Search Results (42,008)

Fungal extracts have garnered considerable attention in recent years due to their diverse pharmaceutical potential. The present study investigates the secondary metabolite profile and biological activities of Alternaria citri, a fungal strain associated with citrus fruits. Metabolites were extracted from A. citri grown in Potato Dextrose Broth (PDB) using ethyl acetate and subsequently evaluated for antimicrobial, antioxidant, and cytotoxic activities, alongside gas chromatography–mass spectrometry (GC–MS) profiling. GC–MS analysis identified 14 bioactive compounds in the fungal extract. The extract exhibited antimicrobial activity against Aspergillus flavus, Trichoderma hamatum, Staphylococcus aureus, and Escherichia coli. Moderate total phenolic and flavonoid contents were observed, which correlated with concentration-dependent antioxidant activity as determined by the DPPH assay. Cytotoxic evaluation using NIH/3T3 cells demonstrated potential anticancer activity, with an IC₅₀ value of 126.63 µg/mL. A. citri is an interesting source of bioactive metabolites with potential therapeutic applications. These findings further strengthen the evidence that Alternaria species can serve as promising sources of natural antioxidants and antimicrobials, thereby supporting their potential applications in pharmaceutical and biomedical formulations. This study expands current knowledge of fungal metabolite diversity and establishes A. citri as a potential source of novel therapeutic agents. Full article

This article analyzes the scale, fluctuations and geographical distribution of olive (Olea europaea) cultivation in Palestine over 550 years, from the Late Mamluk period (1300–1517), through the Ottoman era (1517–1917), until the end of the British Mandate in 1947. Although olive oil played a dominant role in the diet and the local economy, there is currently no research that measures and quantifies the number of olive trees or the number of villages and towns that cultivated olive trees and produced olive oil. We reconstruct the agricultural landscape with its vast olive groves and examine the cultural history of olive tree farming, the growth of the olive oil industries and their economic role and importance. The earliest figures we have, that are from the year 1596, show that 400 villages cultivated 1,400,794 olive trees. By 1943, there were 6,053,367 olive trees that were cultivated by 644 villages. We found a strong correlation (R² = 0.96, p < 0.01) between the number of olive trees and the number of villages, indicating that olive oil demand and the olive oil industry align with population size. The research data derives from a variety of medieval local chroniclers, as well as diaries by European, North African and Middle Eastern travelers who provide descriptions of olive groves and the olive oil industry. Among the most important sources are the 1596 Ottoman tax registers. The tax registers are the first document that present clear-cut figures on the numbers of olive trees, olive presses and the names of the villages that cultivated olive groves. The main sources for the last period dealt with in this study are the British Mandate maps (1943), which display the acreage of the different crops across Palestine. The data from the maps is supplemented by two modern works on olive cultivation written by agronomists Assaf Goor (b. 1894) and Ali Nasouh (b. 1906) who were born in Palestine and employed by the British department of agriculture. The analysis of data shows that demands of local and oversea markets; the olive oil soap industry, which was based on the local olive oil; as well as competing agricultural crops like sugarcane, cotton and citrus, contributed to a complex economic structure. Olive tree cultivation did not depend on government investment. Olive groves in Palestine were rain fed, and, except for the harvest, they required relatively few working days a year. Hence, moderate policies (low taxation during periods of drought and low yields) adopted by enterprising local rulers and the central British government created a unique and relatively balanced relationship between rulers and farmers, which encouraged olive cultivation and led to a constant increase in the number of olive trees and the development of the olive oil industry. Full article

Classical soil mechanics models are inadequate for predicting the traction of wheeled vehicles under high-velocity off-road conditions due to the complex dynamic soil response. To address this, this study proposes a velocity-segmented dynamic compression-shear model for aeolian sandy soil, enhancing classical theories with velocity-dependent corrections for the 0–10 m/s range. A theoretical patterned wheel–soil interaction model is developed, incorporating lug effects via an equivalent radius. Furthermore, a comprehensive vehicle traction model is established by integrating the soil model with a dynamic equilibrium iteration method that couples suspension dynamics, pitch attitude, and axle load distribution. Validation results demonstrate that the single-wheel traction theoretical model achieves an error of less than 18%, while the full vehicle traction model reaches a 73% prediction accuracy for drawbar pull and sinkage, as verified through soil bin tests and full-vehicle experiments. This research provides theoretical framework for the real-time and accurate prediction of wheeled-vehicle traction performance on unprepared terrain, offering significant improvements for high-velocity off-road mobility analysis. Full article

Against the dual backdrop of worsening air pollution and industrial intelligent transformation, industrial robot technology has become an important means to promote air pollution synergistic governance. This study innovatively incorporates public environmental satisfaction and industrial robot application as dynamic mechanism variables, constructing an evolutionary game model involving the government, industrial enterprises, and the public. Through theoretical analysis and numerical simulation, the study reveals the influence mechanism of key cost–benefit parameters on stakeholders’ strategic interaction and the system’s evolution path. The conclusions are as follows: (1) The government’s environmental supervision directly affects enterprises’ green transformation willingness, and enterprises’ behavior reversely impacts public satisfaction and supervision effectiveness, forming a “supervision–response–feedback” closed-loop. (2) The cost and benefit parameters related to industrial robots are crucial for the evolution of the game system, and there is significant heterogeneity in their impact on the strategic choices of the three parties. The robot adaptation transformation of enterprise industrial depends on the comprehensive consideration of the transformation cost and the green benefits. Public supervision is regulated by both the supervision cost and the incentive benefit. The government regulation takes into account both the regulatory cost and the loss of social reputation. Various parameters dynamically regulate the system’s equilibrium by altering the party’s cost–benefit structure. (3) The application of industrial robots and the feedback of public environmental satisfaction form a coupling effect, jointly determining the long-term evolution direction of the game system. When the cost benefit and supervision incentives are well-matched, enterprises will actively promote the green transformation of industrial robots in order to achieve intelligent pollution control. The effectiveness of public supervision has also been fully realized. The dynamic adaptation of the two components can lead the system towards an efficient and stable equilibrium in air pollution governance. Full article

This study investigates the impact response and energy absorption performance of additively manufactured PLA–geopolymer hybrid composites for potential application in road safety barriers. Hybrid Charpy specimens were fabricated with three different infill densities (20%, 60%, and 100%), combining a 3D-printed PLA outer shell with a geopolymer core. Charpy impact tests were conducted in accordance with ISO 179-1 and ASTM D6110, and the absorbed energy, specific energy absorption, and mass efficiency were determined experimentally. A phase-based analytical model was also used to estimate elastic energy contributions, while fracture surfaces were examined to identify infill-dependent damage mechanisms. To extend the material-level findings to an engineering-scale application, the observed trends were transferred to a New Jersey-type road safety barrier model and evaluated using ANSYS Explicit Dynamics. The results showed that infill density strongly affects fracture behavior and energy dissipation performance, with 60% infill providing the most balanced response in terms of energy absorption and mass/material efficiency. The originality of the present study lies in going beyond a material-scale investigation of the impact behavior of additively manufactured PLA–geopolymer hybrid structures by integrally correlating the experimental Charpy results with a theoretical energy-based framework, fracture-surface observations, and explicit dynamic finite element analysis of a New Jersey-type road safety barrier model. Full article

The rapid development of intelligent learning guidance systems has created a favorable environment for personalized learning. By accurately predicting students’ future performance, education can be tailored and teaching strategies optimized. However, traditional prediction algorithms seldom account for highly imbalanced datasets in basic education, overlook temporal factors, and lack further interpretability of the prediction results. To address these shortcomings, we propose Temporal Variational Autoencoder-Generative Adversarial Network (TVAE-GAN), a temporal variational autoencoder-generative adversarial network model aimed at providing early warnings for high-risk students in basic education, with in-depth interpretability analysis of the prediction results to suit the unique context of basic education. TVAE-GAN extracts features from real samples and introduces a Long Short-Term Memory (LSTM) network to capture dynamic features in time series, helping the model better understand temporal dependencies in the data, remember the sequential causal information of students’ online learning, and achieve better data generation performance. Using these features, the generative model generates new samples, and the discriminator model evaluates their quality, producing outputs that closely resemble real samples through training. The effectiveness of the TVAE-GAN model is validated on a collected online basic education dataset while also advancing the timing of interventions in predictions. The performance differences between the proposed method and classic resampling methods, as well as their impact in the educational field, are analyzed, highlighting that misclassification increases teacher workload and affects students’ emotions. Key influencing factors are identified using a decision-tree surrogate model, providing teachers with multidimensional references for academic assessment. Full article

Chronic d-galactose (d-gal) treatment is a model to induce accelerated aging-like phenotypes in rodents. However, the sex differences in behavioral and musculoskeletal manifestations of this model are not well understood. Heme oxygenase-1 (HO-1) is a cytoprotective protein that may have anti-aging properties. The goal of this study was to better understand the sex differences in the behavioral and musculoskeletal effects of chronic d-gal treatment in C57BL/6J mice, as well as the role of HO-1 induction or inhibition. Eight-week-old male and female mice received daily saline or d-gal injections (500 mg/kg, s.c.) for 12 weeks. After this time, mice in the d-gal group were randomized into three groups (n = 6/group/sex): d-gal, d-gal + cobalt protoporphyrin (CoPP) (5 mg/kg, s.c. weekly), and d-gal + zinc deutroporphyrin bisglycol (ZnBG) (42 mg/kg, i.p. triweekly) for a period of 4 weeks. Open-field, novel-object recognition, Barnes maze, grip strength, micro-computed tomography (µ-CT), histology, and protein analysis were performed. Chronic d-gal treatment resulted in a sexual dimorphic response, with female mice being more prone to develop deficits in both short- and long-term spatial memory as well as in non-spatial memory. Male mice exhibited deficits only in long-term spatial memory when treated chronically with d-gal. Inhibition of HO-1 was protective in both females and males. Chronic d-gal treatment did not accelerate the development of osteoporosis or sarcopenia in either males or females. Our results demonstrate a sexual dimorphic response to the chronic effects of d-gal treatment on aging, with greater effects in females than in males, which is dependent on HO-1. Full article

Background: Dementia is one of the most common diseases of the elderly worldwide. Sharing experiences of caring for patients with dementia with other carers is essential to improve the quality of care, promote better outcomes, and learn from others. Aim: to explore nurses’ experiences of working with patients with dementia in Lithuanian supportive treatment and nursing hospitals. Methods: A qualitative descriptive design was employed in this study, with data collected through semi-structured interviews. Nurses with direct experience caring for patients with dementia in supportive treatment and nursing hospitals were recruited through purposive sampling. This sampling strategy was chosen to ensure that participants could provide rich, contextual, and experience-based insights into the phenomenon under investigation. Open-ended questions were divided into three themes: 1. Identifying nursing needs. 2. Care for people with dementia. 3. Patient behavior management and situation management. To ensure methodological rigor and transparency, the Consolidated Criteria for Reporting Qualitative Research (COREQ) were applied throughout the study’s planning, data collection, and analysis processes. Results: Nine nurses working in three different Lithuanian hospitals participated in the study. Theme 1: respondents reported that the needs of patients with dementia depend on their previous lifestyle and hobbies, as well as on essential physiological needs such as eating and drinking, bathing and personal hygiene, and the absence of pain. Theme 2: All participants emphasized that ensuring a safe environment is crucial for people with dementia. Theme 3: When faced with inappropriate patient behaviour, nurses attempt to calm the patient, speak gently, provide distraction, or, when necessary, temporarily separate the patient from others. Additional actions include administering medication and stabilizing the patient. Overall, these findings illustrate that dementia care requires continuous emotional presence, situational judgment, and adaptation to each patient’s individual needs. Conclusions: Patients with dementia require highly individualized care focused on nutrition, hygiene, pain control, and communication. Nurses’ daily activities centered on essential bodily care, medication management, and mobility support to maintain safety and prevent complications. Full article

Renewable energy sources, and wind energy in particular, constitute a central pillar of energy policy at both national and European levels. Nevertheless, the deployment of onshore wind farms is frequently associated with spatial, environmental, and social conflicts, making the evaluation of existing projects imperative. The present study aimed to assess the sustainability of existing onshore wind farms in the Region of Thessaly, with particular emphasis on their spatial planning, technical characteristics, and environmental impacts. The methodological framework consists of four distinct stages: (i) identification and spatial mapping of existing wind farms in the study area, (ii) assessment of the compliance of existing wind installations with the Specific Framework for Spatial Planning and Sustainable Development for Renewable Energy Sources (SFSPSD–RES), (iii) application of the Rapid Impact Assessment Matrix (RIAM) to enable a systematic and comparable evaluation of the impacts of wind installations on specific environmental and anthropogenic parameters, and (iv) estimation of project hazard and operational vulnerability through the application of Operational Risk Management (ORM). Geographic Information Systems (GISs) were employed for data processing and spatial analysis. The assessment showed that 40% of the evaluated wind farms fully comply with all eleven exclusion criteria of the SFSPSD-RES, whereas the remaining 60% show partial compliance, failing to meet between one and three criteria. RIAM results indicate that the most significant adverse impacts (−D and −C) during construction are associated with morphology/soils and the natural environment, mainly due to loss/fragmentation of vegetation and disturbance of fauna, and, in some cases, in areas of increased sensitivity. During operation, the main negative effects (−D and −C) relate to landscape and visual quality, as well as continued disturbance to the natural environment. At the same time, the operation generates important positive effects (+E) on the atmospheric environment through reduced CO₂ emissions. The ORM analysis further shows that the most important risks for most wind farms arise during construction (ORM = 2 and 3), particularly from serious worker accidents during lifting, roadworks, and foundation activities. The study demonstrates that the sustainability of existing wind installations depends on a complex set of spatial, environmental, and technical factors. The proposed framework integrates spatial compliance screening, RIAM-based environmental impact assessment, and ORM-based risk and opportunity evaluation. This connection links the importance of impacts with their operational manageability during construction and operation phases, as well as across sustainability dimensions. Consequently, the study provides a more decision-focused approach for assessing existing wind farms and supporting policy development. Full article

Background/Objectives: Gastro-resistant multiparticulate systems are designed to protect drugs in acidic environments and to ensure intestinal release. In practice, the method of administration may need to be modified: pellet-containing capsules opened or tablets halved for patients with swallowing difficulties, yet the type of liquid used for administration is often not specified. This study examined the stability of gastro-resistant coated pellets after exposure to various aqueous media prior to ingestion. Methods: To evaluate administration instructions, 103 Summaries of Product Characteristics of gastro-resistant products were reviewed. Pellets were produced using a bottom-spray fluidized bed process and coated with Eudragit L 30 D-55. Dissolution testing in pH 1.2 medium was performed after pre-soaking the pellets for 5, 15, and 30 min in beverages with various pH and conductivity. Drug release was measured by UV-VIS method, and morphological changes were assessed by image analysis. Marketed gastro-resistant products were also examined visually. Results: SmPC review revealed that the beverage for intake was frequently unspecified. Among the tested beverages differences in pH and conductivity were observed. Alkaline medicinal mineral waters induced increased and time-dependent premature drug release compared to tap and filtered water. Image analysis indicated a reduction in surface area after exposure to alkaline media. Conclusions: Contact with non-specified aqueous media before swallowing may weaken the protective function of gastro-resistant films. More explicit recommendations on suitable administration manipulation and media may improve therapeutic consistency. Full article

Salmonella enteritidis (SE) is recognized as a primary etiological agent of foodborne infection and food poisoning. Selective and sensitive determination of SE in animal-derived products is of great importance for ensuring safety in the food industry. Here, we report a highly sensitive and specific competition assay for detecting SE in eggs without interference from background fluorescence, by using persistent luminescent nanoparticles (PLNPs) as luminescent probes in combination with aptamer recognition and magnetic separation. Initially, the SE-specific aptamer (SEapt), as previously reported, was conjugated onto the surface of Fe₃O₄ magnetic nanoparticles to serve as both the recognition and separation unit. Meanwhile, the ZnGa₂O₄:Cr (PLNPs) were functionalized with the aptamer-complementary DNA (cDNA), serving as the PL signal generator. The constructed PL aptasensor is composed of the aptamer-conjugated MNPs (MNPs-SEapt) and cDNA-functionalized PLNPs (PLNPs-cDNA), integrating the merits of the long-lasting luminescence of PLNPs, the magnetic separation ability of MNPs and the selectivity of the aptamer. This integration offers a promising approach for autofluorescence-free determination of SE in food samples. The proposed aptasensor exhibited excellent linearity in the range from 1.0 × 10²–1.0 × 10⁷ CFU mL⁻¹ with a limit of detection as low as 32 CFU mL⁻¹. The precision for 11 replicate determinations of 1.0 × 10³ CFU mL⁻¹ SE was 3.4% (relative standard deviation). The developed aptasensor achieved recoveries ranging from 98.8% to 102.8% for the determination of SE in the presence of common foodborne bacterial interferents. The method was successfully applied to the analysis of Salmonella genus in egg samples. In principle, the proposed platform may be adapted to other food matrices by substituting the target-specific aptamer, pending target-dependent optimization and validation. Full article

Background/Objectives: Ovarian cancer (OC) remains the most lethal gynecologic malignancy, largely due to late-stage diagnosis and high rates of recurrence following platinum-based chemotherapy. Growing evidence implicates cancer stem-like cells (CSCs) in OC relapse, as these cells exhibit enhanced chemoresistance, stemness, epithelial–mesenchymal transition (EMT), and the capacity to remodel the tumor microenvironment. Inhibitors of DNA-binding (ID) 1-4 proteins are transcription factors with known redundancy; however, their collective role in OC chemotherapy response remains poorly defined. Here, we examined how ID family signaling responds to chemotherapy and contributes to CSC-associated features and microenvironment remodeling. Methods: Publicly available patient data, OC cell lines, and a subcutaneous xenograft mouse model were used to correlate changes in ID1-4 expression with CSCs, EMT, and the tumor microenvironment (TME). OC cell lines were used for in vitro assays to evaluate CSC features and IL-6 production in the presence of carboplatin and/or a small molecule inhibitor of ID proteins, AGX51. Results: Analysis of clinical datasets, cell lines, and in vivo models revealed enrichment of ID1-4 following chemotherapy, with additive increases across treatment cycles. In vivo ID2 and ID4 expression was associated with IL-6 secretion and loss of anti-tumoral macrophages. Pan-ID inhibition demonstrated that cumulative ID activity minimally supports CSC maintenance during chemotherapy, while more strongly regulating IL-6 secretion. Conclusions: IL-6 production from cancer cells was at least partially dependent on ID proteins, linking collective ID signaling to microenvironment remodeling and relapse potential in ovarian cancer. Full article

This study investigates the acceptance of an AI-powered decision-support chatbot among professionals in a marketing and sales context, addressing a gap in technology acceptance research by examining data-intensive decision environments that remain underexplored. Building on the Unified Theory of Acceptance and Use of Technology (UTAUT), the study proposes an extended model incorporating Behavioral Intention, Performance Expectancy, Effort Expectancy, Social Influence, Output Quality, Time Saving, Source Trustworthiness, Cognitive Load, and Chatbot Self-Efficacy. An experimental study was conducted with 106 professionals using a chatbot-enhanced business analytics platform to complete marketing KPI analysis tasks. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results demonstrate that Behavioral Intention to use decision-support chatbots is significantly influenced by Performance Expectancy, Effort Expectancy, and Social Influence. Performance Expectancy is strongly driven by Output Quality, Time Saving, and Source Trustworthiness, while Effort Expectancy is significantly shaped by reduced Cognitive Load and higher Chatbot Self-Efficacy. The findings suggest that chatbot acceptance in professional decision-making depends not only on usability and performance beliefs but also on cognitive relief, trust in information sources, and efficiency gains, highlighting important implications for both theory and the design of AI-based decision-support systems. Full article

The higher heating value (HHV), sometimes referred to as the gross calorific value, is a crucial metric for determining a fuel’s primary energy potential in energy production systems. By combining extreme gradient boosting (XGBoost) with the differential evolution (DE) optimizer, an innovative machine learning-based model was created in this study to forecast the HHV (dependent variable). As input variables, the model included the constituents of the coal’s ultimate analysis: carbon (C), oxygen (O), hydrogen (H), nitrogen (N), and sulfur (S). For comparative purposes, random forest regression (RFR), M5 model tree, multivariate linear regression (MLR), and previously reported empirical correlations were also applied to the experimental dataset. The results showed that the XGBoost strategy produced the most accurate predictions. An initial XGBoost analysis was carried out to identify the relative contribution of the input variables to coal HHV prediction. In particular, for coal HHV estimates reliant on experimental samples, the XGBoost regression produced a correlation coefficient of 0.9858 and a coefficient of determination of 0.9691. The excellent agreement between observed and anticipated values shows that the DE/XGBoost-based approximation performed satisfactorily. Lastly, a synopsis of the investigation’s key conclusions is provided. Full article

Soil organic carbon (SOC) stocks in cacao agroecosystems are characterized by accumulating large amounts. They depend on the balance between organic matter inputs (plant residues, roots) and losses (decomposition, erosion), being closely related to climatic conditions, soil nature, vegetation type, topography, and land management practices. The objective of this study was to quantify SOC stocks (0–30 cm) and assess key soil fertility indicators across 107 georeferenced sampling locations in cacao production systems of Guamal (Meta, Colombian Llanos Piedmont). Soil pH varies between extremely acidic and moderately acidic (3.8–6.0; mean 4.57), while available P (Bray II) and exchangeable bases showed low concentrations. Organic carbon concentration averaged 1.18% and bulk density averaged 1.17 g cm⁻³. SOC stocks averaged 41.10 Mg C ha⁻¹, ranging from 7.49 to 81.55 Mg C ha⁻¹, evidencing marked spatial contrasts in carbon storage. Spearman correlations highlighted coupled soil chemical controls, including positive associations of pH with Ca²⁺ and P availability and strong negative associations of pH and P with exchangeable Al³⁺, consistent with acidity-driven fertility constraints. Principal component analysis (PCA) further identified a dominant fertility gradient structured by pH, P availability, and Ca²⁺, and a second axis related to organic carbon and cation retention. Spatial modeling using inverse distance weighting (IDW) in ArcGIS supported the visualization of SOC stock variability across the study area. Overall, the results indicate that SOC stocks in these predominantly sandy soils are strongly influenced by acidity-related constraints and heterogeneous nutrient status, underscoring the need for site-specific management to jointly enhance soil fertility and climate-mitigation potential in cacao systems. Therefore, it would be advisable in the future to address the study of differential variations in soil C storage related to chemical fertilizer application rates, especially in the long term. Full article