Browse Articles

Stability analysis of a multistep method for excavating high spoiled slopes on the Guigu expressway: a case study

GDNF overexpression in astrocytes enhances branching and partially preserves hippocampal function in an Alzheimer’s rat model

Abstract Astrocytes are essential for maintaining neuronal health and regulating the brain’s inflammatory environment. In this study, we developed an adeno-associated viral vector (AAV9) designed to selectively overexpress glial cell line-derived neurotrophic factor (GDNF) in astrocytes, using the astrocyte-specific GFAP promoter and TdTomato for transduction tracking. This approach yielded targeted GDNF expression in hippocampal astrocytes. Sholl analysis revealed that GDNF overexpression significantly enhanced astrocytic branching complexity and process length. Using the intracerebroventricular streptozotocin (STZ) model of neurodegeneration, we evaluated the impact of GDNF on astrocytic morphology, neuroinflammation, and hippocampal-dependent memory. Although GDNF prevented astrocytic process length reduction, it did not mitigate neuroinflammation, as evidenced by persistent microglial activation, nor did it improve deficits in the novel object recognition task. However, GDNF + STZ treated animals performed similarly as SHAM controls at exploring the goal sector at the Barnes Maze. These findings demonstrate the capacity of the AAV-GFAP-GDNF-TdTom construct to induce astrocytic branching and partially preserve memory function. They also underscore its partial therapeutic potential in a neuroinflammatory, metabolically compromised and neurodegenerative context.

Integrating microwave-assisted green synthesis, DFT simulations, and biological activity evaluation of copper-doped zinc oxide nanoparticles

Dietary vitamin K intake associates with reduced all-cause mortality in non-alcoholic fatty liver disease patients

The usage of a transformer based and artificial intelligence driven multidimensional feedback system in english writing instruction

Effect of laser remelting and ultrasonic irradiation on crack suppression and properties of Ni-WC laser cladding layer

Parameter extraction of PV models under varying meteorological conditions using a modified electric eel foraging optimization algorithm

Abstract The dependence on photovoltaic (PV) solar systems has increased dramatically to cover the increasing progress of world energy demand. Therefore, accurately specifying the parameters of PV modules is essential for evaluating the behavior and impact of integrating PV systems into electrical systems. In this context, a modified electric eel foraging optimization (MEEFO) is suggested for determining the parameters of solar PV modules. The proposed technique incorporates three improvement strategies: the fitness distance balance (FDB) strategy, fractional-order calculus (FOC), and quasiopposition-based learning (QOBL). These strategies enhance both exploitation and exploration capabilities while helping to prevent local optimization and premature convergence commonly observed in traditional EEFO. First, the proposed MEEFO is evaluated via two benchmark functions, including the basic and CEC 2019 benchmark functions. The results are then compared with those of other novel methods in terms of accuracy, convergence characteristics, and overall performance. The suggested MMEFO is then employed to identify the parameters for the single, double, and triple diode models of various PV cells/modules, including R.T.C. France, PVM752, STM6-40/36, PWP-201, and STP6-120/36. In addition, various meteorological data, such as changes in radiation and temperature, exist. The simulation findings demonstrate that MEEFO outperforms other techniques and is a reliable and superior method for accurately estimating PV module parameters. The application of MEEFO yields the lowest root mean square error (RMSE) values for the considered single, double, and triple diode models of R.T.C. France. Similarly, for STP6-120/36, the RMSE values are 1.660060E−02, 1.66006E−02, and 1.66089E−02, respectively. Additionally, for PWP-20, the RMSE values are 2.425075E−03, 2.42511E−03, and 2.42510E−03, respectively.

Scalable earthquake magnitude prediction using spatio-temporal data and model versioning

Exploring the utility of the 3-minute all-out running test in assessing match performance and external loads in university soccer players

Purpose This study evaluated the utility of the 3-minute all-out running test (3MT) in assessing match performance and physiologically relevant load metrics among male university soccer players. We aimed to explore the relationship between 3MT metrics, including critical speed (CS), finite energy reserve (D’), and maximal running speed (Smax), with key match performance indicators, while also assessing the efficacy of a modified method for tracking player load. Methods Twenty-six male university soccer players completed the 3MT to determine CS, D’, and maximal speed (Smax). Match performance data (n = 3–8 matches per player) were concurrently gathered, including total distance covered, high-speed running (HSR), very high-speed running (VHSR), and overall player load. Correlation analyses were conducted to examine the relationships between 3MT variables and match performance, with a specific focus on how a modified load-tracking method compared to traditional approaches. Results Players with higher CS exhibited smaller fluctuations in D’ kinetics, indicating more efficient energy utilization during matches. A strong positive correlation was found between 3MT-derived Smax and the initiation of both HSR (r = 0.73, p < 0.01) and VHSR (r = 0.69, p < 0.05), highlighting the link between sprint capacity and match-specific high-intensity efforts. Lastly, a modified method for assessing player load demonstrated a high correlation with traditional methods (r = 0.99), while also accounting for individual metabolic demands. The modified approach offers a more nuanced understanding of player workload, potentially improving fatigue management, performance, and injury prevention. Conclusions The 3MT proved to be a valuable tool for evaluating individual physiological conditioning while also mapping on to key match performance metrics and external loads in university soccer players. The association with key performance indicators such as high-speed running capacity and sustained effort highlights its potential for optimizing training strategies.

Research on prediction algorithm of effluent quality and development of integrated control system for waste-water treatment

Abstract Research is implemented to protect the environment from an epidemic of chemical materials that could render living conditions hazardous. In order to efficiently use productivity while maintaining a constant and reliable level of waste quality, severe regulations regarding Waste-Water Treatment and Control Systems (WWTCS) must be adopted to mitigate the serious nature of water pollution and impure performance. Suboptimal treatment efficiency and use of resources are the results of the methods used for WWTCS, which are not highly susceptible to changing impact features and complex biological systems. The present study presented a prediction algorithm and an Integrated Control System (ICS) to address the problems of conventional methods. This research proposes a Deep Learning (DL) for the quality of wastewater prediction that employs a Quantile Regression-Random Forest (QR-RF) meta-learner when combined with Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRU). The proposed method has been implemented into practice and tested at Asia’s Jiangsu Province Metropolitan Waste-Water Treatment Plant (WWTP). With a Root Mean Absolute Error (RMSE) of 4.76 mg/L for 24-h horizons and a Mean Absolute Error (MAE) of 0.85 mg/L for 1-h predictions, the proposed model outperforms conventional methods in terms of prediction accuracy. The ICS is superior to standard WWTCS by a vital error boundary, minimizing energy consumption by 17% and boosting chemical-based consumption optimization by 24%. With an average removal rate of 94.23% for Chemical Oxygen Demand (COD) compared to 88.76% for standard systems, the findings from experiments exhibited significant performance improvements.

Mediating role of systemic inflammation in linking transferrin saturation to all-cause mortality in patients with coronary artery disease: Evidence from a large population-based study

Background Transferrin saturation (TS) is associated with mortality across populations, but its nonlinear relationship with all-cause mortality in coronary artery disease (CAD) and the role of systemic inflammation remain unclear. This study explored the association between TS and mortality in CAD patients, focusing on systemic inflammation as a potential mediator. Methods Data from National Health and Nutrition Examination Survey (NHANES) 1999–2006 included 769 CAD patients (>18 years) with available TS and mortality records. Systemic inflammation markers, such as the systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI), were analyzed. Kaplan–Meier curves, Cox proportional hazards models, and mediation analyses examined the interactions between TS, inflammation, and mortality. Results A U-shaped relationship between TS and all-cause mortality was observed, with an inflection point at 30.5%. TS levels ≤30.5% were inversely associated with mortality (HR = 0.98; 95% CI, 0.96–0.99; P < 0.0001), while levels >30.5% increased mortality risk (HR = 1.05; 95% CI, 1.02–1.08; P < 0.001). Systemic inflammation markers (SII/SIRI) were associated with and may partially mediate the relationship between low TS (≤30.5%) and mortality. (mediation proportions: 28.5% and 21.8%, respectively). No mediation effects were found for TS > 30.5%. Conclusions TS demonstrates a U-shaped relationship with all-cause mortality in CAD patients. Systemic inflammation is linked to both TS and mortality outcomes, suggesting potential mechanistic interplay. Maintaining TS within 20–30% and addressing inflammation may reduce mortality risk.

Molecularly imprinted polypyrrole-based electrochemical sensor for furaldehydes determination in Italian honey samples

Simulation study to evaluate when Plasmode simulation is superior to parametric simulation in comparing classification methods on high-dimensional data

Simulation studies, especially neutral comparison studies, are crucial for evaluating and comparing statistical methods as they investigate whether methods work as intended and can guide an appropriate method choice. Typically, the term simulation refers to parametric simulation, i.e. computer experiments using pseudo-random numbers. For these, the full data-generating process (DGP) and outcome-generating model (OGM) are known within the simulation. However, the specification of realistic DGPs might be difficult in practice leading to oversimplified assumptions. The problem is more severe for higher-dimensional data as the number of parameters to specify typically increases with the number of variables in the data. Plasmode simulation, which is a combination of resampling covariates from a real-life dataset from the DGP of interest together with a specified OGM is often claimed to solve this problem since no explicit specification of the DGP is necessary. However, this claim is not well supported by empirical results. Here, parametric and Plasmode simulations are compared in the context of a method comparison study for binary classification methods. We focus on studies conducted with some specific data type or application in mind whose true, unknown data-generating mechanism is mimicked. The performance of Plasmode and parametric comparison studies for estimating classifier performance is compared as well as their ability to reproduce the true method ranking. The influence of misspecifications of the DGP on the results of parametric simulation and of misspecifications of the OGM on the results of parametric and Plasmode simulation are investigated. Moreover, different resampling strategies are compared for Plasmode comparison studies. The study finds that misspecifications of the DGP and OGM negatively influence the ability of the comparison studies to estimate the classification performances and method rankings. The best choice of the resampling strategy in Plasmode simulation depends on the concrete scenario.

CT radiomics to assess severity of explosion-induced primary blast lung injury in goats

Effect of low-dose esketamine on cardio-biliary reflex and postoperative pain during laparoscopic cholecystectomy surgery: A randomized, controlled trail

Background Cardio-biliary reflex can lead to cardiac arrest, brady-arrhythmia, cardiogenic shock, and other severe complications. NMDA receptor antagonists have been shown to have the effect of anti-vagal reflex. However, the regulation of vagus reflex by esketamine, an NMDA receptor antagonist, remains unclear. Our study aims to investigate intravenous low-dose esketamine on cardio-biliary reflex. Methods In this randomized controlled trial, adult patients undergoing laparoscopic cholecystectomy were allocated in a 1:1 ratio to esketamine group or control group. 5 minutes before surgical incision, participants in the esketamine group received 0.3 mg/kg of esketamine, while the control group received an equivalent volume of normal saline. The primary outcome was the occurrence of cardio-biliary reflex. Postoperative pain was assessed using the Visual Analogue Scale (VAS) on days 1, 2, and 3 post-surgery. Results Our final analysis included 140 participants. The incidence of the cardio-biliary reflex occurred in 15 patients (21.4%) in the control group compared with 6 patients (8.6%) in the esketamine group (relative risk 0.34; 95%confidence interval (95% CI): 0.125–0.947; P < 0.05). Patients in the esketamine group reported lower pain intensity with movement on postoperative days (POD)1, 2, and 3 with mean differences (MD) of 0.59, 0.70, and 0.47 points respectively (all P < 0.05). Additionally, pain intensity at rest was also lower in the esketamine group at all observation time points (POD1: MD 0.51, POD2: MD 0.40, POD3: MD 0.30, all P < 0.05). Conclusions Therapeutic use of low-dose esketamine significantly reduces the occurrence of cardio-biliary reflex and postoperative pain in patients undergoing laparoscopic cholecystectomy.

Comparative metabolic profiling of Cordia myxa leaves and fruits based on UPLC-ESI/MS-MS analysis and investigation of antioxidant activities and enzyme inhibitory properties

Abstract Cordia myxa, Assyrian plum, is an edible deciduous plant belonging to the family Boraginaceae and exhibited different traditional and pharmacological activities, including wound healing, emollient, expectorant, hepatoprotective, immune-modulator, and hypoglycemic. Our study aimed to investigate the metabolic profiling of C. myxa leaves and fruits growing in Egypt using the Ultra Performance Liquid Chromatography-Mass Spectrometry (UPLC-MSn) technique. Alongside, we determined its antioxidant properties and enzyme inhibitory activity against acetylcholinesterase (AChE), butyrylcholinesterase (BChE), tyrosinase, α-glucosidase, and α-amylase. UPLC-MSn analysis revealed the identification of 24 and 19 compounds in the leaf and fruit extracts, respectively. The identified compounds cover different phytochemical classes like phenolic acids, flavonoids, phenolic glycosides, lignans, anthocyanins and fatty acids, flavonoids being the predominant one. The leaf extract showed stronger antioxidant properties (DPPH: 100.80 mg TE/g; ABTS: 134.43 mg TE/g, CUPRAC: 290.87 mg TE/g; FRAP: 205.78 mg TE/g), compared to the fruit extract (DPPH: 22.45 mg TE/g; ABTS: 91.74 mg TE/g; CUPRAC: 41.39 mgTE/g; FRAP: 33.63 mg TE/g). In contrast to other antioxidant assays, the metal-chelating ability of the fruit extract (20.59 mg EDTAE/g) was greater than that of the leaf extract (9.94 mg EDTAE/g). The AChE inhibitory effect of fruit extract (2.59 mg GALAE/g) was higher than that of leaf extract (2.51 mg GALAE/g), but the leaf extract (1.68 mg GALAE/g) showed a stronger BChE inhibitory effect than the fruit extract (1.25 mg GALAE/g). Further, the fruit extract showed almost 2.5 times greater tyrosinase inhibitory activity than the leaf extract. The α-amylase and α-glucosidase inhibitory activities of the leaf extract were superior to those of the fruit extract. The molecular docking studies showed high docking affinities between three compounds, quercetin, kaempferol, and caffeic acid, with all targeted enzymes. As a conclusion, C. myxa signifies an excellent natural supply of treasured bioactive constituents with promising antioxidant and enzyme inhibitory effects. Further phytochemical studies should be performed to isolate the responsible compounds and investigate their mechanism of action.

The complaint handler’s bind: How organisational constraints lead to defensive responses to criticism

Defensiveness is often implicated in systemic organisational failures to explain why early warning signs were ignored and organisational resilience was compromised. But how does an organisation become defensive? We propose that defensiveness can arise as a response to contradictory work demands. Our research focuses on UK hospital staff tasked with responding to criticism online (herein complaint handlers). We examine these responses to criticism using a mixed methods explanatory sequential design. Six defensive tactics were reliably identified: redirecting patients to other channels, evading issues, psychologising concerns, invalidating concerns as incomplete, closing the feedback episode, and individualising concerns with bespoke workarounds. These defensive tactics were generally associated with less organisational learning and were sometimes viewed as unhelpful. To explain these results, we introduce the complaint handler’s bind: staff are tasked with responding to complaints without a viable pathway for organisational learning and an implicit injunction against voicing this dilemma. This demand-control double bind unwittingly gives staff little alternative but to be defensive. Future research, we conclude, needs to conceptualise defensiveness as sometimes a symptom rather than a cause of problems in organisational learning.

Effect of structural properties of unsaturated soils on the performance of biomineralized cementation

Advancing energy integration: renewable sources, ancillary services, and stability

The paper discusses the recent developments and challenges in the energy sector, particularly focusing on the integration of renewable energy sources into microgrids and conventional power systems. It highlights the importance of predicting future energy generation for effective grid integration and discusses the use of Artificial Neural Network (ANN) and Auto-Regressive Moving Average (ARMA) models for this purpose. Additionally, it explores the role of distributed generation in providing ancillary services traditionally offered by conventional power systems and analyzes the impact of renewable energy sources on core parameters like frequency and voltage stability. It also discusses the rapid growth of solar photovoltaic (PV) systems and the need to assess their impacts on distribution networks. Furthermore, it addresses the ongoing energy crisis, particularly in South Asia, and proposes solutions such as power factor correction through technologies like Static VAR Compensators (SVCs) to enhance system stability and efficiency, especially in medium and long transmission lines.

Assessing the feasibility and sustainability of fog water harvesting as an alternative water resource

Abstract Iran is experiencing an escalating freshwater crisis due to factors such as population growth, drought, and inadequate water resource management. Atmospheric water, which is six times the volume of all global rivers, presents an untapped potential. This study assesses Iran’s potential for fog water harvesting (FWH) by analyzing atmospheric conditions—including relative humidity, fog density, and frequency—along with technical feasibility and a cost–benefit analysis. Data from 120 synoptic stations identified regions with high fog water potential, notably the southern areas, exhibiting yields up to 65 L/m2/day, and northern and eastern regions with potentials between 25 and 45 L/m2/day. Compared to similar global projects, Iran’s relative humidity (78%–96%) and the cost of fog water harvesting ($0.25/m3) demonstrate superior feasibility over desalination ($0.6/m3). Additionally, this study highlights the importance of fog type (e.g., advection vs. upslope) and region-specific limitations that may impact implementation. Sustainability considerations—economic, environmental, and social—are addressed, alongside proposed pilot areas such as Kish and Chabahar. Fog water harvesting is positioned as a promising supplement to Iran’s national water strategy.