Search Results (2,661)

Dairy cow body temperature is a key physiological indicator that reflects metabolic level, immune status, and environmental stress responses, and it has been widely used for early disease recognition. Infrared thermography (IRT), as a non-contact imaging technique capable of remotely acquiring the surface radiation temperature distribution of animals, is regarded as a powerful alternative to traditional temperature measurement methods. Under practical cowshed conditions, IRT images of dairy cows are easily affected by complex background interference and generally suffer from low resolution, poor contrast, indistinct boundaries, weak structural perception, and insufficient texture information, which lead to significant degradation in target detection and temperature extraction performance. To address these issues, a lightweight detection model named YOLOv11n-CGSD is proposed for dairy cow IRT images, aiming to improve the accuracy and robustness of region of interest (ROI) detection and body temperature extraction under complex background conditions. At the architectural level, a C3Ghost lightweight module based on the Ghost concept is first constructed to reduce redundant feature extraction while lowering computational cost and enhancing the network capability for preserving fine-grained features during feature propagation. Subsequently, a space-to-depth convolution module is introduced to perform spatial rearrangement of feature maps and achieve channel compression via non-strided convolution, thereby improving the sensitivity of the model to local temperature variations and structural details. Finally, a dynamic sampling mechanism is embedded in the neck of the network, where the upsampling and scale alignment processes are adaptively driven by feature content, enhancing the model response to boundary temperature changes and weak-texture regions. Experimental results indicate that the YOLOv11n-CGSD model can effectively shift attention from irrelevant background regions to ROI contour boundaries and increase attention coverage within the ROI. Under complex IRT conditions, the model achieves P, R, and mAP50 values of 89.11%, 86.80%, and 91.94%, which represent improvements of 3.11%, 5.14%, and 4.08%, respectively, compared with the baseline model. Using T_max as the temperature extraction parameter, the maximum error (Max. Error) and mean error (MAE. Error) in the lower udder region are reduced by 33.3% and 25.7%, respectively, while in the around the anus region, the Max. Error and MAE. Error are reduced by 87.5% and 95.0%, respectively. These findings demonstrate that, under complex backgrounds and low-quality IRT imaging conditions, the proposed model achieves lightweight and high-performance detection for both lower udder (LU) and around the anus (AA) regions and provides a methodological reference and technical support for non-contact body temperature measurement of dairy cows in practical cowshed production environments. Full article

Climate change has intensified summer drought and high solar radiation in Mediterranean ecosystems, generating abiotic stress that limits the establishment of riparian species. We conducted a nursery experiment to evaluate the effects of two levels of water availability and light intensity on the growth and physiological responses of two native riparian species from Mediterranean Chile: Drimys winteri and Persea lingue. A bi-factorial design combined two irrigation treatments (well-watered and water restriction) and two light intensity levels manipulated through a light protection treatment (20% shade mesh and full light exposure). Water restriction was applied gradually until 15–20% (v/v) substrate moisture, defined as maximum water restriction, followed by rehydration. Morphological variables (height, root collar diameter, and shoot-to-root ratio) and physiological traits (predawn water potential, chlorophyll fluorescence, and electron transport rate) were measured. Growth responses were affected by the light protection treatment, which promoted a significant height growth in both species. Water stress affected the global response of both species but they differed in their post-stress hydraulic recovery: P. lingue fully recovered its predawn water potential, whereas Drimys winteri did not. Our study provides measurable and quantifiable values that demonstrate the sensitivity of these species to water stress. Full article

Prostate cancer (PCa) is the leading cause of cancer-related deaths worldwide and the second most common cancer among men. Treatment options depend on factors like age, androgen sensitivity, PSA levels, Gleason score, TNM stage, and recurrence risk. Available treatments include hormonal therapy, radiation, surgery, and chemotherapy. Early immunological treatments were limited by poor lymphocyte infiltration and an immunosuppressive environment. Today, strategies such as dendritic cell vaccines, immune checkpoint inhibitors (ICIs), and adoptive cell therapy (ACT) are used. ACT, especially CAR T-cell strategies, aims to overcome traditional treatment limitations, particularly in advanced and metastatic castration-resistant prostate cancer (mCRPC), though it remains in early development. Personalized medicine uses molecular insights from the diseased tissue to tailor treatments. Variability in patient response, due to tumor heterogeneity and prior treatments, highlights the importance of personalized and combination therapies as future strategies for effective immunotherapy. This review explores the current landscape of PCa. We analyze treatment guidelines established by NCCN and EANM-ESTRO-ESUR-ISUP-SIOG. We comprehensively examine immunotherapeutic strategies currently available or under investigation for prostate cancer, with particular emphasis on ICIs, ACT with a focus on CAR T-cell therapy, combination approaches and therapeutic synergies, and predictive biomarkers of immunotherapy response. Additionally, we discuss the challenges and future directions in the implementation of immunotherapy for the management of prostate cancer. Full article

Semiconductor technologies are susceptible to radiation effects. The particle incidence in susceptible areas of an integrated circuit (IC) can generate physical interactions capable of producing errors. This paper predicts the IC cross sections for Single Event Effects. The cross section is a metric that provides an IC’s susceptibility to radiation. It deals with particle source interaction and physical design volumes. This work evaluates the IC cross section, exploring the physical design characteristics of susceptible regions in logic gates. It explores particles with low LET, identifying the charge collection areas. Also, the heavy ions are used to evaluate the critical cross section range. Distinct benchmark circuits were simulated to characterize sensitivity trends. The influence of circuit input conditions along with cells’ susceptibility reveals significant findings. The results indicate a difference up to ten times between low- and high-energy particles. Consequently, predicting the IC cross section at an early stage of the design flow is essential, especially for electronics devices used in radiation environments. Full article

A vertical Ni/β-Ga₂O₃ Schottky barrier diode was fabricated on an unintentionally doped bulk (−201)-oriented β-Ga₂O₃ single crystal and investigated with a focus on the underlying photoresponse mechanisms. The device exhibits well-defined rectifying behavior, characterized by a Schottky barrier height of 1.63 eV, an ideality factor of 1.39, and a high rectification ratio of ~9.7 × 10⁶ arb. un. at an applied bias of ±2 V. The structures demonstrate pronounced sensitivity to deep-ultraviolet radiation (λ ≤ 280 nm), with maximum responsivity observed at 255 nm, consistent with the wide bandgap of β-Ga₂O₃. Under 254 nm illumination at a power density of 620 μW/cm², the device operates in a self-powered mode, generating an open-circuit voltage of 50 mV and a short-circuit current of 47 pA, confirming efficient separation of photogenerated carriers by the built-in electric field of the Schottky junction. The responsivity and detectivity of the structures increase from 0.18 to 3.87 A/W and from 9.8 × 10⁸ to 4.3 × 10¹¹ Hz^0.5cmW⁻¹, respectively, as the reverse bias rises from 0 to −45 V. The detectors exhibit high-speed performance, with rise and decay times not exceeding 29 ms and 59 ms, respectively, at an applied voltage of 10 V. The studied structures demonstrate internal gain, with the external quantum efficiency reaching 1.8 × 10³%. Full article

Background/Objectives: Percutaneous transthoracic needle biopsy (PTNB) using advanced navigation techniques is increasingly performed; however, pulmonologists’ experience remains limited. This study reports an interventional pulmonologist’s initial experience with cone-beam computed tomography (CBCT) laser-guided PTNB and the diagnostic performance for lesions with diameters greater than or less than 20 mm. Methods: We retrospectively analysed the data of patients who underwent PTNB in a C-arm CBCT-equipped hybrid operating room between July 2020 and March 2024. All patients underwent the biopsy procedure under local anaesthesia. This was preceded by an initial 3D scan for planning of the needle route, followed by coaxial needle insertion. A post-procedural scan was also performed to identify complications. Results: Seventy-seven patients were enrolled in the study. The median distances of the needle path from the skin to the pleura and from the pleura to the lesion were 33.4 mm and 31.7 mm, respectively. The median number of tissue samplings was 4.9 ± 1.8. The median operating room duration was 51.5 ± 25.7 min, respectively. The median total dose area product was 8485.4 ± 5819.9 µGym². The sensitivity and specificity of our study findings were 93.3% (56/60) and 100%, while the accuracy was 94.8% (73/77). The overall complication rate was 13%. Conclusions: PTNB procedure by pulmonologists is a feasible and safe, single-operator workflow in a hybrid operating room. It can be performed under CBCT laser guidance with a similar diagnostic yield, acceptable radiation exposure and procedure duration, and minimal or manageable complications. Full article

Over the past 18 months, we have performed hundreds of temperature characterizations of fiber Bragg gratings inscribed in different germanium-doped silica glass fibers. Under experimental conditions, the main conclusions are as follows: the temperature dependence of the “temperature gauge factor” or the normalized temperature sensitivity, K_T, was found to be quadratic in the −50–200 °C range, while it may be considered linear for the −20–100 °C range; K_T values at 20 °C vary from 5.176 × 10⁻⁶ K⁻¹, for a B/Ge co-doped fiber up to 6.724 × 10⁻⁶ K⁻¹, for a highly Ge-doped fiber; K_T does not depend on the hydrogen-loading process or the gratings coupling strength; K_T is essentially independent of wavelength in the 1500–1600 nm range, its value being accurately determined with a relative error ~0.2%; based on the accurate value of K_T = 6.165 × 10⁻⁶ K⁻¹, at 20 °C, obtained for gratings inscribed in the SMF-28 fiber, we calculated a value of 19.4 × 10⁻⁶ K⁻¹ for the thermo-optic coefficient of bulk germanium glass; and gratings produced by femtosecond-laser radiation and UV-laser radiation exhibit comparable values of K_T. The previous achievements allow, by having knowledge of K_T for a single grating, the accurate determination of the temperature dependence of the Bragg wavelength for any other grating inscribed in the same fiber; the presented methodology enables one to determine the “unknown” gratings’ temperature sensitivity, typically with an error of 0.01 pm/°C, being, therefore, very useful in research labs and computer simulations. Thus, expressions for the temperature dependence of K_T for gratings inscribed in several fibers are given, as well as an expression for K_T as a function of the effective refractive index. We have also fully analyzed the potential sources of error in K_T determination. Full article

Extreme environments such as low pressure, high temperature, and intense radiation pose severe challenges for humidity sensors, causing conventional hygroscopic materials to exhibit sluggish responses, drift, and instability. In response, recent research has adopted multi-level strategies involving material modification, structural engineering, and packaging optimization to enhance the adaptability of humidity-sensitive materials in extreme environments. This review examines humidity sensing from an environmental perspective, integrating sensing mechanisms, material classifications, and application scenarios. The performance, advantages, and limitations of six major categories of humidity-sensitive materials, including carbon-based, metal oxides, conductive and insulating polymers, two-dimensional (2D) materials, and composites, are systematically summarized under extreme conditions. Finally, emerging development trends are discussed, highlighting a shift from material-driven to system-driven approaches. Future progress will rely on multidisciplinary integration, including interface engineering, multiscale structural design, and intelligent algorithms, to achieve higher accuracy, stability, and durability in extreme-environment humidity sensing. Full article

Background/Objectives: Lung cancer is the leading cause of cancer-related mortality worldwide, and early detection using low-dose computed tomography (LDCT) substantially improves survival outcomes. However, variations in CT acquisition and reconstruction parameters including Hounsfield Unit (HU) calibration, reconstruction kernels, slice thickness, radiation dose, and scanner vendor introduce significant intensity and contrast variability that undermine the robustness and generalizability of deep-learning (DL) systems. Methods: This systematic review followed PRISMA 2020 guidelines and searched PubMed, Scopus, IEEE Xplore, Web of Science, ACM Digital Library, and Google Scholar for studies published between 2020 and 2025. A total of 100 eligible studies were included. The review evaluated preprocessing and harmonization strategies aimed at mitigating CT intensity variability, including perceptual contrast enhancement, HU-preserving normalization, physics-informed harmonization, and DL-based reconstruction. Results: Perceptual methods such as contrast-limited adaptive histogram equalization (CLAHE) enhanced nodule conspicuity and reported sensitivity improvements ranging from 10 to 15% but frequently distorted HU values and reduced radiomic reproducibility. HU-preserving approaches including HU clipping, ComBat harmonization, kernel matching, and physics-informed denoising were the most effective, reducing cross-scanner performance degradation, specifically in terms of AUC or Dice score loss, to below 8% in several studies while maintaining quantitative integrity. Transformer and hybrid CNN–Transformer architectures demonstrated superior robustness to acquisition variability, with observed AUC values ranging from $0.90$ to $0.92$ compared with $0.85$–$0.88$ for conventional CNN models. Conclusions: The evidence indicates that standardized HU-faithful preprocessing pipelines, harmonization-aware modeling, and multi-center external validation are essential for developing clinically reliable and vendor-agnostic AI systems for lung-cancer screening. However, the synthesis of results is constrained by the heterogeneous reporting of acquisition parameters across primary studies. Full article

Terrestrial ecosystems in Hunan Province have undergone marked yet spatially heterogeneous vegetation changes under concurrent climate change and intensifying human activities. The aim of this study is to resolve how vegetation responses vary among land-use types by quantifying kernel Normalized Difference Vegetation Index (kNDVI) dynamics during 2000–2023 using precipitation, temperature, and solar radiation, coupled with trend analysis and a partial-derivative-based attribution. Mean kNDVI increased overall at 0.0016 yr⁻¹; vegetation improved over 76.30% of the area, whereas 5.72% of the area experienced degradation. Built-up land exhibited the largest degraded fraction (35.04%). Human activities and temperature emerged as the dominant drivers of kNDVI change, contributing 62.25% and 27.92%, respectively, while precipitation (3.08%) and solar radiation (6.77%) played comparatively minor roles. Spatially, human activities primarily controlled vegetation dynamics in plains and urban clusters (~78% of the area), whereas temperature constrained vegetation in high-elevation mountain ranges. Analysis along the human footprint (HFP) gradient reveals that driver composition remains steady in resilient ecosystems (farmland and forest), despite increasing anthropogenic pressure, whereas fragile ecosystems (grassland and bareland) exhibited pronounced volatility and heightened sensitivity to environmental constraints. These findings provide a quantitative basis for developing sustainable ecological security strategies, incorporating region-specific measures such as adaptive afforestation, sustainable agricultural management, and strict ecological protection, to enhance ecosystem resilience by prioritizing the climate resilience of mountain forests and the stability of fragile grassland systems. Full article

Silicon carbide (SiC) power converters are increasingly used in automotive, renewable energy, and industrial applications. While reliability assessments are typically performed at either the device or system level, an integrative approach that simultaneously evaluates both levels remains underexplored. This article presents a novel system-level simulation method with two strategies to evaluate the reliability of power devices and a resonant converter under varying temperatures and total ionizing doses (TIDs). Temperature-sensitive electrical parameters (TSEPs), such as on-state resistance ($R_{\mathrm{ON}}$) and threshold voltage shift ($\Delta V_{\mathrm{TH}}$), are calibrated and analyzed using a B1505A curve tracer. These parameters are incorporated into the system-level simulation of a 300 W resonant converter with a boosting cell. Both Silicon (Si) and SiC-based power resonant converters are assessed for power application in space engineering and harsh environments. Additionally, gate-oxide degradation and $\Delta V_{\mathrm{TH}}$-related issues are discussed based on the simulation results. The thermal-strategy results indicate that SiC MOSFETs maintain a more stable conduction loss at elevated temperatures, exhibiting higher reliability due to their high thermal conductivity. Conversely, increased TIDs result in a negative shift in conduction losses across all SiC devices under the radiation strategy, affecting the long-term reliability of the power converter. Full article

Ionizing radiation remains the primary approach for treating brain cancer and is frequently used in combination with chemotherapy. However, when it comes to gliomas, the effective delivery of therapeutic agents is hindered by the limited permeability of the blood–brain barrier (BBB). Consequently, selecting the most suitable and least harmful type of ionizing radiation is essential, given its potential side effects on healthy cells within the tumor microenvironment. In this study, we explored the impact of X-ray exposure on two in vitro BBB endothelial cell models—murine and human. Post-irradiation, we evaluated cell viability, clonogenic capacity, cell cycle progression, reactive oxygen species (ROS) levels, formation of micronuclei and γ-H2AX foci, as well as alterations in cytoskeletal organization, cell migration, and intracellular calcium dynamics. The results demonstrate notable differences between the two endothelial cell lines, suggesting the human cell line is more sensitive to X-rays. In conclusion, our study provides valuable insights into the brain microvascular endothelial cells’ response to radiation, laying the groundwork for strategies to protect healthy brain tissue. Full article

Background: Acute renal colic, most often caused by ureteral stones, is a common cause of emergency admissions. While non-contrast computed tomography (CT) is the diagnostic gold standard, its use is limited by radiation exposure, cost, and accessibility. Growth Differentiation Factor-15 (GDF-15) is a stress-induced cytokine elevated in various acute pathologies. This study investigated the diagnostic and predictive value of serum and urine GDF-15 in patients with acute renal colic due to ureteral stones. Methods: In this prospective observational study (January 2024–March 2025), 76 patients presenting with sudden-onset flank pain were enrolled. A total of 41 patients with radiologically confirmed ureteral stones formed the stone-positive group, and 35 patients without urinary pathology served as controls. Serum and urine GDF-15 levels were measured by ELISA, along with routine laboratory tests. CT was used to assess stone characteristics, hydronephrosis grade, and ureteral wall thickness. Group comparisons were performed using the Mann–Whitney U test, correlations with Spearman’s test, and diagnostic performance with ROC analysis. Results: Both serum and urine GDF-15 levels were significantly higher in stone-positive patients (p < 0.001). Urine GDF-15 demonstrated excellent diagnostic accuracy (AUC = 0.986; sensitivity = 92.7%; specificity = 91.4), while serum GDF-15 showed moderate performance (AUC = 0.767). GDF-15 levels showed modest positive correlations with CRP and were numerically higher in patients with ureteral wall thickness > 1 mm and proximal stones. No significant association was found with spontaneous stone passage (p > 0.05). Conclusions: Urine GDF-15 shows promising diagnostic accuracy for ureteral stones and may serve as a non-invasive adjunctive tool when imaging is limited. While associated with inflammation and stone location, it did not predict spontaneous stone passage. These findings support its potential as a clinical biomarker, though further large-scale validation is required. Full article

The simulation accuracy of crop models is highly dependent on the proper calibration of key parameters. To enhance the applicability of the Next-Generation agricultural production systems sIMulator (APSIM NG) in dryland wheat production within the Loess Hilly Region, this study proposes a crop model parameter calibration framework that deeply integrates Morris and DREAM-zs methodologies. Morris was employed to conduct a global sensitivity analysis on parameters related to the APSIM NG dryland wheat grain and leaf growth sub-models. The DREAM-zs algorithm was then utilized for multi-objective collaborative optimization of key parameters. Results indicate that Morris excels at capturing nonlinear and coupled relationships among model parameters. Optimized key parameters include maximum grain size (0.055 g), radiation use efficiency (1.540 g·MJ⁻¹), and extinction coefficient (0.443). Post-optimization, the root mean square error (RMSE) and mean absolute error (MAE) for wheat yield decreased by 24.1% and 23.2%, respectively, while those for LAI decreased by 16.9% and 19.2%. This framework conserves computational resources and accelerates convergence when handling nonlinear internal model parameters and complex coupling relationships, providing technical support for the localized application of APSIM NG in the Loess Hilly Region of Northwest China. Full article

High-sensitivity microwave sensing plays a vital role in material characterization and nondestructive testing, with its performance being largely determined by the quality factor (Q factor) of the sensing structure. In this work, a high-Q microwave metasurface sensor based on the mechanism of bound states in the continuum (BIC) is designed and realized to overcome the intrinsic Q-factor limitations of conventional microwave resonators. By introducing a controlled asymmetric perturbation into the meta-atom, a quasi-BIC mode is successfully excited, and its sensing performance is systematically investigated through frequency-domain simulations. The results indicate that the proposed metasurface achieves an exceptionally high radiation Q factor of up to 4599.7 in the microwave band, along with a refractive index sensitivity of 31.267 GHz/RIU. These findings not only demonstrate the significant potential of the BIC mechanism for achieving ultra-high-Q microwave resonators but also provide an effective and promising approach for the development of high-performance microwave sensing systems. Full article