Research Paper Research Articles

Surrogate motherhood as a right of procreational will for infertile couples in Ecuador

This research paper contributes to the regulation of surrogacy in Ecuador, a controversial topic that has gained attention in scientific and social circles. Although the practice is not legally regulated, there has been an increase in discussion and interest in this topic in the country. The objective is to examine the Ecuadorian regulations and jurisprudence applicable to the regulation of surrogate motherhood considering ethical and social principles. It was based on a historical, normative and jurisprudential study. The qualitative methodology was applied, by means of the empirical analytical method that allowed analyzing the opinions of experts in family law, human rights and bioethics, and evaluating how surrogate motherhood would be integrated within the existing legal framework in Ecuador, which requires further research and an informed debate to structure a legal and ethical framework that regulates surrogate motherhood in Ecuador. We were able to conclude the potential impact that surrogacy has in terms of equity and reproductive justice, as well as in the integral protection of the rights of all parties involved. However, it must be recognized that this discussion must encompass a variety of perspectives, including the opinions of experts in bioethics, reproductive medicine and psychology.

Techno-economic process design of multi-stage flash- reverse osmosis for water and power production using solar-wind resources

This paper introduces a newly developed hybrid power plant design that combines renewable energy sources to produce both electricity and freshwater. The design offers a higher gain output ratio (GOR) and improved efficiency in power and freshwater production, all at a lower cost compared to existing research papers. To generate power, the power plant incorporates a range of technologies, such as a horizontal-axis wind turbine (WT), photovoltaic panels (PV), parabolic trough collectors (PTC), a steam Rankine cycle, a multi-stage flash (MSF) desalination unit that cleverly harnesses excess heat from the Steam Rankine cycle, and an Reverse osmosis (RO) unit. With the assistance of ASPEN Plus, ASPEN Economic, and HOMER PRO software, the process parameters undergo significant improvement. According to the results, the power plant has the capacity to generate 57.63 MW of electricity and produce 2505 m3h of freshwater. Additionally, it has a GOR of 9.09 and utilizes 7285 m3h of seawater, which has a renewability factor of 97.6 %. In addition, the efficiency of the steam Rankine cycle stands at 32 %, providing notable energy savings. The production costs for electricity and freshwater are 0.037 $kW and 1.38 $m3, respectively, indicating their affordability. The economic analysis reveals promising results for the project, with an anticipated annual profit of 41 % and a relatively short capital payback period of 2.4 years. By implementing the proposed hybrid cogeneration power plant, the region can tackle its water and energy scarcity issues with a sustainable and long-lasting solution.

Determinants of External Debt in Developing Countries: The Case of Algeria

Background: Developing countries seek to eliminate external debt problems towards financial obligations with a view of alleviating the debt burden to avert economic volatility in the context of debt accumulation. Since the beginning of the 1970s, developing countries, including Algeria, have experienced rapid growth in external debt accumulation in an effort to finance domestic deficits and not enter into economic recession. All these reasons ignore the topic of external debt as an interesting topic of study. This study attempts to analyse and measure some of Algeria's external debt indicators during the study period. Purpose: This research paper focuses on identifying the determinants of external debt in Algeria. Methods: The study utilized the autoregressive distributed lag (ARDL) model and cointegration test to analyze both short- and long-term relationships among the study variables from 1990 to 2021. Results: The findings show that the exchange rate and government spending significantly and positively impact external debt in the long run, whereas GDP per capita and foreign direct investment are significantly negatively correlated with external debt. The short-term results align with those of the long term. Conclusions: The paper advises that the Algerian government and other developing countries should assess their foreign debts, rationalize government spending, diversify their economies, and enhance their investment climates.

Sustainability and resilience interface at typical urban green and blue infrastructures: costs, benefits, and impacts assessment

The rapid urbanization witnessed in recent years has led to the deterioration of urban ecosystems, resulting in various environmental and socioeconomic challenges. In response to these concerns, the implementation of Green and Blue Infrastructures (GBI) has gained prominence as a sustainable urban planning approach. GBI is a planned network system of natural and semi-natural spaces, along with other environmental elements, managed and designed to provide a wide range of ecosystem services and improve ecological conditions, thereby contributing to citizens' wellbeing and quality of life. This study presents a comprehensive assessment of the costs, benefits (ecosystem services), and impacts (ecosystem dis-services) associated with the incorporation of GBI in urban environments using the technique of emergy accounting. To achieve this, the research paper introduces a novel integrated valuation framework. This framework encompasses key components such as constructing/maintenance costs, ecosystem services, needed costs to human health and biodiversity damage, as well as ecosystem dis-services. Furthermore, the study conducts a comparative analysis of the costs, benefits, and impacts associated with different urban GBIs via ternary phase diagram, shedding light on their varying contributions to the urban ecosystem. The findings reveal that green roofs offer more ecosystem benefits as compared to other GBIs, but this study also highlights that green roof entail higher initial construction costs and produce a greater number of dis-services. Conversely, street trees have lower initial costs and impacts yet generate higher benefits. Furthermore, green walls, despite having a lower input emergy value and fewer benefits, result in higher impacts compared to other green-blue ecosystems. These findings provide valuable insights for urban planners, policymakers, and stakeholders, enabling them to make informed decisions in developing sustainable cities for the wellbeing of present and future generations.

Gender representation and stereotyping in Moroccan print media coverage of the 2023 Haouz Earthquake

ABSTRACT Natural crises often amplify and reflect preexisting societal inequalities, with varying impacts on women across different regions. This research paper examines gender representation in the visual coverage of the 2023 Haouz earthquake. Data was collected from images published in Morocco's leading Arabic newspapers – Assabah, Bayanalyawm, and Alayam. The study analyzes how these visuals frame gender and argues that they reinforce existing gender stereotypes and cultural norms in Moroccan society. The coverage often portrayed women in limited, gender-specific roles, depicting them primarily as helpless victims. While this approach elicited sympathy from readers and donors, motivating immediate support for those affected, it may also have exploited the politics of sympathy, inadvertently perpetuating gender stereotypes.

THE IMPACT OF ADMINISTRATIVE EMPOWERMENT OF EMPLOYEES IN ENHANCING THE ADOPTION OF HUMAN RESOURCES GOVERNANCE PRINCIPLES ACCORDING TO ISO 30804 STANDARD - A FIELD STUDY OF THE ALGERIAN ELECTRICITY PRODUCTION COMPANY, M'SILA UNIT

Objective: This study evaluates administrative empowerment application among employees at M'Sila Unit, assesses adherence to human resources governance principles, and analyzes the relationship between empowerment and governance. It aims to determine if empowerment positively influences human resource governance. Theoretical Framework: The theoretical framework outlines the concepts of administrative empowerment and human resources governance. It discusses the role of organizational structure, self-determination theory, and stakeholder theory in empowering employees. It also discusses the importance of balancing stakeholder interests and addressing agency problems. The framework suggests citing relevant literature, visual representation, and real-world examples to support the research and understanding of the relationship between administrative empowerment and HR governance. Method: The research design, participants, questionnaire development, data collection procedure, statistical tools, reliability and validity, and limitations of the method are all essential aspects of a research study. The study's objectives, target population, sample size, sampling technique, questionnaire structure, data collection procedure, ethical considerations, and statistical tools used are also discussed. The method section should include examples, flowcharts, diagrams, and pilot studies for clarity. Results and Discussion: The study focuses on administrative empowerment and HR governance principles in the Algerian Electricity Production Company. Descriptive statistics are presented, along with correlation and regression analyses. Key findings highlight the positive impact of administrative empowerment on HR governance principles. The study's findings are compared with existing literature, theoretically and practically, and provide actionable recommendations for improvement. Limitations include sample size and generalizability issues. Future research should address these limitations. Research Implications: The research on administrative empowerment and human resources governance at the Algerian Electricity Production Company - M'Sila Unit has significant theoretical and practical implications. It contributes to existing literature, validates existing theories, and proposes new theories. Practical implications include organizational strategies, policy development, and training programs. The research also impacts human resources practices, employee engagement, performance management, and the broader energy sector. Future research directions include exploring gaps and promoting longitudinal studies. The findings emphasize the importance of addressing the relationship between empowerment and HR governance for organizational effectiveness. Originality/Value: The Originality/Value section of a research paper highlights the unique contributions and significance of a study on administrative empowerment and human resources governance at the Algerian Electricity Production Company - M'Sila Unit. It identifies gaps in existing literature, provides context-specific insights, and uses an innovative methodology. The research also offers practical recommendations and policy implications, enhancing employee engagement and organizational performance. It also provides a foundation for future studies in management and human resources.

Stablecoins for Transferring Value in the Cryptocurrency Market

Stablecoins have gained prominence as an effective means to mitigate the inherent volatility in the cryptocurrency markets by providing a stable and reliable medium for value preservation and transfer. This research paper investigates the attributes that render stablecoins a preferable vehicle for value retention and transaction within these markets. By employing a quantitative methodology, this study collected data through surveys, with a sample size of 714 individuals chosen via purposive sampling techniques. To analyze the data, both descriptive and inferential statistical methods were applied. The demographic profiles of the sample were summarized using descriptive statistics such as frequencies and percentages. For examining the relationships between demographic factors (such as gender, age, education, income, and place of residence) and the perceived efficacy of stablecoins, inferential techniques including Chi-square tests and logistic regression were utilized. The logistic regression analysis specifically assessed how these variables influenced the likelihood of participants favoring stablecoins for financial transactions. The results indicate that the preference for stablecoins as a means of holding or transferring value within the cryptocurrency domain in Thailand varies significantly across different demographic groups, specifically influenced by factors such as gender, education, income, and place of residence. These outcomes provide insightful implications concerning the demographic influences on the adoption and utilization of stablecoins in financial activities. Keywords: stablecoin, holding, transferring, value, cryptocurrency market

Quantifying Influence: Propensity Score Matching Unravels the True Effect Sizes of Learning Management Models on Students’ Analytical Thinking

<p style="text-align:justify">Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.</p>

The case study– a useful research strategy in the field of military sciences

This article argues for the usefulness of adopting the case study as an effective and sufficient strategy from the perspective of developing research papers in the field of Military Science. In the first stage, using Saunders’ model, I showed the logical course of a researcher’s reasoning up to the moment of establishing a suitable research strategy according to his object of study, the topic of interest or the problem formulated at the initiation of the scientific approach. Afterwards, I justified the motivation for choosing the case study as a research strategy, bringing to attention the main advantages and disadvantages that it entails. I thus had two objectives in writing this article: to emphasize the importance of clarifying and establishing certain research design, exemplified by going through the layers of Saunders’ model, and subsequently to highlight the versatility and flexibility of the case study as a research strategy, as it is accepted and used in all fields of scientific research.

Perceptions on service quality at licensing service centres

Organisations in the public sector are faced with challenges in the delivery of high-quality services to clients. This research paper reports on a study conducted to determine clients’ perceptions of service quality at licensing service centres (LCSs) in the City of Tshwane (CoT) Metropolitan Municipality, South Africa. The research adopted a quantitative approach to realise the research objective. A convenience sampling method was used to collect primary data. 262 respondents participated in the research. A structured questionnaire was used to collect primary data from respondents. The research used the SERVPERF instrument to measure service quality. Respondents were asked to rate the level of service at LSCs. The descriptive data analysis method was used to analyse the primary data with the aid of a statistical software package, Statistical Package for Social Sciences (SPSS). Cronbach's alpha values were used to measure the internal consistency and reliability of the measurement scales. The results revealed that all rated service quality dimensions were average, which means that respondents neither agreed nor disagreed with statements about the level of service offered by LSCs. The research paper includes recommendations on the continuous improvement of service quality at LSCs and on future research directions.

Detecting play behaviour in weaned dairy calves using accelerometer data.

This research paper describes a validation study evaluating the ability of IceTag accelerometers (Peacock Technology, UK) to detect play behaviour in weaned dairy calves. Play behaviour is commonly observed in young animals and is regarded as an indicator of positive welfare states. Eight Holstein Friesian calves aged three to five months old were monitored using leg-mounted accelerometers for 48 h. Data generated by accelerometers to quantify calf activity included step count, lying times and a proprietary measure of overall activity termed 'motion index' (MI). Calf behaviour was filmed continuously over the same 48-h period using closed circuit television cameras and analysed using one-zero sampling to identify the presence (1) or absence (0) of play within each 15-min time period. A positive correlation between MI and visually recorded play was found. Visual observations were compared with accelerometer-generated data and analysed using 2 × 2 contingency tables and classification and regression tree analysis. A MI value of ≥69 was established as the optimum threshold to detect play behaviour (sensitivity = 94.4%; specificity = 93.6%; balanced accuracy = 94.0%). The results of this study suggest that accelerometer-generated MI data have the potential to detect play behaviour in weaned dairy calves in a more time efficient manner than traditional visual observations.

Transforming Governance Through Public Participation: A Model for Voting on Manifestos and Tax Allocation

This research paper explores the potential of transforming governance by shifting the focus of electoral participation from individual candidates to their manifestos, alongside proposing a public voting mechanism for tax allocation. By integrating blockchain technology, this model aims to enhance transparency, accountability, and citizen engagement in the democratic process. It posits that decentralizing authority and empowering the public can mitigate corruption and promote a more responsive government aligned with community needs.

Substituting imported soybean meal with locally produced novel yeast protein in concentrates for Norwegian Red dairy cows: implications for rumen microbiota and fatty acid composition.

This research paper addresses the hypothesis that substituting soybean meal with locally produced yeast protein from Cyberlindnera jadinii in barley-based concentrates for Norwegian Red (NR) dairy cows does not have adverse effects on milk fatty acid (FA) composition, rumen microbiota and sensory quality of milk. As soybeans also represent valuable protein sources for human consumption, alternative protein sources need to be investigated for animal feed. A total of 48 NR dairy cows were allocated into three feeding treatments, with the same basal diet of grass silage, but different concentrates. The concentrates were all based on barley, but 7% of the barley in the barley-concentrate (BAR; negative control) was replaced by either soybean meal (SBM; conventional control) or yeast microbial protein (YEA). The experiment lasted for a total of 10 weeks, including 2 weeks of adaptation with the soybean meal concentrate. Analysis of the feed revealed some differences in the FA composition of the YEA concentrate compared to the SBM and BAR concentrates. In milk, only two FAs (C17:1n-8cis9 and an unidentified isomer of C18:3) were significantly different between the YEA- and SBM-group, while six FAs differed between the BAR- and SBM-group. However, the amount of these FAs was low compared to the entire FA profile (<0.7 g/100 g). The experimental diets did not affect rumen microbiota nor the milk sensory quality. This study shows that C. jadinii can replace soybean meal as a protein source in concentrates (7% inclusion) for NR dairy cows fed a diet composed of grass silage and concentrates without any effects on rumen microbiota, and without compromising the FA composition or sensory quality of milk.

Blockchain Enabled Secure Data Transmission With NB‐IoT Deployment in Smart Agriculture Crop Watch

ABSTRACTThe integration of Narrowband Internet of Things (NB‐IoT) and blockchain technology presents a promising solution to address security and efficiency concerns in data transmission within the Internet of Things (IoT). This research focuses on its application in crop Watch, an agricultural monitoring system. The IoT has revolutionized various industries, including agriculture, by facilitating the collection and transmission of extensive data through sensors and devices. However, ensuring secure and efficient data transmission remains a critical challenge. NB‐IoT boasts advantages such as improved coverage in challenging areas, massive connectivity with up to 100 000 links, low energy usage through prolonged discontinuous receipt (eDRX), and cost‐effectiveness. Despite these benefits, NB‐IoT faces security issues, including authentication, anonymity, and fault tolerance. To enhance data security, public key cryptography is proposed to be incorporated into the NB‐IoT framework. Blockchain technology, with its decentralized and immutable nature, can potentially address these security concerns and enhance data accountability. By creating a trust‐less and transparent infrastructure, blockchain complements NB‐IoT's capabilities and provides a robust mechanism for data verification and integrity. This research paper emphasizes the logical integration of NB‐IoT, public key cryptography, and blockchain technology, offering a secure and efficient data transmission framework for agricultural applications like crop Watch. Bridging the gap between data connectivity and security holds promise for advancing agricultural monitoring and driving IoT innovations.

Vertical back movement of cows during locomotion: detecting lameness with a simple image processing technique.

This research paper proposes a simple image processing technique for automatic lameness detection in dairy cows under farm conditions. Seventy-five cows were selected from a dairy farm and visually assessed for a reference/real lameness score (RLS) as they left the milking parlor, while simultaneously being video-captured. The method employed a designated walking path and video recordings processed through image analysis to derive a new computerized automatic lameness score (ALDS) based on calculated factors from back arch posture. The proposed automatic lameness detection system was calibrated using 12 cows, and the remaining 63 were used to evaluate the diagnostic characteristics of the ALDS. The agreement and correlation between ALDS and RLS were investigated. ALDS demonstrated high diagnostic accuracy with 100% sensitivity and specificity and was found to be 100% accurate with a perfect agreement (ρc = 1) and strong correlation (r = 1, P < 0.001) for lameness detection in binary scores (lame/non-lame). Moreover, the ALDS had a strong agreement (ρc = 0.885) and was highly correlated (r = 0.840; 0.796-1.000 95% confidence interval, P < 0.001) with RLS in ordinal scores (lameness severity; LS1 to LS5). Our findings suggest that the proposed method has the potential to compete with vision-based lameness detection methods in dairy cows in farm conditions.

Constitutional Rights of Women in Ghana: An Expansion of the Legal Framework

The research paper elucidates the expansion of the legal framework of women’s rights in Ghana to address all forms of discrimination against them. The article considers a three-fold reform process, including a constitutional reform to influence the enactment of an extensive parliamentary Act either domesticating the Maputo Protocol or incorporating its principles. The article acknowledges the existence of some legislation on specific forms of discrimination against women and advocates that these may support the proposed comprehensive Parliamentary Act. The third reform process considers strategic litigation as a means of implementation and compliance.

Machine learning applications of network security enhancement: review

Machine learning (ML) is being used to improve intrusion detection mechanisms and identification in cyber security. Network data volume scaling (with the help of Machine learning) — Automated analysis and pattern recognition for large amounts of network-data, thereby detection of anomalies / potentially malicious activities that escape current rule-based techniques. By training ML models on historical data, these models can learn benign network behavior as well the anomalies in them that may result from malicious activities. The purpose of this essay/report is to begin taking a look under the hood at how ML can be used for security threat detection and analysis in-networking on an ongoing basis. This paper covers the automation of ML algorithms to enhance network security. Given the current state of electronic threats and their evolution, traditional security methods are typically insufficient. ML can analyze large volumes of data, learn patterns from it and this makes it suitable to complement network defense mechanisms. It then discusses different ML applications in network cybersecurity: intrusion detection, anomaly detection, spam and malware analysis; which the paper characterizes. It analyzes the potential, benefits and constrains of major ML methods in network security like supervised learning; unsupervised learning and reinforcement-learning. Finally, this paper represents recent progress in the use and impact of ML techniques along with case studies.The paper discusses the existing difficulties in the field such as the necessity for datasets and the vulnerability of machine learning models to adversarial attacks.T he paper also highlights avenues for exploration by focusing on developing scalable security solutions based on machine learning that are resilient and flexible.The goal of this examination is to offer both researchers and industry professionals valuable perspectives into the opportunities and obstacles linked to utilizing machine learning, in the domain of network security. ML methods have potential to improve network security by addressing the challenges posed by the increasing cyber threats that traditional security measures struggle to combat effectively over time. One key strength of ML lies in its capacity to analyze datasets and identify intricate patterns efficiently. The research paper delves into applications of ML in enhancing network security. The list covers security tools like Intrusion Detection Systems (IDS) examining malware and phishing attempts as well as anomalies in network activity and user behavior analysis (UEBA). The study explores both supervised and unsupervised learning methods. How they are used for quick threat detection and response in real time scenarios.You will find case studies and recent developments that showcase the implementation and effectiveness of these strategies.In addition the article delves into the obstacles linked to using machine learning techniques in network security including the necessity, for datasets, The paper's goal is to give an enlightening summary to scholars and practitioners about how machine learning can be applied to network security in order to provide solutions that are robust, adaptive, and scalable. To this end, it touches on several relevant aspects. One is the threat posed by adversarial attacks on the sorts of models that are likely to be used in this context. Another is the imperative, deriving from both adversarial threat and model drift, that models needed in this context be available in a form usable for continuous update. Keywords: Network Security, machine learning (ML), Intrusion Detection Systems (IDS), entity behavior analytics (UEBA).

EXCHANGE RATE DYNAMICS AND THEIR IMPLICATIONS

This research paper explores the dynamics of exchange rate fluctuations and their far-reaching implications for the global economy. Exchange rates are pivotal in shaping trade balances, inflation, and capital flows, making them a critical factor for policymakers, multinational corporations, and investors. By examining both theoretical frameworks and empirical evidence, this study analyzes the effects of exchange rate movements on key economic variables such as inflation rates, gross domestic product (GDP), foreign direct investment (FDI), and international trade balances. The paper employs a combination of econometric modeling and historical data analysis to evaluate how these fluctuations have influenced emerging and developed economies over the past two decades. Results indicate that exchange rate volatility can lead to inflationary pressures in import-dependent economies, disrupt trade balances, and influence FDI inflows. The findings also underscore the importance of stable exchange rate policies to mitigate economic uncertainty. This study concludes with recommendations for future research, particularly regarding the influence of digital currencies and geopolitical tensions on exchange rate stability.

Current Status of Logistics Infrastructure Associated with the Development of Vietnam’s Sea Tourism

With a coastline of 3260 kilometers, 2.773 islands, and 28 coastal provinces, Vietnam has a great potential for sea tourism development. One of the factors affecting this development is logistics infrastructure. This research paper aims to analyze all of the logistics infrastructure factors including highways, railways, inland waterways, seaway, and airways; and the connection between logistics transport infrastructure and marine tourism development. The result shows that coastal tourism areas have made strong investments in logistics infrastructure and future planning. However, the lack of synchronization in transport networks connecting tourist destinations, the adaptation of the seaport systems and waterway transports, along with the overall infrastructure serving the needs of accommodations and tourism services have not met the increasing demand. Based on these bases, this paperwork proposes solutions to developing the logistics infrastructure associated with the development of Vietnam’s sea tourism.

Low-Cost Device for Measuring Wastewater Flow Rate in Open Channels

This research paper describes the development of a low-cost device for measuring wastewater flow rates in open channels, a significant advancement enabled by the evolution of microcomputers and processing techniques. A laboratory setup was constructed to validate the device’s accuracy against a standard flow measurement method, optimizing key parameters to achieve a linear relationship between detected and set flow rates, while considering hardware limitations and energy efficiency. The central focus of the research was developing a method to measure the velocity of contaminated fluid using ultrasonic signals, employing the cross-correlation method for signal delay analysis in a stochastic environment. This was complemented by a procedure to measure fluid levels, also based on ultrasonic signals. The device’s reliability was assessed through repeatability and uncertainty measurements, confirming its accuracy with an extended uncertainty not exceeding an average of 3.47% for flows above 40 L/min. The device has potential to provide valuable data on the operational dynamics of sanitary networks, crucial for developing and calibrating simulation models.