bluuebunny/crossref_metadata_2025 huggingface dataset:
Interactive Effect of Nano Chitosan and Soil Mulching on Salt Affected Soil Characteristics and Phaseolus vulgaris L. Productivity
Authors: Abdel- Kader Nasser , Elbagory Mohssen , Ahmed Mohamed E. , Saber Esraa , Omara Alaa El-Dein , Khalifa Tamer H.
Published: December 2023

Soil salinity is seen as a major restriction for crop production, and with water scarcity this problem becomes more complicated. Mulching is crucial to salinity dynamics management by decreasing evaporation with improving the soil’s characteristics. Using chitosan as an eco-friendly biostimulant can enhance plant defense genes during different abiotic stresses. Recently, agricultural research has recognized nanoparticles as a pioneer material due to their distinctive physicochemical features. Therefore, a lysimeter experiment was conducted to investigate the interactive effects of mulching (UNM: un-mulched, WPM: white plastic, RSM: rice straw and SDM: sawdust) and chitosan foliar application (Ch0: control, Ch1: 250 mg chitosan L-1, Ch2: 125 mg nano chitosan L-1, and Ch3: 62.5 mg nano chitosan L-1) on the biochemical soil characteristics and common beans productivity under salt affected soil conditions. Organic mulching (RSM and SDM) treatments significantly improved the soil's organic carbon, available nutrient content, and total count of bacteria. WPM treatment lowered soil EC to 6.63 dS m-1 and increased soil water content to 34.13%. The application of Ch3 caused considerable increases in the plant height, shoot dry weight, root dry weight, grain yield, and nutrient content in the seed. The total fungi count in the soil and Na% in the seed was significantly decreased due to chitosan foliar applications. Moreover, the interactive effect of different mulch materials plus foliar by chitosan applications gave a statistically similar seed yield in both seasons. Overall, this study revealed the potential of the mulching treatments and foliar application of nano chitosan in improved biochemical soil characteristics and common bean productivity under saline soil conditions.
Diagnosis of Parkinson’s Disease Using Convolutional Neural Network by Hand Drawing Images
Authors: Afandi Moh , Ardhianto Peter , Lin Jun-Dai
Published: December 2023

Neurodegenerative illnesses, such as Parkinson’s disease (PD), have a substantial impact on the overall well-being of those who are affected. This study investigates and contrasts the capabilities of convolutional neural networks (CNN) in detecting Parkinson’s disease (PD) by utilising hand-drawn images alongside wave and spiral images as input data. This study employs pre-trained CNN models, specifically MobileNet, ResNet50, EfficientNet-B1, and InceptionV3, to classify Parkinson’s disease (PD). The findings demonstrate that MobileNet surpasses other architectural designs, as evidenced by the F1-Score of the four classes: Spiral Normal (0.87), Spiral Parkinson (0.86), Wave Normal (0.97), and Wave Parkinson (0.97). MobileNet has also shown a remarkable accuracy of 0.92 in diagnosing Parkinson’s disease. The result demonstrates the efficacy of MobileNet in extracting features from images. The results of this study enhance the application of deep learning methods in the early detection of PD, as well as help indicate the effectiveness of patient therapy and exercise, promising better patient outcomes through timely intervention and treatment.
Dietary Serine Supplementation Improves Growth Performance, Meat Quality, and Composition of Gut Microbes and Metabolites in Growing‐Finishing Pigs
Authors: Yiting Guo , Fang He , Zhiying Deng , Jie Yin , Guiping Guan , Zhengjun Xie , Xihong Zhou
Published: December 2023

Serine is widely involved in antioxidant synthesis, immune response, and fat metabolism. However, it remains unclear whether dietary serine supplementation affects fat deposition in the skeletal muscles of pigs. Thus, we explored the effects of dietary serine supplementation on growth performance, meat quality, and composition of gut microbes and their metabolites in growing-finishing pigs. Forty-eight boars weighing approximately 20 kg were fed either a basal diet or a basal diet supplemented with 0.15% serine. The results showed that dietary serine increased the daily weight gain and improved the antioxidant ability of pigs, as indicated by the decreased malondialdehyde content and increased glutathione and superoxide dismutase content. Pigs supplemented with serine had better meat quality, as shown by the lower drip loss and higher IMF content. Furthermore, dietary serine increased the relative abundance of Streptococcus and Lactobacillus and decreased the relative abundance of Clostridium_sensu_stricto_1 and Terrisporobacter. Differential microbial metabolites were mostly enriched in metabolic pathways related to lipid synthesis, such as alpha-linolenic acid metabolism and steroid hormone biosynthesis. Correlation analysis showed that the altered metabolites were closely related to the intestinal microbiota. In conclusion, our results suggested that serine serves as a potential additive for improving meat quality in growing-finishing pigs.
A New Sequential Statistical Test Procedure from Observation Differences for Geodetic Deformation Analysis
Authors: Matsuoka Marcelo , Rofatto Vinicius , Assunção Jhonatta , Silva Lincon , Klein Ivandro , Camargo Paulo
Published: December 2023

One of the main challenges in geodetic deformation analysis is to infer whether the geometry of some engineering structures or zones of natural hazards has changed from their initial state or not. The pillar that supports such an analysis is tightly based on the fundamentals of statistical hypothesis testing. The null hypothesis model indicates that no displacement has occurred. It is tested against a class of alternative models, which stipulate different displacement patterns. In this contribution, we present an innovative geodetic displacement detection which integrates combinatorial analysis and likelihood ratio tests into a sequential procedure for the case where the differences between observations of two epochs are in play. This framework is applied and investigated to two test scenarios: a synthetic and a real simulated trilateration network. From a statistical point of view, our approach is rigorous, because the alternative model can identify simultaneously more than one unstable point. In addition, the relationship between the unknown parameters and the observations is always linear, even if the problem manifests itself as non-linear. Consequently, we avoid a potential loss of statistical test power due to the model linearization. In addition, the proposed method controls the false positive rate efficiently. One of the problems that arise here is also related to the selection of the maximum number of points to be considered in the test procedure ( ). Here, we provide an innovative methodology based on rank computation of the design matrices to define , which can even be extended to the problem of outlier detection. Determining avoids the problem of having non-separable models in identifying unstable points. The algorithms and data are available in the repository.
Decoding Financial Futures: The Power of Numerical Indicators in Predicting Bankruptcy
Authors: Billios Dimitris , Seretidou Dimitra , Stavropoulos Antonios
Published: December 2023

The review aims to examine how well numerical indicators of business bankruptcy can predict outcomes. The paper examines ten critical studies that concentrate on statistical models for bankruptcy predictions utilizing PRISMA criteria. The findings highlight the usefulness of numerical indicators in indicating financial hardship, particularly cash flow ratios. In order to connect theoretical knowledge with real-world corporate strategy applications, the study ends by reaffirming the importance of these indicators in strategic decision-making.
Pharmacokinetic and Pharmacodynamic Analysis Using Monte Carlo Simulation of the Oxacephem Antibiotic Flomoxef against Extended-Spectrum β-Lactamase-Producing Enterobacterales from Dogs
Authors: Kusumoto Mizuki , Jitsuiki Makoto , Motegi Tomoki , Harada Kazuki
Published: December 2023

Flomoxef (FMX) may be a potential alternative to carbapenems for dogs infected with Enterobacterales producing extended-spectrum β-lactamase (ESBL-E). However, the appropriate dosage of FMX in dogs with ESBL-E infections has yet to be established. This study was carried out to establish appropriate treatment regimens for FMX against ESBL-E infections in dogs by a pharmacokinetics–pharmacodynamics (PK–PD) approach. Five dogs received an intravenous bolus dose of FMX (40 mg/kg). Serum FMX concentrations were evaluated using high-performance liquid chromatography-tandem mass spectrometry, and PK indices were determined based on non-compartmental model. The cumulative fraction of response (CFR) was calculated based on the distribution of minimum inhibitory concentrations among wild-type ESBL-E from companion animals. As the results, the dosage regimens of 40 mg/kg q8h and q6h were estimated to achieve a CFR of >90% for wild-type isolates of ESBL-producing Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis for dogs. In contrast, all regimens exhibited a CFR of <80% for ESBL-producing Enterobacter cloacae. Our results indicated that dosage regimens of 40 mg/kg FMX q8h and q6h can be a non-carbapenem treatment for dogs infected with ESBL-producing isolates of Escherichia coli, Klebsiella pneumoniae, and Proteus mirabilis, but not for those infected with ESBL-producing Enterobacter cloacae.
Prevalence and Risk Factors of Human Taenia solium Cysticercosis in Mbulu District, Northern Tanzania
Authors: Bandi Vedasto , Ngowi Bernard , Mpolya Emmanuel , Kilale Andrew Martin , Vianney John-Mary
Published: December 2023

Background: Taeniasis and cysticercosis are human infections caused by the pork tapeworm, Taenia solium. This study is a baseline for the Community-based intervention. We determined the prevalence of human cysticercosis and associated risk factors following deworming program conducted throughout the country, Mbulu District being among the districts in Northern Tanzania.Methods: Human cysticercosis was determined by enzyme-linked Immunosorbent assay (Ag- ELISA). Household interviews and observations were conducted to identify risk factors for cysticercosis transmissions among households and communities. Results: Three hundred individuals participated in the study. The age ranged from five to 89 years, with a median of 19 years. The prevalence of human cysticercosis was 23(7.67%). The prevalence was high 6(11.76%) among individuals aged 26 to 35 years and ±45 years. There was no statistically significant difference in the prevalence by age group, sex, or occupation. Among the 300 participants, 82(27.3%) had received anthelmintic during the previous year; among these, 5(21.7%) were infected. The likelihood of infection was low among anthelmintic users by 28% [0.72 (0.26-2.01)], but the protection was not significant. The communities differed in risk factors on the availability of clean and safe water supply; 52.7% (46/86) of households visited had no pit latrine. The cysticercosis prevalence showed a significant difference by communities. Conclusion: The prevalence of human cysticercosis was high and associated with higher age groups. The prevalence was low among those who had taken anthelmintic and was associated with lower age groups. The school current school deworming program has a positive effect for school children meanwhile the elderly are at higher risk because the intervention did not target them. It is recommended to scale up anthelmintic intervention to higher age groups.
Numerical Simulation of Flow around a Pitching Airfoil with Combined Morphing Leading Edge and Trailing Edge Wing
Authors: Bashir Musavir , Negahban Mir Hossein , Botez Ruxandra Mihaela , Wong Tony
Published: December 2023

An integrated approach to active flow control is proposed by finding both the drooping leading edge and the morphing trailing edge for flow management. This strategy aims to manage flow separation control by utilizing the synergistic effects of both control mechanisms, which we call the Combined Morphing Leading Edge and Trailing Edge (CoMpLETE) technique. This design is inspired by a bionic porpoise nose and the flap movements of the cetacean species. The motion of this mechanism achieves a continuous, wave-like, variable airfoil camber. The dynamic motion of the airfoil's upper and lower surface coordinates in response to unsteady conditions is achieved by combining the thickness-to-chord (t/c) distribution with the time-dependent camber line equation. A parameterization model was constructed to mimic the motion around the morphing airfoil at various deflection amplitudes at stall angle of attack and morphing actuation start times. The mean properties and qualitative trends of the flow phenomena are captured by the transition-SST (Shear Stress Transport) model. The effectiveness of the dynamically morphing airfoil as a flow control approach is evaluated by obtaining the flow field data, such as velocity streamlines, vorticity contours, and aerodynamic forces. Different cases are investigated for the CoMpLETE morphing airfoil, which evaluates the airfoil’s parameters, such as its morphing location, deflection amplitude, and morphing starting time. The morphing airfoil’s performance is analyzed to provide further insights into the dynamic lift and drag force variations at pre-defined deflection frequencies of 0.5 Hz, 1 Hz, and 2 Hz. The findings demonstrate that adjusting the airfoil camber reduces streamwise adverse pressure gradients, thus preventing significant flow separation. Although the trailing edge deflection and its location along the chord influence the generation and separation of the Leading-Edge Vortex (LEV), these results show that the combined effect of the morphing leading edge and trailing edge has the potential to mitigate flow separation. The morphing airfoil successfully contributes to the flow reattachment and significantly increases the maximum lift coefficient (c_(l,max))). This work also broadens its focus to investigate the aerodynamic effects of a dynamically morphing leading and trailing edge, which seamlessly transitions along the side edges. The aerodynamic performance analysis is investigated across varying morphing frequencies, amplitudes, and actuation times.
Automorphism Group of Polyhedral Graphs
Authors: Ghorbani Modjtaba , Alidehi-Ravandi Razie , Dehmer Matthias
Published: December 2023

Symmetry, as a key concept in geometry and the foundational principle of mathematical concepts, is a fundamental part of geometry and nature, creating patterns that help us conceptually organize our world. It is often linked with aesthetic beauty and can be observed in both natural phenomena and human-made objects, such as artworks and manufactured products, across the globe. The automorphism group of a graph is a mathematical structure that captures all the symmetries of the graph. symmetry refers to the property of a graph, indicating that it can be transformed without changing its structure, while the automorphism group is the collection of all permutations of the vertices that preserve the graph's adjacency relationships. In graph theory, the concepts of symmetry group and automorphism group play fundamental roles in understanding the symmetries and structural properties of graphs. This paper aims to explore the relationship between symmetry groups and automorphism groups, shedding light on their interconnected nature and their significance in graph theory. We delve into the definitions and properties of both symmetry groups and automorphism groups, highlighting their similarities and distinctions. Furthermore, we discuss their applications in various fields, including computer science, chemistry, and network analysis. Through this exploration, we aim to provide a comprehensive understanding of the relationship between symmetry groups and automorphism groups, deepening our comprehension of the symmetries and structures inherent in graphs.
Pain or Pressure? Delineating between Primary and Secondary Headache
Authors: Davis Jr. Vernon , Desai Dev , Malafi Maria Eleni
Published: December 2023

Headache is considered to be one of the most common causes of medical treatment and evaluation worldwide in both acute and outpatient settings. It is the most common neurological symptom seen worldwide affecting all genders, ages, ethnicities, and socioeconomic levels. It’s impact is noted in educational decline in school-aged children and decreased productivity through sick leave in adults. Its overall burden is well documented in well-resourced countries but limited data is seen low resourced countries. While many underlying causes bring about secondary headaches, primary headaches and more specifically migraines have been more widely explored. Migraines have a distinct criterion that is inclusive of one day duration (4 hours to 7 days, unilateral distribution, nausea and vomiting and disability as a few examples. However, migraines can vary and proper documentation through a migraine diary can help to guide treatment. Management of migraines can vary. Lifestyle modification is a key factor in the overall prevention and reduction of triggers in migraines. In addition to this, pharmacotherapy can be given in a tier-based approach based on overall severity and frequency of the migraine. Interventions have progressed from botox injection and have seen the advent of new medications such as nasal sprays to novel formulations of pre-existing drug formulations. Nonetheless, there is great room for further studies of headaches and migraines. Research specifically in low-resource countries can prove to beneficial.
Modelling and Measuring Trust in Human-Robot Collaboration
Authors: Loizaga Erlantz , Bastida Leire , Sillaurren Sara , Moya Ana , Toledo Nerea
Published: December 2023

Recognizing trust as a pivotal element for success within Human-Robot Collaboration (HRC) environments, this article examines its nature, exploring the different dimensions of trust, analysing the factors affecting each of them, and proposing alternatives for trust measurement. To do so, we designed an experimental procedure involving 50 participants interacting with a modified 'Inspector game' while we monitor their brain, electrodermal, respiratory, and ocular activities. This procedure allowed us to map dispositional (static individual baseline) and learned (dynamic, based on prior interactions) dimensions of trust considering both demographic and psychophysiological aspects. Our findings challenge traditional assumptions regarding the dispositional dimension of trust and establish clear evidence that the first interactions are critical for the trust-building process and the temporal evolution of trust. By identifying more significant psychophysiological features for trust detection and underscoring the importance of individualized trust assessment, this research contributes to understanding the nature of trust in HRC. Such insights are crucial for enabling more seamless human-robot interaction in collaborative environments.
Beyond Traditional Assessment: A Fuzzy Logic-Infused Hybrid Approach to Equitable Proficiency Evaluation via Online Practice Tests
Authors: Glushkova Todorka , Ivanova Vanya Angelova , Zlatanov Boyan
Published: December 2023

This article presents a hybrid approach to assessing students’ foreign language proficiency in a cyber-physical educational environment. It focuses on the advantages of integrated assessment of student knowledge by considering the impact of automatic assessment, learners’ independent work, and their achievements to date. An assessment approach is described using the mathematical theory of fuzzy functions, which are employed to ensure fair evaluation of students. The largest possible number of students, whose re-evaluation of test results will not affect the overall performance of the student group, is automatically determined. The study also models the assessment process in the cyber-physical educational environment through the formal semantics of calculus of context-aware ambients (CCA).
Research on the Wood Density Measurement in Standing Trees though the Micro Drilling Resistance Method
Authors: Yao Jianfeng , Zhao Yabin , Lu Jun , Liu Hengyuan , Wu Zhenyang , Song Xinyu , Li Zhuofan
Published: December 2023

To achieve a micro-destructive and rapid measurement of the wood density of standing trees, this study investigated the feasibility of using the micro-drilling resistance method, formulated a mathematical model, explored the potential for a unified model across multiple tree species, and analyzed the influence of moisture content on measurement accuracy. First, 231 tree cores and drill resistance data were sampled from Pinus massoniana, Cunninghamia lanceolate, and Cryptomeria fortunei. The basic density and moisture content of each core were measured, and the average value of each resistance data record was calculated. Second, the average drill resistance, the natural logarithm of average drill resistance, and absolute moisture content were used as independent variables, while the wood basic density was used as the dependent variable. Third, the total model of the three tree species and sub-model for each tree species were established through a stepwise regression method. Finally, the accuracy of each model was compared and analyzed with that of using the average basic density of each tree species as an estimated density. The results revealed that the estimation accuracy of the sub-model for each tree species was 1.670 percentage points higher than the average value of each tree species used as the density estimation value for these tree species. Additionally, except for Cryptomeria fortunei, the natural logarithm of drill resistance significantly influenced the wood density model at a significance level of 0.05. Moreover, moisture content significantly affected the total model and sub-models of Pinus massoniana at a significance level of 0.05. The estimation accuracy of the total mathematical model was 2.125 percentage points lower than that achieved using the average basic density of each tree species to predict their density. The results indicated the feasibility of using the micro-drilling resistance method to measure the wood density of standing trees. Moreover, the relationship between wood density and drill resistance did not follow a linear pattern, and moisture content slightly influenced the drill needle resistance. Furthermore, the establishment of a mathematical model for each tree species was deemed essential. This study provides valuable guidance for measuring the wood density of standing trees through the micro-drilling resistance method.
Riboflavin or Ascorbic Acid Enhances Wheat Drought Tolerance by Improving Both Yield and Water Productivity
Authors: Abdelhalim Abdelhady Kh. , Sallam A. A. , Waleed Fares , Merah Othmane , Abdelhamid And Magdi T.
Published: December 2023

Wheat is widely grown in the Mediterranean region, where plants frequently face water shortages. Recently, more attention to rationalizing irrigation water has been increased due to the adoption of sustainable agricultural systems. Therefore, two field trials were conducted at the Agriculture Research Station of Nubaria, Egypt, in two consecutive seasons (2017/2018 and 2018/2019) to examine three irrigation regimes' effects, i.e., 60, 80, and 100% of crop evapotranspiration (ETc) combined with foliar ascorbic acid (AsA) or vitamin B2 (VB2) on yield and water productivity of wheat in two separate experiments. A split-plot design was used with three replicates. Irrigation treatments occupied the main plots, while the subplot in the first experiment was placed by ascorbic acid (AsA) and vitamin B2 in the second experiment. Results indicated that 100% ETc produced higher wheat yield and its attributes and insignificantly surpassed 80% ETc. Compared to the unsprayed plots, the foliar application of 6 mM ascorbic acid or 2.0 mM vitamin B2 significantly increased grain yield, components, and water use efficiency. The interaction between irrigation regimes (100% ETc or 80% ETc) and foliar application of 6.0 mM ascorbic acid or 2.0 mM vitamin B2 resulted in the highest values with no significant difference. Foliar application of ascorbic acid or vitamin B2 saved 20% of irrigation water while yielding a reduction that did not exceed 10%. The biplot graph of treatments x traits (TT) was a useful statistical tool for examining the impact of treatments on yield and its characteristics and identifying the links between these factors. Results suggest that riboflavin or ascorbic acid may have a potential role as an effective antioxidant for enhancing the tolerance for drought stress in wheat.
Quasi-gasodynamic heterogeneous model for describing a mixture of compressible fluids. One-dimensional case
Authors: Khaytaliev Ismatolo Ramazanovich , Shilnikov Evgeny Vladimirovich , Elizarova Tatiana Gennadyevna
Published: December 2023

Quasi-gasdynamic type regularization is presented for a heterogeneous model of a two-fluid mixture of compressible fluids. This model allows to describe the flows of stiffened gases. The reduced four-equation model for dynamics of the heterogeneous compressible two-fluid mixture with equations of state of a stiffened gas is considered. A further reduced form of this model with the excluded volume concentrations and a quadratic equation for the common pressure of the components can be called a quasi-homogeneous form. A finite difference algorithm is used, built with the finite volume method. Using examples of solving typical one-dimensional problems, it is shown that the presented algorithm is a stable and reliable way to model problems with strong shock waves.
An Illustration of a Latent Class Analysis for Interrater Agreement: Identifying Subpopulations with Different Agreement Levels
Authors: ALAGÖZ Ömer Emre Can , GÜRLÜK Yılmaz Orhun , KORMAZ Mediha , CÖMERT Gizem
Published: December 2023

This study proposes a latent class analysis (LCA) approach to investigate interrater agreement based on rating patterns. LCA identifies which subjects are rated similarly or differently by raters, providing a new perspective for investigating agreement. Using an empirical dataset of parents and teachers evaluating pupils, the study found two latent classes of respondents, one belonging to a moderate agreement pattern and one belonging to low agreement pattern. We calculated raw agreement coefficient (RAC) per behaviour in the whole sample and each latent class. When RAC was calculated in the whole sample, many behaviour had low/moderate RAC values. However, LCA showed that these items had higher RAC values in the high agreement and lower RAC values in the low agreement class.
Kinetic Characteristics of Kerogens in the Kuonamka Complex, Lower and Middle Cambrian of the Siberian Platform
Authors: Burshtein L.M. , Deshin A.A. , Parfenova T.M. , Yaroslavtseva E.S. , Kozyrev A.N. , Safronov P.I.
Published: December 2023

—The kinetic characteristics of kerogen (activation energy and frequency factor distributions of the initial generative potential) determine the dynamics of naphthide generation during catagenesis. In the previous studies on quantitative modeling of naphthidogenesis in the Kuonamka source rocks, the kinetic characteristics were taken by analogy with the known kerogens from other complexes and provinces. It seems relevant to determine the effective kinetic characteristics of the kerogen from the Kuonamka source rocks from experimental data. To estimate the kinetic parameters, specialized multi-rate pyrolysis studies were performed. The variations in pyrolysis data was reported to be presumably associated with the conditions of kerogen and source rock formation during accumulation and diagenesis of organic matter. The effect of carbonate and organic carbon contents on the temperature range of the second pyrolysis peak is recorded. Reconstruction of the average (effective) kinetic characteristics of kerogens from the Kuonamka source rock, was conducted using data on kerogens from Serkinsky-5 and 10 and Tit-Ebya-6 wells, which are less degraded than kerogens from Ust’-Maiskaya-366 well and probably attained the early mesocatagenesis grades. The current average effective kinetic characteristics of kerogen were estimated and corrected for the possible partial degradation of reference samples. The obtained effective kinetic models of kerogen are compared with models of kerogens of various genetic types known from the literature. The estimated effective kinetic characteristics of kerogens or Menil-1 and Type B kerogens with similar characteristics are to be taken, as a first approximation, in regional historical-genetic (basin) modeling of naphthide generation in the Kuonamka source rock.
Towards Legal Regulations of Generative AI in the Creative Industry
Authors: Shumakova N. I. , Lloyd J. J. , Titova E. V.
Published: December 2023

Objective: this article aims to answer the following questions: 1. Can generative artificial intelligence be a subject of copyright law? 2. What risks the unregulated use of generative artificial intelligence systems can cause? 3. What legal gaps should be filled in to minimize such risks?

Methods: comparative legal analysis, sociological method, concrete sociological method, quantitative data analysis, qualitative data analysis, statistical analysis, case study, induction, deduction.

Results: the authors identified several risks of the unregulated usage of generative artificial intelligence in the creative industry, among which are: violation of copyright and labor law, violation of consumers rights and the rise of public distrust in government. They suggest that a prompt development of new legal norms can minimize these risks. In conclusion, the article constants that states have already begun to realize that the negative impact of generative artificial intelligence on the creative industry must not be ignored, hence the development of similar legal regulations in states with completely different regimes.

Scientific novelty: the article provides a comprehensive study of the impact of generative artificial intelligence on the creative industry from two perspectives: the perspective of law and the perspective of the industry. The empirical basis of it consists of two international surveys and an expert opinion of a representative of the industry. This approach allowed the authors to improve the objectivity of their research and to obtain results that can be used for finding a practical solution for the identified risks. The problem of the ongoing development and popularization of generative artificial intelligence systems goes beyond the question “who is the author?” therefore, it needs to be solved by introduction of other than the already existing mechanisms and regulations - this point of view is supported not only by the results of the surveys but also by the analysis of current lawsuits against developers of generative artificial intelligence systems.

Practical significance: the obtained results can be used to fasten the development of universal legal rules, regulations, instruments and standards, the current lack of which poses a threat not only to human rights, but also to several sectors within the creative industry and beyond.
Copyrights to the Results of Artificial Intelligence Activity and Means of Their Protection
Authors: Kazantsev D. A.
Published: December 2023

Objective: to substantiate the mechanisms of legal protection of intellectual property objects created with the use of artificial intelligence.

Methods: the use of artificial intelligence to create works that are traditionally considered copyright objects was investigated with a set of general scientific and theoretical-legal methods of scientific cognition, including comparison, analogy and synthesis. In addition, the practice of using artificial intelligence, including neural networks, to create such works was considered in several aspects on the basis of retrospective and multifactor analysis.

Results: the paper summarizes the current practice of using artificial intelligence to create works that traditionally belong to intellectual property objects (texts, images, music, software), taking into account the formulated scientific and legal positions. Several qualitatively different variants of the use of artificial intelligence were identified. For each of these variants the mechanism of legal protection was proposed and the areas of their effective application were indicated. Proposals were made to regulate the legal protection of the results of artificial intelligence activity; this was made not in the paradigm of competing doctrines, but by combining several tools, each of them to be applied in a relevant situation.

Scientific novelty: the paper presents ontological differentiation of the results of artificial intelligence activity and the corresponding mechanisms of their legal protection. The author propose to consider the results of activity created by artificial intelligence not as a single object of legal regulation, but as a set of externally similar, but ontologically different objects, each requiring a separate approach to legal protection.

Practical significance: the ontological differentiation of the results of artificial intelligence activity and their corresponding legal protection mechanisms proposed in this paper is relevant both as a basis for further research and as proposals to supplement civil legislation.
Artificial Intelligence Impact on the Environment: Hidden Ecological Costs and Ethical-Legal Issues
Authors: Zhuk A.
Published: December 2023

Objective: to identify the hidden ecological costs associated with the elaboration, implementation and development of artificial intelligence technologies, in order to ensure its sustainable and harmonious integration with various economic sectors by identifying optimal moral-ethical and political-legal strategies.

Methods: the conducted research is based on an ecological approach to the development and implementation of artificial intelligence, as well as on an interdisciplinary and political-legal analysis of ecological problems and risks of algorithmic bias, errors in artificial intelligence algorithms and decision-making processes that may exacerbate environmental inequalities and injustice towards the environment. In addition, analysis was performed in regard to the consequences of natural ecosystems destruction caused by the development of artificial intelligence technologies due to the computing energy-intensiveness, the growing impact of data centers on energy consumption and problems with their cooling, the electronic waste formation due to the rapid improvement of equipment, etc.

Results: the analysis shows a range of environmental, ethical and political-legal issues associated with the training, use and development of artificial intelligence, which consumes a significant amount of energy (mainly from non-renewable sources). This leads to an increase in carbon emissions and creates obstacles to further sustainable ecological development. Improper disposal of artificial intelligence equipment exacerbates the problem of e-waste and pollution of the planet, further damaging the environment. Errors in artificial intelligence algorithms and decision-making processes lead to environmental injustice and inequality. AI technologies may disrupt natural ecosystems, jeopardizing wildlife habitats and migration patterns.

Scientific novelty: the environmental consequences of the artificial intelligence use and further development, as well as the resulting environmental violations and costs of sustainable development, were studied. This leads to the scientific search for optimal strategies to minimize environmental damage, in which legal scholars and lawyers will have to determine ethical-legal and political-legal solutions at the national and supranational levels.

Practical significance: understanding the environmental impact of AI is crucial for policy makers, lawyers, researchers, and industry experts in developing strategies to minimize environmental harm. The findings emphasize the importance of implementing energy efficient algorithms, switching to renewable energy sources, adopting responsible e-waste management practices, ensuring fairness in AI decision-making and taking into account ethical considerations and rules of its implementation.
Achieving Algorithmic Transparency and Managing Risks of Data Security when Making Decisions without Human Interference: Legal Approaches
Authors: Zharova A. K.
Published: December 2023

Objective: to compare modern approaches in law to the use of program codes and algorithms in decision-making that meet the principles of transparency and openness, as well as the increasingly stringent requirements for ensuring the security of personal and other big data obtained and processed algorithmically.

Methods: the main methods for researching the principle of transparency in algorithmic decision-making were formal-legal and comparative analysis of legal acts and international standards of information security, as well as the principles and legal constructions contained in them.

Results: it was determined that the development of information security standardization, inclusion in legal acts of requirements for the development of information technologies that comply with the principles of transparency and openness of applied algorithms will minimize the risks associated with the unlawful processing of users' big data and obtaining information about their privacy. Proposals were identified, related to the implementation of algorithmic transparency in the field of data processing legal regulation. Recommendations were formulated, based on which the legislator can solve the problem of ensuring the openness of the logic of information technology algorithms with regard to modern standards of information security.

Scientific novelty: it consists in the substantiation of new trends and relevant legal approaches, which allow revealing the logic of data processing by digital and information technologies, based on the characterization of European standards of the “privacy by design” concept in new digital and information technologies of decision-making and data protection, as well as on the new legal requirements for artificial intelligence systems, including the requirement to ensure algorithmic transparency, and criteria for personal data and users' big data processing. This said, data protection is understood as a system of legal, technical and organizational principles aimed at ensuring personal data confidentiality.

Practical significance: it is due to the need to study the best Russian and international practices in protecting the privacy of users of digital and information technologies, as well as the need for legislative provision of requirements for the use of algorithms that meet the principles of transparency and openness of personal data processing, taking into account the need to ensure confidentiality at all stages of the life cycle of their processing, which will ensure the continuity of security management.
Legal Nature of Smart Contracts: Contract or Program Code?
Authors: Varbanova G.
Published: December 2023

Objective: due to the rapid technological changes, digital economy and contractual relations determine law transformation and legislation development towards adaptation to prospective spreading and application of smart contracts in civil and commercial turnover. In this regard, the study focuses on determining the legal essence of smart contracts as a fundamental step towards the development of their timely and clear regulation.

Methods: the research is based on the methodology of formal-legal and comparative legal analysis. It compares the current Bulgarian legislation with supranational legal sources and identifies the characteristic features of smart contracts as demanded instruments necessary for modern law and economy. The article also compares them with the classical understanding of contracts, making it possible to understand and define the nature of smart contracts more accurately.

Results: it was determined that a smart contract is a software code in which the parties predetermine conditions under which the contractual relationship between them is created, modified and terminated. The research proved that the contract execution does not depend on the action or inaction of its parties, but rather on the occurrence of a predetermined condition (a certain fact relevant to the parties) under which the contract must self-execute. It was substantiated that the will of the parties cannot be changed or replaced because of the special way in which the smart contract is recorded in a distributed ledger. It is found that the fundamental problem of transferring the will from the legal language to the program code of the smart contract persists: if the will of the parties is incorrectly transferred to the program code, the smart contract may self-execute, but its execution will not be the result that the parties counted on.

Scientific novelty: the analysis made it possible to compare the current national (Bulgarian) legislation and supranational (European) law. It revealed the vagueness of smart contracts regulation, both at the national and international level, and identified a number of issues in need of scientific and legal interpretation, which refer to the legal nature of smart contracts in view of the self-executing program code concept.

Practical significance: the study can serve as a basis for further development of legislation towards its adaptation to the prospects of smart contracts spreading and application in civil and commercial turnover. It also allows an in-depth analysis of the smart contracts practice referring to such unsolved problems as accurate transference of the parties' will to the program code (translation of specific terms from the legal language into the smart contract program code), electronic identification of subjects - parties to the transaction and many other issues.
Smart Contracts and International Trade: European Legal Strategies for Managing Challenges
Authors: Lamappulage Donn Th. D.
Published: December 2023

Objective: the automation inherent in smart contracts makes them an attractive tool for global trade applications, especially for the automation of transactions. The prospects foreseeable will significantly impact international economic relations and the transformation of international trade rules. This fact determines the study objective - to identify the possibilities of transforming the said rules and the political and legal strategies adopted by European countries to implement smart contracts in international trade.

Methods: the study, devoted to the current international trade regulation in the context of contracts digitalization and spread of smart contracts, uses a combination of formal-legal and comparative-legal methods. They allow researching the international trade rules, analyzing and comparing the UK and the EU political and legal positions on the smart contracts introduction in international trade, as well as predicting the legal consequences of using smart contracts in international trade.

Results: the research shows that the proliferation of smart contracts has significant implications for international trade and its regulation. Smart contracts have numerous advantages, such as increased efficiency, reduced costs, and wide availability. However, they may lead to legal challenges when harmonizing traditional legal principles with the digital environment, in particular concerning the authentication of subjects, enforceability under specific circumstances of a case, and jurisdictional issues.

Scientific novelty: the current literature on the transformation of international trade regulation in the context of digitalization processes and the spread of smart contracts is complemented by the results of a comparative analysis of the legal positions existing in the European legal space and developed on the basis of problems, lessons and achievements in the smart contracts implementation in international trade.

Practical significance: understanding the legal implications of smart contracts is important for businesses involved in international trade. The study provides insights into the UK and the EU legal positions from which guidance can be provided to companies navigating the digital landscape. Policymakers can also benefit from the findings when developing appropriate legal acts to balance the benefits of smart contracts with the need for legal certainty and protection in international trade.
Digital Transformations of the South African Legal Landscape
Authors: Mokofe W. M.
Published: December 2023

Objective: South Africa is a country with great potential for intensive development due to the active growth and adoption of digital technologies. The rapidly emerging digital landscape is transforming the legal framework, which in turn influences the digital environment. This transformative relationship determined the focus of the research, which is to identify the legal system adaptability under dynamic changes, as well as the legal landscape evolution under digitalization and technological progress.

Methods: the study of the changing legal landscape required an interdisciplinary approach that combines legal analysis with ideas from sociology, economics, etc. In doing so, the formal-legal method was used to examine the key legal instruments shaping South Africa's digital environment and providing the opportunities and challenges of the interaction between digital technologies and South African law.

Results: the paper provides insights into how the South African legal system is addressing digital challenges; assesses the integration of digital innovations into the legal system; highlights the transformative impact of digital technologies on traditional legal processes, including collecting evidence, dispute resolution and access to justice. Finally, it evaluates the role of digital technologies in making legal processes more efficient.

Scientific novelty: the study contributes to the ongoing debate on the complex relationship between digital technologies and South African law. It shows how South African law is coping with digital complexities and substantiates new insights into the transformation of the traditional legal paradigm as a result of digitalization, as well as its implications for legal proceedings and access to justice. By delving into the adaptations, challenges and innovations arising at the intersection of law, technologies and digitalization, insights are gained into how South African law navigates the dynamic digital landscape.

Practical significance: adapting the legal landscape to digitalization and technological advances is critical to ensure rapid technological progress. It also requires collaboration between government agencies, civil society, experts in law and technology. The study provides valuable recommendations and suggestions for policymakers, legal practitioners and stakeholders shaping South Africa's legal ecosystem. The author addresses the challenges of ensuring personal data privacy, enhancing electronic interactions, and countering cybercrime. The importance of introducing technological achievements while maintaining robust legal safeguards is emphasized.