Performance Trends Research Articles

Social determinants of health and their associations with outcomes in pediatric out-of-hospital cardiac arrest: A national study of the NEMSIS database

BackgroundSocial determinants of health (SDOH) impact health disparities, though little is known about the effects of SDOH on pediatric out-of-hospital cardiac arrest (POHCA). MethodsThis cross-sectional study utilized the NEMSIS Database to obtain nationwide POHCA data from 2021 to 2023. Outcomes included performance of bystander cardiopulmonary resuscitation (CPR), automated external defibrillator (AED) usage, and obtainment of return of spontaneous circulation (ROSC). SDOH data was obtained from the US Census Bureau and included minority race/ethnicities status, poverty levels, and educational attainment of the community where POCHAs occurred. Multivariable logistic regression and Cochran-Armitage trend tests were used to assess associations between SDOH and POHCA outcomes. ResultsQuery of the NEMSIS Database yielded 27,137 POHCAs. The odds of CPR performance and obtainment of ROSC were significantly higher (p < 0.001) in communities with lower levels of minority races/ethnicities. The odds of bystander CPR, AED usage, and obtainment of ROSC all increased significantly (p < 0.001) in the wealthiest communities compared to the poorest communities. The odds of bystander AED usage (p = 0.001) and ROSC (p = 0.003) were significantly higher in communities with the highest educational attainment. As the minority status and poverty level of the community increased and educational attainment decreased, there was a significant decreasing trend (p < 0.001) in performance of bystander CPR, AED usage, and obtainment of ROSC. ConclusionsCommunity-level SDOH, including increasing community minority status, poverty levels, and decreasing educational attainment, are associated with less bystander CPR, AED usage, and ROSC obtainment in POHCAs. Understanding SDOH offers opportunities for public health interventions addressing disparities in POHCA outcomes.

Rational Design of Diatomic Active Sites for Elucidating Oxygen Evolution Reaction Performance Trends.

Diatomic catalysts, especially those with heteronuclear active sites, have recently attracted significant attention for their advantages over single-atom catalysts in reactions with relatively high energy barrier, e.g. oxygen evolution reaction. Rational design and synthesis of heteronuclear diatomic catalysts are of immense significance but have so far been plagued by the lack of a definitive correlation between structure and catalytic properties. Here, we report macrocyclic precursor constrained strategy to fabricate series of transition metal (MT, Ni, Co, Fe, Mn, or Cu)-noble (MN, Ir or Ru) centers in carbon material. One notableperformance trend is observed in the order of Cu-MN < Mn-MN < Fe-MN < MN < Co-MN < Ni-MN. However, thepathway has been not altered, still following the traditional adsorption reaction mechanism. The effect of the MT atoms on theperformances could possibly originate from the distinct adsorption/desorption behaviors of key intermediates (i.e. *OH, *O and/or *OOH), strongly implying that ΔG*OOH-ΔG*OH could be used as the performance descriptor. We believe that our work provides useful strategy for synthesis of diatomic active sites with sole coordination configuration and varied composition, and in-depth insight to their catalytic mechanism, which could be used for further optimization of diatomic catalysts towards oxygen electrocatalysis.

Tuning metal-support interactions in nickel–zeolite catalysts leads to enhanced stability during dry reforming of methane

Ni-based catalysts are highly reactive for dry reforming of methane (DRM) but they are prone to rapid deactivation due to sintering and/or coking. In this study, we present a straightforward approach for anchoring dispersed Ni sites with strengthened metal-support interactions, which leads to Ni active sites embedded in dealuminated Beta zeolite with superior stability and rates for DRM. The process involves solid-state grinding of dealuminated Beta zeolites and nickel nitrate, followed by calcination under finely controlled gas flow conditions. By combining in situ X-ray absorption spectroscopy and ab initio simulations, it is elucidated that the efficient removal of byproducts during catalyst synthesis is conducted to strengthen Ni–Si interactions that suppress coking and sintering after 100 h of time-on-stream. Transient isotopic kinetic experiments shed light on the differences in intrinsic turnover frequency of Ni species and explain performance trends. This work constructs a fundamental understanding regarding the implication of facile synthesis protocols on metal-support interaction in zeolite-supported Ni sites, and it lays the needed foundations on how these interactions can be tuned for outstanding DRM performance.

Semantic Web-Based Prediction Method for Goodwill Impairment in Listed Companies Using Mamba

In the context of globalization and intense market competition, mergers and acquisitions (M&amp;A) have become a common strategy for enterprises to expand and transform. However, goodwill issues in M&amp;A are increasingly concerning. Traditional goodwill impairment prediction models face drawbacks like reliance on precise predictions, large datasets, complexity, poor interpretability, high computational costs, and data acquisition difficulties. This paper proposes a prediction model based on an improved Mamba algorithm. By processing financial data from listed companies in the CSMAR database, the model constructs lagged and rolling statistical features to reflect performance trends. The Mamba algorithm dynamically adjusts input parameters through a Selective State-Space Model (SSM), capturing dependencies in long-sequence data and improving prediction accuracy and timeliness. Experimental results show the Mamba algorithm excels in handling long-sequence data, offering valuable guidance for financial management and risk control.

National Trends and Outcomes of Pedal Bypass Surgery

ObjectiveThe technical demands associated with pedal bypass (PB) surgery place it at risk of underutilization and may be limiting its widespread adoption as a valuable revascularization modality. This study aims to evaluate trends in PB performance, assess its outcomes, and compare its results between high- and low-volume centers. MethodsAll patients receiving a PB between 2003 and 2023 were identified in the Vascular Quality Initiative (VQI) infrainguinal bypass (IIB) module. The ratio of PB to total IIB performed was calculated for each year and trended over the study period. Centers performing PB were categorized according to their annual PB volume into tertiles of low-volume centers (LVC, <2 PB/year), medium-volume centers (MVC, 2-4 PB/year), and high-volume centers (HVC, >4 PB/year) for comparison. Patient characteristics and outcomes were compared using the χ2 or Fisher exact test as appropriate for categorical variables and the analysis of variance test or Kruskal-Wallis test as appropriate for continuous variables. Cox regression analysis was used to study the association between center volume and the primary outcomes of primary patency, primary-assisted patency, secondary patency, reintervention, amputation, and major adverse limb events (MALE), defined as the composite outcome of amputation and/or reintervention. ResultsA total of 3466 patients received a PB during the study period. The ratio of PB to IIB dropped from 14% to 4% between 2003 and 2023. Primary, primary-assisted, and secondary patency rates were 65%, 76%, and 80%, respectively, and limb salvage rate was 83% at 1 year. Nineteen percent of centers performing IIBs in the VQI did not perform any PBs during the study period. Of the 246 centers performing PBs, 78% were LVC, 15% were MVC, and only 7% were HVC. On Cox regression analysis, HVCs were associated with a lower risk of primary patency loss (hazard ratio [HR], 0.79; 95% confidence interval [CI], 0.66-0.95; P = .010), reintervention (HR, 0.75; 95% CI, 0.60-0.95; P = .016), amputation (HR, 0.77; 95% CI, 0.61-0.98; P = .034), and MALE (HR, 0.78; 95% CI, 0.66-0.93; P = .005) compared with LVCs. No difference in secondary patency between high- and low-volume centers was observed (P = .680). ConclusionsThe utilization of PB operations experienced a four-fold decrease over the past 20 years, despite favorable patency and limb salvage outcomes. Centers with a higher operative volume in PB achieve better outcomes than LVCs, and accordingly, patients with extensive tibioperoneal disease may benefit from evaluation at centers with documented expertise in PB before resorting to an alternative revascularization modality or a major limb amputation.

Continuous Global Improvement of Human Papillomavirus (HPV) Genotyping Services: The 2022 and 2023 HPV LabNet International Proficiency Studies.

The International Human Papillomavirus (HPV) Reference Center launches annual global HPV genotyping proficiency panels to enhance the precision and international standardization of HPV genotyping services. This study aims to assess the proficiency levels achieved in the global HPV genotyping proficiency panels conducted in 2022 and 2023, and to evaluate trends in performance over time. The proficiency panels comprised 44 blinded samples each, including 40 samples containing various purified plasmids corresponding to HPV types combined with human DNA, plus four control samples (one negative control and three extraction controls). Proficiency required a sensitivity of 50 International Units (IU)/5 µL for HPV 16 and HPV 18 500 IU/5 µL for HPVs 6, 11, 31, 33, 45, 52, and 58 and 500 genome equivalents (GE)/5 µL for other HPV types in both single and multiple infections, while avoiding false positivity. In 2022, 78 laboratories submitted a total of 154 data sets, and in 2023, 81 laboratories contributed 141 data sets. Most data sets (87%, 258/295) utilized commercially available HPV assays. Proficiency was common, with 77% of data sets meeting the proficiency criteria in 2022 and 79% in 2023. False positive results significantly decreased from 22% in 2022 to 13% in 2023. The high proficiency and increasing specificity in HPV genotyping services indicates progress toward more reliable HPV testing. High accuracy is crucial for supporting global efforts in HPV and cervical cancer elimination.

Statistical reliability estimation of space launch vehicles: 2000–2022

This research examines the reliability of space launch vehicles (SLVs) performing commercial, civil, and military space lift missions through trend analysis and a variety of statistical methods. Data sets obtained from the Seradata database are analyzed for trends by examining data subsets including launch date, sector (commercial, civil or military), launch country, intended mission orbit, SLV family, and failed subsystem. Evolving, time-dependent first-level Bayesian success rate analysis is performed to assess SLV reliability and performance trends on 1873 launches occurring during the period 1 January 2000 to 31 December 2022. It was determined that even with a near-exponential increase in launch events in the 2020s, the number of failures is less than 6% each year, with the average success rate being 95% annually. Overall, 56% of launches were sent into low Earth orbit (LEO) and 32% were sent into geosynchronous Earth orbit (GEO) or geostationary Earth orbit (GSO). Although SLVs servicing missions to these orbital regimes featured success rates above 92%, LEO launches accounted for approximately 73% of total launch failures, while GEO-GSO launches accounted for 18% of failures. Specifically looking at U.S. and Russian SLV families, the main subsystem responsible for failure was propulsion, which accounted for 72.3% of 47 reported launch failures. First-level and second-level (using method of moments) Bayesian techniques were performed on 37 launch vehicle families and it was found that vehicles with a high accrual of launches performed with a higher reliability than vehicles with a low number of launches, resulting in first-level success rates of greater than 90%.

Comparison of rotor hovering aerodynamic performance in free-surface and ground effects using numerical methods

The aerodynamic performance of the rotor hovering on the air–water free-surface, which is significant for cross-medium unmanned aerial vehicles, is merely studied. In this study, a compressible two-phase flow model is used to compare the aerodynamic performance in the free-surface effect (FSE) and the ground effect (GE) with various dimensionless distances, γ, between the rotor and the ground (or free-surface). According to the results, the vortex core in FSE moves further in both vertical and radial directions than in GE for the early stages. Additionally, the blade surface is separated into three parts. In zone I, the aerodynamic performance is mostly determined by proximity effects. For both FSE and GE, the downward induced velocity at the rotor disk rises with increasing γ, leading to a decrease in the sectional thrust coefficient CT,S. By the way, CT,S is larger in FSE. In zone III, the aerodynamic performance is mostly governed by the blade tip vortex. The trend of aerodynamic performance with γ is reversed compared with zone I. The above-mentioned two opposing tendencies result in a smaller rotor thrust in FSE than in GE within the range of 0.60≤γ≤3.00, but a higher rotor thrust in FSE within the range of γ≤0.60.

Analgesic effect of dance movement therapy: An fNIRS study

ObjectiveThis study aims to explores the physiological and psychological mechanisms of exercise-induced hypoalgesia (EIH) by combining the behavioral results with neuroimaging data on changes oxy-hemoglobin (HbO) in prefrontal cortex (PFC). MethodsA total of 97 healthy participants were recruited and randomly divided into three groups: a single dance movement therapy (DMT) group, a double DMT group, and control group. Evaluation indicators included the pressure pain threshold (PPT) test, the color-word stroop task (CWST) for wearing functional near-infrared spectroscopy (fNIRS), and the self-assessment manikin (SAM). The testing time is before intervention, after intervention, and one hour of sit rest after intervention. Results1) Repeated measures ANOVA revealed that, there is a time * group effect on the PPT values of the three groups of participants at three time points. After 30 min of acute dance intervention, an increase in the PPT values of 10 test points occurred in the entire body of the participants in the experimental group with a significant difference than the control group. 2) In terms of fNIRS signals, bilateral DLPFC and left VLPFC channels were significantly activated in the experimental group. 3) DMT significantly awakened participants and brought about pleasant emotions, but cognitive improvement was insignificant. 4) Mediation effect analysis found that the change in HbO concentration in DLPFC may be a mediator in predicting the degree of improvement in pressure pain threshold through dance intervention (total effect β = 0.7140). ConclusionIn healthy adults, DMT can produce a diffuse EIH effect on improving pressure pain threshold, emotional experience but only showing an improvement trend in cognitive performance. Dance intervention significantly activates the left ventrolateral and bilateral dorsolateral prefrontal cortex. This study explores the central nervous system mechanism of EIH from a physiological and psychological perspective.

Study on the effect of thickness on sound absorption performance of foam aluminum

Abstract This paper investigates the effects of different thicknesses on the sound absorption performance of foam aluminum with different pore sizes through a combination of experiments and theoretical research. The results show that the average sound absorption coefficient of small-pore foam aluminum increases with increasing material thickness. As the thickness increases, there is a trend of the peak sound absorption performance shifting towards lower frequencies. In the mid-frequency range, although the sound absorption coefficient increases with the thickness of foam aluminum, the growth rate decreases. The average sound absorption coefficient of large-pore foam aluminum significantly increases with the material thickness and is reflected across various frequency ranges. With the increase in thickness, the sound absorption efficiency also improves, but the rate of improvement gradually slows down after reaching a certain thickness. Samples with the same thickness exhibit different performances in sound absorption coefficient, especially in frequencies above 2000Hz, where these differences are more pronounced. In the high-frequency range, the sound absorption coefficient of 100mm-thick large-pore foam aluminum material approaches 1, approximately 0.95.

Innovative Approaches to Assessing the Competitiveness of Business Structures Using the Method of Analysis of Hierarchies in Multi-Criteria Ranking

The primary objective of this paper is the practical testing of a multi-criteria rating methodology for assessing the competitiveness of business structures. This aims to evaluate critical functional areas of their operations and justify specific managerial decisions to ensure sustainable competitiveness. Maintaining the competitiveness of business structures becomes a primary task in the context of high uncertainty and competition, as well as the presence of crises and politico-economic problems. To achieve the set objective, the Analytic Hierarchy Process (AHP), developed by T. Saaty, was utilized. This practical method allows for multi-criteria comparisons using expert evaluations and calculations of eigenvectors and values, providing systematization and quantitative assessment of criteria and alternatives' priorities. AHP includes procedures for synthesizing multiple judgments and obtaining priorities, allowing for consideration of the 'human factor' in decision-making preparation. The study results demonstrate that the multi-criteria approach to rating the competitiveness of business structures effectively accounts for all areas of their activities and forms an adequate comprehensive measure of competitiveness. Within the study's framework, three business structures with different performance trends were analyzed. The comparative importance of criteria and sub-criteria for competitiveness assessment was determined using the Analytic Hierarchy Process, considering the specifics of the business structures and their business activities. The proposed methodology for multi-criteria rating of business structures' competitiveness allows for a comprehensive assessment of their activities and justification of specific managerial decisions to ensure sustainable competitiveness. The use of the Analytic Hierarchy Process helps to consider the influence of various factors and conditions, contributing to a more objective assessment and strategic decision-making. The application of the proposed methodology is universal and can be effectively used in various sectors of business structures' activities, showcasing its adaptability.

Comparative analysis of Physician Assistant/Associate National Certifying Examination (PANCE) performance trends: pre and during COVID-19 era

BackgroundCOVID-19 significantly impacted physician assistant/associate (PA) education programs. Most programs transitioned didactic and clinical education from in-person to remote, and clinical training opportunities diminished. Graduates of accredited PA programs take the Physician Assistant National Certifying Examination (PANCE), a five-hour exam with 300 multiple-choice questions, and must attain or exceed the scaled passing score of 350 (range: 200–800). We examined first-time examinees’ trends in PANCE scores and passing rates three years prior to the pandemic and three years during.MethodsWe analyzed data (N = 59,459) from the National Commission on Certification of Physician Assistants. The two primary outcomes were PANCE scores and pass rates. The main exposure was the timeframe: three years pre-pandemic (2017–2019) and three years during the pandemic (2020–2022). The 2017–2018 scores were equated to the new passing standard implemented in 2019. Covariates included age, gender, years the PA program has been accredited, program region, and rural-urban setting. Analyses consisted of descriptive, bivariate, and multivariate statistics.ResultsThe mean PANCE score and pass rate during the six-year study period were 463 and 93%, respectively. In unadjusted analyses comparing each year individually, mean PANCE score was highest in 2020 and lowest in 2022 than in all other years except for 2017. When comparing each pandemic year to the pooled three pre-pandemic years and adjusting for test-taker and PA program covariates, examinees scored significantly higher in 2020; there was no difference in 2021, and they scored lower in 2022. When controlling for covariates, examinees had 1.24 higher odds of failing in 2022 compared to the pooled pre-pandemic period.ConclusionFindings suggest that PANCE scores and pass rates were impacted during the third year of the pandemic. PANCE assesses if examinees have the essential clinical knowledge to enter the PA profession. It is crucial to determine whether the pandemic affected PANCE scores and pass rates to ensure PAs provide safe and high-quality patient care.

Trends in enrolment and academic performance of scheduled tribe students at the undergraduate level in Assam: A decadal analysis

This research work examines the enrolment and performance pattern of the Scheduled Tribe (ST) students at the undergraduate level in Assam for the period of 2012-2022. Based on the enrolment data collected from various ST students, the study examines the gender pattern and course selection of students in different disciplines such as B.A., B.Com., and B.Sc. The study reveals major trends in enrolment increase, gender distribution, and course choices for the decade. Using chi-square tests and comparative performance measures, the study reveals factors that affect academic performance and enrolment. Furthermore, bar graphs and line charts are used to present these trends and to give further analysis. The conclusion of this study provides significant implications for the policymakers and educators who are interested in improving the educational access and opportunities for ST students in the higher education in Assam.

Empowering the circular economy practices: Lifecycle assessment and machine learning-driven residual value prediction in IoT-enabled microwave oven

In an era of resource scarcity and environmental concerns, integrating Internet of Things (IoT) technology into the circular economy (CE), particularly for household appliances like microwaves, is crucial. The lack of systematic assessment of their post-use residual values often reduces utilization and shortens lifespans. Inadequate disposal and management contribute to electronic waste and environmental pollution. Addressing these challenges is vital for efficient appliance management within resource constraints, ensuring meaningful contributions to sustainable resource management. Thus, this study addresses these concerns by integrating IoT technology into microwave ovens, enabling real-time monitoring of key parameters such as voltage, current, door closures, and motor/blade rotations. Data from integrated sensors enables performance analysis and trend tracking, offering potential for advancing CE practices and sustainable product management. Subsequently, utilizing the insights stored from IoT data analysis and tailored surveys, a predictive maintenance model is developed, aiming to predict the life cycles of microwave oven components and categorize them within the CE principles, including reuse, repair, remanufacturing, and cascade. Finally, to mitigate the challenges of lower effective utilization and shortened operating lifespans observed in household appliances, this research employs machine learning models such as Random Forest, Gradient Boosting, and Decision Tree to accurately predict the residual values of IoT-enabled microwaves. Notably, Random Forest demonstrates superior accuracy compared to the other models. Therefore, these technological advancements allow household appliances to be utilized more effectively, thereby enhancing resource utilization.

Analyzing the Performance Trends in Licensure Examination for Teachers (LET) Among Bachelor of Elementary Education (BEEd) Graduates: A Quantitative Approach

The study analyzes the performance trends in the Licensure Examination for Teachers (LET) among Bachelor of Elementary Education (BEEd) graduates from Sultan Kudarat State University – Kalamansig Campus from 2018 to 2023. A descriptive-comparative research design was employed to statistically measure the objectives of the study. Data were obtained from the Professional Regulation Commission (PRC). The study’s respondents are 73 first-timers and 112 repeaters. A total of 185 BEEd examinees were the respondents of the study. Also, the study utilized frequency and percentage counts, z-scores, and p-values to compare the performance and test for significant differences. The results revealed that the performance trends among the BEEd graduates was fluctuating. Performance of first-timers are higher than repeaters in most periods, with institutional passing rates below national passing rates. Notably, exceptional performances were recorded during the March 2019, June 2022, and October 2022 examination periods, where institutional passing rates surpassed national passing rates. The study identifies several factors influencing LET performance, including academic preparation, review sessions, and external disruptions such as the COVID-19 pandemic, which impacted the consistency and preparation of examinees. The data suggest that while first-timers showed relatively strong performance, repeaters faced significant challenges, underscoring the need for targeted support systems to enhance their preparedness and outcomes. The findings highlight the critical importance of continuous monitoring and strategic interventions to improve LET performance. Implementing effective support mechanisms for repeaters, improving academic and review processes, and addressing external factors are essential steps toward enhancing the quality of teacher education.

The Correlation Dynamics Between Sensex 30 Returns and INR/USD Exchange Rate Movements

The Sensex 30 is a benchmark index for India's largest companies, indicating the health of the stock market. Its movements are influenced by domestic economic conditions, corporate performance, and global trends. The INR/USD exchange rate, which represents the Indian rupee vs. the US dollar, is crucial for India's international trade and investment. A depreciating rupee benefits export-oriented companies but increases import costs, affecting market performance. Understanding this dynamic is essential for investors and policymakers. The fluctuating link between the INR/USD currency pair and SENSEX 30 stock index is examined in this study from 2014 to 2024, with an emphasis on how changes in the exchange rate affect stock market performance. As India continues to integrate into the global economy, the interaction between foreign investments and the Indian stock market has become increasingly relevant for understanding investor sentiment and economic stability. This study particularly examines how returns from the SENSEX 30, an index that monitors 30 of India's biggest and most traded firms, are impacted by changes in the INR/USD exchange rate. The research's main finding is that there is a strong positive correlation between the INR/USD exchange rate and the SENSEX 30 index, with a rise of 1 in the SENSEX 30 for every 0.90 increase in the exchange rate. This implies that the depreciation of the Indian currency (INR) in relation to the US Dollar (USD) may result in increased stock market returns, especially in industries that rely heavily on exports, as Indian goods become more competitive in international markets due to the weaker currency. On the other hand, persistent depreciation may also result in higher import prices and inflationary pressures, which might be detrimental to business profitability and the state of the economy as a whole. Given that currency changes may have an impact on their investment decisions, foreign institutional investors (FIIs) are essential to this dynamic.. Decreased international gains are eroded by a lower INR, which frequently leads to portfolio modifications and more market volatility. Exchange rate fluctuations and stock market performance are influenced by the participation of foreign institutional investors (FIIs) and the Reserve Bank of India's (RBI) monetary policy choices. For example, the RBI's changes to interest rates have an effect on investor mood and influence market movements. Global economic variables that affect the US stock market and exchange rate include geopolitical tensions, changes in the price of commodities, particularly oil, and US Federal Reserve policies. The study uses a variety of statistical techniques, including as trend analysis, a t-test, and correlation analysis, to assess the link between the performance of the SENSEX 30 and the INR/USD exchange rate during a ten-year period. The results of the t-test demonstrate that the difference between the mean values of the SENSEX 30 and the INR/USD exchange rate is statistically significant, with a t-statistic of 30.278 and very tiny p-values. The SENSEX 30 exhibits a significantly bigger variation than the INR/USD, suggesting that the stock market is more volatile than the currency rate. This result is in line with predictions because stock markets are often more erratic than exchange rates. As a result, the study emphasizes how much exchange rate fluctuations affect the Indian stock market. It is recommended that investors keep a careful eye on currency changes since they have the International Journal of Scientific Research in Engineering and Management (IJSREM) Volume: 08 Issue: 09 | Sept - 2024 SJIF Rating: 8.448 ISSN: 2582-3930 © 2024, IJSREM | www.ijsrem.com DOI: 10.55041/IJSREM37610 | Page 2 potential to impact business profitability and stock market performance, particularly in industries that depend on imports or exports. The results also emphasize how crucial it is to diversify portfolios and hedge against risk related to currencies in order to successfully manage the intricate relationships between monetary policy, market volatility, and global economic situations.

Protección sísmica de estructuras civiles mediante dispositivo INERTER en la provincia de Huancayo

This research work proposes the use of a Tuned-Mass-Damper-Inerter (TMDI), which combines a new configuration of passive vibration control using an “Inerter”. This two-terminal mechanical flywheel device, based on the well-known Tuned-Mass-Damper (TMD), generates resistance forces proportional to the relative acceleration of its terminals. TMDI takes advantage of the “mass amplification effect” of Inerter to improve performance compared to TMD. For harmonically excited primary linear systems, closed-form analytical software is modeled to obtain optimal design and tuning parameters of the TMDI, using established methods. It is observed that, with proper distribution of the dampers, the TMDI system is more effective in suppressing vibrations close to the natural frequency of the uncontrolled primary system and is more resistant to the effects of detuning and misdistribution. Furthermore, the results of the modeled structures show the effectiveness of the TMDI, modeled as a classical damper, in suppressing the fundamental mode of vibration for linear MDOF structures. The incorporation of the Inerter in the proposed TMDI configuration can replace part of the vibrating mass, achieving lightweight passive vibration control solutions or improving structural performance. The solution proposed and modeled with traditional dampers behaves linearly, in line with current performance trends for minimally damaged structures protected by passive control devices. Additionally, optimized TMDI is applied for vibration suppression and displacement control, offering optimal seismic protection.

Electrochemical aspects of Li[Ni0.6Co0.2Mn0.2]O2 cathode materials doped by various ionic radius cations

The capacity of Li[Ni0.6Co0.2Mn0.2]O2 cathode materials decreases rapidly due to layer structure degradation, grain cracking, and electrolyte side reaction during cycling. In this paper, metal ions with different ionic radius (W6+= 0.62 Å, Mg2+= 0.72 Å, Y3+= 0.90 Å) were doped into single crystal Li[Ni0.6Co0.2Mn0.2]O2, which were synthesized by high-temperature solid-phase technology. X-ray diffraction (XRD), energy dispersive spectrometry (EDS) and scanning electron microscopy (SEM) were employed to characterize various samples doped with different ionic radius. The results reveal that the radius of the doped ions plays a crucial role in improving the stability of material structure. It is attributed to the incorporation of metal ions into the Li+ or Ni2+ site, thus maintaining the integrity of the layer and reducing cation mixing. However, it is also detrimental to the performance of single crystal Li[Ni0.6Co0.2Mn0.2]O2 because of lattice distortion caused by the ionic radius of the doped metal being much greater than that of the doped site. These results show superior capability and reveal the performance trend of Li[Ni0.6Co0.2Mn0.2]O2 with metal ions of different radius. The initial discharge capacity at 0.1 C for the undoped sample was 183.8 mAh/g, compared with 189.9, 192.3 and 199.8 mAh/g for NCM622-W, NCM622-Mg, and NCM622-Y, respectively. After 100 cycles, NCM, NCM-W, NCM-Mg, and NCM-Y delivered retentions of 90.88 %, 98.16 %, 97.13 %, 94.37 %, respectively. The defect model is mainly responsible for the improvement in electrochemical performance.

Influence of Cultural Factors on Organizational Performance of Multinational Corporations: A Bibliometric Review from 1983 to 2020

Cultural factors are critical in shaping the organizational performance of multinational corporations (MNCs) operating across diverse countries and cultures. This study conducts a comprehensive bibliometric analysis to explore scientific developments in this research area from 1983 to 2020, based on 856 documents published across 195 journals indexed in the Web of Science. The analysis provides insights into (i) productivity and performance trends within the field, (ii) the most influential countries, regions, journals, authors, and citations, and (iii) frequently occurring keywords that highlight future research directions. This study captures the historical evolution of research on cultural factors, providing a valuable baseline for understanding the pre-COVID-19 context and enabling MNCs to better navigate cross-cultural communication and collaboration in an increasingly complex global environment.

Gemini AI vs. ChatGPT: A comprehensive examination alongside ophthalmology residents in medical knowledge.

The rapid advancement of artificial intelligence (AI), particularly in large language models like ChatGPT and Google's Gemini AI, marks a transformative era in technological innovation. This study explores the potential of AI in ophthalmology, focusing on the capabilities of ChatGPT and Gemini AI. While these models hold promise for medical education and clinical support, their integration requires comprehensive evaluation. This research aims to bridge a gap in the literature by comparing Gemini AI and ChatGPT, assessing their performance against ophthalmology residents using a dataset derived from ophthalmology board exams. A dataset comprising 600 questions across 12 subspecialties was curated from Israeli ophthalmology residency exams, encompassing text and image-based formats. Four AI models - ChatGPT-3.5, ChatGPT-4, Gemini, and Gemini Advanced - underwent testing on this dataset. The study includes a comparative analysis with Israeli ophthalmology residents, employing specific metrics for performance assessment. Gemini Advanced demonstrated superior performance with a 66% accuracy rate. Notably, ChatGPT-4 exhibited improvement at 62%, Gemini at 58%, and ChatGPT-3.5 served as the reference at 46%. Comparative analysis with residents offered insights into AI models' performance relative to human-level medical knowledge. Further analysis delved into yearly performance trends, topic-specific variations, and the impact of images on chatbot accuracy. The study unveils nuanced AI model capabilities in ophthalmology, emphasizing domain-specific variations. The superior performance of Gemini Advanced superior performance indicates significant advancements, while ChatGPT-4's improvement is noteworthy. Both Gemini and ChatGPT-3.5 demonstrated commendable performance. The comparative analysis underscores AI's evolving role as a supplementary tool in medical education. This research contributes vital insights into AI effectiveness in ophthalmology, highlighting areas for refinement. As AI models evolve, targeted improvements can enhance adaptability across subspecialties, making them valuable tools for medical professionals and enriching patient care. What is known AI breakthroughs, like ChatGPT and Google's Gemini AI, are reshaping healthcare. In ophthalmology, AI integration has overhauled clinical workflows, particularly in analyzing images for diseases like diabetic retinopathy and glaucoma. What is new This study presents a pioneering comparison between Gemini AI and ChatGPT, evaluating their performance against ophthalmology residents using a meticulously curated dataset derived from real-world ophthalmology board exams. Notably, Gemini Advanced demonstrates superior performance, showcasing substantial advancements, while the evolution of ChatGPT-4 also merits attention. Both models exhibit commendable capabilities. These findings offer crucial insights into the efficacy of AI in ophthalmology, shedding light on areas ripe for further enhancement and optimization.