Search Results (209)

Orchard wind-assisted spraying technology relies on auxiliary airflow to disturb the canopy and improve droplet deposition uniformity. However, there are few effective means of quantitatively assessing the dynamic response of fruit tree leaves to airflow or the changes in airflow patterns within the canopy in real time. To address this, this study proposed an online monitoring method for the aerodynamic characteristics of fruit tree leaves using strain gauge sensors. The flexible strain gauge was affixed to the midribs of leaves from peach, pear and apple trees. Leaf deformations were captured with high-speed video recording (100 fps) alongside electrical signals in controlled wind fields. Bartlett low-pass filtering and Fourier transform were used to extract frequency-domain features spanning between 0 and 50 Hz. The AdaBoost decision tree model was used to evaluate classification performance across frequency bands. The results demonstrated high accuracy in identifying wind exposure (98%) for pear leaf and classifying the three leaf types (κ = 0.98) within the 4–6 Hz band. A comparison with the frame analysis of high-speed video recordings revealed a time error of 2 s in model predictions. This study confirms that strain gauge sensors combined with machine learning could efficiently monitor fruit tree leaf responses to external airflow in real time. It provides novel insights for optimizing wind-assisted spray parameters, reconstructing internal canopy wind field distributions and achieving precise pesticide application. Full article

This paper presents a hybrid architecture for automatic sentiment analysis of Kazakh-language political discourse. The Kazakh language is characterized by an agglutinative structure, a complex word-formation system, and the limited availability of digital resources, which significantly complicates the application of standard neural network approaches. To account for these characteristics, a multi-level system was developed that combines morphological and syntactic analysis rules, ontological relationships between political concepts, and multilingual representations of the XLM-R model, used in zero-shot mode. A corpus of 12,000 sentences was annotated for sentiment polarity and used for training and evaluation, while Universal Dependencies annotation was applied for morpho-syntactic analysis. Rule-based components compensate for errors related to affixation variability, modality, and directive constructions. An ontology comprising over 300 domain concepts ensures the correct interpretation of set expressions, terms, and political actors. Experimental results show that the proposed hybrid architecture outperforms both neural network baseline models and purely rule-based solutions, achieving Macro-F1 = 0.81. Ablation revealed that the contribution of modules is unevenly distributed: the ontology provides +0.04 to Macro-F1, the UD syntax +0.08, and the rule-based module +0.11. The developed system forms an interpretable and robust assessment of tonality, emotions, and discursive strategies in political discourse, and also creates a basis for further expansion of the corpus, additional training of models, and the application of hybrid methods to other tasks of analyzing low-resource languages. Full article

This article examines augmented plurals in Russian, mostly focusing on those in -ĭj- (e.g., pero/perʲja ‘feather.sg/pl’). The accentual behavior of -ĭj-plurals is sensitive to animacy: while inanimates show stem-final stress, animates appear with inflectional stress. This is explained by different constituent structures: while for inanimates, -ĭj- combines with the stem, animate stems require complex suffix formation so as to not create neuter animates, which are not tolerated in Russian. The position of the accent is then derived from the usual assumptions about Russian stress and the hypothesis that -ĭj- is accented but unaccentable. Other plural augments are also discussed. Full article

Bantu languages represent a typical example of how morphology and syntax are deeply intertwined. Indeed, these agglutinative languages employ affixes, hence morphemes, to express relations that in other languages—like Italian or English—are conveyed by independent words, in syntax. In particular, in this work, I am going to discuss Bantu causative and applicative constructions, which are formed by means of verbal extensions, i.e., affixes that adjoin to verb stems in order to derive complex syntactic structures. Through the comparison with other languages, in particular Italian and English, we will argue that a biclausal analysis of Bantu causatives is tenable and, even more, this analysis can be extended to applicative and ditransitive verbs, taking into consideration the different behaviour of symmetrical and asymmetrical Bantu languages. Finally, we will discuss the peculiar situation of Italian, which behaves like symmetrical Bantu languages as concerns object pronominalization in the complex constructions under analysis; we will conclude that the co-occurrence of clitic pronouns is linked to their different morphological forms, which suggests that they occupy different positions in the clitic/affix string, underlying once more how morphology and syntax feed each other. Full article

Despite many raptors establishing urban populations globally, Golden Eagles (Aquila chrysaetos) tend to avoid urban areas, including while in flight. The contiguous cities of Reno and Sparks, NV, USA, host a dense guild of breeding raptors (>10 species) but Golden Eagles only nest in trees and cliffs in the wildlands immediately adjacent urban development. We affixed GPS transmitters to nine non-breeding Golden Eagles to monitor their local-scale movements from 2015 to 2017, and investigated whether they use the airspace associated with the urbanized landscape. We found that they moved throughout the wildlands adjacent to, but rarely entered (0.17% of point locations), the urban area. Given that the wildlands around the urban area contain montane forest, sagebrush, and grassland habitats, which support some of the prey that Golden Eagles consume the most (Lepus, Sylvilagus, Otospermophilus, and Marmota spp.), it is likely that they use the wildlands for dietary and nesting resources but avoid the urban habitat itself. Our study provides a snapshot of a single geographic area but parallels existing research elsewhere. Full article

Traditional environmental research remains affixed in fragmented metrics (e.g., CO₂ emissions or ecological footprints) that undermine the systemic equilibrium between economic demand and ecological regeneration. Biocapacity, representing the capacity of lands (crop and grazing), forests, and other natural systems, is the backbone of economic livelihoods and environmental resilience. Recent literature frequently calls for operationalizing models with robust environmental sustainability indicators, such as the load capacity factor (LF), a comprehensive compass that measures biocapacity (e.g., forests, croplands) relative to ecological footprint. For this purpose, the integrated model combined environment-related policies (regulations, ENRs), technologies (ERTs), sectoral structures, and LF, with the latest available data (2000–2022) of G20 economies. Results of the multiple tests, including feasible generalized least squares, sensitivity tests (alternate proxies), and panel-corrected standard errors, highlighted a paradox: even though ENRs and ERTs tend to improve environmental sustainability through forestation, land use, and green initiatives, the results showed adverse effects of both indicators on environmental sustainability (LF), reflecting a misalignment between policies and environmental outcomes. While industrialization, renewable energy use, and rising per capita income had enhanced environmental sustainability (LF) gains, structural frictions in the services, manufacturing, and trade sectors undermined these advantages, revealing diffusion lags and transitional lock-ins across sampled countries. With LF embedded as a new tool for sustainable governance of forests and land management, the paper advances three critical contributions: (i) uncovering paradoxical deteriorations in sustainability under misaligned policy and technology interventions, (ii) showing an imperative need for performance-based, adaptive, and innovation-financed policies, and (iii) demonstrating LF as a standard for positioning technology, economic transitions, and policy with ecological and cropland-forests resilience. Full article

Linear velocity is commonly used to estimate 1-repetition maximum (1RM) from a load–velocity profile (LVP), as well as prescribe training intensity. However, no study has assessed angular velocity, which may be more representative of joint motion. The purpose of this study was to compare the prediction of 1RM from linear velocity (1RM_linear) and angular velocity (1RM_angular) LVPs in men and women. Fourteen recreationally trained college-aged subjects (7 males, 7 females) completed 1RM testing on day 1, then a randomized submaximal (30–90% 1RM) squat protocol on day 2. Linear velocity was measured with a linear position transducer, while angular velocity was recorded using an accelerometer affixed to the thigh. 1RM_angular was not significantly different from actual 1RM (p = 0.951), with a trivial effect size (d = 0.02), and nearly perfect correlation with actual 1RM (r = 0.984). 1RM_linear had a near perfect correlation with actual 1RM (r = 0.991) but was significantly different than actual 1RM (p < 0.001) with a large effect size (d = 1.56). Additionally, 1RM_angular had a significantly (p = 0.020) lower absolute error (6.7 ± 5.3 kg) than 1RM_linear (12.9 ± 8.2 kg). Regardless of prediction method, males (12.9 ± 8.2 kg) had a greater absolute error in 1RM prediction than females (6.7 ± 5.2 kg). During submaximal loads, a significant load × gender interaction was observed for linear velocity (p < 0.001), with men showing faster velocities at 30% (p = 0.009) and 40% (p = 0.044) 1RM, with no significant interaction (p = 0.304) of main effect of gender (p = 0.116). Angular velocity may provide strength and conditioning coaches a more accurate 1RM prediction during submaximal sets of back squat than using linear velocity; however, neither meet all criteria to be considered highly valid. Lastly, the gender differences in linear velocity at submaximal exercises suggest gender-specific considerations in velocity-based training particularly at lighter loads. Full article

Part-of-speech (POS) tagging in low-resource, morphologically rich languages (LRLs/MRLs) remains challenging due to extensive affixation, high out-of-vocabulary (OOV) rates, and pervasive polysemy. We propose MRL-POS, a unified Transformer-CRF framework that dynamically selects informative affix features and integrates them with deep contextual embeddings via a novel dual-gating co-attention mechanism. First, a Dynamic Affix Selector adaptively adjusts n-gram ranges and frequency thresholds based on word length to ensure high-precision affix segmentation. Second, the Affix–Context Co-Attention Module employs two gating functions that conditionally amplify contextual dimensions with affix cues and vice versa, enabling robust disambiguation of complex and ambiguous forms. Third, Layer-Wise Attention Pooling aggregates multi-layer XLM-RoBERTa representations, emphasizing those most relevant for morphological and syntactic tagging. Evaluations on Uyghur, Kyrgyz, and Uzbek show that MRL-POS achieves an average F₁ of 84.10%, OOV accuracy of 84.24%, and Poly-F₁ of 72.14%, outperforming strong baselines by up to 8 F₁ points. By explicitly modeling the symmetry between morphological affix cues and sentence-level context through a dual-gating co-attention mechanism, MRL-POS achieves a balanced fusion that both preserves local structure and captures global dependencies. Interpretability analyses confirm that 89.1% of the selected affixes align with linguistic expectations. This symmetric design not only enhances robustness in low-resource and agglutinative settings but also offers a general paradigm for symmetry-aware sequence labeling tasks. Full article

Background: Accurate and stable instrument positioning is critical in dental implant procedures, particularly in anatomically constrained regions. Conventional navigation systems assume a static patient head, limiting adaptability in dynamic surgical conditions. This study proposes and validates a real-time motion compensation framework that integrates optical motion tracking with a collaborative robot to maintain tool alignment despite patient head movement. Methods: A six-camera OptiTrack Prime 13 system tracked rigid markers affixed to a 3D-printed human head model. Real-time head pose data were streamed to a Kuka LBR iiwa robot, which guided the implant handpiece to maintain alignment with a predefined target. Motion compensation was achieved through inverse trajectory computation and second-order Butterworth filtering to approximate realistic robotic response. Controlled experiments were performed using the MAiRA Pro M robot to impose precise motion patterns, including pure rotations (±30° at 10–40°/s), pure translations (±50 mm at 5–30 mm/s), and combined sinusoidal motions. Each motion profile was repeated ten times to evaluate intra-trial repeatability and dynamic response. Results: The system achieved consistent pose tracking errors below 0.2 mm, tool center point (TCP) deviations under 1.5 mm across all motion domains, and an average latency of ~25 ms. Overshoot remained minimal, with effective damping during motion reversal phases. The robot demonstrated stable and repeatable compensation behavior across all experimental conditions. Conclusions: The proposed framework provides reliable real-time motion compensation for dental implant procedures, maintaining high positional accuracy and stability in the presence of head movement. These results support its potential for enhancing surgical safety and precision in dynamic clinical environments. Full article

Subway stations are complex spaces with high passenger density and mobility, making evacuation efficiency particularly important. The position of evacuation signage is a key factor affecting the efficiency of passenger wayfinding. This study constructed a virtual subway station scenario by virtual reality technology (VR), recording and analyzing the evacuation time and exit selection of 60 participants. The results showed that hanging evacuation signage, with their superior visual advantages, can greatly improve passenger wayfinding efficiency, followed by signage affixed to walls and columns, and finally signage on the ground. This study has provided a theoretical basis for the scientific layout and optimization of evacuation signage positions in subway stations, thereby enhancing passenger safety and evacuation efficiency. Full article

Amirthalingamia macracantha (Joyeux and Baer, 1935) larvae, a member of the Gryporhynchidae family (Cestoda: Cyclophyllidea), are commonly found in a variety of African fish species, including Nile tilapia (Oreochromis niloticus, Linnaeus, 1758). Nonetheless, little is known regarding their existence in native Egyptian fish species. Two hundred O. niloticus were examined in the current investigation, using standard parasitological techniques to detect the presence of these larvae in different fish organs. According to this study’s findings, A. macracantha larvae were found in 35% of the microscopically examined samples as red nodules, attaching to the serosa of both the anterior and posterior sections of the intestine and stomach, respectively. The mean abundance of the infection was 3.5 ± 0.05 (CI 95% 3.4–3.5), and its mean intensity was 10 ± 1.7 (CI 95% 8.2–11.7). The existence of two rows of twenty rostellar hooks of varying lengths is the main characteristic of the parasite. The upper row consisted of four large hooks and six smaller ones, while the lower row contained smaller hooks of consistent length. According to histopathological analysis, the larvae with a hook-and-spiny rostellum were affixed to the stomach serosa of O. niloticus. Additionally, there was a notable presence of degranulated mast cells and lymphocytes of varying sizes within the stomach’s lamina propria, submucosa, and blood vessels, as well as a loss of gastric epithelium, fibrosis, and enlargement of submucosal lymph vessels. This study offers a succinct description of this larval stage, representing the first reported occurrence of its presence in Egyptian O. niloticus. Full article

This contribution studies the control of the yaw motion of large wind turbines. Two aspects are considered: the first is maximising the energy conversion by yawing the rotor in accordance with the wind direction. The other aspect is synchronising the control of all yaw actuators, which are affixed to the yaw gear rim. In a first phase, P and PI controllers are used in all control loops. Later on, the yaw controller and the synchronisers are replaced with nonlinear PI (NPI) controllers. Moreover, all actuator position P controllers are changed using nonlinear P (NP) controllers. Simulation experiments are carried out on the NREL 5 MW reference wind turbines. The results are very promising. Full article

Background/Objectives: For aging men experiencing lower urinary tract symptoms (LUTS), bladder diaries (BD) and uroflowmetry (UFM) are commonly used non-invasive diagnostic tools. However, bladder diaries often suffer from subjectivity and incomplete data, while traditional hospital-based uroflowmetry lacks convenience and repeatability. Therefore, there is a growing need for a user-friendly, artificial intelligence (AI)-powered at-home uroflow monitoring solution. This study aims to develop a novel, vibration-based home uroflowmetry system capable of recognizing uroflow curve patterns and measuring voiding parameters, and to compare its performance with other existing home-based uroflowmetry methods. Methods: Seventy-six male participants, all of whom provided informed consent, underwent uroflowmetry to assess voiding symptoms. An accelerometer affixed to the uroflowmeter’s urine container captured vibration signals, which were used to calculate the root mean square (RMS) values and maximum amplitude (Mmax). Simultaneously, the uroflowmeter recorded standard voiding parameters and generated uroflow curves. These vibration signals were then analyzed using a convolutional neural network (CNN) to classify six distinct uroflow curve patterns, aiding in diagnostic evaluation. Results: Seventy-six participants’ voiding volume ranged from 50 mL to 690 mL (median [Q1, Q3]: 160 [70.00, 212.50] mL). The correlation analysis revealed positive correlations between the vibration signals and voiding parameters, including the voided volume and RMS (R = 0.768, p < 0.001), Qmax and Mmax (R = 0.684, p < 0.001), voiding time and signal time (R = 0.838, p < 0.001), time to Qmax and time to Mmax (R = 0.477, p < 0.001). AI pattern recognition demonstrated high accuracy with all three indicators (precision, recall, and F1 score) surpassing 0.97. Conclusions: This AI-assisted vibration-based home uroflowmetry enables accurate voiding parameter measurement and uroflow pattern recognition, showing high precision, recall, and F1-score. It might offer a convenient solution for continuous and subjective bladder monitoring outside clinical settings. Full article

The implantable capsule grouting pile is a novel pile foundation technology in which a capsule is affixed to the side of the implanted pile to facilitate grouting and achieve extrusion-based reinforcement. This technique is designed to improve the bearing capacity of implanted piles in coastal areas with deep, soft soil. This study conducted model tests involving multiple grouting positions across different foundation types to refine the construction process and validate the enhancement of bearing capacity. Systematic measurements and quantitative analyses were performed to evaluate the earth pressure distribution around the pile, the resistance characteristics of the pile end, the evolution of side friction resistance, and the overall bearing performance. Special attention was given to variations in the lateral friction resistance adjustment coefficient under different working conditions. Furthermore, an actual case analysis was conducted based on typical soft soil geological conditions. The results indicated that the post-grouting process formed a dense soil ring through the expansion and extrusion of the capsule, resulting in increased soil strength around the pile due to increased lateral earth pressure. Compared to conventional piles, the grouted piles exhibited a synergistic improvement characterized by reduced pile end resistance, enhanced side friction resistance, and improved overall bearing capacity. The ultimate bearing capacity of model piles at different grouting depths across different foundation types increased by 6.8–22.3% compared with that of ordinary piles. In silty clay and clayey silt foundations, the adjustment coefficient η_s of lateral friction resistance of post-grouting piles ranged from 1.097 to 1.318 and increased with grouting depth. The findings contribute to the development of green pile foundation technology in coastal areas. Full article

Background: To overcome the limitations of conventional CRC (colorectal cancer) mouse models in replicating metastasis and enabling efficient therapeutic evaluation, we developed a novel implantation method using tissue adhesive to establish reproducible orthotopic and metastatic tumors. Conventional models using injection or suturing techniques often suffer from technical complexity, inconsistent tumor establishment, and limited metastatic reliability. Methods: We developed and validated a novel orthotopic and metastatic CRC model utilizing tissue adhesive for tumor transplantation. Uniform tumor fragments derived from bioluminescent HCT116/Luc xenografts were affixed to the cecum of nude mice. Tumor growth and metastasis were monitored through bioluminescence imaging and confirmed by the results of histological analysis of metastatic lesions. The model’s utility for therapeutic testing was evaluated using MK801, an NMDA receptor antagonist. Results: The biological-based model demonstrated rapid and reproducible tumor implantation (<5 min), consistent primary tumor growth, and robust metastasis to the liver and lungs. The biological-based approach achieved 80% tumor engraftment (4/5), with consistent metastasis to the liver and lungs in all mice, compared with lower and variable metastasis rates in injection (0%, 0/5) and suturing (20%, 1/5) methods. MK801 treatment significantly suppressed both primary tumor growth and metastasis, validating the model’s suitability for preclinical drug evaluation. Conclusions: By enabling rapid, reproducible, and spontaneous formation of metastatic lesions using a minimally invasive tissue adhesive technique, our model represents a significant methodological advancement that supports high-throughput therapeutic screening and bridges the gap between experimental modeling and clinical relevance in colorectal cancer research. Full article