Search Results (625)

The process of urbanization has intensified the urban heat environment, with the degradation of thermal conditions closely linked to the morphological characteristics of different functional zones. This study delineated urban functional areas using a multivariate dataset and investigated the seasonal and threshold effects of landscape and architectural features on land surface temperature (LST) through boosted regression tree (BRT) modeling and Spearman correlation analysis. The key findings are as follows: (1) LST exhibits significant seasonal variation, with the strongest urban heat island effect occurring in summer, particularly within industry, business, and public service zones; residence zones experience the greatest temperature fluctuations, with a seasonal difference of 24.71 °C between spring and summer and a peak temperature of 50.18 °C in summer. (2) Fractional vegetation cover (FVC) consistently demonstrates the most pronounced cooling effect across all zones and seasons. Landscape indicators generally dominate the regulation of LST, with their relative contribution exceeding 45% in green land zones. (3) Population density (PD) exerts a significant, seasonally dependent dual effect on LST, where strategic population distribution can effectively mitigate extreme heat events. (4) Mean building height (MBH) plays a vital role in temperature regulation, showing a marked cooling influence particularly in residence and business zones. Both the perimeter-to-area ratio (LSI) and frontal area index (FAI) exhibit distinct seasonal variations in their impacts on LST. (5) This study establishes specific indicator thresholds to optimize thermal comfort across five functional zones; for instance, FVC should exceed 13% in spring and 31.6% in summer in residence zones to enhance comfort, while maintaining MBH above 24 m further aids temperature regulation. These findings offer a scientific foundation for mitigating urban heat waves and advancing sustainable urban development. Full article

The aim of this study was to develop a mathematical model to predict the body weight of tilapia fingerlings using variables obtained through computer vision. A total of 2092 tilapia fingerlings and juveniles, weighing between 10 and 100 g, were fasted for 12 h, anesthetized, weighed, and photographed using an iPhone 12 Pro Max at 33 cm height in a closed container with different bottom colors. Images were segmented using Roboflow’s instance segmentation model, achieving 99.5% mean average precision, 99.9% precision, and 100% recall. From the segmented images, area, perimeter, major axis (MA), minor axis (SA), X and Y centroids, compactness, eccentricity, and the MA/SA ratio were extracted. Seventy percent of the data was used to build the model, and 30% for validation. Stepwise multiple regression (backward selection) was performed, using body weight as the dependent variable. The prediction model was: −17.7677 + 0.0007539(area) – 0.0848303 (MA) – 0.108338(SA) + 0.0034496(CX). The validation model showed similar coefficients and R² = 0.99. The second validation, using observed versus predicted values, also yielded an R² of 0.99 and a mean absolute error of 1.57 g. Correlation and principal component analyses revealed strong positive associations among body weight, area, axes, and predicted values. Computer vision proved effective for predicting tilapia fingerlings’ weight. Full article

The habenula (Hb) of the epithalamus is formed of the medial (MHb) and lateral (LHb) parts. The improper functioning of the Hb may lead to depression and anxiety. The glutamate excitotoxicity is accompanied by astroglia reactivity and leads to the damage of nervous system structures. The aim of the study was to assess the influence of monosodium glutamate (MSG) administrated subcutaneously to rats in doses of 2 g/kg b.w. (I) and 4 g/kg b.w. (II), on astroglia in the MHb and LHb. Based on immunohistochemical reactions, the morphology, number of astrocytes immunoreactive for glial fibrillary acidic protein (GFAP-IR) and S100β protein (S100β-IR), and their surface area, perimeter, number and length of processes, and cytoplasmic-nuclear immunostaining intensity for the studied proteins were assessed. In the MHb of animals receiving MSG, especially at a high dose, hypertrophy and an increase in the number of GFAP-IR and S100β-IR cells were demonstrated. In the LHb, only hypertrophy of processes in S100β-positive glia was observed. The immunostaining intensity increased in GFAP-IR glia and decreased in S100β-IR cells only in animals from group I. The results revealed that astroglia respond to MSG depending on its dose and the Hb part. This different behavior of glia may indicate their different sensitivity and resistance to damaging factors. Full article

Potato (Solanum tuberosum L.) crop yields may be reduced by nitrogen deficiency stress tolerance. An evaluation of 144 tetraploid potato genotypes was carried out during two consecutive seasons (2019 and 2020), with the objective of characterizing their variability in key physiological and agronomic parameters. Physiological parameters included chlorophyll content and fluorescence, stomatal conductance, NDVI, leaf area, and perimeter, while agronomic characteristics such as yield, tuber fresh weight, tuber number, starch content, dry matter, and reducing sugars were evaluated. To genotype the population, the GGP V3 Potato array was used, generating 18,259 high-quality SNP markers. Marker–trait association analysis was conducted using the GWASpoly package in R, applying Q + K linear mixed models to enhance precision. This methodology enabled the identification of 18 SNP markers that exhibited statistically significant associations with the traits analyzed in both trials and periods, relating them to genes whose functional implication has already been described. Genetic loci associated with chlorophyll content and tuber number were detected across non-stress and stress treatments, while markers linked to leaf area and leaf perimeter were identified specifically under nitrogen deficiency stress. The genomic distribution of these markers revealed that genetic markers or single-nucleotide polymorphisms (SNPs) correlated with phenotypic traits under non-stress conditions were predominantly located on chromosome 11, whereas SNPs linked to stress responses were mainly identified on chromosomes 2 and 3. These findings contribute to understanding the genetic mechanisms underlying potato tolerance to nitrogen deficiency stress, offering valuable insights for the development of future marker-assisted selection programs aimed at improving nitrogen use efficiency and stress resilience in potato breeding. Full article

To address the problems of traditional methods that rely on destructive sampling, the poor adaptability of fixed equipment, and the susceptibility of single-view angle measurements to occlusions, a non-destructive and portable device for three-dimensional phenotyping and biomass detection in lettuce was developed. Based on the Structure-from-Motion Multi-View Stereo (SFM-MVS) algorithms, a high-precision three-dimensional point cloud model was reconstructed from multi-view RGB image sequences, and 12 phenotypic parameters, such as plant height, crown width, were accurately extracted. Through regression analyses of plant height, crown width, and crown height, and the R² values were 0.98, 0.99, and 0.99, respectively, the RMSE values were 2.26 mm, 1.74 mm, and 1.69 mm, respectively. On this basis, four biomass prediction models were developed using Adaptive Boosting (AdaBoost), Support Vector Regression (SVR), Gradient Boosting Decision Tree (GBDT), and Random Forest Regression (RFR). The results indicated that the RFR model based on the projected convex hull area, point cloud convex hull surface area, and projected convex hull perimeter performed the best, with an R² of 0.90, an RMSE of 2.63 g, and an RMSEn of 9.53%, indicating that the RFR was able to accurately simulate lettuce biomass. This research achieves three-dimensional reconstruction and accurate biomass prediction of facility lettuce, and provides a portable and lightweight solution for facility crop growth detection. Full article

The present study aims to investigate the multi-year effects (5 years) of individualized whole-body vibration (WBV) on locomotion, postural control, and handgrip strength in a 68-year-old man with relapse remitting multiple sclerosis (PwRRMS). The dose–response relationship induced by a single session was quantified by determining the surface electromyographic activity (sEMG) of the participant. The participant wore an orthosis to limit the lack of foot dorsiflexion in the weakest limb during walking in daily life. The gait alteration during walking was assessed at 1, 2 and 3 km/h (without the orthosis) through angle–angle diagrams by quantifying the area, perimeter and shape of the loops, and the sEMG of leg muscles was recorded in both limbs. The evaluation of postural control was conducted during upright standing by quantifying the displacement of the center of pressure (CoP). The handgrip strength was assessed by measuring the force–time profile synchronized with the sEMG activity of upper arm muscles. The participant improved his ability to walk at higher speeds (2–3 km/h) without the orthosis. There were greater improvements in the area and perimeter of angle–angle diagrams for the weakest limb (Δ = 36–51%). The sEMG activity of the shank muscles increased at all speeds, particularly in the tibialis anterior of weakest limbs (Δ = 10–68%). The CoP displacement during upright standing decreased (Δ = 40–60%), whereas the handgrip strength increased (Δ = 32% average). Over the 5-year period of intervention, the individualized WBV improved locomotion, postural control and handgrip strength without side effects. Future studies should consider the possibility of implementing an individualized WBV in PwRRMS. Full article

Hydrodynamic cavitation is one of the most promising technologies for sustainable process intensification in the food, nutraceutical, and environmental sectors, due to its ability to generate highly localized and intense implosions. Venturi-type devices, known for their simplicity and efficiency, are widely used for non-thermal extraction, microbial inactivation, and cellular disruption. However, the effectiveness of cavitation critically depends on internal geometry—particularly the perimeter-to-area ratio (P/A), which influences both pressure gradient distribution and the density of nucleation sites. In this context, an innovative configuration based on the Reuleaux triangle is proposed, allowing for a significant increase in the P/A ratio compared to conventional circular-section devices. This theoretical study extends the Navier–Stokes and Rayleigh–Plesset models to describe bubble dynamics and assess the influence of geometric and rotational variants (VRAt) on the localization and intensity of cavitation collapse. The results suggest that optimized internal geometries can reduce treatment times, increase selectivity, and improve the overall energy efficiency of cavitation processes, offering strong potential for advanced and sustainable industrial applications. This work is entirely theoretical and is intended to support the future design and experimental validation of next-generation cavitating devices. Full article

Breeding programs often overlook the use of root traits. Therefore, we investigated the relevance of sorghum root traits in explaining its adaptation to combined drought and heat stress (CDHS). Six (i.e., three pre-release lines + three checks) sorghum genotypes were established at two low-altitude (i.e., <600 masl) locations with a long-term history of averagely very high temperatures in the beginning of the summer season, under two management (i.e., CDHS and well-watered (WW)) regimes. At each location, the genotypes were laid out in the field using a randomized complete block design (RCBD) replicated two times. Root trait data, namely root diameter (RD), number of roots (NR), number of root tips (NRT), total root length (TRL), root depth (RDP), root width (RW), width–depth ratio (WDR), root network area (RNA), root solidity (RS), lower root area (LRA), root perimeter (RP), root volume (RV), surface area (SA), root holes (RH) and root angle (RA) were gathered using the RhizoVision Explorer software during the pre- and post-flowering stage of growth. RSA traits differentially showed significant (p < 0.05) correlations with grain yield (GY) at pre- and post-flowering growth stages and under CDHS and WW conditions also revealing genotypic variation estimates exceeding 50% for all the traits. Regression models varied between pre-flowering (p = 0.013, R² = 47.15%, R² Predicted = 29.32%) and post-flowering (p = 0.000, R² = 85.64%, R² Predicted = 73.30%) growth stages, indicating post-flowering as the optimal stage to relate root traits to yield performance. RD contributed most to the regression model at post-flowering, explaining 51.79% of the 85.64% total variation. The Smith–Hazel index identified ICSV111IN and ASAREACA12-3-1 as superior pre-release lines, suitable for commercialization as new varieties. The study demonstrated that root traits (in particular, RD, RW, and RP) are linked to crop performance under CDHS conditions and should be incorporated in breeding programs. This approach may accelerate genetic gains not only in sorghum breeding programs, but for other crops, while offering a nature-based breeding strategy for stress adaptation in crops. Full article

The principles of fractal geometry have revolutionized the characterization of complex geometric objects since Benoit Mandelbrot’s groundbreaking work. Richardson’s method for determining the fractal dimension of boundaries laid the groundwork for Mandelbrot’s later developments in fractal theory. Despite extensive research, challenges remain in accurately calculating fractal dimensions, particularly when dealing with digital images and their inherent limitations. This study examines the numerical artifacts introduced by Richardson’s method when applied to the Von Koch Island, a classic fractal curve, and proposes a novel approach for computing fractal dimensions in image analysis. The Koch snowflake serves as a key example in this analysis; it serves to assess the algorithm of fractal dimension calculation as his theoretical one is known. However, there is a fundamental difference between the theoretical calculation of fractal dimension and the actual calculation of the fractal dimension from digital images with a given resolution undergoing discretization. We propose eight different calculation methods based on Richardson’s area–perimeter relationship: the Self-Convolution Patterns Research (SCPR) method accurately estimates the fractal dimension, as the 95% confidence interval includes the theoretical dimension. Full article

In this manuscript, we study the coverage of convex spherical domains by spherical circles. This question can be applied to the location of satellites, weather balloons, radio towers, etc. We present an upper bound on the number of spherical circles of radius r needed to cover a spherical convex domain K, in terms of the respective area and perimeter. Then, we calculate the asymptotic density of such cover, when the radius approaches zero. Full article

Background/Objectives: Anatomical and functional damage of the mitral valve (MV) apparatus in patients with dilated cardiomyopathy (DCM) is secondary to left ventricular (LV) injury, leading to functional mitral regurgitation (FMR). Real-time four-dimensional echocardiography (RT 4DE) is a useful imaging technique in different pathologies, including DCM. Left atrial (LA) strain, as measured by left atrium quantification software, is an accurate technique for evaluating increased filling pressure. The MV has a complex three-dimensional morphology and motion. Four-dimensional echocardiography (4DE) has revolutionized clinical imaging of the mitral valve apparatus. This study aims (1) to characterize the mitral annulus (MA) parameters in patients with DCM and advanced-stage heart failure (HF) according to etiology and (2) to find correlations between left atrial function and MA remodeling in this group of patients, using 4DE quantification software. Methods: A total of 82 patients with DCM and an LV ejection fraction ≤ 40% were recruited. Conventional 2DE and RT 4DE were conducted in DCM patients with a compensated phase of HF before discharge. The measured parameters were left atrial reservoir strain (LASr), annular area (AA), annular perimeter (AP), anteroposterior diameter (A-Pd), posteromedial to anterolateral diameter (PM-ALd), commissural distance (CD), interregional distance (ITD), annular height (AH), nonplanar angle (NPA), tenting height (TH), tenting area (TA), and tenting volume (TV). Results: Measured parameters revealed more advanced damage of LA and MA parameters in ischemic compared to nonischemic etiology. Univariate analysis identified AA, AP, A-Pd, PM-ALd, CD, ITD, TH, TA, and TV (p < 0.0001) as determinants of LASr. Including these parameters in a stepwise multivariate logistic regression, PM-ALd (p = 0.03), TH (p = 0.043), and TV (p = 0.0001) were the best predictors of LAsr in these patients. Conclusions: The results of this study revealed the correlation between LA function depression and MA remodeling in patients with DCM. Full article

The integration of traditional geomorphological approaches with advanced artificial intelligence techniques represents a promising frontier in flood risk assessment for arid regions. This study presents a comprehensive analysis of the Wadi Ranuna basin in Medina, Saudi Arabia, combining detailed morphometric parameters with advanced Geospatial Artificial Intelligence (GeoAI) algorithms to enhance flood susceptibility modeling. Using digital elevation models (DEMs) and geographic information systems (GISs), we extracted 23 morphometric parameters across 67 sub-basins and applied XGBoost, Random Forest, and Gradient Boosting (GB) models to predict both continuous flood susceptibility indices and binary flood occurrences. The machine learning models utilize morphometric parameters as input features to capture complex non-linear interactions, including threshold-dependent relationships where the stream frequency impact intensifies above 3.0 streams/km², and the compound effects between the drainage density and relief ratio. The analysis revealed that the basin covers an area of 188.18 km² with a perimeter of 101.71 km and contains 610 streams across six orders. The basin exhibits an elongated shape with a form factor of 0.17 and circularity ratio of 0.23, indicating natural flood-moderating characteristics. GB emerged as the best-performing model, achieving an RMSE of 6.50 and an R² value of 0.9212. Model validation through multi-source approaches, including field verification at 35 locations, achieved 78% spatial correspondence with documented flood events and 94% accuracy for very high susceptibility areas. SHAP analysis identified the stream frequency, overland flow length, and drainage texture as the most influential predictors of flood susceptibility. K-Means clustering uncovered three morphometrically distinct zones, with Cluster 1 exhibiting the highest flood risk potential. Spatial analysis revealed 67% of existing infrastructure was located within high-risk zones, with 23 km of major roads and eight critical facilities positioned in flood-prone areas. The spatial distribution of GBM-predicted flood susceptibility identified high-risk zones predominantly in the central and southern parts of the basin, covering 12.3% (23.1 km²) of the total area. This integrated approach provides quantitative evidence for informed watershed management decisions and demonstrates the effectiveness of combining traditional morphometric analysis with advanced machine learning techniques for enhanced flood risk assessment in arid regions. Full article

Urban green spaces (UGS) serve as critical mitigators of urban heat islands (UHIs), yet the scale-dependent mechanisms through which UGS morphology regulates thermal effects remain insufficiently understood. This study investigates the multi-scale relationships between UGS spatial patterns and cooling effects in Macao, employing morphological spatial pattern analysis (MSPA) to characterize UGS configurations and geographically weighted regression (GWR) to examine city-scale thermal interactions, complemented by patch-scale buffer analyses of area, perimeter, and landscape shape index effects. Results demonstrate that high-UGS-integrity areas significantly enhance cooling capacity (area with proportion of core ≥35% showing optimal performance), while fragmented elements (branches, edges) exacerbate UHIs, with patch-scale analyses revealing nonlinear threshold effects in cooling efficiency. A tripartite classification of UGS by cooling capacity identifies strong mitigation types with optimal shape metrics and cooling extents. These findings establish a tripartite UGS classification system based on cooling performance and identify optimal morphological parameters, advancing understanding of thermal regulation mechanisms in urban environments. This research provides empirical evidence for UGS planning strategies prioritizing core area conservation, morphological optimization, and seasonal adaptation to improve urban climate resilience, offering practical insights for sustainable development in high-density coastal cities. Full article

This study utilizes UAV-based LiDAR to analyze doline microtopography within a karst mountainous terrain. The study area, ‘Gulneomjae’ in Mungyeong City, South Korea, features steep slopes, limited accessibility, and abundant vegetation—conditions that traditionally hinder accurate topographic surveying. UAV LiDAR data were acquired using the DJI Matrice 300 RTK equipped with a Zenmuse L2 sensor, enabling high-density point cloud generation (98 points/m²). The point clouds were processed to remove non-ground points and generate a 0.25 m resolution DEM using TIN interpolation. A total of seven dolines were detected and delineated, and their morphometric characteristics—including area, perimeter, major and minor axes, and elevation—were analyzed. These results were compared with a 1:5000-scale DEM derived from the 2013 National Basic Map. Visual and numerical comparisons highlighted significant improvements in spatial resolution and feature delineation using UAV LiDAR. Although the 1:5000-scale DEM enables general doline detection, UAV LiDAR facilitates more precise boundary extraction and morphometric analysis. The study demonstrates the effectiveness of UAV LiDAR for detailed topographic mapping in complex karst terrains and offers a foundation for future automated classification and temporal change analysis. Full article

Thermal comfort of occupants is characterized by operative temperature (Top), while thermal environment is usually controlled by air temperature (Ta). For perimeter areas in buildings, the use of Ta in the control may lead to uncomfortable conditions. In this paper, thermostat controls based on air (TC-Ta) and Top (TC-Top) were compared in an office module based on different glazing ratio (GR) and indoor units. The results showed that, for a fan–coil system, with TC-Top, thermal comfort can be better, while for a ceiling panel system thermal comfort was similar with both controls. For fan coils, with TC-Top, Ta in offices became higher in the winter and lower in the summer, which improved thermal comfort along with increased energy use. For both GR conditions, the radiant panel could compensate for the presence of cold/warm surfaces, and it decreased the differences between the two controls, especially during cooling, which made the radiant system more suitable in large GR condition. With TC-Top, for the ceiling panel system, the increment of energy use was quite small. According to the results, under large GR, TC-Top was better for the fan–coil system to assure thermal comfort, and both control methods could be used in ceiling panel system. This study presents a comprehensive comparison of the two control strategies for both convective and radiant systems, highlighting their performance under varying GR conditions. The results also provide guidance for the optimal control of different indoor units under different GR conditions. Full article