Search Results (5,350)

The relationship between temperature and mortality is well-documented, yet most existing studies assume this relationship remains static over time. This study investigates whether the temperature-mortality association in Chicago from 1987 to 2000 has changed in shape or location of key features, such as change points. We apply nonparametric regression techniques to estimate the temperature-mortality functions for each year using daily mortality and temperature data from the National Morbidity, Mortality, and Air Pollution Study (NMMAPS) database. A permutation-based test is used to assess whether the shapes of these functions differ across time, while a bootstrap procedure evaluates the consistency of change points. Intensive simulation studies are conducted to evaluate the permutation-based test and bootstrap procedure based on Type I error and power. The proposed tests are compared with F tests in terms of Type I error and power. For the real data set, the analysis finds significant variation in the functional shapes across years, indicating evolving mortality responses to temperature. However, the estimated change points—temperatures associated with peak mortality—remain statistically consistent. These findings suggest that while the population’s overall vulnerability pattern may shift, the temperature threshold linked to maximum mortality has remained stable. This study contributes to understanding the temporal dynamics of climate-sensitive health outcomes and highlights the importance of flexible modeling in public health and climate adaptation planning. Full article

Introduction: Oxidative stress is a key factor in the pathogenesis of many chronic diseases, especially in postmenopausal women. Xylitol, a sugar alcohol with potential antioxidant properties, may affect oxidative balance when used as a sugar substitute. Aim: This pilot study aimed to assess the effect of replacing sucrose with xylitol on serum antioxidant capacity in postmenopausal women. Methods: This study included 34 women aged 50 to 65 years who successively consumed 5 g/d, 10 g/d, and 15 g/d of xylitol. The dietary intervention lasted a total of 6 weeks, with each phase covering a 2-week period. Diet was assessed twice based on a 7-day dietary interview (Diet 6.0, NIZP–PZH, Warsaw). The material for this study was venous blood. Antioxidant capacity was determined using the DPPH radical scavenging method and the ABTS cation radical scavenging method. Results: In both methods, a significant increase in serum antioxidant potential was observed after replacing sugar with xylitol (p < 0.0001). An increase in the ability to neutralize free radicals was observed in almost all women studied. Additional analysis of the effect of selected nutrients on the obtained effects of the nutritional intervention showed that the most significant effect could potentially be exerted by manganese, maltose, sucrose, and mercury, and the strongest positive correlation was exerted by vitamin A, retinol, and vitamin E. Although the values obtained in the constructed models were not statistically significant, the large effect indicates potentially significant relationships that could have a significant impact on serum antioxidant potential in the studied group of women. Conclusions: The results suggest a potential role of xylitol in enhancing antioxidant defense mechanisms in menopausal women. Although the sample size was relatively small, this study was powered at approximately 80% to detect large effects, supporting the reliability of the observed results. Nevertheless, given the pilot nature of this study, further research with larger cohorts is warranted to confirm these preliminary observations and to clarify the clinical significance of xylitol supplementation in populations exposed to oxidative stress. Full article

Background/Objectives: This study aimed to create a ‘carbapenem resistance score’ with the risk factors of carbapenem-resistant Gram-negative bacterial infections (GNBIs) in patients with hematological malignancies. Methods: Patients with carbapenem-resistant and susceptible GNBIs were included in this study and compared in terms of risk factors. Three models of “carbapenem resistance risk scores” were created with statistically significant variables. Results: The study included 154 patients with hospital-acquired GNBIs, of whom 64 had carbapenem-resistant GNBIs and 90 had carbapenem-susceptible GNBIs. Univariate and multivariate analyses identified several statistically significant risk factors for carbapenem resistance, including transfer from another hospital or clinic (p = 0.038), prior use of antibiotics like fluoroquinolones (p = 0.009) and carbapenems (p = 0.001), a history of carbapenem-resistant infection in the last six months (p < 0.001), rectal Klebsiella pneumoniae colonization (p < 0.001), hospitalization for ≥30 days (p = 0.001), and the presence of a urinary catheter (p = 0.002). Notably, the 14-day mortality rate was significantly higher in the carbapenem-resistant group (p < 0.001). Based on these findings, three risk-scoring models were developed. Common factors in all three models were fluoroquinolone use in the last six months, rectal K. pneumoniae colonization, and the presence of a urinary catheter. The fourth variable was transfer from another hospital (Model 1), a history of carbapenem-resistant infection (Model 2), or hospitalization for ≥30 days (Model 3). All models demonstrated strong discriminative power (AUC for Model 1: 0.830, Model 2: 0.826, Model 3: 0.831). For all three models, a cutoff value of >2.5 was adopted as the threshold to identify patients at high risk for carbapenem resistance, a value which yielded high positive and negative predictive values. Conclusions: This study successfully developed three practical risk-scoring models to predict carbapenem resistance in patients with hematological malignancies using common clinical risk factors. A cutoff score of >2.5 proved to be a reliable threshold for identifying high-risk patients across all models, providing clinicians with a valuable tool to guide appropriate empirical antibiotic therapy. Full article

The piston-type expander (PTE), as the primary output component, significantly influences the performance of an energy storage system. This paper proposes a non-cam variable valve actuation system for the PTE, supported by a mathematical model. An enhanced S-curve trajectory planning method is used to design the valve lift curve. The study investigates the effects of various valve lift design parameters on output power and efficiency at different rotational speeds, employing orthogonal design and SPSS Statistics 27 (Statistical Product and Service Solutions) simulations. A grey comprehensive evaluation method is used to identify optimal valve lift parameters for each speed. The results show that valve lift parameters influence PTE performance to varying degrees, with intake duration having the greatest effect, followed by maximum valve lift, while intake end time has the least impact. The non-cam PTE outperforms the cam-based PTE. At 800 rpm, the optimal design yields 7.12 kW and 53.5% efficiency; at 900 rpm, 8.17 kW and 50.6%; at 1000 rpm, 9.2 kW and 46.8%; and at 1100 rpm, 12.09 kW and 41.2%. At these speeds, output power increases by 18.37%, 11.42%, 11.62%, and 9.82%, while energy efficiency improves by 15.01%, 15.05%, 14.24%, and 13.86%, respectively. Full article

This study aimed to investigate the effects of mental fatigue on physical and cognitive performance (lower-limb power, isometric and handgrip strength, and psychomotor vigilance). Twenty-two physically active young adults (12 males, 10 females; M_age = 20.82 ± 1.47) were randomly assigned to either a Mental Fatigue (MF) or Control group (CON). The MF group showed a statistically significant (p = 0.019) reduction in non-dominant handgrip strength, declining by approximately 2.3 kg (about 5%), while no such change was observed in the CON group or in dominant handgrip strength across groups. Reaction time (RT) was significantly impaired following the mental fatigue protocol: RT increased by 117.82 ms, representing an approximate 46% longer response time in the MF group (p < 0.001), whereas the CON group showed a smaller, non-significant increase of 32.82 ms (~12% longer). No significant differences were found in squat jump performance, indicating that lower-limb explosive power may be less affected by acute mental fatigue. These findings demonstrate that mental fatigue selectively impairs fine motor strength and cognitive processing speed, particularly reaction time, while gross motor power remains resilient. Understanding these effects is critical for optimizing performance in contexts requiring fine motor control and sustained attention under cognitive load. Full article

Artificial intelligence has taken a seat at the executive table and is threatening the fact that human beings are the only ones who should be in a position of power. This article gives conjectures on the future of leadership in which managers will collaborate with learning algorithms in the Neural Adaptive Artificial Intelligence Leadership Model, which is informed by the transformational literature on leadership and socio-technical systems, as well as the literature on algorithmic governance. We assessed the model with thirty in-depth interviews, system-level traces of behavior, and a verified survey, and we explored six hypotheses that relate to algorithmic delegation and ethical oversight, as well as human judgment versus machine insight in terms of agility and performance. We discovered that decisions are made quicker, change is more effective, and interaction is more vivid where agile practices and good digital understanding exist, and statistical tests propose that human flexibility and definite governance augment those benefits as well. It is single-industry research that contains self-reported measures, which causes research to be limited to other industries that contain more objective measures. Practitioners are provided with a practical playbook on how to make algorithmic jobs meaningful, introduce moral fail-safes, and build learning feedback to ensure people and machines are kept in line. Socially, the practice is capable of minimizing bias and establishing inclusion by visualizing accountability in the code and practice. Filling the gap between the theory of leadership and the reality of algorithms, the study provides a model of intelligent systems leading in organizations that can be reproduced. Full article

Introduction: Haglund’s deformity, characterized by bony enlargement at the back of the heel, often coincides with Achilles tendon pathology due to impingement on the retrocalcaneal bursa and tendon insertion. Surgical management of Haglund’s deformity with a preexisting Achilles tendon rupture is complex, and understanding the outcomes of this subset of patients is essential for optimizing treatment strategies. Methods: This retrospective study reviewed patients undergoing open surgical management for Haglund’s syndrome between January 2015 and December 2023. Patients with chronic degenerative changes secondary to Haglund’s deformity and a preoperative Achilles tendon rupture were compared to those without. Data on demographics, surgical techniques, weightbearing protocols, and complications were collected. Univariate analysis was performed using χ² or Fisher’s exact test for categorical variables, and the T-test or Wilcoxon rank-sum test for continuous and ordinal variables, with normality assessed via the Shapiro–Wilk test. Results: Four hundred and three patients were included, with 13 having a preoperative Achilles tendon rupture. There was a higher incidence of preoperative ruptures among males. Surgical repair techniques and postoperative weightbearing protocols varied, though were not randomized. Complications included persistent pain, wound breakdown, infection, plantar flexion weakness, and revision surgery. While patients with Haglund’s deformity and a preoperative Achilles tendon rupture demonstrated a trend toward higher complication rates, including postoperative rupture and wound breakdown, these differences were not statistically significant in our analysis. Conclusions: A cautious approach is warranted in managing these patients, with careful consideration of surgical planning and postoperative rehabilitation. While our findings provide valuable insights into managing patients with Haglund’s deformity and preoperative Achilles tendon rupture, the retrospective design, limited sample size of the rupture group, and short duration of follow-up restrict generalizability and the strength of the conclusions by limiting the power of the analysis and underestimating the incidence of long-term complications. Therefore, the results of this study should be interpreted with caution. Further studies with larger patient cohorts, validated functional outcome measures, and comparable follow-up durations between groups are needed to confirm these results and optimize treatment approaches. Full article

The spectral variation hypothesis (SVH) posits that the complexity of spectral information in remote sensing imagery can serve as a proxy for regional biodiversity. However, the relationship between spectral diversity (SD) and biodiversity differs for different environmental conditions. Previous SVH studies often overlooked these differences. We utilized species data from field surveys in Inner Mongolia and drone-derived multispectral imagery to establish a quantitative relationship between SD and biodiversity. A geographically weighted regression (GWR) model was used to describe the SD–biodiversity relationship and map the biodiversity indices in different experimental areas in Inner Mongolia, China. Spatial autocorrelation analysis revealed that both SD and biodiversity indices exhibited strong and statistically significant spatial autocorrelation in their distribution patterns. Among all spectral diversity indices, the convex hull area exhibited the best model fit with the Margalef richness index (Margalef), the coefficient of variation showed the strongest predictive performance for species richness (Richness), and the convex hull volume provided the highest explanatory power for Shannon diversity (Shannon). Predictions for Shannon achieved the lowest relative root mean square error (RRMSE = 0.17), indicating the highest predictive accuracy, whereas Richness exhibited systematic underestimation with a higher RRMSE (0.23). Compared to the commonly used linear regression model in SVH studies, the GWR model exhibited a 4.7- to 26.5-fold improvement in goodness-of-fit. Despite the relatively low R² value (≤0.59), the model yields biodiversity predictions that are broadly aligned with field observations. Our approach explicitly considers the spatial heterogeneity of the SD–biodiversity relationship. The GWR model had significantly higher fitting accuracy than the linear regression model, indicating its potential for remote sensing-based biodiversity assessments. Full article

The energy generated from renewable sources has an intermittent nature since solar irradiation and wind speed vary continuously. Hence, their energy should be stored to be utilized throughout their shortage. There are various forms of energy storage systems while the most widespread technique is the battery storage system since its cost is low compared to other techniques. Therefore, batteries are employed in several applications like power systems, electric vehicles, and smart grids. Due to the merits of the lithium-ion (Li-ion) battery, it is preferred over other kinds of batteries. However, the accuracy of the Li-ion battery model is essential for estimating the state of charge (SOC). Additionally, it is essential for consistent simulation and operation throughout various loading and charging conditions. Consequently, the determination of real battery model parameters is vital. An innovative application of the red-billed blue magpie optimizer (RBMO) for determining the model parameters and the SOC of the Li-ion battery is presented in this article. The Shepherd model parameters are determined using the suggested optimization algorithm. The RBMO-based modeling approach offers excellent execution in determining the parameters of the battery model. The suggested approach is compared to other programmed algorithms, namely dandelion optimizer, spider wasp optimizer, barnacles mating optimizer, and interior search algorithm. Moreover, the suggested RBMO is statistically evaluated using Kruskal–Wallis, ANOVA tables, Friedman rank, and Wilcoxon rank tests. Additionally, the Li-ion battery model estimated via the RBMO is validated under variable loading conditions. The fetched results revealed that the suggested approach achieved the least errors between the measured and estimated voltages compared to other approaches in two studied cases with values of 1.4951 × 10⁻⁴ and 2.66176 × 10⁻⁴. Full article

This paper aims to find an efficient optimization algorithm to bring down the cost function without compromising the stability of the system and respect the operational constraints of the Hybrid Renewable Energy System. To accomplish this, MATLAB simulations were carried out using three optimization techniques: Grey Wolf Optimization (GWO), Teaching–Learning-Based Optimization (TLBO), and Multi-Objective Particle Swarm Optimization (MOPSO). The study compared their outcomes to identify which method yielded the most effective performance. The research included a statistical analysis to evaluate how consistently and stably each optimization method performed. The analysis revealed optimal values for the output power of photovoltaic systems (PVs), wind turbines (WTs), diesel generator capacity (DGs), and battery storage (BS). A one-year period was used to confirm the optimized configuration through the analysis of capital investment and fuel consumption. Among the three methods, GWO achieved the best fitness value of 0.24593 with an LPSP of 0.12528, indicating high system reliability. MOPSO exhibited the fastest convergence behaviour. TLBO yielded the lowest Net Present Cost (NPC) of 213,440 and a Cost of Energy (COE) of 1.91446/kW, though with a comparatively higher fitness value of 0.26628. The analysis suggests that GWO is suitable for applications requiring high reliability, TLBO is preferable for cost-sensitive solutions, and MOPSO is advantageous for obtaining quick, approximate results. Full article

This study examines the impact of free trade zone (FTZ) establishment on regional economic resilience (RER) in China, using provincial-level panel data spanning from 2010 to 2022 and a multi-period difference-in-differences (DID) approach. The empirical results indicate that FTZ implementation significantly enhances regional economic resilience by 3.46%, with the development of green finance acting as a key moderating mechanism that amplifies this positive effect. Heterogeneity analysis uncovers notable disparities across policy cohorts and geographical regions: the first wave of FTZs demonstrates the most pronounced resilience-enhancing impact, whereas later cohorts exhibit weaker or even adverse effects. Coastal regions experience substantial benefits from FTZ policies, in contrast to statistically insignificant outcomes observed in inland areas. These findings suggest that strategically expanding the FTZ network, when paired with tailored implementation mechanisms and the integration of green finance, could serve as a powerful policy tool for post-COVID economic recovery. Importantly, by strengthening economic resilience through institutional openness and green investment, this study offers valuable insights into balancing economic growth with environmental sustainability. It provides empirical evidence to support the optimization of FTZ spatial governance and institutional innovation pathways, thereby contributing to the pursuit of sustainable regional development. Full article

Background/Objectives: Iron deficiency without anaemia (IDNA) is common in non-dialysis-dependent chronic kidney disease (CKD) and contributes to fatigue, reduced exercise tolerance, and impaired quality of life (QoL). While intravenous (IV) iron replacement is known to benefit anaemic patients, its role in IDNA remains uncertain. This study aimed to evaluate the impact of ferric derisomaltose (FDI) on patient-reported QoL outcomes in CKD patients with IDNA. Methods: This was a post hoc analysis of the double-blind, multicentre Iron and the Heart randomised controlled trial. Fifty-four participants with IDNA (ferritin < 100 µg/L or transferrin saturation < 20% and haemoglobin 110–150 g/L) and CKD stages G3b–G5 were randomised 1:1 to receive either 1000 mg FDI (n = 26) or placebo (n = 28). An additional 10 iron-replete CKD patients served as controls. SF-36v2 QoL surveys were collected at baseline, 1 month, and 3 months. Results: SF-36v2 scores declined across all domains, but deterioration was consistently milder in the FDI group. Role physical declined by 3% in the FDI group versus 12% with placebo and 4% in controls. Bodily pain improved by 2.8% with FDI but worsened by 1.5% in the placebo group. Mental health improved by 3.4 points with FDI and declined by 2.7 points in the placebo group, creating a 6.1-point separation. While differences did not reach statistical significance, likely due to small sample size, the consistent trends favour FDI. Conclusions: IV iron may attenuate QoL decline in non-dialysis-dependent CKD patients with IDNA. These findings support the need for larger, adequately powered trials to assess patient-centred outcomes in this population. Full article

Background: Crystalline glucosamine sulfate (cGS) claims to be a stabilized form of glucosamine sulfate with a defined crystalline structure intended to enhance chemical stability. It is proposed to offer pharmacokinetic advantages over regular glucosamine sulfate (rGS) which is stabilized with potassium or sodium chloride. However, comparative human bioavailability data are limited. Since both forms dissociate in gastric fluid into constituent ions, the impact of cGS formulation on absorption remains uncertain. This pilot study aimed to compare the bioavailability of cGS and rGS using a randomized, double-blind, crossover design. Methods: Ten healthy adults received a single 1500 mg oral dose of either cGS or rGS with a 7-day washout between interventions. Capillary blood samples were collected over 24 h. Glucosamine and its metabolite concentrations were quantified by Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS), and pharmacokinetic parameters—including maximum concentration (C_max), time to reach C_max (T_max), and area under the curve (AUC)—were calculated. Results: Mean AUC_0–24, C_max, T_max, and T_½ values for glucosamine and glucosamine-6-sulfate (GlcN-6-S) were comparable between cGS and rGS. Although the AUC_0–24 for glucosamine was modestly higher with rGS (18,300 ng·h/mL) than with cGS (12,900 ng·h/mL), the difference was not statistically significant (p = 0.136). GlcN-6-S exposure was also similar between formulations (rGS: 50,700 ng·h/mL; cGS: 50,600 ng·h/mL), with a geometric mean ratio of 1.39, a delayed T_max (6–8 h) and longer half-life, consistent with its role as a downstream metabolite. N-acetylglucosamine levels remained stable, indicating potential homeostatic regulation. Conclusions: This pilot study found no significant pharmacokinetic advantage of cGS over rGS. These preliminary findings challenge claims of cGS’ pharmacokinetic superiority, although the small sample size limits definitive conclusions. Larger, adequately powered studies are needed to confirm these results. Full article

Energy harvesting systems (EHSs) are widely used to power wireless sensors. Piezoelectric harvesters have the advantage of producing an electric signal directly related to the exciting force and can thus be used to power condition monitoring sensors in dynamically loaded structures such as bridges. The need for such monitoring is exemplified by the fact that the condition of close to 25% of public roadway bridges in, e.g., Germany is not satisfactory. Stack-based piezoelectric energy harvesting systems (pEHSs) installed near bridge bearings could provide information about the traffic and dynamic loads on the one hand and condition-dependent changes in the bridge characteristics on the other. This paper presents an approach to co-optimizing the design of the mechanical and electrical components using a nonlinear solver. Such an approach has not been described in the open literature to the best of the authors’ knowledge. The mechanical excitation is estimated through a finite element simulation, and the electric circuitry is modeled in Simulink to account for the nonlinear characteristics of rectifying diodes. We use real traffic data to create statistical randomized scenarios for the optimization and statistical variation. A main result of this work is that it reveals the strong dependence of the energy output on the interaction between bridge, harvester, and traffic details. A second result is that the methodology yields design criteria for the harvester such that the energy output is maximized. Through the case study of an actual middle-sized bridge in Germany, we demonstrate the feasibility of harvesting a time-averaged power of several milliwatts throughout the day. Comparing the total amount of harvested energy for 1000 randomized traffic scenarios, we demonstrate the suitability of pEHS to power wireless sensor nodes. In addition, we show the potential sensory usability for traffic observation (vehicle frequency, vehicle weight, axle load, etc.). Full article

One of the persistent challenges in multispectral image analysis is the interference caused by dense cloud cover and its resulting shadows, which can significantly obscure surface features. This becomes especially problematic when attempting to monitor surface changes over time using satellite imagery, such as from Landsat-8. In this study, rather than simply masking visual obstructions, we aimed to investigate the role and influence of clouds within the spectral data itself. To achieve this, we employed Independent Component Analysis (ICA), a statistical method capable of decomposing mixed signals into independent source components. By applying ICA to selected Landsat-8 bands and analyzing each component individually, we assessed the extent to which cloud signatures are entangled with surface data. This process revealed that clouds contribute to multiple ICA components simultaneously, indicating their broad spectral influence. With this influence on multiple wavebands, we managed to configure a set of components that could perfectly delineate the extent and location of clouds. Moreover, because Landsat-8 lacks cloud-penetrating wavebands, such as those in the microwave range (e.g., SAR), the surface information beneath dense cloud cover is not captured at all, making it physically impossible for ICA to recover what is not sensed in the first place. Despite these limitations, ICA proved effective in isolating and delineating cloud structures, allowing us to selectively suppress them in reconstructed images. Additionally, the technique successfully highlighted features such as water bodies, vegetation, and color-based land cover differences. These findings suggest that while ICA is a powerful tool for signal separation and cloud-related artifact suppression, its performance is ultimately constrained by the spectral and spatial properties of the input data. Future improvements could be realized by integrating data from complementary sensors—especially those operating in cloud-penetrating wavelengths—or by using higher spectral resolution imagery with narrower bands. Full article