Search Results (3,734)

Catalytic and bioelectrocatalytic properties of four white rot fungal laccases (Trametes hirsuta, ThL; Coriolopsis caperata, CcL; Steccherinum murashkinskyi, SmL; and Antrodiella faginea, AfL) from different orthologous groups were comparatively studied in homogeneous reactions of electron donor substrate oxidation and in a heterogeneous reaction of dioxygen electroreduction. The ThL and CcL laccases belong to high-redox-potential enzymes (E⁰_T1 = 780 mV), while the AfL and SmL laccases are medium-redox-potential enzymes (E⁰_T1 = 620 and 650 mV). We evaluated the efficiency of laccases in mediatorless bioelectrocatalytic dioxygen reduction by the steady-state potential (E_ss), onset potential (E_onset), half-wave potential (E_1/2), and the slope of the linear segment of the polarization curve. A good correlation was observed between the T1 center potential of the laccases and their electrocatalytic characteristics; however, no correlation with the homogeneous reactions of electron donor substrates’ oxidation was detected. The results obtained are discussed in the light of the known data on the three-dimensional structures of the laccases studied. Full article

Primary ciliary dyskinesia (PCD) is a rare, genetically heterogeneous disorder that impairs mucociliary clearance and leads to progressive lung disease. This study aimed to characterize lung function decline in a genetically homogeneous cohort of Puerto Rican patients with RSPH4A-associated PCD and to develop a clinical tool to predict lung function decline and support transplant referral decisions. We conducted a retrospective chart review of patients (n = 25) with a confirmed RSPH4A [c.921+3_6delAAGT] genetic variant, collecting longitudinal spirometry data and applying linear regressions to calculate each patient’s individual FEV₁ decline. The median FEV₁ at diagnosis was 55%, with a median annual decline of −0.75% predicted. Adults exhibited significantly lower lung function compared to pediatric patients, while no difference was seen between males and females. Based on this observed decline, we developed the Predicted Capacity Decline Index (PCDx), an index that estimates the age and time until a patient reaches the 30% FEV₁ threshold, the point at which lung transplant referral is typically considered. Our findings underscore the need for early intervention and suggest that genotype-specific tools like the PCDx may enhance clinical decision-making in managing progressive lung disease in PCD. Full article

Sport volunteering plays an important role in achieving the goals of sustainable development by supporting the social dimension of sustainability, fostering social integration, and promoting a healthy lifestyle. However, there is a lack of systematic research in Poland on the motivations of sport volunteers, particularly in the context of mass endurance events. This study employed a quantitative, cross-sectional design involving 148 sport volunteers engaged in mass endurance events in Poznan, Poland. To measure motivation, the Polish adaptation of the VMS-ISE scale was used. Data analysis was conducted using one-way analysis of variance (ANOVA). The results showed that volunteer motivations were relatively homogeneous regardless of gender and education level, with the exception of passion for sport, which was significantly stronger among men (p = 0.037). Significant differences were found based on place of residence: residents of medium-sized cities demonstrated the highest motivation for personal development (p < 0.001), whereas individuals from rural areas exhibited stronger patriotism, a greater need for interpersonal interaction, and a higher valuation of external rewards (p < 0.05). The motivations of sport volunteers in Poland are complex and sensitive to environmental factors. Understanding these differences allows for better alignment of recruitment and volunteer management strategies, which can enhance both the effectiveness and sustainability of volunteer engagement. It is recommended to develop volunteer programs that take into account the demographic and socio-cultural characteristics of participants. Full article

Beech forests in the Italian peninsula are actively managed and they also support a high level of biodiversity. Hence, biodiversity conservation can be synergistic with timber production and carbon sequestration, enhancing the overall economic benefits of forest management. This study aimed to evaluate the effect of forest management regimes on bird communities in the Italian Peninsula during 2022 through audio recordings. We studied the structure, composition, and specialization of the breeding bird community in four managed beech stands (three even-aged beech stands aged 20, 60, and 100 years old, managed by a uniform shelterwood system; one uneven-aged stand, managed by a single-tree selection system) and one uneven-aged, unmanaged beech stand in the northern Apennines (Tuscany region, Italy). Between April and June 2022, data were collected through four 1-hour audio recording sessions per site, analyzing 5 min sequences. The unmanaged stand hosted a richer (a higher number of species, p < 0.001) and more specialized (a higher number of cavity-nesting species, p < 0.001; higher Woodland Bird Community Index (WBCI) values, p < 0.001; and eight characteristic species, including at least four highly specialized ones) bird community, compared to all the managed forests; moreover, the latter were homogeneous (similar to each other). Our study suggests that the unmanaged beech forests should be a priority option for conservation, while in terms of the managed beech forests, greater attention should be paid to defining the thresholds for snags, deadwood, and large trees to be retained to enhance their biodiversity value. Studies in additional sites, conducted over more years and including multi-taxon communities, are recommended for a deeper understanding and generalizable results. Full article

The double wishbone suspension (DWS) system is widely used in automotive engineering because of its favorable kinematic properties, which affect vehicle dynamics, handling, and ride comfort; hence, it is important to have an accurate 3D model, simulation, and analysis of the system in order to optimize its design. This requires efficient computational tools for parametric study. The development of effective computational tools that support parametric exploration stands as an essential requirement. Our research demonstrates a complete Wolfram Mathematica system that creates parametric 3D kinematic models and conducts simulations, performs analyses, and generates interactive visualizations of DWS systems. The system uses homogeneous transformation matrices to establish the spatial relationships between components relative to a global coordinate system. The symbolic geometric parameters allow designers to perform flexible design exploration and the kinematic constraints create an algebraic equation system. The numerical solution function NSolve computes linkage positions from input data, which enables fast evaluation of different design parameters. The integrated 3D visualization module based on Mathematica’s manipulate function enables users to see immediate results of geometric configurations and parameter effects while calculating exact 3D coordinates. The resulting robust, systematic, and flexible computational environment integrates parametric 3D design, kinematic simulation, analysis, and dynamic visualization for DWS, serving as a valuable and efficient tool for engineers during the design, development, assessment, and optimization phases of these complex automotive systems. Full article

The rapidly changing dynamics of the digital age reshape the addiction relationship that high school students establish with technology. While smartphones remove boundaries in terms of communication and access to information, their usage triggers a source of anxiety and nomophobia. The increase in students’ anxiety levels because of their over-reliance on mobile phone use leads to significant behavioral changes in their mental health, academic performance, social interactions and financial dependency. This study examined the nomophobia levels of high school students according to selected socio-demographic indicators. Using the relational screening model, the multistage sampling technique was used to select a sample of 884 participants: 388 from Science High School and 496 from Anatolian High School (459 female, 425 male, Mage = 16.45 ± 1.14 year). Independent sample test and One-way ANOVA were applied. Depending on the homogeneity assumption of the data, Welch values were considered, and Tukey tests were applied as a second-level test from post hoc analyses. Comprehensive analyses of nomophobia levels revealed that young individuals’ attitudes towards digital technology differ significantly according to their demographic and behavioral characteristics. Variables such as gender, physical activity participation, grade level and duration of smartphone use are among the main factors affecting nomophobia levels. Female individuals and students who do not participate in physical activity exhibit higher nomophobia scores. Full article

In this study, a highly cadmium (II)-resistant bacterium strain, C10-4, identified as Bacillus altitudinis, was isolated from a sediment sample collected from Baiyangdian Lake, China. The minimum inhibitory concentration (MIC) of Cd(II) for strain C10-4 was 1600 mg/L. Factors such as the contact time, pH, Cd(II) concentration, and biomass dosage affected the adsorption of Cd(II) by strain C10-4. The adsorption process fit well to the Langmuir adsorption isotherm model and the pseudo-second-order kinetics model, based on the Cd(II) adsorption data obtained from the cells of strain C10-4. This suggests that Cd(II) is adsorbed by strain C10-4 cells via a single-layer homogeneous chemical adsorption process. According to the Langmuir model, the maximum biosorption capacity was 3.31 mg/g for fresh-strain C10-4 biomass. Cd(II) was shown to adhere to the bacterial cell wall through SEM-EDS analysis. FTIR spectroscopy further indicated that the main functional sites for the binding of Cd(II) ions on the cell surface of strain C10-4 were functional groups such as N-H, -OH, -CH-, C=O, C-O, P=O, sulfate, and phosphate. After the inoculation of strain C10-4 into Cd(II)-contaminated soils, there was a significant reduction (p < 0.01) in the exchangeable fraction of Cd and an increase (p < 0.01) in the sum of the reducible, oxidizable, and residual fractions of Cd. The results show that Bacillus altitudinis C10-4 has good potential for use in the remediation of Cd(II)-contaminated soils. Full article

Urban health planning requires a multi-scalar understanding of the territory, capable of capturing socio-economic inequalities and health needs at the local level. In the case of Rome, current administrative subdivisions—Urban Zones (Zone Urbanistiche)—are too large and internally heterogeneous to serve as effective units for equitable health planning. This study presents a methodology for the territorial redefinition of Rome’s Municipality III, aimed at supporting healthcare planning through an integrated analysis of census sections. These were grouped using a combination of census-based socio-demographic indicators (educational attainment, employment status, single-person households) and real estate values (OMI data), alongside administrative and road network data. The resulting territorial units—21 newly defined Mesoareas—are smaller than Urban Zones but larger than individual census sections and correspond to socio-territorially homogeneous neighborhoods; this structure enables a more nuanced spatial understanding of health-related inequalities. The proposed model is replicable, adaptable to other urban contexts, and offers a solid analytical basis for more equitable and targeted health planning, as well as for broader urban policy interventions aimed at promoting spatial justice. Full article

This study investigates the delineation of management zones (MZs) to support site-specific crop management by simplifying within-field variability in irrigated (54.6 ha) and rainfed (7.9 ha) sorghum and soybean fields in Brazil. Historical yield, apparent soil electrical conductivity (ECa) at 0.75 m and 1.50 m, and terrain data were analyzed using multivariate statistics to define MZs. Two clustering methods—fuzzy c-means (FCM) and hierarchical clustering—were compared for variance reduction effectiveness. Rainfed areas showed greater spatial variability (yield CV 9–12%; ECa CV 20–27%) than irrigated fields (yield CV < 7%; ECa CV ~5%). Principal component analysis (PCA) identified subsoil ECa and elevation as key variables in irrigated fields, while surface ECa and topography influenced rainfed variability. FCM produced more homogeneous zones with fewer classes, especially in irrigated fields, whereas hierarchical clustering better detected outliers but required more zones for similar variance reduction. Yield correlated strongly with slope and moisture in rainfed systems. These results emphasize aligning MZ delineation with production system characteristics—enabling variable rate irrigation in irrigated fields and promoting moisture conservation in rainfed systems. FCM is recommended for operational efficiency, while hierarchical clustering offers higher precision in complex contexts. Full article

While personal thermal comfort is critical for well-being and productivity, it is often overlooked by traditional building management systems that rely on uniform settings. Modern data-driven approaches often fail to capture the complex interactions between various data streams. This pilot study introduces a high-accuracy, interpretable framework for thermal comfort classification, designed to identify the most significant predictors from a comprehensive suite of environmental, physiological, and anthropometric data in a controlled group of young adults. Initially, an XGBoost model using the full 24-feature dataset achieved the best performance at 91% accuracy. However, after using SHAP analysis to identify and select the most influential features, the performance of our ensemble models improved significantly; notably, a Random Forest model’s accuracy rose from 90% to 94%. Our analysis confirmed that for this homogeneous cohort, environmental parameters—specifically temperature, humidity, and CO₂—were the dominant predictors of thermal comfort. The primary strength of this methodology lies in its ability to create a transparent pipeline that objectively identifies the most critical comfort drivers for a given population, forming a crucial evidence base for model design. The analysis also revealed that the predictive value of heart rate variability (HRV) diminished when richer physiological data, such as diastolic blood pressure, were included. For final validation, the optimized Random Forest model, using only the top 10 features, was tested on a hold-out set of 100 samples, achieving a final accuracy of 95% and an F1-score of 0.939, with all misclassifications occurring only between adjacent comfort levels. These findings establish a validated methodology for creating effective, context-aware comfort models that can be embedded into intelligent building management systems. Such adaptive systems enable a shift from static climate control to dynamic, user-centric environments, laying the critical groundwork for future personalized systems while enhancing occupant well-being and offering significant energy savings. Full article

The relationship between self-rated personality and nonverbal intelligence has been studied in young students, but these studies have generally not considered nested data, despite their allowing us to analyse between-classroom variability. The present cross-sectional study involved third- to sixth-grade students (n = 447) who were nested into their classrooms (n = 32). The participants completed the Raven’s Coloured Progressive Matrices (CPM) as a measure of nonverbal intelligence and a personality questionnaire based on the Five Factor Model. At the class level, the study data included class size, class-average CPM scores, and class-homogeneity in CPM performances. Multilevel modelling with class-mean centring of personality predictors was applied to examine class-average differences in CPM scores and interaction effects between personality and class-homogeneity on CPM scores. The results showed significant differences in average CPM performances across classrooms, significant fixed and random slope effects linking nonverbal intelligence and Imagination, and a cross-level effect revealing that Imagination is a stronger predictor of CPM scores when class-homogeneity in intelligence is lower. Beyond confirming the intelligence–Imagination association generally observed in the literature, the present findings emphasise the importance of using nested structures when collecting personality and intelligence data in classrooms. More attention needs to be paid to how the classroom environment affects children’s self-reported personality and intelligence test performances. Full article

Data-driven approaches and calibration techniques for mathematical models, starting from observed data, are attracting more and more interest in the field of civil engineering. Among them, evolutionary polynomial regression (EPR) is an artificial intelligence (AI) technique that combines genetic algorithms (GAs) and regression strategies. However, the difficulties and uncertainties inherent in the method have pointed out how the implementation of proper computational methods together with the use of recent and qualified databases of experimental data are essential to carry out reliable formulations. In this framework, this paper explores a new robust EPR approach able to remove potential outliers and leverage points often occurring in biased dataset and simultaneously accounting for the effects of probabilistic uncertainties. Uncertainties are incorporated in the EPR methodology by adopting the direct perturbation method. In particular, it is shown the importance to set the parameters representative of experimental and analytical dispersions on the basis of the characteristics of the database in terms of homogeneity. With this purpose, two different case-studies are analyzed, dealing with the shear capacity of RC beams without stirrups and the compressive strength of cement-based mortar specimens, respectively. Finally, the best capacity equations are selected and discussed. Full article

Growing environmental concerns have driven increased interest in solid-state thermal technologies based on the elastocaloric properties of shape memory alloys (SMA). This work examines the elastocaloric effect (eCE) in Ni-Ti SMA sheets subjected to cyclic bending, providing quantitative thermal characterization of their behavior under controlled loading conditions. The experimental investigation employed passive thermography to analyze the thermal response of Ni-Ti sheets under two deflection configurations at 1800 rpm loading. Testing revealed consistent adiabatic temperature variations (ΔT_ad) of 4.14 °C and 4.26 °C for the respective deflections during heating cycles, while cooling phases demonstrated efficient thermal homogenization with temperature gradients decreasing from 4.13 °C to 0.13 °C and 4.43 °C to 0.68 °C over 60 s. These findings provide systematic thermal documentation of elastocaloric behavior in bending-loaded Ni-Ti sheet elements and quantitative data on the relationship between mechanical loading parameters and thermal gradients, enhancing the experimental understanding of elastocaloric phenomena in this configuration. Full article

Background: Post-hepatectomy liver failure (PHLF) is the most worrisome complication after a major hepatectomy and is the leading cause of postoperative mortality. The most important predictor of PHLF is the future liver remnant (FLR), the volume of the liver that will remain after the hepatectomy, representing a major concern for hepatobiliary surgeons, radiologists, and patients. Therefore, an accurate preoperative assessment of the FLR and the prediction of PHLF are crucial to minimize risks and enhance patient outcomes. Recent radiomics and deep learning models show potential in predicting PHLF and the FLR by integrating imaging and clinical data. However, most studies lack external validation and methodological homogeneity and rely on small, single-center cohorts. This review outlines current CT-based approaches for surgical risk stratification and key limitations hindering clinical translation. Methods: A literature analysis was performed on the PubMed Dataset. We reviewed original articles using the subsequent keywords: [(Artificial intelligence OR radiomics OR machine learning OR deep learning OR neural network OR texture analysis) AND liver resection AND CT]. Results: Of 153 pertinent papers found, we underlined papers about the prediction of PHLF and about the FLR. Models were built according to machine learning (ML) and deep learning (DL) automatic algorithms. Conclusions: Radiomics models seem reliable and applicable to clinical practice in the preoperative prediction of PHLF and the FLR in patients undergoing major liver surgery. Further studies are required to achieve larger validation cohorts. Full article

Weeds represent increasingly troublesome threats to modern wheat production. Jiangsu Province, China, is one of the largest wheat-planting areas, characterized by a high level of agricultural mechanization, in the country. In 2024, we surveyed weed communities of 924 wheat lands from 308 sites in Jiangsu and compared them with historical data surveyed in 1999–2000 in this province. A total of 156 weed species belonging to 103 genera and 39 families were recorded. Compositae and Poaceae showed the highest species richness, with 26 and 23 species, respectively. Poaceae weeds accounted for 54.3% of the overall weeds in dominance values. Beckmannia syzigachne showed the highest proportion of the overall weeds in dominance values (19.2%). Compared with the historical data, weed diversity increased by 33.3% in species, and by 62.5% in families; grassy weeds such as Beckmannia syzigachne, Alopecurus japonicus, and Alopecurus myosuroides became more dominant, while several low-growing grassy weeds became less dominant. The dominance of broadleaf weeds, such as Galium spp., Vicia spp., and Veronica spp., decreased greatly, and a clear trend of weed homogenization among different areas and types of wheat lands was observed. This is the first investigation of weed community succession against the background of agricultural modernization in China. Full article