Ethical Practice Research Articles

Technological Processes Applied to Laboratory Animal Feeds and New Feeding Approaches

Laboratory animal nutrition plays a crucial role in ensuring the health, welfare, and scientific validity of research studies involving animals. Technological advancements in feed processing have provided researchers with innovative tools and techniques to enhance the nutritional quality and stability of laboratory animal diets. Recent developments in feed processing technology have focused on improving the precision, consistency, and nutrient bioavailability of laboratory animal diets. Techniques such as pelleting, extrusion, and coating have been utilized to create homogeneous feed formulations with controlled nutrient profiles. In addition to advances in feed processing, new feeding approaches have emerged to address the specific nutritional requirements of laboratory animals. Precision feeding technologies, incorporating real-time monitoring systems and data analytics, allow for the customization of feed formulations based on individual animal needs. Overall, the integration of technological processes and new feeding approaches in laboratory animal nutrition represents a promising avenue for advancing animal welfare, research quality, and scientific outcomes in preclinical and biomedical research. By leveraging cutting-edge feed processing techniques and tailored feeding strategies, researchers can ensure the optimal nutrition, health, and well-being of laboratory animals, fostering both ethical research practices and robust scientific results. This review provides an overview of the technological processes applied to laboratory animal feeds and introduces new feeding approaches aimed at optimizing animal health and research outcomes.

Beliefs and Practices Levels Associated with Use of Performance Enhancing Substances and Methods among Mixed Martial Arts Athletes in Kenya

Mixed Martial Arts (MMA) has seen a surge in popularity in Kenya, with athletes from various backgrounds participating in the sport. However, with this growth comes an increased risk of performance-enhancing substances (PES) use. The intense physical demands of MMA may drive athletes to seek an edge through these substances, leading to significant concerns about health risks and sports integrity. The aim of this study is to assess the practices and beliefs regarding PES, traditional herbs (TH), and food supplements (FS) among Kenyan MMA athletes. Additionally, the study explores the sources of PES, the factors motivating their use, and the efficacy of current Anti-Doping testing practices. To conduct the study, a cross-sectional survey design was employed, sampling 800 athletes from a target population of 4,000 across six MMA federations. Data were collected using structured questionnaires adapted from the World Anti-Doping Agency (WADA) and the Performance Enhancement Attitude Scale (PEAS), with pre-testing to ensure reliability. Data analysis involved descriptive statistics and One- and Two-Way Analysis of Variance (ANOVA) using SPSS version 22. The results indicate that the majority of MMA participants are male (79.9%), with a median age of 25 years and a mean age of 26.8±4.1 years. Over half of the athletes perceived PES as a problem, but less than one-third viewed traditional herbs as a concern. Food supplements were used by nearly a fifth of the athletes, with bodybuilders showing the highest usage rate (44.4%). Coaches, team doctors, and physiotherapists were primary sources of these substances, while some athletes reported chemists and medical practitioners as suppliers of PES. The study found that the primary reasons for using PES and FS were to boost economic status through prize money, with additional pressures from coaches, family, and colleagues. Anti-doping testing revealed that 20.6% of athletes had been tested out of competition, while 34.4% believed they could provide a sample that wasn't theirs. The study concludes that while many MMA athletes recognize the risks associated with PES, there is a lack of consistent understanding regarding traditional herbs and food supplements. This inconsistency, combined with external pressures, may lead to risky behavior, compromising the athletes' health and the sport's integrity. To address these issues, the study recommends implementing comprehensive education programs for MMA athletes, coaches, and support personnel to raise awareness of PES risks. Strengthening anti-doping regulations and monitoring sources of PES and FS is also crucial. Additionally, promoting ethical coaching practices and addressing external pressures can foster a safer environment and uphold the values of fair competition in Kenyan MMA.

AI Through Ethical Lenses: A Discourse Analysis of Guidelines for AI in Healthcare

While the technologies that enable Artificial Intelligence (AI) continue to advance rapidly, there are increasing promises regarding AI’s beneficial outputs and concerns about the challenges of human–computer interaction in healthcare. To address these concerns, institutions have increasingly resorted to publishing AI guidelines for healthcare, aiming to align AI with ethical practices. However, guidelines as a form of written language can be analyzed to recognize the reciprocal links between its textual communication and underlying societal ideas. From this perspective, we conducted a discourse analysis to understand how these guidelines construct, articulate, and frame ethics for AI in healthcare. We included eight guidelines and identified three prevalent and interwoven discourses: (1) AI is unavoidable and desirable; (2) AI needs to be guided with (some forms of) principles (3) trust in AI is instrumental and primary. These discourses signal an over-spillage of technical ideals to AI ethics, such as over-optimism and resulting hyper-criticism. This research provides insights into the underlying ideas present in AI guidelines and how guidelines influence the practice and alignment of AI with ethical, legal, and societal values expected to shape AI in healthcare.

The Role of Machine Learning in Enhancing Risk Management Strategies in Financial Institutions

Purpose: The aim of the study was to examine the role of machine learning in enhancing risk management strategies in financial institutions. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study revealed that integration of machine learning into risk management strategies within financial institutions has demonstrated significant potential for enhancing decision-making processes and mitigating various risks. The study have consistently shown that machine learning algorithms outperform traditional statistical methods in areas such as credit risk assessment, fraud detection, market risk management, and loan portfolio optimization. These advancements have led to improved accuracy, efficiency, and timeliness in risk assessment, enabling financial institutions to make more informed decisions while reducing losses and enhancing overall performance. Unique Contribution to Theory, Practice and Policy: Modern Portfolio Theory (MPT), Efficient Market Hypothesis (EMH) & Agency Theory may be used to anchor future studies on role of machine learning in enhancing risk management strategies in financial institutions. Invest in building robust data infrastructure and governance frameworks to support the implementation of machine learning models in risk management practices. High-quality data is crucial for training accurate and reliable machine learning algorithms. Establish regulatory guidelines and standards for the responsible use of machine learning in risk management within the financial industry. These guidelines should address issues such as model transparency, fairness, and accountability to ensure ethical and responsible practices.

Influence of Artificial Intelligence on Credit Risk Assessment in Banking Sector

Purpose: The aim of the study was to examine the influence of artificial intelligence on credit risk assessment in banking sector. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study found that AI-driven models demonstrate superior performance in identifying risky borrowers and capturing complex credit risk patterns compared to traditional methods. Additionally, the integration of explainable AI (XAI) techniques has enhanced transparency and interpretability in credit risk assessment processes, facilitating better understanding among stakeholders and improving decision-making transparency. Unique Contribution to Theory, Practice and Policy: Decision theory & technology acceptance model (TAM) may be used to anchor future studies on influence of artificial intelligence on credit risk assessment in banking sector. Continuously invest in research and development to advance the theoretical understanding of AI-driven credit risk assessment models. This includes exploring the integration of machine learning with behavioral economics theories to better predict borrower behavior and default probabilities. Encourage banks to adopt a hybrid approach that combines the strengths of AI-driven models with human expertise. Develop comprehensive regulatory guidelines and standards to govern the use of AI in credit risk assessment and ensure ethical and responsible practices. This includes establishing transparent model validation and governance frameworks to mitigate the risks of algorithmic bias, data privacy violations, and discriminatory lending practices. Regulatory authorities should also promote industry-wide collaboration and knowledge sharing to foster innovation while safeguarding consumer interests and financial stability.

Evaluating the Problem of Fraudulent Participants in Health Care Research: Multimethod Pilot Study.

The shift toward online recruitment methods, accelerated by the COVID-19 pandemic, has brought to the forefront the growing concern of encountering fraudulent participants in health care research. The increasing prevalence of this issue poses a serious threat to the reliability and integrity of research data and subsequent findings. This study aims to explore the experiences of health care researchers (HCRs) who have encountered fraudulent participants while using online recruitment methods and platforms. The primary objective was to gain insights into how researchers detect and mitigate fraudulent behavior in their work and provide prevention recommendations. A multimethod sequential design was used for this pilot study, comprising a quantitative arm involving a web-based survey followed by a qualitative arm featuring semistructured interviews. The qualitative description approach framed the qualitative arm of the study. Sample sizes for the quantitative and qualitative arms were based on pragmatic considerations that in part stemmed from encountering fraudulent participants in a concurrent study. Content analysis was used to analyze open-ended survey questions and interview data. A total of 37 HCRs participated, with 35% (13/37) of them engaging in qualitative interviews. Online platforms such as Facebook, email, Twitter (subsequently rebranded X), and newsletters were the most used methods for recruitment. A total of 84% (31/37) of participants indicated that fraudulent participation occurred in studies that mentioned incentives in their recruitment communications, with 71% (26/37) of HCRs offering physical or electronic gift cards as incentives. Researchers identified several indicators of suspicious behavior, including email surges, discrepancies in contact or personal information, geographical inconsistencies, and suspicious responses to survey questions. HCRs emphasized the need for a comprehensive screening protocol that extends beyond eligibility checks and is seamlessly integrated into the study protocol, grant applications, and research ethics board submissions. This study sheds light on the intricate and pervasive problem of fraudulent participation in health care research using online recruitment methods. The findings underscore the importance of vigilance and proactivity among HCRs in identifying, preventing, and addressing fraudulent behavior. To effectively tackle this challenge, researchers are encouraged to develop a comprehensive prevention strategy and establish a community of practice, facilitating real-time access to solutions and support and the promotion of ethical research practices. This collaborative approach will enable researchers to effectively address the issue of fraudulent participation, ensuring the conduct of high-quality and ethically sound research in the digital age.

AI development in financial markets: a balanced scorecard analysis of its impact on sustainable development goals (February 2024)

PurposeThe primary purpose is to empower financial institutions in AI integration decisions. By combining QSFS and the Golden Cut technique, the study establishes a robust foundation for assessing AI progress effects, aligning implementation with performance goals, and promoting technical innovation. Dimensions explored include AI-related workforce competency, technological adaption, and ethical AI practices, crucial components within the BSC framework for technological innovation.Design/methodology/approachThis study employs a distinctive approach, integrating the Balanced Scorecard (BSC) framework with Quantum Spherical Fuzzy Sets (QSFS) and the Golden Cut approach to explore the dynamic landscape of AI deployment. The integration addresses uncertainties, enhancing impact assessment accuracy amid ambiguity associated with AI outcomes. QSFS and the Golden Cut technique together facilitate precise identification of thresholds and crucial values.FindingsThe research delves into the intricate relationship between enduring financial stability and AI progress, recognizing technology's crucial influence on financial decision-making. Findings underscore technology's significant impact on financial institutions' AI integration decisions. This novel approach provides a strong quantitative basis, offering insights into workforce competency, technological adaption, and ethical AI practices.Research limitations/implicationsDespite valuable contributions, the study acknowledges limitations, such as potential biases and generalizability concerns, emphasizing the need for cautious interpretation and suggesting future research directions. Recognizing the research's boundaries and complexities in studying AI deployment in financial institutions underscores the need for ongoing exploration.Originality/valueThe research's originality lies in presenting an innovative methodology, integrating BSC, QSFS, and the Golden Cut, providing a unique perspective for decision-making. Contributions extend beyond academia, offering practical insights to enhance AI strategic implementation in the financial industry. This novel approach enriches the technology and finance discourse, fostering theoretical and practical advancements.

Legal and Policy Implications in the Age of Social Media in South Africa

Purpose: The aim of the study was to examine the legal and policy implications in the age of social media in South Africa Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: The study revealed that privacy concerns, copyright infringement, cyberbullying, data protection regulations, content moderation, online political advertising, employer surveillance, and emerging technologies like deepfake, researchers have shed light on the evolving legal frameworks governing social media platforms. The study emphasized the critical need for enhanced privacy protection measures, transparent content moderation policies, comprehensive cyberbullying laws, and stricter regulation of online activities to safeguard users' rights and mitigate potential harms. Unique Contribution to Theory, Practice and Policy: Social Contract Theory, Diffusion of Innovations Theory & Network Society Theory may be used to anchor future studies on legal and policy implications in the age of social media in South Africa. Formulate policies that strike a balance between freedom of expression and the need to curb harmful content such as hate speech, misinformation, and online harassment. Legal frameworks should provide guidance on content moderation practices while safeguarding fundamental rights. Encourage social media companies to adopt ethical principles and practices that prioritize user well-being and societal good over profit maximization. This includes measures to combat online addiction, promote digital well-being, and mitigate the negative impacts of their platforms on mental health and democracy. This contributes to both legal theory and practice by emphasizing the role of corporations in upholding broader societal values.

Bringing To Light The Characteristics And Difficulties Faced By Female Entrepreneurs In The Garment Industry In The Pursuit Of Sustainable Production

The study explored the attributes and challenges faced by Filipino women entrepreneurs in the garment business who have been operating for at least 5 years in select cities in the Philippines. The research aimed to determine the entrepreneurs' attributes, problems and challenges they face, and use the findings to create an entrepreneurial model for business success. The attributes of the women entrepreneurs differed based on factors like age, years in business, marital status, number of children, education level, and whether they dreamed of being an entrepreneur as a child. There were significant differences in their personality traits, goal orientation, appreciation of support networks, and socially responsible attributes when considering these demographic factors. The respondents viewed issues like balancing work/family, risk aversion, negotiation skills, male discrimination, lack of family support and financial constraints as neutral challenges. However, their socially responsible attributes were linked to self/family/social problems, while goal orientation related to marketing/mobility issues. Most respondents considered themselves successful or very successful business owners. The proposed entrepreneurial model emphasizes that successful women entrepreneurs must have: a positive personality, goal orientation, appreciation for networking/teamwork, adherence to ethical practices, responsibility to society/environment, and the ability to balance work/life commitments. The recommendations include strengthening continuing education for entrepreneurs, disseminating information on government support programs, and enhancing gender equality in business lending from banks.

What does TikTok have to do with it? Experiences of Young Adults with Social Media and Life Satisfaction: A Qualitative Analysis of Influences

This qualitative study investigates the impact of TikTok usage on the life satisfaction and its contribution towards self-actualization of young adults aged 18-25. Adopting a phenomenological approach, the research explores the experiences and perceptions of TikTok engagement and its relation to the life satisfaction of five young adults. Six main themes emerged for the analysis: 1) Love & Belonging, 2) Influence, 3) Life Satisfaction, 4) Self-Esteem and Identify, 5) Mood, and 6) Risks and Challenges. These findings uncover various aspects of TikTok use, such as content consumption patterns and emotional responses, offering insights into the nuanced ways TikTok influences young adults' perceptions of their lives and contribute to a deeper understanding of the relationship between the platform engagement and life satisfaction. Furthermore, this research underscores the importance of social workers' role in advocating for ethical social media practices and clinical interventions tailored to address the impacts of social media on the overall wellbeing of young adults.

Exploring Regulatory Dimensions in Computing and Artificial Intelligence through Comprehensive Analysis

Computing and artificial intelligence (AI) are advancing at a pace that offers opportunities to benefit human life, from healthcare and education to transportation and entertainment. However, they also pose a variety of ethical dilemmas that society will need to solve to ensure that their use is responsible and just. This study provides an inclusive examination of the ethics of computing and AI, making a comprehensive consideration based on the history of past practices currently prevailing and prospects. By integrating quantitative data with qualitative observations over a mixed-method approach, the study captures much of the complexity and depth of the ethical field. Many results raise concerns about ethics, particularly in the areas of privacy, autonomy, and bias. The authors offer a variety of practical recommendations to developers, policy-makers, and users on the basis of these reflections to help encourage the practice of ethics in AI development and deployment. Focusing on transparency, accountability, and inclusion in AI systems, these recommendations argue for the development of strong ethical standards and oversight mechanisms for the increasingly complex ethical landscape of AI and computing technologies. This study addresses these challenges, aiming to help change the way AI is experienced across society by developing innovations while enhancing efficiency and delivering them fairly and justly to create a world in which an unequal distribution of AI opportunities does not exist.

Catalyzing Ethical Business Practices: Exploring the Role of Islamic Finance in Contemporary Markets

Catalyzing Ethical Business Practices: Exploring the Role of Islamic Finance in Contemporary Markets

Eco-chic or trendy-chic? Decoding consumer preferences in sustainable and fast fashion across the EU

Abstract The ongoing transformation of the fashion industry is driven by an increasing focus on sustainability, ethical practices, and responsible consumer behavior. Simultaneously, social media platforms have emerged as influential forces in this field, shaping fashion trends and consumer preferences. Despite a substantial body of literature investigating consumer preferences between fast and sustainable fashion, a gap in understanding the intricate relationship between fashion preferences, socio-economic profiling, and social media engagement is evident. Thus, this research was aimed at comparatively decoding EU consumers’ preferences for fast fashion against sustainable fashion by exploring the interplay of demographic factors ‒ age, gender, and geographical location ‒ on fashion preferences, as expressed through the digital engagement with fashion-related content on the Meta social platforms. The research methodology implied resorting to logistic regression analysis, aiming to uncover the underlying patterns that fundamentally characterize consumers’ preferences for fashion in the EU. The results provide novel insights into how digital engagement with fashion-related content can act as a barometer for regional fashion identities and preferences, useful for the identification of both convergence and inflection points. Moreover, findings offer a robust foundation for crafting strategies that promote sustainable fashion practices, tailored to specific EU age, gender, and location demographics, by leveraging the insights gained about EU consumer preferences.

SOCIO-ECONOMIC SIGNIFICANCE OF INTERNAL AUDIT IMPROVEMENT IN THE REPUBLIC

Improving internal audit processes plays a crucial role in shaping socio-economic landscapes in various sectors. This improvement has significant implications for financial integrity, fraud prevention, compliance, governance, operational efficiency, risk management, investor confidence, job creation, public trust, innovation, growth and global competitiveness. By ensuring clarity, transparency and ethical practices, improved internal audits contribute to a sustainable and prosperous economy, while building trust among stakeholders and attracting investment.

The rise of intelligent procurement: Embracing AI and data analytics for crossfunctional synergy

This paper delves into the transformative role of procurement in modern corporate structures, especially in North American businesses, highlighting its evolution from a transactional function to a strategic asset within organisations. The core aim is to explore how technological advancements, particularly in data analytics and cognitive artificial intelligence (AI), are redefining procurement’s role, facilitating cross-functional collaboration and driving innovative practices. The scope of this paper encompasses the historical perspective of procurement’s underestimated strategic potential, its current integration into various organisational facets and the profound impact of AI and data analytics in enhancing procurement’s efficacy and strategic value. Readers can expect to gain a comprehensive understanding of the strategic transformation of procurement, particularly how it has moved beyond traditional cost management to become a central player in innovation, risk management and sustainability efforts. The paper provides insights into the practical applications of data analytics and AI in procurement, showcasing how these technologies enable predictive decision making, enhance supplier relationship management and contribute to effective risk assessments and budget forecasting. The paper also underscores procurement’s growing influence in strategic decision making and its critical role in fostering cross-functional partnerships. Readers will also learn about the increasing importance of trust and ethical practices in procurement, reinforcing their position as a vital component of organisational success. Ultimately, the reader will be equipped with the essential knowledge to understand the evolving landscape of procurement, its strategic implications and the potential of AI and data analytics in shaping future procurement practices.

Headspace gas chromatography with various sample preparation and chemometric approaches to improve discrimination of wild and feeding civet coffee

Abstract Civet coffee, or kopi luwak, has attracted significant attention within the coffee industry in certain regions due to its distinct flavor characteristics that arise from the digestive processes of the civet. The ability to discriminate between wild and feeding civet coffee is of major importance in upholding the industry’s established standards of quality and transparency. This study introduces an innovative method to differentiate between these two coffee types using Headspace Gas Chromatography-Mass Spectrometry (HS-GCMS) with advanced data analysis using machine-learning techniques. This study encompasses seven samples collected from various regions, all of which were subjected to analysis in both roasted and unroasted forms. The data analysis consisted of Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), which revealed clear trends that were mostly influenced by processing, indicating how roasting affects the chemical profiles of various coffee types. Further classification was conducted using Support Vector Machine (SVM) and Random Forest (RF) machine learning algorithms. SVM exhibited notable accuracy at 90%, effectively discriminating between wild and feeding civet coffee, whereas RF outperformed it with a remarkable 100% accuracy. This study contributes to the field of coffee characterization by presenting a robust approach to discriminate between roasted and unroasted wild and feeding civet coffee. This tool serves as a starting step for a valuable resource for both farmers and customers, as it promotes sustainable and ethical practices while retaining the distinct flavor characteristics of this exceptional specialty coffee.

Through Patients' Eyes: Evaluating the Consent Process in Elective Orthopedic Surgery at a Tertiary Referral Center in Ireland.

Informed consent is a critical component of ethical clinical practice, particularly in elective orthopedic procedures. It ensures that patients understand the nature, benefits, and risks of the medical procedures they agree to undergo. This study aims to evaluate the informed consent process at Merlin Park University Hospital from the patient's perspective. This cross-sectional observational study included 140 participants undergoing elective orthopedic procedures. Data were collected via a questionnaire focusing on socio-demographic information and the informed consent process, including details on who provided the information, where and when the consent was signed, and patient understanding and satisfaction. Responses were analyzed using SPSS version 26 (IBM Corp., Armonk, NY). The majority of participants were females, with 80 (57.1%) women and 60 (42.9%) men. The average age of the participants was 60.86 years. Most participants were employed, constituting 75 (53.6%) of the sample, and 55 (39.3%) had attained university or higher education. The most common procedures were total hip replacement, with 30 (21.4%) participants, and total knee replacement, with 20 (14.3%) participants. Information during the consent process was primarily provided by consultants in 80 (57.1%) cases. High satisfaction levels were reported, with 139 (99.3%) participants expressing satisfaction. Significant correlations were found between satisfaction and the type of healthcare provider, type of operation, and educational level. The informed consent process at Merlin Park University Hospital is generally effective, with high patient satisfaction and understanding. However, there is a preference for concise information delivery. Enhancing the process through personalized information delivery could further improve patient satisfaction and comprehension. These findings contribute valuable insights into patient-centered care and informed consent in elective orthopedic surgeries.

CINDERELLA clinical trial: Using artificial intelligence–driven healthcare to enhance breast cancer locoregional treatment decisions.

TPS621 Background: Breast cancer treatments often pose challenges in balancing efficacy with quality of life. The CINDERELLA Project pioneers an artificial intelligence (AI)-driven approach (CINDERELLA APP) for shared decision-making process, aiming to harmonise locoregional therapeutic interventions with breast cancer patients' expectations about aesthetic outcomes. The CINDERELLA clinical trial aims to establish a new standard in patient-centred care by bridging the gap between clinical treatment options and patient expectations through innovative technology. The trial focuses on evaluating the effectiveness of the CINDERELLA APP in improving patient satisfaction regarding locoregional treatment aesthetic outcomes, aligning patient expectations with real-world results, and assessing its impact on overall quality of life and psychological well-being. Methods: Trial design and statistical methods: This international multicentric interventional randomised controlled open-label clinical trial will recruit and randomise patients into two groups: one receiving standard treatment information and the other using the AI-powered CINDERELLA APP. The primary objective is to assess the levels of agreement among patients' expectations regarding the aesthetic outcome before and 12 months after locoregional treatment. The trial will also evaluate the aesthetic outcome level of agreement between the AI evaluation tool and self-evaluation. The impact of the intervention on aligning expectations with outcomes will be evaluated using the Wilcoxon signed-rank test. The improvement in classification of aesthetic results post-intervention will be measured by calculating the Weighted Cohen's kappa. Outcomes across different groups will be compared using statistical tests and bootstrap methods. CANKADO functions as the base system, allowing doctors to supervise APP content for patients and handle data gathering, while upholding principles of privacy, data security, and ethical AI practices. Intervention planned: Using the CINDERELLA APP, the patient will have access to supervised medical information approved by breast cancer experts, and the AI system will match patient's information to pictures showing the potential aesthetic outcome (spectrum of good-poor) according to different locoregional approach. Major eligibility criteria: Non-metastatic breast cancer patients eligible for either breast-conserving surgery or mastectomy with immediate reconstruction. Current enrollment: Recruitment is currently open at six study sites. The recruitment started on 8 August 2023, aiming to enroll at least 515 patients/arm. As of January 26, 2024, clinical study sites have successfully randomised 177 patients. Clinical trial information: NCT05196269 .

A NEW APPROACH TO CREATE SUSTAINED PONZI-LIKE SYSTEMS BY INCORPORATING PERPETUAL LIQUIDITY AND TIME EPOCHS

This paper leverages the transformative capabilities of blockchain technology to introduce a new approach to developing Ponzi-like systems by integrating perpetual liquidity and time epochs within immutable smart contracts. Blockchain’s transparent nature establishes a foundation for trust in the ecosystem. Departing from the unsustainable nature and inevitable collapse associated with traditional Ponzi schemes, the proposed framework ensures continuous token availability, mitigating supply depletion and thus minimizing system failure risk. The introduction of time epochs is a key feature that enhances the sustainability of our system. It enables continuous rebalancing, predictability, and transparency within the system. Through predetermined intervals, users can claim a percentage of tokens from previous epochs, ensuring a fair distribution mechanism and preventing stagnation. This predictable cycle fosters the user’s confidence in the longevity of the protocol. The mechanics of the proposed system are designed to incentivize rational behaviour and trust among participants. Users are motivated to contribute to the ecosystem, knowing that their efforts will be reciprocated with proportional rewards. We design, implement and present the new model as a paradigm shift in Ponzi-like structures. Through a multidisciplinary lens encompassing economics, game theory, and sustainable development, this research aims towards fostering long-term viability and ethical financial practices.

Telepsychology: Key recommendations for ethical, legal, and effective practice.

Telepsychology: Key recommendations for ethical, legal, and effective practice.