Search Results (41,184)

Background: Monitoring skeletal muscle mass (SMM) during radiotherapy (RT) is important, as SMM loss is associated with poorer clinical outcomes. Cone-beam CT (CBCT), acquired before each RT fraction, offers the potential to track the lumbar skeletal muscle index (LSMI) over time. However, CBCT has lower image quality than conventional CT. This study assessed the agreement between CT and CBCT and evaluated the reliability of LSMI measurements in patients with head and neck squamous cell carcinoma. Methods: Patients who underwent both CT and CBCT on the same day during RT were included. The cross-sectional muscle area at C3 was measured, converted to L3, and used to calculate the LSMI. Two researchers analyzed all scans, with one repeating the measurements. Agreement and reliability were quantified using intraclass correlation coefficients (ICCs) and visualized with Bland–Altman plots. Results: LSMI measurements showed excellent agreement between CBCT and CT (ICC: 0.97–0.99; 95% CI: 0.95–0.99). The intrarater (ICC: 0.99; 95% CI 0.98–0.99) and interrater reliability (ICC: 0.97; 95% CI: 0.66–0.99) were high. Bland–Altman plots, however, revealed wide limits of agreement. Conclusion: CBCT provides reliable LSMI measurements and agrees well with CT, but the observed variability suggests cautious interpretation. When both modalities are available, CT remains the preferred standard for SMM assessment. Full article

Spaceborne microwave imagers are vital for monitoring global precipitation due to their wide swath and high sensitivity. This study proposes a deep learning approach that integrates a U-Net with a multi-task learning (MTL) framework. The model was separately trained over land and ocean using GPM Microwave Imager (GMI) brightness temperatures, with collocated precipitation rates and types from the Dual-frequency Precipitation Radar (DPR) as labels. This combines the accuracy of radars with the coverage of imagers to produce high-precision, wide-swath precipitation estimates. In the MTL setup, near-surface precipitation rate retrieval is the main task, and precipitation type classification is the auxiliary task. A composite loss (weighted MSE and quantile regression) is used for the main task, and weighted cross-entropy for the auxiliary task. Residual blocks and an attention mechanism are incorporated to improve physical representation and generalization, thereby significantly enhancing the model’s capability to retrieve heavy precipitation. The model was trained on 2015–2024 GPM data and evaluated on an independent six-month 2025 GMI dataset. Compared to a standard U-Net, the MTL model achieved significant gains: Pearson Correlation Coefficient (PCC) increased by 9.7% (ocean) and 13.7% (land), and Critical Success Index (CSI) by 10.7% (ocean) and 10.8% (land). The method was also applied to the FY-3G Microwave Radiation Imager (MWRI-RM). In case studies, it outperformed the official product, achieving average increases of 20.1% in PCC and 15.7% in CSI, respectively. Validation against FY-3G Precipitation Measurement Radar (June–August 2024) yielded over ocean PCC = 0.757, RMSE = 1.588 mm h⁻¹, MAE = 0.355 mm h⁻¹; over land PCC = 0.691, RMSE = 2.007 mm h⁻¹, MAE = 0.692 mm h⁻¹. The study demonstrates that the MTL-enhanced U-Net significantly improves the accuracy of spaceborne microwave imager rainfall retrieval and shows robust practical applicability. Full article

Background/Objectives: DNA methylation is a key epigenetic modification involved in regulating many cellular processes, including gene expression and the maintenance of genome stability. Ultraviolet (UV) radiation induces DNA damage in the form of pyrimidine-pyrimidone (6-4) photoproducts [(6-4)PPs] and cyclobutane pyrimidine dimers (CPDs), which can lead to mutations if not efficiently repaired. While cytosine methylation has been implicated in influencing UV-induced DNA damage formation, the effect of DNA methylation modulators such as S-adenosyl-L-methionine (SAM) and RG108 on UV damage formation and repair remains unclear. Methods: Here, using immunoslot blot assays, we investigated the effects of SAM and RG108 on UV-induced DNA damage formation and repair in human lymphoblastoid cells. Results: We found that SAM, but not RG108, rapidly suppresses the formation of both (6-4)PP and CPD, with detectable effects within minutes of exposure. Although SAM pretreatment was associated with modestly accelerated early (6-4)PP repair, this effect was accompanied by substantially lower initial damage levels. When cells were treated with SAM or RG108 immediately after UV irradiation to ensure equivalent initial damage burden, no significant differences in repair were observed for either lesion type, demonstrating that the accelerated early (6-4)PP repair reflects reduced lesion burden rather than increased intrinsic nucleotide excision repair (NER). Global 5-methylcytosine (5mC) levels remained stable following SAM or RG108 treatment and during UV damage repair, suggesting that these effects occur independently of global alterations in DNA methylation. Conclusions: Together, our findings reveal that SAM modulates UV damage susceptibility at the level of lesion formation without altering repair, highlighting a previously unrecognized role for DNA methylation modulators in regulating genome stability. Full article

This study presents a comprehensive flavour profile analysis of 12 Morchella samples (5 cultivated and 7 wild species) collected from diverse regions across China. The contents of free amino acids and volatile organic compounds were determined using UHPLC-QE-HRMS and HS-SPME-GC-MS. Flavour contribution was assessed by calculating taste activity values (TAVs) and relative odor activity values (rOAVs), and the influence of environmental factors on flavour compound accumulation was further explored. The findings indicated that cultivated Morchella exhibited pronounced fruity, floral, sweet, and mushroom-like notes (e.g., 1-octen-3-one, beta-damascone, and 1-(2-aminophenyl)ethanone), rendering them suitable for fresh consumption. In contrast, wild Morchella exhibited higher levels of herbaceous and smoky aroma compounds (e.g., (E,Z)-2,6-nonadienal, benzenemethanethiol, and non-8-enal), suggesting potential for premium product development. Correlation analysis revealed metabolic associations between taste-active amino acids and key volatile organic compounds via intermediates of the lipoxygenase pathway and the tricarboxylic acid cycle. Furthermore, environmental parameters including elevation, annual precipitation, and solar radiation were found to significantly influence the accumulation of flavour-related metabolites. These findings provide insights into the chemical basis underlying the flavour diversity of Morchella and offer a theoretical foundation for species identification, flavour-directed breeding, and differentiated product development. Full article

The transverse beam size is a key parameter for characterizing the performance of synchrotron radiation sources. Accurate measurement of the transverse beam size is crucial for assessing beam quality. In this study, a fiber array-photomultiplier tube (PMT) beam measurement system was developed to enable high-precision sampling of beam profile information for beam-size measurement. Furthermore, a hybrid method integrating nonlinear least squares (NLLS) fitting and Gaussian basis-function fitting was proposed to reconstruct the beam intensity profile from discrete sampling data. Before performing NLLS fitting, a median absolute deviation (MAD)-based threshold filter is employed to remove outliers and suppress random noise, thereby improving the stability and robustness of the parameter estimation. The filtered data are then fitted using NLLS to obtain the reconstructed distribution. To capture potential high-order modal features in the beam profile, a Gaussian basis-function fitting model was also introduced for comparison, and its performance was evaluated under complex intensity distributions. Additionally, the relationship between the full width at half maximum (FWHM) and beam intensity was experimentally verified while accounting for measurement effects in the system. The results demonstrate that the proposed hybrid algorithm improves reconstruction accuracy and robustness, enabling precise recovery of the beam-intensity profile in the fiber-array PMT system. Full article

Background/Objectives: Image quality of mammograms in breast cancer screening is strongly operator-dependent, particularly in the mediolateral oblique (MLO) projection where adequate visualisation of the pectoralis major muscle serves as a surrogate marker of posterior tissue inclusion. Current positioning assessment is predominantly qualitative and subject to inter-observer variability. This study aimed to quantitatively evaluate pectoral muscle visualisation and compression force variability among radiographers participating in a national screening programme. Methods: A retrospective observational study was conducted at Clinical Hospital Center Rijeka in January and February 2020. A total of 464 digital MLO mammograms were analysed. Images from nine radiographers were randomly retrieved from the institutional Picture Archiving and Communication System (PACS). Pectoral muscle length and width were measured using a standard clinical workstation with an integrated distance measurement tool. Additional variables included radiographer gender, breast side (LMLO vs. RMLO), imaging order, and applied compression force. Statistical analyses included Welch’s ANOVA, one-way ANOVA, t-tests, and appropriate post hoc comparisons. Results: Across all MLO projections, the combined mean pectoral muscle width was 41.0 ± 11.4 mm and the mean length was 134.3 ± 21.7 mm. Significant inter-operator differences were observed in pectoral muscle width (p < 0.001) and length (p = 0.023). Mean muscle width ranged from 35.0 mm to 54.2 mm, and mean length from 126.5 mm to 139.4 mm across radiographers. No significant differences were found with respect to radiographer gender, breast side, or imaging order (all p > 0.05). Compression force differed significantly among radiographers (p < 0.001), ranging from 117.0 ± 18.3 N to 184.8 ± 33.9 N. Conclusions: This study demonstrates significant inter-operator variability in both pectoral muscle visualisation and applied compression force during MLO mammography. These findings indicate that important technical aspects of mammographic examination remain strongly operator-dependent and highlight the need for more consistent positioning practices within screening programmes. Quantitative measurement of pectoral muscle dimensions may serve as a practical and objective approach for monitoring positioning quality and supporting quality assurance in routine clinical practice. Full article

The use of millimeter-wave spectrum in fifth-generation (5G) systems is increasing the need for accurate prediction of received power and coverage in real deployment scenarios. In this context, ray tracing (RT) is a promising approach for site-specific analysis, although its reliability depends on how accurately different tools reproduce measurements in complex urban environments. This work presents a comparative assessment at 27 GHz of three RT tools: in-house Exact tool based on Vertical Plane Launching (VPL), Matlab 5G and open-source Sionna RT based on Shooting and Bouncing Rays (SBR). The comparison relies on a large outdoor walk-test campaign, including about 14,725 measurement points collected in a real urban area around a 27 GHz mMIMO base station, using real operator-provided antenna radiation patterns. Measured and simulated power levels are compared using statistical metrics, including Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and a planning-oriented coverage-rate metric. The results show a reasonable agreement between simulations and measurements, with RMSE and MAE values around 10–12 dB, highlighting tool-specific behaviors related to boundary effects, interaction modeling, and high-power overestimation. This work confirms that RT is a flexible support for 5G preliminary network design, reducing the need for extensive drive tests. Full article

This study experimentally investigates the combustion behavior of RP-3 aviation kerosene pool fires (300~800 mm) within a confined space, specifically focusing on the complex interaction between buoyancy-driven plumes and mechanical negative pressure ventilation. By integrating high-precision mass loss measurements with multiple characteristic parameters, this research uniquely characterizes the transition of energy feedback mechanisms under confined suction flow. Results show that ventilation enhances combustion intensity and compresses the fire cycle. For an 800 mm pool, the peak mass loss rate rose by 57.1%, from 16.71 g/s to 26.25 g/s. This enhancement stems from boundary layer thinning, which transitions the combustion from diffusion-controlled to kinetics-controlled. Ventilation also induces severe flame tilt with a non-monotonic trend. The tilt angle peaks at 84° for 600 mm pools but drops to 64° at 800 mm as buoyancy momentum increases. Additionally, an energy contrast of vertical cooling and horizontal heating was observed. Axial peak temperatures decreased by 20%, while downwind thermal radiation flux increased by up to 125%. The ventilation system essentially acts as a directional energy projector, shifting heat loads toward the downwind region. These findings support the optimization of fire safety and detection designs for industrial ventilation systems. This study experimentally investigates the combustion behavior of RP-3 aviation kerosene pool fires (300–800 mm) within a confined space, specifically focusing on the complex interaction between buoyancy-driven plumes and mechanical negative pressure ventilation. By integrating high-precision mass loss measurements with multi-point thermal and imaging diagnostics, this research uniquely characterizes the transition of energy feedback mechanisms under confined suction flow. Full article

Microelectromechanical systems are being increasingly deployed in nuclear industry robotics, where their great sensitivity and mechanically stable silicon structures enable reliable sensing in radiation-exposed environments. An ultra-thin silicon strain gauge without an oxide substrate layer designed for robotic electronic skin is evaluated under Co-60 γ irradiation, representative of nuclear decommissioning conditions. The sensor performance is evaluated based on electrical measurements conducted before and after irradiation, focusing on cumulative radiation-induced effects. The results show that silicon strain gauge signal maintains a high linearity (R² > 0.99) under strain. Across an accumulated dose range up to approximately 15 Gy, only minor variations are observed, including a resistance increase within 1.3% and a reduction in gauge factor within 5% for most specimens. The radiation-induced resistance increases and sensitivity degradation results in a maximum strain estimation error of approximately 22.5 με (≈3.5%) within the tested operating range below 700 με. Full article

Chroococcidiopsis sp. was isolated from the endolithic habitat of the Atacama Desert (northern Chile), one of the most challenging-to-life polyextreme environments on Earth. The photosynthetic machinery of microorganisms inhabiting this environment is supposed to be highly adapted to cope with the intense solar radiation of the area. Thus, PAR-red light ranging from 100 to 900 µmol photon·m⁻²·s⁻¹ has been investigated as a strategy to enhance culture productivity and stimulate the synthesis of bioactive molecules in Chroococcidiopsis sp. A control culture was maintained under white light at 100 µmol photon·m⁻²·s⁻¹. The results revealed that red light was utilized more efficiently than white light of similar irradiance, and its modulation enhanced both growth and photosynthetic activity of the cyanobacterium. Furthermore, Chroococcidiopsis sp. appeared to activate mechanisms to mitigate photooxidative stress produced by excess light energy. Specifically, increasing light irradiance induced photoacclimation responses, characterized by a decrease in chlorophyll content and a concomitant increase in carotenoid accumulation, likely aimed at reducing photon flux transduced to photosynthesis. Additionally, scytonemin synthesis was enhanced under high irradiances, contributing to dissipating excess light energy. Overall, this study demonstrates that modulation of red-light irradiance effectively improves the growth of Chroococcidiopsis sp. while promoting the accumulation of antioxidant compounds—primarily carotenoids and, to a lesser extent, scytonemin. Full article

Background: To explore the correlation between spatial dose distribution and post-implant urinary toxicity, aiming to assist decision making in low-dose-rate (LDR) treatment planning, thereby improving patient outcomes. Methods: Eighty-five prostate LDR patients with >12-month follow-up were included. Patient-reported urinary toxicity was collected prospectively using the International Prostate Symptom Score (IPSS) questionnaire, from before implant (baseline) to post-implant follow-up. Patients were then grouped into those whose symptom scores returned to ≤2 points above baseline by 12 months (no long-term toxicity) vs. those who did not (long-term toxicity). A total of 106 features were extracted for each patient, including principal components of dose-volume histograms (DVHs) from multiple prostate subzones, the whole prostate and urethra, along with baseline IPSS, implantation characteristics, and additional DVH indicators for the prostate and the urethra. A machine learning (ML) model incorporating backward feature selection algorithm was developed to predict long-term toxicity status, using a shuffle-and-split validation strategy for model evaluation during feature selection. A univariate statistical analysis was conducted on the model’s selected features. Results: Out of 85 patients, 41 (48%) had long-term urinary toxicity. Seven features were selected during model training, including baseline IPSS and six dosimetric features from several prostate subzones primarily located in the posterior prostate. The model achieved a high mean area under the receiver operating characteristic curve (AUC) of 0.81, with a balanced sensitivity and specificity of 0.78 by adjusting the probability threshold. In univariate analysis, only baseline IPSS and one selected dose feature were significantly correlated with long-term toxicity with AUC < 0.71. Conclusions: The proposed ML model, integrating baseline IPSS and spatial dosimetric features, effectively predicts long-term urinary toxicity after prostate LDR. This approach offers a practical method for risk stratification, allowing clinicians to identify patients at elevated risk and prioritize them for targeted preventative measures and closer follow-up. Full article

Infrared and visible image fusion aims to combine the complementary advantages of thermal radiation information and rich texture details to generate more informative images for downstream perception tasks. However, existing deep learning-based methods usually assume ideal imaging conditions and often suffer from performance degradation in complex environments such as low illumination, rain interference, and strong lighting disturbances. To address this problem, this paper proposes an adaptive prompting-driven degradation-aware fusion framework. Specifically, a degradation-aware prompt generation module is introduced to automatically perceive degradation patterns from the input images and generate structured conditional prompts. These prompts guide the network to adaptively adjust feature representations through learnable affine modulation. Furthermore, a semantic-aligned feature learning strategy is designed to ensure consistent cross-modal representation in the latent space. Extensive experiments demonstrate that the proposed method achieves superior performance compared with several state-of-the-art fusion approaches under both normal and degraded conditions. Full article

The construction sector remains a major contributor to global energy consumption and greenhouse gas emissions. Heat loss through building envelopes plays a key role, especially in regions with long heating seasons. Hollow building blocks are widely used due to their low cost and structural simplicity, but their inadequate thermal insulation requires additional layers of insulation, increasing costs and complicating installation. The production of cement and traditional insulation materials is associated with a high carbon footprint and disposal issues, which conflict with sustainable development principles and decarbonization goals. In contrast to previous reviews that primarily address bio-based insulation in general building envelopes or focus on bioaggregates in concrete mixes, this paper specifically targets the application of biomaterials in hollow building blocks. It emphasizes how bio-based loose-fill and bound fillers interact with the peculiar thermo-fluid behavior of hollow cavities, including natural convection, conduction and radiation. The effects on thermal performance (thermal conductivity, U-value of walls) are analyzed, along with selected aspects of mechanical strength and durability. Gaps in long-term data on biodegradation are identified. Recommendations for selecting strategies depending on climate and design are offered, as well as directions for future research, including numerical modeling of thermal conditions. The results highlight the potential of biomodified blocks for creating energy-efficient and environmentally friendly wall systems. Full article

Functionally graded AA2024/B4C metal matrix composites were fabricated via mechanical alloying and hot pressing to investigate structure–property–radiation shielding relationships. Single-layer, two-layer, and three-layer architectures with varying B4C contents were systematically produced. Microstructural homogeneity and phase constitution were examined using SEM/EDS and XRD, while thermal stability was evaluated by thermogravimetric analysis. Density and porosity measurements were conducted to assess the influence of reinforcement distribution and functional grading on densification behavior. Gamma radiation shielding performance was experimentally evaluated using a 152Eu source and an HPGe detector over a wide photon energy range. Key shielding parameters, including linear and mass attenuation coefficients, half-value layer, tenth-value layer, mean free path, and radiation protection efficiency, were determined. The results reveal that functional grading significantly enhances radiation attenuation compared to monolithic composites. The three-layer AA2024/B4C composite exhibited the highest attenuation coefficients and the lowest HVL, TVL, and MFP values at all investigated energies, achieving nearly 100% improvement in shielding efficiency relative to unreinforced AA2024. These findings demonstrate that controlled B4C distribution and layered composite architecture provide a synergistic improvement in thermal stability, physical integrity, and radiation shielding performance, positioning functionally graded AA2024/B4C composites as efficient lightweight materials for advanced radiation shielding applications. These results indicate that the developed functionally graded AA2024/B4C composites are promising candidates for advanced radiation shielding applications in nuclear facilities, aerospace structures, and medical radiation protection systems, where lightweight and high-performance materials are critically required. Full article

Understanding the long-term dynamics of cropland water use efficiency (WUE) and its underlying environmental drivers is essential for ensuring food and water security, particularly for regions facing intensified climate change. Here, we investigated the spatial patterns and long-term trends of gross primary productivity (GPP), evapotranspiration (ET), and WUE in cropland ecosystems across Northeast China during the past two decades as the nation’s primary commodity grain base using the time-series Breathing Earth System Simulator (BESS) products. Subsequently, the ridge regression method was used to quantitatively disentangle the relative contributions of key climatic variables to the observed WUE trends of cropland. Our results revealed a pronounced decreasing gradient in both GPP and ET along the southeast–northwest direction. A significant increase in GPP was observed over the 20-year period (p < 0.01), with 95.94% of the cropland area showing positive trends. ET showed a slight, non-significant increase (p > 0.05), though 82.77% of pixels exhibited positive trends, particularly in the northwest. Consequently, WUE showed a widespread and significant enhancement (p < 0.01), with approximately 98% of cropland pixels exhibiting increasing trends. Attribution analysis identified air temperature as the dominant environmental variable, accounting for 92.4% of the observed WUE increase, while solar radiation and precipitation contributed modestly (3.4% and 3.2%, respectively). Our findings underscore the predominant role of thermal conditions in shaping the carbon–water coupling efficiency of agroecosystems in semi-arid to semi-humid transition zones. This study provides quantitative evidence that warming climate, rather than changes in water availability or radiation, has been the primary climatic factor driving the improved cropland WUE over the past two decades. These insights have important implications for developing adaptive water management strategies to enhance agricultural climate resilience in Northeast China and similar regions worldwide. Full article