Search Results (4,708)

The soil environment has been considered capable of storing toxic substances without serious consequences for the inhabitants since plants are able to bioaccumulate pollutants without compromising their survival. The application of chemicals to increase soil productivity and the dumping of waste have worsened soil quality. Recently, following a greater awareness of the importance of monitoring the damage deriving from the consumption of contaminated crops for humans and of the protection of biodiversity, studies aimed at identifying the effects of soil contamination on terrestrial animals have increased considerably. Studies using field lizards as model organisms fit into this scenario; this research has shed light on the uptake, accumulation, and toxicity of soil pollutants on reptiles. This review summarizes data collected on lizards of the Podarcis genus, a group of resilient wild species capable of living in both pristine and anthropized areas; the data reveal that many of the effects recorded in lizard tissues at the molecular, biochemical, and histological levels are independent of the chemical composition of the contaminants and are mostly linked to the type of cellular response. Overall, these studies confirm Podarcis lizards as a good model system in ecotoxicological and cytotoxicological research, providing an accurate description of the effects of pollutants, clarifying the defense mechanisms activated in relation to different exposure routes and, finally, providing predictive information on the risks faced by other animals. Since the effects recorded in lizards have often also been observed in mammals, it can be concluded that the results obtained from studies on these animals can be translated to other terrestrial vertebrates, including mammals. Full article

(1) Background: Postoperative atrial fibrillation (POAF) is the most common complication following cardiac surgery. It leads to increased perioperative morbidity and costs. Our study aimed to determine the incidence of new-onset POAF in patients undergoing isolated aortic valve replacement (AVR) and develop a multivariate model to identify its predictors. (2) Methods: We conducted a retrospective study including all consecutive patients who underwent isolated AVR at our institution between January 2010 and December 2022. Patients younger than 18, with a history of atrial fibrillation, previous cardiac surgery, or those who underwent concomitant procedures were excluded. Patients were dichotomized into POAF and No POAF groups. Multivariate logistic regression with backward elimination was utilized for predictive modeling. (3) Results: This study included 1108 patients, of which 297 (27%) developed POAF. The final multivariate model identified age, larger valve size, cardiopulmonary bypass time, delayed sternal closure, ventilation time, and intensive care unit stay as predictors of POAF. The model exhibited fair predictive ability (AUC = 0.678, p < 0.001), with the Hosmer–Lemeshow test confirming good model fit (p = 0.655). The overall correct classification percentage was 65.6%. (4) Conclusions: A POAF prediction model offers personalized risk estimates, allowing for tailored management strategies with the potential to enhance patient outcomes and optimize healthcare costs. Full article

Polyandry is widespread among eusocial Hymenoptera, and the honey bee is a typical representative of this. It has been widely shown that polyandry can confer benefits to queens and their offspring, including enhanced productivity and fitness, stronger resistance to pathogens, and resilient division of labor, which promotes colony-level homeostasis. A previous study conducted in Australia demonstrated that 33.8% commercial Apis mellifera queens produced in autumn were not adequately mated. Beekeepers of Apis cerana in China also claimed that the queens reared in autumn are inferior to those reared in spring. To confirm whether the quality difference of queens produced in different periods is related to their mating frequency, we estimated the observed mating frequency (k) and the effective mating frequency (m_e) of A. cerana queens produced at the beginning and end of the queen production season in Liaoning Province. We found that all the queens were suitably mated and there was no significant difference in the mating frequency between early spring queens and late summer queens. In addition, our study indicated that the queens and their offspring workers owned a high level of heterozygosity and their inbreeding coefficients were universally low. Further studies on the queens’ performance and health are required to verify the statement that the queens reared in autumn are not as good as those reared in spring. Full article

Monitoring animal welfare on farms and in research settings is attracting increasing interest, both for ethical reasons and for improving productivity through the early detection of stress or diseases. In contrast to video-based monitoring, which requires good light conditions and has difficulty tracking specific animals, recent advances in the miniaturization of wearable devices allow for the collection of acceleration and location data to track individual animal behavior. However, for broilers, there are several challenges to address when using wearables, such as coping with (i) the large numbers of chickens in commercial farms,(ii)the impact of their rapid growth, and (iii) the small weights that the devices must have to be carried by the chickens without any impact on their health or behavior. To this end, this paper describes a pilot study in which chickens were fitted with devices containing an Inertial Measurement Unit (IMU) and an Ultra-Wideband (UWB) sensor. To establish guidelines for practitioners who want to monitor broiler welfare and activity at different scales, we first compare the attachment methods of the wearables to the broiler chickens, taking into account their effectiveness (in terms of retention time) and their impact on the broiler’s welfare. Then, we establish the technical requirements to carry out such a study, and the challenges that may arise. This analysis involves aspects such as noise estimation, synergy between UWB and IMU, and the measurement of activity levels based on the monitoring of chicken activity. We show that IMU data can be used for detecting activity level differences between individual animals and environmental conditions. UWB data can be used to monitor the positions and movement patterns of up to 200 animals simultaneously with an accuracy of less than 20 cm. We also show that the accuracy depends on installation aspects and that errors are larger at the borders of the monitored area. Attachment with sutures had the longest mean retention of 19.5 days, whereas eyelash glue had the shortest mean retention of 3 days. To conclude the paper, we identify current challenges and future research lines in the field. Full article

In alignment with China’s “carbon peak and carbon neutrality” goals, carbon reduction and energy structure transformation are central priorities. As a major emitter, the power industry plays a key role in this transition, and identifying effective pathways for its green energy transformation is essential to driving broader industrial green transformation and ensuring sustainable development. This article calculates the elasticity of substitution between clean and non-clean energy within China’s power sector from 1993 to 2021, employing the kernel density estimation method. By further comparing the goodness-of-fit across various nested structures of clean energy sources, the study identifies the optimal internal nested structure and examines the interactions among its components. The results underscore two key insights: on the one hand, a robust substitutive relationship exists between clean and non-clean energy, with the substitution elasticity of 1.646, exhibiting pronounced regional heterogeneity characterized as “weaker in the east and stronger in the west”; on the other hand, the optimal nested structure of clean energy is identified as (hydropower + nuclear power)—wind power—solar power. In this structure, the elements display a substitutive relationship in the Eastern Region, while in the Western Region, they exhibit a complementary relationship. Full article

The Childbearing Motivations Scale (CMS) is a multidimensional self-report measure of positive and negative motivations influencing the decision to become a parent. This study aimed to validate the Italian version of the CMS. A sample of 522 participants (27% men and 73% women) aged from 18 to 55 years was recruited. The four-factor model for the positive subscale and the five-factor model for the negative subscale of the CMS demonstrated a good fit. Reliability values ranged from 0.70 to 0.91. Both factors had evidence for convergent validity with sex, age, and relationship duration: women reported lower in some of the negative motivations to become a mother in contrast to men. Moreover, the greater the age, the lower the negative motivations for becoming a parent. Those in a longer relationship indicated lower negative motivations. No significant correlations were found for the positive motivations subscale. Significant differences were found for income levels (low vs. medium/high) regarding personal fulfillment, financial problems, and body-image concerns, as well as in cultural levels (medium vs. high) concerning economic constraints, intergenerational continuity, immaturity, and physical suffering. These findings suggest that individuals with lower economic resources scored higher across all these areas on the Negative Childbearing Motivations subscale. Our findings indicate that the CMS can be used to reliably assess the motivations for parenthood among Italian men and women. Full article

Research is needed on the myths regarding child sexual abuse in order to address commonly held misconceptions in persons training for professional careers in relevant fields for child protection. We present our translated, validated, and expanded Child Sexual Abuse Myth Scale (CSAMS-G). It was tested on a sample of 569 students studying either education, social work, law, or policing. Results of confirmatory factor analysis revealed a good model fit for our assumed factorial structure. Acceptable results on internal consistency were confirmed with McDonald’s ω. We also present the first results on the acceptance of child sexual abuse myths in our sample. Overall, myth acceptance was low, but a few exceptions were found, especially for the newly added items. We found group differences in factor scores for gender as well as between survivors and non-survivors of child sexual abuse. Full article

Small-batch workpieces in smart manufacturing demand process parameter modeling, but existing models lack analysis across varying sample sizes and runtime conditions. This study proposes a novel surface-roughness prediction method, Response Surface Methodology-BP Neural Network (RSM-BPNN), designed for experimental data from single small-batch workpieces with varying sample sizes. First, polynomial feature transformation and selection are performed based on the proposed process parameters to improve the feature quality of input data. Second, a Dynamic Central Composite Design-Response Surface Methodology (DCCD-RSM) determines the optimal experimental region and fits surface roughness, while a BPNN trains a deep learning model for prediction. The BPNN fusion method combines both approaches to create a general, adaptive predictive model for surface roughness. Finally, the accuracy and practicality of the BPNN model were verified through reverse calculation and parameter optimization in actual robot grinding experiments. The model demonstrated good predictive performance for surface roughness in aluminum alloy grinding, providing reliable guidance for surface quality prediction and process parameter optimization in small-batch workpieces within the context of smart manufacturing. Full article

Rollover crashes are among the most prevalent types of accidents in developing countries. Various factors may contribute to the occurrence of rollover crashes. However, limited studies have simultaneously investigated both traffic stream and road-related variables. For instance, the effects of T-intersection density, U-turns, roadside parking lots, the entry and exit ramps of side roads, as well as traffic stream characteristics (e.g., standard deviation of vehicle speeds, speed violations, presence or absence of speed cameras, and road surface deterioration) have not been thoroughly explored in previous research. Additionally, the simultaneous modeling of crash frequency and intensity remains underexplored. This study examines single-vehicle rollover crashes in Yazd Province, located in central Iran, as a case study and simultaneously evaluates all the variables. A dataset comprising three years of crash data (2015–2017) was collected and analyzed. A crash index was developed based on the weight of crash intensity, road type, road length (as dependent variables), and road infrastructure and traffic stream properties (as independent variables). Initially, the dataset was refined to determine the significance of explanatory variables on the crash index. Correlation analysis was conducted to assess the linear independence between variable pairs using the variance inflation factor (VIF). Subsequently, various models were compared based on goodness of fit (GOF) indicators and odds ratio (OR) calculations. The results indicated that among ten crash modeling techniques, namely, Poisson, negative binomial (NB), zero-truncated Poisson (ZTP), zero-truncated negative binomial (ZTNB), zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), fixed-effect Poisson (FEP), fixed-effect negative binomial (FENB), random-effect Poisson (REP), and random-effect negative binomial (RENB), the FENB model outperformed the others. The Akaike information criterion (AIC) and Bayesian information criterion (BIC) values for the FENB model were 1305.7 and 1393.6, respectively, demonstrating its superior performance. The findings revealed a declining trend in the frequency and severity of rollover crashes. Full article

Neural network models based on GNNs often achieve good results in traffic flow prediction tasks of traffic networks. However, most existing GNN-based methods apply a fixed graph structure to capture spatial dependencies between nodes, and fixed graph structures may not be able to reflect the spatiotemporal changes in node dependencies. To address this, introducing a self-attention mechanism applied to an adaptive adjacency matrix, the neural network architecture is improved based on Graph WaveNet, and a new approach called self-attention dynamic graph wave network (SA-DGWN) is proposed, which can fit the spatiotemporal dependencies of the road network. In an experiment, traffic flow data were extracted based on RFID from certain roads in Nanjing, China. The results show that under the same configuration, compared to Graph WaveNet, MAE, MAPE, and RMSE from the proposed method reduced by 3.08%, 3.68%, and 2.6%, respectively. In addition, for the training data, we explored the impact of temporal feature and sampling periods on the training effect. The additional results indicate that adding hour-minute-second information to the input improved the model’s accuracy, reducing MAE, MAPE, and RMSE by 15.28%, 12.28%, and 14.01%, respectively. Adding day-of-the-week features also brought substantial performance improvements. For different sampling periods, the model performed better overall with a 10 min sampling period compared to 5 min and 15 min periods. For single-step prediction tasks, the longer the sampling period, the better the prediction effect. Full article

The Earth abounds in water resources; however, only 0.4% of the freshwater resources are suitable for drinking. The scarcity of freshwater resources has a severe impact on the sustainable development of human society. Desalination is regarded as one of the most effective solutions. In this study, a research approach integrating materials and devices was utilized to synthesize manganese oxide-coated carbon nanospheres (CS@MnO₂). Experimental results demonstrated that the system, by combining the distinctive performance merits of the CS@MnO₂ material and the balanced desalination features, exhibited outstanding desalination performance. In the EDS elemental mapping analysis, the relatively feeble signal of carbon was ascribed to the encapsulation of MnO₂ on the outer surface of CS. Through computational TGA analysis, the mass fraction of carbon in CS@MnO₂-2 was determined to be approximately 51.2%. The excellent hydrophilicity of the material facilitated the permeation of the salt solution throughout the electrode, thereby enhancing the capacitance. CS@MnO₂-2 manifested a high salt adsorption capacity of 27.42 mg g⁻¹ and the fastest electrosorption rate of 7.81 mg g⁻¹ min⁻¹. During 50 adsorption desorption cycles, the adsorption capacity showed good results. The adsorption kinetics and adsorption isotherm fitting indicated that the desalination process involved electrostatic and multilayer adsorption. This study holds great significance for reducing the cost of desalinated water and guaranteeing a sustainable supply of freshwater resources. Full article

As a kind of bioactive component in the rhizome of natural plant Curcuma longa L. (turmeric), curcumin is almost insoluble in water at neutral and acidic pH, which limits its further utilization and development. At the same time, traditional extraction and separation processes typically require the use of a large number of organic solvents. Ionic liquids (ILs) are organic molten salts with melting points below 100 °C. When an ionic liquid exists in a liquid state at or near room temperature, it is referred to as a room-temperature ionic liquid (RTIL). They have a temperature range, good physical and chemical stability, and good structural designability. They have a strong solubilization enhancement effect for many organic compounds. This study first explored the molecular forms of curcumin in ionic liquid aqueous solutions and the intermolecular interactions between curcumin and ionic liquids using spectral analysis and computational chemistry methods; furthermore, using an ionic liquid aqueous solution as an extraction agent, curcumin-like substances (curcuminoids) were extracted from turmeric powders under ultrasound assisted conditions, revealing the relationship between the structure of the ionic liquid and the extraction efficiency. After that, a kinetic study was conducted for the extraction of curcuminoids from turmeric powders, using second-order kinetics fitting to obtain the rate constant and initial extraction rate during the extraction process. Finally, the comparison with a ComplexGAPI tool and antioxidant experiment was performed on the extraction by using ionic liquids and traditional solvent. The full results can provide reference for the design of IL extractants and their application for natural products. Full article

There is no doubt that leadership is one of the most researched and disseminated topics in recent years, and over time, some distinguished models have developed a solid foundation and a reputable structure. From this perspective, this study analyzes the evidence of validity and reliability of a scale that assesses leadership styles in non-profit institutions. The study had an instrumental design. The sample consisted of 272 workers from nine Latin American countries, aged between 19 and 68 years (M = 34.08 and SD = 8.61), recruited through non-probabilistic sampling. A validity and reliability analysis of the scale confirmed the nine items and three original factors (servant, empowering and shared leadership). The KMO test reached a high level (0.898 > 0.70), and the Bartlett test reached a highly significant level (Sig. = 0.000). The scale also showed good internal consistency (α = 0.918 to 0.956; CR = 0.918 to 0.957; AVE = 0.755 to 0.880). Likewise, for the Confirmatory Factor Analysis, a measurement adjustment was performed, obtaining excellent and acceptable fit indices for Model 2 (CMIN/DF = 1.794; CFI = 0.993; SRMR = 0.023; RMSEA = 0.054; Pclose = 0.369). This study provides a brief and useful tool to measure leadership styles in Latin America, as a scale used specifically for this context would allow for a more accurate and valid assessment. This is crucial for generating effective organizational interventions, fostering the development of authentic leaders, and improving the competitiveness of non-profit institutions. Full article

The cement-based materials widely used in infrastructure construction, such as bridges and ports, are subjected to seawater erosion and medium erosion during their service life, and their durability has always been a concern. The diffusion coefficient of chloride ions is an important indicator in the research of cement-based materials’ durability, and the pore structure is one of the most fundamental reasons affecting the diffusion behavior of chloride ions. In this paper, Mercury intrusion porosimetry (MIP), Nuclear magnetic resonance (NMR), and Nitrogen adsorption method (NAD) were used to analyze the pore structures of mortars with different volume fractions of sands. The relationship between mortar pore structure and chloride ion diffusion coefficient was established to predict its chloride ion diffusion coefficient. It may provide a new idea for studying the durability of cement-based materials. Results indicated that similar to cement paste, the pore structure of mortar satisfied the fractal characteristics of solid phase within a certain range of pores. The most probable gel pore diameter of mortars with different sand volume fractions was about 4 nm, while the most probable capillary pore diameter was approximately 46 nm, and the critical pore diameter was ranging from 50 to 60 nm. MIP results indicated that with the increase in sand volume fraction (ϕ_agg), the total porosity (f_mip) of the mortar decreased, satisfying the relationship of f_mip = 0.1859 − 0.0789ϕ_agg. However, the porosity of the matrix (f_base) increased with the increase in sand volume fraction, which was due to the introduction of more interfaces by the addition of aggregates. The effective chloride ion diffusion coefficient (D_cp,base) of the matrix can be obtained by fitting. Based on this, the interface transition zone (ITZ) and the cement matrix were comprehensively considered as a whole fractal phase. The predicted value of the chloride ion diffusion coefficient obtained by the Mori–Tanaka homogenization method was in good agreement with the results obtained from rapid chloride migration (RCM) experiments, and the maximum error between the simulated and experimental values did not exceed 11%. This finding can provide new ideas for accurately predicting the chloride ion diffusion coefficient of mortar and even concrete. Full article

Background: Cannabidiol (CBD) is a highly lipophilic compound with potential therapeutic applications in neurological disorders. However, its poor aqueous solubility and bioavailability, coupled with instability in physiological conditions, significantly limit its clinical use. Objectives: This study aimed to develop and characterize nanovesicles incorporating Tween 20 to enhance CBD encapsulation, stability, and the performance across the blood–brain barrier (BBB). Methods: Nanovesicles were prepared via thin-film hydration followed by sonication and optimized for size, polydispersity index, and zeta potential. Stability studies were conducted under physiological conditions and during storage at 4 °C. In vitro release studies employed the dialysis bag method, while permeability across the BBB was assessed using PAMPA-BBB and the hCMEC/D3-BBB cell line, characterized for brain endothelial phenotype and largely employed as a model of human blood–brain barrier (BBB) function. Cytotoxicity was evaluated via MTT and LDH assays. Results: The quantification of CBD was carried out by HPLC-DAD and HPLC-MS/MS. Nanovesicles with Tween 20 (VS-CBD) exhibited smaller size (65.27 ± 1.27 nm vs. 90.7 ± 0.2), lower polydispersity (0.230 ± 0.005 vs. 0.295 ± 0.003), and higher stability compared to conventional liposomes (L-CBD). VS-CBD achieved high encapsulation efficiency (96.80 ± 0.96%) and recovery (99.89 ± 0.52%). Release studies showed sustained CBD release with Higuchi model fitting (R² = 0.9901). Both PAMPA-BBB and hCMEC/D3-BBB cell lines demonstrated an improved controlled permeability of the formulation compared to free CBD. Cytotoxicity tests confirmed the good biocompatibility of VS-CBD formulations. The addition of Tween 20 to nanovesicles enhanced CBD encapsulation, stability, and controlled release. Conclusions: These nanovesicles represent a promising strategy to improve CBD delivery to the brain, offering sustained therapeutic effects and reduced dosing frequency, potentially benefiting the treatment of neurological disorders. Full article