Expert Analysis Research Articles

ANALYSIS OF THE IMPACT AND ACTUALITY OF CHALLENGES, RISKS AND THREATS TO THE SECURITY OF THE REPUBLIC OF SERBIA

Challenges, risks and threats to the security of the Republic of Serbia are defined by the National Security Strategy of the Republic of Serbia. However, the concept of security at the global level can be considered before and after beginning of the Russian-Ukrainian conflict. Consequently, the question arises of the need to analyze the relevance of the existing interpretation of challenges, risks and threats to the security of the Republic of Serbia. The goal of the work was stated, and for this purpose the research was conducted using: survey methods (survey technique) and statistical methods, with the fact that in the research process it was inevitable to implement the methods of expert evaluations, analysis and synthesis, induction and deduction. Respondents (experts) in the research were retired and active members of the military and civilian security services, members of the Committee for Defence and Security and the Committee for Control of Security Services of the National Assembly of the Republic of Serbia, diplomatic representatives of the Republic of Serbia and members of the academic community whose sphere of interest is security science. The research, at the level of scientific description, resulted in the following outcome, an expert analysis of the list of dangers to the security of the Republic of Serbia from the National Security Strategy of the Republic of Serbia was performed, and on the basis of which observed deficiencies can be eliminated. The analysis consisted of: checking the list of dangers according to changes in the strategic environment, determining their impact and selection by groups.

DEVELOPMENT OF ACECLOFENAC LOADED MICROSPONGE GELS: A STATISTICAL QUALITY BY DESIGN (QBD) APPROACH TOWARDS OPTIMIZATION AND EVALUATION

Objective: The current research aims to deliver Aceclofenac in a controlled manner through a microsponges-loaded drug delivery system for the treatment of inflammation. Methods: The formulations were prepared by the Quasi-emulsion solvent diffusion method and characterized for particle size and drug entrapment efficiency. For the optimization of the formulation through the Quality by Design (QbD) approach, Quality target product profiles (QTPP) were set up considering various key factors that affect the quality of the formulation. Further optimization of the important factors in relation to the major Critical Quality Attributes (CQAs) was conducted by applying full factorial design using the Design of Expert Software (11.0 software, Stat-Ease, Inc., USA). The optimized formulation was incorporated into the gel, and characterized for morphological analysis by Scanning Electron Microscopy (SEM), drug content, and ex-vivo permeation studies (DD solver, Version 2.0). Results: It was found that process parameters such as drug-to-polymer ratio, the volume of the internal phase, and concentration of the emulsifier and polyvinyl alcohol (PVA), played a crucial role in improving the drug entrapment efficiency and particle size. On the other hand, stirring time did not significantly affect the particle size. Through Design of Expert (DOE) analysis, a PVA concentration of 0.641 mg/ml and an internal phase volume of 12.5 ml were identified to be the ideal concentrations to obtain the optimized microspongal gel formulation (MS4). Characterization studies were carried out on MS4, which displayed a drug encapsulation of 94%, with a Cmax of 81.62 mg/ml, and a Tmax of 12 h. Stability studies carried out as per the International Conference of Harmonization (ICH) guidelines confirmed no noticeable change in physical appearance and drug content. Conclusion: Overall, this study focused on optimizing the formulation of microsponges for efficient dermal drug delivery, considering various critical variables and process parameters. The resulting optimized formulation demonstrated promising drug release and potential for the effective management of inflammation disorders.

Abstract 17420: Enhanced Identification of Cardiac Wall Motion Abnormalities: An Externally Validated Deep Neural Network Approach Outperforms Expert and Quantitative Analysis of Electrocardiograms

Background: Cardiac wall motion abnormalities (WMA) independently predict mortality and other adverse events beyond ejection fraction. Clinical screening relies on detection of ECG Q waves yet has poor predictive accuracy. Hypothesis: We hypothesized that ECG features beyond the Q wave could be identified by deep learning to improve WMA detection over standard ECG measurements. Methods: We collected ECGs and echocardiogram pairs (Panel A) in 35,210 unique patients who underwent both studies within 60 days at Stanford University. WMAs were determined by natural language processing (NLP) of clinical reports (Panel B). Five second ECG signals were extracted digitally and used to develop and test a DNN. For development, 80% of the pairs were used and 20% (N = 7042) were reserved for internal validation. We then tested the model performance on 2,338 echo/ECG pairs from Emory University. For comparison, qualitative physician statements from the ECG interpretation suggesting myocardial injury, ischemia, or infarct were labeled using NLP, and a logistic regression model was developed to include quantitative Q-wave measurements. Results: In the internal validation cohort (62.9±16.9 years, 47% female, 58% white), DNN of the ECG detected echocardiographic WMA with a c-statistic of 0.781 (CI: 0.764-0.798) which was superior to quantitative ECG Q wave measurement (0.632, CI: 0.605-0.661) or qualitative interpretation (0.595) (Panel C). Performance was not improved by incorporating demographic data. In the external cohort (61.9±16.0 years, 48% female, 48% white), the DNN AUC was 0.723 (CI:0.689-0.758). Conclusion: Deep learning improves detection of cardiac WMAs from the electrocardiogram in an externally validated model compared with standard ECG analysis. Application of this model may provide improved screening for regional myocardial injury. Further work will determine which features beyond the Q wave provide improved performance.

HLA Typing and Donor-Specific Antibody Screening in Kidney Transplantation: Bridging the Past to the Future

Human leukocyte antigens (HLA) are unique proteins expressed on the surface of human cells, playing a pivotal role in the immune system, particularly in the contexts of infection, cancer, and transplantation. The widespread adoption of HLA typing methods has become an essential component in assessing donor-recipient compatibility, a crucial limiting factor in solid organ transplantation. In general, the greater the disparity between a donor's and recipient's HLA types, the higher the likelihood of provoking an alloimmune response, which frequently results in alloimmune graft rejection. With significant advancements in organ transplantation techniques, immunosuppressive medications, and surgical procedures, attention has increasingly turned toward understanding and managing humoral rejection processes. Pre-transplant antibody screening plays a critical role in identifying individuals with elevated levels of antibodies against potential donor antigens. This screening aids in risk assessment and planning to mitigate the risk of antibody-mediated rejection (AbMR). Several methods are available for assessing circulating antigen-specific antibodies and HLA tissue typing, including cell-based assays like serological assays, complement-dependent cytotoxicity, and flow cytometry. However, non-cell-based approaches, such as molecular methods, HLA imputation techniques and high-throughput HLA-matchmaker assays have gained significant popularity due to their ability to provide higher resolution and robust donor-recipient matching. Despite the advancements in precision and sensitivity observed in HLA cutting-edge technologies, numerous challenges still persist. These challenges involve complexities linked to allelic ambiguities, the differentiation of closely related alleles, and the ongoing effort to establish a standardized HLA testing methodology across diverse laboratories. Additionally, correlating the HLA crossmatch results with the clinical outcomes for transplant donors poses another important aspect that warrants attention and requires expert analysis. In this review, we will enumerate the different methods of HLA typing and DSA screening and discuss the unmet needs and future directions for HLA typing methods.

Plasma Aβ42/Aβ40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease.

Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aβ) into screening algorithms may improve screening efficiency. Plasma Aβ, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by>20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status. The area under the receiver operating curve (AUC) was 0.87 for Aβ42/Aβ40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95. Including plasma p-tau217/np-tau217 along with Aβ42/Aβ40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials. gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.

To the revision of the ISO 1999:2013 standard "Acoustics. Assessment of hearing loss due to noise exposure": an excessive correction for the "impulsiveness" of noise

Introduction. In connection with the development of measuring and computer technology, new opportunities and approaches are opening up to solve the problem of measurement, hygienic assessment, normalization and prediction of hearing impairment from exposure to unstable, in particular, pulse noise.
 The study aims to analyze the applicability of a model for assessing hearing loss based on the use of an excessive correction to the exposure of impacting noise, according to the draft ISO 1999:2023 standard.
 Materials and methods. The scientists have conducted an expert and analytical comparative analysis of ISO 1999 standards, which define the basis for assessing hearing loss due to noise exposure. The experts have carried out a literary review of domestic and foreign sources on the problem of using the index of the distribution of instantaneous values of sound pressure — excess to assess constant and non-constant noise, as well as its role in the formation of hearing loss under the action of non-Gaussian pulse noise, the applicability of the prediction model of the ISO 1999 standard to various types of noise exposure.
 Results. The scientists presented the results of the analysis of: indicators for assessing the adverse effects of non-constant, including pulse noise; the relationship between the effects of non-Gaussian noise and the constant shift in the hearing thresholds of workers; statistical indicator of excess — an indirect indicator of the temporal structure of noise, a significant risk factor in combination with noise exposure in the assessment of hearing loss.
 Conclusion. Revision of the ISO 1999:2013 standard with the introduction of a new indicator of the temporal structure of noise — kurtosis, will improve the accuracy of the method of predicting hearing loss when exposed to constant, non-constant noise, including impulsive.
 Ethics. In preparing the article, the authors were guided by the ethical principles of medical research set out in the Helsinki Declaration of the World Medical Association of the last revision.
 Limitation. Features of ISO 1999 standards dedicated to the assessment of the impact of industrial noise and the assessment of noise-induced hearing impairment.

Physical relief potential through robot-assisted mobilization in nursing care: an exploratory study

PurposePhysically demanding activities at the nursing bed are a key factor in the overwork of nursing staff and play a major role in the development of musculoskeletal disorders. The heavy back strain plays a significant part in this. Technical aids such as robotic assistance systems have the potential to minimize this overload during nursing activities. In the present work, we have investigated the relief potential of a supporting robotic assistance system developed in the AdaMeKoR project. An exploratory study design was developed to assess the relief potential of the robotic system for nurses during the care action of repositioning from the supine position to the sitting position at the edge of a nursing bed under kinaesthetic principles.MethodsThe study was conducted in March 2022 with a total of 21 nursing professionals participating. Safety precautions at this stage of the robot’s development made it necessary to use a 40 kg patient simulator instead of having a human act as the patient. Each participant performed the repositioning three times in the conventional manner and three times with the robotic-assistance. The conventional and the robotic-assisted task execution was compared using different perspectives of analysis. From a sensory perspective, ground reaction forces and electromyography data were collected and analyzed. A kinaesthetic perspective was added using 3D-video data which was analyzed by professional kinaesthetics trainers. A third perspective was added by collecting the subjective workload experiences of the participants.ResultsWhile participants’ self-assessment based on a NASA-TLX questionnaire suggests more of a physical and psychological strain from using the robot, electromyography shows a 24.41% reduction in muscle activity for left back extensors and 7.99% for right back extensors. The kinaesthetic visual inspection of the study participants also allows conclusions to be made that the robot assistance system has a relieving effect when performing the nursing task.ConclusionsThe conducted study suggests that overall the robotic-assistance has the potential of relieving nurses of partial physical exertion during mobilization. However, the different focuses of analysis show varying results in regard to external, i.e. sensor data and expert analysis, compared to internal, i.e. the nurses, perspectives. Going forward, these results have to be further expanded to get more robust analyses and insights on the interdependencies of subjective factors contributing to the experience of workload. In view of the fact that robotics for nursing is still a relatively new field and there are various lessons to be learned regarding the conceptualization of studies and corresponding evaluations, our approach of combining perspectives of analysis allows for a more differentiated view of the subject at hand.

Understanding the Drivers of Drought Onset and Intensification in the Canadian Prairies: Insights from Explainable Artificial Intelligence (XAI)

Abstract Recent advances in artificial intelligence (AI) and explainable AI (XAI) have created opportunities to better predict and understand drought processes. This study uses a machine learning approach for understanding the drivers of drought severity and extent in the Canadian Prairies from 2005 to 2019 using climate and satellite data. The model is trained on the Canadian Drought Monitor (CDM), an extensive dataset produced by expert analysis of drought impacts across various sectors that enables a more comprehensive understanding of drought. Shapley additive explanation (SHAP) is used to understand model predictions during emerging or worsening drought conditions, providing insight into the key determinants of drought. The results demonstrate the importance of capturing spatiotemporal autocorrelation structures for accurate drought characterization and elucidates the drought time scales and thresholds that optimally separate each CDM severity category. In general, there is a positive relationship between the severity of drought and the time scale of the anomalies. However, high-severity droughts are also more complex and driven by a multitude of factors. It was found that satellite-based evaporative stress index (ESI), soil moisture, and groundwater were effective predictors of drought onset and intensification. Similarly, anomalous phases of large-scale atmosphere–ocean dynamics exhibit teleconnections with Prairie drought. Overall, this investigation provides a better understanding of the physical mechanisms responsible for drought in the Prairies, provides data-driven thresholds for estimating drought severity that could improve future drought assessments, and offers a set of early warning indicators that may be useful for drought adaptation and mitigation. Significance Statement This work is significant because it identifies drivers of drought onset and intensification in an agriculturally and economically important region of Canada. This information can be used in the future to improve early warning for adaptation and mitigation. It also uses state-of-the-art machine learning techniques to understand drought, including a novel approach called SHAP probability values to improve interpretability. This provides evidence that machine learning models are not black boxes and should be more widely considered for understanding drought and other hydrometeorological phenomena.

IMPROVING THE MECHANISM OF ADMINISTRATIVE AND LEGAL ENSURING OF THE FINANCIAL AND ECONOMIC SECURITY OF THE STATE

The main purpose of the article is to improve the mechanism of administrative and legal ensuring for the financial and economic security (FES) of the state. The object of the study is to ensure the FES of the state. The scientific task is to formulate blocks for improving the mechanism of administrative and legal ensuring for the FES of the state, taking into account measures to counter the negative impact of threats to this type of security at the state level. The methodology includes methods, such as the method of analysis and synthesis for research and work with information and information on the issue, as well as the abstract-logical method, which helped to generalize this and draw conclusions, expert analysis to determine the main threats and the method of paired comparisons to streamline administrative and legal measures to counter the main threats to ensure the FES of the state, which serves as the basis for improving the mechanism. The study proves that the mechanism of administrative and legal ensuring for the FES of the state should include measures to counter the negative impact of the main threats, the influence of which is increasing due to the dynamism of the external environment. A methodology for determining the priority of implementing administrative and legal measures to counter threats to ensuring the FES of the state is presented, which served as the basis for improving the mechanism. The author's novelty lies in the presentation of the improvement process the mechanism of administrative and legal ensuring for the FES of the state. The study has two main limitations: not taking into account all possible threats during the expert analysis and taking into account the specifics of only Ukraine and its characteristics and conditions for the development of security as a result of the war.

Andrew Mayes’ expert analysis of a case of memory distortion

In this single-case study of memory distortion where Andrew Mayes was involved as an expert witness, a surgeon falsely recalled aspects of a patient safety adverse event in which he was involved, and where he was put through an investigatory process by a regulatory body. Andrew Mayes’ expert analysis of the role of memory distortion in this case resulted in the surgeon being exonerated.

Fault diagnosis of photovoltaic systems using artificial intelligence: A bibliometric approach

Conventional fault detection methods in photovoltaic systems face limitations when dealing with emerging monitoring systems that produce vast amounts of high-dimensional data across various domains. Accordingly, great interest appears within the international scientific community for the application of artificial intelligence methods, which are seen as a highly promising solution for effectively managing large datasets for detecting faults. In this review, more than 620 papers published since 2010 on artificial intelligence methods for detecting faults in photovoltaic systems are analyzed. To extract major research trends, in particular to detect most promising algorithms and approaches overcoming excessive time calculations, a conventional bibliographic survey would have been extremely difficult to complete. That is why this study proposes to carry out a review with an innovative approach based on a statistical method named Bibliometric and a Expert qualitative content analysis. This methodology consists of three stages. First, a collection of data from databases is carried out with all precautions to achieve a large, robust, high-quality database. Second, multiple bibliometric indicators are chosen based on the objectives to be achieved and analyzed to assess their real impact, such as the quantity and nature of publications, collaborative connections among organizations, researchers, and countries or most cited articles. Finally, the Expert qualitative content analysis carried out by experts identifies the current and emerging research topics that have the greatest impact on fault detection in photovoltaic systems using artificial intelligence.

Android-Based Project-Based Learning Integrated Gravimetric Analysis for Chemical Expertise Analysis of Vocational School: Development of Teaching Materials

This study aimed to produce gravimetric analysis teaching materials and determine the validity test of gravimetric analysis teaching materials. The development of teaching materials is carried out using the ADDIE development model (Analysis-Design-Development-Implementation-Evaluation). The results of the development of teaching materials are in the form of applications with the APK extension that can be run on Android smartphones. The teaching material validation test obtained the percentage of assessment which included aspects of the content of teaching materials by 84.3% (very feasible), media aspects by 83.9% (very feasible), construct aspects of teaching materials by 81.7% (very feasible), aspects the language used is 79.2% (decent), and the aspect of conformity with the PjBL is 80.9% (very decent). Of the five aspects of the gravimetric analysis validation test assessment, the teaching materials developed were very feasible, with a total percentage of 82.87%. While the readability test got a percentage of 87.3%, so it was categorized as very feasible to use

FUZZY MODELS FOR AIR QUAITY MONITORING TECHNOLOGY IN AERODROME

This article aims to develop a methodology, which can improve the reliability of monitoring air pollution results in the aerodrome environment in the case of Almaty airport. In order to achieve this goal, the Digital Transformation technology was analytically justified and considered. To solve this multidimensional problem effectively in the conditions of the aerodrome environment, a number of problems were investigated theoretically and practical recommendations were proposed. Furthermore, a vector of atmospheric ingredients which pollutes the aerodrome environment was formed which takes into account the natural-climatic and geographical features of the Almaty airport. An expert analysis was carried out to find out an impact of contaminants to the aerodrome atmospheric environment of Almaty airport. In addition, a model of integrated assessment has been developed to analyse the quality of the aerodrome habitat per person. Also, a technological solution based on an UAV has been developed for a control and measurement process which monitors the air quality. This is carried out with the help of monitoring system control operator who specifies a height and radius of an aerodrome virtual atmospheric “cylinder”. Also, formal models have been developed with the function of statistical characteristics of the parameters of a multi-agent control in order to assess and predict the risks of air quality control near an aerodrome environment. Finally, a computer experiment was carried out and 3D models of the simulation results were built.

Phenomenological Analysis of School Curriculum

The article considers school curricula as a pedagogical phenomenon, which is understood as a general reflection of theoretical ideas about the content of education, fixed in a normative document and maintaining relative stability over a long period of time. The purpose of the article is to describe the main characteristics of curricula that determine the features of the school curriculum as a pedagogical phenomenon. The main research method is phenomenological analysis, auxiliary methods are historical and pedagogical analysis and expert analysis of documents. The analysis of curricula created over 100 years in Soviet and Russian schools is carried out in the logic of a systematic approach. As a result of the study, the author identified a set of qualitative characteristics of curricula: focus on achieving learning outcomes, objectivity, integrativity, consistency, variability, stability (sustainability), richness, flexibility, cultural conformity. Among them, a “core” of permanent characteristics has been singled out, which have been characteristic of curricula for decades in an almost unchanged form and which ensure the functionality of this type of pedagogical documentation. In addition, the author additionally highlights additional qualities that, in different periods of the development of the education system, are manifested in curricula to varying degrees, from the minimum to the maximum possible. The identified complex of characteristics reveals the value-semantic basis of curricula and their deep non-linear connections with the content of education.

Non-financial reporting of corporations

One of the important directions in the development of modern corporate reporting is the disclosure of the sustainable development of a corporation, which involves assessing the results of operations and managing changes on the way to a sustainable economy that combines data on long-term profitability, social responsibility and care for environmental protection. Therefore, non-financial reporting is becoming the main tool for communicating the information to stakeholders about the economic, environmental, and social results of a corporation’s activities. Currently, the publication of non-financial reports is carried out by transnational and large national corporations, state and municipal organizations in many countries. In the Russian Federation, the need to promote non-financial reporting is approved by the Concept for the Development of Public Non-Financial Reporting (Concept), as a state task that defines this reporting as an element of the management system, development of communications with stakeholders, a prerequisite for increasing efficiency and strengthening corporate competitiveness. A significant impact on the development of public non-financial reporting was made by the United Nations resolution containing 17 goals in the field of sustainable development, which determines the need to develop indicators that evaluate the achievement of goals at the national and global levels and reflect the contribution of the corporation to sustainable development, which are solved in the framework of public nonfinancial reporting. Large and transnational corporations are encouraged to apply sustainable production practices and reflect information on the rational use of resources in their reports. Meaningful, complete, timely, accurate, balanced, comparable and reliable information of public non-financial reporting ensures that stakeholders make informed economic decisions about the sustainability of the corporation, the impact on the environment and society. At the state level, information from public non-financial reporting makes it possible to assess the achievement of strategic goals, the need to combine or separate the activities of sectors of society. The aim of the study was to assess the key concepts of sustainability reporting, the order and specifics of disclosure of its elements and material topics reflecting the impact of the corporation on the economy, environment and society. Among the objectives set by the authors is the assessment of the principles of this type of reporting: comparability, completeness, timeliness, and verifiability, which are closely related to those used in financial reporting. Since the calculation of separate indicators of non-financial reporting and the methodology of formation of consolidated financial reporting (participation method, joint activities, etc.) are closely related, the scope of the study includes the ways of reflecting the elements of reporting. Such scientific methods as logical, expert and substantive analyses, interpretation were used in the work. The results of the research can be used by corporate specialists in the formation of reporting in the field of sustainable development, university professors in the educational process, and other parties interested in the results of corporate activities

Creation and Assessment of a Novel Design Evaluation Tool for Additive Manufacturing

Abstract Additive manufacturing (AM) is a rapidly growing technology within the industry and education sectors. Despite this, there lacks a comprehensive tool to guide AM novices in evaluating the suitability of a given design for fabrication by the range of AM processes. Existing design for additive manufacturing (DfAM) evaluation tools tend to focus on only certain key process-dependent DfAM considerations. By contrast, the purpose of this research is to propose a tool that guides a user to comprehensively evaluate their chosen design and educates the user on an appropriate DfAM strategy. The tool incorporates both opportunistic and restrictive elements, integrates the seven major AM processes, outputs an evaluative score, and recommends processes and improvements for the input design. This paper presents a thorough framework for this evaluation tool and details the inclusion of features such as dual-DfAM consideration, process recommendations, and a weighting system for restrictive DfAM. The result is a detailed recommendation output that helps users to determine not only “Can you print your design?” but also “Should you print your design?” by combining several key research studies to build a comprehensive user design tool. This research also demonstrates the potential of the framework through a series of user-based studies, in which the opportunistic side of the tool was found to have significantly improved novice designers’ ability to evaluate designs. The preliminary framework presented in this paper establishes a foundation for future studies to refine the tool’s accuracy using more data and expert analysis.

Parent attitudes towards data sharing in developmental science

Background Data sharing in developmental science is increasingly encouraged, supported by funder and publisher mandates for open data access. Data sharing can accelerate discovery, link researchers with high quality analytic expertise to researchers with large datasets and democratise the research landscape to enable researchers with limited funding to access large sample sizes. However, there are also significant privacy and security concerns, in addition to conceptual and ethical considerations. These are particularly acute for developmental science, where child participants cannot consent themselves. As we move forward into a new era of data openness, it is essential that we adequately represent the views of stakeholder communities in designing data sharing efforts. Methods We conducted a comprehensive survey of the opinions of 195 parents on data sharing in developmental science. Survey themes included how widely parents are willing to share their child’s data, which type of organisations they would share the data with and the type of consent they would be comfortable providing. Results Results showed that parents were generally supportive of curated, but not open, data sharing. In addition to individual privacy and security concerns, more altruistic considerations around the purpose of research were important. Parents overwhelmingly supported nuanced consenting models in which preferences for particular types of data sharing could be changed over time. This model is different to that implemented in the vast majority of developmental science research and is contrary to many funder or publisher mandates. Conclusions The field should look to create shared repositories that implement features such as dynamic consent and mechanisms for curated sharing that allow consideration of the scientific questions addressed. Better communication and outreach are required to build trust in data sharing, and advanced analytic methods will be required to understand the impact of selective sharing on reproducibility and representativeness of research datasets.

A fenntartható ellátási láncok rövidítése Magyarországon és Európában

The study examines the impact of supply disruptions arising from the COVID-19 pandemic and the energy security challenges primarily resulting from the Russian-Ukrainian war on the re-evaluation of sustainability considerations and the European green transition, especially regarding the potential strategic importance of renewable energy sources. The justification for the shortening of the long supply chains can be argued from the perspectives of supply security and sustainability. Furthermore, the economic validation of sustainability considerations is receiving increasing attention in professional discourse, sparking public debate. One of the primary tensions underlying these polemics is the conflict between short-term economic interests and long-term sustainability and environmental considerations. These interests often contradict each other, and the ongoing professional debate surrounding the shortening of supply chains provides relevant insight into these conflicts. However, the supply disruptions resulting from COVID-19 have re-emphasized the importance of supply security, prompting many economic actors to reconsider their supply strategies. The growing significance of supply security is evident in surveys, expert analyses, and economic strategic documents. The energy challenges posed by the Russian-Ukrainian war have, in turn, prompted EU policymakers to reform the energy strategy. The risks associated with energy security highlighted the vulnerabilities stemming from dependency on external fossil-based energy sources. This article aims to answer the question of how short-term economic interests and longer-term sustainability goals can be reconciled in light of the supply disruptions experienced during COVID-19 and the Russian-Ukrainian war. It does this through a literature review of professional debates and relevant expert analyses, strategic EU documents, and by examining key indicators of the EU's energy dependence. The restructuring of the EU's energy policy demonstrates the feasibility of rapidly implementing major transformations in complex systems when necessary. Beyond facilitating professional discourse, the experiences from these events can also boost the European green transition, as a green Europe built on its renewable resources can be more resilient against challenges of the future. This is in line with both economic and environmental objectives. The main conclusion of the research is that the EU's successful transition to renewable energy sources, in addition to achieving environmental goals, can contribute to reducing external risks through the alleviation of energy dependence. Furthermore, energy security provided by its own energy sources facilitates the growth of the real economy and underpins the EU's geopolitical position.

Revolutionizing Medical Microbiology: How Molecular and Genomic Approaches Are Changing Diagnostic Techniques.

Molecular and genomic approaches have revolutionized medical microbiology by offering faster and more accurate diagnostic techniques for infectious diseases. Traditional methods, which include culturing microbes and biochemical testing, are time-consuming and may not detect antibiotic-resistant strains. In contrast, molecular and genomic methods, including polymerase chain reaction (PCR)-based techniques and whole-genome sequencing, provide rapid and precise detection of pathogens, early-stage diseases, and antibiotic-resistant strains. These approaches have advantages such as high sensitivity and specificity, the potential for targeted therapies, and personalized medicine. However, implementing molecular and genomic techniques faces challenges related to cost, equipment, expertise, and data analysis. Ethical and legal considerations regarding patient privacy and genetic data usage also arise. Nonetheless, the future of medical microbiology lies in the widespread adoption of molecular and genomic approaches, which can lead to improved patient outcomes and the identification of antibiotic-resistant strains. Continued advancements, education, and exploration of ethical implications are necessary to fully harness the potential of molecular and genomic techniques in medical microbiology.

Comparative Analysis of Expert and Public Perspectives on Prominent Urban Street Components Which Determine Physical Safety and Comfort of Users:

Comparative Analysis of Expert and Public Perspectives on Prominent Urban Street Components Which Determine Physical Safety and Comfort of Users: