Search Results (2,272)

The Aquila Optimizer (AO), inspired by the hunting behavior of Aquila birds, is a recent nature-inspired metaheuristic algorithm recognized for its simplicity and low computational cost. However, the conventional AO often suffers from premature convergence and an imbalance between exploration and exploitation when applied to complex engineering optimization problems. To overcome these limitations, this study proposes a modified Aquila Optimizer (m-AO) incorporating three enhancement strategies: an adaptive chaotic reverse learning mechanism to improve population diversity, an elite alternative pooling strategy to balance global exploration and local exploitation, and a shifted distribution estimation strategy to accelerate convergence toward promising regions of the search space. The performance of the proposed m-AO is evaluated using 23 classical benchmark functions, IEEE CEC 2022 benchmark problems, and a practical plate–fin heat exchanger (PFHE) design optimization problem. Numerical simulations demonstrate that m-AO achieves faster convergence, higher solution accuracy, and improved robustness compared with the original AO and several state-of-the-art metaheuristic algorithms. In the PFHE application, the proposed method yields a significant improvement in thermal performance, accompanied by a reduction in entropy generation and pressure drop under prescribed design constraints. Statistical analyses further confirm the superiority and stability of the proposed approach. These results indicate that the modified Aquila Optimizer is an effective and reliable tool for solving complex thermal system design optimization problems. Full article

Monkeypox virus (MPXV) is a zoonotic Orthopoxvirus responsible for Monkeypox (Mpox), historically associated with sporadic zoonotic transmission but increasingly characterised by sustained human-to-human spread. While vaccinia-based vaccination is known to confer cross-protection against MPXV, the durability of such immunity over a human lifetime remains incompletely characterised. Here, we assessed humoral and cellular immune responses to MPXV in octogenarians and nonagenarians vaccinated against smallpox during childhood. Twenty-three adults aged 79–94 years (median 83), who self-reported childhood vaccinia vaccination between 1925 and 1940, were recruited. MPXV-specific antibody responses were evaluated using ELISA, targeting homologous vaccinia and MPXV proteins, and live-virus neutralisation assays. Cellular immunity was assessed by IFN-γ ELISpot following stimulation with peptide pools derived from highly conserved vaccinia antigens. Responses were also obtained from younger, recently MVA–BN-vaccinated and unvaccinated control donors. All historically vaccinated participants exhibited MPXV-reactive IgG responses, with antibody binding and neutralisation levels comparable to recently vaccinated individuals. Functional neutralising activity against MPXV was detected in all donors, with ≥50% neutralisation observed in 78% of participants. Antibody concentrations correlated strongly with neutralisation capacity. T-cell responses were detectable in all historically vaccinated donors, most prominently against the major core protein A10L, although reduced magnitudes were observed in participants over 90 years of age. No MPXV-specific humoral or cellular responses were detected in unvaccinated controls. These findings demonstrate that childhood vaccinia vaccination induces durable humoral and cellular immunity against MPXV persisting for over seven decades. Historical smallpox vaccination status may therefore remain a relevant determinant of protection against Mpox. Full article

Classical beamforming (CBF) beamforming constrains the accuracy and quality of underwater acoustic imaging by producing wide main-lobes that reduce resolution, high sidelobes that cause leakage, and point-spread functions that blur targets. Existing approaches typically address only one of these issues at a time, limiting their ability to resolve multiple, interrelated problems simultaneously. In this study, we introduce a double-compression deconvolution high-resolution beamforming method designed to enhance multi-beam sonar imaging using an underwater uniform linear array. The proposed approach formulates imaging as a sparse deconvolution problem and suppresses off-target interference through two sparse constraints, thereby improving the sonar’s resolving capability. During sparse reconstruction, an auxiliary-parameter iterative shrinkage-threshold algorithm is employed to recover azimuthal sparse signals with higher accuracy. Simulations and controlled pool experiments demonstrate that, relative to classical beamforming, the proposed method significantly improves resolution, suppresses off-target interference, expands the imaging intensity dynamic range, and yields clearer target representations. This study provides an effective strategy to mitigate intrinsic limitations in high-resolution underwater sonar imaging. Full article

Intensive agriculture has intensified soil acidification in southern China, threatening crop productivity and ecosystem sustainability. Biochar can neutralize acidity, improve pH buffering, and enhance nutrient retention and microbial habitat in acidic soils. Accordingly, we produced biochars from pruned eucalyptus (ABC), camphora (ZBC), and guava (FBC) branches via pyrolysis at 500 °C. The three biochars were characterized by elemental analysis, Fourier Transform Infrared Spectroscopy (FTIR), and SEM (Scanning Electron Microscopy), and their effects on soil properties, enzyme activities, and bacterial communities were evaluated through a 56-day incubation experiment in an acidified, continuously cropped soil. Physicochemical characterization revealed that ZBC and FBC possessed more oxygen-containing functional groups and greater potential for pH buffering and nutrient release, whereas ABC exhibited higher aromaticity and structural stability. Biochar significantly increased soil pH by 0.62–1.42 units and improved nutrient availability and carbon pools (p < 0.05). Additionally, 4% ZBC increased urease and sucrase activities by 21.54% and 79.34%, respectively, while 2% FBC increased cellulase activity by 25.99%. High-throughput sequencing identified Acidobacteria and Proteobacteria as the dominant phyla; ZBC and FBC at 0.5% and 2% significantly increased Shannon and Chao1 indices. Redundancy analysis indicated that available potassium, pH, soil organic carbon, urease, sucrase, and cellulase were the primary drivers of bacterial community variation and positively associated with carbon-cycling phyla. These findings demonstrate that feedstock-specific biochar properties critically regulate soil biogeochemical processes, offering a sustainable strategy to remediate acidified soils and valorize agroforestry residues. Full article

Background/Objectives: With the rising incidence of obesity-related endometrial cancer, there is renewed interest in physiologic, low-cost approaches to identify women with hormonally active endometrium who may benefit from early preventive interventions. The progesterone challenge test (PCT), an established clinical tool for evaluating amenorrhea, has been previously proposed as a method to detect endometrial pathology. This study systematically evaluated the diagnostic accuracy of the PCT for detecting endometrial hyperplasia, intraepithelial neoplasia, and carcinoma in asymptomatic postmenopausal women to determine its potential role as a physiologic marker of endometrial cancer risk. Methods: A systematic review and meta-analysis were conducted following PRISMA-DTA guidelines. MEDLINE, EMBASE, EBM Reviews, and CINAHL were searched from inception to 20 January 2025, along with ClinicalTrials.gov and grey literature. Eligible studies prospectively evaluated the PCT with endometrial biopsy as the reference standard. Data extraction and risk-of-bias assessment were performed in duplicate. Risk of bias was assessed using QUADAS-2. Pooled sensitivity, specificity, and predictive values were estimated using hierarchical summary receiver operating characteristic models. Results: Nineteen studies (n = 3902) met the inclusion criteria. The pooled sensitivity and specificity of the PCT for detecting endometrial pathology were 95% (95% CI 86–100%) and 87% (76–96%), respectively. The positive predictive value was 32% (95% CI, 16–50%) and the negative predictive value was 100% (100–100%). When endometrial proliferation was included in the target condition, sensitivity decreased to 82%, but positive predictive value increased to 70%. Conclusions: The PCT shows high diagnostic accuracy for identifying estrogen-driven endometrial pathology in asymptomatic postmenopausal women. Re-evaluating this simple, physiologic test as a functional risk-stratification tool could inform precision prevention strategies for endometrial cancer. Full article

Background: Food insecurity may adversely affect cognitive function through pathways involving nutritional deficiencies, chronic stress, and comorbid health conditions, with potentially different effects across cognitive domains. Longitudinal evidence remains limited by time-varying confounding, and it is unclear whether Supplemental Food Assistance Program (SNAP) participation modifies these associations. Objectives: To examine the longitudinal association between food insecurity and cognitive function using marginal structural models (MSMs), and whether SNAP participation buffers these associations for overall cognition, episodic memory, and attention/mental processing. Methods: 30,641 adults aged ≥50 in the 1998–2020 Health and Retirement Study (HRS) contributed 156,066 person-year observations. MSMs with stabilized inverse probability of treatment weights were used to account for time-varying socioeconomic, health, and cognitive confounding affected by prior exposure. Weighted pooled linear regression models estimated marginal associations and interaction effects. Results: Moderate and high food insecurity were associated with lower overall cognition (b = −0.36 and −0.71, respectively; p < 0.001). Similar graded associations were observed for episodic memory (b = −0.22; −0.43) and attention/mental processing (b = −0.15; −0.28; all p < 0.001). SNAP participation significantly attenuated these associations across cognitive domains, with stronger buffering effects among non-Hispanic Black and Hispanic respondents. Effect sizes corresponded to differences equivalent to several years of cognitive aging. Conclusions: Food insecurity is associated with poorer cognitive function across multiple domains, while SNAP participation mitigates these associations. Despite limitations of observational data, these findings highlight the methodological value of MSMs and the potential role of food assistance programs in reducing cognitive health disparities in later life. Full article

Biochar is known to enhance soil potassium (K) availability and promote plant K uptake; however, its influence on the transformation pathways of fertilizer potassium and the mechanisms regulating crop potassium accumulation remains insufficiently understood. This study conducted a pot experiment using three soil types—Albic, Brown, and Sandy soils—with different biochar application rates (0, 10, and 20 g·kg⁻¹) in combination with potassium fertilizer, to systematically evaluate the regulation of soil K forms, K fertilizer transformation rates, K use efficiency, and K uptake and accumulation in soybeans. The results demonstrated that the combined application of biochar and K fertilizer significantly increased the contents of available, water-soluble, exchangeable, and non-exchangeable K across all three soils. At the highest biochar application rate (20 g·kg⁻¹), available K increased by 15.37%, 16.78%, and 11.77% in the Albic, Sandy, and Brown soils, respectively, compared to the control. Furthermore, biochar altered the transformation pathways of fertilizer K; it consistently reduced the conversion rate of fertilizer K into exchangeable K across all soils, redirecting it toward the water-soluble and non-exchangeable K pools, thus functioning as a potassium “scheduling center”. Adsorption–desorption experiments revealed that biochar exhibits a strong multilayer adsorption capacity for K ions, with most of the adsorbed K not easily desorbed, providing mechanistic support for the observed shift in transformation pathways. In terms of K use efficiency, biochar reduced the K of agronomic efficiency (KAE) due to a “dilution effect” from its inherent K content. Under the high application rate (20 g·kg⁻¹), the KAE decreased by 11.79% in Albic soil, 88.48% in Sandy soil, and 71.73% in Brown soil, while significantly increasing the partial factor productivity of K (PFPK) and apparent recovery efficiency of K (AREK). Ultimately, the co-application of biochar and K fertilizer significantly enhanced total K accumulation and seed yield in soybeans by increasing K concentrations in various plant parts and promoting dry matter accumulation. At the biochar application rate of 20 g·kg⁻¹, the potassium accumulation and soybean yield under biochar treatment reached maximum increases of 70.77% (in Brown soil) and 42.63% (in Albic soil), respectively. This study demonstrates that biochar can synergistically reduce potassium (K) leaching and improve fertilizer use efficiency by regulating K transformation pathways. This provides a practical guideline for utilizing biochar as a dual-function amendment, which acts as both a supplemental K source and a soil conditioner, thereby supporting the development of more sustainable potassium management practices in diverse cropping systems. Full article

Preeclampsia (PE) is a serious pregnancy complication characterized by hypertension and organ dysfunction. Its pathogenesis involves impaired trophoblast invasion and inadequate spiral artery remodeling; however, the underlying molecular mechanisms remain unclear. This study investigated the role of arylacetamide deacetylase (AADAC) in PE and its effects on trophoblast function by analyzing placental tissues from 30 patients with PE and 15 controls. Exploratory RNA sequencing was performed on pooled placental samples from six patients with severe PE and six controls, and AADAC expression was validated by semi-quantitative PCR and Western blotting. HTR8/SVneo cells were exposed to cobalt chloride (CoCl₂) under hypoxia-mimicking conditions, and AADAC expression was manipulated by siRNA-mediated knockdown (KD) and overexpression (OE). RNA sequencing revealed increased AADAC expression in PE placentas (fold change > 2.0, raw p < 0.05). Although AADAC mRNA levels were elevated in PE tissues, protein levels were reduced. CoCl₂ exposure was associated with increased expression of AADAC and hypoxia-inducible factor-1 alpha (HIF-1α). Under hypoxia-mimicking conditions, AADAC silencing was associated with increased trophoblast invasion and tube formation, whereas AADAC overexpression reduced tube formation without significantly affecting invasion. These findings suggest that dysregulated, hypoxia-responsive AADAC expression influences trophoblast invasive and angiogenic behavior in preeclampsia. Full article

The proliferation of smart devices and the Internet of Things (IoT) has led to massive data generation, particularly in complex domains such as aerospace. Cloud computing provides essential scalability and advanced analytics for processing these vast datasets. However, relying solely on the cloud introduces significant challenges, including high latency, network congestion, and substantial bandwidth costs, which are critical for real-time on-orbit spacecraft services. Cloud-edge Internet of Things (cloud-edge IoT) computing emerges as a promising architecture to mitigate these issues by pushing computation closer to the data source. This paper proposes an improved YOLOV8-based model specifically designed for edge computing scenarios within a cloud-edge IoT framework. By integrating the Cross Stage Partial Spatial Pyramid Pooling Fast (CSPPF) module and the WDIOU loss function, the model achieves enhanced feature extraction and localization accuracy without significantly increasing computational cost, making it suitable for deployment on resource-constrained edge devices. Meanwhile, by processing image data locally at the edge and transmitting only the compact segmentation results to the cloud, the system effectively reduces bandwidth usage and supports efficient cloud-edge collaboration in IoT-based spacecraft monitoring systems. Experimental results show that, compared to the original YOLOV8 and other mainstream models, the proposed model demonstrates superior accuracy and instance segmentation performance at the edge, validating its practicality in cloud-edge IoT environments. Full article

We present a simplified phenomenological computational framework that integrates the GABA shunt into established metabolic mechanisms underlying pancreatic beta cell insulin secretion. The GABA shunt introduces carbon into the tricarboxylic acid (TCA) cycle via succinate, thereby functioning as an anaplerotic pathway. This anaplerotic input is coupled to oscillatory cataplerotic fluxes, primarily involving α-ketoglutarate, whose effective extrusion requires coordinated counter-fluxes of malate and aspartate. Within the model, these cataplerotic exchanges are facilitated by UCP2-mediated transport processes and necessitate complementary anaplerotic replenishment through pyruvate carboxylase (PC). Based on this functional interdependence, we introduce the Dual Anaplerotic Model (DAM), which conceptually links two anaplerotic routes—the GABA shunt-mediated pathway and the glucose-dependent PC pathway—into a unified metabolic response module. DAM describes a coordinated, breathing-like redistribution of carbon between mitochondrial and cytosolic metabolite pools, while efficient oxidative metabolism of glucose-derived carbon entering the TCA cycle via pyruvate dehydrogenase is maintained. The model is driven by experimentally observed ATP/ADP and Ca²⁺ dynamics and is not intended to generate autonomous oscillations. Instead, it enables qualitative, phase-dependent visualization of how dual anaplerotic fluxes constrain and shape oscillatory metabolic states in beta cells. DAM provides an integrative conceptual scaffold for interpreting experimental observations and for motivating future quantitative modeling and experimental studies addressing metabolic regulation in physiological and pathophysiological contexts. Full article

Aiming at issues such as reactive power distribution fluctuations and insufficient local support caused by large-scale integration of renewable energy in new power systems, as well as the poor adaptability of traditional methods and bottlenecks of deep reinforcement learning in complex power grids, a two-stage intelligent optimization method for grid reactive power based on dynamic voltage partitioning is proposed. Firstly, a comprehensive indicator system covering modularity, regulation capability, and membership degree is constructed. Adaptive MOPSO is employed to optimize K-means clustering centers, achieving dynamic grid partitioning and decoupling large-scale optimization problems. Secondly, a Markov Decision Process model is established for each partition, incorporating a penalty mechanism for safety constraint violations into the reward function. The DDPG algorithm is improved through multi-experience pool probabilistic replay and sampling mechanisms to enhance agent training. Finally, an optimal reactive power regulation scheme is obtained through two-stage collaborative optimization. Simulation case studies demonstrate that this method effectively reduces solution complexity, accelerates convergence, accurately addresses reactive power dynamic distribution and local support deficiencies, and ensures voltage security and optimal grid losses. Full article

Background: Postpartum haemorrhage (PPH) remains the leading cause of maternal mortality globally. Women with inherited or unexplained bleeding disorders such as von Willebrand disease (VWD), factor XI deficiency (FXI), platelet function disorders, or bleeding disorder of unknown cause (BDUC) face a higher risk. While tranexamic acid (TXA) is routinely used in obstetric care, its specific efficacy and safety in these populations remain unclear. Methods: A systematic review and meta-analysis followed PRISMA 2020 guidelines (PROSPERO: CRD420251082349). Databases searched included PubMed, Scopus, Web of Science, and Dimensions. Studies evaluating TXA for PPH prevention or treatment in women with bleeding disorders were included. Six cohort studies (2016–2024) involving 213 deliveries met the criteria. Three contributed to a meta-analysis on primary PPH; the other three were synthesised narratively. Results: TXA use was associated with a 56% reduction in primary PPH risk (risk ratio 0.44; 95% CI: 0.27–0.70; p = 0.0007), with no observed heterogeneity (I² = 0%). Because contributing cohorts were phenotypically heterogeneous (BDUC, FXI, mixed), the pooled effect reflects an average across disorders rather than disorder-specific efficacy. TXA also appeared to reduce secondary and severe PPH in some cohorts. However, bleeding occurred in 26–36% of high-risk deliveries despite prophylaxis. No maternal deaths or thromboembolic events were reported in 136 TXA-exposed cases. Attribution was complicated by concurrent use of desmopressin and platelet transfusions. Most studies had moderate to severe bias. Conclusions: TXA significantly lowers the risk of primary PPH in women with bleeding disorders and appears safe. Despite this, residual bleeding underscores the need for trials to optimise TXA use alongside disease-specific strategies. However, this conclusion is derived from only six observational studies with heterogeneous patient populations and co-interventions. The evidence remains preliminary and should be interpreted cautiously. TXA should be considered as part of a multimodal postpartum haemorrhage management algorithm rather than a stand-alone therapy. Full article

Background/Objectives: Functional dyspepsia (FD) is a gastrointestinal disorder typically treated by changes in diet and lifestyle. However, in the Colombian population, few studies have addressed its etiology and diagnosis. This exploratory study aimed to identify predictive variables associated with the presence of dyspeptic symptoms (DS). Methods: To address this, a self-survey was conducted evaluating sociodemographic characteristics, clinical history, and dietary habits. A DS index was calculated using participant’s clinical history to explore the characteristics of the groups with more and less DS (MDS and LDS groups). Additionally, a regression model was applied to identify the predictors of higher DS scores. Pooled data from the rolling, cross-sectional eating habits and DS survey between May and July of 2024. We enrolled 102 Colombian participants between 18 and 65 years old. Results: Significant differences were identified between MDS and LDS groups in occupation and dietary habits, with students exhibiting a higher DS index. Moreover, MDS exhibited greater consumption of fatty and fried foods than LDS groups. Regression analysis revealed that high intake of fatty foods and sesame were the best predictors of higher DS index. In contrast, the consumption of Saccharomyces boulardii probiotic and white onion was associated with better gastrointestinal health. Conclusions: Changes in dietary habits are associated with lower DS; the effect and its etiology might also depend on the participants’ occupation and nutritional habits. Full article

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss; anti-vascular endothelial growth factor (anti-VEGF) therapy is standard care for neovascular AMD (nAMD), yet treatment response varies. We systematically reviewed and meta-analyzed artificial intelligence (AI) and machine learning (ML) models using optical coherence tomography (OCT)-derived information to predict anti-VEGF treatment response in nAMD. PubMed, Embase, Web of Science, and IEEE Xplore were searched from inception to 18 December 2025 for eligible studies reporting threshold-based performance. Two reviewers screened studies, extracted data, and assessed risk of bias using PROBAST+AI; pooled sensitivity and specificity were estimated with a bivariate random-effects model. Seven studies met inclusion criteria, and six were synthesized quantitatively. Pooled sensitivity was 0.79 (95% CI 0.68–0.87), and pooled specificity was 0.83 (95% CI 0.62–0.94), with substantial heterogeneity. Specificity tended to be higher for long-term and functional outcomes than for short-term and anatomical outcomes. Most studies had a high risk of bias, mainly due to limited external validation and incomplete reporting. OCT-based AI models may help stratify treatment response in nAMD, but prospective, multicenter validation and standardized outcome definitions are needed before routine use; current evidence shows no consistent advantage of deep learning over engineered radiomic features. Full article

Background: Quantitative flow ratio (QFR) is a novel technology to assess the functional significance of coronary stenoses based on standard coronary angiography, which can be alternatives to invasive fractional flow reserve (FFR) assessment. However, the evidence is limited to single-center studies and small sample sizes. This study systematically determined the diagnostic performance of QFR to diagnose functionally significant stenosis with FFR as the reference standard. Methods: A systematic review and meta-analysis of studies assessing the diagnostic performance of angiography-derived QFR systems were performed. All relevant studies from six literature databases were searched and screened according to the inclusion and exclusion criteria. The pooled sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR−), and diagnostic odds ratio (DOR), along with their 95% confidence intervals (CIs), were calculated using DerSimonian–Laird methodology. The summary receiver operating characteristic (SROC) curve and area under the curve were estimated. Meta-regression analysis was performed to identify a potential source of heterogeneity. Results: Fifty-seven studies comprising 13,215 patients and 16,125 vessels were included in the final analysis. At the vessel level, the pooled sensitivity and specificity of QFR for detecting a significant coronary stenosis were 0.826 (95% CI: 0.798–0.851) and 0.919 (95% CI: 0.902–0.933). Pooled LR+ and LR− were 10.198 (95% CI: 8.469–12.281) and 0.189 (95% CI: 0.163–0.219), with a pooled DOR of 53.968 (95% CI: 42.888–67.910). The SROC revealed an area under the curve (AUC) of 0.94 (95% CI: 0.91–0.96). The summary AUCs were 0.90 (95% CI: 0.87–0.92) for fixed-flow QFR (fQFR), 0.95 (95% CI: 0.92–0.96) for contrast-flow QFR (cQFR), 0.97 (95% CI: 0.95–0.98) for Murray law-based QFR (μQFR), and 0.91 (95% CI: 0.89–0.94) for non-specified QFR. The adjusted pooled DORs were as follows: 126.25 for μQFR, 45.49 for cQFR, 26.12 for adenosine-flow QFR (aQFR), 25.88 for fQFR, and 36.54 for non-specified QFR. Conclusions: The accuracy of angiography-derived QFR was strong to assess the functional significance of coronary stenoses with FFR as a reference. μQFR demonstrated the highest diagnostic performance among the five evaluated modes. Full article