Expert Analysis Research Articles

Modernisation of the personnel management system of the Armed Forces of Ukraine in the context of the ongoing military conflict with Russia

Considering the ongoing military conflict with the Russian Federation, the modernisation of the personnel management system of the Armed Forces of Ukraine is of utmost significance. Effective training of new officers is becoming a strategic task to strengthen the country’s defence capability and ensure its national security. The purpose of this research is to thoroughly analyse and justify ways to modernise the personnel management system of the Armed Forces of Ukraine in the context of the current military conflict, with a focus on improving the education and training of the new generation of officers. The research is based on a statistical analysis of data obtained through expert analysis and a survey of highly qualified professionals. The analysis demonstrated that the existing personnel management system of the Armed Forces of Ukraine requires significant modifications to respond to the current challenges of military operations. In particular, there is a need to introduce advanced teaching methods and use modern technologies in the training of officers. In addition, it is essential to improve the organisational structures that provide training for officers. It includes revision of programmes, adaptation to modern conflicts and implementation of international standards of military training. In addition, the psychological and social aspects of the design and development of the officer corps should be considered to ensure its stability and productivity in the long term. A special emphasis is placed on the need to introduce international experience and cooperation with partner countries, which may include the exchange of experience, and joint exercises and training programmes. The results obtained are essential for the development and implementation of strategic plans for the modernisation of the personnel management system of the Armed Forces of Ukraine, which will help to increase the effectiveness of military activities and strengthen the country’s defence capabilities in the face of ever-growing security threats.

PROBLEMS OF JUDICIAL ACTS REVIEW IN THE SUPREME COURT OF THE REPUBLIC OF KAZAKHSTAN

The work is devoted to studying the problems of reviewing court decisions of lower courts by the Supreme Court of the Republic of Kazakhstan. This article examines the control of higher courts over lower courts' activities in the system to ensure the rule of law in case consideration and decision-making. The procedure of reviewing judicial decisions by a higher court that have become effective and those that are not effective in the order of cassation and supervisory review, as well as representations of the President of the Supreme Court, and protests of the Prosecutor General of Kazakhstan, are investigated. Problems of citizens' implementation of their constitutional rights to judicial protection and appeals against court decisions are highlighted. The grounds for reviewing judicial acts that have entered into force, the range of subjects entitled to apply for review, criteria for the admissibility of appealing judicial acts as well as procedure for preliminary consideration of complaints and protest by a judge alone is shown. The analysis of these issues allows us to conclude that the current grounds and procedure for reviewing judicial decisions of the appeal and cassation courts based on the submissions of the Chairman of the Supreme Court and the Attorney General of the Republic of Kazakhstan firstly hinder the realization of citizens' constitutional right to judicial protection, including the right to appeal against judicial decisions, and secondly prevent the formation of consistency in judicial practice. The lack of guidance to lower courts on reviewing judicial decisions by way of cassation and supervision has once again convinced courts of their inability to achieve consistency in the interpretation and application of law, as well as failure to contribute effectively to citizens' exercise of the right to justice. The paper provides a critical analysis of judges, lawyers, and legal experts on the current process for the Supreme Court of the Republic of Kazakhstan to review appeals and cassation court decisions. At the end of the paper, the author draws conclusions and makes suggestions regarding the enhancement of the constitutional right to judicial protection and uniformity in court practice.

CURRENT ISSUES AND DEVELOPMENT PROSPECTS OF MODERN DIGITAL TECHNOLOGIES IN THE WORK OF THE «102 (112)» SERVICE

The work deals with current issues of information provision of the National Police based on a retrospective analysis of literary sources. The use of information technologies in the National Police of Ukraine is a critically important step for increasing the efficiency and transparency of police activities. It can also be added that these technologies ensure the efficiency, speed and completeness of the work of law enforcement agencies. The methodological basis of scientific work is a system of general scientific and special methods of analysis: systematization and generalization (definition of the main categories, their relationship, formation of conclusions and proposals); monographic and system-structural analysis; assessment and situational; graphic (visualization of theoretical research results); factor analysis; expert and tabular analyses. The object of the research is modern digital call-centers on the example of Call Way and AVAYA, as a component of the information support of the national police in the services of the «102» and «112» lines. The subject of the research is the theoretical, scientific and methodological provisions and applied aspects of effective formation of the work of emergency services, information support of the national police in the services of the «102» and «112» lines. It was found that the use of modern digital technologies can significantly increase the efficiency and quality of service to citizens in emergency situations. Modern digital call centers were analyzed by the evaluation-situational method using the example of Call Way and AVAYA. Prospective directions for the development of the automation of the «102 (112)» service have been determined, namely the introduction of voice recognition; use of artificial intelligence (AI); expansion of communication channels; introduction of video calls; data analysis for forecasting; integration with other security systems; application of augmented reality (AR); ensuring mobility; reliability and data protection; creation of interactive instructions, which will become a perspective for further research in this direction.

App-Based Volleyball Scoreboard Performance Evaluation

Study purpose. This research aims to develop and evaluate an application-based volleyball scoreboard game device designed to facilitate the process of recording and managing scores in real time. Materials and methods. This research uses the R&D development method which aims to develop a device-based volleyball game scoreboard application. This research involved 3 IT experts, 5 referees who acted as evaluators of the initial product that had been developed. In addition, there were 5 samples in the small-scale test and 30 samples in the large-scale test. Results. The results of the analysis of the development of application-based volleyball scoreboard game devices by conducting feasibility / justification tests involving economic, technical, business and environmental aspects by refereeing experts, which obtained an average value of 91.60%, where the value was included in the very good category. While the results of the analysis of IT experts obtained an average value of 90.89%, where the value is included in the very good category. The results of the analysis of the effectiveness of the media development of the application-based volleyball scoreboard game device through a small scale test, which obtained an average value of 92.63%, which means it can be concluded that the development model of the application-based volleyball scoreboard game device that has been developed can be implemented/applied with a very good category. Meanwhile, the results of the large-scale test or broad-scale test obtained an average value of 90.94%, which means it can be concluded that the development model of the application-based volleyball scoreboard game device that has been developed is in the excellent category. Conclusion. In conclusion, this application-based volleyball scoreboard game device can be an effective solution to overcome the obstacles of manual score recording, while improving the quality of organising volleyball matches

Female entrepreneurial support requirements: post pandemic ecosystems in India

PurposeThe corona virus outbreak has affected the entrepreneurial ecosystem adversely. This in particular has impacted on females. This study aims to identify the factors affecting the entrepreneurial intention (EI) of females under post-COVID adverse conditions.Design/methodology/approachA total of 340 articles were screened applying the preferred reporting items for systematic reviews and meta-analyses method. The EI of individuals undertaking different professional courses from three top National Institute Ranking Framework (NIRF) government institutes were then analyzed. In the expert analysis, the nominal group technique (NGT) and analytic hierarchy process (AHP) were used to identify and rank the crucial factors. Subsequently, in the exploratory analysis, a 19-item questionnaire was framed. The data was analyzed using SmartPLS 3.FindingsResilience, entrepreneurial education, self-concept and self-efficacy, social influence and opportunity perception were identified as critical indicators. Resilience was identified as the most significant factor. The partial least square structural equation modeling (PLS-SEM) revealed that all the factors except social influence had significant effect on the EI of females.Research limitations/implicationsThis study focuses primarily on factors affecting females in India. As ecosystems and support vary by region and country, the authors suggest that this study be replicated in different regions/countries in the future.Practical implicationsThe potential entrepreneurs can use this study's reference to identify the abilities they need. The government and academic institutions can have skill/training programs to enhance the effect of important factors identified in the study.Originality/valueWhile there is growing research of entrepreneurship and entrepreneurial marketing post-pandemic, there are a lack of Indian studies and female entrepreneurship studies.

Good Intentions, Risky Inventions: A Method for Assessing the Risks and Benefits of AI in Mobile and Wearable Uses

Integrating Artificial Intelligence (AI) into mobile and wearables offers numerous benefits at individual, societal, and environmental levels. Yet, it also spotlights concerns over emerging risks. Traditional assessments of risks and benefits have been sporadic, and often require costly expert analysis. We developed a semi-automatic method that leverages Large Language Models (LLMs) to identify AI uses in mobile and wearables, classify their risks based on the EU AI Act, and determine their benefits that align with globally recognized long-term sustainable development goals; a manual validation of our method by two experts in mobile and wearable technologies, a legal and compliance expert, and a cohort of nine individuals with legal backgrounds who were recruited from Prolific, confirmed its accuracy to be over 85%. We uncovered that specific applications of mobile computing hold significant potential in improving well-being, safety, and social equality. However, these promising uses are linked to risks involving sensitive data, vulnerable groups, and automated decision-making. To avoid rejecting these risky yet impactful mobile and wearable uses, we propose a risk assessment checklist for the Mobile HCI community.

Nutritional Monitoring of Rhodena Lettuce via Neural Networks and Point Cloud Analysis

In traditional farming, fertilizers are often used without precision, resulting in unnecessary expenses and potential damage to the environment. This study introduces a new method for accurately identifying macronutrient deficiencies in Rhodena lettuce crops. We have developed a four-stage process. First, we gathered two sets of data for lettuce seedlings: one is composed of color images and the other of point clouds. In the second stage, we employed the interactive closest point (ICP) method to align the point clouds and extract 3D morphology features for detecting nitrogen deficiencies using machine learning techniques. Next, we trained and compared multiple detection models to identify potassium deficiencies. Finally, we compared the outcomes with traditional lab tests and expert analysis. Our results show that the decision tree classifier achieved 90.87% accuracy in detecting nitrogen deficiencies, while YOLOv9c attained an mAP of 0.79 for identifying potassium deficiencies. This innovative approach has the potential to transform how we monitor and manage crop nutrition in agriculture.

Организационно-финансовые аспекты выбора интраокулярных линз при хирургии катаракты в условиях ценностно-ориентированной системы здравоохранения.

Relevance. In modern conditions, value-based healthcare provides for the provision by medical organizations of medical care of appropriate quality with mandatory control of its cost. Treatment outcomes that are important to the patient become no less significant than clinical performance indicators and payment for medical services, regardless of the profile of medical care. The gradual change in paradigms of healthcare systems from a paternalistic to a person-centric model required changes in organizational, legislative and financial approaches when introducing health-saving healthcare technologies. Purpose of the study: analysis of the current organizational, legal, financial and clinical models of surgical treatment of patients with age-related cataracts, astigmatism and development of proposals for the implementation of the patient’s right to choose intraocular lenses, taking into account his modern expectations from the results of treatment. Materials and methods. Statistical and analytical methods were used (content analysis methods, expert assessment methods, analysis and synthesis methods). Results. An analysis of the legislation in organizing the provision and financing of medical care to the adult population in the field of ophthalmology is presented, and state guarantees for the use of medical products – types of intraocular lenses implanted into the human body for the surgical treatment of senile cataracts and astigmatism – are considered. Clinical models of the disease are systematized, taking into account the frequency and frequency of provision of medical services and the list of medical devices implanted into the human body, professional, medico-economic, medico-legal and reputational risks are described when exercising the patient’s right to choose intraocular lenses in the treatment of ophthalmological pathology. Proposals have been developed to change clinical recommendations, standards of medical care for senile cataracts and astigmatism, and improve payment for ophthalmological care. Conclusions. The transition to value-based healthcare requires the consolidation of the efforts of all structures of the healthcare industry to achieve the best results in the treatment of ophthalmic diseases and increase the clinical effectiveness associated with the choice of intraocular lenses in the surgical treatment of adults in the field of ophthalmology.

Evaluation of silk industrial heritage value based on IAHP, D-S theory and mixed decision model: the case of Hangzhou-Jiaxing-Huzhou in China

ABSTRACT A comprehensive understanding of the diverse value of industrial heritage is a prerequisite for preservation and reuse. After studying the composition and evaluation methods of the value of world cultural heritage, this paper puts forward a mixed decision model based on the combination of interval analytic hierarchy process, expert clustering ranking weighting method, fuzzy set and D-S theory. Firstly, an evaluation system that can describe the value of modern silk industry heritage in Hangzhou-Jiaxing-Huzhou area is established, which reflects comprehensiveness and particularity. Then, the interval analytic hierarchy process and expert clustering ranking method are proposed to calculate the weight of various indicators in the evaluation system, which can effectively reduce the influence of subjective experience and extreme experts on group decision-making. In addition, the fuzzy set theory and D-S theory are used to calculate the protection grades of several modern silk industrial heritages, and compared with the actual protection grades recognized by the state, which verifies the scientificity and effectiveness of the mixed decision-making model. Finally, the results show that the mixed decision model can accurately calculate the protection level consistent with the reality, demonstrating high feasibility and providing new ideas for the future evaluation of industrial heritage values.

A - 146 Psychiatric Drugs Can Precipitate Neuropsychological Predicates of Homicide

Abstract Objective A man inexplicably killed his beloved wife. He had no history of violence, was a prominent member of the community, and gave no indications of the impending horrific act. He had been recently commenced treatment with psychiatric drugs, and his condition deteriorated, culminating in homicide. After his incarceration, he stopped taking psychiatric drugs and his mental health improved. Many practitioners are not aware that psychiatric drugs can create a risk for violence - or precursors of violence - such as anger, hostility, and agitation. This risk is often described on the product label. Method The subject was an intensive care nurse who became exhausted and despondent serving long hours during the Covid epidemic, when many of his patients were put on ventilators and died. He had suffered panic attacks from his difficulty breathing through the respiratory masks. He temporarily left employment and sought psychiatric assistance for his professional “burn-out” condition. After three doses of venlafaxine, he reported side effects including increased anxiety, blood pressure and heart rate. He was then prescribed escitalopram without tapering of the venlafaxine. As his anxiety progressed, he was prescribed escitalopram once daily and buspirone three times daily, yet he continued to deteriorate until the homicide. Results Expert genetic analysis found susceptibility to the psychiatric drugs prescribed. The neuropsychological evaluation, months post-homicide, found excellent neuropsychological function, although psychomotor and processing speed was deficit. Personality testing found no disorders, with a profile inconsistent with violent behavior. Conclusions Prescribers need to monitor patients carefully for potentially adverse and violent outcomes of treatment.

The history of the great migration: Movement to the urban north (1916-1970) and its cultural, social, and political impact

The main purpose of the article is to conduct a historical analysis of the extensive migration that took place during 1916-1970. The object of the study is the cultural, social and political effect of this phenomenon. The methodology of the study involves the use of historical analysis methods, methods of systematization of available historical information, the method of expert analysis, the method of hierarchical analysis and the method of pair comparison. As a result of the study, key cultural, social and political factors that influenced the process of formation of large migration in the period 1916-1970 were identified through the conducted expert historians. A model of the hierarchical influence of these factors on the formation and development of migration processes is presented. The study has a limitation and takes into account only a specific period in history. At the same time, in further studies, a significant scientific emphasis should be placed on economic factors.

Evaluation of an automated laminar cartilage T2 relaxation time analysis method in an early osteoarthritis model.

A fully automated laminar cartilage composition (MRI-based T2) analysis method was technically and clinically validated by comparing radiographically normal knees with (CL-JSN) and without contra-lateral joint space narrowing or other signs of radiographic osteoarthritis (OA, CL-noROA). 2D U-Nets were trained from manually segmented femorotibial cartilages (n = 72) from all 7 echoes (AllE), or from the 1st echo only (1stE) of multi-echo-spin-echo (MESE) MRIs acquired by the Osteoarthritis Initiative (OAI). Because of its greater accuracy, only the AllE U-Net was then applied to knees from the OAI healthy reference cohort (n = 10), CL-JSN (n = 39), and (1:1) matched CL-noROA knees (n = 39) that all had manual expert segmentation, and to 982 non-matched CL-noROA knees without expert segmentation. The agreement (Dice similarity coefficient) between automated vs. manual expert cartilage segmentation was between 0.82 ± 0.05/0.79 ± 0.06 (AllE/1stE) and 0.88 ± 0.03/0.88 ± 0.03 (AllE/1stE) across femorotibial cartilage plates. The deviation between automated vs. manually derived laminar T2 reached up to - 2.2 ± 2.6ms/ + 4.1 ± 10.2ms (AllE/1stE). The AllE U-Net showed a similar sensitivity to cross-sectional laminar T2 differences between CL-JSN and CL-noROA knees in the matched (Cohen's D ≤ 0.54) and the non-matched (D ≤ 0.54) comparison as the matched manual analyses (D ≤ 0.48). Longitudinally, the AllE U-Net also showed a similar sensitivity to CL-JSN vs. CS-noROA differences in the matched (D ≤ 0.51) and the non-matched (D ≤ 0.43) comparison as matched manual analyses (D ≤ 0.41). The fully automated T2 analysis showed a high agreement, acceptable accuracy, and similar sensitivity to cross-sectional and longitudinal laminar T2 differences in an early OA model, compared with manual expert analysis. Clinicaltrials.gov identification: NCT00080171.

Inferring cancer type-specific patterns of metastatic spread.

The metastatic spread of a cancer can be reconstructed from DNA sequencing of primary and metastatic tumours, but doing so requires solving a challenging combinatorial optimization problem. This problem often has multiple solutions that cannot be distinguished based on current maximum parsimony principles alone. Current algorithms use ad hoc criteria to select among these solutions, and decide, a priori, what patterns of metastatic spread are more likely, which is itself a key question posed by studies of metastasis seeking to use these tools. Here we introduce Metient, a freely available open-source tool which proposes multiple possible hypotheses of metastatic spread in a cohort of patients and rescores these hypotheses using independent data on genetic distance of metastasizing clones and organotropism. Metient is more accurate and is up to 50x faster than current state-of-the-art. Given a cohort of patients, Metient can calibrate its parsimony criteria, thereby identifying shared patterns of metastatic dissemination in the cohort. Reanalyzing metastasis in 169 patients based on 490 tumors, Metient automatically identifies cancer type-specific trends of metastatic dissemination in melanoma, high-risk neuroblastoma and non-small cell lung cancer. Metient's reconstructions usually agree with semi-manual expert analysis, however, in many patients, Metient identifies more plausible migration histories than experts, and further finds that polyclonal seeding of metastases is more common than previously reported. By removing the need for hard constraints on what patterns of metastatic spread are most likely, Metient introduces a way to further our understanding of cancer type-specific metastatic spread.

From CFOs to crypto: exploratory study unraveling factors in corporate adoption

Cryptocurrency adoption has gained significant attention across various fields owing to its disruptive potential and associated challenges. However, companies' adoption of cryptocurrencies remains relatively low. This study aims to comprehensively examine the factors influencing cryptocurrency adoption, their interrelationships, and their relative importance. To achieve this objective, we employ a Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach coupled with network analysis tools. By adopting a practical approach rather than a purely theoretical one, our unique contribution lies in the valuable insights derived from experienced Chief Financial Officers (CFOs) of various companies with experience in both traditional finance and cryptocurrencies. Furthermore, the unique blend of analytical rigor and industry expertise supports the study's relevance, offering nuanced insights that are not only academically robust but also immediately applicable in the corporate landscape. Our findings highlight the paramount importance of safety in transactions and trust in the chosen platform for companies considering cryptocurrency adoption. Additionally, criteria such as faster transactions without geographical limitations, lower transaction fees, seamless integration with existing systems, and potential cost savings are identified as crucial drivers. Both the DEMATEL approach and network analysis reveal strong interconnections among the criteria, emphasizing their interdependence and, notably, their reliance on transactional safety. Furthermore, our causes and effects analysis indicates that CFOs perceive company-led cryptocurrency adoption to positively impact the broader cryptocurrency market.

Infantry Weapon Systems Used by Special Operations Forces to Carry Out Assigned Missions

Abstract Special Operations Forces (SOF) operate in dynamic, challenging environments, requiring accurate and versatile infantry weapon systems to effectively perform their assigned missions. This article provides a comprehensive review of the diverse range of infantry weapon systems used by SOF units in different theatres of operations. Through a synthesis of empirical data, operational perspectives and expert analysis, the study aims to elucidate the critical role of specialised weaponry in increasing the success rate of SOF missions. The analysis covers a broad spectrum of weapon platforms, each tailored to meet distinct mission requirements. In addition, the article explores the integration of advanced technologies into weapon construction, such as high-performance optical systems, silencers and other modular accessories, which enhance the lethality, accuracy and stealth capabilities of special forces units.

MANAGING HUMAN RESOURCES IN CONDUCTING FOREIGN ECONOMIC ACTIVITIES: ENSURING FINANCIAL SECURITY IN TOURISM INDUSTRY ENTERPRISES

Within the scope of this article, it is proposed to evaluate human resource management in the context of ensuring financial security at tourism industry enterprises. Accordingly, it is noted that the object of study is the human resource management system and the financial security system. The task is to present a methodological approach that, through surveying, calculating an integral indicator, and evaluating the most significant components, can effectively assess the level of human resource management in tourism enterprises. For this purpose, the methodology adopts several methods including expert analysis and integral evaluation. It is proven that the formation of an appropriate group of indicators and their subsequent grouping will facilitate an effective reflection of a single integral indicator for evaluating human resource management in the context of ensuring financial security at tourism industry enterprises. It is established that tourism industry enterprises are highly active in foreign economic activities, and in this context, the issue of financial security and management systems plays a paramount role. As a result, a group of experts and tourism industry enterprises were selected. The most significant indicators were distinguished and the corresponding calculations were conducted. As a result, it was established that a significant number of tourism industry enterprises fall short of a high level of human resource management, which poses a direct threat to their financial security during foreign economic activities. The presented process of evaluating human resource management in the context of ensuring financial security at tourism industry enterprises may find its practical application in the context of the activities of key security subjects. Limitations include not considering all possible indicators and focusing only on one industry, specifically the tourism industry.

Modern environmental, economic, and legal challenges of tourism enterprises

Choosing the best strategy for the functioning of a tourism enterprise is a considerable factor that affects its safety and development. Such choices depend on a considerable number of variables, including environmental, economic, and legal challenges, which are exacerbated by the hyper-dynamic environment. The purpose of this study was to develop a methodical approach to evaluating the strategies of functioning of a tourism enterprise. The key research methods were the expert analysis method, which helped to determine the impact of certain challenges, and the BOCR method, which formed the basis for modelling. The study created a model for evaluating the proposed two variants for the strategy of functioning of a tourism enterprise according to the four BOCR criteria: positive effects, costs, opportunities, and risks of environmental, economic, and legal nature. Thus, it was possible to create a basis for building an information framework for the development and implementation of an optimised strategy that will satisfy all the environmental, economic, and legal needs of the modern tourism industry. It was found that martial law in Ukraine leads to an increase in the dynamism of the external environment, wherein an adaptive approach allows such open socio- economic systems as modern tourism enterprises to function safely. The study found that the best strategy for tourism enterprises as of 2024 is a dynamic adaptive one, which involves dynamic actions and allocation of own resources for the development of domestic tourism with the expansion of international corporate cooperation and partnership. The study described how the proposed strategy of operation affects the legal security of tourism enterprises. The practical value and significance of the findings obtained is that the proposed methodological approach to assessing the strategies of functioning of a tourism enterprise can be used by the subjects of both economic and legal security, which include the management of the enterprises themselves and persons making managerial decisions in the field of ensuring their security

Detecting APS failures using LSTM-AE and anomaly transformer enhanced with human expert analysis

This study develops a novel semi-supervised approach for detecting Air Pressure System (APS) failures in Heavy-Duty Vehicles (HDVs) by exploiting two modern Machine Learning (ML) models: Long Short-Term Memory Autoencoder (LSTM-AE) and Transformer for Anomaly Detection (TranAD), and enhancing their performance with human expertise. To tackle the failure detection problem, a dataset comprising 30 days of operational time-series data from 110 healthy vehicles with no recorded APS issues and 30 vehicles that experienced APS failures requiring road assistance was acquired. Several preprocessing steps are proposed and three key features are extracted as APS health indicators. These features are then utilized both in human expert analysis (HEA) and training of ML models. When compared to HEA, both LSTM-AE and TranAD models exhibit superior performance individually in APS failure detection, achieving F1 scores of 0.75 and 0.79 respectively, and the same accuracy of 91.4%. Further, the integration of HEA with those ML models enhances model effectiveness in all experimental results, especially in reducing false alarms that cause customer dissatisfaction. The TranAD model combined with human expert analysis achieved the best performance with an unprecedented 0.82 F1 score and 92.8% accuracy. In addition to presenting a new methodology for failure detection, this paper suggests a way for more efficient and reliable predictive maintenance practices for HDVs.

Can enhanced CSR quality reduce the cost of debt capital? An empirical analysis of CEO expertise and non-financial reporting practices in China

This study aims to investigate whether stockholders and creditors place a positive value on corporate social responsibility (CSR) information disclosure when making decisions about providing financing to firms, thereby influencing their investment choices. Utilizing data from the China Stock Market & Accounting Research Database (CSMAR) and HEXUN, the study analyzes CSR disclosures and financial data of 7,123 firm-year observations of A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2012 to 2020. A comprehensive methodology involving regression analysis was applied to assess the relationship between CSR quality and the cost of debt capital. Various robustness tests, including different model specifications and alternative variable measurements, were conducted to ensure the reliability and validity of the findings. The results obtained indicate that higher CSR quality significantly correlates with a lower cost of debt capital, supporting the hypothesis that improved CSR disclosure reduces perceived credit risk. However, CEO financial expertise shows a significantly positive relationship with the cost of debt capital. Furthermore, the study reveals that CSR assurance and engagement with Big 4 accounting firms do not noticeably affect the price of debt capital, whereas mandatory CSR reporting does. The findings underscore the importance of CSR quality in financial decision-making, offering valuable insights. AcknowledgmentThis paper is co-funded by the European Union through the European Education and Culture Executive Agency (EACEA) within the project “EU Best Practice of Life Cycle Assessment, Social, Environmental Accounting and Sustainability Reporting” – 101047667-ERASMUS-JMO-2021-MODULE https://jm.snau.edu.ua/en/eu-best-practice-of-life-cycle-assessment-social-environmental-accounting-and-sustainability-reporting/ Oleh Pasko expresses sincere gratitude for the support from the Kirkland Research Program, generously provided by the Leaders of Change Foundation established by the Polish-American Freedom Foundation.

Spatial Immunophenotyping from Whole-Slide Multiplexed Tissue Imaging Using Convolutional Neural Networks.

The multiplexed immunofluorescence (mIF) platform enables biomarker discovery through the simultaneous detection of multiple markers on a single tissue slide, offering detailed insights into intratumor heterogeneity and the tumor-immune microenvironment at spatially resolved single cell resolution. However, current mIF image analyses are labor-intensive, requiring specialized pathology expertise which limits their scalability and clinical application. To address this challenge, we developed CellGate, a deep-learning (DL) computational pipeline that provides streamlined, end-to-end whole-slide mIF image analysis including nuclei detection, cell segmentation, cell classification, and combined immuno-phenotyping across stacked images. The model was trained on over 750,000 single cell images from 34 melanomas in a retrospective cohort of patients using whole tissue sections stained for CD3, CD8, CD68, CK-SOX10, PD-1, PD-L1, and FOXP3 with manual gating and extensive pathology review. When tested on new whole mIF slides, the model demonstrated high precision-recall AUC. Further validation on whole-slide mIF images of 9 primary melanomas from an independent cohort confirmed that CellGate can reproduce expert pathology analysis with high accuracy. We show that spatial immuno-phenotyping results using CellGate provide deep insights into the immune cell topography and differences in T cell functional states and interactions with tumor cells in patients with distinct histopathology and clinical characteristics. This pipeline offers a fully automated and parallelizable computing process with substantially improved consistency for cell type classification across images, potentially enabling high throughput whole-slide mIF tissue image analysis for large-scale clinical and research applications.