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Impact of two different hesperidin forms loaded on nanoscale modified borate bioglass scaffolds on rat critical-sized calvarial defects

Abstract Bone defects remain a major clinical challenge because of their limited self-healing capacity. This study aimed primarily to evaluate whether nanoscale modified borate bioglass scaffolds (MBBGS) could enhance the delivery of hesperidin (HPN), an antioxidant flavonoid, to bone defects, and secondarily to compare the osteogenic effects of micro- and nano-sized HPN (mHPN and nHPN) on bone regeneration. Scaffolds were fabricated and fully characterized. Fifty-six healthy male albino rats were anesthetized, and bilateral critical-sized calvarial defects were created. The rats were divided into four groups: control (empty defects), MBBGS alone, MBBGS loaded with mHPN, and MBBGS loaded with nHPN. The animals were euthanized at the end of the 2nd and 6th weeks postoperatively. The skulls were harvested and processed for radiological, histological, and immunohistochemical analyses. Radiographic evaluation showed progressive defect closure over time, with the greatest reduction in defect size observed in the MBBGS + nHPN group compared to the other groups. Histologically, the MBBGS + nHPN group revealed the greatest osteogenic impact and significantly increased osteopontin (OPN) immunoreactivity, followed by MBBGS + mHPN and MBBGS groups, while the control group exhibited minimal bone healing and weak OPN reactivity. In conclusion, the newly fabricated MBBGS effectively promoted calvarial bone regeneration, which was further enhanced by loading with nHPN.

Overweight and obesity association with mortality in patients with heart failure and reduced or preserved ejection fraction-a cohort study

Background Obesity is a risk factor for incident heart failure, but patients with excess weight and heart failure have lower mortality. This “obesity paradox” may be explained either by a favourable effect of the adipose tissue or by confounding. We aimed to assess if body mass index (BMI) is associated with lower mortality after extensive adjustment for prognostic factors in patients with reduced (HFrEF) or preserved (HFpEF) ejection fraction. Methods Prospective, observational study including consecutive patients hospitalized for acute heart failure. Two years hazard of mortality was assessed in a multivariable Cox model, in the whole population and separately for HFrEF and HFpEF. Results Among 957 included patients (mean age 76 years, 41% women), 500 (47%) had HFrEF and 443 (53%) HFpEF. Four hundred (39%) were in the normoweight, 301(30%) in the overweight, and 256(25%) in the obese category (Class I obesity:144 patients; class II or III: 112). Corresponding mortality was 37%, 26% and 22%. Unadjusted hazard ratio (HR) for mortality was 0.96 (95% CI 0.94–0.98) for each BMI point in the whole population, 0.97 (95% CI 0.94–1.02) in patients with HFrEF, and 0.94 (95% CI 0.92–0.97) in HFpEF. After adjustment for age, sex, atrial fibrillation, diabetes, chronic obstructive pulmonary disease, chronic anaemia, hypertension, glomerular filtration rate, and NT-proBNP, HR was 1.00 (95% CI 0.96–1.02) in the whole population, 1.02 (0.96–1.07) in HFrEF, and 0.98 (95% CI 0.94–1.01) in HFpEF. Conclusions Excess weight was associated with an apparent survival benefit in patients with acute heart failure, particularly in patients with HFpEF. This advantage disappeared completely after adjustment for confounding factors including NT-proBNP. The obesity paradox can be completely explained by differences in demographics, co-morbidities, and severity of heart failure.

Effects of icon semantic distance and cultural background on visual search efficiency in vehicle control interfaces

Path planning for UAVs in complex terrain based on the PGD model: Algorithmic improvements combining feature extraction and reinforcement learning

This paper proposes the PGD model for UAV path planning in complex terrain, addressing key challenges such as high-dimensional state processing, blind path exploration, and poor cross-scene adaptability. The PGD model integrates Transformer, GAN, and DDPG, forming a “compression-generation-optimization" closed-loop system. The Transformer module compresses high-dimensional terrain data, alleviating training bottlenecks, while the GAN module generates high-quality candidate paths, reducing ineffective exploration. DDPG then optimizes the path planning strategy efficiently. Experimental results demonstrate the superior performance of PGD on the UAVDT (suburban) and AirSim (canyon) datasets. In terms of path length ( P l ), PGD achieves 20.0m/22.0m, compared to baseline models such as PPO-DRL (23.8m) and Soft Actor-Critic (24.0m). PGD also outperforms in collision rate ( C r ) with 2.5%/3.0% and computational efficiency ( T c ) with 13.5s/16.0s, respectively. The PGD model shows significant improvements in path planning efficiency and adaptability, particularly in high-complexity terrains. Compared to traditional models, PGD’s multi-module synergy enhances feature correlation and physical path constraints, offering a novel framework for intelligent planning in complex environments. Future work will focus on enhancing model adaptability to extreme weather and multi-agent collaborative scenarios.

XGBoost based surrogate technique for system reliability analysis of foundation over cavity aided with bootstrapping

Exploring phonological complexity in statistical learning of artificial words

Purpose This study examined whether phonological complexity enhances auditory word learning within a statistical learning framework. Specifically, we tested if exposure to phonologically complex speech patterns (i.e., marked consonant clusters) facilitates the segmentation and generalization of both complex and simple artificial words. Method Seventy-eight adults were randomly assigned to either a complex or simple pattern induction group and exposed to bisyllabic artificial words varying in onset complexity. Participants then heard an auditory stream containing both complex and simple words, followed by a wordlikeness rating task assessing both previously heard and novel items. Results Exposure to complex speech patterns did not enhance wordlikeness ratings for either previously heard (stream) or novel (generalization) artificial words. Wordlikeness ratings were significantly higher for stream items than for generalization items, indicating sensitivity to exposure, but no reliable effects of induction condition or stimulus complexity were observed. Conclusions Findings suggest that passive exposure to complex patterns does not enhance generalization within a statistical learning paradigm.

Enhancing start-up and torque in Darrieus VAWTs through a novel plain gurney flap design

Abstract Enhancing aerodynamic efficiency and self-starting torque in Darrieus-type Vertical Axis Wind Turbines (VAWTs) is essential for power generation under low and intermittent wind conditions. This study presents a systematic evaluation of Plain Flap (PF), Gurney Flap (GF), and hybrid Plain Gurney Flap (PGF) modifications applied to the NACA 0015 aerofoil. Two-dimensional Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulations using the SST k-ω model were conducted across a tip-speed-ratio (TSR) range of 0.2–4.5 and Reynolds numbers ((Re = 5.4 × 10 4 –2.7 × 10 5 ), with results validated by prototype testing. The optimal 0.5c, 10° PF configuration demonstrated the most robust and stable performance across the full operational range. At low TSR (0.2–0.5), the PF significantly improved mean Cm by 30–40% and Cp by 40% by increasing effective camber. While the 0.015c PGF generated higher instantaneous torque, it incurred larger downwind losses. At moderate TSR (0.8–1.5), PF and PGF achieved similar high Cp gains (40–50%). Beyond TSR = 2.0, the PF maintained superior aerodynamic stability and consistent efficiency, whereas the PGF performance declined due to drag penalties. Prototype testing conclusively confirmed these numerical trends, with PF blades increasing shaft speed by up to 51% at 5.5 m/s compared to the baseline. Overall, PF and PGF configurations effectively mitigate weak self-starting and low efficiency, providing a validated passive-flap design pathway for efficient small-scale and hybrid solar-wind energy systems.

Soil environment effects on the occurrence of black sesame spot and clubroot disease in Chinese Cabbage

Chinese cabbage is a popular leafy vegetable widely consumed in Asian cuisine, particularly in China. However, it is susceptible to various diseases, including clubroot and black sesame spot, which can significantly impact yield and quality. The soil environment plays a crucial role in developing these two diseases. In our experiment, we measured eight soil indicators-soil pH, organic matter, alkali-hydrolyzable nitrogen, available phosphorus, rapidly available potassium, total salinity, total nitrogen, and slowly available potassium-across 38 cabbage-growing locations in Jiaozhou County, China. We compared the soil environments of disease-infested and non-infested sites. Our results indicated that no significant association was found between the measured soil variables and observed clubroot incidence. However, there is a significant association between acidic soils with low available phosphorus and a higher incidence of black sesame spot. Overall, our study provides a comprehensive understanding of how the soil environment affects the occurrence of clubroot and black sesame spot, offering valuable insights for the integrated management of these challenging cabbage diseases.

Mitigating drought stress in bitter gourd (Momordica charantia L.) through foliar application of potassium, zinc, calcium, and silicon

An intelligent control algorithm for gas precise drainage problem based on Model Predictive Control

Intelligent extraction of coal seam gas constitutes a crucial development direction for managing underground gas disasters. Building on an established mathematical model, this study develops an intelligent control model for gas extraction. In this model, controlled variables include gas extraction concentration, gas extraction flow rate, negative pressure, and extraction pump efficiency ratio, while control variables are defined as the valve opening of extraction boreholes and the power of extraction pumps. The ideal curve of the controlled quantity with time is obtained by using the recurrent neural network (SimpleRNN), and the controlled quantity is intelligently controlled by the model predictive control (MPC) algorithm so that the actual value of controlled quantity approaches the reference value at the corresponding time of its ideal curve. Taking the simulated gas extraction data as an example, an algorithm simulation experiment is performed. The experimental results show that the ideal reference curve of the controlled quantity obtained by the cyclic neural network has a good data fitting degree. The dynamic control of the controlled quantity by the model predictive control algorithm can overcome the interference of environmental and nonlinear factors and achieve a better control effect, which provides a certain reference for the intelligent control of gas drainage.

A linear programming model for power system planning with hydrogen integration

Impact of African swine fever emergency on the mental health of first responders in the Dominican Republic

African swine fever (ASF) has become a global pandemic, affecting nearly 2 million pigs since 2022 alone and causing significant disruption to food security and trade. The Dominican Republic (DR) has been affected by ASF since 2021. Veterinarians are key first responders in animal health emergencies and at risk for negative impacts from prolonged emergency response. We used mixed methods and network analysis to characterize the mental and social impacts of ASF on 29 DR swine veterinarians. All 29 veterinarians were involved with the ASF response through field-based or non-field-based roles. Responses were gathered via a questionnaire and analyzed using network analysis. Preliminary quantitative results were explored further through qualitative focus group interviews. Veterinarians experienced high levels of anger and hopelessness from the ASF epidemic, which were centrally located variables in the network. They were associated with a perceived lack of communication, trust, and transparency between government authorities, veterinarians, and farmers. The impact that animal diseases have on the mental health of veterinarians is often neglected. As animal, human, and zoonotic diseases, such as ASF and avian influenza, continue to emerge and expand, these results bring attention to the need for considering actions to prevent and mitigate their impact on the mental health of first responders and, ultimately, improve the effectiveness of the response.

Mechanisms of FOXK1-regulated glycolipid metabolism in mediating TOX-induced histone lactylation to promote CD8⁺ T cell exhaustion in high-grade serous ovarian cancer

Recovery-induced tipping in Stommel’s kicked ocean box model

Ocean circulation, a key driver of global climate, is subject to recurrent disturbances including freshwater input from glacial melt. Stommel’s idealized two-box model predicts two distinct stable regimes of thermohaline ocean circulation and offers a conceptual framework in which to explore the effects of salinity perturbations. A study that superimposed discrete salinity kicks onto the flow of the otherwise continuous model revealed a counterintuitive phenomenon: extending the recovery period between salinity kicks caused a trajectory to tip into an alternative basin of attraction. Here we analyze the recovery-induced tipping phenomenon in Stommel’s kicked model across a broader swath of disturbance parameters, finding that the phenomenon is robust across a significant set of kick sizes. Furthermore, bifurcation analysis of flow-kick fixed points reveals that recovery-induced tipping stems from an alternative attractor migrating across an original separatrix as flow times vary. This migration also occurs in a continuous analog of salinity perturbation. Although the recovery times associated with seasonal or decadal freshwater influxes far exceed those associated with recovery-induced tipping, the qualitative dynamics we uncover in Stommel’s perturbed model alert us that similar phenomena may occur in other models and real-world systems.

Smart CaCO3-coated probiotics relieve constipation by enhancing intestinal motility and modulating microbial enzymes in a loperamide-induced rat model

Assessing the validity of post-discharge readmission and mortality as a composite outcome among newborns in Uganda

Background Composite outcomes, which include mortality and readmission rates, are often used in risk prediction models following hospital discharge when event rates for the primary outcome of interest, mortality, are low. However, greater readmission rates may result in reduced mortality making interpretation of the composite outcome difficult. We assess the usefulness of a composite outcome of post-discharge readmission and mortality as a target outcome in this context. Methods This was a secondary analysis of data collected among mothers and their newborn(s) admitted for delivery at two regional referral hospitals in Uganda. Six-week post-discharge mortality (all-cause) and readmission in newborn infants were analyzed using a competing risk framework. The Sub distribution Hazard Ratios (SHRs) were compared across predictor variables to examine the relationship between the two outcomes. Results A total of 6040 newborns with complete six-week follow-up were enrolled, of whom 50.6% were male and 64% of mothers delivered via caesarean section. Thirty-five (0.58%) infants died within the six-week follow-up period and 241 (3.99%) were readmitted. Of the 206 predictors, 81 had a consistent association with both outcomes. These include a higher weight (SHRs: 0.14, 0.68) and length of the baby (SHRs: 0.85, 0.91). However, 125 variables depicted an association in opposing directions which may be linked to social and financial barriers to care-seeking. These include a travel time to the hospital of greater than 1 hour (SHRs: 1.4, 0.28). Conclusion While mortality is unequivocally a negative outcome, readmission may be a positive outcome, reflecting health seeking, or a negative outcome, reflecting recurrent illness. This directional dichotomy is reflected to varying degrees within different variables. When using a composite outcome for a prediction model, caution should be exercised to ensure that the model identifies individuals at risk of the intended outcomes of interest, rather than merely the proxies used to represent those outcomes. Identifying predictors with a consistent relationship for both outcomes may yield a more optimized and less biased prediction model for use in clinical care.

Evaluation of mineral composition and in-vitro nutrient digestibility of macrophytes to assess their potential as sustainable animal feed

The key technologies of a computer-aided design system for removable partial denture frameworks

This paper presents a computer-aided design (CAD) system for removable partial denture (RPD) frameworks, addressing the challenges of dentition defects. The system takes a digitized dental model obtained via optical scanning as input and generates an RPD framework model ready for 3D printing. Key technologies include spline curve editing and modeling, mesh offsetting, texture image-based modeling, and component models fusion. The system utilizes conformal mapping between the dental model and a disk. This enables spline curve editing to be executed in the parameterized 2D domain, ensuring both accuracy and efficiency. An iterative approximation method with adaptive mesh simplification is introduced to achieve precise mesh offsetting while avoiding self-intersections. Furthermore, texture mapping enables interactive modeling of holes for denture base connectors and 3D branch-like wax patterns for major connectors. An enhanced Boolean algorithm, combined with smoothing and simplifying techniques for intersecting regions, is utilized to ensure seamless and natural integration of various components. Clinical evaluations demonstrate that the system achieves a performance level comparable to advanced commercial CAD systems, having successfully completed over 30,000 clinical designs with high reliability and meeting all required standards.

Preoperative radiomics models for predicting risks of distinct recurrence patterns in pancreatic ductal adenocarcinoma based on contrast enhanced CT

Genomic characterization and prognostic significance of copy number alterations in Tunisian patients with acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is a heterogeneous malignancy characterized by various genomic alterations playing a crucial role in disease classification, prognosis, and response to treatment. However, molecular diagnosis and effective management of this hematological malignancy remain a major challenge, particularly in developing countries, including Tunisia. In this study, we aimed to conduct a detailed analysis of copy number alterations (CNAs) associated with ALL in a cohort of 60 primary samples from Tunisian patients. Using multiplex ligation-dependent probe amplification (MLPA), major genetic lesions, including IKZF1 , CDKN2A/2B , PAX5 , ETV6 , BTG1, and genes located in the PAR1 region, were analyzed and their associations with clinical and laboratory features, as well as survival outcomes, were also evaluated. Our analysis revealed that 70% of patients had deletions and/or amplifications in at least one gene. The most frequently observed deletions were in CDKN2A/2B (33.3%, n = 20), IKZF1 (30%, n = 18), and PAX5 genes (25%, n = 15). BTG1 deletions were significantly associated with female gender, IKZF1 deletions were more frequent in adult patients, in those with elevated white blood cell (WBC) counts, and in cases involving the BCR::ABL1 translocation, while duplications of the PAR1 region were significantly associated with hyperdiploïdy. Regarding treatment response, cases of IKZF1 deletions showed a significant association with poor glucocorticoid response (GC) at day 8 of treatment and positive minimal residual disease (MRD) rates at days 33 and 63, particularly in B-ALL cases. Furthermore, patients with IKZF1 deletions were associated with significantly lower survival rates in both univariate and multivariate analyses compared to those without these deletions. Additionally, the integration of IKZF1 deletion status into risk stratification models revealed markedly different survival outcomes, highlighting its potential interest in developing new stratification algorithms. These results underscore the critical importance of molecular profiling, particularly IKZF1 status, for improving outcomes in ALL patients in Tunisia.