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Although physical education (PE) teachers have increased access to digital/online continuous professional development activities, there are few robust accounts of how they engage with and experience these environments. Purpose: The purpose of this study was to examine PE teachers' participation patterns within self-directed online PE continuous professional development activities using mobile instant messenger. Methods: Data were generated from (a) 5,246 messages exchanged in the mobile instant messenger chatroom from 281 teachers, (b) semistructured interviews with 10 teachers, and (c) 1,275 messages posted by the 10 interviewed teachers. Quantitative data were analyzed for measures of central tendency, and qualitative data were analyzed inductively. Findings: Five patterns of PE teachers' usage of mobile instant messenger were identified: (a) ringmasters, (b) passive uploaders, (c) active uploaders, (d) requesters, and (e) bystanders. Discussion: The findings suggest that each engagement pattern illustrates the differential goals of learning, types of interaction, and forms of participation by teachers engaged in online continuous professional development.

The material transport system, facilitated by motor proteins, plays a vital role in maintaining a non‐equilibrium cellular state. However, understanding the temporal coordination of motor protein activity requires an advanced imaging technique capable of measuring 3D angular displacement in real‐time. In this study, a Fourier transform‐based plasmonic dark‐field microscope has been developed using anisotropic nanoparticles, enabling the prolonged and simultaneous observation of endosomal lateral and rotational motion. A sequence of discontinuous 3D angular displacements has been observed during the pause and run phases of transport. Notably, a serially correlated temporal pattern in the intermittent rotational events has been demonstrated during the tug‐of‐war mechanism, indicating Markovian switching between the exploitational and explorational modes of motor protein exchange prior to resuming movement. Alterations in transition frequency and the exploitation‐to‐exploration ratio upon dynein inhibitor treatment highlight the relationship between disrupted motor coordination and reduced endosomal transport efficiency. Collectively, these results suggest the importance of orchestrated temporal motor protein patterns for efficient cellular transport. [ABSTRACT FROM AUTHOR]

In recent years, ESG (environmental, social, and governance) has emerged as a critical investment concept. Its goal is to create value for both shareholders and society, encouraging companies to optimize social value. However, the exploration and research into "the proportion of firms exporting and the pathways through which the environmental, social, and governance activities of carbon-intensive firms influence firms' financial performance" remains largely unexplored. This study establishes a research framework within this context, utilizing listed Chinese manufacturing companies as the research subjects. Taking agency theory rationale and signaling theory as the theoretical framework, this study thoroughly investigates the relationship between ESG ratings, corporate export ratios, and corporate financial performance through panel regression models using fixed-time, fixed-industry, and bi-directional fixed-effects models. The results of this study show that (1) ESG ratings have a positive impact on corporate financial performance; (2) firms' export ratios play a mediating role in the relationship between ESG ratings and corporate financial performance; and (3) carbon-intensive firms have a positive moderating effect on the relationship between ESG ratings and corporate financial performance. Based on these findings, we propose policy recommendations at the firm and government levels to increase the importance of ESG, strengthen corporate governance, and promote continuous progress in ESG. This study provides micro evidence of the interactions between ESG ratings, export ratios, carbon-intensive firms, and firm performance to enable investors to make informed decisions. [ABSTRACT FROM AUTHOR]

This study utilizes Thermal Infrared (TIR) imaging technology to detect hotspots in photovoltaic (PV) modules of solar power plants. Unmanned aerial vehicle (UAV)-based TIR imagery is crucial for efficiently analyzing fault detection in solar power plants. This research explores optimal operational parameters for generating high-quality TIR images using UAV technology. In addition to existing variables such as humidity, emissivity, height, wind speed, irradiance, and ambient temperature, newly considered variables including the angle of incidence between the target object and the thermal infrared camera are analyzed for their impact on TIR images. Based on the solar power plant's tilt (20°) and the location coordinate data of the hotspot modules, the inner and outer products of the vectors were used to obtain the normal vector and angle of incidence of the solar power plant. It was discovered that the difference between measured TIR temperature data and Land Surface Temperature (LST) data varies with changes in the angle of incidence. The analysis presented in this study was conducted using multiple regression analysis to explore the relationships between dependent and independent variables. The Ordinary Least Squares (OLS) regression model employed was able to explain 63.6% of the variability in the dependent variable. Further, the use of the Condition Number (Cond. No.) and the Variance Inflation Factor (VIF) revealed that the multicollinearity among all variables was below 10, ensuring that the independence among variables was well-preserved while maintaining statistically significant correlations. Furthermore, a positive correlation was observed with the actual measured temperature values, while a negative correlation was observed between the TIR image data values and the angle of incidence. Moreover, it was found that an angle of incidence between 15° and 20° yields the closest similarity to LST temperature data. In conclusion, our research emphasizes the importance of adjusting the angle of incidence to 15–20° to enhance the accuracy of TIR imaging by mitigating overestimated TIR temperature values. [ABSTRACT FROM AUTHOR]

Dementia has become a profound public health problem due to the number of patients increasing every year. Previous studies have reported that environmental factors, including greenness, may influence the development and progression of dementia. Studies have found that exposure to green space is associated with a lower incidence of dementia. However, many definitions of green space exist, and the effects of its use may differ with the type of green space. Therefore, two types of green space measures were considered in this study to assess the differences in their impact on the prevalence of dementia among females and males. This study used five years of data (2017–2021) from 235 districts in South Korea. The two green space measures used were open space density and normalized difference vegetation index (NDVI), which were derived from satellite images. The analysis utilized a combination of traditional and spatial panel analyses to account for the spatial and temporal effects of independent variables on dementia prevalence. The spatial autocorrelation results revealed that both measures of greenness were spatially correlated with dementia prevalence. The spatial panel regression results revealed a significant positive association between NDVI and dementia prevalence, and open space had a negative association with dementia prevalence in both genders. The difference in the findings can serve as the basis for further research when choosing a greenspace measure, as it affects the analysis results, depending on the objective of the study. This study adds to the knowledge regarding improving dementia studies and the application of spatial panel analysis in epidemiological studies. [ABSTRACT FROM AUTHOR]

Cell separation and sorting are essential steps in cell biology research and in many diagnostic and therapeutic methods. Recently, there has been interest in methods which avoid the use of biochemical labels; numerous intrinsic biomarkers have been explored to identify cells including size, electrical polarizability, and hydrodynamic properties. This review highlights microfluidic techniques used for label-free discrimination and fractionation of cell populations. Microfluidic systems have been adopted to precisely handle single cells and interface with other tools for biochemical analysis. We analyzed many of these techniques, detailing their mode of separation, while concentrating on recent developments and evaluating their prospects for application. Furthermore, this was done from a perspective where inertial effects are considered important and general performance metrics were proposed which would ease comparison of reported technologies. Lastly, we assess the current state of these technologies and suggest directions which may make them more accessible. Figure A wide range of microfluidic technologies have been developed to separate and sort cells by taking advantage of differences in their intrinsic biophysical properties

Although physical education (PE) teachers have increased access to digital/online continuous professional development activities, there are few robust accounts of how they engage with and experience these environments. Purpose: The purpose of this study was to examine PE teachers' participation patterns within self-directed online PE continuous professional development activities using mobile instant messenger. Methods: Data were generated from (a) 5,246 messages exchanged in the mobile instant messenger chatroom from 281 teachers, (b) semistructured interviews with 10 teachers, and (c) 1,275 messages posted by the 10 interviewed teachers. Quantitative data were analyzed for measures of central tendency, and qualitative data were analyzed inductively. Findings: Five patterns of PE teachers' usage of mobile instant messenger were identified: (a) ringmasters, (b) passive uploaders, (c) active uploaders, (d) requesters, and (e) bystanders. Discussion: The findings suggest that each engagement pattern illustrates the differential goals of learning, types of interaction, and forms of participation by teachers engaged in online continuous professional development. [ABSTRACT FROM AUTHOR]

Catastrophic forgetting, which means a rapid forgetting of learned representations while learning new data/samples, is one of the main problems of deep neural networks. In this paper, we propose a novel incremental learning framework that can address the forgetting problem by learning new incoming data in an online manner. We develop a new incremental learning framework that can learn extra data or new classes with less catastrophic forgetting. We adopt the hippocampal memory process to the deep neural networks by defining the effective maximum of neural activation and its boundary to represent a feature distribution. In addition, we incorporate incremental QR factorization into the deep neural networks to learn new data with both existing labels and new labels with less forgetting. The QR factorization can provide the accurate subspace prior, and incremental QR factorization can reasonably express the collaboration between new data with both existing classes and new class with less forgetting. In our framework, a set of appropriate features (i.e., nodes) provides improved representation for each class. We apply our method to the convolutional neural network (CNN) for learning Cifar-100 and Cifar-10 datasets. The experimental results show that the proposed method efficiently alleviates the stability and plasticity dilemma in the deep neural networks by providing the performance stability of a trained network while effectively learning unseen data and additional new classes. [ABSTRACT FROM AUTHOR]

Modern land/property valuation practice requires three-dimensional (3D) valuation, which is crucial to better valuate and assess values of property units. However, conventional land/property valuation systems primarily exist in 2D form, which hinders the accurate valuation of buildings, condominiums and land. The present study introduces the first step toward establishing an advanced land/property valuation system in Mongolia, where it is urgent to meet such requirements. We examined relevant Mongolian geospatial standards and documents, those related to land valuation (i.e., cadastral parcels and buildings), and a valuation information model, which is based on the ISO 19152:2012 Land Administration Domain Model (LADM), with the aim of developing an LADM Valuation Information Model country profile for Mongolia. After the in-depth analysis of the data model of both the LADM Valuation Information Model and the national geospatial relevant standards, we proposed the LADM Valuation Information Model country profile as a conceptual model. Our study results demonstrate how the LADM Valuation Information Model can be adapted to the Mongolian land administration system. Our findings can be used to serve a reference data model to construct 3D land/property valuation systems for efficient valuation of land (e.g., mass appraisal) and taxation purposes. [ABSTRACT FROM AUTHOR]