Search Results (8,349)

Study region: This study focused on the Iznik Lake Watershed in northwestern Türkiye. Study focus: Climate change is increasingly affecting water resources worldwide, raising concerns about future hydrological sustainability. This study investigates the impacts of climate change on river streamflow in the Iznik Lake Watershed, a critical freshwater resource in northwestern Türkiye. To capture possible future conditions, downscaled climate projections were integrated with the SWAT+ hydrological model. Recognizing the inherent uncertainties in climate models and model parameterization, the analysis examined the relative influence of climate realizations, emission scenarios, and hydrological parameters on streamflow outputs. By quantifying both the magnitude of climate-induced changes and the contribution of different sources of uncertainty, the study provides insights that can guide decision-makers in future management planning and be useful for forthcoming modeling efforts. New hydrological insights for the region: Projections indicate wetter winters and springs but drier summers, with an overall warming trend in the study area. Based on simulations driven by four representative grid points, the results at the Karadere station, which represents the main inflow of the watershed, indicate modest changes in mean annual streamflow, ranging from −7% to +56% in the near future and from +19% to +54% in the far future. Maximum flows (Q_max) exhibit notable increases, ranging from +0.9% to +47% in the near future and from +21% to +63% in the far future, indicating a tendency toward higher peak discharges under future climate conditions. Low-flow conditions, especially in summer, exhibit the greatest relative variability due to near-zero baseline discharges. Relative change analysis revealed considerable differences in Karadere and Findicak sub-catchments, reflecting heterogeneous hydrological responses even within the same basin. Uncertainty analysis, conducted using both an ANOVA-based approach and Bayesian Model Averaging (BMA), highlighted the dominant influence of climate projections and potential evapotranspiration calculation methods, while land use change contributed negligibly to overall uncertainty. Full article

As energy exploration and development continue to advance into deep and ultradeep formations, systematic studies of rock mechanical properties face significant challenges due to high core acquisition costs and sample damage under extreme conditions. To overcome these challenges, high-precision, minimally invasive, or non-destructive testing methods are urgently needed. This study systematically characterizes the microstructural features and mechanical heterogeneity of deep carbonate rocks from the Shunbei area by integrating XRD, SEM-EDS, and nanoindentation techniques. The results show that these rocks are primarily composed of a continuous calcite phase, with quartz as the secondary phase occurring in regional aggregates embedded within the calcite matrix. The two phases commonly exhibit an intergrown texture, and mineral distribution displays notable spatial heterogeneity and sample-to-sample variation. Nanoindentation tests reveal that the quartz phase exhibits excellent mechanical stability, with elastic moduli ranging from 70.6 to 101.8 GPa and hardness values between 10.8 and 13.5 GPa. The data are tightly clustered, indicating structural homogeneity and strong resistance to deformation. In contrast, the calcite phase shows lower and more scattered mechanical parameters, with elastic moduli of 27.4~76.0 GPa and hardnesses of 0.7~2.3 GPa, reflecting pronounced microscale heterogeneity. Furthermore, a strong negative correlation exists between hardness and maximum indentation depth, further confirming the dominant influence of mineral composition on local mechanical response. Notably, despite similar mineralogical compositions among samples A13, A15, and A18, their micromechanical performance follows the order A15 > A18 > A13, indicating that subtle differences in diagenetic history, crystal development, and local stress conditions can significantly affect rock mechanical behavior. Full article

Background: Helmet therapy is considered to be a treatment for infants with positional plagiocephaly. Although some studies suggest that anterior fontanelle (AF) size may also affect treatment outcomes, evidence and influence remain unclear. The aim of this study is to assess the impact of anterior fontanelle size on the effectiveness of helmet therapy, with the goal of determining the optimal timing and patient criteria for treatment. Methods: We conducted a retrospective study of 94 infants treated with helmet therapy for positional plagiocephaly at Kwangju Christian Hospital between January 2020 and December 2021. Patients were divided into two age groups (≤6 months and >6 months) and three SAF quartiles (≤25%, 25–75%, ≥75%). Parameters reflecting the degree of cranial asymmetry correction, including cranial vault asymmetry (CVA) and cranial vault asymmetry index (CVAI), were recorded at the start and end of treatment. Results: Infants aged ≤6 months showed significantly greater improvements in cranial vault asymmetry (CVA) and cranial vault asymmetry index (CVAI) compared to older infants (CVA: 4.57 ± 2.30 mm vs. 7.04 ± 3.85 mm, p = 0.003; CVAI: 3.10 ± 1.55% vs. 4.45 ± 2.44%, p = 0.011). When analyzed by anterior fontanelle (AF) size quartiles (≤25%, 25–75%, ≥75%), no significant differences in treatment outcomes were observed at the end of therapy for CVA (p = 0.88) or CVAI (p = 0.91). In infants ≤6 months, SAF quartile analysis also showed no significant differences in CVA (p = 0.97) or CVAI (p = 0.98) improvements. Conclusions: Our findings indicate that anterior fontanelle size is not a predictor of helmet therapy outcomes in positional plagiocephaly. Early initiation of helmet therapy (≤6 months) remains the most critical factor for achieving optimal results. Full article

Detecting structural defects is one of the primary challenges engineers face. Consequently, the development of techniques and methods capable of detecting structural defects has always been critical. It should be emphasized that crack detection is only meaningful if it occurs before the final stages of structural failure. Accordingly, the early identification of structural defects has become a significant research challenge, motivating the development of techniques and diagnostic parameters that can effectively capture and reflect the structure’s nonlinearity or non-uniform behavior. This study aims to provide a more detailed examination of modulation phenomena observed in the measured response using the vibro-acoustic modulation (VAM) method, and propose a new model that simultaneously incorporates all three conventional modulation types (amplitude, frequency, and phase), which may offer a more accurate representation of the response signal behavior. Both theoretical and experimental results clearly confirm that the phase shifts of individual frequency components in the frequency domain vary throughout the lifetime of the tested specimen. This behavior, as anticipated by the proposed model, reveals a strong correlation between phase shifts and modulation indices (MIs). Furthermore, the relative sensitivity analysis indicates that the phase shift is more sensitive than the modulation index (MI), suggesting its strong potential as an indicator for early defect detection in structural components. Full article

Self-supervised monocular depth estimation has demonstrated high practical utility, as it can be trained using a photometric image reconstruction loss between the original image and a reprojected image generated from the estimated depth and relative pose, thereby alleviating the burden of large-scale label creation. However, this photometric image reconstruction loss relies on the Lambertian reflectance assumption. Under non-Lambertian conditions such as specular reflections or strong illumination gradients, pixel values fluctuate depending on the lighting and viewpoint, which often misguides training and leads to large depth errors. To address this issue, we propose a multitask learning framework that integrates albedo estimation as a supervised auxiliary task. The proposed framework is implemented on top of representative self-supervised monocular depth estimation backbones, including Monodepth2 and Lite-Mono, by adopting a multi-head architecture in which the shared encoder–decoder branches at each upsampling block into a Depth Head and an Albedo Head. Furthermore, we apply Intrinsic Image Decomposition to generate albedo images and design an albedo supervision loss that uses these albedo maps as training targets for the Albedo Head. We then integrate this loss term into the overall training objective, explicitly exploiting illumination-invariant albedo components to suppress erroneous learning in reflective regions and areas with strong illumination gradients. Experiments on the ScanNetV2 dataset demonstrate that, for the lightweight backbone Lite-Mono, our method achieves an average reduction of 18.5% over the four standard depth error metrics and consistently improves accuracy metrics, without increasing the number of parameters and FLOPs at inference time. Full article

Predicting internal quality parameters, such as Brix and water content, of apples, is essential for quality control. Existing near-infrared (NIR) and hyperspectral imaging (HSI)-based techniques have limited applicability due to their dependence on equipment and environmental sensitivity. In this study, a transportable quality assessment system was proposed using spatiotemporal domain analysis with long-wave infrared (LWIR)-based thermal diffusion phenomics, enabling non-destructive prediction of the internal Brix of apples during transport. After cooling, the thermal gradient of the apple surface during the cooling-to-equilibrium interval was extracted. This gradient was used as an input variable for multiple linear regression, Ridge, and Lasso models, and the prediction performance was assessed. Overall, 492 specimens of 5 cultivars of apple (Hongro, Arisoo, Sinano Gold, Stored Fuji, and Fuji) were included in the experiment. The thermal diffusion response of each specimen was imaged at a sampling frequency of 8.9 Hz using LWIR-based thermal imaging, and the temperature changes over time were compared. In cross-validation of the integrated model for all cultivars, the coefficient of determination (R²_cv) was 0.80, and the RMSEcv was 0.86 °Brix, demonstrating stable prediction accuracy within ±1 °Brix. In terms of cultivar, Arisoo (Cultivar 2) and Fuji (Cultivar 5) showed high prediction reliability (R²_cv = 0.74–0.77), while Hongro (Cultivar 1) and Stored Fuji (Cultivar 4) showed relatively weak correlations. This is thought to be due to differences in thermal diffusion characteristics between cultivars, depending on their tissue density and water content. The LWIR-based thermal diffusion analysis presented in this study is less sensitive to changes in reflectance and illuminance compared to conventional NIR and visible light spectrophotometry, as it enables real-time measurements during transport without requiring a separate light source. Surface heat distribution phenomics due to external heat sources serves as an index that proximally reflects changes in the internal Brix of apples. Later, this could be developed into a reliable commercial screening system to obtain extensive data accounting for diversity between cultivars and to elucidate the effects of interference using external environmental factors. Full article

Background: New-onset postoperative atrial fibrillation (NOAF) is the most prevalent arrythmia after cardiac surgery with a significant clinical and economic impact. Therefore, simple and practical biomarkers for NOAF prediction remain a clinical priority. Increasing evidence indicates that malnutrition is linked to postoperative complications, including the onset of atrial fibrillation. The Prognostic Nutritional Index (PNI), which reflects the immunonutritional and inflammatory status through serum albumin concentration and lymphocyte count, has emerged as a reliable prognostic indicator in cardiovascular disease. The present study aimed to investigate the association between PNI and the development of NOAF in patients undergoing surgical aortic valve replacement (SAVR). Methods: A total of 241 consecutive patients who underwent AVR for severe aortic stenosis or regurgitation were enrolled in this study. The population was stratified into two groups according to the development of NOAF (NOAF group) or the lack thereof (no NOAF group). Results: In both univariate and multivariate logistic regression analyses adjusted for several established NOAF determinants, age and PNI, both as continuous variables, were independently associated with NOAF in both univariate (OR = 1.03; CI 95% = 1.01–1.06, p = 0.009, and OR = 0.9; CI 95% = 0.8–0.9, p = 0.01, respectively) and multivariate models (OR = 1.02; CI 95% = 1.01–1.06, p = 0.05, and OR = 0.9; CI 95% = 0.8–0.9, p = 0.03, respectively). When PNI was analyzed by tertiles, patients in the lowest tertile (PNI < 41.5) showed a significantly higher risk of developing NOAF at both univariate (OR = 1.9; CI 95% = 1.2–2.8, p = 0.004) and multivariate analysis (OR = 1.6; CI 95% = 1–2.6, p = 0.03), whereas age lost statistical significance (OR = 1.0; 95% CI = 0.9–1.05; p = 0.06). Furthermore, when the study population was divided into two groups based on the median age (70 years), PNI values differed significantly between NOAF and no NOAF patients only in patients under 70 years (p = 0.01). In this younger subgroup, PNI remained an independent predictor of NOAF, both when considered as a continuous variable (OR = 0.86; CI 95% = 0.74–0.98, p = 0.02), and nominal variable (PNI < 41.5, OR = 0.88; CI 95% = 0.80–0.97, p = 0.01). Conclusions: Overall, these findings identify PNI as an independent predictor of NOAF following SAVR, particularly in patients younger than 70 years. This study underlines the potential clinical value of preoperative nutritional assessment for risk stratification. Incorporating nutritional parameters such as PNI into current predictive models may enhance the accuracy of prognostic evaluation and support targeted perioperative management strategies. Full article

Membrane computing, and more specifically P systems, has been a useful tool in the simulation of biological systems, both at the biomolecular and cellular levels, and also in microbial and ecological communities. The need for greater realism in the simulations of these systems has been growing in the recent years. Thus, it has become clear that the rules, objects and structures of P systems cannot always be useful to model some aspects of biological systems. Specifically, some aspects of population dynamics were not perfectly reflected in the P systems that supported these models. In this work we propose new types of rules that help to model some aspects of biological systems in a more realistic way. Fundamentally, our proposal focuses on the use of probabilistic parameters that help create probabilistic and stochastic models for biological systems. In addition, given the high complexity of some of these systems, in this work we describe two software tools that we have developed and that help in the validation and debugging of these systems. Full article

Since the number of existing steel-reinforced concrete buildings affected by carbonation-induced corrosion is steadily increasing, there is a high demand for durable repair methods. Chemical re-alkalization (CRA) represents one such approach, relying on the transport of alkaline pore solution from a repair mortar into carbonated concrete. With the introduction of clinker-reduced binder systems such as hybrid alkali-activated binders (HAABs), their suitability for CRA and governing material parameters require further clarification. In this study, material-related chemical and structural influences on CRA were investigated using an adapted form of Fick’s second law of diffusion, incorporating a time-dependent attenuation factor, β(t). The CRA progression was evaluated over 28 days, distinguishing between an initial suction phase and a subsequent diffusion phase. The results show that a high initial alkalinity of the mortar pore solution (pH > 14) significantly enhances re-alkalization during the suction phase, reflected by suction factors a > 1. In contrast, progression during the diffusion phase is primarily governed by the potassium concentration gradient at the mortar–concrete interface, while structural parameters such as capillary porosity show no systematic correlation with the deceleration factor b (−0.46 ≤ b ≤ −0.26). The findings indicate that, within the investigated range, mortar pore solution chemistry has a stronger influence on CRA than structural properties, providing guidance for the targeted design of alkaline repair mortars. Full article

Background/Objectives: Three-dimensional virtual surgical planning (VSP) is increasingly central to contemporary orthognathic surgery, enhancing diagnostic precision and enabling more reliable forecasts of postoperative outcomes. NemoFAB (Nemotec, Madrid, Spain) is a recently developed digital platform that integrates CBCT data, digital dental models, and facial photographs into a single workflow. Despite its growing clinical use, independent validation of its predictive accuracy remains limited. This study evaluated how closely NemoFAB virtual predictions corresponded to actual postoperative results using standardized cephalometric parameters. Methods: Forty adult patients with dento-maxillofacial deformities requiring combined orthodontic–surgical treatment were included. Eleven cephalometric variables—common to both WebCeph (2D) and NemoFAB (3D)—were measured preoperatively, virtually in NemoFAB, and postoperatively. AI-assisted landmark placement was manually verified by two orthodontists. Statistical analyses included repeated-measures ANOVA, paired t-tests, Bland–Altman plots, and intraclass correlation coefficients (ICC) to evaluate agreement and predictive accuracy. Results: Overjet, overbite, maxillary incisor inclination, maxillary incisor exposure, mandibular incisor projection to the True Vertical Line, and occlusal plane angulation all showed statistically significant changes after surgery (p < 0.05). Bland–Altman analysis demonstrated the narrowest limits of agreement in Nemo–Post comparisons, indicating strong predictive alignment. ICC values showed excellent agreement for incisor angulation (ICC = 0.921–0.984) and Pogonion projection (ICC = 0.943). Consistently poor pre-Nemo agreement reflected expected discrepancies between initial anatomy and planned surgical correction. Conclusions: When predicting skeletal and dentoalveolar changes brought about by orthognathic surgery, NemoFAB showed a high degree of agreement, especially for parameters that are directly impacted by jaw repositioning. Its strong concordance with postoperative outcomes supports its reliability for virtual planning, interdisciplinary coordination, and surgical execution. Advances in soft-tissue modeling and AI-driven automation may further enhance predictive accuracy. Full article

The winemaking industry represents one of the most important sectors of the Mediterranean agrifood economy, generating large amounts of solid residues, especially grape pomace. The study aimed to evaluate during two consecutive harvest years the influence of the production system (conventional vs. organic) and cultivar on the mineral, chemical, and antioxidant composition, as well as the colorimetric properties, of grape pomaces obtained from four Vitis vinifera L. cultivars in Alentejo-Portugal. The results showed that mineral composition was significantly affected by both production system and cultivar, with organic grape pomace showing higher K and Mn contents, whereas Ca and Cu showed consistently higher content under conventional. Protein content tended to increase under organic production, while fiber and fat were overall higher in conventional, particularly in the first year. Sugars displayed strong cultivar specificity, with Arinto showing the highest concentrations (30 to 40%), and considering all cultivars, total phenolic content ranged between 4000 ando 9000 mg GAE/100 g, while antioxidant capacity varied among cultivars and years. Colorimetric parameters were essentially influenced by cultivar and harvest year rather than production system. The PCA revealed that PC1 (44.06%) represented a gradient associated with mineral and antioxidant composition, while PC2 (21.26%) reflected minor variation in color and sugars, and the hierarchical clustering distinguished Syrah and Alicante Bouschet as the cultivars most responsive to production system, whereas Aragonez and Arinto exhibited greater compositional stability across years. Overall, the findings indicate that both cultivar and management practices (organic and conventional) influence the compositional profile of grape pomace, with organic showing a tendency to enhance K, Mn, protein, and antioxidant parameters, whereas conventional practices favored higher levels of Ca, Cu, and fiber. The results provide valuable insights for the valorization of grape pomace and the development of sustainable viticultural strategies in Mediterranean environments. Full article

The chemical compositions and formation temperatures of magnesian calcite and dolomite were estimated by using the combination of chemical analysis, crystallographic parameters, and a plethora of various diagrams and mathematical calculations. This study presents an example of the calculated crystallo-chemical formula (Ca_0.960Mg_0.039Fe_0.001)CO₃, obtained from chemical analysis on a representative marble sample from the Bukulja–Venčac area in central Serbia. Substituting CaCO₃ with MgCO₃ and FeCO₃ in dolomite adds approximately 3–5 mol. %, enhancing the classification and indicating that it is more accurately identified as magnesium-excess dolomite. The estimated formation temperature of magnesian calcite (1) is approximately 528 °C, whereas magnesian calcite (2) forms at about 341 °C. The ~187 °C difference corresponds to ~3.28 mol. % MgCO₃ (~7.18% dolomite), reflecting the distinction between magnesian calcite (1) and magnesian calcite (2). Considering the presence of the submicroscopic intergrowth and exsolution of dolomite within magnesian calcite (1), which are further subdivided in magnesian calcite (2), the estimated formation temperature of ~341 °C appears to be more realistic. The synthesis of the results suggests that this combined method could be helpful in the geothermometry of marble samples after the treatment with acetic acid. However, despite the promising results, additional experiments are necessary to validate the proposed modified geothermometry approach. Full article

Purpose: This study assessed the adaptations resulting from implementing an experimental, integrated training program tailored to sex-specific traits. The aim was to enhance motor abilities, aerobic capacity, and metabolic variables in female and male rugby sevens athletes. Methods: Employing a combined observational and experimental design, initial and post-intervention assessments were conducted over three months (March–June 2023) with 24 elite professional players, divided equally by sex (12 females, 12 males). The protocol consisted of 12 micro-cycles, each lasting 7 days and comprising 12 training sessions. The evaluations included sprint and jumping tests, as well as functional assessments such as resting metabolic rate and cardiopulmonary exercise testing. Results: Using one-way repeated measures ANOVA, significant improvements were noted across all performance parameters (p < 0.001), with effect sizes ranging from small to very large. Sex-specific differences were evident, with females demonstrating consistent improvements in aerobic capacity and jumping ability, while males excelled in explosive power and longer sprints. Despite initial performance disparities, both sexes improved in short-distance sprints (10 m and 40 m). Cardiovascular efficiency improved as indicated by reduced maximum heart rates and lower respiratory quotients. Conclusions: Males showed superior progress in strength and explosive power tests, reflecting distinct physiological traits. These findings underscore the need for individualized and sex-specific training programs to optimize performance in high-intensity sports, such as rugby sevens. Full article

Among the most promising alloys for photovoltaic applications is copper–indium–gallium–selenide (CIGS) because of its enhanced optical properties. This study examines the influence of current density and pulse timing on the electrodeposition of Cu(In, Ga)Se₂ (CIGS) thin films from a dilute electrolyte. It assesses how these parameters affect deposition quality, film characteristics, and device performance. CIGS absorber layers were electrodeposited using a pulsed-current method, with systematic variations in current density and pulse on/off durations in a low-concentration solution. The deposited precursors were subsequently selenized and incorporated into fully assembled CIGS solar cell architectures. Structural characteristics were analyzed by X-ray diffraction (XRD), whereas composition and elemental distribution were assessed by energy-dispersive X-ray spectroscopy (EDS). Optical properties pertinent to photovoltaic performance were evaluated through transmittance and reflectance measurements. The results indicate that moderate current densities, when combined with brief off-times, produce dense, microcrack-free films exhibiting enhanced crystallinity and near-stoichiometric Cu/(In + Ga) and Ga/(In + Ga) ratios, in contrast to films deposited at higher current densities and extended off-times. These optimized pulse parameters also produce absorber layers with advantageous optical band gaps and improved device performance. Overall, the study demonstrates that regulating pulse parameters in attenuated electrolytes is an effective strategy to optimize CIGS film quality and to facilitate the advancement of economical, solution-based fabrication methods for high-performance CIGS solar cells. Full article

This study explores the intestinal microbiota of eight 18-month-old male alpacas from two distinct high-altitude regions in Peru: the Wet Puna (4200 m above sea level) and the Dry Puna (4900 m above sea level). Using 16S rRNA and 18S rRNA metabarcoding, microbial communities of bacteria, archaea, fungi, and protists were analyzed from the first compartment of the stomach (C1) to investigate the diversity, taxonomic composition, and correlations with hematological parameters. Significant differences in microbial diversity and composition were observed between regions, driven by dietary and environmental factors. The Wet Puna exhibited greater alpha diversity in bacterial and fungal communities, while beta diversity highlighted distinct microbial compositions. Key taxa, such as Prevotella ruminicola and Acetitomaculum, were associated with energy metabolism and host adaptation, whereas methanogenic archaea (Methanobrevibacter, Methanosphaera) dominated in the Dry Puna, reflecting adaptations to arid conditions. Correlations between microbial taxa and hematological variables, such as Acetitomaculum with red blood cell count and Eremoplastron with neutrophil percentage, emphasize the complex interplay between microbiota and host physiology. These findings contribute to understanding microbial adaptations in high-altitude livestock and provide practical insights for enhancing alpaca management and conservation strategies through tailored nutritional approaches and sustainable grazing practices. Full article