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How to govern non-financial enterprises engaged in shadow banking activities is of great practical significance. This study investigates whether and how corporate digitization affects shadow banking. Using a sample of Chinese listed companies for the period 2012-2022, we find that corporate digitization has a significant negative effect on shadow banking business. Mechanism tests show that corporate digitization is conducive to enhancing product core competencies, broadening market channels, and improving operational efficiency, thus inhibiting firms from engaging in shadow banking activities. Moreover, the negative impact of corporate digitization on corporate shadow banking is especially noticeable for non-state-owned companies and in areas where local governments have more stringent financial risk regulations. The findings contribute to enriching the literature on the determinants of corporate shadow banking business, and deepen our understanding of the economic consequences of corporate digitization.

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This research aims to investigate the relationships and mutual influence between the digitalization of international trade and customer satisfaction in the context of the post-COVID-19 economy. To achieve this objective, a comprehensive research project has been developed, involving a quantitative approach that combines the advantages of experiments and surveys. Customer satisfaction was assessed based on key service quality parameters in the SERVQUAL model. The study involved 4 stores operating on the AliExpress international trading platform. The sample included a total of 3796 customers. The research findings confirmed the impact of digitalization on customer satisfaction in international trading operations across nearly all dimensions of the SERVQUAL model. The implementation of basic digital innovations substantially enhanced reliability, order processing and delivery speed, product packaging, and the process of selecting and ordering goods, as well as the regularity of notifications and data security. However, the introduction of a chatbot significantly reduced customer satisfaction with the provision of additional information, leading to a decrease in customer empathy. The academic contribution of this study lies in its ability to complement and expand the scientific understanding of the impact of digitalization on customer satisfaction in international trade in the post-COVID-19 era. The study demonstrated that not all digital innovations are perceived equally positively by customers and do not necessarily lead to increased satisfaction. Accordingly, the practical outcome of this research is the empirical confirmation of the need to test customer satisfaction when implementing digital innovations.

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To assess the impact of Strut Adjusted Volume Implant (SAVI) catheter digitization variability on dosimetric evaluation parameters of HDR breast brachytherapy treatment plans. Four clinically approved SAVI cases were chosen for this digitization variability analysis. All patients were implanted with 6-1 SAVI device. Six experienced physicists independently digitized SAVI catheters. Plans utilizing significant peripheral loading were used for this study where SAVI catheters were near the chest wall and/or skin. After digitization was completed for each case by each physicist, the original clinical dwell times were copied over for comparison. This ensured that only variability among plans is the digitization of SAVI catheters by different users. The original plan that went through two physicists' checks and one physician's review was considered the "ground truth" plan to which all other plans were compared. Plans were evaluated on planning parameters for lumpectomy cavity's PTV_Eval D90, V150, V200 and for the OARs (Chest-Wall/Ribs and Skin), on D0.03cc, D0.1cc, D1cc, D2cc. Additionally, a visualization window setting-based uncertainty test was performed on the same 4 cases. Our results showed that the average and maximum dwell positional digitization uncertainties were 0.36 and 0.75 mm, respectively. Average PTV_Eval D90 was 97.11+/-2.93 %, V150 was 23.10+/-4.25 cc, V200 was 11.88+/-1.93 cc. All OAR constraints were met on all plans - Chest-Wall/Ribs (CW/Ribs) and Skin D0.03cc was 103.40+/-9.23 % and 93.60+/-6.14 %, respectively. Aggregate analysis across all plans shows a clinically nonsignificant spread around the mean for all parameters considered. The robustness of SAVI treatment plans to minor variation in catheter digitization was proved through our multiuser study. Our study showed that SAVI planning constraints are stable within reasonable variation of digitization differences. Such uncertainty analysis is useful in standardization of digitization practices in a department and in defining action levels on digitization fixing request during a 2nd check.

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Urban industrial pollution plays a dominant role in environmental pollution in China. Exploring the digital governance path of urban industrial pollution can provide strong support for improving environmental quality. This article empirically investigates the role and path of digitalization in the governance of urban industrial pollution from three dimensions: economic scale, structural scale, and technological scale. The results show that there is an inverted "U"-shaped relationship between digitalization and urban industrial pollution, with initial promotion followed by suppression. Among them, economic scale, industrial transformation and upgrading, and green innovation are the paths for digital governance of urban industrial pollution. In addition, there is a chain path of "green innovation-industrial transformation and upgrading" between the two. Through spatial Durbin model and regional heterogeneity analysis, it is found that digitalization has a spatial spillover effect on urban industrial pollution control, and eastern regions, regions with high economic development level and industrialized cities benefit more from digital urban industrial pollution control. The research conclusions of this article provide references for the Chinese government to formulate relevant policies, deepen the integration of digitalization and urban industrial pollution, and promote digital governance of urban industrial pollution.

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BACKGROUND: The digital transformation in health care requires training nursing and health professionals in the digitally competent use of digital assistive technologies (DAT). The continuing education training "Beratende für digitale Gesundheitsversorgung" ("Consultant for Digital Healthcare") was developed to fill this gap. The effectiveness of the training program will be assessed in this study. OBJECTIVE: The primary objective is to record and measure the participants' learning success. We will assess whether the previously defined teaching intentions, learning objectives, competencies, and participants' expectations have been achieved and whether a transfer of learning occurred. The secondary objective is participant satisfaction and feasibility of the training. The tertiary objective is the successful transfer of DAT by participants in their institutions. METHODS: Approximately 65 nursing and health care professionals will participate in the pilot phase of the further training and evaluation process, which is planned in a mixed methods design in a nonsequential manner. The different methods will be combined in the interpretation of the results to achieve a synaptic view of the training program. We plan to conduct pre-post surveys in the form of participant self-assessments about dealing with DAT and content-related knowledge levels. Exploratory individual interviews will also be conducted to build theory, to examine whether and to what extent competence (cognition) has increased, and whether dealing (affect) with DAT has changed. Furthermore, an interim evaluation within the framework of the Teaching Analysis Poll (TAP) will occur. The knowledge thereby gained will be used to revise and adapt the modules for future courses. To assess the transfer success, the participants create a practical project, which is carried out within the training framework, observed by the lecturers, and subsequently evaluated and adapted. RESULTS: We expect that the learning objectives for the continuing education training will be met. The attendees are expected to increase their level of digital competence in different skills areas: (1) theoretical knowledge, (2) hands-on skills for planning the application and practical use of DAT, (3) reflective skills and applying ethical and legal considerations in their use, (4) applying all that in a structured process of technology implementation within their practical sphere of work. CONCLUSIONS: The aim of this study and appropriate further training program are to educate nursing and health care professionals in the use of DAT, thereby empowering them for a structured change process toward digitally aided care. This focus gives rise to the following research questions: First, how should further training programs be developed, and which focus is appropriate for addressee-appropriate learning goals, course structure, and general curriculum? Second, how should a training program with this specific content and area be evaluated? Third, what are the conditions to offer a continued program? INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/57860.

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Introducción: El vértigo se define como la distorsión en la sensación de movimiento propio cuando se realiza un movimiento normal de la cabeza, para su estudio y categorización por el médico general, se recomienda el enfoque TiTrATE, que determina el momento de inicio, duración, evolución y los desencadenantes del vértigo. Objetivo: creación de una aplicación web progresiva (PWA) llamada TiTrATEapp y aplicarla en los pacientes que acudan a la emergencia en el mes de febrero 2023. Método: estudio tipo prospectivo, experimental, observacional, de análisis comparativo. Resultado: se creó una aplicación web progresiva (PWA) llamada TiTrATEapp, basada en el algoritmo TiTrATE, comparándose el tiempo de cálculo de la aplicación del algoritmo de forma manual y digital, obteniendo como resultado que la aplicación digital es más rápida y eficaz. Conclusión: Las aplicaciones móviles son una herramienta objetiva que ayuda los profesionales de la salud a diagnosticar y a tomar decisiones clínicas de forma práctica basadas en la evidencia científica, la digitalización del TiTrATE permite a los médicos realizar un diagnóstico acertado de forma rápida y orientan a la referencia del paciente a la especialidad correcta y la eficiencia de recursos. (AU)

Introduction: Vertigo is defined as the distortion in the sensation of self-movement when a normal movement of the head is made, for its study the TiTrATEapproach is recommended for the general practitioner, which determines the moment of onset, duration, evolution and triggers of vertigo for its study and categorization accurately. Objective: to create a progressive web application (PWA) called TiTrATEapp, Method: Prospective, observational, longitudinal study. Result: creation of a progressive web application (PWA) called TiTrATEapp, based on the TiTrATE algorithm, comparing the calculation time of the application of the algorithm manually and digitally, resulting in the digital application being faster and more efficient. Discussion: Vertigo is a difficult symptom to decipher in the emergency room, due to the subjective description of patients and the wide variety of probable causes, the digitization ofTiTrATE allows to rule out potentially dangerous causes, quickly, accurately. At present there are no studies that measure the effectiveness of mobile applications for the study of vertigo. Conclusion: Mobile applications are an objective tool that helps health professionals diagnose and make clinical decisions in a practical way based on scientific evidence, the digitalization of TiTrATE allows resident doctors to make an accurate diagnosis quickly and guide the patient's referral to the correct specialty and resource efficiency. (AU)

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The complex systematics of the genus Sedum, the difficulties of its classification and the ambiguity of the concrete identification of the taxa brought about the need to implement a measurement system adaptable to field conditions, so as to facilitate the accuracy of data collection, avoiding the etiolation of samples and, therefore, the deterioration of the morphological structures subject to analysis. Thus, our study describes a digitization of the classic method of making measurements using millimeter paper, thus facilitating the subsequent statistical processing of quantifiable values. Depending on the number of pixels in the photos taken and the pixel/millimeter ratio, a variable measurement scale can be created depending on the size of the analyzed taxomes. The method used adds to the classic taxonomy, which is based on the analysis of morphological characteristics to determine the species of these succulent plants. The applicability of our method is shown by means of the example of an analysis performed on the flowers of the native species of the genus Sedum in the territory of Romania.

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This paper presents computer and color vision research focusing on human color perception in VR environments. A VR art gallery with digital twins of original artworks is created for this experiment. In this research, the field of colorimetry and the application of the L*a*b* and RGB color models are applied. The inter-relationships of the two color models are applied to create a color modification of the VR art gallery environment using C# Script procedures. This color-edited VR environment works with a smooth change in color tone in a given time interval. At the same time, a sudden change in the color of the RGB environment is defined in this interval. This experiment aims to record a user's reaction embedded in a VR environment and the effect of color changes on human perception in a VR environment. This research uses lie detector sensors that record the physiological changes of the user embedded in VR. Five sensors are used to record the signal. An experiment on the influence of the user's color perception in a VR environment using lie detector sensors has never been conducted. This research defines the basic methodology for analyzing and evaluating the recorded signals from the lie detector. The presented text thus provides a basis for further research in the field of colors and human color vision in a VR environment and lays an objective basis for use in many scientific and commercial areas.

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BACKGROUND: The incidence of chronic diseases is on the rise worldwide, with a high mortality rate in China, posing a serious threat to the health-related quality of life (HRQoL) of middle-aged and older adults. This study explores the association between chronic diseases and the HRQoL of middle-aged and older adults, as well as the role of physical activity (PA) and degree of digitization in this relationship. METHODS: The data used in this study was obtained from the 2018 China Health and Retirement Longitudinal Study (CHARLS), which included 13,620 middle-aged and older Chinese adults (≥ 45 years). The study utilized correlation analysis, and bootstrapping to investigate the mediating role of PA and the moderating influence of the degree of digitization. Data analysis was conducted using SPSS 26.0. RESULTS: The study findings indicate that the severity of chronic disease has a significant negative predictive effect on HRQoL (PCS, physical component summary; MCS, mental component summary) (PCS: ß = -2.515, p < 0.01, MCS: ß = -0.735, p < 0.01). Further analysis revealed that PA plays a mediating and masking role in the impact of chronic disease on PCS and MCS. Additionally, the degree of digitization moderates the relationship between chronic disease and PA, chronic disease and PCS, and PA and PCS. CONCLUSION: For middle-aged and older persons, chronic diseases have a detrimental effect on their HRQoL; nevertheless, PA can help. Furthermore, proper internet usage can help older individuals to some extent in mitigating the negative impact of chronic diseases. Therefore, it is encouraged to promote PA among the elderly with chronic diseases to improve their physical health, as well as to guide them in the proper use of the Internet to establish healthy behaviors.

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Time-resolved spectroscopic and electron-ion coincidence techniques are essential to study dynamic processes in materials or chemical compounds. For this type of analysis, it is necessary to have detectors capable of providing, in addition to image-related information, the time of arrival for each individual detected particle ("x, y, time"). The electronics capable of handling such sensors must meet requirements achievable only with time-to-digital converters (TDC) with a resolution on the order of tens of picoseconds and the use of a field-programmable gate array (FPGA) to manage data acquisition and transmission. This study introduces the design and implementation of an innovative TDC based on two FPGAs working symbiotically with different tasks: the first (AMD/Xilinx Artix® 7) directly implements a TDC, aiming for a temporal precision of 12 picoseconds, while the second (Intel Cyclone® 10) manages the acquisition and connectivity with the external world. The TDC has been optimized to operate on eight channels (+ sync) simultaneously but is potentially extendable to a greater number of channels, making it particularly suitable for coincidence measurements where it is necessary to temporally correlate multiple pieces of information from various measurement systems.

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The evaluation of clinical utility is essential for the successful adoption of new technology in clinical practice. An approach to evaluating clinical utility is presented here using the example of digitized measurement instruments.

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The digital era is reshaping agricultural practices, opening new avenues for sustainable growth, and proving indispensable in global challenges like food security and environmental conservation. However, a comprehensive understanding of this evolving landscape remains paramount. This research evaluates 344 papers from the Web of Science database to delve into sustainable agriculture's historical and current patterns in the digital era through bibliometric analysis and project future domains. Specifically, citation analysis identified influential papers, journals, institutions, and countries, while co-authorship analysis verified the interactions between authors, affiliations, and countries. Co-citation analysis found four hotspot clusters: prosperity and challenges in agricultural sustainability, digital information and agricultural development, innovations for sustainable agriculture, and geospatial analysis in environmental studies. The co-occurrence of keywords analysis revealed four main clusters for future studies: smart agriculture and biodiversity conservation, digitalization and sustainable agriculture, technologies and agricultural challenge management, and digital intelligence and farmer adoption. The study pioneers the use of bibliometric analysis to explore sustainable agriculture in the digital era. It presents invaluable insights into the evolving landscape of this field, summarizing its hotspots and suggesting future trajectories.

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Orthodontics is undergoing a digital revolution, transforming traditional techniques with modern technology. This evolution is driven by the need for precise diagnosis and treatment planning. Digital platforms, including digital radiography and cone beam computed tomography (CBCT), are replacing conventional methods, enhancing documentation, analysis, and appliance production. Three-dimensional imaging enables customized treatment plans and appliance design using computer-aided design and computer-aided manufacture (CAD/CAM). Integration of digital models and software facilitates treatment simulation and patient communication. Digital videography enhances diagnostic capabilities. Embracing digital processes is essential for improved patient care and practice efficiency in orthodontics. This review article on digital orthodontics aims to provide a comprehensive overview and critical analysis of the current advancements, technologies, applications, benefits, and challenges in the field of orthodontics utilizing digital tools and technologies.

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Background: The exponential growth in computing power and the increasing digitization of information have substantially advanced the machine learning (ML) research field. However, ML algorithms are often considered "black boxes," and this fosters distrust. In medical domains, in which mistakes can result in fatal outcomes, practitioners may be especially reluctant to trust ML algorithms. Objective: The aim of this study is to explore the effect of user-interface design features on intensivists' trust in an ML-based clinical decision support system. Methods: A total of 47 physicians from critical care specialties were presented with 3 patient cases of bacteremia in the setting of an ML-based simulation system. Three conditions of the simulation were tested according to combinations of information relevancy and interactivity. Participants' trust in the system was assessed by their agreement with the system's prediction and a postexperiment questionnaire. Linear regression models were applied to measure the effects. Results: Participants' agreement with the system's prediction did not differ according to the experimental conditions. However, in the postexperiment questionnaire, higher information relevancy ratings and interactivity ratings were associated with higher perceived trust in the system (P<.001 for both). The explicit visual presentation of the features of the ML algorithm on the user interface resulted in lower trust among the participants (P=.05). Conclusions: Information relevancy and interactivity features should be considered in the design of the user interface of ML-based clinical decision support systems to enhance intensivists' trust. This study sheds light on the connection between information relevancy, interactivity, and trust in human-ML interaction, specifically in the intensive care unit environment.

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Objective.Cardiovascular diseases are a major cause of mortality globally, and electrocardiograms (ECGs) are crucial for diagnosing them. Traditionally, ECGs are stored in printed formats. However, these printouts, even when scanned, are incompatible with advanced ECG diagnosis software that require time-series data. Digitizing ECG images is vital for training machine learning models in ECG diagnosis, leveraging the extensive global archives collected over decades. Deep learning models for image processing are promising in this regard, although the lack of clinical ECG archives with reference time-series data is challenging. Data augmentation techniques using realistic generative data models provide a solution.Approach.We introduceECG-Image-Kit, an open-source toolbox for generating synthetic multi-lead ECG images with realistic artifacts from time-series data, aimed at automating the conversion of scanned ECG images to ECG data points. The tool synthesizes ECG images from real time-series data, applying distortions like text artifacts, wrinkles, and creases on a standard ECG paper background.Main results.As a case study, we used ECG-Image-Kit to create a dataset of 21 801 ECG images from the PhysioNet QT database. We developed and trained a combination of a traditional computer vision and deep neural network model on this dataset to convert synthetic images into time-series data for evaluation. We assessed digitization quality by calculating the signal-to-noise ratio and compared clinical parameters like QRS width, RR, and QT intervals recovered from this pipeline, with the ground truth extracted from ECG time-series. The results show that this deep learning pipeline accurately digitizes paper ECGs, maintaining clinical parameters, and highlights a generative approach to digitization.Significance.The toolbox has broad applications, including model development for ECG image digitization and classification. The toolbox currently supports data augmentation for the 2024 PhysioNet Challenge, focusing on digitizing and classifying paper ECG images.

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BACKGROUND: Decision analytic models and meta-analyses often rely on survival probabilities that are digitized from published Kaplan-Meier (KM) curves. However, manually extracting these probabilities from KM curves is time-consuming, expensive, and error-prone. We developed an efficient and accurate algorithm that automates extraction of survival probabilities from KM curves. METHODS: The automated digitization algorithm processes images from a JPG or PNG format, converts them in their hue, saturation, and lightness scale and uses optical character recognition to detect axis location and labels. It also uses a k-medoids clustering algorithm to separate multiple overlapping curves on the same figure. To validate performance, we generated survival plots form random time-to-event data from a sample size of 25, 50, 150, and 250, 1000 individuals split into 1,2, or 3 treatment arms. We assumed an exponential distribution and applied random censoring. We compared automated digitization and manual digitization performed by well-trained researchers. We calculated the root mean squared error (RMSE) at 100-time points for both methods. The algorithm's performance was also evaluated by Bland-Altman analysis for the agreement between automated and manual digitization on a real-world set of published KM curves. RESULTS: The automated digitizer accurately identified survival probabilities over time in the simulated KM curves. The average RMSE for automated digitization was 0.012, while manual digitization had an average RMSE of 0.014. Its performance was negatively correlated with the number of curves in a figure and the presence of censoring markers. In real-world scenarios, automated digitization and manual digitization showed very close agreement. CONCLUSIONS: The algorithm streamlines the digitization process and requires minimal user input. It effectively digitized KM curves in simulated and real-world scenarios, demonstrating accuracy comparable to conventional manual digitization. The algorithm has been developed as an open-source R package and as a Shiny application and is available on GitHub: https://github.com/Pechli-Lab/SurvdigitizeR and https://pechlilab.shinyapps.io/SurvdigitizeR/ .

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The current work presents the generation of a comprehensive spatial dataset of a lightweight beam element composed of four twisted plywood strips, achieved through the application of Structure-from-Motion (SfM) - Multi-view Stereo (MVS) photogrammetry techniques in controlled laboratory conditions. The data collection process was meticulously conducted to ensure accuracy and precision, employing scale bars of varying lengths. The captured images were then processed using photogrammetric software, leading to the creation of point clouds, meshes, and texture files. These data files represent the 3D model of the beam at different mesh sizes (raw, high-poly, medium-poly, and low-poly), adding a high level of detail to the 3D visualization. The dataset holds significant reuse potential and offers essential resources for further studies in numerical modeling, simulations of complex structures, and training machine learning algorithms. This data can also serve as validation sets for emerging photogrammetry methods and form-finding techniques, especially ones involving large deformations and geometric nonlinearities, particularly within the structural engineering field.

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Enhancement of the health care system in Russia continues to be one of key directions of National development. In conditions of deficiency of personnel, systemic changes are needed to transit to qualitatively new level. The application of digital platforms permits to resolve a number of issues related to accessibility and quality of medical services. The paper characterizes current state of health care digitization and level of competitiveness of medical institutions. On the basis of analysis of corporate culture of medical institutions, conclusions are made that it contributes to successful implementation of unified medical information system and development of best corporate standards and traditions.

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The article considers results of study of the R&D sector directions development in system of Russian medical higher education in the context of digitization. The analysis made it possible to substantiate timeliness and importance of solving problems of improving medical services quality against the background of necessity for medical workers to systematically master breakthrough digital technologies in current medical practice. This conditions importance to ensure efficiency of R&D in Russian higher medical education in the context of digitization. The main models of organization of activities in the field of R&D are characterized, taking into account sources of financing and staffing. Based on on-line surveys of students in Google docs about their attitude to their further participation in R&D during education and after graduation, weak motivation to be engaged in R&D during their university education was revealed that is justified by non-obviousness of prospects of financial remuneration. Along with this, study established high degree of interest among students to mastering breakthrough digital technologies in order to further apply them in medical practice together with the latest medical technologies.

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The digitization of production systems has revolutionized industrial monitoring. Analyzing real-time bottom-up data enables the dynamic monitoring of industrial processes. Data are collected in various types, like video frames and time signals. This article focuses on leveraging images from a vision system to monitor the manufacturing process on a computer numerical control (CNC) lathe machine. We propose a method for designing and integrating these video modules on the edge of a production line. This approach detects the presence of raw parts, measures process parameters, assesses tool status, and checks roughness in real time using image processing techniques. The efficiency is evaluated by checking the deployment, the accuracy, the responsiveness, and the limitations. Finally, a perspective is offered to use the metadata off the edge in a more complex artificial-intelligence (AI) method for predictive maintenance.