Search Results (383)

Advances in sensor technology have significantly improved the efficiency and precision of agricultural spraying. Unmanned aerial vehicles (UAVs) are widely utilized for applying plant protection products (PPPs) and fertilizers, offering enhanced spatial control and operational flexibility. This study evaluated the performance of an autonomous UAV-based precision spraying system that applies variable rates based on zone levels defined in a prescription map. The system integrates real-time kinematic global navigation satellite system positioning with a proximity-triggered spray algorithm. Field experiments on a rice field were conducted to assess spray accuracy and fertilization efficacy with liquid fertilizer. Spray deposition patterns on water-sensitive paper showed that the graded strategy distinguished among zone levels, with the highest deposition in high-spray zones, moderate in medium zones, and minimal in no-spray zones. However, entry and exit deviations—used to measure system response delays—averaged 0.878 m and 0.955 m, respectively, indicating slight lags in spray activation and deactivation. Fertilization results showed that higher application levels significantly increased the grain-filling rate and thousand-grain weight (both p < 0.001), but had no significant effect on panicle number or grain count per panicle (p > 0.05). This suggests that increased fertilization primarily enhances grain development rather than overall plant structure. Overall, the system shows strong potential to optimize inputs and yields, though UAV path tracking errors and system response delays require further refinement to enhance spray uniformity and accuracy under real-world applications. Full article

The effects of administering 10 mL of maternal bovine appeasing substance (mBAS) or water (control; CT) at weaning (day 0) before transport on feedlot adaptation and efficiency were evaluated in twenty-two Angus-influenced heifers (n = 11/treatment) over 28 days. Body weight (BW), salivary cortisol, blood for complete blood cell count, rectal temperature, chute score and exit speed were collected on days 0, 14 and 27. Intake, feeding duration, frequency and rate, as well as activity and rumination were monitored daily using automated systems. Average daily gain (ADG) and gain-to-feed ratio (G:F) were calculated for each 14-day interval as well as for the entire feeding period. Treated heifers spent less time eating (p ≤ 0.06) on weeks 1 and 2, with greater feeding rate and activity (p < 0.01) in week 1, followed by reduced activity (p ≤ 0.05) in weeks 2, 3 and 4. Rumination was longer (p < 0.05) in weeks 3 and 4, coinciding with greater (p ≤ 0.05) final BW, ADG_0–27, ADG_14–27, and G:F_0–27, G:F_14–27. Lymphocyte and hematocrit were lower (p < 0.05) on days 14 and 27, respectively, and platelets tended to be greater (p = 0.08) than CT for the entire period. Treated heifers achieved numerically greater profit margins than CT. Overall, mBAS enhanced feedlot adaptability post-weaning, improving production efficiency, which may translate into potential profitability; however, this interpretation should be viewed cautiously considering some design limitations. Full article

The lossof ear tags in breeding pigs can lead to the loss or confusion of individual identity information. Timely and accurate detection, along with continuous tracking of breeding pigs that have lost their ear tags, is crucial for improving the precision of farm management. However, considering the real-time requirements for the detection of ear tag-lost breeding pigs, coupled with tracking challenges such as similar appearances, clustered occlusion, and rapid movements of breeding pigs, this paper proposed a dual-view synergistic method for detecting ear tag-lost breeding pigs and tracking individuals. First, a lightweight ear tag loss detector was developed by combining the Cascade-TagLossDetector with a channel pruning algorithm. Second, a synergistic architecture was designed that integrates a localized top-down view with a panoramic oblique view, where the detection results of ear tag-lost breeding pigs from the localized top-down view were mapped to the panoramic oblique view for precise localization. Finally, an enhanced tracker incorporating Motion Attention was proposed to continuously track the localized ear tag-lost breeding pigs. Experimental results indicated that, during the ear tag loss detection stage for breeding pigs, the pruned detector achieved a mean average precision of 94.03% for bounding box detection and 90.16% for instance segmentation, with a parameter count of 28.04 million and a detection speed of 37.71 fps. Compared to the unpruned model, the parameter count was reduced by 20.93 million, and the detection speed increased by 12.38 fps while maintaining detection accuracy. In the tracking stage, the success rate, normalized precision, and precision of the proposed tracker reached 86.91%, 92.68%, and 89.74%, respectively, representing improvements of 4.39, 3.22, and 4.77 percentage points, respectively, compared to the baseline model. These results validated the advantages of the proposed method in terms of detection timeliness, tracking continuity, and feasibility of deployment on edge devices, providing significant reference value for managing livestock identity in breeding farms. Full article

Background/Objectives: The ongoing prevalence of dental issues within the school-age population continues to present significant public health challenges. This study aims to thoroughly evaluate the oral health conditions of schoolchildren aged 7–10 years, with a particular focus on identifying the prevalence and severity of dental caries, as well as their relationship with dental hygiene and dietary habits. Methods: A cross-sectional approach was employed involving 700 children aged from 7 to 10 years, recruited from nine urban and rural educational institutions across two Romanian counties, namely Mureș and Bistrița-Năsăud. Data were collected regarding the sociodemographic characteristics of participants, including parental educational background and occupational status. Furthermore, information on dental hygiene routines was gathered, encompassing tooth brushing habits, flossing usage, frequency of brushing, along with dietary details such as daily meal count, snacking frequency, and sugar intake levels. An oral examination was performed by a trained specialist to assess the condition of the children’s teeth, documenting the number of decayed, missing, and filled teeth. The presence of plaque was evaluated using a plaque index, and the dental caries status was quantified using the Decayed, Missing, and Filled Teeth (DMFT) index. Results: The findings revealed that the average plaque score was marginally higher in boys (mean = 0.69 ± 0.36) compared to girls (mean = 0.65 ± 0.40). Additionally, children from urban environments demonstrated a mean plaque score of 0.61 ± 0.32, whereas their rural counterparts exhibited a higher score of 0.73 ± 0.38. In multivariable models, irregular brushing, higher daily sugar consumption, and ≥3 snacks/day were independently associated with both caries prevalence (DMFT > 0) and greater DMFT counts (p < 0.05). Conclusions: The evidence denotes a concerning association between poor oral hygiene practices and higher rates of tooth decay among children, particularly among those with elevated sugar intake and frequent snacking behaviors. Dental public health professionals are encouraged to incorporate considerations of oral hygiene habits when developing future health promotion strategies aimed at improving the oral health status of children. Full article

In shrimp farming, determining the physical traits of shrimp is vital for assessing their health and growth. One of the critical traits is their size, as it serves as a key indicator of growth rates, biomass, and effective feed management. However, the accurate measurement of shrimp size is challenged by factors such as their naturally curved body posture, frequent overlapping among individuals, and their tendency to blend with the background, all of which hinder precise size estimation. Traditional methods for measuring the size of shrimp involve manual sampling, which is labor-intensive and time consuming. In contrast, image processing and classical computer vision techniques provide some reasonable results but often suffer from inaccuracies, making them unsuitable for large-scale monitoring. To address this problem, this paper proposes a dual-segmentation deep learning-based framework for accurately estimating shrimp size. It integrates instance segmentation using the RTMDet-m model with an enhanced semantic segmentation model to effectively predict the centerline of the shrimp’s body, enabling precise size measurements. The first stage employs the RTMDet-m model for the instance segmentation of shrimp, achieving an average precision (${\mathrm{AP}}_{50}$) of 96% with fewer parameters and the highest frames per second (FPS) count among state-of-the-art models. The second stage utilizes our custom segmentation model for centerline predictive module, attaining the highest FPS and F1-score of 88.3%. The proposed framework achieves the lowest mean absolute error of 1.02 cm and a root mean square error of 1.27 cm in shrimp size estimation compared to the baseline methods discussed in comparative study sections. Our proposed dual-segmentation framework outperforms both traditional and deep learning based methods used for measuring shrimp size. Full article

Since the 1990s, glaciers in the Ányêmaqên Mountains of the Qinghai–Tibet Plateau have exhibited anomalous retreat and thinning. This persistent deglaciation has triggered secondary disasters including glacial debris flows, ice collapses, and glacial lake outburst floods, posing significant threats to regional ecological security and sustainable socioeconomic development. To address this issue, we conducted a comprehensive analysis of glacial morphological characteristics using multi-source time-series high-resolution remote sensing imagery spanning 2013–2024. Glacier boundaries were extracted through integrated methodologies combining manual visual interpretation, band ratio thresholding, three-dimensional geomorphic analysis, and an optimized DeepLabV3+ convolutional neural network with adaptive activation thresholds. Extraction accuracy was rigorously validated using quantitative metrics (Accuracy, Precision, Recall, Loss, and F1-score). Key findings reveal the following: dominant glacier types include ice caps, valley glaciers, and hanging glaciers distributed at mean elevations of 5200–5600 m; total glacial area decreased from 102.71 km² to 81.10 km², yielding an average annual decrease rate of −1.93%; glacier count increased from 74 to 86, corresponding to a mean relative change rate of 1.18% per annum; and thirty-eight geohazard sites were identified predominantly on upper slopes (30–50°) of north-facing terrain, with elevations ranging from 4500–5400 m (base) to 5120–6050 m (crest). These results provide critical data support for enhancing ecological resilience, strengthening disaster mitigation capabilities, and safeguarding public safety and infrastructure against climate change impacts in the region. Full article

This work presents a novel time-to-digital converter based on the analog sampling of dual-phase periodic signals generated from a free-running oscillator. A proof-of-concept ASIC, implemented in 130 nm CMOS technology, achieves an average single-shot precision of 0.9 ps-rms for time intervals up to 3 ns, with a best performance of 0.79 ps-rms. It maintains a precision below 3.7 ps-rms for intervals up to 25 ns. The design demonstrates excellent linearity, with a peak-to-peak differential nonlinearity of 0.56 LSB and a peak-to-peak integral nonlinearity of 1.43 LSB. The free-running oscillator is shareable across multiple channels, enabling power consumption of approximately 4.1 mW per channel and efficient area utilization. These features make the design highly suitable for detection systems requiring picosecond-level precision and high channel density, such as silicon pixel sensors, SPADs, LiDARs, and time-correlated single-photon counting systems. Furthermore, the architecture shows strong potential for use in high-count-rate applications, reaching up to 22 Mcps. Full article

The red swamp crayfish (Procambarus clarkii) is an exceptionally invasive species introduced into the Egyptian freshwater ecosystems in the 1980s for aquaculture purposes. Despite its ecological and economic significance, the age distribution of this species has not been assessed properly using an accurate method. This study is the first to validate the use of growth band counts in the mesocardiac ossicles as a direct technique for age determination in P. clarkii using 166 known-age individuals reared under various temperature regimes. The findings confirm that band counts represent age rather than number of molts. Field comparisons between northern (Giza) and southern (Aswan) Nile populations revealed maximum longevities of six and seven years, respectively, using direct methods, while indirect size–frequency analysis underestimated age at three years. Growth rates were higher at 25 °C compared to 32 °C, both in the lab and in situ. Males matured at larger sizes than females, though age at sexual maturity averaged one year in both regions. This study demonstrates the superiority of direct aging over traditional indirect aging methods, offering critical insights for managing crayfish populations and ensuring sustainable fisheries in the River Nile in Egypt. Full article

Chemical Looping Combustion (CLC) technology has emerged as a promising approach for carbon capture owing to its CO₂ separation capability, which addresses the pressing challenge of global climate change. Although iron-based oxygen carriers offer economic advantages owing to their abundance and low cost, their limited cyclic stability restricts their industrial deployment. This study focused on optimizing the performance of iron-based oxygen carriers through composite modification with Al₂O₃ and TiO₂. Using Cantera (2.5.0) software and the minimum Gibbs free energy principle, conversion rates and product distributions of Fe₂O₃, Fe₂O₃/Al₂O₃, and Fe₂O₃/TiO₂ were systematically analyzed under varying temperatures (800–950 °C), oxygen carrier-to-fuel molar ratios (O/C = 1–15), and pressures (0.1–1.0 MPa). The optimal conditions were identified as 900 °C, O/C = 8, and 0.1 MPa. After 50 simulation cycles, Fe₂O₃/Al₂O₃ and Fe₂O₃/TiO₂ achieved average total reaction counts of 503 and 543, respectively, substantially exceeding 296 cycles for Fe₂O₃. The results indicated that Al₂O₃ and TiO₂ improved cyclic stability via physical support and structural regulation mechanisms, thereby offering a practical carrier composite modification strategy. This study provides a theoretical basis for the development of high-performance oxygen carriers and supports the industrial application of CLC technology for efficient carbon capture and emission mitigation. Full article

Background: Postoperative wound complications following total joint arthroplasty (TJA) significantly impact patient outcomes and healthcare costs. Reliable preoperative biomarkers for identifying patients at increased risk are critical for optimizing patient management and reducing complication rates. This study evaluated the predictive utility of the C-reactive protein to albumin ratio (CAR) and the prognostic nutritional index (PNI) for periprosthetic joint infection (PJI) and postoperative wound complications in patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA). Methods: We retrospectively studied patients who underwent primary THA and TKA in our department from March 2019 to April 2024. The study included a total of 842 patients (568 knees and 274 hips). Preoperative blood samples were assessed for serum CRP, albumin, and total lymphocyte count, facilitating the calculation of CAR and PNI values. Patient outcomes were monitored, identifying PJI and aseptic wound complications such as persistent wound drainage, hematoma, seroma, skin erosion, and wound dehiscence within 2 weeks post-surgery. Results: The average follow-up time for patients was 39.2 months (range 13–73 months). PJI was significantly linked with elevated admission CAR and diminished PNI ratio (p < 0.001 and p < 0.001). ROC analysis demonstrated optimal predictive cut-off values for CAR at 3.1 (Area under curve [AUC]: 0.92, specificity 97.4%, sensitivity 92.3%) and PNI at 49.4 (AUC: 0.93, specificity 94.7%, sensitivity 91.7%). Furthermore, both CAR (Odds ratio [OR]: 3.84, 95% confidence interval [CI]: 1.6–9.1, p = 0.002) and PNI (OR: 21.8, 95% CI: 9–48.6, p < 0.001) were identified as two independent risk factors associated with the development of PJI following THA or TKA. Further subgroup analysis revealed distinct predictive thresholds for CAR and PNI according to surgical procedure type (TKA and THA), enhancing diagnostic accuracy. Conclusions: Preoperative admission elevated CAR and decreased PNI effectively predict PJI and postoperative wound complications in THA and TKA, supporting their utility as simple, cost-effective biomarkers in clinical practice. Incorporating CAR and PNI evaluations into preoperative assessments can enhance patient stratification and preventive strategies, thus mitigating risks and improving surgical outcomes. Full article

Seed germination is a key determinant of wheat seed quality, strongly affected by genetic potential, weather conditions during production, and storage duration. Although numerous studies have investigated seed viability, little is known about how the interaction between annual climatic variability and storage length affects long-term germination performance of winter wheat. The objective of this study was therefore to assess the influence of weather conditions and storage period on germination energy and germination of 50 Croatian winter wheat (Triticum aestivum L.) cultivars released between 1947 and 2010. The experiment was conducted over five consecutive production years (2013/2014–2017/2018). Seeds of each cultivar were reproduced under standardized field conditions, harvested annually, and stored under identical controlled conditions (5 °C, 30–35% RH). Germination energy (first count, day 4) and total germination (final count, day 8) were evaluated according to ISTA protocols. The results revealed significant effects of both production year and cultivar on germination performance. Seeds produced in 2016/2017 exhibited the highest germination (96.21%), which was ~15% higher than the lowest rate observed in 2013/2014 (80.48%). Germination energy of 2013/2014 seeds was 23% lower compared to 2015/2016 and 2016/2017. Unexpectedly, seeds stored for only one year (2017/2018 production) showed lower germination (90.92%) than those stored for two (96.21%) or three years (95.01%), likely due to excessive rainfall (>100% above average) during seed maturation in 2018 that impaired seed quality. Several cultivars, including Una, Tonka, Žitarka, and Kuna, consistently maintained high germination rates (>94%) even after five years of storage, demonstrating strong physiological stability and long-term viability. These findings underline the combined importance of weather conditions during seed production and storage duration for seed longevity. In practical terms, cultivars with proven stability may be recommended for long-term storage and reliable field performance. Future research should extend germination assessment to additional vigor indices (e.g., germination synchrony, vigor index, abnormal seedlings) and explore genetic mechanisms underlying superior seed longevity in modern wheat breeding. Full article

This work presents an experimental study of the effect of blade count on the flow field and the radiated noise in a low-speed axial fan with a rotating shroud. A two-component Laser Doppler Velocimetry (LDV) system and Particle Image Velocimetry (PIV) instrumentation have been employed to investigate the flow in the gap region and in front of the rotor blades. Additionally, the fan has been installed in a hemi-anechoic chamber and far-field acoustic measurements have been taken with a microphone mounted on-axis upstream of the rotor to show changes in the spectral features of the radiated noise. The tested rotor is a variable-geometry one that has allowed for studying rotor configurations with different numbers of blades of the same chord and shape, i.e., of the same geometry but different solidity. Rotor pressure rise and flow rate are average quantities that have a relevant effect on the leakage flow. Keeping them fixed while varying solidity allows us to highlight the local effects of circumferential pressure non-uniformity caused by differing blade loading. The results show that, at low solidity, the flow leaving the gap is mainly directed radially outward and follows a longer path before being ingested by the rotor, thus losing strength due to mixing with the main flow. As solidity increases, the flow becomes less radial and is more rapidly ingested by the rotor. In all cases, the sound pressure level spectrum shows marked subharmonic humps and peaks originating from the interaction between the leakage flow and rotor. The departure of such peaks from the blade passing frequency increases with the solidity, while the associated energy increases up to seven blades and then decreases. Full article

Accurate, real-time, and cost-effective detection and counting of pre-weaning piglets are critical for improving piglet survival rates. However, achieving this remains technically challenging due to high computational demands, frequent occlusion, social behaviors, and cluttered backgrounds in commercial farming environments. To address these challenges, this study proposes a lightweight and attention-enhanced piglet detection and counting network based on an improved YOLOv8n architecture. The design includes three key innovations: (i) the standard C2f modules in the backbone were replaced with an efficient novel Multi-Scale Spatial Pyramid Attention (MSPA) module to enhance the multi-scale feature representation while a maintaining low computational cost; (ii) an improved Gather-and-Distribute (GD) mechanism was incorporated into the neck to facilitate feature fusion and accelerate inference; and (iii) the detection head and the sample assignment strategy were optimized to align the classification and localization tasks better, thereby improving the overall performance. Experiments on the custom dataset demonstrated the model’s superiority over state-of-the-art counterparts, achieving 88.5% precision and a 93.8% $mA{P}_{0.5}$. Furthermore, ablation studies showed that the model reduced the parameters, floating point operations (FLOPs), and model size by 58.45%, 46.91% and 56.45% compared to those of the baseline YOLOv8n, respectively, while achieving a 2.6% improvement in the detection precision and a 4.41% reduction in the counting MAE. The trained model was deployed on a Raspberry Pi 4B with $ncnn$ to verify the effectiveness of the lightweight design, reaching an average inference speed of <87 ms per image. These findings confirm that the proposed method offers a practical, scalable solution for intelligent pig farming, combining a high accuracy, efficiency, and real-time performance in resource-limited environments. Full article

Background/Objectives: Many cancer survivors continue to experience persistent symptoms such as pain, fatigue, and depression. Exercise and increasing physical activity (PA) are recommended as methods that can help alleviate these symptoms. However, maintaining regular exercise can be difficult due to the challenge of maintaining motivation. This secondary analysis uses data from a randomized controlled pilot study that examines the feasibility of the technology-enhanced combined exercise and other nonpharmacological interventions, such as the TEHEplus program, in managing symptoms. The program used mobile technologies and sent weekly physical performance reports to maintain engagement. In this study, we aimed to examine the impact of weekly physical performance reports on daily symptoms and PA and explored characteristics as moderators. Methods: This secondary analysis included participants who completed the 12-week TEHEplus program. Daily data of steps (PA), sleep duration, and symptoms (rated on a 4-point scale) were collected for 84 days. Mixed-effects and lagged regression models were used to assess the impact of weekly physical performance reports and the moderating effects of baseline characteristics. Results: Seventy-seven survivors of solid tumor cancer (mean age, 59.79, SD = 12.17) were analyzed. During this 84-day period, participants reported a reduction in low energy (B = −0.003, p = 0.004). Step counts increased by an average of 141 steps immediately after each weekly report (B = 140.857, p = 0.027). An increase of 5000 steps on the prior day was related to decreasing pain (B = −0.047, p < 0.001) and fatigue/low energy (B = −0.082, p < 0.001). Two additional hours of prior-night sleep worsened pain (B = 0.029, p = 0.001) and fatigue/low energy (B = 0.027, p = 0.002). Gender, employment, race, caregiver, and type of treatments moderate the relationship between daily PA, sleep (B = −0.131~0.078, p_s < 0.05). Conclusions: Weekly physical performance reports promoted PA, which possibly led to self-reported improvement of symptoms. Higher PA was associated with better self-report symptoms, but longer sleep duration was associated with worsened symptoms, suggesting the need for future studies. The moderating effects suggested that tailoring interventions to individual profiles may enhance the program’s effectiveness. Full article

Background: Rugby Union’s physical demands lead to high injury rates, requiring players to optimize their abilities. Altitude training enhances performance but poses risks to injuries. Methods: This cross-sectional observational study compares the Portuguese Rugby team’s injury rates and Global Positioning System (GPS) performance data during the Rugby World Cup (RWC) 2023 preparation phase. Two medical doctors from the medical Portuguese department diagnosed and recorded all the injuries occurred. GPS players data recorded the following: running distance (RD), high-speed running distance (HSRD), number of accelerations of high intensity (HI), maximum velocity (MV), and percentage of personal maximum velocity (% MV). Data were analyzed by position and growth rate (∆) comparing sea level (Cycle 1) and altitude (Cycle 2). The players were analyzed by injury severity, type, anatomical location, and GPS performance metrics. Results: A higher number of injuries was recorded in Cycle 2 compared to Cycle 1 (∆ = +5 for forwards; ∆ = +3.5 for backs). While average values for MV and % MV showed a downward trend, RD, HSRD, and HI exhibited upward trends. However, none of these differences reached statistical significance. Conclusions: Injury counts and training volume indicators showed upward trends, while MV and % MV declined, though none reached statistical significance. These patterns should be interpreted cautiously, and further research is needed to explore GPS metrics in injury monitoring. Full article