind speeds, warm and dry air, sinking motions, and low pressure collocated with each other, while regions of weaker wind speeds, cooler and moister air, ascending motions, and high pressure were associated with each other. With terrain contributing to favorable conditions, the large vertical and horizontal wind shears resulted from the southward acceleration of low-level cold air and the northward movement of the lee trough played an important role in initiating the wind oscillations. [ABSTRACT FROM AUTHOR]

This paper proposes a probabilistic hazard assessment model for debris flows considering the uncertainties of multiple influencing factors based on copula approaches. Fifty-nine rainfall-induced debris flows occurred between 2001 and 2009 in Taiwan are taken as an illustrative example to validate the proposed approaches. A copula-based probabilistic model is developed to model the joint probability distribution of debris-flow volume V and its influencing factors (e.g., rainfall intensity, RI and landslide area, AL). The developed model is then used to make probabilistic prediction of debris-flow volume for a specific hazard level, and compared with the empirical approaches. The proposed probabilistic model is also used to develop the exceedance probability charts of quantities for a specific debris-flow basin. Results show that the developed V–RI–AL probabilistic model can provide reasonable estimates of debris-flow volume in Taiwan for a specific probability level of 0.94, and show better predictive performance than the empirical relationships by using an independent debris-flow dataset in Taiwan for validation. The developed multivariate joint probabilistic model can also provide the exceedance probability of debris flows through considering the uncertainties of debris flow and its influencing factors, providing a preliminary reference for hazard assessment of the debris flows. [ABSTRACT FROM AUTHOR]

Climate change has exacerbated severe rainfall events, leading to rapid and unpredictable fluctuations in river water levels. This environment necessitates the development of real-time, automated systems for water level detection. Due to degradation, traditional methods relying on physical river gauges are becoming progressively unreliable. This paper presents an innovative methodology that leverages ResNet-50, a Convolutional Neural Network (CNN) model, to identify distinct water level features in Closed-Circuit Television (CCTV) river imagery of the Chengmei Bridge on the Keelung River in Neihu District, Taiwan, under various weather conditions. This methodology creates a virtual water gauge system for the precise and timely detection of water levels, thereby eliminating the need for dependable physical gauges. Our study utilized image data from 1 March 2022 to 28 February 2023. This river, crucial to the ecosystems and economies of numerous cities, could instigate a range of consequences due to rapid increases in water levels. The proposed system integrates grid-based methods with infrastructure like CCTV cameras and Raspberry Pi devices for data processing. This integration facilitates real-time water level monitoring, even without physical gauges, thus reducing deployment costs. Preliminary results indicate an accuracy range of 83.6% to 96%, with clear days providing the highest accuracy and heavy rainfall the lowest. Future work will refine the model to boost accuracy during rainy conditions. This research introduces a promising real-time river water level monitoring solution, significantly contributing to flood control and disaster management strategies. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to compare the differential impact of Taiwan High-speed Railway (T-HSR) and Hainan East Ring High-speed Railway (HER-HSR) stations on the surrounding construction land expansion, reveal the underlying institutional reasons, and then provide policy recommendations for coordinating the rational development of land resources and ecological environment protection around high-speed railway (HSR) stations. The research methods include the Institutional Analysis and Development (IAD) framework, buffer analysis, and GIS spatial analysis. The results show that (1) The spillover impact of HSR stations on the surrounding construction land expansion is the result of the game between different actors around the development and protection of land around HSR stations under the action scenarios of various external factors. The surrounding construction land of 12 stations of T-HSR increased by 269.98 km2 within the study scope and period, while the surrounding area of 10 stations in HER-HSR increased by 187.61 km2. (2) There are nine stations in T-HSR that affect the expansion of surrounding construction land within 1.0–3.0 km and lead to the expansion of construction land of 22.44 km2, while there are six stations in HER-HSR that affect the expansion of construction land within 1.5–3.5 km and lead to the expansion of construction land of 24.20 km2. Other stations cannot effectively identify their areas of influence due to other reasons. (3) Each station of HER-HSR has a stronger influence intensity and degree on the expansion of surrounding construction land than that of T-HSR, which is closely related to institutional factors such as land planning, land property rights, and public participation. In conclusion, the differences in land planning, land property rights, public participation, and other basic systems will lead to differences in the expansion of surrounding construction land for HSR stations. This research aims to provide institutional adjustment suggestions to achieve coordinated economic development and ecological protection around HSR stations in two Chinese islands with different institutional environments. [ABSTRACT FROM AUTHOR]

Many countries of the world have implemented subsidy programs to maintain a minimum amount of farm production especially for rice. Agricultural support programs usually cause significant fiscal burdens on government budgets. These programs can be generally categorized into decoupled and coupled programs, and one longstanding research interest of previous literature is whether these programs are decoupled or coupled with farm production practices. In Taiwan, a unique land direct payment (LDP) program to rice farms was implemented to ease severe financial burden of the price support program with government purchase. In contrast to production control programs imposing quantity restrictions on farm production, this program is voluntary for rice farms, and participants are paid at a fixed rate per hectare of farmland. This paper examines the impacts of this program on farm income and farm production practices in Taiwan. The causal effect of the program is identified based on the exogenous rollout of the policy across multiple times and areas. We construct a dataset linking nationally representative rice farm surveys over several years and administrative records on program recipients to estimate the local average treatment effect of the program. We find that the effect is 4% of farm income. In addition, program participants rely less on price support programs and produce less rice and use less fertilizer, pesticide, and machinery. Although the LDP reduces rice production, we find that it causes overall government spending on the price support and direct payment programs to increase by 8.7% after the LDP. [ABSTRACT FROM AUTHOR]

• Significant ionospheric disturbances during the 2021 Typhoon Chanthu were observed by GPS and GLONASS. • The ionospheric disturbances following the Typhoon are accompanied and propagated with the "N"-type wave. • The propagation velocity and center frequency of ionospheric disturbances are within the range of gravity waves. Severe typhoons often result in substantial economic and human losses. Therefore, near-real-time monitoring and forecasting of severe typhoons have a significant importance. In this paper, characteristics of ionospheric disturbances during the 2021 Typhoon Chanthu are estimated and investigated from GPS and GLONASS measurements. We calculate high-precision de-trended and filtered ionospheric vertical total electron content (VTEC) data based on GPS and GLONASS data from intensive Global Navigation Satellite System (GNSS) observations at 30-second intervals in Taiwan. Based on the VTEC values, we analyze the characteristics of ionospheric disturbances caused by Typhoon Chanthu, such as the time of appearance of ionospheric disturbances, changes in the magnitude of these disturbances, alterations in two-dimensional disturbances, fluctuations in the speed of disturbance propagation, and shifts in the frequency spectrum. The results reveal that both GPS-TEC and GLONASS-TEC exhibit noticeable disturbances during the specified timeframe. These disturbances are accompanied by the occurrence of "N"-type anomalies in TEC. Notably, at the occurrence of the disturbance, the elevation angle of GPS PRN32 and GLONASS PRN1 satellites is approximately 50°-55°, and their respective distances from the typhoon eye are roughly 350 km and 150 km. The propagation velocity and center frequency of the ionospheric disturbances are located in the range of gravity waves. Specifically, the disturbances propagation speeds of GPS PRN32 and GLONASS PRN1 are approximately 129.36 m/s and 128.33 m/s, respectively, while the center frequencies are about 1.17 mHz and 1.43 mHz. The ionospheric perturbations observed by GPS and GLONASS exhibit certain similarities, which provide valuable insights into the relationship between typhoons and ionospheric disturbances. [ABSTRACT FROM AUTHOR]

This paper examines the effect of the 2008 financial crisis on Taiwan's fertility by exploiting a natural experiment in which public‐sector workers are unaffected due to job security. The financial crisis reduces the number of children by increasing the first‐birth interval, which leads to a lower probability of first birth. Women aged 33–38 experienced the largest decline in the probability of first birth, increasing the risks of permanent childlessness. Low‐income households and those with less‐educated spouses have a greater increase in the first‐birth interval. The number of children and the probability of first birth remain significantly lower 9 years after 2008. [ABSTRACT FROM AUTHOR]

Neuroctenus taiwanicus Kormilev, 1955 is a flat-bodied and enigmatic bug that was first discovered on the island of Taiwan, China. In this study, the whole mitochondrial genome of N. taiwanicus was sequenced and annotated for the first time, and its genomic data were uploaded to Genbank feedback number OR675057. The mitochondrial genome of N. taiwanicus is 15,340 bp in length, a typical circular DNA encoding 37 genes and a control region with 68.4% AþT content. The phylogeny reveals the taxonomic status of N. taiwanicus, which is most closely related to N. yunnanensis, and demonstrates the sister relationship among Neuroctenus, Mezira, and Brachyrhynchus. In addition, the results also confirm that Aradinae and Calisiinae are the earliest branching and more primitive in the family Aradidae, which is consistent with the analysis of the traditional classification. [ABSTRACT FROM AUTHOR]

Nowadays, national governments and international organizations are increasingly interested in the sustainable development of the cultural and creative industries through the integration of culture, art, science, and education and their influence on local economic and cultural development and promotion. However, to the best of our knowledge, only few studies have proposed a comprehensive framework based on the multi-criteria decision-making concept for evaluating the sustainable development of such industries. The main purpose of this paper is to determine which criteria are important for sustainable development, how these criteria interact, and how the sustainability performance of the evaluated subjects can be measured. Four sustainability perspectives are incorporated into the framework, economic, social, environmental, and governmental institutional, and 17 evaluation criteria. In the methodology, the neutrosophic decision-making trial and evaluation laboratory (N-DEMATEL) method is first used to identify the influential relationships between the sustainability criteria. Then, a modified technique for order priority by similarity to ideal solution (TOPSIS) method is used to calculate the performance of the sustainable cultural and creative industries. Neutrosophic fuzzy logic is applied to reflect the ambiguity of the expert evaluations, with the three parameters of truth, falsity, and indeterminacy incorporated to obtain more potential uncertainty information for neutrosophic decision support. The validity and practicality of the proposed model are demonstrated through a real-world example for the National Museum of Natural Science located in Central Taiwan. The results show that local government involvement, policy promotion and marketing, and the promotion of concept of sustainability are the most influential criteria for sustainability in the cultural and creative industries. The research findings can be used to guide the long-term development of the cultural and creative industries for industry and government and the method can be adapted for other performance evaluation issues. Government agencies can use the model to encourage the development of the cultural and creative industries through financial support, promotion, and partnerships with other agencies using its resources and allocation capabilities. [ABSTRACT FROM AUTHOR]

This paper examines how businesses in Taiwan's servicescapes are adapting to the growing trend of mobile payments and innovation ecosystems. Through the analysis of four case studies, we uncover the strategies these firms employ to address the challenges posed by changing consumer payment habits. Our research reveals that these companies are establishing efficient mechanisms within their ecosystems, supported by well-structured organizational frameworks. By leveraging innovation ecosystems, they are reshaping financial services and promoting collaborative growth among participants through technology, platforms, resource sharing, and knowledge exchange. This collaborative approach is driving significant changes in the sector, helping these businesses navigate through various challenges while fostering innovation and growth. Additionally, the scarcity of comprehensive observations of the digital payment ecosystem highlights the necessity for further exploration of actor interactions, regulatory mechanisms, and ecosystem management strategies. Such research efforts are crucial for enhancing our understanding of the evolving landscape of digital payments and innovation ecosystems, facilitating informed decision-making and promoting sustainable development in this dynamic industry. [ABSTRACT FROM AUTHOR]

In this paper, we build neural-network model-based automatic speech recognition (ASR) systems incrementally for performance improvement. First, we add an adversarial text discriminator module to train the speech recognition model to correct typos in recognition results. Experiments show that the character error rate (CER) and word error rate (WER) of the ASR system achieved 12.3% and 31.4%. Second, we insert a pre-trained speech synthesis (text-to-speech, TTS) module to the ASR model. When we exploit a pre-trained TTS in ASR training, the CER and WER are reduced from 12.6% and 31.7% to 10.8% and 24.4%, demonstrating that pre-trained TTS can improve ASR. Finally, we include both pre-trained TTS and text discriminator in ASR training. The performance of this ASR system is further improved, achieving the CER and WER of 9.9% and 22.7% respectively. On Formosa Speech Recognition Challenge task using Taibun Hàn-jī transcription, the proposed method also achieves better CER than a system based on hybrid DNN-HMM chain model. [ABSTRACT FROM AUTHOR]

In recent years, the escalating electricity demand in Taiwan has heightened the prominence and discourse surrounding the issue of power supply. With the enactment of the European climate law, global commitment to achieving net-zero emissions has gained momentum. Concurrently, the Taiwanese government has articulated the Taiwan 2050 net-zero emissions policy. To realize this objective, Taiwan has vigorously promoted renewable energy in recent years, increasing the proportion of renewable energy in its energy mix. However, confronted with the intermittent and unpredictable nature of renewable energy generation, challenges arise concerning the stability and quality of power supply. In response to the impact of integrating renewable energy into the grid, the Taiwan Power Company (Taipower) has introduced the day-ahead ancillary service market. Through this platform, power generation and battery energy storage systems (BESSs) engage in competitive bidding, fostering the integration of diverse distributed energy resources into the system. These resources serve as dispatchable assets for Taipower, contributing to grid stability by providing ancillary services. This study has developed an advanced dynamic regulation reserve controller by employing an industrial PC (IPC) in conjunction with a multifunctional power meter. Through real-time measurement of the power grid frequency by the multifunctional power meter, a sophisticated dynamic frequency reserve control strategy has been devised, taking into account the charging state of energy storage systems. This strategy exhibits high operational quality, effectively regulating the charging and discharging of energy storage systems. In addition to swiftly adjusting the current grid frequency, it encompasses the capability to facilitate the transfer of peak electrical energy. This effectively stabilizes the power grid, alleviating supply pressures during nighttime peaks and enhancing the overall supply stability of the power system. [ABSTRACT FROM AUTHOR]

Copyright of Taiwan Economic Forecast & Policy is the property of Institute of Economics, Academia Sinica, Taiwan Economic Forecast & Policy and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Kawasaki disease (KD) is an inflammatory vasculitis disorder of unknown etiology. It is a rare but fatal disease and the leading cause of acquired coronary heart disease in children under the age of 5 years. We examined the association of KD with the demographics of family members, parents' characteristics, and perinatal factors in Taiwanese children. This nested case–control study used data from Taiwan's Health and Welfare Data Science Center and initially included children born in Taiwan between January 1, 2006, and December 31, 2015 (n = 1,939,449); the children were observed for KD development before the age of 5 years (n = 7870). The control group consisted of children without KD who were matched with each KD case by sex and birth date at a ratio of 8:1. The odds ratio (ORs) of the aforementioned associations were estimated using conditional logistic regression. The risk of KD decreased in children with younger parents [<25 years; younger maternal age, OR = 0.72, 95% confidence interval (CI), 0.66–0.79; younger paternal age, OR = 0.68, 95% CI, 0.59–0.78], lower socioeconomic status, more than 2 siblings (OR = 0.80, 95% CI, 0.73–0.89), and siblings with a history of KD (OR = 4.39, 95% CI, 3.29–5.86). Children living in suburban (OR = 0.95, 95% CI, 0.90–1.00) and rural (OR = 0.81, 95%CI, 0.74–0.90) areas exhibited a lower risk of KD than children living in urban areas. In conclusion, a higher incidence rate of KD was observed in children aged <5 years who had an urban lifestyle, had siblings with KD, were born to older mothers, and belonged to high-income and smaller families. Parental allergic or autoimmune diseases were not associated with the risk of KD. [ABSTRACT FROM AUTHOR]

Dengue is one of the world's most rapidly spreading mosquito-borne viral diseases. As it is found mostly in urban and semi-urban areas, urbanization and associated human activities that affect the environment and larval habitats could become risk factors (e.g., lane width, conditions of street ditches) for the spread of dengue. However, there are currently no systematic studies of micro-scale urbanization-based risk factors for the spread of dengue epidemics. We describe the study area, two micro-scale environmental risk factors associated with urbanization, and meteorological data. Since the observations involve spatial and temporal correlations, we also use some statistical methods for the analysis of spatial and spatial-temporal data for the relationship between urbanization and dengue. In this study, we analyzed data from Kaohsiung, a densely populated city in southern Taiwan, and found a positive correlation between environmental risk factors associated with urbanization (ditches positive for mosquito larvae and closely packed streets termed "dengue lanes") and clustering effects in dengue cases. The statistical analysis also revealed that the occurrence of positive ditches was significantly associated with that of dengue lanes in the study area. The relationship between climate variables and positive ditches was also analyzed in this paper, indicating a relationship between dengue and both rainfall and temperature, with temperature having a greater effect. Overall, this work is immediately relevant and applicable for policymakers in government, who will need to reduce these favorable habitats for vector-born disease spreaders and implement regulations for new urban constructions to thus reduce dengue spread in future outbreaks. [ABSTRACT FROM AUTHOR]

The neglect of perception ability to the surrounding traffic conditions has always been the major cause of traffic accidents and the inattention to blind spots is the most important factor during driving. Existing solutions are facing the problems of using expensive equipment, wrong classification of the target object type, not suitable for nighttime, and incorrectly determining if the target object is in the blind zones. This paper aims to improve driving perception ability by developing an all-day object detection and recognition system with more accurate performance for blind zones. The proposed method uses a general-purpose camera as a single input and a two-stage deep network architecture for object detection and recognition. The proposed system is based on a two-stage cascaded network structure. At first, the style conversion process is performed to convert the daytime and nighttime images with different brightness into consistent brightness. Then the objects in the visual blind zones are detected and identified. Therefore, the accuracy of object detection can be significantly improved. Due to the diversity and complexity of Taiwan's road conditions, the public databases cannot effectively fulfill local application model training needs. Therefore, we have built training data set from available night images. Experimental results show that the proposed method has demonstrated promising performance in all-day object detection and recognition for blind zones. [ABSTRACT FROM AUTHOR]

This study employs information economics and the financial intermediary theory to explore the influences of private information in virtual communities and financial technology (fintech) derived from virtual currency on financial stocks. The paper conducts robust analyses on 67,166 data observations of the stock markets in China and Taiwan and finds that virtual currency development causes a structural change in the financial industry. The financial stocks in Taiwan are obviously driven by virtual factors, whereas those in China are subject to both pull from substantial factors and push from virtual factors. The research findings also suggest that the non-fundamental herding behavior driven by private information interferes with the value of financial stocks. However, financial innovations boost the competitiveness of the financial industry. It is advised to establish a policy to closely monitor the diffusion of private information and the exchange rate volatility between cryptocurrencies and home currencies to facilitate proactive financial risk management. [ABSTRACT FROM AUTHOR]

Construct-based models have become a mainstay of management and information systems research. However, these models are likely overfit to the data samples upon which they are estimated, making them risky to use in explanatory, prescriptive, or predictive ways outside a given sample. Empirical researchers currently lack tools to analyze why and how their models may not generalize out of sample. We propose a composite overfit analysis (COA) framework that applies predictive tools to describe the sources and ramifications of overfit in terms of the focal concepts important to empirical researchers: cases, constructs, and causal paths. The COA framework begins by using a leave-one-out crossvalidation procedure to identify cases with unusually high predictive error given their in-sample fit—a difference we describe as predictive deviance. The framework then employs a novel deviance tree method to group deviant cases that have similar predictive deviance and for similar theoretical reasons. We then employ a leave-deviant-group-out method, which sequentially analyzes how each deviant group affects model parameters, thereby identifying potentially unstable paths in the model. We can then infer descriptive reasons for why and how overfit affects a given model and data sample using the grouping criteria of the deviance tree, construct scores of deviant groups, and resulting unstable paths. These insights allow researchers to identify unexpected behavior that could define boundary conditions of their theory or point to new theoretical phenomena. We demonstrate the practical utility of our analytical framework on a technology adoption model in a new context. This paper was accepted by Dongjun Wu, information systems. Funding: This work was partially supported by the Ministry of Science and Technology, Taiwan [Grants 109-2811-H-007-503 and 108-2410-H-007-091-MY3] and by the 2021 Arts and Social Sciences Benefaction Fund of Trinity College Dublin, Ireland. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2023.4705. [ABSTRACT FROM AUTHOR]

This paper reports the findings of a bibliometric analysis using VOSviewer on 392 Scopus database documents published from 2003 to 2022, aiming to understand the global landscape of the e-learning field and to identify the most prominent authors, institutions, countries and reference publications, as well as the research topics that have recently received the most attention in students' readiness for e-learning in Higher Education Institutions (HEIs). The findings indicate that there has been an upward trend in e-learning readiness among students in HEIs over time. Among the countries studied, the United States, Taiwan, Australia, and Malaysia were found to have the most effective approaches to addressing students' readiness for e-learning. The most highly cited author in this field is M-L. Hung. Based on the citations, the most recognised journal in this field was "Computers and Education" and the universities that were most persuasive were two Taiwan universities in the first position. The data also revealed relatively low levels of collaboration among authors, institutions and nations regarding students' readiness for e-learning.

Involving the global issues as listed in Sustainable Development Goals (SDGs) in education is necessarily done in the education process, especially in English as a Foreign Language (EFL) learning. Exposure to global issues is known to improve students' understanding, awareness, and ability to solve urgent issues faced by global society. This paper aims to find out the trend of research on the coverage of SDGs in students' learning process. This systematic literature analysis was done by applying Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Method. A total of 25 studies were recognized through a systematic search by using Sustainability, SDGs, and EFL as keywords. The result shows that the trend of associating SDGs with EFL settings was done mostly in Indonesia. In the recent year 2022, it reached the highest number of studies in the particular matter with 7 total of research. It was also found that the study involving SDGs on EFL learning was mostly done in the tertiary setting, compared with K-12, junior high school, secondary, high school, and other educational institutions. It was also discovered that the specific area of study enhances EFL students' learning achievement, environmental awareness, global citizen values, as well as students' levels of self-norms, beliefs, and self-value.

The review article presents an analysis of the literature on environmental literacy in sustainable development. By utilizing techniques to examine multiple documents published between 2013 and 2023, including citation analysis, co-authorship analysis, subject area analysis, and keyword analysis, this study aims to provide valuable information and insights into the research landscape surrounding environmental literacy and its contribution to promoting sustainable development. A systematic search was conducted to gather several scientific articles, conference papers, and publications from the Scopus database from 2013 to 2023. The findings of this analysis shed light on authors, influential institutions, and active research groups that contributed to the study of environmental literacy and sustainable development. This comprehensive review offers an understanding of the state of research in this field while identifying areas for further exploration and research gaps. The insights gained from this study can be highly beneficial for researchers, policymakers, and practitioners seeking to advance knowledge and take action toward promoting literacy's role in sustainable development. This analysis is a foundation for advancing our understanding of literacy's significance while emphasizing its vital role in sustainable development efforts.

Background: Interdisciplinary collaboration is known to foster professional innovation and enhance student learning across different domains. However, the research on the effectiveness of integration of interdisciplinary learning in pediatric nursing education is limited. Therefore, this study aimed to examine the effectiveness of integrating game-based learning, an interdisciplinary approach to teaching, into pediatric nursing education's play courses. Methods: We used a mixed methods study with pre-test/post-test quantitative analyses and a descriptive qualitative analysis of students' reflection journals. Data were collected between August 2019 and July 2020 to gauge course effectiveness. Quantitative data obtained from the questionnaires were analyzed using a t-test, correlation, and regression analysis. Qualitative data using students' reflective journals were collected and analyzed using content analysis. One hundred and three second-year nursing students enrolled in a four-year nursing program. Nursing students attended classes in university classrooms and served learning in a kindergarten or hospital in Northern Taiwan. Results: The subscales of Students' Learning Outcome in knowledge, abilities, and attitudes showed significantly higher mean post-test scores compared to pre-test scores: 26.15 (SD = 3.35) vs. 16.82 (SD = 4.49), p <.001; 18.03 (SD = 2.13) vs. 11.43 (SD = 2.95), p <.001; and 12.90 (SD = 2.12) vs. 8.72 (SD = 2.52), p <.001. Furthermore, scores on the Service-Learning Abilities Scale indicated a significant increase in communication, problem-solving, knowledge application, and cross-cultural competence. Integrating instruction to improve problem-solving skills and knowledge application predicts student learning outcomes. Qualitative findings revealed nursing students' reflections on integrating different learning areas, communication, problem-solving, and practical knowledge skills. Conclusions: Integration of interdisciplinary learning effectively stimulates learning among nursing students and enhances their knowledge, abilities, and attitudes toward therapeutic play, benefiting children's health. Our findings demonstrate that integration of interdisciplinary learning significantly enhances nursing students' healthcare-giving competence, particularly in communication, problem-solving, knowledge application, and cross-cultural competence as measured by the Service-Learning Scale. Integrating social service with integration of interdisciplinary learning exposes nursing students to diverse challenges and needs, thereby enhancing their communication skills, knowledge application, and problem-solving abilities. Nursing students can blend knowledge and skills through integrated learning, which is crucial for nursing career preparation. Trial registration: N/A. It was a survey on educational activities. [ABSTRACT FROM AUTHOR]

Accurately imaging seismogenic structures is crucial for seismic hazard assessment. This is especially important around the deformation front (DF) region off SW Taiwan, where seismic potential is high but the fault structure and seismic activity are still poorly understood. Here, we present a comprehensive delineation of seismogenic structures along the onshore and offshore DF of SW Taiwan, utilizing hypocenter relocations and first-motion focal mechanism solutions from January 1991 to March 2019. Five distinctive seismogenic structures are delineated. Particularly, the energetic seismic activity initialled after the 2017 Mw5.3 Tainan earthquake and migrated northeastward along the western side of the DF. The offshore trace of the DF could serve as a boundary delimiting the seismic activity driven by the flexural stress of the subducted Eurasia Plate to the west of the DF. This observation could constrain the magnitude estimation of future earthquakes offshore SW Taiwan. Meanwhile, the areas with higher seismic moment release are located near the DF rather than known faults, indicating that the DF may dominate the seismic moment release. However, further study is warranted into the intricate relationship among seismic strain variation, the structure of DF, and seismic activity to further understand the seismic potential. Our first-motion focal mechanism solutions show that several earthquakes in SW Taiwan were characterized by P-axis orientations parallel to the strike of the Taiwan orogeny. Those events are preferably explained by the lateral compression induced by the ongoing collision between the Eurasia and Philippine Sea plates. Key Points: The deformation front has high seismic potential but seismogenic structure remains unclear. The deformation front confined seismic activity and released relatively large seismic moments. The role of the deformation front must be considered in seismic hazard assessment. [ABSTRACT FROM AUTHOR]

Background: Given the increasing complexity of illnesses and rapid pace of technological advancements in professional training, it is vital to offer nurses ample opportunities to hone their clinical expertise and skills, particularly in ensuring the delivery of premier medical care. This study aimed to determine the factors and predictors influencing nurses' satisfaction with adopting mobile learning approaches in intensive care unit healthcare settings. Additionally, it sought to investigate the applicability of the technology acceptance model in explaining their inclinations and validating the measurement scales employed in the research. Methods: The study employed a cross-sectional survey research design, utilizing a technology acceptance questionnaire and a learning satisfaction questionnaire. The survey was conducted in six intensive care unit departments. A total of 212 participants completed the survey as the primary instrument. Rigorous assessments were conducted to establish the content validity and ensure instrument reliability. Results: The findings demonstrated that perceived usefulness was the most influential factor affecting nurses' intentions to embrace mobile learning approaches, with perceived ease of use emerging as the principal determinant of perceived usefulness. Conclusions: Incorporating mobile learning methodologies is paramount to increasing the calibration of professional nursing education programs. By effectively integrating digital information technology and tools, nursing educators can overcome teaching challenges, deliver innovative clinical nursing education content through mobile learning approaches, and foster optimal development in the field. [ABSTRACT FROM AUTHOR]

This study investigated the ability of a sarcopenia screening test to predict mortality among cancer inpatients. We conducted a prospective study of patients admitted to the oncology ward of a teaching hospital in southern Taiwan. Over a 5‐month period, 82 patients were enrolled for evaluation and were followed for 3 years. All participants received a comprehensive assessment at the time of admission, including Eastern Cooperative Oncology Group (ECOG) performance status, cognitive ability, nutrition index, body mass index, and short physical performance battery (SPPB). Age, ECOG performance status, dementia, SPPB score, and albumin level were associated with sarcopenia. Of the enrolled participants, 53 (64.6%) were diagnosed with sarcopenia. Patients with sarcopenia were associated with worse overall survival (OS) than patients without sarcopenia (28.8% vs. 82%, p = 0.01). Metastasis (hazard ratio [HR]: 5.166; 95% confidence interval [CI]: 1.358–19.656) and albumin level (HR: 4.346; 95% CI: 1.493–12.654) were independent and significant predictors of OS for the whole study population. Age was a predictor of 2‐year all‐cause mortality among patients aged ≥65 years but not among those aged <65 years (OS: 25.6% vs. 100%, p = 0.04). To summarize, the sarcopenia screening results were found to predict OS and all‐cause mortality and may be helpful for patient stratification during in‐hospital care. [ABSTRACT FROM AUTHOR]