Aggregate Level Research Articles

Effect of Remote Ischemic Conditioning and Red Blood Cells Biomarkers on Outcomes in Patients With Acute Stroke.

Remote ischemic conditioning (RIC) is a simple and low-cost intervention that is thought to increase collateral blood flow through the vasodilatory effects of nitric oxide (NO) produced by the endothelium and red blood cells (RBCs). The aim of this study was to investigate whether RBC form and function are associated with short- and long-term outcomes in patients with acute ischemic stroke, and whether RIC treatment modified this effect. This is a predefined substudy to the RESIST (Remote Ischemic Conditioning in Patients with Acute Stroke Trial) randomized clinical trial conducted in Denmark. RIC was started in the ambulance and continued at the hospital for 7 days. RBC deformability and erythrocyte aggregation rate were assessed using ektacytometry, NO using flowcytometry, and nitrite content using ozone chemiluminescence. Logistic regression and mixed effect models were used. Out of 1500 prehospital randomized patients, and between July 28, 2020 and November 11, 2023, 486 patients had blood samples taken. Of these 249 (51%) had acute ischemic stroke and were included in this study. In the acute phase, higher levels of RBC deformability, aggregation, and RBC NO content were associated with worse clinical outcome if patients were treated with RIC compared with sham. Similar results were found at 24 hours, except for a potential effect on early neurological improvement in RIC-treated patients with an increased deformability level at 24 hours. RIC may have time-dependent and biomarker-specific effects on stroke outcomes, and detrimental interactions between increasing biomarker levels and RIC were observed. This may explain previous failures to translate RIC into an effective neuroprotective therapy in the hyperacute phase.

Soil Bulk Density, Aggregates, Carbon Stabilization, Nutrients and Vegetation Traits as Affected by Manure Gradients Regimes Under Alpine Meadows of Qinghai–Tibetan Plateau Ecosystem

Climate change and overgrazing significantly constrain the sustainability of meadow land and vegetation in the livestock industry on the Tibetan–Plateau ecosystem. In context of climate change mitigation, grassland soil C sequestration and forage sustainability, it is important to understand how manure regimes influence SOC stability, grassland soil, forage structure and nutritional quality. However, the responses of SOC fractions, soil and forage structure and quality to the influence of manure gradient practices remain unclear, particularly at Tianzhu belt, and require further investigation. A field study was undertaken to evaluate the soil bulk density, aggregate fractions and dynamics in SOC concentration, permanganate oxidizable SOC fractions, SOC stabilization and soil nutrients at the soil aggregate level under manure gradient practices. Moreover, the forage biodiversity, aboveground biomass and nutritional quality of alpine meadow plant communities were also explored. Four treatments, i.e., control (CK), sole sheep manure (SM), cow dung alone (CD) and a mixture of sheep manure and cow dung (SMCD) under five input rates, i.e., 0.54, 1.08, 1.62, 2.16 and 2.70 kg m−2, were employed under randomized complete block design with four replications. Our analysis confirmed the maximum soil bulk density (BD) (0.80 ± 0.05 g cm−3) and micro-aggregate fraction (45.27 ± 0.77%) under CK, whilst the maximum macro-aggregate fraction (40.12 ± 0.54%) was documented under 2.70 kg m−2 of SMCD. The SOC, very-labile C fraction (Cfrac1), labile C fraction (Cfrac2) and non-labile/recalcitrant C fraction (Cfrac4) increased with manure input levels, being the highest in 2.16 kg m−2 and 2.70 kg m−2 applications of sole SM and the integration of 50% SM and 50% CD (SMCD), whereas the less-labile fraction (Cfrac3) was highest under CK across aggregate fractions. However, manures under varying gradients improved SOC pools and stabilization for both macro- and micro-aggregates. A negative response of the carbon management index (CMI) in macro-aggregates was observed, whilst CMI in the micro-aggregate fraction depicted a positive response to manure addition with input rates, being the maximum under sole SM addition averaged across gradients. Higher SOC pools and CMI under the SM, CD and SMCD might be owing to the higher level of soil organic matter inputs under higher doses of manures. Moreover, the highest accumulation of soil nutrients,, for instance, TN, AN, TP, AP, TK, AK, DTPA extractable Zn, Cu, Fe and Mn, was recorded in SM, CD and SMCD under varying gradients over CK at both aggregate fractions. More nutrient accumulation was found in macro-aggregates over micro-aggregates, which might be credited to the physical protection of macro-aggregates. Overall, manure addition under varying input rates improved the plant community structure and enhanced meadow yield, plant community diversity and nutritional quality more than CK. Therefore, alpine meadows should be managed sustainably via the adoption of sole SM practice under a 2.16 kg m−2 input rate for the ecological utilization of the meadow ecosystem. The results of this study deliver an innovative perspective in understanding the response of alpine meadows’ SOC pools, SOC stabilization and nutrients at the aggregate level, as well as vegetation structure, productivity and forage nutritional quality to manure input rate practices. Moreover, this research offers valuable information for ensuring climate change mitigation and the clean production of alpine meadows in the Qinghai–Tibetan Plateau area of China.

Research on soil bacterial community assembly and function under different straw returning practices in arid and semi-arid agricultural ecosystems over multiple years

IntroductionStraw return has gained attention for its potential to improve soil quality and crop yields, particularly in semi-arid regions like the Tumu Chuan Plain Irrigation Area. Soil bacteria play a crucial role in regulating soil biological processes, and understanding how straw return affects bacterial populations can guide better agricultural management practices.MethodsWe investigated the impact of continuous straw return on soil bacterial communities using 16S rRNA gene sequencing. Four treatments were applied: Farmers’ shallow rotation (CK), straw incorporated with deep tillage (DPR), straw incorporated with subsoiling (SSR), and no-tillage mulching straw return (NTR). Bacterial community structure, metabolic pathways, and assembly mechanisms were analyzed using Bugbase and PICRUSt2 for phenotypic and metabolic pathway predictions.ResultsThe study found that straw return practices significantly altered the relative abundance and life history strategies of bacterial phyla, mainly influenced by soil organic matter (SOM) and enzyme activity. The K-strategist to r-strategist ratio was highest in CK (2.06) and lowest in SSR (1.89). DPR and NTR treatments significantly changed bacterial community structure compared to CK (p < 0.05), resembling SSR. Predictions showed that DPR and NTR enhanced carbohydrate and amino acid metabolism and promoted more stable bacterial networks, with homogenous selection and drift effects. Bacterial aggregation in all treatments was driven by random processes, with varying aggregation levels: CK (20%), DPR (38.6%), SSR (16.5%), and NTR (30.7%).DiscussionThe study demonstrates that continuous straw return practices significantly impact soil bacterial communities. DPR and NTR notably improved microbial diversity, bacterial cooperation, and ecosystem stability. These findings provide valuable insights for sustainable agricultural practices in semi-arid regions, enhancing soil microbial ecology and soil health through strategic straw return.

Bridging Europe’s Innovation Divide: How European Union Research Policy Drives Growth in Less Developed Regions

Background This research examines the impact of competitive European research and development funding—specifically from the European Union’s Seventh Framework Programme and Horizon 2020—on regional economic growth, research capacities, and innovation performance across NUTS2 regions, representing mid-level administrative divisions within European Union Member States. Given the persistent disparities in research and innovation output between more and less developed regions, we focus on how these funding mechanisms influence economic and scientific development, particularly in less developed and peripheral regions. While European Union research programs aim to foster knowledge production and technological advancement, their role in mitigating regional inequalities and supporting economic convergence remains an open question. Methods To assess the effects of European Union Research and Development (EU R&D) funding, we conduct a quantitative analysis using data from Eurostat, PATSTAT, Web of Science, and the European Commission’s CORDIS database. We measure changes in three key indicators —publication output, patent applications, and GDP per capita— between 2011 and 2022. GDP per capita, representing a region’s total economic output divided by its population, is a key indicator of regional economic performance. Ordinary least squares regression models are employed to evaluate the relationship between funding intensity and regional research and economic development, controlling for factors such as regional R&D investments, international collaboration, and initial economic conditions. Results Our findings reveal significant and persistent interregional disparities in research and innovation outcomes. While participation in European Union’s Seventh Framework Programme and Horizon 2020 is associated with stronger research capacities in already well-developed regions, no significant relationship is found between EU-funded R&D and increases in publications or patents at an aggregate level. However, a positive correlation emerges between EU R&D funding and GDP growth in less developed regions, suggesting that while direct scientific outputs may not always materialize, economic benefits arise through alternative channels such as small and medium-sized enterprise (SME) engagement, infrastructure improvements, and knowledge diffusion. Conclusions The study highlights the broader implications of transnational funding frameworks for regional economic convergence within the EU. Despite limited effects on immediate research outputs in less developed regions, competitive EU R&D programs contribute to economic resilience in lagging regions, raising important considerations for multi-level governance and international cooperation. These results align with debates in International Relations regarding the role of supra-national institutions in shaping equitable economic outcomes and addressing structural imbalances across Member States. As EU funding strategies evolve, a more integrated approach that strengthens innovation ecosystems in underperforming regions could enhance European research policy's inclusivity and long-term impact.

A novel Dual GLP-1/CCK Receptor Agonist Improves Cognitive Performance and Synaptogenesis in the 5 × FAD Alzheimer Mouse Model.

Glucagon-like peptide 1 (GLP-1) is a peptide hormone and growth factor. Cholecystokinin (CCK) is another peptide hormone, growth factor and neurotransmitter. Both peptide hormones have shown good neuroprotective effects in animal models of Alzheimer's disease (AD). In this study, we tested the effects of a dual GLP-1/CCK (25nmol/kg ip. for 14days) receptor agonist that had previously shown good effects in animal models of diabetes. The GLP-1 analogue Liraglutide (50nmol/kg ip.) was used as a positive control. Memory was improved in the water maze and the Y-maze, spontaneous activity was increased, the chronic inflammation response had been reduced and levels of NLRP3, IL-10 and TNFα were brought back to physiological levels. Levels of amyloid aggregates in the brain were reduced by the drugs. The expression of proteins SIRPα and CD47 which is related to reduced inflammation levels was reduced. Importantly, growth factor signalling was much improved and growth levels of BDNF, TrkB receptor, p-CREB, and an upregulation of the PI3K-AKT signalling pathway had been observed. Post-synaptic density protein (PSD) and synaptophysin levels were reduced, too. In transmission electron microscope analysis, the synaptic cleft was found to be wider in 5xFAD mice. In Golgi stain evaluations, synapse numbers were brought back to normal levels by the drugs. In a direct comparison with Liraglutide, the dual GLP-1/CCK receptor agonist was superior in the water maze tests and in the upregulation of BDNF and TrkB levels in the brain. In other parameters, the dual agonist and Liraglutide showed comparable effects. In conclusion, the combination of GLP-1 and CCK receptor activation did not show overall improvements over single GLP-1 receptor activation.

Neoliberalism and Globalization Are Not Undermining Democracy: Panel Evidence From More Than 140 Countries, 1980–2022

ABSTRACTThe rise of neoliberal reforms in the period of globalization is often claimed to be linked with wider outcomes, such as increased inequality, unemployment, and different cultural grievances. Because of these economic and cultural concerns, voters might seek solutions to their ostensible problems by turning to illiberal populist parties, which tend to undermine democracy and its basic principles. The present article empirically tests if neoliberalism, operationalized with the Fraser Institute's Economic Freedom of the World, and globalization, operationalized with the KOF's Globalization Index, were somehow associated with democratic integrity. The analysis is performed through fixed‐effects regressions in more than 140 countries between 1980 and 2022. The main results show that over‐time increases in both neoliberalism and globalization predicted over‐time increases in five different types of democracy scores. Furthermore, the analyses with disaggregated indexes showed that freedom of international trade, modesty of regulation, legal system and property rights, and social globalization are what drive the relationship at the aggregate level. Results also showed that there are no statistically significant relationships between economic freedom and Freedom House's democracy scores specifically in the time period between 2011 and 2022. Furthermore, there are no statistically significant results indicating a relationship between globalization and democracy during the same time period. This is an interesting observation since this time period is commonly understood as most clearly embodying the democratic recession.

Improving the functionality of intraoperative nerve monitoring during thyroid surgery: is lidocaine an alternative?

Background. The role of intraoperative nerve monito­ring (IONM) in thyroid surgery remains a controversial issue for surgeons regardless of their training and experience. This monitoring method is not intended to visualize the recurrent laryngeal nerve, but rather to assess its function intraoperatively and to help make a prognosis in patients who develop recurrent laryngeal nerve paralysis. Because of its simplicity and cost-effectiveness, electromyography recording of the vocal cords using surface electrodes integrated into or attached to the endotracheal tube is probably the most commonly used IONM method. Full functionality of IONM depends on near-complete laryngeal relaxation and reflex inhibition without the use of neuromuscular blocking agents. The depth of anesthesia required to meet these criteria often results in hemodynamic instability. During our study, we used intravenous lidocaine infusion, which allowed for good operating and monitoring conditions without significant hemodynamic fluctuations. The purpose of the study is to evaluate the effect of lidocaine administered intravenously in estimated doses on the IONM and laryngotracheal reflexes during surgical interventions on the thyroid and parathyroid glands. Materials and methods. Forty-six patients were randomly assigned to group 1 where lidocaine was administered and group 2 with no lidocaine was used. All patients were anesthetized with a narcotic analgesic and inhalation anesthetic. The loading dose of lidocaine was administered at the rate of 1 mg/kg intravenously, and the maintenance dose was calculated at 1.5 mg/kg/hour. For IONM, a Dragonfly single-channel laryngeal surface electrode (Electrode LSE 500Ms; Neurovision Medical Products, Ventura, CA, USA) attached to a cuffed endotracheal tube 7.0 (Medicare, China) was used during surgery according to the manufacturer’s instructions. Results. The number of patients who required stimulating current at 0.5 mA (the manufacturer’s recommended strength is 1.5 mA) was significantly higher in the lidocaine group (P = 0.001) than in the no lidocaine group (P = 0.00006). Similarly, the proportion of patients with < 50 % drop in aggregate impedance level at the end of surgery was significantly higher in group 1 than in group 2. In addition, the proportion of patients with hypotensive episodes and need to correct blood pressure with medications more than twice during surgery was significantly lower in group 1 than in group 2 (P < 0.05). ­Conclusions. Patients who were prescribed lidocaine intravenously were more resistant to laryngotracheal irritation during surgery, and this made it possible to maintain such a condition of the larynx, which was necessary to ensure its increased relaxation and suppression of reflexes when using IONM. Our ability to elicit a positive signal with stimulating current of 0.5 mA intraoperatively and provide a drop in aggregate impedance level < 50 % before the end of surgery was statistically significant in the intravenous lidocaine group.

Highly Adaptable Analysis Tools for Mapping Spatial Features of Cellular Aggregates in Tissues.

Multiplex imaging technologies have developed rapidly over the past decades. The advancement of multiplex imaging has been driven in part by the recognition that the spatial organization of cells can represent important prognostic biomarkers and that simply studying the composition of cells in diseased tissue is often insufficient. There remains a lack of tools that can perform spatial analysis at the level of cellular aggregates (a common histopathological presentation) such as tumors and granulomas, with most analysis packages focusing on smaller regions of interest and potentially missing patterns in the overall lesion structure and cellular distribution. Here, we present protocols to quantitatively describe the cellular structure of entire tissue lesions, built around two novel metrics. The Total Cell Preference Index reports whether a lesion tends to change in density in its central versus peripheral areas and can indicate the extent of necrosis across the entire lesion. The Immune Cell Preference Index then reports whether each immune cell type is located more centrally or peripherally across the entire lesion. The output of both indexes is a single number readout for simple interpretation and visualization, and these indexes can be applied to lesions of any size or shape. This simplifies cross-lesion comparison compared to traditional Euclidian distance-based analysis, which outputs multiple values for each lesion (one for output for each band used in the infiltration analysis). Additionally, this approach can be applied to any slide-scanning multiplexed imaging system, based on either protein or nucleic acid staining. Finally, the approach uses the open-source software QuPath and can be utilized by researchers with a basic understanding of QuPath, with the full analysis able to be applied to pre-generated images within 1 hr. © 2025 The Author(s). Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Image preparation and lesion selection Basic Protocol 2: Total Cell Preference Index and Immune Cell Preference Index.

Testing the Liquidity Support Effects of the U.S. Treasury Buyback Program

The U.S. Treasury’s recently introduced liquidity support buyback program offers a natural setting to evaluate whether providing a regular mechanism for selling less liquid off-the-run Treasury securities can enhance market liquidity. In this paper, I present a direct test of this mechanism and quantify the liquidity support effects at both the individual security level and the aggregate balance sheet level of primary dealers. I utilize operational considerations related to the Treasury's selection of buyback securities that are independentof the securities’ liquidity conditions—notably, whether a security matures in a month characterized by significant cash inflows to the Treasury—to construct an instrumental variable for the Treasury’s buyback selection decisions. I find that buybacks moderately narrow bid-ask and off-the-run spreads and raise prices for securities listed by buyback, further boost prices for those purchased, and reduce primary dealers’ net holdings of Treasury bills and coupons. The liquidity support effects are particularly pronounced when dealers hold large Treasury inventories. I rationalize these findings using a model in which buybacks serve as predictable demand for dealers facing inventory constraints and holding costs, thereby mitigating illiquidity risks.

New Performance Measurement Framework for Realizing Patient-Centered Clinical Decision Support: Qualitative Development Study.

Patient-centered clinical decision support (PC CDS) exists on a continuum that reflects the degree to which its knowledge base, data, delivery, and use focus on patient needs and experiences. A new focus on value-based, whole-person care has resulted in broader development of PC CDS technologies, yet there is limited information on how to measure their performance and effectiveness. To address these gaps, there is a need for more measurement guidance to assess PC CDS interventions. This paper presents a new framework that incorporates patient-centered principles into traditional health IT and clinical decision support (CDS) evaluation frameworks to create a unified guide to PC CDS performance measurement. We conducted a targeted literature review of 147 sources on health IT, CDS, and PC CDS measurement and evaluation to develop the framework. Sources were reviewed if they included the sociotechnical components relevant to PC CDS, covered the full IT life cycle of PC CDS, and addressed measurement considerations at different user and system levels. We then validated and refined the measurement framework through key informant interviews with 6 experts in measurement, CDS, and clinical informatics. Throughout the framework development, we gathered feedback from a 7-member expert committee on the methods, findings, and the framework's relevance and application. The PC CDS performance measurement framework includes 6 domains: safe, timely, effective, efficient, equitable, and patient centered. The 6 domains contain 34 subdomains that can be selected to assess performance, depending on the type of PC CDS intervention or the specific research focus. In addition, there are 4 levels of aggregation at which subdomains can be measured (individual, population, organization, or IT system) that account for the multilevel impact of PC CDS. We provide examples of measures and approaches to patient centeredness for each subdomain, followed by 2 illustrative use cases demonstrating the framework application. This framework can be used by researchers, health system leaders, informaticians, and patients to understand the full breadth of performance and impact of PC CDS technology. The framework is significant in that it (1) covers the entire PC CDS life cycle, (2) has a direct focus on the patient, (3) covers measurement at different levels, (4) encompasses 6 independent but related domains, and (5) requires additional research and development to fully characterize all domains and subdomains. As the field of PC CDS matures, researchers and evaluators can build upon the framework to assess which components of PC CDS technologies work; whether PC CDS technologies are being used as anticipated; and whether the intended outcomes of delivering evidence-based, patient-centered care are being achieved.

The multiverse of social class. A large-scale assessment of macro-level, meso-level and micro-level approaches to class analysis

Abstract Different class theories suggest competing mechanisms behind stratification and assume primacy of different levels of occupational aggregation. By comparing eight class schemes across 12 outcomes with data from more than 546,000 individuals in 61 countries, we offer the most comprehensive multi-scheme comparison of class stratification. Additionally, we evaluate scheme differences across different analytical settings (pooled data, smaller random samples, selected country comaprisons). We asses scheme performance by average effect strength and model fit. Results suggest that microclasses are the best analytical choice with sufficiently large samples. If parsimony is taken into account and samples are smaller, aggregated class schemes are superior in terms of model fit. Country differences in relative scheme performance are negligible and unsystematic supporting the application of class analysis for cross-national comparative designs. The article concludes with a nuanced guide for empirical class analysis.

Shift‐Share Analysis and Multifactor Partitioning: What do Aggregated Data Hide?

ABSTRACTShift‐share analysis (SSA) is a widely used tool for studying economic changes, particularly in employment, due to its simplicity and minimal data requirements. However, its reliance on crude growth rates and issues associated with aggregation can lead to biases, such as Simpson's Paradox, that may hide regional and industry‐specific insights. Multifactor Partitioning (MFP) addresses these limitations by standardizing growth rates in a way that disentangles industry and regional effects. This paper compares SSA and MFP using employment data from 10 U.S. states between 2005 and 2019. The analysis incorporates three levels of disaggregation: (1) aggregate employment and time, (2) disaggregated employment with aggregated time, and (3) both sectoral and temporal disaggregation. Results show that while SSA and MFP yield similar conclusions at an aggregate level, discrepancies emerge in disaggregated analyses, particularly in high‐growth regions. These findings highlight the importance of data disaggregation and MFP's capacity to provide nuanced insights for policymakers and researchers.

Migrant worker policies and the spillover effects on educational outcomes and employment aspirations of national children in the Gulf

This paper examines the socio-economic and socio-demographic profile of foreign-born children in the Gulf Cooperation Council (GCC) to understand their influence on current educational and future employment outcomes of national children. The study uses country level population data and aggregate level student performance data from Program for International Student Assessment (PISA) for selected GCC countries. The findings show that foreign-born students outperform national students in reading, science and mathematics scores and in completion of tertiary education. The Gulf countries would benefit by providing opportunities for the two groups to integrate and assimilate through schooling with ability-based placement of both types of students.

Data-oriented shopfloor management: an inductively developed holistic conceptual model

Abstract Data plays a fundamental role in shopfloor management in order to make better decisions and increase efficiency throughout the production system. The idea of data-oriented shopfloor management has been discussed in the literature as an innovative concept, but unlike traditional or digital shopfloor management, it has not been conceptualised from a holistic perspective. For this reason, this paper used qualitative research in the form of expert interviews to collect holistic conceptual requirements for data-oriented shopfloor management. The data were analysed using the Gioia Methodology and transferred into a data structure to derive conceptual requirements at different levels of aggregation. On the basis of the empirical data, data-oriented shopfloor management was modelled, consisting of the system elements shopfloor, management approach with four subsystems and information system. Specifically, two conceptual models were developed for data-oriented shopfloor management as a distinction was made between episodic configuration and strategic adaptation and the persistent operating mode. Both conceptual models represent the reciprocal relationships and interdependencies of the system elements within data-oriented shopfloor management. Looking to the future, this paper provides the basis for further research to refine the conceptual models based on the empirically collected conceptual requirements with a higher level of detail.

Assessment of Mechanical and Physical Properties of Concrete with Polypropylene Plastic Granule Aggregates

The increasing use of plastic materials has significantly contributed to the global accumulation of plastic waste. Incorporating plastic waste into concrete offers a partial yet promising solution to this environmental challenge. This study investigates the use of polypropylene (PP) plastic granules as a partial replacement for fine aggregates in concrete. The primary objective is to evaluate the physical and mechanical properties of concrete incorporating PP granules, focusing on parameters such as compressive strength, split tensile strength, workability, and density. Mixes were prepared with 10%, 20%, 30%, and 40% replacement levels of fine aggregates by PP granules. The corresponding slump values observed were 8.10 cm, 8.40 cm, 8.60 cm, and 8.80 cm, indicating a slight improvement in workability with increased plastic content. However, the inclusion of PP granules adversely affected the mechanical properties, with compressive and split tensile strength showing significant reductions at 40% replacement, the compressive strength decreased by up to 60%, suggesting that high levels of substitution may not be suitable for structural applications.

Progressing towards the 2030 health-related SDGs in ASEAN: A systematic analysis.

The Sustainable Development Goals (SDGs) articulate an ambitious global agenda and set of targets to achieve by 2030. Among the health-related SDGs, many formidable challenges remain in settings like the Association of Southeast Asian Nations (ASEAN) which face wide-ranging social, economic and health inequalities. In advance of the 2030 horizon, charting the trajectory of the health SDGs is critical for informing policy and programmatic course corrections to advance health and well-being among ASEAN's 10 member countries with its 667 million people. We used estimates from the Global Burden of Disease (GBD) Study 2021 and surveillance data to identify 27 health-related SDG indicators. The indicators were classified into 7 thematic areas: (i) nutrition, (ii) maternal, child and reproductive health (MCH), (iii) infectious diseases, (iv) non-communicable diseases (NCDs), (v) environmental health, (vi) universal health coverage (UHC), and (vii) road injuries. We developed an attainment index ranging from 0 to 100 for each SDG indicator by referencing the SDG targets and projected their progress to 2030. We find an overall positive progress towards the health-related SDG targets in ASEAN from 1990 to 2030. At the aggregate level by 2030, 2 member countries, Singapore and Brunei, are projected to achieve their targets (attainment score≥90). At a wider regional level, ASEAN is projected to make substantial progress in nutrition, MCH, and UHC, with a majority of countries projected to come close to or achieve their targets. However, progress is projected to be slower in the areas of reducing the incidence of infectious disease (i.e., HIV and AIDs, hepatitis B, TB, and neglected tropical diseases), NCD-related mortality and its risk factors (i.e., harmful alcohol use and smoking), environment-related mortality and its risk factors (i.e., unsafe water and poor hygiene, and air pollution), and road injuries. Substantial disparities are identified in the region, with Singapore, Brunei, Malaysia and Thailand generally performing better than elsewhere. A limitation of our study was its reliance on historical trends which may not fully capture future political, social, or technological changes. As a regional bloc, ASEAN faces persistent challenges in achieving health-related SDG targets by 2030, with unequal progress between countries. Moreover, epidemiological transitions and worsening environmental threats further compound potential gains. At the country level, efforts to enhance health system financing, quality and equity will need to be coupled with wider approaches that address structural drivers of disease. Furthermore, coordinated regional efforts will be essential to effectively respond to emerging threats posed by pollution and environmental risks.

Stated preference survey for predicting eco-friendly transportation choices among Mansoura University students

This paper explores the attitudes and travel mode preferences of Mansoura University students towards eco-friendly transportation options, specifically shared electric scooters (SESs) and shared bikes (SBs). An online stated preference survey was administered to 790 students via Google Forms, yielding approximately 9,590 choice scenarios for analysis. The dataset was split into training (70%) and testing (30%) sets, with 6,717 cases in the training set and 2,880 cases in the testing set. A multinomial logit model and ten machine learning classifiers were used to predict mode choice behavior. The variables considered in the models include total travel time, travel cost, gender, health issues, bike ownership, ability to ride a bike and scooter, residency, prior knowledge of shared modes, smartphone ownership, frequency of public transport use, trip cost, trip time, and monthly personal income. Model performance was evaluated at two levels: individual and aggregate. At the individual level, accuracy reflects the overall percentage of correct predictions. At the aggregate level, accuracy is assessed based on the predicted market shares for each mode. The Extreme Gradient Boosting (XGB) model was the most accurate, achieving an accuracy slightly above 60%, followed by the Gradient Boosting (GB) and Random Forest (RF) models, both with accuracies slightly above 50%. Ensemble models like RF, GB, and XGB provided relatively accurate aggregate predictions with minimal deviations from actual mode shares. These models slightly overestimated the bus mode share but offered accurate predictions for other modes, making them robust choices for this classification task.

Enhancing primary care quality improvement through national data collection and validation: the primary care quality initiative in Sweden

Objective Quality measures in healthcare are crucial for improving outcomes and ensuring patient safety. This study investigated the evolution, implementation, and impact of Primary Care Quality (PCQ). The PCQ aims to facilitate nationwide quality benchmarking, serving as a tool for quality improvement (QI) and research. Design/Settings A descriptive design outlining the development and operationalisation of the PCQ, a national framework for automatic and systematic data collection and feedback. Results The national PCQ system is a tool for continuous QI in primary care in Sweden. PCQ has achieved extensive adoption, with over 97% of Swedish primary care centres, both private and public driven, utilising the platform for automatic data extraction from patient records and data visualisation. Quality indicators were developed through a structured approach involving primary care professionals, evidence-based clinical practices, and expert contributions from established knowledge organisations, reflecting the breadth of general practice. Data are automatically retrieved from medical records and visualised in real time, with the possibility of benchmarking at an aggregate level and identifying individuals locally at primary care centres. The PCQ has facilitated improvements by enabling quality dialogue among healthcare professionals and supporting continuous local QI. Regionally, the PCQ supports needs assessments and patient safety initiatives. Nationally, it establishes standardised indicators for quality measurement, enabling effective benchmarking and strategic healthcare planning. Conclusions The implementation of the national PCQ system provided a framework and tool for continuous QI in primary care. The system has influenced national standardization of primary care indicators, with quality improvement results demonstrated regionally and locally through the PCQ.

Understanding how banking channels grow and share customers

PurposeBanks provide multiple channels for customers to use, but little is known about how these channels grow or share customers. This study investigates this by testing patterns known to empirically describe brand competition—Double Jeopardy (DJ), duplication of usage (DoU) and user profile homogeneity (UPH)—across banking channel contexts.Design/methodology/approach427 Australian customers self-reported their banking channel usage at each purchase process stage (i.e. information, acquisition and usage). DJ analysis examined the relationship between channel penetration and average usage frequency. DoU analysis examined the relationship between channel penetration and customer multichannel usage. Mean Absolute Deviation analysis measured UPH across channels.FindingsDJ is observed at the usage stage and aggregate level: larger channels have more customers, and those customers use the larger channels more frequently. DJ is not seen at the information or acquisition stages. DoU is observed across stages: channels share more customers with larger channels and fewer customers with smaller channels. UPH across channels was observed at the aggregate level: profiles of customers who use different channels are similar. There was lower homogeneity at the individual stages.Practical implicationsDJ patterns imply that channel growth results from customer acquisition, rather than increasing usage frequency. DoU results imply that customer co-usage across channels is in line with channel size and any deviations should be investigated further to better understand and service customers. UPH suggests that category reach is a better-suited strategy over segmentation for channel growth.Originality/valueDJ, DoU and UPH patterns provide novel insights of banking channel growth and customer sharing. This informs more effective channel management strategies.

ASSESSMENT OF THE SENSITIVITY OF UKRAINIAN ENTERPRISES’ INVESTMENT ACTIVITY ON PROFITS AS A FACTOR OF APPROACHING TO THE MODEL OF SUSTAINABLE BUSINESS DEVELOPMEN

The article is devoted to thoroughly testing the tools for quantitative assessment of the sensitivity of enterprises’ investment activity to the size of the profit they receive. The urgent need to take into account the inevitable time lag that naturally occurs between the periods of receiving profit increment and the subsequent periods of the revival of investment activity caused by such profit increment, as well as carefully taking into account the significant impact of the profitability of alternative directions of using the profit received, ultimately led to the use of fundamental principles and advanced tools of cost-benefit analysis to effectively form the research database. The comprehensive results obtained allowed us to confidently substantiate the clear presence of a well-defined trend towards gradually increasing the sensitivity of business investment activity to the actual size of the profits received. We explicitly interpret this as compelling evidence of the enormous potential of those policy levers that strategically encourage enterprises to fully comply with the key requirements of the sustainable development model, including actively investing in significantly improving the energy efficiency of production, systematically introducing innovative resource-saving technologies, and meaningfully expanding business participation in directly financing the continuous development of human capital, etc., using targeted economic incentives. The meaningful results obtained convincingly characterize the prevailing tendency of businesses to prudently invest their accumulated profits in tangible real assets (expansion of production capabilities) only at the aggregate level of the entire economy and without properly taking into account the detailed distribution of investments by specific direction (in both tangible and intangible assets and in more detail: in land; in existing buildings and structures; in machinery and equipment; in software, etc.). Accordingly, further in-depth research should explicitly clarify the actual sensitivity of business investment activity to continuous changes in profit levels in a highly differentiated manner – within individual types of economic activity and distinct sectors, and also ensure that all critical differences in the technological and reproductive structure of investments are fully taken into account.