Search Results (79)

The water status of plants is affected by abiotic and biotic environmental factors and influences the growth and yield formation of crops. Assessment of the leaf water content (LWC) of grapevine using hyperspectral imaging (1000–2500 nm) was investigated under controlled conditions for its potential to study the effects of the downy mildew pathogen Plasmopara viticola on LWC of host tissue in compatible and incompatible interactions. A calibration curve was established for the relationship between LWC and the Normalized Difference Leaf Water Index (NDLWI₁₉₃₇) that uses spectral information from the water absorption band and NIR for normalization. LWC was significantly lower for abaxial than for adaxial leaf sides, irrespective of grapevine genotype and health status. Reflecting details of leaf anatomy, vascular tissue exhibited effects reverse to intercostal areas. Effects of P. viticola on LWC coincided with the appearance of first sporangia on the abaxial side and increased during further pathogenesis. Continuous water loss ultimately resulted in tissue death, which progressed from the margins into central leaf areas. Tiny spots of brown leaf tissue related to the reaction of partial resistant cultivars could be monitored only at the sensor’s highest spatial resolution. Proximal sensing enabled an unprecedented spatial resolution of leaf water content in host–pathogen interactions and confirmed that resistance reactions may produce a combination of dead and still-living cells that enable the development of biotrophic P. viticola. Full article

Football is a complex game that requires combined technical, tactical, and psychological skills. The effect of training methods on players is crucial to improve their performance significantly. Different training methods can improve certain performance; however, the effect of combined training methodologies has not been sufficiently investigated. This study aimed to investigate the differential effects of small-sided games (SSGs), strength training (ST), and a combined training model (CTM) on the physical performance of soccer players. In this study, we analyzed 60 players in three groups. Two groups were trained independently with two single-training methods, small-sided games and a strength training model, and one group was trained independently with a double-training method, a combination of single-training methods. Before each training session, each group was given theoretical education specific to the training program they would perform. Eighteen physical measurements of the players were obtained using sensitive devices before and after they were completed. Four tree-based machine learning models, decision tree, random forest, gradient boosting, and extreme gradient boosting, were applied to solve the complex pattern of training strategies using the measurements. Extensive and comparative experiments were conducted to distinguish the groups of players. The distinction between the initial and final measurements was analyzed separately, and the extreme gradient boosting model achieved 0.73–0.80 and 1.00 accuracy for initial and final tests by outperforming other models. A superior model, XGBoost, was used to analyze the effective decisive factors that improved after the training sessions. The results showed that players in the double-training group demonstrated significantly greater improvements in skill performance compared to both single-training groups. In contrast, the skill gains observed in the single-training groups were modest and partially overlapping, indicating limited differentiation between them. These results suggest that integrated training programs may offer more comprehensive benefits and can inform evidence-based decision-making for coaches seeking to optimize physical development in soccer players. Full article

Leaf biochemical traits are crucial for understanding plant physiological status and ecological dynamics. Partial least squares regression (PLSR) models have been widely used to estimate leaf biochemical traits from spectral reflectance information. However, variations in sun–sensor geometry, the sensor field of view, and the random orientation of leaves can introduce multi-angular reflection properties that differ between leaf sides. In this context, the transferability of PLSR models across different leaf sides and viewing zenith angles (VZAs) remains unclear. This study investigated the potential of multi-angular spectral reflection from dorsiventral leaves to improve the transferability of PLSR models for estimating the leaf chlorophyll content (LCC) and equivalent water thickness (EWT). We compared models trained using multi-angular data from both leaf sides with models trained using nadir data (from the adaxial side, abaxial side, or their combination). The results show that the PLSR models trained with multi-angular data from both leaf sides outperformed the models trained with nadir data, achieving the highest accuracy in estimating biochemical traits (LCC: R² = 0.87, RMSE = 7.17 μg/cm², NRMSE = 10.71%; EWT: R² = 0.86, RMSE = 0.0015 g/cm², NRMSE = 10.00%). In contrast, the PLSR models trained using single-angle reflection from either the adaxial or abaxial side showed a lower estimation accuracy and greater variability across leaf sides and VZAs. The superior performance across datasets obtained under different measurement conditions (e.g., integrating spheres and leaf clips) further confirmed the improved generalizability of the PLSR model trained with multi-angular data from dorsiventral leaves. These findings highlight the potential of the multi-angular spectral reflection of dorsiventral leaves to enhance the estimation of biochemical traits across various leaf sides, viewing angles, and measurement conditions. They also underscore the importance of incorporating spectral diversity into model training for improved transferability. Full article

Negative pressure wound therapy (NPWT) is widely recognized for its efficacy in treating diabetic wounds, but the mechanisms involved in the wound healing process remain unclear. By examining changes in blood cytokine levels as molecular signaling precursors, we aim to provide a comprehensive cytokine profile to support adjunctive therapy research and clinical applications. A diabetic mouse wound model was established to compare cytokine profiles between NPWT-treated and standard dressing groups, identifying key signaling candidates that may facilitate wound healing. By integrating normal mouse data with large-scale cytokine analysis, we developed a time-stratified NPWT approach to track acute-phase cytokine fluctuations in diabetic conditions. NPWT did not significantly enhance coagulation-related cytokine expression but effectively reduced inflammation, albeit with a delayed regulatory effect compared to wild-type mice. A one-sided binomial test revealed that NPWT advanced the cytokine expression peak from 16 to 2 h, partially restoring the early healing pattern seen in normal mice and suggesting its potential role in modulating early-stage wound repair. These findings provide novel insights into early cytokine regulation during wound healing and highlight the potential of NPWT to inform therapeutic strategies. This refined monitoring approach may contribute to improved clinical decision-making and support enhanced wound management in diabetic patients. Full article

This paper proposes a modified polar coding-based selected mapping (PC-SLM) scheme to reduce the peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing (OFDM) systems. In the proposed transmitter, modulated signal vector for a subset of frozen bits, termed PAPR bits, are precomputed, enabling a single polar encoder and modulator to generate multiple modulation symbols, thereby significantly reducing the hardware complexity compared to existing PC-SLM schemes. To achieve side information (SI)-free transmission, a novel belief propagation (BP)-based receiver is introduced, incorporating a G-matrix-based early termination criterion and a frozen bit check (BP-GF) for joint detection and decoding. Simulation results show that the proposed scheme significantly reduces PAPR across various code lengths, with greater gains as the number of PAPR bits increases. Furthermore, for PC-SLM schemes employing the partially frozen bit method, the BP-GF-based receiver achieves a PAPR reduction and error correction performance comparable to that of the successive cancellation (SC)-based receiver. Additionally, the BP-GF-based receiver exhibits lower decoding latency than the successive cancellation list (SCL)-based receiver. Full article

This study systematically explored the impact of the spatial metaphor of time on attentional bias using visual order stimuli. Three experiments were conducted. Experiment 1, comprising Experiments 1a and 1b, investigated how the spatial metaphor of time shaped attentional bias across five disorder levels. Experiment 1a examined horizontal orientations, while Experiment 1b focused on vertical orientations. Experiment 2 compared attentional biases toward stimuli with the same disorder level in both orientations. The key distinction between the stimuli was that one represented short-term memory, while the other did not involve memory. Building on the findings of Experiment 2, Experiment 3 compared attentional biases between fully ordered structures (intact Gestalt structures) as non-memory representations and partially disordered structures in short-term memory. The results revealed a significant preference for future-related information, particularly on the right side in horizontal orientations. Short-term memory representations enhanced attentional attraction and triggered inhibition of return (IOR), while fully ordered structures attracted attention as effectively as partially disordered structures, thereby neutralizing attentional biases. Overall, this study contributes to a deeper understanding of the cognitive mechanisms underlying visual attention and the influence of temporal metaphors. Full article

Anaerobic ammonium oxidation (anammox) technologies have attracted substantial interest due to their advantages over traditional biological nitrogen removal processes, including high efficiency and low energy demand. Currently, multiple side-stream applications of the anammox coupling process have been developed, including one-stage, two-stage, and three-stage systems such as completely autotrophic nitrogen removal over nitrite, denitrifying ammonium oxidation, simultaneous nitrogen and phosphorus removal, partial denitrification-anammox, and partial nitrification and integrated fermentation denitritation. The one-stage system includes completely autotrophic nitrogen removal over nitrite, oxygen-limited autotrophic nitrification/denitrification, aerobic de-ammonification, single-stage nitrogen removal using anammox, and partial nitritation. Two-stage systems, such as the single reactor system for high-activity ammonium removal over nitrite, integrated fixed-film activated sludge, and simultaneous nitrogen and phosphorus removal, have also been developed. Three-stage systems comprise partial nitrification anammox, partial denitrification anammox, simultaneous ammonium oxidation denitrification, and partial nitrification and integrated fermentation denitritation. The performance of these systems is highly dependent on interactions between functional microbial communities, physiochemical parameters, and environmental factors. Mainstream applications are not well developed and require further research and development. Mainstream applications demand a high carbon/nitrogen ratio to maintain levels of nitrite-oxidizing bacteria, high concentrations of ammonium and nitrite in wastewater, and retention of anammox bacteria biomass. To summarize various aspects of the anammox processes, this review provides information regarding the microbial diversity of different genera of anammox bacteria and the engineering aspects of various side streams and mainstream anammox processes for wastewater treatment. Additionally, this review offers detailed insights into the challenges related to anammox technology and delivers solutions for future sustainable research. Full article

Partial discharge is an important symptom of cable aging, and timely detection of potential defects is of great significance to ensure the stability and safety of the power supply. However, due to the diversity of inspection equipment and information blockage, the staff often show blindness to the partial discharge spectrum and the defects corresponding to the spectrum. In view of this phenomenon, a partial discharge spectrum recognition method based on a convolutional neural network was developed. Firstly, a database of typical partial discharge spectrum was established, including partial amplifiers in the laboratory and at the work site, and then the convolutional neural network was used to train the defect spectral library. This paper proposes a processing technology for the on-site partial discharge spectrum; the unified grayscale image is obtained by grayscale processing, linearized stretching and size unification, and then the shape and color feature parameters are extracted according to the grayscale image, which solves the image distortion and statistical spectrum movement caused by the on-site environment or photographic angle on the user side. The partial discharge type can be obtained by comparing the processed spectrum with the database through the intelligent terminal, which greatly improves the accuracy and efficiency of on-site operations. Full article

In modern (5G) and future Multi-User (MU) wireless communication systems Beyond 5G (B5G) using Multiple-Input Multiple-Output (MIMO) technology, base stations with a large number of antennas communicate with many mobile stations. This technology is becoming especially relevant in modern multi-user wireless sensor networks in various application scenarios. The problem of organizing an MU mode on the downlink has arisen, which can be solved by precoding at the Base Station (BS) without using additional channel frequency–time resources. In order to utilize an efficient precoding algorithm at the base station, full Channel State Information (CSI) is needed for each mobile station. Transmitting this information for massive MIMO systems normally requires the allocation of high-speed channel resources for the feedback. With limited feedback, reduced information (partial CSI) is used, for example, the codeword from the codebook that is closest to the estimated channel vector (or matrix). Incomplete (or inaccurate) CSI causes interference from the signals, transmitted to neighboring mobile stations, that ultimately results in a decrease in the number of active users served. In this paper, we propose a new downlink precoding approach for MU-MIMO systems that also uses codebooks to reduce the information transmitted over a feedback channel. A key aspect of the proposed approach, in contrast to the existing ones, is the transmission of new, uncorrelated information in each cycle, which allows for accumulating CSI with higher accuracy without increasing the feedback overhead. The proposed approach is most effective in systems with dynamic user selection. In such systems, increasing the accuracy of CSI leads to an increase in the number of active users served, which after a few cycles, can reach a maximum value determined by the number of transmit antennas at the BS side. This approach appears to be promising for addressing the challenges associated with current and future massive MIMO systems, as evidenced by our statistical simulation results. Various methods for extracting and transmitting such uncorrelated information over a feedback channel are considered. In many known publications, the precoder, codebooks, CSI estimation methods and other aspects of CSI transmission over a feedback channel are separately optimized, but a comprehensive approach to jointly solving these problems has not yet been developed. In our paper, we propose to fill this gap by combining a new approach of precoding and CSI estimation with CSI accumulation and transmission over a feedback channel. Full article

The Chang’e-6 (CE-6) landing area on the far side of the Moon is located in the southern part of the Apollo basin within the South Pole–Aitken (SPA) basin. The statistical analysis of impact craters in this region is crucial for ensuring a safe landing and supporting geological research. Aiming at existing impact crater identification problems such as complex background, low identification accuracy, and high computational costs, an efficient impact crater automatic detection model named YOLOv8-LCNET (YOLOv8-Lunar Crater Net) based on the YOLOv8 network is proposed. The model first incorporated a Partial Self-Attention (PSA) mechanism at the end of the Backbone, allowing the model to enhance global perception and reduce missed detections with a low computational cost. Then, a Gather-and-Distribute mechanism (GD) was integrated into the Neck, enabling the model to fully fuse multi-level feature information and capture global information, enhancing the model’s ability to detect impact craters of various sizes. The experimental results showed that the YOLOv8-LCNET model performs well in the impact crater detection task, achieving 87.7% Precision, 84.3% Recall, and 92% AP, which were 24.7%, 32.7%, and 37.3% higher than the original YOLOv8 model. The improved YOLOv8 model was then used for automatic crater detection in the CE-6 landing area (246 km × 135 km, with a DOM resolution of 3 m/pixel), resulting in a total of 770,671 craters, ranging from 13 m to 19,882 m in diameter. The analysis of this impact crater catalogue has provided critical support for landing site selection and characterization of the CE-6 mission and lays the foundation for future lunar geological studies. Full article

Silicon carbide (SiC) has significant potential as a third-generation semiconductor material due to its exceptional thermal and electronic properties, yet its high hardness and brittleness make processing costly and complex. This study introduces ultraviolet laser ablation as a method for direct SiC material removal, investigating the effects of varying scanning speeds on surface composition, hardness, and ablation depth. The results indicate optimal processing speeds for the Si and C faces at 200 mm/s and 100 mm/s, respectively. Ablation depth is linearly correlated with laser repetitions, achieving a 25% improvement in removal efficiency at 100 mm/s on the C face compared to higher speeds. A composition analysis shows that the Si and C faces of SiC exhibit consistent ratios of Si, O, and C both before and after ablation. Post-ablation, the proportion of Si and C decreases with an increased presence of oxygen. At scanning speeds below 200 mm/s, the variation in speed has minimal effect on the compositional ratios, indicating a stable elemental distribution across the surface despite differences in processing speed. Hardness testing indicates an initial hardness of 13,896 MPa for the C face, higher than that of the Si face, with both surfaces experiencing a drop to less than 1% of their original hardness (below 50 MPa) after ablation. Lattice structure analysis shows Moissanite-5H SiC and cubic silicon formation on the Si face, while the C face retains partial SiC structure. This study found that when laser parameters are used to process SiC, the processing parameters required on both sides are different and provide important reference information for future industrial processing applications to shorten the time and process cost of SiC surface thinning. Full article

Partially cable-stayed bridges have the characteristics of continuous rigid-frame bridges and cable-stayed bridges, making them a novel composite bridge system. This study focuses on the construction project of a multi-tower high-pier curved partially cable-stayed bridge to investigate the bridge’s stability during construction. The Midas/Civil software was used to establish a model for key construction stages of the bridge, considering structural linear elasticity and geometric nonlinearity. The study examines the impact of static wind loads, asymmetric construction of the main girder, closure sequence, and the load and detachment of the hanging basket on the bridge’s stability during construction. The results indicate that static wind loads have a significant impact on structural geometric nonlinearity, with a maximum reduction of 4.99%. Asymmetric construction at both ends of the main girder can cause structural instability and should be avoided. The geometric nonlinearity stability coefficient for the hanging basket load decreased by 10.83% during the maximum no-cable stage and by 7.84% during the cable stage, significantly affecting the stability during construction. A bridge closure sequence of side-span, secondary midspan, and midspan provides the most stable condition during the construction phase. The results of this study can inform the construction of similar partially cable-stayed bridges. Full article

This work introduces the notion of a hesitant bipolar-valued intuitionistic fuzzy graph (HBVIFG), which reflects four different characterizations: membership with positive/negative aspects and non-membership with positive/negative aspects, incorporating multi-dimensional alternatives in all of its information. HBVIFG generalizes both HBVFG and BVHFG due to its diversified nature in observing four perspectives along with multiple attributes in a piece of information. Numerous studies, examples, and graphical representations emphasize the concept’s distinctiveness and importance. The following graph theory terms are defined: strong directed HBVIFG, full directed HBVIFG, directed spanning HBVIFSG, directed HBVIFSG, and partial directed hesitant bipolar-valued intuitionistic fuzzy subgraph (HBVIFSG). Examples of operations utilizing two HBVIFGs are Cartesian, direct, lexicographical, and strong products. A scenario is used to generate the mapping of relations, which includes homomorphism, isomorphism, weak isomorphism, and co-weak isomorphism. We describe a directed HBVIFG application that employs an algorithm to determine the most dominant person and self-persistent person in a social system and a comparative study is also provided. The proposed method provides a more detailed framework for assessing the most dominant and self-persistent individual in a social network across multi-level attributes along with positive and negative side membership and non-membership grades in each element of a network. Full article

Background: Thrombosis is the abnormal formation of blood clots within blood vessels; it results from an imbalance between fibrinolytic, pro-coagulant, and anticoagulant systems. Pediatric arterial thrombosis, especially related to catheter usage, is an emerging issue with limited evidence. This study evaluates the efficacy of enoxaparin in treating arterial thrombosis in pediatric patients at a single center. Methods: A retrospective single-center study included children under 14 years old diagnosed with catheter-related arterial thrombosis (CAT) and treated with low-molecular-weight heparin (LMWH) at King Abdulaziz Medical City between 2016 and 2021. Patients without follow-up at our institution or those using other anticoagulants were excluded. Data collected included age, sex, weight, catheter type, location and degree of thrombosis, ultrasonographic results, treatment duration, hemoglobin and platelet levels, and missed refills. Radiologic confirmation of CAT was required for inclusion. Results: This study included 111 children treated with enoxaparin for non-cerebral arterial thrombosis. The median age at diagnosis was 3 months, with 58% being male patients. Most cases (87%) involved cardiac catheterization, and all were confirmed using ultrasonography. Complete thrombus resolution was achieved in 90% of patients, partial resolution in 8.1%, and 1.8% had no resolution. The median duration of enoxaparin therapy was 20 days. Multivariate analysis indicated that higher age and lower body weight were associated with a higher risk of non-resolution. Indwelling catheters also posed a greater risk of non-resolution compared to cardiac catheters. Conclusions: Enoxaparin proved effective in treating catheter-related arterial thrombosis in children, with high resolution rates and few side effects. This study helps inform treatment strategies in pediatric thrombosis management and highlights the need for further research to refine treatment durations and address patient risk factors. Full article

(1) Background: Some cancer patients do not experience tumour shrinkage but are still at risk of experiencing unwanted treatment side effects. Radiomics refers to mining biomedical images to quantify textural characterization. When radiomics features are labelled with treatment response, retrospectively, they can train predictive machine learning (ML) models. (2) Methods: Radiomics features were determined from lymph node (LN) segmentations from treatment-planning CT scans of head and neck (H&N) cancer patients. Binary treatment outcomes (complete response versus partial or no response) and radiomics features for n = 71 patients were used to train support vector machine (SVM) and k-nearest neighbour (k-NN) classifier models with 1–7 features. A deep texture analysis (DTA) methodology was proposed and evaluated for second- and third-layer radiomics features, and models were evaluated based on common metrics (sensitivity (%S_n), specificity (%S_p), accuracy (%Acc), precision (%Prec), and balanced accuracy (%Bal Acc)). (3) Results: Models created with both classifiers were found to be able to predict treatment response, and the results suggest that the inclusion of deeper layer features enhanced model performance. The best model was a seven-feature multivariable k-NN model trained using features from three layers deep of texture features with %S_n = 74%, %S_p = 68%, %Acc = 72%, %Prec = 81%, %Bal Acc = 71% and with an area under the curve (AUC) the receiver operating characteristic (ROC) of 0.700. (4) Conclusions: H&N Cancer patient treatment-planning CT scans and LN segmentations contain phenotypic information regarding treatment response, and the proposed DTA methodology can improve model performance by enhancing feature sets and is worth consideration in future radiomics studies. Full article