Primary Problems Research Articles

Research Advances in Facial Expression Recognition Technology

As a key area in artificial intelligence and computer vision, facial expression analysis technology has been taking hold rapidly, yielding dazzling advances. This technology extracts even the subtlest facial movements to identify when a human is sad, happy, or angry. It has extensive application value in markets like mental diagnosis, secure monitoring, and intelligent interaction. The paper will provide a brief overview of the kernel technology of facial expressions recognition: geometric features, appearance features, and deep learning. And compared the experimental results of different experiments, as a goal, the experiments compare functions of several methods in a multi-dataset context, concentrating the primary problems in the tasks like dataset bias, real-time requirements, and different light levels and partial occlusions in various environments. Eventually, the paper forecasts the imminent growth trend in data fusion and deep learning improvement. This also indicates that emerging technologies, especially in terms of applications, will have the upper hand.

Growth Optimizer Algorithm for Economic Load Dispatch Problem: Analysis and Evaluation

The Growth Optimizer algorithm (GO) is a novel metaheuristic that draws inspiration from people’s learning and introspection processes as they progress through society. Economic Load Dispatch (ELD), one of the primary problems in the power system, is resolved by the GO. To assess GO’s dependability, its performance is contrasted with a number of methods. These techniques include the Rime-ice algorithm (RIME), Grey Wolf Optimizer (GWO), Elephant Herding Optimization (EHO), and Tunicate Swarm Algorithm (TSA). Also, the GO algorithm has the competition of other literature techniques such as Monarch butterfly optimization (MBO), the Sine Cosine algorithm (SCA), the chimp optimization algorithm (ChOA), the moth search algorithm (MSA), and the snow ablation algorithm (SAO). Six units for the ELD problem at a 1000 MW load, ten units for the ELD problem at a 2000 MW load, and twenty units for the ELD problem at a 3000 MW load are the cases employed in this work. The standard deviation, minimum fitness function, and maximum mean values are measured for 30 different runs in order to evaluate all methods. Using the GO approach, the ideal power mismatch values of 3.82627263206814 × 10−12, 0.0000622209480241054, and 5.5893360695336 × 10−7 were found for six, ten, and twenty generator units, respectively. The GO’s dominance over all other algorithms is demonstrated by the results produced for the ELD scenarios.

Strategies for Enhancing Slum Settlement Study Case: Tegal Sari Mandala III, Medan Denai District

Tegal Sari Mandala III in the Medan Denai District is a residential area characterized by poor sanitation and a high risk of flooding, making it a mild slum. To prevent slum conditions from becoming normalized in Indonesian society, it is essential to address and eliminate such settlements. Each location presents unique challenges and requires tailored solutions to tackle slum issues effectively. This research employs both qualitative and quantitative methods, which are suitable for examining slum areas. The analysis reveals that the primary problems include poor environmental maintenance, such as garbage accumulation and improper waste management, leading to flooding, polluted rivers, and foul-smelling surroundings. Solutions to these issues include developing and enhancing the settlement quality by establishing a night market and creating green spaces along the banks of the Sulang Saling River.

Optimal adaptive heuristic algorithm based energy optimization with flexible loads using demand response in smart grid.

Demand response-based load scheduling in smart power grids is currently one of the most important topics in energy optimization. There are several benefits to utility companies and their customers from this strategy. The main goal of this work is to employ a load scheduling controller (LSC) to model and solve the scheduling issue for household appliances. The LSC offers a solution to the primary problems faced during implementing demand response. The goal is to minimize peak-to-average demand ratios (PADR) and electricity bills while preserving customer satisfaction. Time-varying pricing, intermittent renewable energy, domestic appliance energy demand, storage battery, and grid constraints are all incorporated into the model. The optimal adaptive wind-driven optimization (OAWDO) method is a stochastic optimization technique designed to manage supply, demand, and power price uncertainties. LSC creates the ideal schedule for home appliance running periods using the OAWDO algorithm. This guarantees that every appliance runs as economically as possible on its own. Most appliances run the risk of functioning during low-price hours if just the real time-varying price system is used, which could result in rebound peaks. We combine an inclined block tariff with a real-time-varying price to alleviate this problem. MATLAB is used to do a load scheduling simulation for home appliances based on the OAWDO algorithm. By contrasting it with other algorithms, including the genetic algorithm (GA), the whale optimization algorithm (WOA), the fire-fly optimization algorithm (FFOA), and the wind-driven optimization (WDO) algorithms, the effectiveness of the OAWDO technique is supported. Results indicate that OAWDO works better than current algorithms in terms of reducing power costs, PADR, and rebound peak formation without sacrificing user comfort.

Pre-hospital care for children: a descriptive study from Central Norway

BackgroundPre-hospital incidents involving pediatric and neonatal patients are infrequent, and clinical characteristics and care for these patients differ from the adult population. Lack of knowledge, guidelines, and experience can make pre-hospital pediatric care challenging, and there is limited research on the epidemiology and best practice of care for this population. We examined the pre-hospital pediatric population in the county of Sør-Trøndelag, Norway, to improve our understanding of this population in our region.MethodsWe conducted a retrospective observational cohort study of emergency incidents involving children under twelve years of age with dispatch of Emergency Medical Services (EMS) in Sør-Trøndelag between 2018 and 2022. Incidents and patient characteristics were extracted from the Emergency Medical Communication Center (EMCC) database. In addition, data on patient characteristics and interventions for more serious incidents seen by the Helicopter Emergency Medical Service (HEMS) were included from the database LABAS. We provided descriptive statistics and estimated population incidences using Poisson regression.ResultsThe catchment area of EMCC Sør-Trøndelag has a population of approximately 43,000 children under the age of twelve years. During the five-year study period, there were 7005 emergency calls concerning this patient population, representing 6% of all emergency calls (total no. 108,717). Of these, 3500 (50%) resulted in the dispatch of an ambulance and/or HEMS, yielding an annual incidence of EMS dispatches of 17 per 1000 children. The three most common primary medical problems were respiratory distress, altered consciousness, and trauma. Among the 309 HEMS patients, 131 (42%) received advanced interventions from the HEMS physician. Assisted ventilation was the most frequent intervention.ConclusionsPediatric and neonatal patients make up a small proportion of pre-hospital patient dispatches in Sør-Trøndelag. Consequently, each EMS provider infrequently encounters children in the pre-hospital environment, resulting in less experience with pediatric advanced medical interventions. This study identifies some clinical characteristics and interventions regarding pediatric and neonatal patients that have been pointed out as focus areas for pediatric pre-hospital research.

Constructing an Evaluation and Assessment System for Urology Specialists Based on Entrustable Professional Activities.

This study aimed to establish a comprehensive evaluation and assessment system for urology specialists based on entrustable professional activities (EPAs). A research group was formed to develop a preliminary index system for the evaluation and assessment of urology specialists through an extensive literature review and group discussions. The Delphi method was employed to design a questionnaire, and two rounds of expert consultations were conducted to finalize the index system and design a corresponding assessment method. A total of 24 experts participated in the two rounds of consultations, with authority coefficients of 0.885 and 0.894, and agreement levels of 0.270 and 0.256, respectively, indicating a high level of expertise and strong consensus among the participants. Based on the expert feedback, 16 key indicators were identified: Recognizing and admitting urological patients, selecting and interpreting specialized tests, diagnosing and differentiating diseases, making therapeutic decisions, documenting medical information, delivering oral clinical case reports, identifying and managing primary care and speciality medical problems, managing critical illness, handling patient transfers and departmental handovers, communicating informed medical decisions, performing basic and specialized surgical operations, providing health guidance, responding to public health emergencies, and engaging in clinical teaching. All indicators scored above 3.5 in importance, with coefficients of variation below 0.25, signifying their appropriateness. The expected confidence levels for each indicator at various stages were determined, and a comprehensive assessment method encompassing "process evaluation, peer impression review, and endpoint assessment" was developed. This research successfully established an initial EPAs-based evaluation and assessment index system for urology specialists, defined the expected confidence levels for each indicator across different time points, and devised a specific assessment methodology, thereby providing a scientific foundation for the training and evaluation of urology specialists.

A multi-scale uncertainty quantification model encompassing minimum-size unit cells for effective properties of plain woven composites

The uncertainty quantification is crucial to the high-precision prediction of composites’ effective properties. However, the unclear input uncertainties of multiscale parameters, complex uncertainty propagations of inter-scale correlations, and unaffordable computational cost of massive simulations are three primary problems at present. In this work, an innovative model with high accuracy and feasible cost for the mechanical property prediction of plain woven composites is developed encompassing minimum-size unit cells and multi-scale uncertainty quantification. For the accuracy holding, an uncertainty analysis process consists of the traceability description, inter-scale propagation and quantification is established. The uncertainties of geometry are described by uniform distributions for fiber, fiber bundle and composite scales, respectively; that of constituent properties is described by normal distributions for fiber and matrix, and its propagations to bundle and composite scales are realized by Nataf transformation methods with the consideration of parameter correlations. For the cost control, minimum-size unit cells are formulated by exhaustive analysis of structural symmetries to reduce the computational cost without accuracy compromising for the single simulation, and 1/8 and 1/16 unit cells compared with traditional full-size ones are obtained. The evolution convergence for statistical uncertainties of effective properties is finally obtained with totally reduced computational cost of 89%.

HSTrans: Homogeneous substructures transformer for predicting frequencies of drug-side effects

Identifying the frequencies of drug-side effects is crucial for assessing drug risk-benefit. However, accurately determining these frequencies remains challenging due to the limitations of time and scale in clinical randomized controlled trials. As a result, several computational methods have been proposed to address these issues. Nonetheless, two primary problems still persist. Firstly, most of these methods face challenges in generating accurate predictions for novel drugs, as they heavily depend on the interaction graph between drugs and side effects (SEs) within their modeling framework. Secondly, some previous methods often simply concatenate the features of drugs and SEs, which fails to effectively capture their underlying association. In this work, we present HSTrans, a novel approach that treats drugs and SEs as sets of substructures, leveraging a transformer encoder for unified substructure embedding and incorporating an interaction module for association capture. Specifically, HSTrans extracts drug substructures through a specialized algorithm and identifies effective substructures for each SE by employing an indicator that measures the importance of each substructure and SE. Additionally, HSTrans applies convolutional neural network (CNN) in the interaction module to capture complex relationships between drugs and SEs. Experimental results on datasets from Galeano et al.’s study demonstrate that the proposed method outperforms other state-of-the-art approaches. The demo codes for HSTrans are available at https://github.com/Dtdtxuky/HSTrans/tree/master.

An Investigation of Classical Model Predictive Controller Path Tracking Performance of a Two-Wheel and Four-Wheel Steering Vehicle

Studies on self-driving vehicles have become a trend in recent years, and many systems have been developed to enable autonomous manoeuvre. Various methods have been used to improve path-tracking algorithms which increase vehicle performance, including tracking accuracy and stability. Path tracking is one of the primary problems for autonomous vehicles where the vehicle deviates from target paths, which leads to unnecessary counter-correction. Conventional front wheel steering is unable to satisfy the manoeuvre with a high lateral acceleration since the front steering angle is limited in accurately responding to vehicle dynamics. Moreover, the characteristics of front wheel steering vehicles affect handling stability due to the fact that the turning radius is larger than the vehicle itself. This disadvantageous can compromise safety during under-steer and over-steer situations. The main objective of this preliminary study is to investigate the performance of a four-wheel steering system (4WS) in path tracking for autonomous vehicles using a classical model predictive controller (MPC). Conventional two-wheel steering (2WS) tracking performance following the desired driving system with the same MPC controller is compared with 4WS vehicles. The driving system is developed using Driving Scenario Designer to extract the desired yaw angle and lateral position for controller references constructed in Matlab Simulink. Fixed MPC constraint, prediction, control horizon, yaw angle and lateral position weights were used to compare the performance between 2WS and 4WS vehicles. The simulation results show that 4WS is three times better than 2WS vehicles in tracking predetermined paths. 4WS vehicle show 74.55% better performance in lateral position tracking and 68.75% better performance in trailing predetermined yaw angle value. The simulation data from the preliminary study will be used as a guideline to develop an advanced controller of 4WS vehicles.

An Overview of Social Marketing in Türkiye

Background of the Country The Republic of Türkiye, is a transcontinental country located in East Thrace in south-eastern Europe and on the peninsula of Anatolia in southwestern Asia. With the collapse of the Ottoman Empire, which was an immense power in Eurasia and Africa from southeast Europe to western Asia and North Africa, and the proclamation of the Republic in 1923, the Turkish people gained the right to self-government for the first time in centuries. With an amendment to the Constitution of the Republic, Türkiye became governed by a new system in which the president has executive powers. Türkiye ranked 48th out of 191 countries in the 2022 Human Development Index. Primary social Problems in the Country Unemployment has been a major socio-economic problem in Türkiye. Other important social issues include the integration of irregular migrants into social life, education inequality, violence against women, and forest fires. Use of Social Marketing Although they have not been found to be sufficient to solve the fundamental social problems there are projects that have been carried out in Türkiye for many years. These projects are corporate social responsibility initiatives that focus on market research to solve a fundamental social problem, in a select target market in a bid to change behavior through effective communication. Academic Stakeholders and Activities The few social marketing projects carried out in Türkiye have been funded by marketing academics and have focused primarily on the development of environmentally friendly behaviors. Social marketing courses are included in the curricula of a small number of universities in Türkiye. It can be stated that the concept of social marketing in Türkiye is not clearly understood by practitioners. However, efforts to develop behavior change for the benefit of society seem to have started with charity and evolved into corporate social responsibility projects. Discussion and Conclusions Despite not being deemed sufficient to solve the fundamental social problems, there are projects that have been ongoing in Türkiye for many years. These projects are corporate social responsibility initiatives aimed at addressing crucial social issues. Social marketing has been used in Türkiye for four decades but still has not achieved its full potential. Because social marketing is a concept similar to the understanding of the philanthropy that existed in Turkish culture many centuries ago, it can easily be adapted to the Turkish market. It is recommended that the government of Türkiye use social marketing to promote behavioral practices that benefit society.

RESIDENTS’ PERCEPTION ON MANAGEMENT BODIES’ SERVICE DELIVERABLES: THE CASE OF AFFORDABLE STRATA HOUSING IN KLANG VALLEY, MALAYSIA

The rapid urbanization in Malaysia has led to a significant increase in low-cost and low-medium-cost strata housing. However, managing these schemes presents unique challenges due to residents' financial constraints. Challenges often happen in this housing scheme, resulting in poor maintenance, overcrowding, and inadequate amenities, affecting residents' overall quality of life. The study aims to understand the challenges residents and management bodies face in these strata schemes and develop strategies for improving their management. This study helps identify primary issues and problems encountered by residents, assess their perceptions of their management body performance, and propose practical strategies for improving strata management practices. A mixed-mode methodology is employed utilizing primary data collected through questionnaire surveys of strata residents and analysed using SPSS. The findings highlight the differences between active and non-active management bodies in managing strata properties. This study highlights residents' perceptions that shed light on the difficulties in managing and maintaining affordable housing strata schemes, offering important information for formulating strategies to improve strata management practices in Malaysia.

Administrative Law in the Era of Digital Technologies: New Opportunities for the Saving of Cultural Heritage and Public Education

The rapid development of digital technologies has transformed various aspects of human life, including the save and promotion of cultural heritage. The present article explores the intersection of administrative law and digital technologies in relation to the protection of cultural heritage and public education. The study aims to analyze the role of administrative law in providing a legal framework for the utilization of digital technologies to safeguard cultural heritage, address the challenges arising from the adoption of new technologies, and promote public education on the importance of saving historical values. The article begins by examining the innovative methods employed in the save of cultural heritage, such as virtual museums, augmented and virtual reality technologies, and artificial intelligence. The role of administrative law in facilitating the integration of these technologies into the save process is emphasized, as it provides the necessary legal support and guidance to ensure their effective and responsible use. Next, the article delves into the primary challenges and problems faced by the cultural heritage sector in adopting digital technologies. These include issues related to data privacy and security, intellectual property rights, and the need for harmonization between national and international legal frameworks. The article highlights the importance of administrative law in addressing these challenges and ensuring a balanced approach that respects the rights of all stakeholders. The study then discusses the interaction between technology and law in the context of heritage protection. It analyzes the existing legal frameworks governing the use of digital technologies in the cultural heritage sector and identifies areas for improvement and potential legal developments. The role of administrative law in facilitating international cooperation and collaboration in the save of cultural heritage is also explored. Finally, the article presents an overview of the prospects for the development of digital cultural heritage management. It outlines the potential benefits of integrating digital technologies into the save process, such as increased accessibility and awareness of cultural heritage, as well as the opportunities for public education and engagement. The article concludes by emphasizing the crucial role of administrative law in ensuring that the digital transformation of the cultural heritage sector is carried out responsibly and sustainably.

Working Capacity Impairment and Primary Disability Problems of Ukraine Urological Patients During Recent Years (2018–2022)

The objective: to determine regional and generalized indicators of primary disability of the adult population of Ukraine, resulting from diseases of the genitourinary system in 2018–2022, specifics depending on age and established groups. Materials and methods. The dynamics of data initially recognized as disabled due to diseases of the genitourinary system among the adult population of Ukraine and the analysis of regional characteristics in the period 2018–2022 years using data from official reporting and collections on the main indicators of urological care in Ukraine are presented. For statistical processing using the “SPSS for Windows software package. Version 11” and “MedStat” we used the chi-square test, comparing the proportion for the two groups using Fisher’s angular transformation (with Yates’ correction); a difference of p < 0.05 was considered significant. Results. Against the background of fluctuations in the absolute number of newly registered disabled persons due to diseases of the genitourinary system in adults (18+ years) during 2018–2022 years, the largest indicator was noted in 2022. In terms of the absolute number of the population in this year, the difference is significant compared to each from the previous ones (p < 0.001) with an upward trend in the Western region in 2022 compared to 2018 and 2019 (p = 0.054 and 0.076). The structure of disability by group did not change in 2018–2022, the largest share is made up of persons of the III degree disability who are unable to work, with the Western region leading in terms of relative level. During this period, the number of persons recognized as I degree disabled for the first time is the largest in the city of Kyiv and the Southern region – 60% in 2021 and 48% in 2022, respectively. The relative level of disability (per 10 thousand people) in the country was the highest in 2022, significantly different from 2019, 2021 (p = 0.015) and 2020 (p = 0.009). The Western region has been the leader forall 5 years of observation with the highest rate in 2022 compared to 2018–2020 (p < 0.001). During the period 2018–2022, both in Ukraine as a whole and in each of the regions, the number of urologists per 1 million of population did not change reliably (p ≥ 0.05); the largest indicator of provision of these specialists for adults is in the city of Kyiv and the Western region (about 50 per 1 million population). No correlation was found between the number of urologists in each region (per 1 million population) and initially recognized disabled people due to diseases of the genitourinary system (per 10,000 population) in the regions of Ukraine and in the city of Kyiv. Conclusions. The determined indicators of the first recognized disabled people in Ukraine with regional features during the last 5 years, including in the conditions of wartime in 2022 year, allow to optimize the provision of urological care, with the aim of reducing the number of disabled people in adulthood, providing specialists and renal replacement therapy in case of CKD, as well as creating better socio-economic conditions for treatment and rehabilitation.

Cloud Computing Security Issues, Challenges, and Solutions

Cloud computing has revolutionized the way agencies manage and deliver their IT offerings by means of imparting scalable, bendy, and fee-effective solutions. However, with these good sized blessings come complicated protection demanding situations. The allotted nature of cloud environments, coupled with multi-tenant infrastructures, offers new risks that require sturdy and adaptive security frameworks. This paper goals to provide an in-intensity exploration of the primary security problems in cloud computing, the underlying challenges companies face in securing cloud services, and the solutions designed to mitigate these dangers

Investigating the optoelectronic properties of Mn and Fe doped CuAlS₂ for intermediate band solar cell applications

Chalcopyrites demonstrate compelling features for optoelectronic and photovoltaic devices, attributed to their valuable properties. Their remarkable light-absorption capabilities and well-suited band gap render them so attractive for applications in these fields. By allowing low-energy sub-bandgap photons to pass through and reducing the thermalisation loss from high-energy photons, intermediate-band materials address the primary problems in solar cells. This approach allows for more efficient use of the solar spectrum, helping solar cells exceed the traditional efficiency limits defined by the Shockley-Queisser limit. The objective of this study was to evaluate the electronic and optical characteristics of CuAlS2 systems doped with transition metals (TM = Mn, Fe) using the Full Potential Linearized Augmented Plane Wave approach within the framework of Density Functional Theory. A stable phase within the systems was observed upon replacing the Al atom with TM. The functionality of the intermediate band was governed by the 3d electronic characteristics of the TM3+ ion and its electronic configuration. The optical properties of CuAlS2 doped with Mn and Fe were analysed by calculating the dielectric function, refractive index, reflectivity, and absorption coefficient. Furthermore, the introduction of Mn and Fe through doping led to the creation of an intermediate band, enhancing visible light absorption and power conversion efficiency. Consequently, the optical spectrum of Mn-doped CuAlS2 and Fe-doped CuAlS2 compounds exhibits additional absorption peaks, accompanied by a significant improvement in absorption intensity. Our findings highlighted the need for continued and futuristic research into the scalability of these materials for practical applications in solar cells, optoelectronics, and spintronic devices. This investigation suggests that Mn-doped CuAlS2 holds the highest potential due to its high charge carriers and low recombination rate, indicating enhanced performance in CuAlS2-based intermediate band solar cells.

Staging Conscience

Through an in-depth analysis of Johannes Nomsz’s play Iemant en Niemant (1768), this article explores how the seemingly anachronistic genre of zinnespel (morality play) could serve to negotiate key issues of eighteenth-century aesthetical discourse. The combination of abstract ideas and sensual images ingrained into this genre made it an ideal vehicle with which to approach one of the primary problems of the period, namely the mediation between reason and the senses. Nomsz’s play deals with this rationalist/empiricist divide concerning the moral philosophical question of whether reason or feelings guide human ethical behaviour. Through empathy with the allegorical character of Nobody, Nomsz draws his audience into the teeth of a moral dilemma through emotion rather than teaching them a moral lesson. At the same time, he connects moral sentiments to a rational procedure of moral self-judgement by staging conscience as an inner court. I call this way of applying the late medieval genre of morality play to the key questions of eighteenth-century aesthetics and philosophy ‘Enlightened zinnespel’. Turning to the zinnespel with its special capacity to merge mind and senses indicates that at this time, the role of art changed. Art was no longer seen as a medium of knowledge transference, but as a medium that could generate knowledge in a unique way because of its ability to combine cognitive, affective, and sensual dimensions.

Differences in prescribing patterns of opioid dependence drugs among patients with primary alcohol use problems and opioid use disorders within New York State by social determinant factors, 2005-2018

BackgroundThe increase in alcohol use problems and opioid use disorder (OUD) highlights the need for research on effective medication treatments for patients with dual diagnoses. ObjectivesThis study analyzed trends and social disparities in prescribing OUD medications for patients who initially had alcohol use problems and later received their first OUD diagnosis. MethodsThis study used merged data from the New York State Office of Addiction Services and Supports and the Medicaid to analyze individuals aged 18 years and older who initially had primary alcohol use problems and later had OUD for the first time between 2005 and 2018. It examined the rates of new buprenorphine and naltrexone prescriptions across various demographic and socioeconomic groups. ResultsAmong 27,029 clients, the average rate of new buprenorphine was 64.23 per 1000 clients (95% CI 61.30–67.15), with upward trends. The 18-35 age group had the highest buprenorphine utilization (111.48 per 1000 clients) and highest increase rates compared with other age groups. The white non-Hispanic group had the highest rates of buprenorphine (119.23 per 1000 clients) and showed larger increase over time compared with other race/ethnicity groups. Disabled patients showed slower increasing rates of buprenorphine than other groups. Upward trends were observed in naltrexone. All observed differences were statistically significant (P < 0.05). ConclusionsTrends showed increased use of OUD medications, with varying rates of buprenorphine utilization across different ages, races, and employment statuses. Despite this, the rates of receiving new buprenorphine remained low, suggesting a need for innovative methods to expand access to treatments.

"Nothingness Will Save Me from Nothingness" or Kenosis, the Brihadaranyaka Upanishad, and an Advaitic Panegyric of God and Abraham in Kierkegaard's Fear and Trembling

precis: The universal sense of nothingness resident at the heart of the very conception of evil in existence is one of the primary problems with which all philosophy and theology must grapple. It is at the origin of creation stories universally. My proposal in this essay is to demonstrate that this nothingness is not a negative concept but, rather, is the "obverse" of fullness—experiential and mystical—and that the path to fullness must pass through nothingness, a path that is manifested epistemically in the form of apophasis and, in the ethical dimension, as kenosis, culminating in a realization of the nondual/advaitic nature of reality. Cutting across time and traditions, then, through a textual exegesis of the Principal Upanishads and Kierkegaard's Fear and Trembling , I seek to delineate how both texts lead us, nondually, from nothingness to fullness. I formulate this hypothesis finally in the form of the following paradox: "Nothingness will save us from nothingness"—a formulation associated with the Japanese philosopher Keiji Nishitani.

Control measures during the enforcement process

This paper addresses the pressing issues surrounding the current mechanisms of enforcing court decisions in Ukraine, focusing on the inefficiencies that result in a low percentage of effectively executed judgments by both the State Enforcement Service (SES) and private enforcers. The study identifies the primary problems within the enforcement system, including insufficient legislative regulation, lack of effective oversight, and limited protection of debtor's rights. The paper provides an in-depth analysis of the existing mechanisms for control and appeal in the enforcement process, highlighting judicial control under Article 74 of the Law of Ukraine "On Enforcement Proceedings". The judicial control aspect is explored through the examination of court practices in both courts that issued enforcement documents and administrative courts. The paper identifies the number of appeals related to the enforcement process and discusses the effectiveness of judicial oversight. Additionally, the paper examines the extrajudicial control mechanisms, particularly the oversight exercised by the Ministry of Justice over both state and private enforcers. The study reveals significant challenges, such as the deprivation of the debtor's right to seek extrajudicial control, and discusses the reasons behind such legislative changes, along with their positive and negative consequences. The paper also presents the findings from recent research and publications that have begun to address these issues, and highlights the aspects of the general problem that have not been previously addressed, to which this paper is dedicated. To address these challenges, the paper proposes several improvements and legislative amendments. These include enhancing judicial control by establishing clearer criteria for reviewing appeals against enforcer actions, extending court powers to mandate specific actions by enforcers, and providing compensation for damages caused by unlawful enforcement actions. In terms of extrajudicial control, the paper suggests restoring the debtor's right to appeal to the Ministry of Justice, implementing a pre-screening mechanism to filter out baseless complaints, and strengthening the Ministry's monitoring capabilities.

Digital Dialects: The Impact of Social Media on Language Evolution And Emerging Forms of Communication

The advent of social media has profoundly influenced language evolution, introducing novel linguistic trends and emergent forms of communication. This literature review, titled "Digital Dialects: The Impact of Social Media on Language Evolution and Emerging Forms of Communication," explores three primary research problems. First, it investigates how social media contributes to language change. Second, it examines the emergent of new forms of communication. Third, it assesses the positive and negative impacts of social media on language proficiency and literacy. The research aims to analyze the contribution of social media in language change, identifying new forms of communication, and evaluating their impact on language learning and literacy development. Utilizing a documentary design, this study systematically reviews existing literature on the subject, drawing from previous publications to provide a comprehensive overview of the ways in which social media shapes language use. The findings reveal that social media acts as a catalyst for linguistic innovation, while also presenting challenges and opportunities for language proficiency and literacy. This review contributes to a deeper understanding of the dynamic relationship between social media and language, offering insights into the ongoing evolution of communication in the digital age.