Practical Applications Research Articles

Assessment of Soil Quality and Erosion Hazards Using Statistical and PCA Analysis: A Case Study of the Arjasa Subwatershed

This study aims to analyze the soil quality and erosion hazard level of each cluster in the Arjasa Subwatershed, which is the upstream part of the Bedadung Watershed, Indonesia. Land use in this area is production forest, dry land agriculture, and mixed dry land agriculture with slopes varying from 3-8% to >40%. The soil types include Andic Dystrudepts, Lithic Hapludands, Typic Dystrudepts, Typic Eutrudepts, and Typic Hapludands. Soil samples were taken at 30 random sample points at a depth of 0-20 cm. Soil physical and chemical parameters were used in this study. Statistical analysis used were Anova, Duncan test, PCA, and regression-correlation. Quantitative analysis of erosion hazard level was conducted using the USLE formula developed by Wischmeier and Smith (1978). This research has identified three main problems, namely the unavailability of soil quality analysis data, the magnitude of the erosion hazard level in the sub-watershed, and the magnitude of the impact of erosion on soil quality. After assessing these issues, the soil quality index data was found to be in the medium (0.47) to high (0.65) range. Meanwhile, the amount of erosion hazard in each cluster has also been obtained, which shows a range of 4.39 tons/ha/year which is categorized as very light, covering 19.91% of the total area, to 184.81 tons/ha/year, which is included in the heavy category, amounting to 33.37%. In addition, it can be seen that there is a negative relationship at a moderate level (r = 0.56) between the level of erosion hazard and the soil quality index, which means that soil erosion can have an impact on reducing the soil quality index. Finally, it can be suggested that good soil conservation practices such as terracing and organic fertilizer application in agricultural practices are needed to prevent increased erosion so that soil quality does not further decline.

Development and Validation of a Decision Support Tool for Baby Formula Prescription.

Although there are acceptable medical reasons for the use of food supplements, most prescriptions for newborns do not comply with current recommendations, putting continued breastfeeding at risk. This study aimed to create and validate a flowchart for newborn supplement prescription. The flowchart was created and submitted to two rounds of assessments by a panel of judges, who calculated the content validity index (CVI) (acceptable > 0.80). Flowchart use in clinical practice (applicability) was validated by professional prescribers through the resolution of 3 clinical cases. Data were analyzed using Pearson`s chi-squared test (p < 0.05). The flowchart was assessed by 17 judges and validated regarding its content (CVI = 0.84). Took part in validating the applicability of this study 169 doctors and nutritionists who work in maternal and child health. There was a statistical association between correct case resolution and flowchart utilization in two of the three clinical cases (p < 0.05). In situation 1, the use of a validated flowchart increased the likelihood of correct answers 7.76 times. Prescribing baby formula is complex and requires careful assessment of several factors. Thus, knowledge translation is an effective intervention to eliminate the gaps between knowledge and clinical practice. The validated flowchart allows more assertive conduct regarding breastfeeding management and food supplement prescription for newborns.

How big data impacting CSR application in listed companies in emerging countries: evidence from Vietnam

Purpose This study aims to use the SmartPLS method for empirical analysis and explore the impact of various factors on the enhancement of corporate social responsibility (CSR) application among listed companies in Vietnam. With the increasing scrutiny over CSR disclosures and the pivotal role of internal and external factors, the research seeks to uncover how factors such as management’s perception, big data application, firm characteristics, organisational culture and stakeholder pressure significantly influence CSR application. Design/methodology/approach The research assesses the relationships among these factors by drawing on a sample of 255 listed Vietnamese companies across various sectors. Partial least squares structural equation modeling (SmartPLS) is applied to analyse the data and uncover the impact of the identified factors on CSR application. Findings The findings demonstrate that big data applications, organisational cultures and firm characteristics significantly impact CSR applications. Additionally, management’s perception, directly and indirectly, influences CSR applications through its effect on big data applications. Research limitations/implications The study is limited to listed companies in Vietnam, which may affect the generalizability of the findings to other contexts. Further research is needed to validate these findings in different markets and settings. Practical implications These results provide valuable insights for corporate governance practitioners in Vietnam and similar emerging markets. By highlighting the critical role of big data applications in CSR practices, the study suggests pathways for enhancing corporate governance frameworks to improve CSR applications. Social implications Improved CSR practices driven by the factors identified in this study can lead to more sustainable and socially responsible business operations. Originality/value This study contributes to the existing literature by using the SmartPLS method to analyse the impact of various factors on CSR applications in an emerging market. It emphasises the importance of big data applications in shaping effective CSR practices and offers valuable recommendations for corporate governance enhancements.

Problematika Aplikasi Sistem Informasi Manajemen Nikah Dalam Praktik Pernikahan Pada Masyarakat Muslim Di Kelurahan Blimbing

Currently registration can be done online through the Marriage Management Information System (SIMKAH) application. This study aims to identify problems of the application of marriage management information systems in marriage practices in the muslim community in Blimbing Village. This study uses a descriptive qualitative research method. Data collection techniques through observation, in-depth interviews, and documentatiton. Data analysis tchniques through data collection, data condensation, data presentation, and conclusions. The results of the study indicate that the condition of the Blimbing Village community is that there are categories of understanding a little, understanding, and very understanding of the SIMKAH application. The application of the SIMKAH application in marriage practices is used by the Muslim community, namely prospective brides and grooms, married brides and grooms, families of prospective brides and grooms, and the head of the KUA Paciran District. The problems with the SIMKAH application are that some muslims do not understand the SIMKAH application, the problem of data unsynchronization, widows under 19 years old are asked for a dispen permit from the religious court and there is no delete menu when the marriage certificate has been printed or after the examination is complete which is canceled. The role of the government in dealing with these problems is to provide socialization, guidance, assistance, and periodic evaluation. The conclusion is that the problematic application of SIMKAH in marriage practices in the muslim community in Blimbing Village needs to be resolved with assistance from the government so that marriage practices can run well and smoothly.

Evaluation of the effectiveness of a digital escape room for learning veterinary anatomy.

Anatomy plays a key role in veterinary training, and alternatives to traditional teaching methods, such as game-based learning and escape rooms, are emerging as innovative and effective methods. However, the effectiveness of these approaches, particularly in areas such as veterinary anatomy, remains under-researched. The aim of this study was to evaluate the effectiveness of a digital escape room in teaching veterinary anatomy to first-year students at the Toulouse Veterinary School. It included interactive elements and puzzles based on veterinary anatomy content. Participants were randomly assigned to either an experimental group (n = 81) that engaged with the digital escape room or a control group (n = 81). Pre- and post-tests were conducted with a score out of 100 to assess knowledge acquisition, and the participants' perception of the digital escape room was evaluated using a questionnaire. When comparing the difference between pre- and post-test scores, the experimental group showed a statistically significant difference (p < 0.0001). When comparing the post-test, the experimental group achieved a higher test scores with statistical significance comparing to the control group (p < 0.0001), indicating improved knowledge acquisition. The questionnaire reported that the digital escape room helped increase motivation and interest in learning. However, the lowest score in student-teacher interaction indicates a potential lack of feedback to support student progress. Digital escape rooms are a promising effective and engaging tool for teaching veterinary anatomy, offering practicality, scalability, and potential application across various disciplines of veterinary studies.

The fundamental principles of child upbringing in islam: a historical perspective

This article examines the fundamental principles of child upbringing in Islam from a historical perspective. The study analyzes the teachings of the Qur'an and Hadith, explores the views of medieval Islamic scholars, and evaluates the role of Islamic civilization in shaping parenting practices. It also discusses their application in modern parenting practices.

Soil Health and Challenges to Sustainable Soil Management in Denmark: Stakeholder Perceptions

ABSTRACTMaintaining soil health is essential to ensuring an adequate food supply and preserving the environment. Insights from multiple stakeholder inquiries can provide a more nuanced understanding of conditions for soil health to support the adoption of sustainable soil management practices to meet national and regional goals. This article aimed to gather insights from stakeholders' perceptions of soil health and the state of soil knowledge in Denmark. Seven stakeholder inquiries, collected through a series of recent European soil research activities, were synthesised to identify perceptions of soil health, concerns about soil challenges and needs for harmonising production and use of knowledge related to sustainable soil management. Each inquiry was analysed individually, and common themes were discussed across topics. The data showed that the ecosystem service framework related to soil health was not evenly familiar across stakeholder categories. Identified concerns for soil health included climate change effects, knowledge transfer, economic pressure/risk, and soil challenges. The top ‘priority’ soil challenges identified were improving soil organic matter/peat soil, avoiding soil compaction and improving nutrient retention/use efficiency. Soil knowledge gaps related to soil challenges included: multidisciplinary and interdisciplinary long‐term experiments, site‐specific measures, science–policy–stakeholder interactions and knowledge feasibility at the farm level. Identified barriers preventing wider adoption of sustainable management practices included farm applicability of practices, farmers' engagement, knowledge sharing and lack of regulations for challenges such as soil compaction. Farmers were also concerned about the time and effort required to learn new practices, especially as it relates to their work/life balance and the challenge of implementing sustainable practices on commercial farms while ensuring profitability. These concerns might partially arise from knowledge gaps between stakeholder categories. Raising awareness of sustainable practices and addressing current and future risks such as pests and weather extremes are crucial for policy and stakeholder engagement.

Process development of guava leaves with alkali in removal of zinc ions from synthetic wastewater

BackgroundThis research investigation delves into the efficient removal of zinc ions from synthetic wastewater through the utilization of KOH treated guava leaves as an adsorbent. The study employs advanced analytical techniques including SEM, FTIR, XRD, and BET analysis to characterize the physicochemical properties of the treated guava leaves. The research extensively explores the impact of various experimental factors on the adsorption process, encompassing agitation time, adsorbent dosage, pH levels, and desorption, to identify optimal conditions for maximum Zn (II) ion removal. MethodsThe research methodology involves subjecting guava leaves treated with KOH to thorough analysis using SEM, FTIR, XRD, and BET techniques to gain insights into their physical and chemical attributes. The study systematically investigates the adsorption process by manipulating crucial parameters such as agitation time, adsorbent dosage, and pH levels. Different isotherm models including Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich are applied to comprehend the adsorption mechanism. Additionally, kinetic calculations are performed, leading to the determination that the pseudo-second-order model best fits the removal of zinc metal. Significant FindingsThe research uncovers essential findings regarding the efficacy of KOH treated guava leaves as an adsorbent for zinc ions. Optimum conditions are pH 3 are identified, an adsorbent dosage of 100 mg/L, and an equilibrium period of 20 min, resulting in peak efficiency of the adsorption process. The study reveals an adsorption capacity of 14.5 mg/g for the studied metal, emphasizing the potential of KOH treated guava leaves as an efficient adsorbent for zinc ions. The adsorption capacity is 5.1 mg/g for the untreated guava leaves. The findings underscore the feasibility of utilizing this eco-friendly approach for wastewater management, thereby contributing to environmental remediation and pollution control efforts. The research highlights the practical application of KOH treated guava leaves in wastewater treatment processes, advocating for further exploration and optimization of this sustainable solution to address heavy metal contamination and promote greener technologies for water purification and waste management.

Nanoencapsulation of Zataria multiflora Essential Oil Containing Linalool Reduced Antibiofilm Resistance against Multidrug-resistant Clinical Strains

Background: The rise in antimicrobial resistance, caused by the production of biofilms by bacteria, is a significant concern in the field of healthcare. Nanoemulsion technology presents itself as a viable alternative in the quest to circumvent antibiotic resistance in pathogenic bacteria. Objective: The aim of this research was to form a sustainable nanoemulsion from Z. multiflora, and evaluate its antibacterial and anti-biofilm activities against the clinical isolates of Pseudomonas aeruginosa, Proteus mirabilis, and Staphylococcus aureus. Materials and Methods: Bioactive compounds of the oil were identified using GC-MS. Zataria multiflora essential oil (ZMEO) nanoemulsion was formulated as a water-dispersible nanoemulsion with a diameter of 184.88 ± 1.18 nm. The antibacterial and antibiofilm activities of the essential oil in both pure and nanoemulsion forms were assessed against pathogenic bacteria causing hospital-acquired infections using minimal inhibitory concentrations (MICs) and the microtiter method, respectively. Results: The main constituents were found to be linalool (78.66 %), carvacrol (14.25 %), and α- pinene (4.53%). Neither ZMEO nor the emulsified ZMEO showed any antimicrobial activity. However, ZMEO exhibited a low inhibition of biofilm formation by P. mirabilis, S. aureus, and P. aeruginosa. The most promising finding was that when the emulsified ZMEO was present at a concentration of 750 μg/mL, it significantly reduced biofilm formation by the aforementioned bacteria to 39.68% ± 2.62, 56.54% ± 3.35, and 59.60% ± 2.88, respectively. This result suggests that ZMEO nanoemulsion has the potential to effectively disrupt persistent biofilms and enhance the penetration of antimicrobial agents into the biofilm matrix. Conclusion: In conclusion, the study provides evidence supporting the use of ZMEO nanoemulsion as a potential treatment option for combating biofilm-related infections caused by Pseudomonas aeruginosa, Proteus mirabilis, and Staphylococcus aureus. Further research is warranted to explore the practical application of the proposed essential oil in clinical settings.

Fully printed non-contact touch sensors based on GCN/PDMS composites: enabling over-the-bottom detection, 3D recognition, and wireless transmission

ABSTRACT The rapid advancement in intelligent bionics has elevated electronic skin to a pivotal component in bionic robots, enabling swift responses to diverse external stimuli. Combining wearable touch sensors with IoT technology lays the groundwork for achieving the versatile functionality of electronic skin. However, most current touch sensors rely on capacitive layer deformations induced by pressure, leading to changes in capacitance values. Unfortunately, sensors of this kind often face limitations in practical applications due to their uniform sensing capabilities. This study presents a novel approach by incorporating graphitic carbon nitride (GCN) into polydimethylsiloxane (PDMS) at a low concentration. Surprisingly, this blend of materials with higher dielectric constants yields composite films with lower dielectric constants, contrary to expectations. Unlike traditional capacitive sensors, our non-contact touch sensors exploit electric field interference between the object and the sensor’s edge, with enhanced effects from the low dielectric constant GCN/PDMS film. Consequently, we have fabricated touch sensor grids using an array configuration of dispensing printing techniques, facilitating fast response and ultra-low-limit contact detection with finger-to-device distances ranging from 5 to 100 mm. These sensors exhibit excellent resolution in recognizing 3D object shapes and accurately detecting positional motion. Moreover, they enable real-time monitoring of array data with signal transmission over a 4G network. In summary, our proposed approach for fabricating low dielectric constant thin films, as employed in non-contact touch sensors, opens new avenues for advancing electronic skin technology.

Sustainable Agricultural Transformation: Insights from the Emilia-Romagna Region

Today, Kazakhstan's agricultural industry remains one of the most risk-prone, heavily influenced by adverse weather conditions, volatile market prices, and insufficient infrastructure. The study aims to assess opportunities for enhancing Kazakhstan's agricultural sector's competitiveness through the adoption of smart technologies, drawing lessons from the Emilia-Romagna region in Italy. The research employs a combination of comparative analysis and case study methodologies to evaluate the applicability of international best practices in the context of Kazakhstan's agricultural development. The study relies on a variety of data sources, including government reports, international case studies, and performance metrics from both Kazakhstan and the Emilia Romagna Region. The findings demonstrate that integrating technologies such as IoT, robotics, and blockchain can improve productivity, sustainability, and market attractiveness in the agricultural sector. The study also highlights the need to enhance farmer and manager competencies and promote family businesses and cooperatives. By adopting these strategies, Kazakhstan could address the existing challenges in its agricultural sector, reduce vulnerabilities, and create a more robust agro-industrial ecosystem. Future research should focus on developing specific pilot programs that apply these integrated approaches at a regional level, as well as assessing the long-term impacts of digital and sustainable practices in enhancing the competitiveness of Kazakhstan's agricultural sector.

Cross-National Findings of Factors Affecting the Acceptance of AI-Based Sustainable Fintech

This study utilized mixed (qualitative and quantitative) methods to discover the current research trends for AI in sustainable Fintech and to validate a research model through empirical analysis. The primary purpose of this research is to explore the factors influencing the acceptance of AI tools within the sustainable Fintech industry through a cross-national perspective, identifying key benefit and sacrifice dimensions, along with sustainability considerations, that affect users’ intentions to adopt AI tools. Drawing on a bibliometric keywords approach, we first conducted an overall review of academic literature using Web of Science and VOSviewer (version 1.6.17), covering areas related to AI applications in Fintech and sustainable Fintech practices. Additionally, for a cross-national study, this study built and validated a conceptual framework on the intention to use AI tools by selecting subjects from Republic of Korea and China. As core theoretical premises of the conceptual framework, the study drew on the Value-Based Adoption Model (VAM) and the Technology Acceptance Model (TAM). Furthermore, we extended the TAM to embrace sustainable dimensions (perceived responsibility and perceived transparency). Overall, the study concludes that AI not only improves Fintech efficiency but also significantly contributes to sustainable development, suggesting collaboration between experts in AI, finance, sustainability, and other relevant fields for more research on AI integration with sustainable Fintech management. This research contributes to existing literature by highlighting the synergistic benefits of combining AI and sustainable Fintech and offers practical insights for industry practitioners and policymakers.

Mengintegrasikan Kecerdasan Emosional, Kecerdasan Spiritual Dan Kecerdasan Buatan Dalam Praktik-Praktik Manajemen Sumber Daya Manusia Pada Organisasi Bisnis

With the increasingly complex and dynamic business world, the integration of emotional intelligence (EQ), spiritual intelligence (SQ), and artificial intelligence (AI) into human resource management (HRM) practices offers a holistic approach to improving workplace effectiveness and well-being. Emotional intelligence plays a vital role in managing interpersonal relationships, communication, and conflict management, which are crucial for effective leadership and teamwork. Spiritual intelligence supports the search for meaning and purpose in work, creating an organizational culture that aligns with personal and collective values. Artificial intelligence, on the other hand, automates processes, provides data-driven analytics, and improves operational efficiency through cutting-edge technology. Integrating these three intelligences can create a more productive, innovative, and fulfilling work environment. This article examines the basic theories of each intelligence and explains how their application in HRM practices can yield significant benefits to organizations.

Scientific Translations of “Da-xue” in 19th Century Russia: A Comparative Analysis of Approaches of Nikita Bichurin and Dmitry Sivillov

This article presents a comparative analysis of two translations of the Confucian text “Da-xue,” undertaken by prominent Russian sinologists N. Ya. Bichurin and D. P. Sivillov in the 19th century. The aim of the study is to juxtapose the scholars’ approaches to translating and interpreting this classical Chinese philosophical text. The research material consists of manuscript translations and original Chinese canonical texts. The findings demonstrate a high level of scholarly accuracy in both translations, despite differences in methodology. Bichurin’s translation, based on a Qing dynasty educational resource, is distinguished by its rich commentary and cultural explanations. In contrast, Sivillov’s work, which relies on the original “Da-xue” text, is characterized by its conciseness and fidelity to the source. The analysis reveals divergent translation strategies employed by the scholars: Bichurin aimed for a more literal translation while preserving culturally specific elements, whereas Sivillov adapted the text for the Russian readership. Both translations significantly contributed to the development of scientific translation methodology for Chinese classics in 19th century Russia. The study underscores the value of these works for the understanding of Confucian philosophy and the history of Russian sinology. The results may find application in contemporary translation practices and in teaching the history of sinology.

Axial compressive performance of low-carbon high-strength recycled aggregate concrete

AbstractThis paper introduces a novel material, low-carbon high-strength recycled aggregate concrete (LCHRAC), developed by activating ground granulated blast-furnace slag (GGBS) and silica fume (SF) in an alkaline environment and integrating recycled aggregate. To evaluate its mechanical properties, uniaxial compressive tests were performed, systematically analyzing the effects of recycled concrete aggregate (RCA) substitution ratios, as well as the characteristic parameters of steel and polypropylene(PP) fibers, on LCHRAC’s mechanical behavior. The results indicated that compressive strength shows a gradual decline as the RCA substitution ratio increases, with a moderate reduction of 7.1% up to 50% replacement, and a more significant drop, retaining only 68.6% at 100% replacement. In contrast, the peak strain increases linearly, showing a 29% improvement at full replacement, while the toughness index exhibits a consistent upward trend, increasing by approximately 123% at a 100% replacement rate. Based on experimental data, empirical models were developed to predict the influence of key control variables on the compressive strength, peak strain, elastic modulus, and the uniaxial compressive stress–strain behavior of LCHRAC. Additionally, advanced characterization techniques, including X-ray diffraction (XRD), thermogravimetric analysis (TGA/DTG), scanning electron microscopy (SEM), and energy dispersive spectroscopy (EDS), were employed to elucidate the hydration mechanisms of the slag-silica fume composite system. These findings provide a comprehensive understanding of the mechanical performance and microstructural characteristics of LCHRAC, contributing to its potential application in sustainable construction practices.

Assessing the applicability of international AI practices in construction management: A systematic review with implications for Vietnam

This study systematically reviews 94 journal articles published between 2000 and 2024 to examine the application of artificial intelligence (AI) in construction management (CM). The review focuses on AI's role in managing quality, time, and cost, which are critical factors for project success. The findings reveal a growing trend in AI adoption, particularly in areas such as scheduling and quality control. However, the use of AI for on-site CM, especially in Vietnam, remains limited and underexplored. This research aims to assess international AI practices and their potential applicability to Vietnam, analyzing how these technologies could improve efficiency, accuracy, and safety in construction projects. The implications of these findings suggest that embracing AI technologies could lead to enhanced project outcomes in Vietnam's construction industry by optimizing quality management, improving scheduling efficiency, and better controlling costs.

FUNDAMENTALS OF MODERN METHODS OF RESEARCH OF GEOTECHNICAL AND HYDROGEOLOGICAL SYSTEMS

The article examines the development of a synergistic paradigm in the Earth sciences, in particular in geotechnics and engineering hydrogeology. It was determined that in the second half of the 20th century, as a result of changes in scientific methodology, there was a need to rethink linear approaches to the study of natural systems. Synergetics, as a science of interaction and self-organization of complex systems, became the basis for new scientific directions, in particular in the field of geosystems and hydrogeotechnical systems research. The work emphasizes the importance of introducing synergistic principles into geological and hydrogeological research, particularly in the context of dynamic processes, such as filtration in hydrogeosystems. It is shown that these processes, in particular in the regimes of hydrodynamic, hydrochemical and hydrothermal changes, have a non-linear nature and can be described by appropriate mathematical models. The work also covers the issue of the influence of climatic and anthropogenic factors on the state of groundwater and soil, which is important for the design of buildings and infrastructure in various regions. The mechanisms that affect the stability of hydrogeosystems, as well as their possible critical states, which can lead to turbulence or irreversible changes in the structures of water-bearing rocks, are considered separately. An important aspect is the human impact on these systems, which can be both directed and accidental, which emphasizes the need to consider synergistic effects to improve natural resource management and minimize negative environmental impacts. The article is aimed at highlighting the potential of synergy in the study of hydrogeotechnical systems and the need for its application in engineering and environmental protection practices. This information will be useful for engineers, geologists, hydrogeologists and students of relevant specialties, as well as for those engaged in research in the field of geotechnics and hydrogeology.

Artificial Intelligence and the Management of Viral Respiratory Infections inChildren

Viral respiratory infections in children are a major public health issue, with high incidence rates and a significant impact on healthcare systems. The application of artificial intelligence (AI) in the medical field offers substantial opportunities for early detection, accurate diagnosis, effective management, and prevention of these infections. Aim: This study aims to analyse the most effective AI-based approaches for managing viral respiratory infections in children, including its application in paediatric hospitals, telemedicine, and routine practices, while also identifying challenges associated with implementation. Methodology: A systematic literature review was conducted following the PRISMA guidelines. The search was performed across 10 major databases: De Gruyter, MDPI, Nature, PubMed, ScienceDirect, Elsevier, SpringerLink, Wiley Online Library, Taylor &amp; Francis, and Frontiers, focusing on articles published between 2020 and 2024. Out of 46,900 scientific articles, 17 relevant studies were selected, including original research, meta-analyses, and systematic reviews.Results: AI has shown high efficiency in the early detection of symptoms, differential diagnosis between viral and bacterial infections, monitoring disease progression, and personalising treatments. Its use in telemedicine and family education has improved accessibility to care and raised awareness. Integration of AI in paediatric hospitals has reduced diagnostic time and optimised resources. However, large-scale implementation depends on collaboration between medical professionals and IT specialists. Conclusions: AI represents a promising solution for improving the management of viral respiratory infections in children. The development of standardised protocols and addressing ethical challenges are essential for the effective integration of this technology into paediatric practice.

Role and Diagnostic Significance of Apolipoprotein D in Selected Neurodegenerative Disorders.

The World Health Organization in 2021 ranked Alzheimer's disease and other dementias as the seventh leading cause of death globally. Neurodegenerative disorders are progressive, intractable, and often fatal diseases. Early diagnosis may allow patients to enjoy prolonged survival with attenuated symptomatology because of early intervention. Hence, further research on finding non-invasive biomarkers of neurodegenerative diseases is warranted. Apolipoprotein D (ApoD) is a glycoprotein involved in lipid metabolism, oxidative stress regulation, and inflammation. It is expressed in various body fluids and regions of the central nervous system. ApoD's roles in neuroprotection, lipid transport, and anti-inflammatory processes are crucial as far as the prevention of neurodegenerative pathologies is concerned. This review aims to summarize the background knowledge on ApoD, and it covers studies indexed in the PubMed, Scopus, and Web of Science databases. It discusses the evidence for the multifaceted roles of ApoD in the mechanisms and pathogenesis of multiple sclerosis, Alzheimer's disease, and Parkinson's disease. ApoD may be a specific, sensitive, easily obtained, cost-effective biomarker for neurodegenerative diseases and its applications in diagnostic practices, treatment strategies, and advancing neurodegenerative disorders' management.

Delphi study and qualitative analysis to establish domains, core competencies, and content in forensic nursing pedagogy

BACKGROUND: The American Nurses Association designated forensic nursing (FN) a specialty in 1995. Nursing schools subsequently adopted Lynch's theoretical framework. Inconsistent sub-specialty-focused graduate education emerged, creating difficult-to-compare early programs of study. AIMS: Update FN domains, descriptions of and context for FN practices, core competencies, and sub-competencies with content for graduate curricula, align FN with new AACN Essentials, and create a certification foundation. METHODS: Methods include the mini-Delphi design (Estimate-Talk-Estimate), with Nominal Group Techniques methods, Cognitive Task Analysis, and NVivo™ qualitative analysis of experts' virtual recordings. The FN sample (N=126) included educators-clinicians, who gathered face-to-face (2002-4, 2014) and virtually (2020-22). RESULTS: The 2002-04 results informed the 2014 meeting, validating major knowledge pillars (legal foundations, forensic science, and nursing science). Analysis of 2020-2022 data named key domains, descriptions of and context for practice, core competencies, sub-competencies, concepts, and content in forensic nurse science and practice. The research included qualitative analysis of participant conversations, naming key content for each pillar. CONCLUSIONS: The 20-year Delphi study transformed knowledge integration for competent future Generalist and Advanced Forensic Nurse education and practice. The study confirmed Lynch’s thesis, three pillars of knowledge, and aligned FN core competencies with AACN Essentials and other national nursing publications, naming common practices, essential for all FNs. The study’s derivation of scientific content, important for certifications, arose from qualitative analysis of expert conversations, implying that as FN science evolves, the diverse practice roles of the FN mature with a common and basic core for application in all FN practices.