Browse Articles

Fully Exposed Cu Clusters with Ru Single Atoms Synergy for High-Performance Acetylene Semihydrogenation

Corruption distance and equity strategies in cross-border M&As: The moderating roles of political connections

This study explores the impact of corruption distance between home and the host countries on equity strategies in cross-border mergers and acquisitions (M&As). In addition, this study evaluates the moderating roles of two distinctive types of political connections. Analyzing cross-border M&A transactions by Chinese acquirers from 2016 to 2021, this study finds that greater corruption distance significantly increases the equity percentage of acquisitions by Chinese acquirers. This is because a greater corruption distance prompts Chinese acquirers to prefer a higher equity percentage, aimed at mitigating transaction costs and securing control over the target firm. Notably, this study argues that inherent political connections weaken the positive effect of corruption distance on the equity percentage of acquisitions; whereas acquired political connections strengthen its positive effect. In conclusion, this study extends the existing literature of the cross-border equity strategies of enterprises from emerging markets and offers practical insights for Chinese enterprises in managing complex cross-border M&A activities.

Shifting Gears: Photochromic Metal–Organic Frameworks with Stimulus-Adaptable Performance

LiMMCov: An interactive research tool for efficiently selecting covariance structures in linear mixed models using insights from time series analysis

The correct specification of covariance structures in linear mixed models (LMMs) is critical for accurate longitudinal data analysis. These data, characterised by repeated measurements on subjects over time, demand careful handling of inherent correlations to avoid biased estimates and invalid inferences. Incorrect covariance structure specification can lead to inflated type I error rates, reduced statistical power, and inefficient estimation, ultimately compromising the reliability of statistical inferences. Traditional methods for selecting appropriate covariance structures, such as AIC and BIC, often fall short, particularly as model complexity increases or sample sizes decrease. Studies have shown that these criteria can misidentify the correct structure, resulting in suboptimal parameter estimates and poor assessment of standard errors for fixed effects. Additionally, relying on trial-and-error comparisons in LMMs can lead to overfitting and arbitrary decisions, further undermining the robustness of model selection and inference. To address this challenge, we introduce LiMMCov, an interactive app that uniquely integrates time-series concepts into the process of covariance structure selection. Unlike existing tools, LiMMCov allows researchers to explore and model complex structures using autoregressive models, a novel feature that enhances the accuracy of model specification. The app provides interactive visualisations of residuals, offering insights into underlying patterns that traditional methods may overlook. LiMMCov facilitates a systematic approach to covariance structure selection with a user-friendly interface and integrated theoretical guidance. This paper details the development and features of LiMMCov, demonstrates its application with an example dataset, and discusses its potential impact on research. The app is freely accessible at https://zq9mvv-vub0square.shinyapps.io/LiMMCov-research-tool/.

Persistent Boryl Radicals as Highly Reducing Photoredox Catalysts for Debrominative Borylations

Effect of weight gain on blood pressure in Ugandan persons with HIV on dolutegravir/lamivudine/ tenofovir disoproxil fumarate over 48 weeks

Background Most people living with HIV in low and middle-income countries are taking fixed dose combination tenofovir disoproxil fumarate/lamivudine/dolutegravir (TLD). Dolutegravir use has been associated with weight gain, a known risk factor for hypertension. We aimed to determine if weight gain in Ugandan anti-retroviral therapy (ART) naïve patients on TLD correlated with increase in blood pressure. Methods We analyzed data from the ‘Glucose metabolism changes in Ugandan persons with HIV (PLHIV) on Dolutegravir (GLUMED)’ study which was a prospective cohort study with ART naïve persons with HIV ≥ 18 years followed up on TLD over 48 weeks. A scatter plot with 95% confidence intervals and regression line illustrating the relationship between weight change and mean arterial pressure (MAP) change from baseline to 48 weeks was created. To further examine the effect of weight change on MAP, we performed a linear regression analysis, with MAP change as the dependent variable and weight change as the independent variable. Results Of the 220 patients’ data analyzed, 129 (58.6%) were female, the median baseline age was 31 years (interquartile range (IQR): 27.0–38.0), the median baseline CD4 cell count was 319 cells/mm3 (IQR 160.0–524.0). The median weight gain over 48 weeks was 3.0 (IQR: −0.1–6.3). We found a moderate positive linear relationship between weight gain and MAP over 48 weeks. For every increase in weight of 1 kg over 48 weeks, there was an adjusted increase in MAP by 0.62mmHG. Conclusion We provide additional evidence to suggest that the noticed weight gain after starting dolutegravir based ART may be associated with a heightened risk of incident hypertension.

Chemically Engineered Affinity Protein Drugs for Covalent Targeted Cancer Therapy

Forecasting monthly residential natural gas demand in two cities of Turkey using just-in-time-learning modeling

Natural gas (NG) is relatively a clean source of energy, particularly compared to fossil fuels, and worldwide consumption of NG has been increasing almost linearly in the last two decades. A similar trend can also be seen in Turkey, while another similarity is the high dependence on imports for the continuous NG supply. It is crucial to accurately forecast future NG demand (NGD) in Turkey, especially, for import contracts; in this respect, forecasts of monthly NGD for the following year are of utmost importance. In the current study, the historical monthly NG consumption data between 2014 and 2024 provided by SOCAR, the local residential NG distribution company for two cities in Turkey, Bursa and Kayseri, was used to determine out-of-sample monthly NGD forecasts for a period of one year and nine months using various time series models, including SARIMA and ETS models, and a novel proposed machine learning method. The proposed method, named Just-in-Time-Learning-Gaussian Process Regression (JITL-GPR), uses a novel feature representation for the past NG demand values; instead of using past demand values as column-wise separate features, they are placed on a two-dimensional (2-D) grid of year-month values. For each test point, a kernel function, tailored for the NGD predictions, is used in GPR to predict the query point. Since a model is constructed separately for each test point, the proposed method is, indeed, an example of JITL. The JITL-GPR method is easy to use and optimize, and offers a reduction in forecast errors compared to traditional time series methods and a state-of-the-art combination model; therefore, it is a promising tool for NGD forecasting in similar settings.

On-Surface Synthesis of a Large-Scale 2D MOF with Competing π–d Ferromagnetic/Antiferromagnetic Order

Visuospatial working memory of abacus trained and untrained children

Background This research investigated whether there was a significant change in the visuospatial working memory of children who underwent abacus training. Method A quasi-experimental research design with a quantitative approach was employed for the study. Ninety (90) children were recruited as the experimental group and one hundred (100) children as the control group. The experimental group participated in abacus training as part of their extracurricular activities at school. A questionnaire assessing visuospatial memory was administered to both groups before and after the training. Findings The findings revealed a significant change in the mean scores of the experimental group from before and after the abacus training (p < .01) compared to the control group. This signified that abacus training may potentially lead to significant improvement in visuospatial working memory. Conclusion It is suggested that future research be conducted using a longitudinal approach to enable a more comprehensive assessment of the full course of abacus training.

Nanoplasmonic Isosbestics Uncover Mesoscale Assembly of Gold Nanoparticles on Soft Templates

Correction: Genetic and morphological divergence in the warm-water planktonic foraminifera genus Globigerinoides

Achieving Diverse CO₂ Conversions through On-Demand Installation of Multivariate Catalytic Sites into One Prototypical Metal–Organic Framework

Impact of lowering the maximum speed limit of city roads on pedestrian traffic accident patients: A nationwide before-and-after study

Traffic accidents (TAs) remain the leading cause of death globally; therefore, numerous efforts have been made to improve their occurrence and outcomes. Lowering the maximum road speed limit, named Safe Speed-5030, implemented in South Korea on April 17, 2021, is an example. This before-and-after study investigated the impact of this policy on pedestrian TA (P-TA) patients. We used the National Emergency Department Information System data for seven major cities in South Korea. We compared the characteristics of the patients who underwent P-TA and assessed the risks of emergency surgery, intensive care unit (ICU) admission, and unfavorable outcomes, using IBM SPSS version 21.0. The total number of patients who met with P-TAs was 26,842, with a 43.1% reduction from 17,105–9,737. A decrease was observed across all age groups; however, the rate was lower in the geriatric and severely injured groups. The proportions of emergency surgeries (46.5%), ICU admissions (36.5%), and unfavorable outcomes (21.5%) decreased. Nevertheless, this decrease was less pronounced in geriatric patients, and there was an increase in unfavorable outcomes among those in their 70s. After adjustment, the risk of emergency surgery did not show a statistically significant difference, but the risk of ICU admission and unfavorable outcomes increased. In conclusion, there was a significant reduction in the number of P-TA patients after the policy was implemented, but the effect was less pronounced in severely injured and geriatric patients. Considering these factors, we believe that Safe Speed-5030 had partly positive effects. Applying a suitably revised policy for specific group rather than completely scrapping it would be more appropriate.

Nickel-Mediated Radical Capture: Evidence for a Concerted Inner-Sphere Mechanism

Hospital-at-home care in Singapore: A review of overseas protocols and guidelines to support implementation and policy redesign (systematic review)

Objective Hospital-at-Home (HaH) is a care model providing acute, hospital-level care to patients in their own homes. It is gaining traction worldwide and could become an integral part of standard healthcare in the future. However, for countries like Singapore, implementation inefficiencies prevent the optimal uptake and establishment of HaH. Currently, there are no standardised guidelines guiding healthcare providers on effective implementation. Thus, our objective is to distil information from existing guidelines worldwide to collate the best practices for HaH implementation. Methods The systematic review is according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 checklist. A literature review across three databases and an Advanced Internet Search was performed to collect guidelines that included recommendations on HaH implementation requirements. Two authors independently extracted recommendations. Two reviewers independently assessed guideline quality using the Appraisal of Guidelines for Research and Evaluation II Instrument (AGREE II), which consisted of twenty-three items across six domains. Overall guideline quality was calculated as the total points from all six domains as a percentage over maximum points, and guidelines with overall scores of 50% or more were deemed high quality. Results Fourteen guidelines and seven sections were identified, which covered the following topics: inclusion & exclusion criteria, admission process, clinical handover, discharge, team structure, partnerships with external stakeholders, and medication administration. Key observations underline deficiencies in addressing staff safety, appropriate medical supply storage, and admission after hours. The main discrepant recommendations included self-discharge, team structure, partnerships with primary care providers, and medication self-administration. Methodological quality of guidelines varied, with overall AGREE II scores ranging from 38.5% to 58.4%. Individual domain scores were consistently low for Rigour of Development and Editorial Independence. Despite low scores in these domains, all fourteen guidelines were deemed appropriate for information extraction. Conclusion Despite inconsistencies among guidelines, a set of streamlined recommendations were consolidated. In Singapore, addressing home environment constraints, fostering stronger partnerships with community providers, and leveraging on multidisciplinary care can enhance the feasibility and sustainability of these HaH recommendations. Policy redesign should focus on further stratifying patients based on home suitability, leveraging on technology to support clinical handovers or collaborations, and investing in multidisciplinary training to strengthen workforce capabilities. In all, healthcare providers around the world should consider contextualising these recommendations within local socioeconomic and healthcare contexts for optimal HaH implementation.

Rapid Oxygen Atom Transfer at a Catalysis-Relevant Ni(I)–Alkyl Complex with N₂O

Non-end-to-end adaptive graph learning for multi-scale temporal traffic flow prediction

Accurate traffic flow prediction is vital for intelligent transportation systems but presents significant challenges. Existing methods, however, have the following limitations: (1) insufficient exploration of interactions across different temporal scales, which restricts effective future flow prediction; (2) reliance on predefined graph structures in graph neural networks, making it challenging to accurately model the spatial relationships in complex road networks; and (3) end-to-end training, which often results in unclear optimization directions for model parameters, thereby limiting improvements in predictive performance. To address these issues, this paper proposes a non-end-to-end adaptive graph learning algorithm capable of effectively capturing complex dependencies. The method incorporates a multi-scale temporal attention module and a multi-scale temporal convolution module to extract multi-scale information. Additionally, a novel graph learning module is designed to adaptively capture potential correlations between nodes during training. The parameters of the prediction and graph learning modules are alternately optimized, ensuring global performance improvement under locally optimal conditions. Furthermore, the graph structure is dynamically updated using a weighted summation approach.Experiments demonstrate that the proposed method significantly improves prediction accuracy on the PeMSD4 and PeMSD8 datasets. Ablation studies further validate the effectiveness of each module, and the rationality of the graph structures generated by the graph learning module is visually confirmed, showcasing excellent predictive performance.

On-Surface Synthesis of a Ferromagnetic Molecular Spin Trimer

A retrospective cohort study evaluating the association between opioid and alcohol-related emergency department presentations and the subsequent risk of hospitalization

Objective Our objective was to evaluate the association between two types of substance use presentations in the emergency department (ED) (opioid and alcohol) and the subsequent risk of hospital admission. Methods The study is a retrospective observational cohort study using administrative data from all patients presenting with substance use disorder (SUD) at Health Sciences North (HSN) from January 1, 2018, to August 31, 2023. Patients were placed in two groups: those with alcohol-related presentations and those with opioid-related presentations. The outcome was the time and number of ED visits between the index ED visit and first admission to the hospital for the substance-related presentation. Results A total of 5,240 individuals (45.98%) presented with opioid use, and 6,140 individuals (45.61%) presented with alcohol use. The opioid group was younger (mean age = 36.86 years, compared to 44.58 years in the alcohol group) and had higher rates of current homelessness (37.47% vs. 9.63%), a higher prevalence of mental disorders (15.71% vs. 10.68%), and a greater likelihood of being diagnosed with cellulitis (5.24% vs. 0.52%). Despite similarities in 30-day ED revisits (41.53% for alcohol vs. 40.88% for opioids) and mean length of stay (12.16 days for opioids vs. 10.04 days for alcohol), individuals in the opioid group had a higher likelihood of inpatient admission with each additional ED visit (hazard ratio = 1.28, 95% CI [1.19, 1.37]). Conclusion Our findings highlight the healthcare needs of individuals presenting to the ED with opioid use versus alcohol use, with opioid-related cases involving more acute and complex healthcare presentations.