Individual States Research Articles

ON THE ISSUE OF THE LEGAL STATUS OF THE OPERATOR OF THE «UNIFIED REGISTER OF INTERNET ADVERTISING» AS AN ORGANISATION EXERCISING CERTAIN STATE POWERS

In the article, the author points out the problem of the lack of not only legal consolidation, but also a clear understanding of the mechanism of vertical delegation of certain state powers to non-governmental organisations in terms of functioning of a unified information system for advertising accounting in the information and telecommunications world wide web “Internet”. The study found that such a transfer of powers by the Russian communication regulator “Roskomnadzor” to commercial organisations is designed to increase the effectiveness of advertising campaigns and limit illegitimate schemes related to tax evasion. The description of the legal status of the operator of the Unified Register of Internet Advertising is given. In this regard, it is concluded that the status of such an operator has significant similarities with the position of an entity performing publicly significant functions, due to the presence of special legal capacity. In addition, it is assumed that the acquisition of such a status by a non-governmental organisation is carried out by issuing an appropriate order by an authorised state body without concluding a contract to be concluded in order to detail the procedure for exercising the transferred individual state powers, including clarifying the amount of financing and responsibility for improper performance of the contract.

EU Social Economy: Means to ending Inequality?

In recent years, the European Union has been facing increasing technological, economic, environmental and social challenges. The issues of strengthening the social economy are becoming increasingly important in an era of instability and uncertainty in the prospects of global development. The subjects of this business model can play a positive role in achieving the UN Sustainable Development Goals, increasing productivity and competitiveness of both individual enterprises and states and their associations through increased solidarity at the territorial and local levels, reducing poverty and inequality. The social economy is designed to create quality jobs, guarantee equal learning opportunities and provide the necessary social services, especially for vulnerable segments of the population, such as migrants, persons with disabilities and unskilled workers. To realise its mission, its enterprises and organisations need to collaborate with public authorities, stakeholders and users capable of finding solutions to collective problems, such as ethical financing and socially responsible banking. This collaboration can give impetus to social inclusion, economic development and territorial cohesion in depressed underdeveloped areas and regions. Today, social indicators in EU countries such as poverty, inequality, long-term and youth unemployment continue to be high, making it difficult to ensure social sustainability. This article analyses EU policies on the social economy as well as its ecosystem in the region.

ПРАВОВИЙ СТАТУС ДИТИНИ ПІД ЧАС ЗБРОЙНОГО КОНФЛІКТУ

The author of the article analyses the legal status of a child during armed conflict. The above concept is considered through the allocation of three components, namely: ‘legal status of a person’, “child” and “armed conflict”. Attention is paid to the opinions of various legal scholars in this area. The author offers his own definition of the concept of ‘legal status of a child during an armed conflict’. In the article, the author focuses on the role and place of the legal status of the child during armed conflict at the level of international legal instruments. In particular, the author examines the international legal norms enshrined in the Universal Declaration of Human Rights, the Declaration of the Rights of the Child, the International Covenant on Civil and Political Rights, the International Covenant on Economic, Social and Cultural Rights, the Convention on the Rights of the Child, etc. These norms are specific international legal norms that do not establish clear rights and obligations, but only indicate the general direction of behaviour of subjects of international law. Such international legal norms do not specify who in each individual state should determine and implement appropriate mechanisms to ensure the legal status of the child during armed conflict. The above-mentioned international legal norms define the general direction of behaviour of subjects of international law regarding the legal status of the child during armed conflict – all participants unanimously agree that the child during armed conflict has a special status and, accordingly, should have special protection. National legislation in this area is formed on the basis of international legal norms. The author examines the national legislation, namely the Law of Ukraine ‘On Protection of Childhood’ and the Resolution of the Cabinet of Ministers of Ukraine ‘On Approval of the Procedure for Granting the Status of a Child Affected by Military Operations and Armed Conflicts’. Key words: child, legal status, armed conflict, international legal norms.

Feasibility Study on Art Therapy Methods for Sleep Disorder Groups Based on Artificial Intelligence Technology

With the rapid development of modern society and the accelerated pace of life, sleep disorders have become a significant issue affecting peoples quality of life. Numerous studies indicate that art therapy, as a non-pharmacological treatment, can externalize the subconscious through creative activities, raising it to a conscious level, thus improving the psychological state and sleep quality of individuals with sleep disorders. However, traditional art therapy methods still face certain limitations, often failing to achieve optimal therapeutic outcomes. The fast-growing field of artificial intelligence (AI), with advances in intelligent algorithms and big data analytics, offers new possibilities for the evolution of art therapy, potentially enhancing its effectiveness. This paper aims to explore the feasibility of integrating AI technology into art therapy for individuals with sleep disorders. By examining applications in mandala painting, intelligent wearable devices, and dream visualization, this study proposes innovative therapeutic approaches that combine traditional art therapy with modern AI technology to provide more efficient and personalized therapeutic solutions for those suffering from sleep disorders.

The in dubio pro natura principle in the light of scientific evidence:state responsibility

The In Dubio Pro Natura has evolved as a separate principle from the precaution principle under environmental law. This article aims to analyse both the In Dubio Pro Natura principle and the precaution principle in the light of scientific evidence and state responsibility. The precaution principle applies as a general rule in cases in which there are potential risks of serious environmental damage irrespective of the existence of scientific certainty over the said risks. On the other hand, the In Dubio Pro Natura principle offers a higher degree of protection to the environment and their interests than the obligation to act with precaution since it is the basis for preferring the interpretation of norms that grants the highest degree of protection to the environment. The author of this article, argues that in scenarios in which state authorities have a higher degree of responsibility over the handling of a situation and could control the adverse effects of a threat to the environment, public health or sustainability, for instance in extractivist projects, the use of the In Dubio Pro Natura principle should be preferred. Conversely, this article examines the global fight against climate change and the setting of global goals in one hand and the potential risks new technologies may have over biodiversity on the other as two examples where the In Dubio Pro Natura principle cannot be applied. In the first case, there is scientific consensus over the urgency to address climate change. However, in spite of global commitments, the individual state responsibility and control over this course of action is weak. In the second scenario, the author refers to the regulation to the use of new technologies where national authorities exercise a higher degree of control in cases where there is not enough certainty over the risks posed to the environment or public health. In these cases, the precaution principle is preferred.

Comparative cross-country studies of regional economy development in modern turbulent conditions

Relevance. In modern turbulent conditions, the global economic system is undergoing a transformation, which causes the emergence of new development centers at various levels. These trends require a search for relevant approaches to ensuring economic development. Therefore, knowledge of the main trends that determine the prospective development of the world economy in the near future is a priority task in the field of ensuring the vital functions of individual states.The purpose of the study is to conduct comparative cross-country studies of economic development to determine the main trends in this area that ensure the vital functions of individual states in modern turbulent conditions.Objectives: to conduct a comparative analysis of the economic development of individual countries of the world based on key development indicators; to identify modern trends that influence the economic development of the world economy.Methodology. In carrying out the research, modern methodological apparatus was used, starting from general methods based on traditional approaches, special tools such as methods of system and economic analysis, synthesis, grouping and comparison, methods of rank statistics, etc.Results. The modern trend occurring in the global economy is substantiated - this is a period of geopolitical fragmentation with a shift in emphasis from ensuring common macroeconomic benefits to protecting national interests, which leads to certain shifts in the global economy and the emergence of new centers of economic development.Conclusions. The article provides a comparative analysis of individual countries of the world and identifies the main trends that determine the prospective development of the world economy. The projected trends in economic development in the world for the coming years are given.

The dynamics of hematopoiesis over the human lifespan.

Over a lifetime, hematopoietic stem cells (HSCs) adjust their lineage output to support age-aligned physiology. In model organisms, stereotypic waves of hematopoiesis have been observed corresponding to defined age-biased HSC hallmarks. However, how the properties of hematopoietic stem and progenitor cells change over the human lifespan remains unclear. To address this gap, we profiled individual transcriptome states of human hematopoietic stem and progenitor cells spanning gestation, maturation and aging. Here we define the gene expression networks dictating age-specific differentiation of HSCs and the dynamics of fate decisions and lineage priming throughout life. We additionally identifiy and functionally validate a fetal-specific HSC state with robust engraftment and multilineage capacity. Furthermore, we observe that classification of acute myeloid leukemia against defined transcriptional age states demonstrates that utilization of early life transcriptional programs associates with poor prognosis. Overall, we provide a disease-relevant framework for heterochronic orientation of stem cell ontogeny along the real time axis of the human lifespan.

Travel specific resource selection by female Kodiak brown bears during the sockeye salmon spawning season

BackgroundAccess to salmon resources is vital to coastal brown bear (Ursus arctos) populations. Deciphering patterns of travel allowing coastal brown bears to exploit salmon resources dispersed across the landscape is critical to understanding their behavioral ecology, maintaining landscape connectivity for the species, and developing conservation strategies.MethodsWe modeled travel behavior of 51 radio-collared female Kodiak brown bears (U. a. middendorffi) from 2008 to 2015 during the sockeye salmon (Oncorhynchus nerka) stream spawning season to identify landscape patterns associated with travel pathways. To accomplish this, we first identified behavioral states of marked individuals, and then developed a resource selection function (RSF) to evaluate environmental covariates that were predictors of selection during travel behavior.ResultsLandcover edges, elderberry-salmonberry stands, lowland tundra, elevation, terrain position, and stream length influenced selection for travel corridors. The RSF validated well and was comparable to corridors identified by pathways used by bears while travelling.ConclusionsModels identified spatial predictions of the relative probability of selection while bears were travelling during the salmon spawning season and identified areas that contained potential movement corridors important for bears inhabiting Kodiak Island. Our results characterized factors influencing travel, identified important movement corridors, and provided managers with information to make informed resource management decisions.

Identification of Mind Awareness from EDA signals using Wavelet based ResNet50 model

Abstract The analysis of spontaneous mind wandering is crucial for comprehending an individual mental state and holds the potential to enhance performance and productivity. This paper proposes a framework using Continuous Wavelet Transform (CWT) based ResNet model to analyze Electrodermal Activity (EDA) signals for mind wandering detection. In this analysis, EDA signals are sourced from an openly accessible database and preprocessed for artifact and noise removal. Time-frequency analysis generates CWT spectrogram images, which are classified using a modified ResNet50 model that is custom built to classify the spectrogram images corresponding the mind wandering and awareness. Hyperparameter tuning is carried to obtain the optimal network parameters that provides the best accuracy. Results indicate that batch size of 32, learning rate 1e-5 provides better results. This hyperparameter tuned model achieved an accuracy of 64% in differentiating between the two classes. This paper proposes an adapted ResNet50 model that could be employed in wearable devices as a potential application of knowing the mind awareness of an individual.

Advancing elderly care through big data analytics and machine learning for daily activity characterization

<p>Confronted with the ongoing demographic shift characterized by an aging population, society grapples with emerging challenges that extend beyond the provision of targeted health services for the elderly. The focus has broadened to encompass the promotion of well-being and vitality throughout the aging process. Addressing these multifaceted issues demands a comprehensive approach that integrates biomedical components with physical, psychological, and social interventions. In the context of my project, a unique strategy is employed, placing significant emphasis on leveraging big data analytics and machine learning. The primary objective is to systematically observe and characterize the physiological conditions of the elderly, facilitating healthcare professionals in monitoring behaviors and promoting active aging. This undertaking involves meticulous data collection and analysis, employing machine learning algorithms (support vector machine (SVM), gradient boosting) within a framework that harnesses extensive data analytics. Ultimately, this approach enables the identification and characterization of daily routines and physiological states of individuals, contributing to a holistic understanding of aging.</p>

Graph neural networks for power grid operational risk assessment under evolving unit commitment

This article investigates the ability of graph neural networks (GNNs) to identify risky conditions in a power grid over the subsequent few hours, without explicit, high-resolution information regarding future generator on/off status or power dispatch decisions. The GNNs are trained using supervised learning to predict the power grid’s aggregated bus-level (either zonal or system-level) or individual branch-level state under different power supply and demand conditions. The variability of the stochastic grid variables (wind/solar generation and load demand), and their statistical correlations, are considered while generating the inputs for the training data. The outputs in the training data include system-level, zonal and transmission line-level quantities of interest (QoIs). The ground truth of QoIs are obtained by numerically solving deterministic optimization problems (e.g., security-constrained unit commitment) with the same inputs. The GNN predictions are used to conduct hours-ahead, sampling-based reliability and risk assessment w.r.t. zonal and system-level (load shedding) as well as branch-level (overloading) failure events. The proposed methodology is demonstrated for three synthetic grids with sizes ranging from 118 to 2848 buses. Our results demonstrate that GNNs are capable of providing fast and accurate prediction of QoIs and can be good proxies for computationally expensive optimization algorithms. The excellent accuracy of GNN-based reliability and risk assessment suggests that GNN models can substantially improve situational awareness by enabling quick, high-resolution reliability and risk estimation.

Is Earthquake Psychological Trauma a Cause of Post-Earthquake Dizziness? (Using Standard Vector Machine)

The aim of this study is to reveal the relationship between complaints such as dizziness of university students who experienced an earthquake in Kahramanmaraş and surrounding provinces on February 6, 2023 and the psychological trauma caused by the earthquake. 476 university students who survived the earthquake that occurred in Kahramanmaraş on February 6, 2023 in Turkey were included in this study. In the first part of the survey, students were asked about dizziness that did not occur before the earthquake but occurred after the earthquake, and in the second part of the survey, a total of 41 questions were asked in the six sub-dimensions of the attitude scale to determine the psychological states of individuals exposed to the earthquake, and each of the six variables, namely detachment from life, social health, psychological change, trauma anxiety, maturation, and avoidance, was compared with dizziness and the relationship between dizziness and the other six variables was tried to be found. In this study, the ‘’Attitude Scale for Determining the Psychological States of Individuals Exposed to Earthquakes’’ was used to reveal the psychological states of the students; and the ‘’Standard Vector Machine’’ (VRM) was used for statistical studies. The study concluded that dizziness that did not occur before the earthquake but occurred after the earthquake was closely related to the psychological trauma experienced due to the earthquake.

Effects of musical tempo on human thermal comfort during interval exercise

Compared to steady-state exercise, thermal comfort during interval exercise varies. Moreover, research on the effects of musical tempo on subjective thermal perception, emotional state, and physiological responses in individuals performing interval exercise remains limited. Based on this, 22 participants were recruited for this study to simulate a gym environment within a climate chamber. The K5 metabolic analyzer combined with questionnaires was used to monitor the subjective responses and physiological parameters of participants during exercise, analyzing the effect of musical tempo on thermal comfort during interval exercise. Furthermore, by externalizing different tempos of music during the exercise phases of the experiment, participants' emotional states were induced to be either pleasant (positive) or boring (negative). The no-music working condition served as a control group for this experiment with no emotional induction. The research results indicate that music tempo affects the subjective thermal response, physiological response, and emotional state of the exercising population, with this influence showing clear differences and patterns. Notably, Regardless of the music tempo, the emotional index (MI) exhibited strong negative correlations with thermal sensation votes (TSV) (r = -0.76, -0.93), metabolic rate (MR) (r = -0.91, -0.95), and heart rate (HR) (r = -0.92, -0.94) across two exercise intensities. Based on these findings, a more adaptive PMV improvement model (PMV*) was developed using correlation analysis and regression fitting. This study provides important insights for the design of personalized exercise environments.

Is there a case for or against patents to incentivize green technologies?: A critical evaluation of innovation incentives for the global north and global south

The world society is in urgent need for new ecological problem solutions on a global scale. However, the current system to incentivize invention and innovation for green technologies is only limitedly able to provide effective solutions—particularly in the “global south”. Since patents that exert distortionary effects remain the dominant mechanisms for incentivizing innovation, the debate about alternative incentivization instruments for fostering green invention and innovation has recently been renewed. Yet, some of these instruments run the danger of a so-called “projectitis”, an obsession with static small-scale projects. Instead, this article argues that we need scalable experiments for a better institutional support of systemic invention and innovation activities by improving the global governance regime that moves beyond individual organizations, industries, sectors, states, and geopolitical blocks. From a sustainability nexus perspective, required scalable innovation ecosystems must therefore account for the interconnections between technological, economic, political, social, and environmental issues. A reformed order that combines patents and alternative incentivization instruments may help to redirect resources towards fostering a more systemic, market-based, and consumer-oriented path of legitimate sustainable global development, as proposed by the 2030 Agenda and its sustainable development goals (SDGs), without leaving particular countries behind, while at the same time maintaining companies’ systemic dynamism in the long run.

N2 exchanges in hyperbaric environments: towards a model based on physiological gas transport (O2 and CO2).

Decompression sickness can occur in divers even when recommended decompression procedures are followed. Furthermore, the physiological state of individuals can significantly affect bubbling variability. These informations highlight the need for personalized input to improve decompression in SCUBA diving. The main objective of this study is to propose a fundamental framework for a new approach to inert gas exchanges. A physiological model of oxygen delivery to organs and tissues has been built and adapted to nitrogen. The validation of the model was made by transferring the N2 to CO2. Under normobaric conditions (air breathing, oxygen breathing, and static apnea) and hyperbaric conditions, the O2 model replicates the reference physiological Po2 (Spearman correlation tests p<0.001). The inert gas models can simulate inert gas partial pressures under normobaric and hyperbaric conditions. However, the lack of reference values prevents direct validation of this new model. Therefore, the N2 model has been transferred to CO2. The resulting CO2 model has been validated by comparing it with physiological reference values (Spearman correlation tests p<0.01). The validity of the CO2 model constructed from the N2 model demonstrates the plausibility of this physiological model of inert gas exchanges. In the context of personalized decompression procedures, the proposed model is of significant interest as it enables the integration of physiological and morphological parameters (blood and respiratory flows, alveolo-capillary diffusion, respiratory and blood volumes, oxygen consumption rate, fat mass, etc.) into a model of nitrogen saturation/desaturation, in which oxygen and CO2 partial pressures can also be incorporated.

Reshaping the European Union Landscape: The Rise of Far-Right Movements and Their Potential Impact on Middle East Policy

The rise of far-right parties within the European Union has raised significant concerns about potential shifts in EU foreign policy, particularly with regard to the Middle East. This development challenges the core values of the EU and has the potential to markedly reshape its diplomatic strategies, aid distribution, and regional engagement. This analysis examines key areas of Middle East policy likely to be influenced by the growing presence of far-right parties in EU institutions, including immigration and refugee policies, the EU's stance on the Israeli-Palestinian conflict, relations with Iran, and involvement in peace processes in the region. Additionally, the study emphasizes potential shifts in power dynamics within EU decision-making bodies concerning Middle East policy, underscoring the urgency of the issue. The hypotheses suggest that the increased influence of far-right parties may result in more restrictive immigration policies, stronger pro-Israel positions, a more confrontational approach towards Iran, diminished EU involvement in Middle East peace initiatives, and a reduction in regional financial aid. The research also explores the likelihood of greater bilateral engagement between individual EU member states and Middle Eastern countries, which could weaken the EU's common foreign policy and lead to a more fragmented regional strategy. This study highlights the critical importance of understanding the complexities of this phenomenon, as the mainstreaming of far-right ideologies has profound implications for European politics and the EU’s role in the Middle East. Addressing these challenges is essential for safeguarding the EU’s foundational values and maintaining its ability to navigate intricate geopolitical landscapes.

Array Optimization for a Wave Energy Converter with Adaptive Resonance Using Dual Bayesian Optimization

A novel Dual Bayesian optimization strategy is formed for an array of wave energy converters with adaptive resonance to maximize the annual performance through the energy conversion processes from irregular waves to electricity. A wave energy converter with adaptive resonance changes the natural frequency of power take-off dynamics for varying irregular waves, resulting in the maximum annual energy production. The first step of the two-step Dual Bayesian optimization determines the geometric layout of the array, which maximizes the first energy conversion to the total array excitation for irregular waves occurring annually. The second step optimizes the operational parameters of individual wave energy converters in the optimized array to maximize the power generation in varying sea states through simultaneous conversion to mechanical and electrical energy. The coupled hydrodynamics are solved in the frequency domain, and the power performance is evaluated by solving the Cummins’ equation in the time domain extended for multiple floating bodies, each strongly coupled with nonlinear power take-off dynamics. The proposed method is applied to a surface-riding wave energy converter, already optimized for single unit operation at individual sea states. Investigating two array layouts, linear and random, the optimized arrays after Step 1 increase the excitation spectral area by up to 40% relative to the single unit operation, indicating the synergy enhancing the first energy conversion. Subsequently, the dual-optimized linear layout attained a q-factor up to 1.13 in commonly occurring sea states, achieving improved average power generation in 60% of the evaluated sea states. The performance of the random layout exhibited the average power fluctuating along the wave spectra with a peak q-factor of 1.07. The individual adaptive resonance is confirmed in the optimized arrays, such that each surface-riding wave energy converter of both layouts adaptively resonates with the peak of the wave excitation spectra, maximizing the power generation for the different irregular waves.

Participation of citizens in the court consideration of criminal cases against minors

Relevance. Citizen participation in the administration of justice increases the openness of legal proceedings and the level of citizen confidence in the judicial system. At the same time, the right of the accused to have their criminal case examined by a court with the participation of representatives of the people is ensured. However, the involvement of non-professional judges in considering criminal cases is always associated with several organizational and procedural problems. To prevent and solve such problems in the criminal process of individual states, restrictions may be introduced on the jurisdiction of criminal cases in courts with the participation of representatives of the people, and specific considerations of certain categories of cases may be provided for. Such specific criminal cases include criminal cases against minors. There is an ongoing debate among Russian scientists and practitioners regarding the possibility of a juvenile defendant exercising the right to have their criminal case heard by a court with the participation of a jury.Purpose: disclosure of historical and modern approaches to the participation of citizens as lay judges in criminal cases involving minors.Objective: to reveal historical and modern approaches to the participation of representatives of the people in the consideration of criminal cases; to identify the possibilities and features of consideration of criminal cases against minors by the court with the participation of citizens; justify the feasibility of forming in the Russian criminal process a special system for considering criminal cases with the participation of representatives of the people.Methodology. In the process of working on the study, comparative-legal, formal-legal methods, and general scientific methods of cognition (analysis, synthesis, analogy) were used.Results. There are proposals formulated to adjust doctrinal and normative approaches to the consideration of criminal cases against minors with the participation of lay judges.Conclusion. The existing model of criminal proceedings with the participation of a jury does not consider the specifics of criminal cases against minors. However, expanding opportunities for citizens to participate in the consideration of this particular category of criminal cases is socially significant. A constructive discussion is required regarding the development of a model for considering criminal cases against minors with the involvement of lay judges.

Causation Puzzles in International Climate Litigation

Abstract The multiplicity of causes of climate change makes it difficult to establish causal connections between individual States’ greenhouse gas emissions and harmful effects of climate change. Several States and companies have invoked this causation puzzle as a defence against claims that they would be responsible for harmful effects. However, in recent opinions and judgments, the International Tribunal for the Law of the Sea, the European Court of Human Rights, and national courts have shown that this causation puzzle does not necessarily preclude a determination of the responsibility of States contributing to climate change. This paper examines how courts have (partially) solved puzzles of cause-effect relations by relying on normative standards based on the imperative to prevent global risks of climate harm. It also articulates possible solutions to the main causation puzzle that courts have not yet cracked: allocating compensation for climate change harm.

Integrating machine learning and sentiment analysis in movie recommendation systems

The fast growth of the film business, along with an ever-increasing number of movie options, has highlighted the need for better recommendation algorithms. This study investigates the application of sentiment analysis in a movie recommendation system with the goal of improving the user experience. The importance of this sector stems from its ability to bridge the gap between user interests and the vast number of cinematic products, addressing individual emotional states and preferences. Researchers choose to generate movie recommendations based on the sentiments conveyed by viewers’ reviews of the movies. Sentiment-based movie recommendation system research employs techniques such as natural language processing and hybrid models with the goal of increasing user satisfaction. To this purpose, the integration of advanced machine learning algorithms such as cosine similarity, support vector machine, and Naive Bayes improves recommendation systems with sentiment analysis. Cosine similarity improves movie recommendations by recognizing minor user preferences, while support vector machines and Naive Bayes enhance sentiment analysis by offering a nuanced interpretation of textual attitudes. Through trials, the proposed system employs two public datasets for sentiment analysis, namely the TMDB5k dataset and the Reviews dataset, and makes predictions (positive, negative, or neutral) based on the content of the review through conducting sentiment analysis on the text using the Viscous Accretion Disk Evolution Resource (VADER) approach. The findings, based on users’ feedback, are more accurate and informative regarding movie quality, where SVM accuracy is 99.28% and Naïve Bayes accuracy is 96.60% when used with VADER sentiment analysis.