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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]

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]

With the development of maritime technology and equipment, most ships are equipped with an automatic identification system (AIS) to store navigation information. Over time, the size of the data increases, rendering its storage and processing difficult. Hence, it is necessary to transform the AIS data into trajectories, and then simplify the AIS trajectories to remove unnecessary information that is not related to route shape. Moreover, topographic information must be considered because otherwise, the simplified trajectory can intersect obstacles. In this study, we propose an AIS trajectory simplification algorithm considering topographic information. The proposed algorithm simplifies the trajectories without the intersection of the trajectory and obstacle using the improved Douglas–Peucker algorithm. Polygon map random (PMR) quadtree was used to consider topographic information on the coast, and the intersection between topographic information and simplified trajectories was efficiently computed using the PMR quadtree. To verify the effectiveness of the proposed algorithm, experiments were conducted on real-world trajectories in the Korean sea. The proposed algorithm yielded simplified trajectories with no intersections of the trajectory and obstacle. In addition, the computational efficiency of the proposed algorithm with the PMR quadtree was superior to that without the PMR quadtree. [ABSTRACT FROM AUTHOR]

An index on the gas market commonly refers to the average price of a certain trading product, e.g., over the period of one month. Index-based sourcing is a widely-used habit in modern gas business. Risks are reduced by averaging prices over the purchasing period. Due to the significant volume, there have been many attempts to "beat the index", i.e., to design a strategy that, over time, offers cheaper prices than the index. Here, we use neural networks to identify n, n ∈ N , optimal shopping points. Both classification- and forecasting-based strategies are tested to decide on each trading day if gas should be purchased or not. Thereby, we use the Front Month index based on prices from the Dutch Title Transfer Facility as an example. Regarding cumulative performance, all but a very simple myopic algorithm are able to outperform the index. However, each strategy has its flaws and some positive results are due to the price increase during 2021. If one opts for an active sourcing strategy, then a forecasting-based approach is the best choice. [ABSTRACT FROM AUTHOR]

In practice, road management data are typically managed in two-dimensional (2D) geospatial forms. However, 2D geographic information system (GIS)-based road infrastructure management data have limitations in their representation of complex roads, such as interchanges, bridges, and tunnels. As such, complex and large road network management data cannot be adequately managed in a 2D GIS-based form. This study discusses the use of the LandInfra standard for road infrastructure management in Korea, considering its focus on land and civil engineering infrastructure facilities. To facilitate the transition from 2D to 3D GIS, we analyzed existing road management models of road pavement and road register information and created Unified Modeling Language (UML) class diagrams depicting these models. Then, existing road management classes and LandInfra classes were mapped. Based on the results, we propose a road management model based on the Facility, Alignment, and Road parts of LandInfra. For its implementation, several classes of the proposed data model were encoded into InfraGML using real-world data input. Taken together, this study shows how the LandInfra standard can be extended and applied to the field of road infrastructure management in Korea, supporting the transition from a 2D to a 3D GIS-based model. [ABSTRACT FROM AUTHOR]

Conventional medical equipment used for treating patients with ischemic heart disease relies on pneumatic compression to achieve intense and instantaneous compression of the legs. Because the pneumatic operation of a compressor inevitably produces noise, the treatment is given to a patient in a separate room to avoid causing discomfort to other patients. This need for a dedicated treatment room could be another source of increased medical costs. In this study, a new electrical motor-driven system was developed to address the noise problem of existing pneumatic compression devices. Additionally, the new system features a reduced footprint and weight, and can be carried by medical staff. To develop a low-noise leg compression machine, the noise level at the surface of the structure was estimated using multibody dynamics simulation. Based on the initial design of the electric leg compression machine, parameters including assembly tolerance, component material, and shape of the structure were adjusted to prepare variations of the initial design, and their noise characteristics were analyzed. It was found that by applying the design variables, the noise levels were reduced by 7.2–11.7% compared with the initial design. The most significant reduction in noise levels was 11.7% and was achieved by reinforcing the section surrounding the gearbox enclosing a noise source. [ABSTRACT FROM AUTHOR]

How does vaccination against foot-and-mouth disease (FMD) affect pregnant cows? Vaccination is the most effective method of preventing the spread of FMD, but it is linked to sporadic side effects, such as abortion and premature birth, which result in economic loss. In this study, ruminoreticular temperature and body activity were measured before and after FMD vaccination using a ruminoreticular biocapsule sensor in Hanwoo cows at different stages of pregnancy. Compared to the unvaccinated groups, the ruminoreticular temperature increased 12 h after vaccination in the vaccinated groups. This increase in temperature is significantly correlated to vaccination. Compared to the nonpregnant and early pregnancy groups, the ruminoreticular temperature of the late pregnancy group increased sharply by more than 40 °C. Moreover, in nonpregnant and early pregnancy groups, a rapid increase in body activity was observed after FMD vaccinations. Of the 73 pregnant vaccinated cows in the study, a total of five cases had side effects (four abortions and one premature birth). Therefore, changes in the ruminoreticular temperature and activity in pregnant cows can be used as raw data to further clarify the association of FMD vaccination with the loss of a fetus and possibly predict abortion, miscarriage, and premature birth following FMD vaccination. [ABSTRACT FROM AUTHOR]

Existing studies on reducing urban heat island phenomenon and building temperature have been actively conducted; however, studies on investigating the warm roof phenomenon to in-crease the temperature of buildings are insufficient. A cool roof is required in a high-temperature region, while a warm roof is needed in a low-temperature or cold region. Therefore, a warm roof evaluation was conducted in this study using the roof color (black, blue, green, gray, and white), which is relatively easier to install and maintain compared to conventional insulation materials and double walls. A remote sensing method via an unmanned aerial vehicle (UAV)-mounted thermal infrared (TIR) camera was employed. For warm roof evaluation, the accuracy of the TIR camera was verified by comparing it with a laser thermometer, and the correlation between the surface temperature and the room temperature was also confirmed using Pearson correlation. The results showed significant surface temperature differences ranging from 8 °C to 28 °C between the black-colored roof and the other colored roofs and indoor temperature differences from 1 °C to 7 °C. Through this study, it was possible to know the most effective color for a warm roof according to the color differences. This study gave us an idea of which color would work best for a warm roof, as well as the temperature differences from other colors. We believe that the results of this study will be helpful in heating load research, providing an objective basis for determining whether a warm roof is applied. [ABSTRACT FROM AUTHOR]

Inertial microfluidics has been providing simple technical solutions to such demands by solely utilizing hydrodynamic forces that have differentially arisen based on flow speed, channel geometry, and particle properties. The growing demands for label-free, high throughput processing of biological, environmental, and industrial samples have instigated technical innovations for inflow particle manipulations with better resolution and purity. Collectively, this Special Issue reports recent advancements in understanding and technological innovations of inertial microfluidics to broaden their applications to real-world and complex samples for high throughput, label-free microscale particle manipulations. [Extracted from the article]

The global warming and the dangerous climate change arising from the massive emission of CO2 from the burning of fossil fuels have motivated the search for alternative clean and sustainable energy sources. However, the industrial development and population necessities make the decoupling of economic growth from fossil fuels unimaginable and, consequently, the capture and conversion of CO2 to fuels seems to be, nowadays, one of the most promising and attractive solutions in a world with high energy demand. In this respect, the electrochemical CO2 conversion using renewable electricity provides a promising solution. However, faradaic efficiency of common electro-catalysts is low, and therefore, the design of highly selective, energy-efficient, and cost-effective electrocatalysts is critical. Carbon-based materials present some advantages such as relatively low cost and renewability, excellent electrical conductivity, and tunable textural and chemical surface, which show them as competitive materials for the electro-reduction of CO2. In this review, an overview of the recent progress of carbon-based electro-catalysts in the conversion of CO2 to valuable products is presented, focusing on the role of the different carbon properties, which provides a useful understanding for the materials design progress in this field. Development opportunities and challenges in the field are also summarized. [ABSTRACT FROM AUTHOR]

Understanding the behavior of a single particle flowing in a microchannel is a necessary step in designing and optimizing efficient microfluidic devices for the separation, concentration, counting, detecting, sorting, or mixing of particles in suspension. Although the inertial migration of spherical particles has been deeply investigated in the last two decades, most of the targeted applications involve shaped particles whose behavior in microflows is still far from being completely understood. While traveling in a channel, a particle both rotates and translates: it translates in the streamwise direction driven by the fluid flow but also in the cross-section perpendicular to the streamwise direction due to inertial effects. In addition, particles' rotation and translation motions are coupled. Most of the existing works investigating the transport of particles in microchannels decouple their rotational and lateral migration behaviors: particle rotation is mainly studied in simple shear flows, whereas lateral migration is neglected, and studies on lateral migration mostly focus on spherical particles whose rotational behavior is simple. The aim of this review is to provide a summary of the different works existing in the literature on the inertial migration and the rotational behavior of non-spherical particles with a focus and discussion on the remaining scientific challenges in this field. [ABSTRACT FROM AUTHOR]

Studies on cell separation with inertial microfluidics are often carried out with solid particles initially. When this condition is applied for actual cell separations, the efficiency typically becomes lower because of the polydispersity and deformability of cells. Therefore, the understanding of deformability-induced lift force is essential to achieve highly efficient cell separation. We investigate the inertial focusing positions of viscous droplets in a triangular channel while varying Re, deformability, and droplet size. With increasing Re and decreasing droplet size, the top focusing position splits and shifts along the sidewalls. The threshold size of the focusing position splitting increases for droplets with larger deformability. The overall path of the focusing position shifts with increasing Re also has a strong dependency on deformability. Consequently, droplets of the same size can have different focusing positions depending on their deformability. The feasibility of deformability-based cell separation is shown by different focusing positions of MCF10a and MCF7 cells. [ABSTRACT FROM AUTHOR]

3D imaging of a biological sample provides information about cellular and subcellular structures that are important in cell biology and related diseases. However, most 3D imaging systems, such as confocal and tomographic microscopy systems, are complex and expensive. Here, we developed a quasi-3D imaging tool that is compatible with most conventional microscopes by integrating micromirrors and microchannel structures on coverslips to provide bidirectional imaging. Microfabricated micromirrors had a precisely 45° reflection angle and optically clean reflective surfaces with high reflectance over 95%. The micromirrors were embedded on coverslips that could be assembled as a microchannel structure. We demonstrated that this simple disposable device allows a conventional microscope to perform bidirectional imaging with simple control of a focal plane. Images of microbeads and cells under bright-field and fluorescent microscopy show that the device can provide a quick analysis of 3D information, such as 3D positions and subcellular structures. [ABSTRACT FROM AUTHOR]

Inertial microfluidics has drawn much attention for its applications for circulating tumor cell separations from blood. The fluid flows and the inertial particle focusing in inertial microfluidic systems are highly dependent on the channel geometry and structure. Flexible microfluidic systems can have adjustable 3D channel geometries by curving planar 2D channels into 3D structures, which will enable tunable inertial separation. We present a poly(dimethylsiloxane) (PDMS)-parylene hybrid thin-film microfluidic system that can provide high flexibility for 3D channel shaping while maintaining the channel cross-sectional shape. The PDMS-parylene hybrid microfluidic channels were fabricated by a molding and bonding technique using initiated chemical vapor deposition (iCVD) bonding. We constructed 3D helical inertial microfluidic channels by coiling a straight 2D channel and studied the inertial focusing while varying radius of curvature and Reynolds number. This thin film structure allows for high channel curvature and high Dean numbers which leads to faster inertial particle focusing and shorter channel lengths than 2D spiral channels. Most importantly, the focusing positions of particles and cells in the microchannel can be tuned in real time by simply modulating the channel curvature. The simple mechanical modulation of these 3D structure microfluidic systems is expected to provide unique advantages of convenient tuning of cell separation thresholds with a single device. [ABSTRACT FROM AUTHOR]

A model-free hybrid fault diagnosis technique is proposed to improve the performance of single and double fault detection and isolation. This is a model-free hybrid method which combines the extended parity space approach (EPSA) with a multi-resolution signal decomposition by using a discrete wavelet transform (DWT). Conventional EPSA can detect and isolate single and double faults. The performance of fault detection and isolation is influenced by the relative size of noise and fault. In this paper; the DWT helps to cancel the high frequency sensor noise. The proposed technique can improve low fault detection and isolation probability by utilizing the EPSA with DWT. To verify the effectiveness of the proposed fault detection method Monte Carlo numerical simulations are performed for a redundant inertial measurement unit (RIMU).