Organization For Economic Cooperation Research Articles

INTERNATIONAL ANTI-CORRUPTION STANDARDS IN THE PRIVATE SPHERE

The article examines the international legal basis for combating corruption of a universal and regional nature, which is recognized by standards and contains norms for preventing this offense in the private sphere. In particular, attention is paid to the provisions of the only universal international treaty - the UN Convention against Corruption (UNCAC), in which the norms for combating corruption in the private sector were established. It is noted that the provisions of the UNCAC became the basis for the development of a comprehensive response to the global problem. The provisions of the treaties (The Criminal Law Convention on Corruption (ETS 173), Additional Protocol to the Convention (ETS 191), Council of Europe Criminal Law Convention on Corruption (ETS 174)) and advisory norms adopted within the framework of the Council of Europe on countering corruption. It is emphasized that the approach of this organization to the fight against corruption has three interrelated aspects: development of pan-European norms and standards, monitoring of their compliance, as well as provision of technical assistance to states and regions. The focus is on the anti-corruption norms of the European Union (Treaty on the Functioning of the European Union, directives, sectoral norms, etc.) and the policy of the Union regarding the reform of existing legal prescriptions and relevant measures in this area. It is noted that a feature of EU acts is the emphasis on the role of the private sector as a partner in the fight against corruption. An analysis of the legal instruments of the Organization for Economic Cooperation and Development (OECD) on combating corruption, bribery and promoting integrity in the public and private sectors was carried out, and it was emphasized that the OECD is the main source of recommendations and guidelines in the field of business integrity. Practical materials, the purpose of which is to provide assistance to member states of the organization in implementing the provisions of treaty norms in the field of responsible business behavior of business entities, are also significant. Appropriate conclusions have been made.

Comparative Analysis of Indoor Air Quality and Thermal Comfort Standards in School Buildings across New Zealand with Other OECD Countries

COVID-19 has improved awareness of the importance of appropriate indoor air quality (IAQ) in indoor spaces, particularly in classrooms where children are expected to learn. Research has shown that poor IAQ and temperature levels affect the cognitive performance of children. In this paper, we critically compare IAQ standards for New Zealand’s Designing Quality Learning Spaces (DQLS Document) against international benchmarks from the Organization for Economic Co-operation and Development (OECD) countries, including ASHRAE 62.1, CIBSE TM57, EN-15251, WHO AQGs, and Building Bulletins 99 and 101. The aim was to ascertain the robustness of New Zealand’s DQLS document, identify areas of superiority, and recommend the required improvement for appropriate IAQ and thermal comfort in classrooms. This comparison review focuses on IAQ parameters: CO2 levels, temperature, ventilation rates, room size, occupant density, and occupancy rates. The findings illuminate a slight lag in New Zealand’s DQLS standards compared to her international counterparts. For instance, while New Zealand’s standards align closely with WHO standards for IAQ concerning temperature and ventilation rates, the recommended CO2 range appears slightly inadequate (800 to 2000 ppm) along with occupancy and classroom size for effectively controlling classroom pollutant growth. This paper emphasises the need to align New Zealand’s IAQ and thermal comfort standards with optimal OECD benchmarks. The identified disparities present opportunities for improving learning spaces in terms of CO2 concentration, size of classroom, and occupant density in schools in New Zealand to meet globally recognised standards, ultimately creating a healthier and more conducive learning environment.

Low PISA Performance Students: Factors, Perceptions, and Improvement Strategies

The PISA assessment serves as a critical tool for evaluating and improving educational systems worldwide. The ethical implications of low performance in PISA are significant, requiring a comprehensive approach to address both immediate educational needs and broader systemic issues. By leveraging insights from PISA and implementing evidence-based interventions, policymakers and educators can work towards creating a more equitable and effective educational environment for all students. This study investigates the underlying factors contributing to the low achievement of Jordanian students in the Program for International Student Assessment (PISA) tests and proposes effective strategies to enhance their performance. PISA, developed by the Organization for Economic Co-operation and Development (OECD), evaluates 15-year-old students' skills in reading, mathematics, and science, focusing on their ability to apply knowledge in real-world contexts. Despite its global significance, Jordanian students have consistently underperformed in these assessments. The study employs a mixed-methods approach, including a comprehensive literature review, analysis of the Jordanian educational context, and surveys with educators and students. The findings reveal several key factors impacting performance: curriculum misalignment with PISA competencies, socio-economic disparities, high teacher turnover, and varying levels of teaching quality. Additionally, perceptions of PISA among educators and students highlight challenges related to unfamiliar test formats and applied knowledge requirements. Based on these insights, the study recommends a series of interventions to improve performance. These include aligning the national curriculum with PISA competencies, enhancing teacher training programs, integrating technology into learning processes, promoting extracurricular activities, and fostering active parental involvement. By addressing these areas, the study aims to provide a roadmap for policymakers, educators, and stakeholders to enhance Jordanian students' performance in future PISA assessments and overall educational outcomes.

Integrating human expertise & automated methods for a dynamic and multi-parametric evaluation of large language models’ feasibility in clinical decision-making

BackgroundRecent enhancements in Large Language Models (LLMs) such as ChatGPT have exponentially increased user adoption. These models are accessible on mobile devices and support multimodal interactions, including conversations, code generation, and patient image uploads, broadening their utility in providing healthcare professionals with real-time support for clinical decision-making. Nevertheless, many authors have highlighted serious risks that may arise from the adoption of LLMs, principally related to safety and alignment with ethical guidelines. ObjectiveTo address these challenges, we introduce a novel methodological approach designed to assess the specific feasibility of adopting LLMs within a healthcare area, with a focus on clinical nursing, evaluating their performance and thereby directing their choice. Emphasizing LLMs’ adherence to scientific advancements, this approach prioritizes safety and care personalization, according to the “Organization for Economic Co-operation and Development” frameworks for responsible AI. Moreover, its dynamic nature is designed to adapt to future evolutions of LLMs. MethodThrough integrating advanced multidisciplinary knowledge, including Nursing Informatics, and aided by a prospective literature review, seven key domains and specific evaluation items were identified as follows:1.State of the Art Alignment & Safety.2.Focus, Accuracy & Management of Prompt Ambiguity.3.Data Integrity, Data Security, Ethics & Sustainability, in accordance with OECD Recommendations for Responsible AI.4.Temporal Variability of Responses (Consistency)5.Adaptation to specific standardized terminology and Classifications for healthcare professionals.6.General Capabilities: Post User Feedback Self-Evolution Capability and Organization in Chapters.7.Ability to Drive Evolution in Healthcare.A Peer Review by experts in Nursing and AI was performed, ensuring scientific rigor and breadth of insights for an essential, reproducible, and coherent methodological approach. By means of a 7-point Likert scale, thresholds are defined in order to classify LLMs as “unusable”, “usable with high caution”, and “recommended” categories.Nine state of the art LLMs were evaluated using this methodology in clinical oncology nursing decision-making, producing preliminary results. Gemini Advanced, Anthropic Claude 3 and ChatGPT 4 achieved the minimum score of the State of the Art Alignment & Safety domain for classification as “recommended”, being also endorsed across all domains. LLAMA 3 70B and ChatGPT 3.5 were classified as “usable with high caution.” Others were classified as unusable in this domain. ConclusionThe identification of a recommended LLM for a specific healthcare area, combined with its critical, prudent, and integrative use, can support healthcare professionals in decision-making processes.

Investigating the Correlation between Air Pollution and Housing Prices in Seoul, South Korea: Application of Explainable Artificial Intelligence in Random Forest Machine Learning

South Korea’s Particulate Matter (PM) concentration is among the highest among Organization for Economic Cooperation and Development (OECD) member countries. However, many studies in South Korea primarily focus on housing characteristics and the physical built environment when estimating apartment prices, often neglecting environmental factors. This study investigated factors influencing apartment prices using transaction data for Seoul apartments provided by the Ministry of Land, Infrastructure, and Transport (MOLIT) in 2019. For this purpose, the study compared and analyzed a traditional hedonic price model with a machine learning-based random forest model. The main findings are as follows: First, the evaluation results of the traditional hedonic price model and the machine learning-based random forest model indicated that the random forest model was found to be more suitable for predicting apartment prices. Second, an importance analysis using Explainable Artificial Intelligence (XAI) showed that PM is more important in determining apartment prices than access to education and bus stops, which were considered in this study. Finally, the study found that areas with higher concentrations of PM tend to have higher apartment prices. Therefore, when proposing policies to stabilize apartment prices, it is essential to consider environmental factors. Furthermore, it is necessary to devise measures such as assigning PM labels to apartments during the home purchasing process, enabling buyers to consider PM and obtain relevant information accordingly.

Wastewater disinfection with photodynamic treatment and evaluation of its ecotoxicological effects

Research has demonstrated the presence of viruses in wastewater (WW), which can remain viable for a long period, posing potential health risks. Conventional WW treatment methods involving UV light, chlorine and ozone efficiently reduce microbial concentrations, however, they produce hazardous byproducts and microbial resistance that are detrimental to human health and the ecosystem. Hence, there is a need for novel disinfection techniques. Antimicrobial Photodynamic Inactivation (PDI) emerges as a promising strategy, utilizing photosensitizers (PS), light, and dioxygen to inactivate viruses. This study aims to assess the efficacy of PDI by testing methylene blue (MB) and the cationic porphyrin TMPyP as PSs, along a low energy consuming white light source (LED) at an irradiance of 50 mW/cm2, for the inactivation of bacteriophage Phi6. Phi6 serves as an enveloped RNA-viruses surrogate model in WW. PDI experiments were conducted in a buffer solution (PBS) and real WW matrices (filtered and non-filtered). Considering the environmental release of the treated effluents, this research also evaluated the ecotoxicity of the resulting solution (post-PDI treatment effluent) on the model organism Daphnia magna, following the Organisation for Economic Cooperation and Development (OECD) immobilization technical 202 guideline. Daphnids were exposed to WW containing the tested PS at different concentrations and dilutions (accounting for the dilution factor during WW release into receiving waters) over 48 h. The results indicate that PDI with MB efficiently inactivated the model virus in the different aqueous matrices, achieving reductions superior to 8 log10 PFU/mL, after treatments of 5 min in PBS and of ca. 90 min in WW. Daphnids survival increased when subjected to the PDI-treated WW with MB, considering the dilution factor. Overall, the effectiveness of PDI in eliminating viruses in WW, the fading of the toxic effects on daphnids after MB’ irradiation and the rapid dilution effect upon WW release in the environment highlight the possibility of using MB in WW PDI-disinfection.

Analyzing the impact of fiscal conditions on private health expenditures in OECD countries: a quantile ARDL investigation.

Organization for Economic Co-operation and Development (OECD) countries have embraced the aim of universal health coverage, as established in Sustainable Development Goal (SDG) 3.8. This goal guarantees access to quality healthcare services without financial hardship or poverty. Additionally, it requires correct and adequate financing sources. A country with weak protection for its population tends to spend less on healthcare and experiences a high share of out-of-pocket payments (OOPs), increasing the likelihood of people falling into poverty. This study aims to understand the relationship and causal effects between macroeconomic and public fiscal conditions and private health expenditure in OECD countries between 1995 and 2019. We retrieved OECD data for 26 OECD countries for the period 1995-2019. Panel AutoRegressive Distributed Lag (PARDL) and panel quantile AutoRegressive Distributed Lag (PQARDL) models were estimated to examine the relationship between private health expenditures and macroeconomic and public fiscal variables. Our results reveal a positive influence of government debt and economic freedom on private health expenditures. They also show a negative influence of the government budget balance, government health expenditures, and economic growth on private health expenditures. These results collectively suggest that public fiscal conditions will likely impact private health expenditures. The findings of this study raise concerns about the equity and financial protection objectives of universal health coverage in OECD countries.

Servicification in Global Value Chains in Emerging and Developing Asian Economies

Servicification in global value chains (GVCs) in emerging and developing Asian economies has become a trend recently. However, there have been no scientific studies to elucidate the mechanism of servicification in GVCs. To fill this gap, this study aims to investigate the involvement of service sectors in GVCs in Asian economies in terms of the quantitative interactions between service inputs and manufacturing exports and inputs and between service inputs and service exports. For this purpose, a panel vector-autoregressive model and the Trade in Value Added database of the Organization for Economic Cooperation and Development (OECD) were used for the empirical analysis during 1995–2018. The estimation results find that, first, there exist reciprocal interactions between the business services and manufacturing sectors; foreign business service inputs are induced by manufacturing exports, whereas manufacturing inputs are induced by business service exports. Second, foreign manufacturing inputs facilitate foreign business service inputs. Third, business service inputs are promoted by business service exports. These trends in the involvement of business services’ involvement in GVCs have accelerated since the mid-2000s. To enhance the role of services in GVCs, Asian economies should facilitate the removal of explicit restrictions in service trade and address regulatory divergence across countries.

Boosting Sinh Cosh Optimizer and arithmetic optimization algorithm for improved prediction of biological activities for indoloquinoline derivatives

Quantitative Structure Activity Relation (QSAR) models are mathematical techniques used to link structural characteristics with biological activities, thus considered a useful tool in drug discovery, hazard evaluation, and identifying potentially lethal molecules. The QSAR regulations are determined by the Organization for Economic Cooperation and Development (OECD). QSAR models are helpful in discovering new drugs and chemicals to treat severe diseases. In order to improve the QSAR model's predictive power for biological activities of naturally occurring indoloquinoline derivatives against different cancer cell lines, a modified machine learning (ML) technique is presented in this paper. The Arithmetic Optimization Algorithm (AOA) operators are used in the suggested model to enhance the performance of the Sinh Cosh Optimizer (SCHO). Moreover, this improvement functions as a feature selection method that eliminates superfluous descriptors. An actual dataset gathered from previously published research is utilized to evaluate the performance of the suggested model. Moreover, a comparison is made between the outcomes of the suggested model and other established methodologies. In terms of pIC50 values for different indoloquinoline derivatives against human MV4-11 (leukemia), human HCT116 (colon cancer), and human A549 (lung cancer) cell lines, the suggested model achieves root mean square error (RMSE) of 0.6822, 0.6787, 0.4411, and 0.4477, respectively. The biological application of indoloquinoline derivatives as possible anticancer medicines is predicted with a high degree of accuracy by the suggested model, as evidenced by these findings.

Comparative Analysis between Quality of Life and Human Labor in Countries Belonging to G7 and BRICS Blocks: Proposition of Discriminant Analysis Model

The aim of the present research is to identify and analyze the variables which help to effectively differentiate Quality of Life (QoL) and human labor in the G7 (Germany, France, Italy, Canada, Japan, United Kingdom, and United States of America—USA) and BRICS countries (Brazil, Russia, India, China, and South Africa) through a discriminant analysis. A discriminant analysis model is developed to classify countries as having a low, mid, or high QoL based on QoL and human labor variables. The variables used in the discriminant analysis were obtained between 2010 and 2022 from two platforms: NUMBEO variables capable of relating QoL to socioeconomic aspects and OECD’s (Organization for Economic Cooperation and Development) human-labor-related variables. Based on the results, the three variables that most discriminate the groups in order of importance are employed women in relation to the female population, the female labor force participation rate, and the female unemployment rate. Countries are classified as having a low, mid, or high QoL. The adopted technique will allow researchers and managers to classify and draw goals for action reorganization and investment in QoL and labor.

The positive relationship between female employment and fertility rates: The role of family benefits expenditure and gender-role ideologies

This article interrogates the impacts of different types of family benefits expenditures on the positive relationship between female employment and fertility rates in developed welfare states. It does this by theorizing how these family benefits align with welfare state regimes’ preferences for different normative gender-role ideologies. Rather than treating family benefits as a monolith, this article investigates the impact of disaggregated expenditures in the Organisation for Economic Co-operation and Development (OECD) family policy database (1. services and in-kind benefits, 2. child-related cash benefits and 3. tax-based financial support for children) on both female employment and fertility rates. This is done using pooled time-series analysis covering the period 2000–9. The analysis yields evidence that expenditure most reflecting a ‘full egalitarian’ gender ideology including service and in-kind benefit provision has the most positive association with female employment and fertility due to an emphasis on defamiliarization. The picture for child-related cash benefits is mixed due to the presence of cash transfer provisions not employment-contingent captured in the indicator. In contrast, tax-based financial support for children harms female employment, reflecting a maternalistic ‘traditional’ ideological orientation, but is positive for fertility rates indicating a moderate pro-natal effect of tax-based financial support for children.

International cross-cultural development and field testing of the primary care practice questionnaire for the PaRIS survey (PaRIS-PCPQ)

BackgroundThe PaRIS survey, an initiative of the Organisation for Economic Co-operation and Development (OECD), aims to assess health systems performance in delivering primary care by measuring the care experiences and outcomes of people over 45 who used primary care services in the past six months. In addition, linked data from primary care practices are collected to analyse how the organisation of primary care practices and their care processes impact care experiences and outcomes. This article describes the development and validation of the primary care practice questionnaire for the PaRIS survey, the PaRIS-PCPQ.MethodThe PaRIS-PCPQ was developed based on domains of primary care practice and professional characteristics included in the PaRIS conceptual framework. Questionnaire development was conducted in four phases: (1) a multi-step consensus-based development of the source questionnaire, (2) translation of the English source questionnaire into 17 languages, (3) cross-national cognitive testing with primary care professionals in participating countries, and (4) cross-national field-testing.Results70 items were selected from 7 existing questionnaires on primary care characteristics, of which 49 were included in a first draft. Feedback from stakeholders resulted in a modified 34-item version (practice profile, care coordination, chronic care management, patient follow-up, and respondent characteristics) designed to be completed online by medical or non-medical staff working in a primary care practice. Cognitive testing led to changes in the source questionnaire as well as to country specific localisations. The resulting 32-item questionnaire was piloted in an online survey and field test. Data from 540 primary care practices from 17 countries were collected and analysed. Final revision resulted in a 34-item questionnaire.ConclusionsThe cross-national development of a primary care practice questionnaire is challenging due to the differences in care delivery systems. Rigorous translation and cognitive testing as well as stakeholder engagement helped to overcome most challenges. The PaRIS-PCPQ will be used to assess how key characteristics of primary care practices relate to the care experiences and outcomes of people living with chronic conditions. As such, policymakers and care providers will be informed about the performance of primary care from the patient’s perspective.

Charting the course: India’s health expenditure projections for 2035

ObjectivesUnderstanding past trends and forecasting future changes in health spending is vital for planning and reducing reliance on out-of-pocket (OOP) expenses. The current study analyzed health expenditure patterns in India and forecasted future trends and patterns until 2035. MethodsData on health expenditure in India from 2000 to 2019 was collected from the Organisation for Economic Co-operation and Development (OECD) iLibrary and National Health Accounts 2019 databases. Gross domestic product (GDP) data from the World Bank was also utilized. Descriptive statistics analyzed the composition and pattern, while the exponential smoothing model forecasted future health expenditures. ResultsThe findings revealed that expenditure made by OOP is the primary health financing source, followed by government and pre-paid private spending. The percentage of GDP allocated to total health expenditure remains stable, while the per capita health expenditure fluctuates. Variations in expenditure among states are observed, with Karnataka relying heavily on pre-paid private coverage. Future projections suggest a decline in per capita and total health expenditure as a share of GDP, with a slight increase in the government’s share. Pre-paid private expenditure per capita and OOP health expenditure as a share of the total is projected to remain relatively constant but still high in absolute terms. ConclusionThe study highlights variations in health spending in India, characterized by high OOP spending, limited public coverage, and a need for investments, and reforms to improve healthcare access and equity.

Evaluation of Neuroprotective effect of Cassia occidentalis L. against Colchicine Induced Memory Impairment in Wistar Rats

Background: Alzheimer’s disease (AD) is a progressive neurological disorder that develops with aging. Objective: In this research, we have examined the anti - Alzheimer’s effect of ethanolic extract from roots of Cassia occidentalis L. on colchicine-induced Alzheimer’s in Wistar rats Methods: Ethanolic extract was obtained and spectroscopic, chromatography analysis was performed. Acute toxicity studies using Organization of Economic Co-operation and Development (OECD) Guidelines 423 were performed to examine and make sure that there were no signs of toxic effects. The induction of AD was done using colchicine which leads to symptoms like neurotoxicity, neuroinflammation, and neurodegeneration. In this experiment, a thorough analysis of body weight, behavioral parameters, locomotor activity, and biochemical evaluation was performed to estimate the medicinal properties of Cassia occidentalis L in treating Alzheimer’s disease. Results: Pharmacognostic analysis showed the presence of vascular bundles, starch grains, fibers, calcium oxalate crystals, elongated parenchyma, and collenchyma mucilage as shown in the supplementary files. Locomotor activity, Escape latency time, Conditioned avoidance response, and Transfer latency were improved with treatment. Interleukin- 6 (IL - 6) levels were reduced significantly in the Colchicine + 200 Cassia mg/kg group (739.2 ± 0.37 pg/ml) than in the Colchicine Group (850.6±0.40 pg/ml). Tumor necrosis factor (TNF-α) was decreased in the Colchicine + 200 Cassia mg/kg Group (1030.93±0.51 pg/ml) than in the Colchicine Group (1455.06±1.25 pg/ml). A significant decrease in total protein level was observed in the Colchicine Group (2.52±0.10 mg/ml), (3.33±0.90 mg/ml) as compared to Colchicine + 200 Cassia mg/kg Group (5.27±0.09 mg/ml, (5.01±0.10 mg/ml) respectively, in the Hippocampus and Entorhinal cortex. The levels of antioxidant enzymes such as Catalase (CAT), Serum superoxide dismutase (SOD), Reduced glutathione (GSH) and Malondialdehyde (MDA) were measured. When compared to the Colchicine Group (7.33±0.16 nM/ mg, the MDA level was lower in the Colchicine + 100 Cassia mg/kg Group (3.20±0.01 nM/ mg). The level of CAT in Colchicine + 200 Cassia mg/kg Group (7.01±0.03 μmoles of H2O2/mg of protein) was seen to be increased when compared to Colchicine Group (3.32 ± 0.17 μmoles of H2O2/mg of protein). The level of SOD in Colchicine + 200 Cassia mg/kg Group (7.43±0.02 U mg -1 of protein) was seen to be increased when compared with Colchicine Group (4.55±0.03 U mg -1 of protein). The level of GSH in Colchicine + 200 Cassia mg/kg Group (10.07±0.19 nM/mg -1 of protein) was increased when compared with the Colchicine Group (5.82±0.11nM/mg -1 of protein). Histopathology of the Hippocampus and Entorhinal cortex showed diminished amyloid plaques, and neurodegeneration in the treatment groups Conclusion: The present study showed that ethanolic extract from the roots of Cassia occidentalis L. At 100 and 200 mg/kg doses in Wistar rats improved memory damage, by reducing oxidative stress. Levels of the antioxidant enzymes as CAT, and SOD, GSH were increased and MDA was decreased. The cytokine levels in the serum of Wistar rats of IL-6 level and TNF-α level were reduced significantly. Estimation of total protein level was found to be increased. It restored neuronal degeneration in the Hippocampus, and Entorhinal cortex and reduced oxidative stress. This suggests that the ethanolic extract of Cassia occidentalis L. could be an effective therapeutic treatment for neurodegenerative diseases like AD.

Measuring patient safety: the Agency for Healthcare Research and Qualityís patient safety indicators

There is a lot of interest in patient safety, but there is still little useable national level information on the actual magnitude of patient safety problems that can be used by providers and policy makers to judge performance. The AHRQ Patient Safety Indicators (PSIs) are a set of measures that can be used with hospital inpatient administrative (discharge) data to provide a perspective on patient safety. They screen for problems that patients experience as a result of exposure to the healthcare system and that are likely amenable to prevention by changes at the system or provider level. There is a growing interest in the possible use of the AHRQ PSIs in international settings. The Organization for Economic Cooperation and Development (OECD) maintains an ongoing project on Health Care Quality Indicators (HCQI) and whose goal is to develop a set of quality indicators that can be used to reliably assess quality of care across countries and raise questions about differences in quality of care internationally. Work is ongoing though a partnership between AHRQ and the Italian National Observatory on Health in the Italian Regions to test the AHRQ QIs with the Italian national hospital discharge data set. Preliminary results indicate that many of the operational issues associated with differences in coding schemes and data set structure are surmountable. With additional refinements on their clinical specificity, increased stability in their definitions over time to permit long-term monitoring and country interest within organizations such as the OECD to build on the existing scientific work of these indicators, their to help answer questions about patient safety worldwide will be significantly enhanced.

The Impact of Social Work Relationships on Preschool Teachers' Social and Emotional Competence

In recent years, the Organization for Economic Co-operation and Development (OECD) initiated a survey focused on the social and emotional competence (SEC) of educators, garnering significant attention across the educational community. Despite this interest, there remains a notable gap in research concerning the development of SEC among preschool teachers within the context of various social relationships. Addressing this gap, our study examines the influence of leadership trust, collegial relationships, pro-teacher relationships, teacher-child interactions, and self-efficacy on the SEC of preschool educators. This investigation aims to elucidate the role these social relationships play in shaping the SEC of preschool teachers. The study sample consisted of 223 Chinese preschool teachers, with data analyzed through hierarchical regression techniques. Findings reveal that leadership trust, pro-teacher relationships, and self-efficacy are significant predictors of teachers' SEC. These results underscore the importance of fostering a positive, trust-based, and supportive social work environment as a pivotal strategy for enhancing preschool teachers' SEC, thereby contributing to the broader understanding of how social relationships influence educators' emotional and social capabilities.

How natural resource, renewable energy, and energy productivity integrate with environmental quality under the load capacity curve in OECD nations

Previous research highlights the impact of renewable energy (REN) sources and natural resources (NRP) on environmental sustainability, but it leaves out the possible consequences of energy production (EP). Additionally, clean environment is addressed by Sustainable Development Goals 7 and 12. This study evaluates the outcomes of meeting the OECD's carbon zero targets by 2050 as well as the UN Climate Change Conference of the Parties' 2030 carbon neutrality target. Therefore, evaluating how these factors affect the load capacity factor (LCF) may have pertinent ramifications for the government's pursuit of sustainable development objectives. Therefore, the effects of REN, NRP, and energy efficiency on LCF were examined for Organization for Economic Cooperation and Development (OECD) countries. The method of momentum quantile regression (MMQR) is applied during the period of 1990–2022. The results show that REN is increasing LCF by 0.157%–0.161% in four quantiles and NRP is also contributing to environmental quality by 0.385%–0.233% in 25th to 90th quantiles. EP is lowering LCF by 0.091%–0.073% in the long run. The paper provides policy implications for a cleaner environment in OECD nations.

Development of a Robust Read-Across Model for the Prediction of Biological Potency of Novel Peroxisome Proliferator-Activated Receptor Delta Agonists.

A robust predictive model was developed using 136 novel peroxisome proliferator-activated receptor delta (PPARδ) agonists, a distinct subtype of lipid-activated transcription factors of the nuclear receptor superfamily that regulate target genes by binding to characteristic sequences of DNA bases. The model employs various structural descriptors and docking calculations and provides predictions of the biological activity of PPARδ agonists, following the criteria of the Organization for Economic Co-operation and Development (OECD) for the development and validation of quantitative structure-activity relationship (QSAR) models. Specifically focused on small molecules, the model facilitates the identification of highly potent and selective PPARδ agonists and offers a read-across concept by providing the chemical neighbours of the compound under study. The model development process was conducted on Isalos Analytics Software (v. 0.1.17) which provides an intuitive environment for machine-learning applications. The final model was released as a user-friendly web tool and can be accessed through the Enalos Cloud platform's graphical user interface (GUI).

In vivo genotoxicity assessment of N-(-9 acridinyl)-b-alanine hydrochloride (S-300) using a validated Pig-a mutagenesis assay.

N-(-9 acridinyl)-b-alanine hydrochloride (S-300) is the main byproduct of red blood cell (RBC) amustaline/glutathione(GSH) pathogen reduction, currently undergoing phase III US clinical trials following successful European studies(1-3). Phosphatidylinositol glycan, class A (Pig-a) X-linked gene mutagenesis is a validated mammalian in vivo mutation assay for genotoxicity, assessed as clonal loss of glycosylphosphatidylinositol-linked CD59 cell-surface molecules on reticulocytes (RETs) and RBCs. Male Sprague-Dawley rats received continuous infusion of S-300 up to the maximum feasible dose (240 mg/kg/day-limited by solubility and volume) for 28 days. Positive controls received a known mutagen by oral gavage on Days 1-3. Plasma levels of S-300 were assessed by HPLC before, during and after infusion. CD59-negative RBCs and RETs were enumerated in pre-dose and Day 28 samples, using a flow cytometric method. Outcome was evaluated by predetermined criteria using concurrent and historical controls. Toxicity was assessed by laboratory measures and necropsy. S-300 reached maximum, dose-dependent levels (3-15 μmol/L) within 2-8 h that were sustained for 672 h and undetectable 2 h after infusion. Circulating RET levels indicated a lack of hematopoietic toxicity. Necropsy revealed minimal-mild observations related to poor S-300 solubility at high concentrations. Pig-a assessment met the preset acceptability criteria and revealed no increase in mutant RBCs or RETs. Maximum feasible S-300 exposure of rats by continuous infusion for 28 days was not genotoxic as assessed by an Organization for Economic Cooperation and Development-compliant, mammalian, in vivo Pig-a gene mutation assay that meets the requirements of International Conference on Harmonization (ICH) S2(R1) and FDA guidances on genotoxicity testing.

Measuring the gap between optimal and observed energy structure: Evidence from 36 OECD countries

Sustainable development has always been given priority by economic authorities, therefore pursuing both environmental emissions reduction and economic growth at the same time is required. However, energy structure is often disregarded in existing performance evaluation methodologies, despite its essential function in determining environmental efficiency or productivity. This study shows how ignoring the energy structure can lead to distorted policy recommendations as well as evaluation results. The present study provides a non-parametric estimating approach to quantify the difference between the optimal (theoretical) energy structure required to achieve sustainable development and the actual (observed) energy structure. This method may assess the energy transition process and evaluate the observed and optimal energy structure of a country or region. We demonstrate that using the countries of the Organization for Economic Co-operation and Development as an example, that only a limited number of countries are able to meet their objectives for carbon reduction and economic development simultaneously without transforming their energy structure. The relationship between energy structure and green total factor productivity (GTFP) was further studied using a two-stage least squares regression on the observed energy structure and GTFP. The findings indicate that most countries need to increase their share of renewable energy in order to achieve green growth.