Search Results (32,510)

Understanding the gross lesion distribution associated with bovine tuberculosis (bTB) and the relationship between antemortem test results is important for optimizing surveillance activities. Antemortem diagnostic test results and postmortem examination results from animals infected with bTB in the United States are routinely collected during surveillance and outbreak response. From 2017 to 2022, data were compiled and analyzed from 403 infected animals, representing both beef and dairy cattle from a variety of herds with different levels of disease prevalence. Overall, 95.3% of cattle infected with Mycobacterium bovis presented with gross lesions. Most cattle had lesions in one anatomic region. Lesions of the thorax and head were most common with 42.4% of infected cattle having lesions in only the thorax, 18.4% having lesions only in the head, and 15.6% having lesions in both the head and thorax. The most frequently affected tissues were the mediastinal, tracheobronchial, and medial retropharyngeal lymph nodes. Results of antemortem skin tests were not found to be associated with lesion count or location. This analysis presents an updated look at the current state and presentation of bTB in the U.S., makes use of data collected in the field, and can help guide future bTB surveillance and control strategies. Full article

This study establishes experimentally grounded circumferential thermal criteria for heat-shrinkable crosslinked polyethylene (PEX) joint casings by coupling DSC-defined thermal activation with through-thickness thermal lag measured under trench-constrained irradiation. The activation temperature was identified as 140 °C from DSC, while an upper bound of the allowable outer-surface temperature was set to avoid thermal damage during installation. Full-scale temperature mapping revealed persistent circumferential non-uniformity caused by geometric line-of-sight limitations and inter-module gap regions, where the outer-surface temperature remained approximately 10–15 °C lower than directly irradiated locations, and the inner surface exhibited a delayed response due to the low thermal conductivity of PEX. Based on these observations, a two-stage heating sequence—an initial high-power stage followed by a reduced-power soaking stage—was experimentally derived to satisfy dual constraints: achieving inner-surface activation (≥140 °C) while maintaining the outer surface below the conservative outer-surface upper bound (~280 °C) and reducing circumferential temperature differences without surface overheating. Comparative joint tests confirmed that the proposed thermal criteria and sequence promote stable interfacial bonding and cohesive failure in the mastic layer, yielding higher repeatability and smaller strength scatter than conventional manual torch heating. The proposed framework provides experimentally grounded thermal criteria and a transferable procedure for designing heating conditions for heat-shrinkable polymer casing systems under constrained field environments. Full article

To overcome the drawbacks of conventional wedge cut blasting—high peak particle velocity (PPV), low blasthole utilization, and a high proportion of large fragments—this paper proposes a delayed blasting method for wedge cut blasting. By integrating the rock-fracturing process of wedge cut blasting, the mechanisms of rock breaking and vibration reduction are investigated and confirm the method through field tests. The results indicate that the rock breaking process can be divided into two stages, the stage of fracture propagation and the stage of cavity ejection, and a rock breaking criterion for wedge cut delayed blasting is established. Considering differences in the vibration waveforms generated by different types of cut holes, a vibration waveform fitting method for wedge cut delayed blasting is proposed. Furthermore, the generation time of the blast-induced free surface during the rock breaking process is calculated, and a calculation Equation for the optimal delayed time is derived. Field tests in the Qi Jiazhuang tunnel show that, compared with conventional blasting, the proposed delayed blasting method increases blasthole utilization by 23.8%, reduces the large fragment rate by 67.4%, lowers PPV by 53.7%, and increases the dominant vibration frequency by 42.0%. These results significantly improve the wedge cut blasting performance and construction safety. Full article

Electron fields (and more generally spinor fields) with a vortex structure in free space that allows them to have arbitrary integer orbital angular momentum along the direction of motion have been studied for some time. We point out that there are several ways to calculate the local velocity of the electron field, defined as the ratio of momentum density to energy density, and that all but one show a singular vorticity at the vortex line. That one, using the Dirac bilinear current with no derivatives, is the only one so far (to our knowledge) studied in the literature in this context and we further show how to understand an apparent conflict in the existing results. The momentum densities corresponding to the three possible velocity fields give different physical results, in particular regarding the electron induced quantum superkicks given to small electron-absorbing test objects. Full article

Ensuring the safety and effectiveness of first responder teams during critical missions requires real-time health monitoring and responsive intervention systems. This study presents a novel system comprising a multimodal wearable device integrated with a remote command centre, designed to support the physiological monitoring and guidance of first responders in the field. The wearable device includes three main components: a physiological and biochemical signal acquisition unit, an electrotactile stimulation unit and a powerful communication interface. The acquisition unit continuously samples heart rate, body temperature, and biochemical markers from sweat, transmitting this data wirelessly to the remote command centre. The transmitted physiological data could be analyzed at the command centre and, based on the inferred first responder condition, appropriate feedback commands could be issued back to the corresponding wearer. The commands are then executed by the electrotactile stimulation unit on the wearable device. Initial testing in laboratory settings confirmed the system’s ability to generate accurate electrochemical readings and dehydration assessment through changes in bulk ionic conductivity. Electrochemical impedance spectroscopy showed good agreement with a commercial potentiostat. Heart rate and temperature readings demonstrated satisfying accuracy with minor removable artifacts. Field trials with first responders validated continuous signal transmission and electrotactile feedback with over 80% success. These results confirm the system’s robustness and modularity, supporting its application in operational environments. Full article

Timely identification of canopy decline in commercial strawberry production is challenging because visual scouting often misses subtle or spatially heterogeneous symptoms. We developed a plant-level UAV-based monitoring framework that integrates repeated multispectral imagery, canopy-derived metrics, unsupervised clustering, and Random Survival Forest (RSF) time-to-event modeling. The framework was applied across three commercial strawberry fields in Oxnard, California using nine UAV surveys collected from December 2022 to June 2023, yielding 159,220 plant-level monitoring units. NDRE- and Redness Index-based classifications quantified proportional and absolute canopy dieback within standardized hexagonal units and supported survival-based modeling of canopy decline progression. Across withheld test plants from all survey dates, overall concordance indices ranged from 0.88 to 0.95 across fields, indicating strong ability to rank plants by time-to-decline risk under heterogeneous field conditions. Spatial risk maps revealed localized high-risk clusters that expanded over time in fields with greater canopy deterioration, while fields with minimal visible decline exhibited diffuse but stable risk distributions. Post-hoc comparison with operational fumigation rates (280, 336, and 392 kg Pic-Clor 60/ha) showed no consistent association with predicted canopy decline risk. These results demonstrate that framing repeated UAV observations as a time-to-event process enables fine-scale spatiotemporal modeling of canopy decline dynamics and supports risk stratification for targeted field monitoring in commercial strawberry systems. Full article

Lakes on the Inner Mongolia–Xinjiang Plateau (IMXP) are increasingly vulnerable to eutrophication under climate change and human pressure, yet long-term monitoring remains limited by sparse field sampling. Here, we reconstruct multi-decadal trophic dynamics across the IMXP using Landsat time series and temporally transferable machine-learning models and further quantify the underlying natural and anthropogenic drivers. We compiled monthly in situ water-quality observations (chlorophyll-a, Chl-a; total phosphorus, TP; total nitrogen, TN; Secchi depth, SD; and permanganate index, COD_Mn;) and calculated the trophic level index (TLI). After rigorous quality control and monthly aggregation, we compiled a dataset of 1345 matched lake–month samples spanning 2000–2024, and divided it into a training set (n = 1076; ≤2019) and an independent test set (n = 269; 2020–2024) to evaluate temporal transferability. We utilized Google Earth Engine to generate monthly surface reflectance composites from Landsat 7 ETM+, Landsat 8 OLI, and Landsat 9 OLI-2. Four supervised regression algorithms—ridge regression (RR), support vector regression (SVR), random forest (RF), and eXtreme Gradient Boosting (XGBoost)—were trained to estimate TLI. On the independent test period, XGBoost performed best (R² = 0.780, RMSE = 3.290, MAE = 1.779), followed by RF (R² = 0.770, RMSE = 3.364), SVR (R² = 0.700, RMSE = 3.842), and RR (R² = 0.630, RMSE = 4.267); we then used XGBoost to reconstruct monthly and yearly TLI for 610 perennial grassland lakes from 2000 to 2024. From 2000 to 2024, the annual mean TLI (48–49) across the IMXP exhibited a statistically significant upward trend (slope = 0.0158 TLI yr⁻¹; 95% confidence interval (CI) = 0.0050–0.0267; p = 0.006). Meanwhile, spatial heterogeneity was distinct (TLI: 41.51–59.70). High values concentrated in endorheic and desert–oasis basins (e.g., Eastern Inner Mongolia Plateau, >51), whereas lower values characterized high-altitude regions (e.g., Yarkant River, <45). Overall, trends ranged from −0.49 to 0.51 yr⁻¹, increasing in 54% of lakes (15.6% significantly) and decreasing in 46% (15.4% significantly). Attribution analyses identified NDVI (33.92%) and temperature (21.67%) as dominant drivers (55.59% combined), followed by precipitation (13.99%) and human proxies (30.42% combined: population 10.66%, grazing 10.31%, built-up 9.45%). Across 53 sub-basins, NDVI was the primary driver in 28, followed by temperature (11), population (7), precipitation (3), grazing (3), and built-up land (1); notably, the top two drivers explained 56.6–87.1% of variations. TWFE estimates revealed bidirectional NDVI effects (significant in 31/53): positive associations in 22 basins were linked to nutrient retention, contrasting with negative effects in nine basins associated with agricultural return flows. Temperature effects were significant in 15 basins and predominantly negative (14/15), except for the Qiangtang Plateau. Overall, eutrophication risk across the IMXP lake region reflects the combined influences of climatic conditions, vegetation conditions, and human activities, with their relative contributions varying among basins. Full article

Local Lorentz Invariance is one of the fundamental postulates of General Relativity, making its experimental verification of paramount importance. Given that various frontier theoretical models predict potential symmetry breaking, the Standard Model Extension framework has been established to systematically study such phenomena. Within the Standard Model Extension gravitational sector, the high-order Lorentz-violating terms with mass dimension $d=6$ exhibit a rapid signal decay with distance, providing a distinct detection advantage in short-range gravity experiments. This work is dedicated to optimizing the testing schemes for $d=6$ Lorentz-violating coefficients. Based on a high-precision torsion balance platform, we propose a novel scheme featuring a comb-stripe design. The improvements are twofold: first, the spatial orientation of the experimental apparatus is optimized to leverage the modulation effects of the Earth’s rotation, thereby enhancing the capability to distinguish and constrain different violation parameters; second, the test and source masses are reconfigured into specifically designed stripe patterns to significantly amplify the fringe-field signals sensitive to Lorentz-violating effects. This paper systematically elaborates on the theoretical foundation and design principles of the new scheme. By performing a detailed comparison of the constraint potentials of various stripe configurations, the five-stripe geometry is identified as the optimal experimental configuration. This study provides a new experimental methodology for exploring physics beyond the Standard Model at higher levels of precision. Full article

In order to find green fungicides derived from natural products, 22 unreported anethole-based thiazolinone-hydrazone compounds were designed and synthesized, and their structures were characterized by FT-IR, ¹H NMR, ¹³C NMR, and HRMS. At a concentration of 50 mg/L, the preliminary antifungal activity of the target compounds against eight plant pathogens was evaluated. The results showed that 5q (R = m-OH C₆H₄) exhibited the best inhibitory activity against most of the tested plant pathogenic fungi, demonstrating that this compound had certain broad-spectrum antifungal activity. In addition, a reasonable and effective 3D-QSAR model (r² = 0.994, q² = 0.529) was established using the comparative molecular field analysis (CoMFA) method to study the relationship between the structures of the target compounds and their antifungal activity against Physalospora piricola. Meanwhile, the results of electrostatic potential calculation of the compounds indicated that the electronic effect caused by different substituents on the benzene ring might be one of the factors affecting antifungal activity. In addition, frontier molecular orbital calculations implied that the anethole moiety and the thiazolinone-hydrazone-benzene structure in the target compounds might play an important role in antifungal activity. The potential binding mode between the target compound 5q (R = m-OH C₆H₄) and the homology-modeled succinic dehydrogenase was explored by molecular docking. Full article

Accurate and timely cotton-field mapping is essential for irrigation management, water resource allocation, and regional yield assessment in arid irrigated agroecosystems. However, existing deep-learning-based crop mapping approaches generally lack interpretability and often exhibit performance variability across phenological stages, thereby limiting their reliability for operational deployment. To address these limitations, we developed an interpretable semantic segmentation framework for cotton mapping in the Wei-Ku Oasis, Xinjiang, China, under multi-source remote sensing conditions. The proposed model integrates Sentinel-2 surface reflectance, Sentinel-1 VV/VH backscatter, DEM, vegetation indices, and GLCM texture features. By incorporating a receptive-field enhancement mechanism together with an embedded feature-attribution module, the framework enables importance estimation of multi-source predictors within the network architecture, thereby providing intrinsic model interpretability. Under a unified training and evaluation protocol, the proposed model achieved an mIoU of 85.62% and an F1-score of 92.96% on the test set, outperforming U-Net, DeepLabV3+, and SegFormer baselines. Monthly classification results indicated that August provided the most discriminative acquisition window (mIoU = 85.54%, F1 = 92.83%), while June–July also maintained high recognition accuracy. Feature attribution results indicate that the importance of different predictors varies across phenological stages: Sentinel-2 red-edge bands remained highly influential throughout the growing season, NDVI/EVI exhibited increased contributions during June–August, SAR VH showed relatively higher importance during peak canopy development, and DEM maintained stable information contribution across all stages. Cross-year and cross-region experiments further demonstrated the model’s generalization capability, achieving an mIoU of 82.81% in same-region cross-year evaluation and 74.56% under cross-region transfer. Overall, the proposed segmentation framework improves classification accuracy while explicitly modeling and quantifying feature importance, providing a methodological reference for cotton-field mapping and acquisition timing selection in arid irrigated regions. Full article

Abies georgei var. smithii (Viguie & Gaussen) is a dominant conifer along the southeastern margin of the Qinghai–Tibet Plateau, where heart rot often develops covertly, complicating forest health monitoring and disease management. Fomitopsis subpinicola B.K. Cui, M.L. Han & Shun Liu is an important causal agent of heart rot affecting A. georgei var. smithii in this region, yet rapid, field-deployable molecular diagnostics of this pathogen remain limited. Here, we developed and evaluated two TEF1α-based isothermal platforms for specific detection of F. subpinicola: RAA and LAMP. To reduce potential cross-reactivity, TEF1α sequences from representative taxa within the F. pinicola species complex and closely related non-complex species were aligned for primer/probe design. Candidate RAA primers were screened by gel electrophoresis to select an optimal pair, and two LAMP primer sets were compared by specificity testing to identify the best-performing set. Both assays specifically detected F. subpinicola with no cross-amplification in the tested non-target fungi. Limits of detection were 9.97 copies/μL for fluorescent RAA (25 min), 9.97 × 10² copies/μL for RAA-LFD (15 min), and 9.97 × 10³ copies/μL for LAMP (35 min). In 30 increment core samples from A. georgei var. smithii, all methods consistently detected samples with obvious decay, while fluorescent RAA additionally yielded positives in some apparently asymptomatic samples, indicating promise for early or low-abundance screening. Together, these assays constitute a tiered and application-oriented detection system, enabling flexible selection of diagnostic approaches according to sensitivity requirements, operational conditions, and field surveillance needs for heart rot of A. georgei var. smithii. Full article

The application of hyperspectral image (HSI) processing techniques has become increasingly important in many fields such as agriculture, environmental detection, and mining. However, the number of annotated samples in existing hyperspectral datasets is limited, and most hyperspectral classification models typically use patch data for model training. There, the pixels to be classified are often taken as the center, and then a mean pixel length is calculated from the surrounding pixel neighborhood to form patch data. However, during model training, the researchers found that there was an area of overlapping pixels between most of the training data and the test data. This inevitably led to data leakage, resulting in excellent classification performance of the model. To solve this problem, we develop a method of replacing overlapping pixels (ROP) in patch data, which means the training pixel points of the same class are used to replace the test pixel points that appear in the overlapping region of the training patch data. Furthermore, a multiple feature extraction and fusion (MFEF) module is also proposed to enhance the capacity of the HSI model to extract spectral–spatial feature information from new patch data. The results on five publicly available HSI datasets demonstrate that the proposed resolving data leakage network (RDLNet) can provide competitive classification results on the patch data reconstructed with the ROP strategy, which outperforms existing state-of-the-art (SOTA) classification methods as well. Full article

Fusarium head blight (FHB) is one of the most devastating diseases of cereal crops worldwide, causing yield losses and mycotoxin contamination. Traditionally associated with warm and humid climates, FHB has increasingly affected cooler and drier regions, including the Volga region of Russia—a major grain-producing area once considered low-risk. In this three-year field study, we evaluated FHB resistance in 50 winter rye accessions under natural infection and artificially enriched infectious backgrounds using high-virulence Fusarium strains from the Volga region. Post-invasive resistance to FHB was generally weak across the tested germplasm. Nevertheless, considerable variability in FHB damage was observed among accessions. Accessions showing the lowest overall FHB severity were identified as promising donors for breeding programs. Specific resistance sources to individual Fusarium species were identified, notably Fusarium sporotrichioides—previously regarded as a weak pathogen but demonstrated here as a serious food safety threat. No significant positive correlation was found between FHB severity and mycotoxin levels, confirming these as partially independent traits; several accessions maintained low mycotoxin content despite severe symptoms. Our study highlights the necessity of multi-environment screening with local pathogen strains and endorses pyramiding approaches for durable FHB resistance in winter rye breeding. Full article

In recent years, pigeon rotavirus A (PiRVA) infection, an important emerging disease, has posed a major threat to the healthy development of the pigeon industry and public health. Therefore, developing an accurate, rapid and convenient detection method for this virus is vital for monitoring and early diagnosis of the disease. In this study, on the basis of the ORF sequence characteristics of the PiRVA VP6 gene, crRNA and reverse transcription recombinase-aided amplification (RT-RAA) primers were designed. On the basis of the CRISPR/Cas12a system, for the first time, the RT-RAA-CRISPR/Cas12a rapid detection method of PiRVA was established by combining RT-RAA and lateral flow strips. This method could specifically detect PiRVA, and there was no cross-reaction with other common viruses originating from pigeons. The minimum detection limit was 16.8 copies/μL, and the results of the intrabatch and interbatch repeated tests were consistent. Moreover, the method established in this study and the previously established common PCR method were used to analyse 56 clinical tissue samples from racing pigeons and domestic pigeons collected in 2025. The positive rates of racing pigeon and domestic pigeon samples detected by PCR were 17.6% and 12.8%, respectively, and the positive rates of racing pigeon and meat pigeon samples detected by the RT-RAA-CRISPR/Cas12a method were 23.5% and 17.9%, respectively, indicating that PiRVA infection occurs in both racing pigeon and domestic pigeon populations in China. In summary, the PiRVA RT-RAA-CRISPR/Cas12a detection method established in this study has good specificity, sensitivity, and reproducibility, and allows visualization of the results, which can be used for field applications. This study provides technical support for epidemiological surveillance and etiological research on PiRVA. Full article

Traditional palliative care education may limit the development of clinical competencies and attitudes required to alleviate suffering and improve quality of life. Gamification has been proposed as an alternative educational strategy in this field. Background/Objectives: This study aimed to assess the association between gamification-based intervention and palliative care knowledge among nursing students at a public university. Methods: This single-group, pre–post-intervention study was conducted in the Nursing Program of the Universidad Técnica del Norte, Ecuador, including 136 students from the accessible population. Palliative care knowledge was assessed before and after the intervention using the validated Palliative Care Quiz for Nursing (PCQN-SV). Student satisfaction and Moodle usability were assessed using a 10-item Likert-type questionnaire. The gamified educational intervention was delivered online over 60 h. Data were analyzed using descriptive statistics and Wilcoxon signed-rank tests for paired comparisons, and exploratory logistic regression analyses were conducted to evaluate contextual differences across hospitals. Statistical significance was set at α = 0.05. Results: The mean age was 22.9 years (SD = 1.89), and 73.5% were female. Knowledge scores increased significantly after the intervention (Wilcoxon signed-rank test, p < 0.001; r = 0.35). The proportion of students achieving sufficient knowledge (≥13 correct responses) increased from 27.2% (37/136) at baseline to 49.3% (67/136) post-intervention. Contextual analysis indicated variability across clinical training sites, with Lago Agrio showing higher odds of sufficient knowledge (aOR = 3.25; 95% CI [1.26–8.41]; p = 0.015). Conclusions: The gamified intervention was associated with increased palliative care knowledge among nursing students. Heterogeneity across hospitals suggests that contextual factors may influence the magnitude of change. Full article