Standardization Issues Research Articles

A Critical Review on Advancing Preventive Health Research in Ayurveda: Strategic Approaches and Imperatives

Preventive health research in Ayurveda offers valuable strategies for disease prevention and health promotion, particularly in the context of modern health challenges such as non-communicable diseases (NCDs) and pandemics like COVID-19. This review critically examines strategic approaches for advancing preventive health research within Ayurveda, emphasizing the need for evidence-based validation, integration with modern scientific methodologies, and global collaboration. Key practices, including Rasayana therapy, Dinacharya, and Ritucharya, demonstrate significant potential in enhancing immunity, promoting longevity, and mitigating lifestyle-related ailments. However, challenges such as limited clinical evidence, standardization issues, and underutilization of advanced research tools hinder progress. Addressing these challenges through rigorous clinical trials, interdisciplinary research, and policy advocacy can ensure Ayurveda’s relevance in contemporary healthcare systems. The integration of traditional Ayurvedic knowledge with modern scientific approaches will enhance the global applicability of Ayurveda in preventive health.

Circular Economy Strategies for Resource Efficiency and Sustainable Development in Manufacturing Industries

The shift to a CE in manufacturing industries has been deemed as a frontrunner among strategies to deal with resource efficiency and sustainable development concerns. The switch to a superior model of circular economy transits from the erstwhile linear models of ‘take-make-dispose’. Strategies in manufacturing in circular economy embrace principles of sustainable product design, redesign of finished products, and recycling in industrial systems to recover products making raw materials closed loop. IT tools such as digital twin, IoT, and AI enable further sophistication of the techniques the manufacturers can use to track resource flows and improve processes as well as product life cycles. Policy maker-led, industry and community-supported partnership effort in carrying CE message through the enabling policies, green supply chain management and consumer awareness. The prospect of CE goes far beyond environmental protection as it helps to build economic stability, create new working places, and gain competitive advantages in the global economy. Nevertheless, some key barriers remain; poor standardization, technological limitations and cultural issues. It is only possible to fix these problems via innovations for these issues, the multi-stakeholder cooperation, and the sound policies for creating a sustainable industrial revolution.

Відкрита наука в сучасному дослідницькому просторі

The article comprehensively examines theoretical and practical aspects of open science development in the modern research space. The evolution of the open science concept has been analyzed. It has been determined that the modern understanding of open science is based on the principles of transparency, collaboration, and inclusivity, which are implemented through open access to publications, research data, and methodologies. The role of leading international organizations in the development of open science has been investigated. In particular, SPARC's activities in overcoming inequalities in scientific communication, Science Europe's contribution to the formation of research data management standards, and Coalition S's impact on the transformation of scientific publishing models have been analyzed. It has been established that these organizations play a key role in shaping open science policies, developing infrastructure, and implementing new models of scientific communication. Special attention has been paid to the development of open science in Ukraine in the context of European integration and the formation of national open access infrastructure. The main directions of development have been analyzed, including the creation of a network of institutional repositories, development of open access journals, legislative support, and international cooperation. Ukraine's high performance in open data has been noted, indicating significant progress in implementing public information transparency policies. Based on the analysis, key components of modern open science have been identified, including open research data complying with FAIR principles, open research methods, open peer review of scientific works, and digital infrastructure. The main challenges of open science development have been revealed, particularly financial aspects of open access publishing, technical issues of data standardization and storage, overcoming cultural barriers, and the need to change established practices. The prospects for further development of open science have been substantiated, which are associated with improving technological infrastructure, implementing effective mechanisms for evaluating scientific activities, and creating incentives for adherence to open science principles

Database-Driven Adaptive Learning: A Systematic Analysis of AI Integration in Educational Personalization

This article examines the transformative role of AI-driven databases in facilitating personalized learning experiences within educational institutions. Through a systematic analysis of implementations across K-12 and higher education settings, we investigate how intelligent database systems enable adaptive learning pathways and real-time intervention strategies. The article synthesizes data from 47 educational institutions implementing AI-enhanced learning management systems over a three-year period (2021-2024), employing a mixed-methods approach to evaluate both technical integration patterns and learning outcomes. Results demonstrate significant improvements in student engagement (mean increase of 27%, p < .001) and academic performance (average GPA increase of 0.4 points) when compared to traditional learning management systems. The article also reveals key implementation challenges, including data standardization issues and faculty adaptation requirements. The findings provide a comprehensive framework for educational institutions seeking to implement AI-driven database systems, while highlighting critical considerations for scalability, privacy, and pedagogical integration. This article contributes to the growing body of literature on educational technology by establishing empirical evidence for the effectiveness of AI-powered personalization in educational contexts and proposing a structured approach to its implementation.

Advancing Coastal Flood Risk Prediction Utilizing a GeoAI Approach by Considering Mangroves as an Eco-DRR Strategy

Traditional coastal flood risk prediction often overlooks critical geographic features, underscoring the need for accurate risk prediction in coastal cities to ensure resilience. This study enhances the prediction of coastal flood occurrence by utilizing the Geospatial Artificial Intelligence (GeoAI) approach. This approach employed models—random forest (RF), k-nearest neighbor (kNN), and artificial neural networks (ANN)—and compared them to the IPCC risk framework. This study used El Salvador as a demonstration case. The models incorporated seven input variables: extreme sea level, coastline proximity, elevation, slope, mangrove distance, population, and settlement type. With a recall score of 0.67 and precision of 0.86, the RF model outperformed the other models and the IPCC approach, which could avoid imbalanced datasets and standard scaler issues. The RF model improved the reliability of flood risk assessments by reducing false negatives. Based on the RF model output, scenario analysis predicted a significant increase in flood occurrences by 2100, mainly under RCP8.5 with SSP5. The study also highlights that the continuous mangrove along the coastline will reduce coastal flood occurrences. The GeoAI approach results suggest its potential for coastal flood risk management, emphasizing the need to integrate natural defenses, such as mangroves, for coastal resilience.

Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review.

Due to increasing traffic congestion, travel modeling has gained importance in the development of transportion mode detection (TMD) strategies over the past decade. Nowadays, recent smartphones, equipped with integrated inertial measurement units (IMUs) and embedded algorithms, can play a crucial role in such development. In particular, obtaining much more information on the transportation modes used by users through smartphones is very challenging due to the variety of the data (accelerometers, magnetometers, gyroscopes, proximity sensors, etc.), the standardization issue of datasets and the pertinence of learning methods for that purpose. Reviewing the latest progress on TMD systems is important to inform readers about recent datasets used in detection, best practices for classification issues and the remaining challenges that still impact the detection performances. Existing TMD review papers until now offer overviews of applications and algorithms without tackling the specific issues faced with real-world data collection and classification. Compared to these works, the proposed review provides some novelties such as an in-depth analysis of the current state-of-the-art techniques in TMD systems, relying on recent references and focusing particularly on the major existing problems, and an evaluation of existing methodologies for detecting travel modes using smartphone IMUs (including dataset structures, sensor data types, feature extraction, etc.). This review paper can help researchers to focus their efforts on the main problems and challenges identified.

Imprisonment and Human Rights in Israel: Uncertainty and Volatility

This article provides an overview of the key issues in international and Israeli human rights standards related to incarceration from a legal and sociological perspective. We argue that the Israeli imprisonment system is currently undergoing uncertain changes, showing high volatility due to its historical development and normative nature. Our account of the tensions between punishment and human rights in Israel over recent decades suggests that this field is highly volatile, making it difficult to predict future developments. Although Israel’s constitutional and human rights-oriented reforms seemed to indicate progress, Israel also experienced a series of harsh and regressive statutory and penological reforms.

A Comprehensive Survey of Artificial Intelligence Applications in UAV-Enabled Wireless Networks

This comprehensive survey paper examines the applications of artificial intelligence (AI) in unmanned aerial vehicle (UAV)-enabled wireless networks. With the increasing demand for efficient and adaptive communication systems, the integration of AI with UAV networks promises to revolutionize various aspects of wireless communication. The paper first outlines the background and motivation behind AI integration, highlighting the potential for enhanced network performance, autonomy, and adaptability. It then delves into the key AI applications across different network layers, including data sensing and collection, placement and trajectory optimization, radio resource management, routing and topology control, edge computing and caching, as well as security and privacy enhancement. For each application, the paper discusses relevant AI techniques, main findings, optimization objects, and the potential benefits and challenges. The survey also identifies open issues, such as the practical implementation gap, standardization issues, and real-world application barriers, and proposes future directions to address these challenges and further advance the field. In conclusion, the integration of AI with UAV-enabled wireless networks (UWNs) holds tremendous potential for transforming wireless communication, enabling new applications and services with unprecedented capabilities.

Toward Generalized Artificial Intelligence by Assessment Aggregation With Applications to Standard and Extreme Classifications.

The article proposes a plural learning framework combining the ingredients found in a tribunal for the derivation of a more generalized artificial intelligence (GAI) when starting from a specialized set of convolutional neural networks (CNNs). This framework involves at least two different training stages called, respectively, specialization and generalization. In the specialization stage, any CNN considered in a given set learns to predict independently of other elements of the set. In the second stage called generalization, an integration network learns to predict from assessment measures fed by downstream specialized CNNs. The assessment measures considered are categorical softmax probabilities and learning to judge from these assessments relies on independent CNNs. Generalization proof of concepts is provided in terms of multimodel, multimodal, and distributed schemes. The multimodel framework is such that different CNN models operating on the same modality cooperate for decision purpose. The multimodal framework implies specializations of CNN with respect to different input modalities. The distributed framework proposed is associated with assessment exchanges: it such that the aggregation aims at determining relevant joint assessments for mapping a given input to a single or a multiple output category. The performance of these aggregation frameworks is shown to be outstanding for both standard and extreme classification issues.

ВИТАМИН D3: ПОДРОБНАЯ ХАРАКТЕРИСТИКА СУБСТАНЦИИ И АНАЛИЗ

The article examines in detail the issues of standardization of the obtained vitamin D substance using its own original technological scheme, and the possibility of further use of the substance to create a standard sample (SS). The work traces the current problem associated with the lack of production of domestic vitamin D substance. The object of study is the vitamin D substance isolated from natural raw materials. To assess the quality of the obtained substance, quantitative and qualitative determination methods, high-performance liquid chromatography (HPLC) at a wavelength of 265 nm, IR spectroscopy in the emission range of the spectrum from 4000 cm-1 to 400 cm-1, organoleptic method, polarimetry, refractometry and other methods of analysis were used. The obtained vitamin D substance, according to its quality characteristics, can be confidently used not only as a material for the manufacture of SS, but also as a starting substance in the pharmaceutical, food and agricultural sectors of the national economy.

Retraction Note: Three-dimensional face reconstruction of static images and computer standardization issues

Retraction Note: Three-dimensional face reconstruction of static images and computer standardization issues

Problems and Solutions Related to The Formation Of Demand For Gastronomic Tourism and The Development Of The Industry

The article focuses on the challenges and solutions related to the demand formation in gastronomic tourism and its impact on the development of the industry. The study reviews research by local and international scholars on factors affecting demand, such as the influence of national food products and traditions. Using dialectical and comparative analysis, the article identifies key strategies for improving demand in gastronomic tourism. These include identifying target audiences, promoting gastro-festivals, and enhancing collaboration with local food producers. The study also highlights the importance of qualified personnel and infrastructure development, suggesting measures to address issues in standardization and quality control. In conclusion, the article provides recommendations for boosting gastronomic tourism through investment, standardization, and training programs, which could support economic growth and cultural heritage preservation

Biofabricated osteoblast-derived nanovesicles as extracellular vesicle mimics for bone repair

Osteoblast-derived extracellular vesicles (EVs) have demonstrated therapeutic utility for bone repair as transporters of key biomolecules capable of accelerating biomineralisation and tissue repair. The clinical translation of these biologically derived nanoparticles, however remains limited due to scalability, heterogeneity and standardisation issues. Herein we investigate the generation of nanovesicles (NVs) from mineralising osteoblasts by extrusion directly compared against natural EV counterparts from the same parental cells.Mineralising osteoblast-derived EVs (MO-EVs) were isolated via ultracentrifugation from cell culture media. The parental osteoblasts were then processed via serial extrusion to <200 nm. EVs and NVs were characterised by comparing their size, concentration and morphology. The presence of tetraspanin markers was detected by Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS). Osteoblasts viability and metabolic activity was assessed after both EV and NV-treatment before comparing their mineralising potency via alizarin red staining.EVs and NVs exhibited similar diameters of approximately 100 nm with a vesicular morphology. EVs were found to be richer in proteins and exhibited a significantly more negative ζ-potential compared to NVs. SP-IRIS analysis confirmed the presence of CD9, CD63 and CD81 in EVs. At both 1 and 10 μg/mL, EVs and NVs reduced the metabolic activity of osteoblasts, however, this was not associated with any cytotoxic effects. The biomineralisation study performed using osteoblasts showed that only EVs significantly increased mineral deposition (p < 0.05) compared to untreated control.In this study, we have established for the first time the biofabrication of cell-derived nanovesicles as a promising alternative to extracellular vesicles derived from mineralising osteoblasts.

Current Applications of the Three-Dimensional Printing Technology in Neurosurgery: A Review.

In the recent years, three-dimensional (3D) printing technology has emerged as a transformative tool, particularly in health care, offering unprecedented possibilities in neurosurgery. This review explores the diverse applications of 3D printing in neurosurgery, assessing its impact on precision, customization, surgical planning, and education. A literature review was conducted using PubMed, Web of Science, Embase, and Scopus, identifying 84 relevant articles. These were categorized into spine applications, neurovascular applications, neuro-oncology applications, neuroendoscopy applications, cranioplasty applications, and modulation/stimulation applications. 3D printing applications in spine surgery showcased advancements in guide devices, prosthetics, and neurosurgical planning, with patient-specific models enhancing precision and minimizing complications. Neurovascular applications demonstrated the utility of 3D-printed guide devices in intracranial hemorrhage and enhanced surgical planning for cerebrovascular diseases. Neuro-oncology applications highlighted the role of 3D printing in guide devices for tumor surgery and improved surgical planning through realistic models. Neuroendoscopy applications emphasized the benefits of 3D-printed guide devices, anatomical models, and educational tools. Cranioplasty applications showed promising outcomes in patient-specific implants, addressing biomechanical considerations. The integration of 3D printing into neurosurgery has significantly advanced precision, customization, and surgical planning. Challenges include standardization, material considerations, and ethical issues. Future directions involve integrating artificial intelligence, multimodal imaging fusion, biofabrication, and global collaboration. 3D printing has revolutionized neurosurgery, offering tailored solutions, enhanced surgical planning, and invaluable educational tools. Addressing challenges and exploring future innovations will further solidify the transformative impact of 3D printing in neurosurgical care. This review serves as a comprehensive guide for researchers, clinicians, and policymakers navigating the dynamic landscape of 3D printing in neurosurgery.

Role of Natural Polymers in Novel Drug Delivery Systems

Natural polymers have gained significant attention in the field of drug delivery due to their inherent biocompatibility, biodegradability, and low toxicity. This review article aims to provide a comprehensive overview of the diverse roles that natural polymers play in the development of novel drug delivery systems. Beginning with a classification of natural polymers based on their origin (plant, animal, microbial), we explore their unique characteristics and advantages over synthetic counterparts. The review discusses the pivotal role of natural polymers in formulating various drug delivery systems, including sustained/controlled release formulations, targeted delivery platforms, mucoadhesive systems, and nanotechnology-based approaches. Techniques such as emulsification, ionotropic gelation, coacervation, and electrospinning for natural polymer-based drug delivery are elucidated, highlighting their versatility and applicability across different administration routes. Furthermore, we delve into the diverse applications of natural polymers in drug delivery, encompassing oral, transdermal, ocular, injectable, nasal, buccal, and vaginal delivery routes. Recent advances and innovations in combining natural polymers with synthetic counterparts, incorporating stimuli-responsive properties, and personalized medicine approaches are also explored. Despite the numerous advantages offered by natural polymers, challenges such as variability in polymer properties, standardization issues, scale-up challenges, and regulatory considerations are discussed. The review concludes with future perspectives, highlighting emerging trends and opportunities for further research and development in the field of natural polymer-based drug delivery systems. Overall, this review provides valuable insights into the pivotal role of natural polymers in advancing drug delivery technology, paving the way for safer, more efficient, and patient-friendly therapeutic interventions.

Sex panic and robots: a critical discourse analysis of the banned Texan robotic brothel

ABSTRACT This study examines the unique relationship between panic, technology, and sexuality using a sex panic framework. Sex panic, a derivative of moral panic theory, focuses on fears related to or because of sexuality or sexual practices. Inextricably tied to emotion, sex panic events are often scripted and based on performativity. In Texas, a sex robot “testing center” attempted to open as a storefront in the suburbs of Houston. Local officials and community leaders condemned the brothel announcement. A critical discourse analysis of sixty news articles and videos, Houston City Council meeting minutes, and the subsequent city ordinances were evaluated to explore the controversy of the ultimately banned brothel. Through this analysis, prevalent discursive themes on the protection of women and children, fears about sex robot users, and concerns over how the Houston community would be viewed were found. Discursive tactics centered on creating panic around issues of rape, dehumanization, and moral standards. This study contributes to the critical scholarship on sex robots and their effects on public discourse.

The lingering safety menace: A 10-year review of enteral misconnection adverse events and narrative review.

In 2011, "Tubing Misconnections: Normalization of Deviance" reported >100 cases of enteral tubing misconnections leading to patient harm. Despite development of safer enteral device connectors, 96 new cases of enteral misconnections have been published since 2011. Publication and safety databases were searched for reports from 2011 to 2023. Reported misconnections lead to death in 4% of the cases and survival with harm were reported in 69% of cases. Reported misconnections occurred more often in infants and children than in adults. This article outlines why these misconnections happen, the history of the issue and development of safer connector standards, the safety threats and recommendations associated with the new cases, current conversion rates, and process steps, education, and resources for the conversion to safer connectors for enteral nutrition devices.

State-of-the-Art Fast Healthcare Interoperability Resources (FHIR)-Based Data Model and Structure Implementations: Systematic Scoping Review.

Data models are crucial for clinical research as they enable researchers to fully use the vast amount of clinical data stored in medical systems. Standardized data and well-defined relationships between data points are necessary to guarantee semantic interoperability. Using the Fast Healthcare Interoperability Resources (FHIR) standard for clinical data representation would be a practical methodology to enhance and accelerate interoperability and data availability for research. This research aims to provide a comprehensive overview of the state-of-the-art and current landscape in FHIR-based data models and structures. In addition, we intend to identify and discuss the tools, resources, limitations, and other critical aspects mentioned in the selected research papers. To ensure the extraction of reliable results, we followed the instructions of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. We analyzed the indexed articles in PubMed, Scopus, Web of Science, IEEE Xplore, the ACM Digital Library, and Google Scholar. After identifying, extracting, and assessing the quality and relevance of the articles, we synthesized the extracted data to identify common patterns, themes, and variations in the use of FHIR-based data models and structures across different studies. On the basis of the reviewed articles, we could identify 2 main themes: dynamic (pipeline-based) and static data models. The articles were also categorized into health care use cases, including chronic diseases, COVID-19 and infectious diseases, cancer research, acute or intensive care, random and general medical notes, and other conditions. Furthermore, we summarized the important or common tools and approaches of the selected papers. These items included FHIR-based tools and frameworks, machine learning approaches, and data storage and security. The most common resource was "Observation" followed by "Condition" and "Patient." The limitations and challenges of developing data models were categorized based on the issues of data integration, interoperability, standardization, performance, and scalability or generalizability. FHIR serves as a highly promising interoperability standard for developing real-world health care apps. The implementation of FHIR modeling for electronic health record data facilitates the integration, transmission, and analysis of data while also advancing translational research and phenotyping. Generally, FHIR-based exports of local data repositories improve data interoperability for systems and data warehouses across different settings. However, ongoing efforts to address existing limitations and challenges are essential for the successful implementation and integration of FHIR data models.

Hepatoprotective activity of medicinal plants, their phytochemistry, and safety concerns: a systematic review.

Medicinal plants and their derivatives represent a promising reservoir of remedies for various ailments. Especially secondary metabolites of these plants, including alkaloids, flavonoids, phenolic compounds, terpenoids, steroids, saponins, tannins, and anthraquinones, play crucial roles in hepatoprotection. Studies have identified several prominent phytoconstituents, such as silymarin, quercetin, luteolin, glycyrrhizin, curcumin, gallic acid, chebulic acid, catechin, aloin, emodin, liquiritin, liquiritigenin, cudraflavone B, and karaviloside, as effective agents for addressing hepatotoxicity. The mechanisms underlying their efficacy include antioxidant, anti-inflammatory, free radical scavenging, and the ability to block oxidative stress, cytokine production, and stabilize liver cell membranes. The application of natural products derived from medicinal plants in treating liver injuries is rooted in their efficacy, cost-effectiveness, and safety profile, contributing to their popularity. Many studies, encompassing invitro, invivo, preclinical, and clinical investigations, have demonstrated that the extracts of medicinal plants mitigate chemical-induced liver damage using animal models. However, intensive research efforts regarding the safety, regulatory standard, and quality control issues for using medicinal plants as hepatoprotective agents remain the strong task of scholars. The primary focus of this systematic review is to analyze the current state of the literature regarding treating liver ailments using extracts from medicinal plants, examining their phytochemical composition, and addressing associated safety considerations.

Involving lead users in firm’s standardization strategy within action groups: evidence from smart robotics

PurposeThis research explores how firms manage the complex technologies standardization in action groups. It considers the strategic issues that technology producers face when involving lead users in architecture design. Drawing on the multi-mode standardization literature, this study addresses two dilemmas regarding value creation and appropriation by technology producers within coalitions. The first dilemma is how to create value by developing solutions in compliance with industry standards. The second one is how to appropriate value while ensuring the technology sharing with action groups. The answers to these two dilemmas contribute to filling the research gap on value creation and appropriation in multi-mode standardization.Design/methodology/approachThe research focuses on technology producers participating in action groups where lead users play a crucial role. We conducted a qualitative analysis based on the standardization experience of a Japanese company specializing in smart robotics. Data are collected through semi-structured interviews with key actors. Action groups are defined operationally as a set of stakeholders including competitors of the technology producers, component suppliers, end users, services providers, research centers and academia. The case study is suitable for highlighting specific aspects of the standardization process during its manifestation. It reveals how firms create and appropriate value, providing details about its standardization strategy.FindingsOur findings show that smart robotics standardization is drivn by collaborative models, where the two dilemmas of value creation and appropriation are evident. Firstly, the case revealed that standardization is lead users oriented. Secondly, lead users’ involvement is crucial to customize technologies. Thirdly, the firm’s position is to share a part of the value with the members. The IPR policy is a matter of interest within action groups, since the collaboration is based on open innovation models to share patents and licenses related knowledge.Research limitations/implicationsThis research has some limitations attributable to the limited generalizability of the results due to the qualitative analysis. In addition, this study considers the perspective of technology producers, but should also take into account the perspective of both collective actions itself and the lead users. Findings have some implications in the strategy negotiation. Participating in action groups is not enough to ensure a competitive advantage. Involving lead users is of strategic importance to acquire a competitive advantage. Lead users contribute to the producers’ technology design, helping firms to differentiate solutions from the industry standard and create value from customized technologies.Practical implicationsThis study helps practitioners understand the competitive side of collective actions, clarifying the value capture and appropriability in standardization. The research provides insights to policymakers and standard development organizations committees when they are called to harmonize standards considering the fallouts on the sector’s competitiveness. Findings suggest appropriate property rights policies to manage the issues related to the value appropriability and technology sharing, recognizing action groups members for their contribution in value creation.Originality/valueThis study shows how firms deal within action groups with the two dilemmas of variety versus technology conformity and property rights versus technology sharing. It fills the research gap in collective actions, emphasizing the perspective of the individual firm in the group rather than the coalition strategy itself. This topic highlights the crucial role of lead users within action groups in managing the two dilemmas, offering a new perspective for understanding critical issues of multi-mode standardization. Reflecting on mechanisms and tools to manage the two dilemmas allows firms to protect their competitive advantage in coalitions.