Search Results (38,129)

Background: Mucormycosis, an invasive fungal infection with high morbidity and mortality rates, requires prompt surgical and antifungal therapies; however, the role of antifungal susceptibility testing (AFST) in clinical management of mucormycosis remains underexplored. We aimed to describe the experience of using AFST in the clinical management of mucormycosis. Methods: We conducted a retrospective study from 1 October 2017 to 8 February 2023. We included non-pregnant patients aged ≥ 18 years old with a positive culture for Mucorales and with proven or probable mucormycosis. We collected clinical and microbiological data using a chart review. Results: Over the study period, a total of 119 patients were included, with 36 (30%) undergoing AFST. Of all patients, the median age was 54 years, with 80 (67%) being White and not Hispanic and 73 (61%) being male. Fifty-three (45%) patients had DM, 27 (23%) had hematological malignancy, 15 (13%) had SOT, and 23 (19%) had COVID-19. Half of the cases met the criteria of proven invasive mucormycosis, with pulmonary involvement being the most common presentation (46, 39%), followed by rhino-cerebral-orbital involvement (35, 29%). The majority of Mucorales isolates were Rhizopus species (79, 66%). Among the 36 who underwent AFST, posaconazole minimal inhibitory concentrations (MICs) were lower than isavuconazole (range 0.03 to 2 µg/mL versus 0.1 to 16 µg/mL, respectively). AFST resulted in a change in antifungal therapy from isavuconazole to posaconazole in 3/36 (8%) cases. There was no statistically significant difference in the mortality between the patients whose isolates received AFST versus those who did not have AFST performed. Conclusions: AFST led to a change in antifungal therapy in a minority of mucormycosis cases. Further studies to understand the epidemiological range of antifungal MICs and the effect of AFST-informed antifungal therapy are needed. Full article

A longstanding debate in finance concerns the impact of social responsibility actions on firms’ long-term profitability. This study provides a broad analysis on the relationship between ESG, its components, and stock returns. Using a dataset that spans from December 2014 to December 2023, this research analyzes an annual average of around 2260 publicly traded companies from Europe and the United States. The findings consistently show a negative link between ESG ratings, their components, and stock returns, a result that is possibly explainable by the mixed effect of a reduction of risk (lower risk premium) from social responsibility, and lower profitability from associated costs. The coefficients for ESG and its pillars in explaining stock returns are generally consistent, with a few exceptions for the environmental and governance components. The environmental pillar has a stronger influence in Europe, across firm sizes, while in the US, the effect is limited to larger companies. For governance, variations align with differing ownership structures across regions and changing investor priorities as firms grow, with stronger influence in Midcaps of both regions and in U.S. Large Caps. The effects of overall ESG scores and individual pillars on stock returns across regions, firm sizes, and their interaction, provide a more comprehensive perspective on their relationship. Full article

Fulfilling social responsibilities within the ESG framework has gradually become a core competitive advantage for sustainable corporate development that also serves to enhance future returns. Charitable donations constitute a crucial method through which corporations fulfill social responsibilities and represent a primary indicator in ESG ratings, ratings that in turn have an impact on future stock market returns. This study, based on data from listed companies on the Shanghai and Shenzhen stock exchanges from 2018 to 2022, employed a fixed effects model to analyze the influence of charitable donations on future returns under ESG rating constraints. The research reveals that ESG rating constraints can reduce speculative charitable donations and help to optimize the peak value of a company’s future returns. After a series of robustness tests, including using the one-period lagged explanatory variable, changing the measurement method of the explained variable, replacing the ESG with the assignment method for value determination, and considering the impact of outliers, the conclusion still holds. Heterogeneity analysis indicates that in state-owned enterprises, companies in a recessionary phase, and industries with lower levels of competition, a decelerating effect of ESG ratings on the impact of charitable donations on future returns dominates. Conversely, for mature companies, ESG ratings accelerate the positive effect of charitable donations on future returns. This paper contributes to the ESG economic consequences literature by offering empirical evidence on corporate social responsibility implementation under sustainability strategies. Full article

The diverse rating scales used by brokerage firms pose significant challenges for aggregating analyst recommendations in financial research. We develop a momentum-based normalization framework that transforms heterogeneous rating changes into standardized sentiment signals using firm-relative, past-only empirical distribution functions with event-based lookback and expanding global quantile classification. Using 68,660 rating events from 270 brokerage firms covering 106 large-cap U.S. stocks (2019–2025), our approach generates statistically significant Buy–Sell spreads at all horizons: 1-month (0.96%, t = 3.07, p = 0.002), 2-month (1.36%, t = 3.07, p = 0.002), and 3-month (1.94%, t = 3.66, p < 0.001). Fama–French six-factor regressions confirm 13.6% annualized alpha for Buy signals (t = 3.81) after controlling for market, size, value, profitability, investment, and momentum factors. True out-of-sample validation on May–September 2025 data achieves 107% retention of in-sample 1-month performance (four of five months positive), indicating robust signal generalization. The framework provides a theoretically grounded and empirically validated methodology for standardizing analyst sentiment suitable for quantitative investment strategies and academic research. Full article

Drastic alterations have been observed in the coastline of Bangkok Bay, Thailand, over the past three decades. Understanding how coastlines change plays a key role in developing strategies for coastal protection and sustainable resource utilization. This study investigates the temporal and spatial changes in the Bangkok Bay coastline, Thailand, using remote sensing and GIS techniques from 1989 to 2024. The historical rate of coastline change for a typical segment was analyzed using the EPR method, and the underlying causes of these changes were discussed. Finally, the variation trend of the total shoreline length and the characteristics of erosion and sedimentation for a typical shoreline in Bangkok Bay, Thailand, over the past 35 years were obtained. An overall increase in coastline length was observed in Bangkok Bay, Thailand, over the 35-year period from 1989 to 2024, with a net gain from 507.23 km to 571.38 km. The rate of growth has transitioned from rapid to slow, with the most significant changes occurring during the period 1989–1994. Additionally, the average and maximum erosion rates for the typical shoreline segment were notably high during 1989–1994, with values of −21.61 m/a and −55.49 m/a, respectively. The maximum sedimentation rate along the coastline was relatively high from 2014 to 2024, reaching 10.57 m/a. Overall, the entire coastline of the Samut Sakhon–Bangkok–Samut Prakan Provinces underwent net erosion from 1989 to 2024, driven by a confluence of natural and anthropogenic factors. Full article

Model predictive control (MPC) has become an attractive solution for doubly fed induction motors (DFIMs) due to its fast dynamic response and multi-variable constraint handling capability. However, the performance of conventional MPC relies on the accuracy of the system model. To further enhance the control performance and adaptability, this paper proposes a fuzzy logic-based model predictive control (FL-MPC) strategy. The proposed method continuously monitors the current tracking errors and their rates of change, utilizing a fuzzy inference system to dynamically optimize the weight distribution within the predictive model. This enables the controller to autonomously adjust its behavior for optimal performance across a wide range of operating conditions. Both simulation and experimental results demonstrate that, compared to the conventional MPC, the proposed FL-MPC strategy achieves superior dynamic response. Full article

Background: Chemical Intolerance (CI), Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactive Disorder (ADHD) are conditions with rising incidence rates not fully explained by greater awareness or changes in diagnostic practices. It is now generally accepted that the interaction between genetic and environmental exposures plays a role in all of these conditions. Prior studies show that these conditions co-occur. This study seeks to explore previous findings using an international sample. Methods: A five-country (N = 5000) stratified panel survey was used to assess self-reported CI in themselves, and ASD and ADHD in their children. A generalized linear model was used to estimate Odds Ratios. Age- and sex-adjusted logistic models used CI as a predictor of ASD and ADHD in separate models. Results: Compared to those classified as Low CI, High levels of CI were associated with greater Odds Ratios (OR) of reporting a child with ASD and ADHD in all countries except Japan. Italy, India, and the USA had over twice the OR of reporting a child with ASD. Mexico had over 1.9 times the OR. The results with ADHD are similar to the ASD results. Conclusions: The results of this study are consistent with two prior U.S. studies, showing an association between ASD and ADHD among women who have CI. However, cross-cultural comparisons, especially prevalence estimates for ASD and ADHD, cannot be interpreted as epidemiologic rates due to serious limitations of the survey methodology. No causal relationship should be inferred from this study. Full article

Heavy precipitation, and its dependence on atmospheric circulation, is one of the most important weather features in Central Europe. The Polish–Czech Sudetes Mountains and their northern foreland are one of the regions where such precipitation, under certain circulation conditions, often results in floods. The main goal of this paper is to examine multiannual changes in seasonal heavy precipitation between 1961–2020 and to assess their relationship with atmospheric circulation. The data were derived from the Polish and Czech meteorological stations, representing various altitudes and geographical regions. For the purposes of the study, several indices were used, including 1-, 3-, and 5-day maximum precipitation, as well as two indices based on the 90th and 95th percentile thresholds. In the analysis concerning atmospheric circulation, the Lityński classification was considered. The results show that the changes in heavy precipitation usually do not indicate homogeneous directions and are strongly affected by applied indices, seasons, and various geographic factors. Those include the northern/southern slope exposition, which significantly determines heavy precipitation under circulation conditions typical for individual seasons. This particularly concerns heavy precipitation for the north and northeast types, which contribute to higher rates of the considered index, especially in the northern part of the mountains. Full article

We examined the acute effects of flywheel eccentric overload (FEO) on countermovement jumps (CMJs), changes of direction (COD), and isometric mid-thigh pulls (IMTPs) in top-level team sports athletes (three females and seven males). FEO was carried out by performing 3 × 6 reps with 0.025 kg·m² inertia and a 2 min passive rest period. Its post-activation potentiation was compared to a control warm-up. Performance was tested at 0, 3, and 6 min post-intervention. Significant improvements were reported in the COD5m times for the left (F = 8.38, p < 0.001, ES = 1.92) and right legs (F = 11.3, p < 0.001, ES = 2.24), as well as for CMJ height (F = 12.4, p < 0.001, ES = 2.35). Significant differences were observed in COD5m between baseline and 3 min (p < 0.001, ES = 0.99 and p = 0.003, ES = 1.25) and 6 min (p = 0.04, ES = 1.19 and p < 0.001, ES = 1.09) for the left and right legs, respectively. Jump height increased significantly at 3 min (p < 0.001, ES = 1.62) and remained elevated at 6 min (p < 0.001, ES = 1.02). CMJ peak power (CMJPP) decreased significantly (F = 6.4, p = 0.002, ES = 1.68), with a drop at 0 min (p = 0.024, ES = 0.85) and a return to baseline at 3 min (p = 0.002, ES = 1.35). No significant effects were found for the CMJ eccentric rate of force development (CMJRFDecc) or IMTP. It was found that FEO can acutely enhance jumping and changes of direction but not strength in elite team sports athletes. A three-minute rest appears to maximize these effects. Full article

In industrial inspection and experimental data-acquisition scenarios, the accuracy and efficiency of digital tubes, which are commonly used display components, directly affect the intelligence of the system. However, models trained on data from specific environments may experience a significant drop in recognition accuracy when applied to different environments derived from impacts of various specific scenarios (e.g., temperature changes, changes in light intensity, changes in rate, and color contrast between equipment displays and environments, among others), which may affect model accuracy. To ensure recognition accuracy, we may need to collect data from specific environments to retrain the model for each specific environment, but manual annotation is often inefficient. To address these issues, this article proposes a solution integrating image processing with deep learning within specific scenarios, encompassing the entire workflow from data acquisition to model training. Employing image processing techniques to provide high-quality training data for models, we construct a semi-supervised adversarial learning framework based on an improved self-training algorithm. The framework employs the k-means clustering algorithm for stratified sampling preparation, adds the Squeeze-and-Excitation B Block to the Convolutional Neural Network backbone, and employs the Adversarial Generative Adversarial Network to generate adversarial examples for adversarial training, thus enhancing both classification accuracy and robustness. Full article

In order to determine the heat and humidity conditions of Igloo-type calf hutches, both in open space and under verandas, an analysis was conducted of the impact of the location of the veranda within the premises of the farm and its orientation in relation to the cardinal compass points and prevailing wind speed, as well as temperature and relative atmospheric humidity. The analysis was conducted based on constant measurement (temperature, relative humidity, air velocity) for climate conditions under the veranda and in the areas between the farm buildings. The 432,432 data points obtained in this way were used for further calculations and analysis of WCT (Wind Chill Temperature) and WCI (Wind Chill Index). Studies have shown that placing the hutch under a shelter allows for more favorable thermal and humidity conditions by reducing wind speed, and consequently increasing the apparent temperature and limiting the rate of heat loss. The analysis has demonstrated that the selection of the location of the hutch or calf enclosure is crucial for calf welfare. It is recommended that environmental studies be conducted individually for farms raising calves, especially dairy cattle breeds. An optimal location and utilisation of existing infrastructure will reduce the financial outlays for implementing new solutions. This analysis, conducted in Eastern Europe, also provides a basis for inferring the impact of climate change on local microclimatic conditions. Full article

Objectives: Glaucoma is an age-related neurodegenerative disease, characterized by retinal ganglion cell loss and progressive visual field deterioration. Beyond intraocular pressure (IOP), vascular and metabolic dysregulation contributes to optic nerve head (ONH) ischemia and neuronal vulnerability. Nutritional factors with antioxidative and vasodilatory properties may help preserve ocular perfusion. This study investigated the acute and subacute effects of a single dose of a dietary supplement containing red ginger extract (Zingiber officinale var. rubra), lutein, and vitamin B6 on ONH blood flow in patients with open-angle glaucoma (OAG). Methods: A retrospective self-controlled study was conducted at Tohoku University Hospital between August 2023 and March 2025. ONH blood flow was quantified using a laser speckle flowgraphy (LSFG) baseline one hour after and one month after continuous oral supplementation in patients with OAG. Systemic parameters, ocular biometry, and concomitant glaucoma medications were recorded in medical charts. Relative mean blur rate (MBR) changes were analyzed using a linear mixed-effects model, accounting for repeated measures and inter-eye correlations. Results: Nineteen glaucoma patients (38 eyes) were included in the acute phase and 13 patients (26 eyes) completed the one-month follow-up. After adjusting for age and sex, a single oral dose of red ginger extract significantly increased the relative MBR at 1 h (106.9 ± 3.1%; p < 0.05), and this enhancement increased after 1 month of continuous intake (115.4 ± 6.7%; p < 0.05). Greater ONH perfusion was particularly prominent in eyes with shorter axial length. Conclusions: Oral supplementation was associated with acute and short-term increases in ONH blood flow in glaucomatous eyes. Although this study was a retrospective study without a placebo-controlled comparison group, our findings offer hypothesis-generating evidence that nutritional interventions may support ocular perfusion alongside conventional glaucoma management. Future prospective randomized controlled trials are required to confirm these associations. Full article

The compression deformation of seed cotton has been identified as a key factor affecting the working reliability of the baling device and the quality of bale molding. However, due to the complex working conditions of seed cotton in the continuous compression process in a confined space, it has proven to be difficult to study the compression molding mechanism of machine-harvested seed cotton in the baling process. The present study employs a universal testing machine to compress the seed cotton. In addition, pressure sensors are utilised to ascertain the internal axial load transfer law of the seed cotton. Furthermore, the internal density distribution equation of the seed cotton is established. Moreover, the Fiber model is employed to establish a spatial helix structure model of the cotton fibre. Finally, the compression simulation test is conducted to calibrate its material parameters. The results of the study indicate that seed cotton exhibits hysteresis in its internal stress–strain transfer. Through the polynomial fitting of the compression–displacement curve, it has been demonstrated that as the seed cotton approaches the compressed side, the rate of change in compression increases. The internal density distribution of the seed cotton must be calculated when it is compressed to a density of 220 kg·m⁻³. It is found that the density of the upper layer of the seed cotton is slightly greater than that of the lower layer of the seed cotton. The density distribution equation must then be obtained through regression fitting. The parameters of the compression model must be calibrated by means of uniaxial compression tests. Finally, the density distribution equation of the cotton fibre must be obtained through the compression test. The parameters of the simulation model, as determined by the uniaxial compression test calibration, are of significant importance. This is particularly evident in the context of the Poisson’s ratio of cotton fibre and the cotton fibre elastic modulus under pressure. The regression equation was obtained through analysis of variance, and the simulation of contact parameter optimisation. The optimal parameter combination was determined to be 0.466, and the pressure at this time. The relative error was found to be 2.96%, and the compression of specific performance was determined to be 10.14%. These findings serve to validate the simulation model. The findings of this study have the potential to provide a theoretical foundation and simulation assistance for the design and optimisation of cotton picker baling devices. Full article

With the rapid development of the low-altitude economy, efficient energy supply and communication systems have become key demands for low-altitude vehicles and Internet of Things (IoT) devices. This study investigates wireless powered communication systems (WPCSs) for low-altitude economy, focusing on the energy consumption characteristics of different power supply schemes under various practical application scenarios. Through simulation experiments, we compared the energy efficiency of traditional battery power, simple wireless power supply, optimized wireless power supply, and the proposed efficient WPCS (with dynamic adjustment) under changes in transmission distance, communication frequency, weather conditions, flight speed, and task complexity. The results show that traditional battery power schemes exhibit high energy consumption in long-distance transmission and high-frequency communication scenarios, while the proposed efficient WPCS significantly reduces the rate of energy consumption increase through dynamic energy transmission adjustment mechanisms, demonstrating the lowest energy consumption levels across all test scenarios. This research provides important theoretical and practical references for the design of WPCS in the low-altitude economy, highlighting the significant advantages of dynamic adjustment mechanisms in improving energy efficiency and offering technical support for the sustainable development of the low-altitude economy. Full article

In this research paper, we introduce the notions of hyperbolic ∗-Ricci solitons and gradient hyperbolic ∗-Ricci solitons. We study the hyperbolic ∗-Ricci solitons on a three-dimensional $\epsilon$-trans-Sasakian manifold. Specifically, we determine the hyperbolic ∗-Ricci solitons on a three-dimensional ($\epsilon$)-trans-Sasakian manifold with a conformal vector field and a proper $\varphi \left({\mathfrak{Q}}^{*}\right)$-type vector field. Using hyperbolic ∗-Ricci solitons with a conformal vector field, we discuss some geometric symmetries on a three-dimensional ($\epsilon$)-trans-Sasakian. In addition, we exhibit the nature of gradient hyperbolic ∗-Ricci solitons on a three-dimensional ($\epsilon$)-trans-Sasakian manifold endowed with a scalar concircular field. Moreover, we demonstrate an example on a three-dimensional ($\epsilon$)-trans-Sasakian manifold that admits the hyperbolic ∗-Ricci solitons and find the rate of change of the hyperbolic ∗-Ricci solitons within the same example. Lastly, we also introduce the concept of modified second hyperbolic ∗-Ricci solitons. Full article