Scientific Research Research Articles

Perlindungan Hak Cipta Dari Tindakan Pembajakan Software di Tinjau Dari Hukum Nasional

Technological developments give birth to new creative ideas and create something that never existed before. The digital world is the main medium to make this happen. Every day more than millions of people use or log in to the internet for various purposes, from scientific research to playing interactive games in cyberspace, or from trading or e-commerce to surfing gambling sites. In this case, there is a legal instrument Law no. 28 of 2014 concerning Copyright which applies in Indonesia where one of the objects that receives copyright protection is a computer program, in this case software. With this, it can be said that the copyright regime has received new challenges after the internet, one of which is the protection of software or computer programs. However, violations of current developments are also increasingly common with the advent of the internet. Software is a computer program that is often used as an object of piracy. Software piracy has long been a serious problem. Software piracy that is often carried out is on CD media, the Internet, and often even directly from computer to computer using a data cable. As a result, Indonesia is faced with the impacts and problems of piracy which are quite significant and well known both internationally and in Indonesia itself. Regulations related to copyright through Law Number 28 of 2014 are currently considered not yet firm enough to regulate software piracy. Therefore, the problem formulation in this research that is studied is: a) What is the form of copyright protection from acts of software piracy in terms of international law b) How is the regulation of legal copyright protection for computer programs (software) according to Law Number 28 of the Year 2014 concerning Copyright and what factors constitute obstacles to its implementation. Meanwhile, the research method uses normative research, namely this research approach is based on library materials which are secondary data or also known as Library Law Research. Meanwhile, data analysis was carried out qualitatively.

ANALYSIS OF THE IMPACT OF CROSS-SECTION DAMAGE ON THE STRENGTH AND DEFORMABILITY OF BENT REINFORCED CONCRETE ELEMENTS

The article analyzes defects and damage in reinforced concrete structures, particularly physical, biological, and chemical, with an emphasis on the impact of prolonged operation and aggressive environmental conditions. Research shows that mechanical damage, such as spalling and potholes, significantly reduces the load-bearing capacity of structures and causes complex deformations. Relevant directions in scientific research have been identified, particularly regarding the behavior of damaged reinforced concrete beams under load, which require further development and improvement of methods for assessing residual load-bearing capacity. The article emphasizes the need for additional experimental studies and the use of modern software for more accurate methods of predicting and calculating reinforced concrete structures.

A Scientific Approach to Improving IELTS Speaking Scores: Best Practices and Techniques

Improving performance in the IELTS Speaking test is critical for non-native English speakers aiming for higher band scores. This article explores various strategies to enhance speaking skills, including understanding the test format, engaging in regular practice, expanding vocabulary, refining pronunciation, developing fluency and coherence, receiving constructive feedback, building confidence, and providing detailed responses. Through a combination of evidence-based methodologies and practical tips, this study aims to equip learners with the necessary tools to excel in the IELTS Speaking test. The findings suggest that a structured and consistent approach can significantly improve test outcomes.

Flexible Strain Sensors with Ultra-High Sensitivity and Wide Range Enabled by Crack-Modulated Electrical Pathways

Abstract This study presents a breakthrough in flexible strain sensor technology with the development of an ultra-high sensitivity and wide-range sensor, addressing the critical challenge of reconciling sensitivity with measurement range. Inspired by the structure of bamboo slips, we introduce a novel approach that utilises liquid metal to modulate the electrical pathways within a cracked platinum fabric electrode. The resulting sensor demonstrates a gauge factor greater than 108 and a strain measurement capability exceeding 100%. The integration of patterned liquid metal enables customisable tuning of the sensor’s response, while the porous fabric structure ensures superior comfort and air permeability for the wearer. Our design not only optimises the sensor’s performance but also enhances the electrical stability that is essential for practical applications. Through systematic investigation, we reveal the intrinsic mechanisms governing the sensor’s response, offering valuable insights for the design of wearable strain sensors. The sensor’s exceptional performance across a spectrum of applications, from micro-strain to large-strain detection, highlights its potential for a wide range of real-world uses, demonstrating a significant advancement in the field of flexible electronics.

Exploring the Experiences of Times Without Care and Encounters in Persons With Dementia in the Swiss and German Nursing Home and Domiciliary Care Settings: Protocol for an Ethnographic Multimethods Study

Background Persons with dementia spend a large part of the day without care and encounters, often without activity, as confirmed by numerous studies. However, no scientific analysis has examined how persons with dementia experience these periods. Such knowledge would be highly relevant for health care professionals and relatives to develop adequate strategies for dealing with times without care. Objective We aim to reconstruct times without care and encounters in persons with dementia in the nursing home and domiciliary care settings and develop a typology. This typology will address the lifeworld understandings of time and the ways of arranging the time of persons with dementia. Methods Our study is designed as an explorative, sequential multimethods investigation. We aim to systematically reconstruct times without care and encounters over a period of 36 months using ethnographic methods. Afterward, we will examine the resulting typology using a survey. To describe different social and caring cultures, practices, and arrangements, we will analyze time periods across all phases of dementia in (1) institutions exclusively caring for persons with dementia, (2) institutions where persons with dementia and those without live together, and (3) domiciliary care. For each type of care, our target is 10 intensive case observations. These observations will occur in both participatory and nonparticipatory ways. We video record selected situations and conduct situational conversations and interviews with persons with dementia and nurses. We are aiming for a minimum sample of 30 persons with dementia plus their caregivers (ie, relatives of people with dementia and professional caregivers). We will analyze data according to grounded theory methodology. Furthermore, we will perform a hermeneutic sequence analysis of selected text passages. To interpret the video material, we will conduct a video interaction analysis. To obtain complementary information about the newly developed typology, we will survey approximately 400 formal and 150 informal caregivers. We will summarize the ethnography and survey findings into an overall concept of times without care and encounters in persons with dementia. To fulfill the research objectives, our cross-disciplinary and cross-country team comprises researchers with expertise in nursing sciences, gerontology, sociology, psychology, and ethnography. Results Our approach allows formulating statements about the nature, frequency, and prevalence of times without care and encounters in people with dementia across countries and types of care. Thus, we will contribute to making visible the lifeworld of persons with dementia. Our study commenced in March 2022 and will conclude in May 2025. The results are expected to be published in the fall of 2025. Conclusions Our research offers points of departure for the representative investigation of times without care and encounters in persons with dementia, for the development of diagnostic instruments, and for dealing critically with possibilities of interruption (eg, by developing targeted interventions). International Registered Report Identifier (IRRID) DERR1-10.2196/58190

In-vivo evaluation of analgesic and anti-inflammatory activities of the 80% methanol extract of Acacia seyal stem bark in rodent models

Abstract Background Pain and inflammation are the major medical condition commonly addressed with traditional remedies. Acacia seyal is a traditional herb widely used in Ethiopian folk medicine for pain management. However, its effectiveness has yet to be validated through scientific or experimental research. Therefore, the current study aims at evaluating the in vivo analgesic and anti-inflammatory effects of 80% methanolic stem bark extract of Acacia seyal in rodent models. Methods After successful extractions of the stem barks of Acacia seyal with 80% methanol, the pain relieving effects of 100, 200 and 400 mg/kg extract were evaluated using acetic acid-induced writhing test and hot plate method whereas the anti-inflammatory profile was determined by carrageenan induced paw-edema model and cotton pellet induced granuloma technique. Results The 80% methanol Acacia seyal stem bark extract exhibited substantial (p < 0.001) analgesic effect in acetic acid induced writing test (p < 0.001). The plant extract also witnessed significant central analgesic effect in hot plate method beginning at 30 min with maximum % elongation time occurred at 120 min. Furthermore, the acacia stem bark extract produced anti-inflammatory effect against carrageenan induced paw-edema model. In cotton pellet induced granuloma model, the 200 and 400 mg/kg doses of the current plant material appeared to inhibit granuloma mass formation and exudate reduction significantly (p < 0.001). Conclusion The collective findings of the current study revealed that 80% methanol extracts of Acacia seyal exhibited considerable analgesic and anti-inflammatory activities, supporting the plant’s traditional use for management of pain and inflammatory disorders.

Exploring the impact of digital knowledge, integration and performance on sustainable accounting, reporting and assurance

Purpose The purpose of this study is to perform bibliometric analysis to systematically and comprehensively examine the current landscape of digital knowledge, integration and performance in the transformation of sustainability accounting, reporting and assurance. Design/methodology/approach This research uses a systematic literature review, following the Scientific Procedures and Rationales for Systematic Literature Review protocol and uses various bibliometric and performance analytical methods. These include annual scientific production analysis, journal analysis, keyword cooccurrence analysis, keyword clustering, knowledge gap analysis and future research direction identification to evaluate the existing literature thoroughly. Findings The analysis reveals significant insights into the transformative impact of digital technologies on sustainability practices. Annual scientific production and journal analyses highlight key contributors to the adoption of digital technologies in sustainability accounting, reporting and assurance. Keyword cooccurrence analyses have identified key themes in sustainability accounting, reporting and assurance, highlighting the transformative role of digital technologies such as artificial intelligence (AI), blockchain, Internet of Things (IoT) and big data. These technologies enhance corporate accountability, transparency and sustainability by automating processes and improving data accuracy. The integration of these technologies supports environmental, social and governance (ESG) reporting, circular economy initiatives and strategic decision-making, fostering economic, social and environmental sustainability. Cluster-by-coupling analyses delve into nine broader revealing that IoT improves ESG report accuracy, eXtensible Business Reporting Language structures ESG data and AI enhances life cycle assessments and reporting authenticity. In addition, digital transformation impacts environmental performance, big data optimizes resource use and edge computing improves eco-efficiency. Furthermore, this study identifies avenues for future research to advance the understanding and implementation of digital technology in sustainability accounting, reporting and assurance practices. Research limitations/implications Academically, this research enriches the understanding of how digital technologies shape sustainability practices and identifies gaps in digital knowledge and integration. Practically, it provides actionable insights for organizations to improve sustainability reporting and performance by effectively leveraging these technologies. Policy-wise, the findings advocate for frameworks supporting the effective implementation of these technologies, ensuring alignment with global sustainability goals. Originality/value This study offers a detailed analysis of the performance and intellectual framework of research on implementing digital technology in sustainability accounting, reporting and assurance. It highlights the evolving research landscape and emphasizes the need for further investigation into how emerging technologies can be leveraged to achieve sustainability goals.

Random Numbers for Machine Learning: A Comparative Study of Reproducibility and Energy Consumption

Pseudo-Random Number Generators (PRNGs) have become ubiquitous in machine learning (ML) technologies because they are interesting for numerous methods. In the context of ML, multiple stochastic streams, produced in black boxes for methods such as stochastic gradient descent or dropout, can produce a lack of repeatability, impacting the ability to debug and explain results. The field of machine learning holds the potential for substantial advancements across various domains. However, despite the growing interest, persistent concerns include issues related to reproducibility and energy consumption. Reproducibility is crucial for robust scientific inquiry and explainability, while energy efficiency underscores the imperative to conserve finite global resources. This study delves into the investigation of whether the leading Pseudo-Random Number Generators (PRNGs) employed in machine learning languages, libraries, and frameworks uphold statistical quality and numerical reproducibility when compared to the original C implementation of the respective PRNG algorithms. Additionally, we aim to evaluate the time efficiency and energy consumption of various implementations. Our experiments encompass Python, NumPy, TensorFlow, and PyTorch, utilizing the Mersenne Twister, Permuted Congruential Generator (PCG), and Philox algorithms. Remarkably, we verified that the temporal performance of machine learning technologies closely aligns with that of C-based implementations, with instances of achieving even superior performances. On the other hand, it is noteworthy that ML technologies consumed only 10% more energy than their C-implementation counterparts. However, while statistical quality was found to be comparable, achieving numerical reproducibility across different platforms for identical seeds and algorithms was not achieved.

COVID-19-related research data availability and quality according to the FAIR principles: A meta-research study

Background According to the FAIR principles (Findable, Accessible, Interoperable, and Reusable), scientific research data should be findable, accessible, interoperable, and reusable. The COVID-19 pandemic has led to massive research activities and an unprecedented number of topical publications in a short time. However, no evaluation has assessed whether this COVID-19-related research data has complied with FAIR principles (or FAIRness). Objective Our objective was to investigate the availability of open data in COVID-19-related research and to assess compliance with FAIRness. Methods We conducted a comprehensive search and retrieved all open-access articles related to COVID-19 from journals indexed in PubMed, available in the Europe PubMed Central database, published from January 2020 through June 2023, using the metareadr package. Using rtransparent, a validated automated tool, we identified articles with links to their raw data hosted in a public repository. We then screened the link and included those repositories that included data specifically for their pertaining paper. Subsequently, we automatically assessed the adherence of the repositories to the FAIR principles using FAIRsFAIR Research Data Object Assessment Service (F-UJI) and rfuji package. The FAIR scores ranged from 1–22 and had four components. We reported descriptive analysis for each article type, journal category, and repository. We used linear regression models to find the most influential factors on the FAIRness of data. Results 5,700 URLs were included in the final analysis, sharing their data in a general-purpose repository. The mean (standard deviation, SD) level of compliance with FAIR metrics was 9.4 (4.88). The percentages of moderate or advanced compliance were as follows: Findability: 100.0%, Accessibility: 21.5%, Interoperability: 46.7%, and Reusability: 61.3%. The overall and component-wise monthly trends were consistent over the follow-up. Reviews (9.80, SD = 5.06, n = 160), articles in dental journals (13.67, SD = 3.51, n = 3) and Harvard Dataverse (15.79, SD = 3.65, n = 244) had the highest mean FAIRness scores, whereas letters (7.83, SD = 4.30, n = 55), articles in neuroscience journals (8.16, SD = 3.73, n = 63), and those deposited in GitHub (4.50, SD = 0.13, n = 2,152) showed the lowest scores. Regression models showed that the repository was the most influential factor on FAIRness scores (R2 = 0.809). Conclusion This paper underscored the potential for improvement across all facets of FAIR principles, specifically emphasizing Interoperability and Reusability in the data shared within general repositories during the COVID-19 pandemic.

Дуальное обучение как условие формирования экологической компетентности студентов в системе среднего профессионального образования

The system of secondary vocational training in Russia is undergoing significant changes regarding the quality of training of competent specialists who are able not only to carry out professional activities in modern socio-economic conditions, but also to successfully compete in those sectors of the national economy where they will work after graduation. As noted in the state program of the Russian Federation “Development of Education” until 2030, special attention is paid to the development of dual education and environmental education of students. In this regard, since 2014, dual (practice-oriented) training has been successfully implemented in secondary vocational education institutions in the country, within which students acquire basic theoretical knowledge in college classes and acquire practical skills at the enterprise. The purpose of the article is to study ways of developing students’ environmental competence in the system of secondary vocational education. Materials and research methods include an analytical review of scientific research related to the formation of environmental competence in dual learning conditions. The results of the study and their discussion are determined by the choice of approaches, technologies, methods, techniques and forms of work to develop students’ environmental competence. In conclusion, the results of the study are summarized.

КОРПОРАТИВНА СОЦІАЛЬНА ВІДПОВІДАЛЬНІСТЬ ЯК КЛЮЧОВИЙ ІНСТРУМЕНТ ЕКОНОМІЧНОЇ БЕЗПЕКИ БІЗНЕСУ ПІД ЧАС ВІЙНИ

Today's state of war is dramatically changing the business environment, creating unprecedented challenges for businesses of all sizes. The instability of the political situation, the disruption of logistics chains, a decrease in investment and a decrease in the purchasing power of the population have a negative impact on economic activity. Enterprises face increased risks, which requires a review of management strategies and ensuring economic security as a basis for further functioning and development. In these conditions, corporate social responsibility (CSR) becomes especially important, becoming not only an ethical imperative, but also a strategic tool for increasing business sustainability. The active participation of companies in solving social and humanitarian problems during martial law strengthens their authority and trust on the part of society and stakeholders, which contributes to the formation of a positive image, the expansion of partnership relations and the creation of additional opportunities for stable functioning in conditions of uncertainty. The growing role of CSR as a component of the enterprise management strategy provides an opportunity not only to preserve the economic security of individual business entities, but also to strengthen public trust in business, which is a key element of ensuring long-term economic stability in Ukraine.Objective.Theoretical generalization of scientific approaches regarding the content and role of corporate social responsibility as the main tool for ensuring the economic security of business in the conditions of martial law in Ukraine and the development of methodological recommendations for strengthening the stability and adaptability of business to crisis conditions. Results. The article provides a theoretical generalization of scientific approaches to the content and role of corporate social responsibility as a key tool for the economic security of business during the martial law in Ukraine. On the basis of scientific approaches, a modern interpretation of the CSR pyramid of Archie B. Carroll was formed. The analysis and assessment of the losses of infrastructure and enterprises of the real sector of the economy of Ukraine from hostilities and missile terror was carried out; an assessment of the main macroeconomic indicators of Ukraine for 2018-2023 is provided, the impact of military operations on a significant reduction in the number of active enterprises and the number of employees and the population of Ukraine in 2018-2023 is determined. The conducted studies highlight the key areas of CSR implementation in wartime, in particular, support for employees, assistance to the mobilized, involvement of stakeholders in the formation of the company's strategy and brand promotion. Scientific novelty. Approaches and methods of their involvement in the establishment of communications and interaction with stakeholders - investors, local communities and state structures are proposed, which will allow companies to adapt more quickly to the challenges of war. Practical significance. To ensure the economic security of business during wartime, it is proposed to integrate new initiatives to support personnel, mobilized workers and their families, as well as local communities. Such an approach will not only contribute to the stability and functionality of the enterprises themselves, but also strengthen their social stability and economic security, provide a deep connection between business and society, which contributes to the long-term development and socio-economic stability of the country in conditions of war. Keywords: corporate social responsibility (CSR), economic responsibility, enterprises, Archie Carroll's pyramid model, stakeholders, business economic security, development strategy, war.

Modal Parameter Identification of Jacket-Type Offshore Wind Turbines Under Operating Conditions

Operational modal analysis (OMA) is essential for long-term health monitoring of offshore wind turbines (OWTs), helping identifying changes in structural dynamic characteristics. OMA has been applied under parked or idle states for OWTs, assuming a linear and time-invariant dynamic system subjected to white noise excitations. The impact of complex operating environmental conditions on structural modal identification therefore requires systematic investigation. This paper studies the applicability of OMA based on covariance-driven stochastic subspace identification (SSI-COV) under various non-white noise excitations, using a DTU 10 MW jacket OWT model as a basis for a case study. Then, a scaled (1:75) 10 MW jacket OWT model test is used for the verification. For pure wave conditions, it is found that accurate identification for the first and second FA/SS modes can be achieved with significant wave energy. Under pure wind excitations, the unsteady servo control behavior leads to significant identification errors. The combined wind and wave actions further complicate the picture, leading to more scattered identification errors. The SSI-COV based modal identification method is suggested to be reliably applied for wind speeds larger than the rated speed and with sufficient wave energy. In addition, this method is found to perform better with larger misalignment of wind and wave directions. This study provides valuable insights in relation to the engineering applications of in situ modal identification techniques under operating conditions in real OWT projects.

Systematic investigation of structural, magneto-electronic, mechanical, thermophysical, optical and thermoelectric properties of Hf2VZ (Z = Ga, In, Tl) inverse Heusler alloy for spintronics applications

Systematic investigation of structural, magneto-electronic, mechanical, thermophysical, optical and thermoelectric properties of Hf2VZ (Z = Ga, In, Tl) inverse Heusler alloy for spintronics applications

Quantifying the association between PM2.5 air pollution and IQ loss in children: a systematic review and meta-analysis

Abstract Background A growing body of epidemiologic and toxicologic literature indicates that fine airborne particulate matter (PM2.5) pollution is neurotoxic and threatens children’s neurobehavioral development, resulting in reduced cognitive function. Understanding the magnitude of this effect is critical for establishing public health policies that will protect children’s health, preserve human capital, and support societal progress. Objective To quantify the association between ambient PM2.5 air pollution and loss of cognitive function in children, as measured by Intelligence Quotient (IQ) scores, through a systematic literature review and meta-analysis. Methods Following PRISMA guidelines, we conducted a systematic literature search across seven databases: Agricultural and Environmental Science, BIOSIS Citation Index, Embase, GreenFILE, PubMed, Scopus, and Web of Science to identify original scientific studies that investigated the impact of PM2.5 exposure during pre-and postnatal periods on IQ loss during childhood. Using data from studies included for final review, we conducted a meta-analysis, using a random effects model to compute a beta coefficient that quantifies the overall effect of PM2.5 exposure on Full-Scale IQ (FSIQ), Performance IQ (PIQ), and Verbal IQ (VIQ). Findings Of the 1,107 unique publications identified, six studies met the inclusion criteria for final review, representing 4,860 children across three continents (North America, Europe, and Asia). The mean PM2.5 concentration across all studies was 30.4 ± 24.4 µg/m3. Exposure timing ranged from the prenatal period to mid-childhood. Children were an average of 8.9 years old at the time of cognitive testing. We found that each 1 µg/m3 increase in PM2.5 concentration is associated with a -0.27 point change in FSIQ (p < 0.001), 0.39 point change in PIQ (p = 0.003), and -0.24 point change in VIQ (p = 0.021). Conclusion Through a systematic review and meta-analysis, we identified a statistically significant relationship between increased exposure to PM2.5 air pollution and reduced cognitive function in children, with the most pronounced impact on PIQ. This analysis will enable estimation of the burden of adverse neurobehavioral development attributable to PM2.5 in pediatric populations and will inform local and global strategies for exposure prevention.

The 30th anniversary of “The History and Geography of Human Genes”

On the occasion of the 30th anniversary of the publication of “The History and Geography of Human Genes”, the story of its origin and motivation is revisited by looking at nearly two decades of work that the book required. By describing details of activities that now have been abandoned thanks to technological advances, we try to communicate the irreplaceable importance of the motivational bases of research. We then look at the remarkable 30 years of the book’s life from its diffusion to the stability and longevity of its citation history, along with its inspirational impact on the scientific inquiries in many different fields.

Determination of the cover coefficient for soil surfaces of the runoff of residential areas

Due to the constant increase in tariffs in the field of public utilities, the problem of the need for accurate calculation of the volume of surface runoff is becoming more acute, which must take into account not only the landscape features of the area, but also the water-absorbing properties of the soil and coatings. The purpose of this work is to determine the coefficient of coverage zi for the most characteristic types of natural and artificial surfaces. The scientific novelty lies in the refinement of the existing methodology set out in the “Recommendations of the State Scientific Research Center of the Russian Federation FSUE Scientific Research Institute VODGEO”, in particular, the establishment of a mathematical dependence of the value of the coefficient of cover zi on the fractional composition of the soil to determine the coefficient of surface runoff Ψ, on which commercial calculations for the drainage of rain and meltwater into the storm sewer system are based.

Concept of architectural formation of construction production complexes in the cities of Donbass

The scientific research is a continuation of the author’s publications and for the first time provides a complete conceptual set of principles and techniques, systematically covering all levels of the architectural and planning organization of construction production complexes. A concept for the architectural formation of construction industrial complexes in the cities of Donbass is proposed, which includes recommendations for the formation of these complexes. The urban planning approach to the selection of territories of non-operating coal mines is generalized. An analysis of existing buildings and structures of the coal mine and the features of construction production complexes was also carried out.

Cost-effectiveness analysis of mHealth applications for depression in Germany using a Markov cohort simulation

AbstractRegulated mobile health applications are called digital health applications (“DiGA”) in Germany. To qualify for reimbursement by statutory health insurance companies, DiGA have to prove positive care effects in scientific studies. Since the empirical exploration of DiGA cost-effectiveness remains largely uncharted, this study pioneers the methodology of cohort-based state-transition Markov models to evaluate DiGA for depression. As health states, we define mild, moderate, severe depression, remission and death. Comparing a future scenario where 50% of patients receive supplementary DiGA access with the current standard of care reveals a gain of 0.02 quality-adjusted life years (QALYs) per patient, which comes at additional direct costs of ~1536 EUR per patient over a five-year timeframe. Influencing factors determining DiGA cost-effectiveness are the DiGA cost structure and individual DiGA effectiveness. Under Germany’s existing cost structure, DiGA for depression are yet to demonstrate the ability to generate overall savings in healthcare expenditures.

Interrelationships between affective disorders in the form of depression and obesity and overweight - A systematic review

Both depression and obesity are significant health, social and economic problems. Depressive disorders were the second most common psychiatric disorder in 2017 after anxiety disorders. According to data published by the World Health Organization (WHO), depression affects about 280 million people worldwide, which is about 3.8 percent of the population. The etiology of depressive disorders is very complex and still not fully understood. The theories described so far complement each other. The factors underlying the development of depressive disorders can be divided into biological, psychological and other factors. Eating disorders in the form of overweight and obesity result from a loss of balance between anabolic and catabolic processes. This is most often led by insufficient physical activity and excess caloric intake. Hormonal disorders, genetic factors and environmental factors may also play an important role in the pathogenesis of obesity. The steadily increasing number of people suffering from depression and obesity prompts the search for links between these two seemingly unrelated disease entities. According to current knowledge, these diseases are bi-directionally linked by genetic, psychological, metabolic and social factors. Depression is associated with an increase in the risk of obesity by about 37% relative to those without depression. Obesity is associated with an increase in the risk of depressive disorders by about 18%. Understanding the links that exist between depressive disorders and obesity enables the search for new therapeutic options. The most important conclusion from the scientific research conducted so far is the advantage of simultaneous treatment of obesity and depression over treating these disease entities individually.

Aromatic Serenity: How Lavender Eases Stress and Anxiety - A Literature Review

In today's fast-paced society, rising stress levels necessitate effective management strategies. While pharmacological treatments are common, their side effects have spurred interest in alternative therapies, particularly those rooted in natural remedies. Lavender (Lavandula angustifolia), long esteemed for its calming properties, has emerged as a promising non-pharmacological option. Historical use in herbal medicine for anxiety and stress-related disorders has inspired modern scientific research to explore its potential. This review synthesizes recent studies on lavender essential oil, examining its mechanisms—such as neurotransmitter modulation—and its effectiveness in diverse settings, from reducing stress among healthcare professionals to improving sleep quality. Despite promising results, limitations like small sample sizes and variability in application methods highlight the need for more rigorous research to establish lavender's efficacy and optimize its therapeutic use in stress management and mental health care.