Search Results (2,778)

Crude oil and grain, as two pivotal global commodities, exhibit significant price co-movement that profoundly affects national economic stability and food security. From the perspective of systems theory, the energy and grain markets do not exist in isolation but rather form a highly coupled complex system, characterized by nonlinear feedback, cross-market risk contagion, and cascading effects. This study systematically investigates the transmission mechanisms from international crude oil prices to the domestic prices of Chinese four major grains, employing the DY spillover index, Vector Error Correction Model (VECM), and a mediation effect framework. The empirical findings reveal three key insights. First, rising international crude oil prices significantly strengthen the pass-through of global grain prices to domestic markets, while simultaneously weakening the effectiveness of domestic price stabilization policies. Second, higher crude oil prices amplify international-to-domestic price spillovers by increasing maritime freight costs, a key channel in global grain trade logistics. Third, elevated oil prices stimulate demand for renewable biofuels, including biodiesel and ethanol, thereby boosting international demand for corn and soybeans and intensifying the transmission of price fluctuations in these commodities to the domestic market. These findings reveal the key pathways through which shocks in the energy market affect food security and highlight the necessity of studying the “energy–food” coupling mechanism within a systems framework, enabling a more comprehensive understanding of cross-market risk transmission. Full article

Sustainable aviation fuel (SAF) is a drop-in alternative to conventional jet fuels, designed to reduce greenhouse gas (GHG) emissions while requiring minimal infrastructure changes and certification under the American Society for Testing and Materials (ASTM) D7566 standard. This study assesses recently identified high-energy-density (HED) strained polycycloalkanes as SAF candidates. Strain energy (E_se) was calculated using density functional theory (DFT), while operational properties such as boiling point (BP) and flash point (FP) were predicted using support vector regression (SVR) models. The models demonstrated strong predictive performance (R² > 0.96) with mean absolute errors of 6.92 K for BP and 9.58 K for FP, with robustness sensitivity analysis. It is found that approximately 65% of these studied polycycloalkanes fall within the Jet A fuel property boundaries. The polycycloalkanes (C₉–C₁₅) with strain energies below approximately 60 kcal/mol achieve an balance between energy density and ignition safety, aligning with the specifications of Jet A. The majority of structures were dominated by five-membered rings, with a few three- or four-membered rings enhancing favorable trade-offs among BP, FP, and HED. This early pre-screening indicates that moderately strained polycycloalkanes are safe, energy-dense candidates for next-generation sustainable jet fuels and provide a framework for designing high-performance SAFs. Full article

Introduction: Clear aligner therapy has become a mainstream alternative to fixed orthodontics due to its versatility. However, the variability in thermoforming and the limited validation of digital workflows remain major barriers to reproducibility and predictability. Methods: This study addresses that gap by presenting a proof-of-concept digital workflow for clear aligner manufacturing by integrating additive manufacturing (AM), thermoforming simulation, and finite element analysis (FEA). Dental models were 3D-printed and thermoformed under clinically relevant pressures (400 kPa positive and −90 kPa negative). Results and Discussion: Geometric accuracy was quantified using CloudCompare v2.13.0, showing that positive-pressure thermoforming reduced maximum deviations from 1.06 mm to 0.4 mm, with all deviations exceeding the expanded measurement uncertainty. Thickness simulations of PETG sheets (0.5 and 0.75 mm) showed good agreement with experimental values across seven validation points, with errors <10% and overlapping 95% confidence intervals. Stress analysis indicated that force transmission was localized at the aligner–attachment interface, consistent with expected orthodontic mechanics. Conclusion: By quantifying accuracy and mechanical behavior through numerical and experimental validation, this framework demonstrates how controlled thermoforming and simulation-guided design can enhance aligner consistency, reduce adjustments, and improve treatment predictability. Full article

Explosions, including those from war weapons, terrorist attacks, etc., can lead to damage and overall collapse of bridges. However, there are no clear guidelines for anti-blast design and protective measures for bridges under blast loading in current bridge design specifications. With advancements in intelligent construction, precast segmental bridge piers have become a major trend in social development. There is a lack of full understanding of the anti-blast performance of precast segmental bridge piers. To study the engineering calculation method for blast load acting on a typical precast segmental reinforced concrete (RC) pier in near-field explosions, an air explosion test of the precast segmental RC pier is firstly carried out, then a fluid–structure coupling numerical model of the precast segmental RC pier is established and the interaction between the explosion shock wave and the precast segmental RC pier is discussed. A numerical simulation of the precast segmental RC pier in a near-field explosion is conducted based on a reliable numerical model, and the distribution of the blast load acting on the precast segmental RC pier in the near-field explosion is analyzed. The results show that the reflected overpressure on the pier and the incident overpressure in the free field are reliable. The simulation results are basically consistent with the experimental results (with a relative error of less than 8%), and the fluid–structure coupling model is reasonable and reliable. The explosion shock wave has effects of reflection and circulation on the precast segmental RC pier. In the near-field explosion, the back and side blast loads acting on the precast segmental RC bridge pier can be ignored in the blast-resistant design. The front blast loads can be simplified and equalized, and a blast-resistant design load coefficient (1, 0.2, 0.03, 0.02, and 0.01) and a calculation formula of maximum equivalent overpressure peak value (applicable scaled distance [0.175 m/kg^1/3, 0.378 m/kg^1/3]) are proposed, which can be used as a reference for the blast-resistant design of precast segmental RC piers. Full article

The prediction of stock prices is challenging due to their volatility, irregular patterns, and complex time-series structure. Reliably forecasting stock market data plays a crucial role in minimizing financial risk and optimizing investment strategies. However, traditional models often struggle to capture temporal dependencies and extract relevant features from noisy inputs, which limits their predictive performance. To improve this, we developed an enhanced recursive feature elimination (RFE) method that blends the importance of impurity-based features from random forest and gradient boosting models with Kendall tau correlation analysis, and we applied SHapley Additive exPlanations (SHAP) analysis to externally validate the reliability of the selected features. This approach leads to more consistent and reliable feature selection for short-term stock prediction over 1-, 3-, and 7-day intervals. The proposed deep learning (DL) architecture integrates a temporal convolutional network (TCN) for long-term pattern recognition, a gated recurrent unit (GRU) for sequence capture, and multi-head attention (MHA) for focusing on critical information, thereby achieving superior predictive performance. We evaluate the proposed approach using daily stock price data from three leading companies—HDFC Bank, Tata Consultancy Services (TCS), and Tesla—and two major stock indices: Nifty 50 and S&P 500. The performance of our model is compared against five benchmark models: temporal convolutional network (TCN), long short-term memory (LSTM), GRU, Bidirectional GRU, and a hybrid TCN–GRU model. Our method consistently shows lower error rates and higher predictive accuracy across all datasets, as measured by four commonly used performance metrics. Full article

Although laboratory testing to assess aerobic capacity has been a ‘gold standard’ in sports science, its high costs and time-consuming protocols may not be feasible for monitoring and tracking progress in limited conditions. In dancesport athletes, several field-based aerobic tests have been proposed, but the majority of them have been developed for ballet or contemporary dancers at the individual level, while the data among dance couples engaging in standard dance styles is lacking. Therefore, the main purpose of this study was to validate a newly developed Ballroom Aerobic Test (BAT) protocol against objective methods. Twelve standard dancesport couples (age: 20.4 ± 3.9 years; height: 172.1 ± 8.7 cm; weight: 60.1 ± 9.4 kg) with 8.2 ± 3.4 years of training and competing experience participated in this study. Ventilatory and metabolic parameters were generated using the MetaMax^® 3B portable gas analyzer (the BAT), while the KF1 (an increase in speed by 0.5 km * h⁻¹ by every minute) and Bruce protocols were followed in laboratory-based settings on the running ergometer. Large to very large correlations were obtained between the BAT and KF1/Bruce protocols for the absolute maximal oxygen uptake (VO₂max; r = 0.88 and 0.87) and relative VO₂max (r = 0.88 and 0.85), respiratory exchange ratio (RER; r = 0.78 and 0.76), expiratory ventilation (VE; r = 0.86 and 0.79), tidal volume (VT; r = 0.75; 95% CI = 0.57–0.87; p < 0.001), ventilatory equivalent for O₂ (VE/VO₂; r = 0.81 and 0.80) and CO₂ (VE/VCO₂; r = 0.78 and 0.82), and dead space (VD/VT; r = 0.70 and 0.74). The Bland–Altman plots indicated no systematic and proportional biases between the BAT and KF1 protocols (standard error of estimate; SEE = ± 3.36 mL * kg⁻¹ * min⁻¹) and the BAT and Bruce protocols (SEE = ± 3.75 mL * kg⁻¹ * min⁻¹). This study shows that the BAT exhibits satisfactory agreement properties against objective methods and is a valid dance protocol to accurately estimate aerobic capacity in dancesport athletes participating in standard dance styles. Full article

Harnessing Europe’s strong wave energy could support net-zero emissions goals, but extreme ocean loads still make wave energy expensive and delay the rollout of commercial wave-energy converters (WECs). To address this, the twin-floater CECO WEC has been redesigned into a single-pivot device called the Pivoting WEC (PWEC), which includes a passive duck diving survival mode to reduce extreme wave impacts. Its performance is evaluated using detailed wave simulations based on Reynolds-Averaged Navier–Stokes (RANS) equations and the Volume-of-Fluid (VoF) method in OpenFOAM-olaFlow, which is validated with data from small-scale (1:20) wave tank experiments. Extreme non-breaking and breaking waves are simulated based on 100-year hindcast data for the case study site of Matosinhos (Portugal) using a modified Miche criterion. These are validated using data of surface elevation and force sensors. Wave height errors averaged 5.13%, and period errors remain below 0.75%. The model captures well major wave loads with a root mean square error down to 47 kN compared to a peak load of 260 kN and an R² up to 0.80. The most violent plunging waves increase peak forces by 5 to 30% compared to the highest non-breaking crests. The validated numerical approach provides accurate extreme load predictions and confirms the effectiveness of the PWEC’s passive duck diving survival mode. The results contribute to the development of structurally resilient WECs, supporting the progress of WECs toward higher readiness levels. Full article

Robotic Process Automation (RPA) is a software-based technology that uses configurable algorithmic software agents (bots) to replicate manual user activities across digital systems. It represents an evolution from earlier workflow scripting tools, and is distinguished by its ability to be used without requiring substantial IT infrastructure modifications or extensive programming knowledge. In the banking and insurance sectors, organizations face increasing pressure to adopt modern technologies that streamline operations and reduce costs while complying with strict regulatory requirements. Robotic Process Automation (RPA) has emerged as a viable and cost-effective solution, enabling automation of repetitive and rule-based tasks without requiring major changes to legacy IT systems. This paper conducts a literature review to examine the current use cases of RPA technologies in banking and insurance, analyzing how these technologies are employed to enhance corporate efficiency and performance. The review draws from recent academic publications and case studies between 2017 and 2025, identifying core implementation areas such as customer onboarding, claims processing, compliance reporting, and underwriting automation. The results highlight substantial improvements in processing speed, error reduction, and resource optimization, along with evolving metrics for measuring effectiveness. The study concludes by identifying key success factors, performance measurement approaches, and challenges in RPA implementation, offering insights for both practitioners and researchers aiming to understand the role of automation in financial services transformation. Full article

Large language models have expanded their application from traditional tasks in natural language processing to several domains of science, technology, engineering, and mathematics. This research studies the potential of these models for financial “nowcasting”–real-time forecasting (of the recent past) for cryptocurrency market conditions. Further, the research benchmarks capabilities of five state-of-the-art decoder-only models, gpt-4.1 (OpenAI), gemini-2.5-pro (Google), claude-3-opus-20240229 (Anthropic), deepseek-reasoner (DeepSeek), and grok-4 (xAI) across 12 major crypto-assets around the world. Using minute-resolution history of a day in USD for the stocks, gemini-2.5-pro emerges as a consistent leader in forecasting (except for a few assets). The stablecoins exhibit minimal deviation across all models, justifying the “nowcast strength” in low-volatility environments, although they are not able to perform well for the highly erratic assets. Additionally, since large language models have been known to better their performance when executed for a higher number of passes, the experimentations were conducted for two passes (Pass@1 and Pass@2), and the respective nowcast errors are found to be reduced by $1.2156\%$ (on average). Full article

Introduction: Drug–drug interactions (DDI) are a major, preventable cause of patient harm, a challenge amplified in Jordan by rising polypharmacy and documented high rates of medication errors. To date, no study in Jordan has systematically compared hospital and community pharmacists. This study aimed to conduct the first national, comparative assessment of DDI management among these two cadres. Materials and Methods: A national, cross-sectional study was conducted with 380 licensed pharmacists (175 hospitals, 205 community) recruited via proportionate stratified random sampling. A validated online questionnaire assessed demographics, objective DDI knowledge, professional attitudes, practices, and barriers. Multivariable logistic regression was used to identify independent predictors of high knowledge and optimal practice. All collected data were coded, cleaned, and analyzed using the Statistical Package for the Social Sciences (SPSS V28.0). Results: Hospital pharmacists achieved significantly higher mean objective knowledge scores than community pharmacists (10.3 vs. 8.1 out of 15, p < 0.001), a gap particularly wide for interactions involving high-risk OTC medications. The primary barrier for community pharmacists was a lack of access to patient data (85.4%), contrasting with high workload and physician resistance in hospitals. Optimal practice was independently predicted by higher knowledge (AOR = 1.25), a hospital practice setting (AOR = 3.65), and was inhibited by perceived physician resistance (AOR = 0.45). Conclusions: Jordanian hospital and community pharmacists operate in distinct worlds of knowledge and practice. A tailored, dual-pronged national strategy is essential. For hospitals, interventions should target interprofessional dynamics. For community pharmacies, health policy reform to provide access to integrated patient data is the most urgent priority. These findings highlight a globally relevant challenge of practice-setting disparities, offering a model for other nations to develop tailored, context-specific interventions to improve medication safety. Full article

Recent studies on detecting hallucinations in summaries follow a method of decomposing summaries into atomic content units (ACUs) and then determining whether each unit logically matches the document text based on natural language inference. However, this fails to consider discourse link relations such as temporal order, causality, and purpose, leading to the inability to detect conflicts in semantic connections between individual summary ACUs, even when the conflicts are present in the document. To overcome this limitation, this study proposes a method of extracting Discourse Link-Aware Content Unit (DL-ACU) by converting the summary into an Abstract Meaning Representation (AMR) graph and structuring the discourse link relations between ACUs. Additionally, to align summary ACUs with corresponding document information in a fine-grained manner, we propose a Selective Document-Atomic Content Unit (SD-ACU). For each summary ACU, the SD-ACU retrieves only the most relevant document sentences and then decomposes them into document ACUs. Applying the DL-ACU module to existing hallucination detection systems such as FIZZ and FENICE reduces the error rate of discourse link errors on FRANK. When both modules are combined, the system improves balanced accuracy and ROC-AUC across major benchmarks. This suggests the proposed method effectively captures discourse link errors while enabling ACU-to-ACU alignment. Full article

The local convergence analysis of the $m+1$-step Newton-Jarratt composite scheme with order $2m+1$ has been shown previously. But the convergence order $2m+1$ is obtained using Taylor series and assumptions on the existence of at least the fifth derivative of the mapping involved, which is not present in the method. These assumptions limit the applicability of the method. A priori error estimates or the radius of convergence or uniqueness of the solution results have not been given either. These drawbacks are addressed in this paper. In particular, the convergence is based only on the operators on the method, which are the operator and its first derivative. Moreover, the radius of convergence is established, a priori estimates and the isolation of the solution is discussed using generalized continuity assumptions on the derivative. Furthermore, the more challenging semi-local convergence analysis, not previously studied, is presented using majorizing sequences. The convergence for both analyses depends on the generalized continuity of the Jacobian of the mapping involved, which is used to control it and sharpen the error distances. Numerical examples validate the sufficient convergence conditions presented in the theory. Full article

Background: The goal of the study was to describe the visual function characteristics of children with developmental epileptic encephalopathy resulting from mutations in the STXBP1 gene. Methods: The study included 26 consecutive patients from the Polish STXBP1 population (11 male and 16 female; mean age: 7 years and 4 months; SD 4.03; range: 2–16 years) evaluated at a single center for strabismus and binocular vision. Data were obtained from medical records, including ophthalmological, neurological, and genetic information, as well as orthoptic and ophthalmological examinations performed in the clinic. Results: No major eye disorders were identified during the ophthalmological evaluation. The average prevalence of hyperopia was 76.9% (mean for OD, OS), with hyperopia above 4.25 D occurring in 17.3% (n = 4) of participants. Astigmatism was present in 96.2% of patients, with values ≥ 2.75 D in 27% (n = 7) of the group. The mean disc–foveal angle across all subjects was 7.23° ± 6.85° (range: −10.34° to 19.77°). Convergence was absent in 53.8% (n = 14) of patients. Mean accommodation responses equal to or higher than +1.0 D in any eye were noted in 90.5% of subjects. The mean accommodative/convergence (AC/A) ratio was 1.16 (SD 1.05; range: 0–3.3). Fusion was diagnosed using the 20 base-out prism test in 77% (n = 20) of patients, of which 85% (n = 17) had a positive response. Conclusions: This is the first study to comprehensively assess visual function in children with STXBP1 synaptopathy. Binocular vision development in individuals with STXBP1 differs from that of the general population. Considering the high prevalence of refractive errors, deficits in accommodation, and a low AC/A ratio, early visual diagnostics and the use of corrective eyewear are recommended in these patients. Full article

There has been a significant increase in scientific publications in recent years, and the nursing field has been no exception. Consequently, the number of publications containing errors that lead to document retractions has also increased. It is essential to understand and delve into this phenomenon within nursing research. Objective: This study aims to identify and analyze the retractions of scientific publications in nursing research worldwide between 2000 and 2024. Methodology: This is a descriptive and cross-sectional study with a bibliometric approach. Data were collected using the Retraction Watch database, from which 408 retracted documents related to nursing research were extracted. Results: Over the last 25 years (2000–2024), a total of 408 documents in the nursing field have been retracted, with the majority concentrated in the 2020–2024 period, accounting for 84.8%. Ethical misconduct was the cause of retraction in 87.3% of the cases. Of the 408 retracted documents, 42.6% involved human participants in research or control groups, totaling 21,369 patients who were part of flawed studies. Conclusions: It is crucial that nursing research remains rigorous and adheres to bioethical standards, as these guide evidence-based nursing practice. Flawed literature can have significant consequences for patient health and care. Full article

Background/Objectives: Phenotypic antimicrobial susceptibility testing (AST) is essential for guiding timely and effective antibiotic therapy. Rapid and accurate reporting of AST results enables earlier optimization of treatment and supports antimicrobial stewardship by minimizing unnecessary use of broad-spectrum antibiotics. This study aimed to evaluate the performance of the Selux DX Next-Generation Phenotyping AST system in comparison with the standard-of-care MicroScan WalkAway Plus system and broth microdilution reference results. Methods: A total of 332 clinical isolates and 97 Antimicrobial Resistance (AR) Bank reference isolates were tested using the Selux DX and MicroScan systems. Performance was assessed by categorical agreement (CA), error rates [very major errors (VMEs), major errors (MEs), minor errors (mEs)], and turnaround time. Results: The Selux DX system demonstrated ≥90% CA for most drug–organism combinations, consistent with Clinical and Laboratory Standards Institute (CLSI) acceptance thresholds, although elevated error rates were noted for erythromycin, aztreonam, cefazolin, minocycline, and ampicillin/sulbactam. Across 5124 drug–bug combinations, 55 VMEs (1.1%), 42 MEs (0.8%), and 203 mEs (4.0%) were identified. The Selux DX system achieved a markedly shorter average turnaround time of 5.5 h compared with 16 h for the MicroScan system, though at the cost of a longer setup time. Conclusions: The Selux DX system provides rapid and reliable phenotypic AST results, supporting earlier clinical decision-making and antimicrobial stewardship. However, discrepancies with certain antimicrobial agents, particularly among highly resistant reference isolates, highlight the need for further validation in larger, multicenter studies. Full article