Search Results (500)

Forest biomass is closely related to carbon sequestration capacity and can reflect the level of forest management. This study utilizes four machine learning algorithms, namely Multivariate Stepwise Regression (MSR), K-Nearest Neighbors (k-NN), Artificial Neural Network (ANN), and Random Forest (RF), to estimate forest aboveground biomass (AGB) in Chenzhou City, Hunan Province, China. In addition, a canopy height model, constructed from a digital surface model (DSM) derived from Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and an ICESat-2-corrected SRTM DEM, is incorporated to quantify its impact on the accuracy of AGB estimation. The results indicate the following: (1) The incorporation of multi-source remote sensing data significantly improves the accuracy of AGB estimation, among which the RF model performs the best (R² = 0.69, RMSE = 24.26 t·ha⁻¹) compared with the single-source model. (2) The canopy height model (CHM) obtained from InSAR-LiDAR effectively alleviates the signal saturation effect of optical and SAR data in high-biomass areas (>200 t·ha⁻¹). When FCH is added to the RF model combined with multi-source remote sensing data, the R² of the AGB estimation model is improved to 0.74. (3) In 2018, AGB in Chenzhou City shows clear spatial heterogeneity, with a mean of 51.87 t·ha⁻¹. Biomass increases from the western hilly part (32.15–68.43 t·ha⁻¹) to the eastern mountainous area (89.72–256.41 t·ha⁻¹), peaking in Dongjiang Lake National Forest Park (256.41 t·ha⁻¹). This study proposes a comprehensive feature integration framework that combines red-edge spectral indices for capturing vegetation physiological status, SAR-derived texture metrics for assessing canopy structural heterogeneity, and canopy height metrics to characterize forest three-dimensional structure. This integrated approach enables the robust and accurate monitoring of carbon storage in subtropical forests. Full article

Methanol Steam Reforming (MSR) is one of the most promising technologies in the hydrogen economy, and copper-based catalysts have become the core materials in this field due to their high activity and low cost. In this paper, we systematically review the design strategies of copper-based catalysts in MSR reactions in recent years, including structure control, component optimization, support effect, and surface modification. We focus on the mechanisms of active site exposure, improvement of anti-sintering ability, and the enhancement of anti-carbon deposition performance. Finally, we summarize the challenges of current research and propose the future development direction. This review aims to provide a reference for subsequent related research through the experience of this paper. Full article

Konjac glucomannan (KGM), derived from Amorphophallus konjac, is increasingly utilized in food and pharmaceutical applications. However, inconsistent KGM production across cultivars jeopardizes its quality and market viability. Lanthanum (La) has been shown to promote KGM levels, but the underlying mechanism remains unclear. In this study, 20~80 mg L⁻¹ La significantly stimulated KGM accumulation compared with the control group. We performed a transcriptome analysis and found 21,047 differentially expressed genes (DEGs), predominantly enriched in carbohydrate and glycan metabolism pathways. A total of 48 DEGs were linked to KGM biosynthesis, with 20 genes (SuSy, INV1/3/5/6, HK1/2, FPK2, GPI3, PGM3, UGP2, GMPP1/4, CslA3~7, CslH2, and MSR1.2) showing significant positive correlations with KGM content. Interestingly, three key terminal pathway genes (UGP1, UGP3, and CslD3) exhibited strong upregulation (log2 fold change > 3). Seven DEGs were validated with qRT-PCR, aligning with the transcriptomic results. Furthermore, 12 hormone-responsive DEGs, including 4 ethylene-related genes (CTR1, EBF1/2, EIN3, and MPK6), 6 auxin-related genes (AUX/IAA1-3, SAUR1-2, and TIR1), and 2 gibberellin-related genes (DELLA1-2), were closely linked to KGM levels. Additionally, the transcription factors bHLH and AP2/ERF showed to be closely related to the biosynthesis of KGM. These results lay the foundation for a model wherein La (Ш) modulates KGM accumulation by coordinately regulating biosynthetic and hormonal pathways via specific transcription factors. Full article

As a promising nuclear technology, molten salt reactors (MSRs) have a bright future in the energy sector due to their unique advantages such as high efficiency, safety, and fuel flexibility. However, the accurate analysis of fission products in MSRs requires reliable fission yield data. Current reactor burnup analysis often uses the ORIGEN2 code, whose fission yield libraries mainly originate from the outdated 1970s ENDF/B-VI nuclear database, thus risking data obsolescence. This study evaluates ORIGEN2’s fission yield libraries (THERMAL, PWRU, PWRU50) against the modern ENDF/B-VIII.0 library. Through a comprehensive comparative analysis of Oak Ridge National Laboratory’s Molten Salt Reactor Experiment (MSRE) model, numerical simulations reveal library-dependent differences in MSR burnup characteristics. The PWRU library best matches ENDF/B-VIII.0 for U-235-fueled cases in keff results, while the PWRU50 library has minimal keff deviation in U-233-fueled setups. Moreover, in both fuel cases, the fission yield library was found to significantly affect the activity of key radionuclides, including Kr-85, Kr-85m, I-133m, Cs-136, Sn-123, Sn-125, Sn-127, Sb-124, Sb-125, Cd-115m, Te-125m, Te-129m, etc. Additionally, the fission gas decay heat power calculated via the ORIGEN2 library is over 20% lower than that from the ENDF/B-VIII.0 library tens of days after shutdown, mainly due to differences in long-lived Kr-85 production. These findings highlight the need to update traditional fission yield libraries in burnup codes. For next-generation MSR designs, this is crucial to ensure accurate safety assessments and the effective development of this promising energy technology. Full article

Subclinical mastitis (SCM) is a stealthy but devastating challenge in the dairy industry, leading to economic losses and hindering efforts to achieve milk self-sufficiency. This study investigated the prevalence of SCM, antimicrobial resistance, and virulence profiles of Escherichia coli. A total of 174 milk samples were analyzed using the California mastitis test (CMT), somatic cell counts (SCCs), bacteriological culture, MALDI-TOF MS, and polymerase chain reaction (PCR). The findings revealed that the SCM prevalence was 68/174 (39.08%) based on CMT and SCC. Among SCM-positive samples, 60/68 (88.23%) were identified as E. coli, confirmed by MALDI-TOF MS and PCR assay. The most frequently detected serogroups were 0113 (11.6%) and 0113 (3.3%). Additionally, the genes for Stx1 and Stx2 were also detected in nine (15%) and one (1.7%), respectively. Antimicrobial susceptibility tests showed widespread resistance, with E. coli isolates demonstrating resistance to penicillin in 43 (71.6%), followed by ciprofloxacin in 42 (70%) and gentamicin in 18 (30%). A larger proportion of the E. coli strains (100%) harbored the bla_VIM gene, while 23 (38.3%), 20%, 20%, and 1.47% contained bla_KPC, bla_NMD, suli1, and msrA. Thirty (50%) isolates were considered multidrug-resistant (MDR). These findings underscore the urgent need for enhanced surveillance and antibiotic stewardship in dairy farming. The presence of MDR E. coli in SCM poses a dual threat of potential transmission to humans and treatment failures in mastitis management. This study highlights the importance of proactive control strategies to mitigate the spread of antimicrobial resistance in livestock and beyond. Full article

The aim of this study was threefold: (i) to analyze the influence of previous match outcome on subsequent weekly training load (TL); (ii) to examine whether accumulated weekly TL varies throughout the season; and (iii) to investigate the influence of performance streaks got during competition on subsequent weekly TL. Twenty-one Spanish male professional soccer players from the same team were involved in the study. Total distance (TD), medium-speed running (MSR, distance 10.8–18.0 km·h⁻¹), high-speed running (HSR, >21 km·h⁻¹), very high-speed running (VHSR, 18.0–25.2 km·h⁻¹), sprinting speed running distance (sprint, >25.2 km·h⁻¹), player load (PL), number of accelerations (ACC), and decelerations (DEC) were recorded during training sessions using 10 Hz GPS devices. Previous match outcome, period of the season, and the performance streaks were also considered. Linear mixed models showed that team covered significantly less TD during the week after draw than after win (p < 0.05). In addition, most of the variables decreased as the season progressed. Finally, after medium-performance streaks, team covered significantly higher TD compared to high-performance streaks (p < 0.05) and low performance streaks (p < 0.01). These findings showed that low-performance streaks could reduce weekly external TL. Full article

A relatively new GelSight Max measurement instrument was applied to the microtopographies of experimental hardened clay surfaces, both with and without fingerprint (dermatoglyph) impressions, and the surface of an archaeological pottery handle fragment with a preserved fingerprint (paleodermatoglyph). The experimental clay surfaces were documented in order to determine the instrument’s ability to capture these surfaces in three-dimensions by imprinting them onto an elastomeric tactile membrane. Fingerprints on the experimental hardened clay and the archaeological pottery fragment were mathematically documented to test this instrument’s ability to capture these impressions. The surface texture measurements of the hardened clay and the pottery fragment were mathematically compared using conventional topographic characterization parameters (height and hybrid), fractal dimensions (Das) with associated coefficients of determination (R²), and multiscalar geometric characterization parameters, particularly relative area (Srel), area-scale complexity (Asfc), relative length (RL), and length-scale complexity (Lsfc). The surfaces of the experimental hardened clay with and without fingerprints and the archaeological pottery handle fragment with a fingerprint can be discriminated using some conventional height parameters, as well as some multiscale geometric topographic characterization parameters. Specifically, relative area (Srel), area-scale complexity (Asfc), relative length (RL), and length-scale complexity (Lsfc) could all discriminate between the hardened clay block with and without fingerprints and the fingerprint on the archaeological pottery handle fragment at different scales of measurement. Mean square ratios (MSRs) above 90% and 95% confidence levels indicated that the discrimination of these multiscale geometric characterizations was significant. In sum, the GelSight Max has the potential to be a valuable instrument for archaeologists studying pottery and fingerprints. Full article

Here we report that the Salmonella Typhimurium NatB (SeNatB) protein N-terminal acetyltransferase acetylated the N-terminal methionine of the nucleoid-associated HU proteins. Our findings were supported by an in vitro analysis of acetylation of the HUα and HUβ proteins and lysine-null (K-null) variants, and by an in vivo analysis of the effect of acetylation on HU-mediated transcriptional regulation of a known target of HU, the hilA promoter. SeNatB did not acetylate the initiating methionines of HU proteins that were oxidized to methionine sulfoxide, but the reduction of these methionine sulfoxide residues restored the acetylation of HU proteins by SeNatB. These results demonstrate that the SeHU proteins are bona fide substrates for the methionine sulfoxide reductases MsrA and MsrB. Finally, we showed that the Bacillus subtilis acetyltransferase, YfmK, is a functional homolog of SeNatB, and that BsYfmK acetylates the N^α amino group of the initiating methionine of the B. subtilis HU protein (HBsu). Full article

In this study, based on total column ozone observations from eight Antarctic stations, we evaluate the applicability of ERA5, C3S-MSR, MERRA-2, and JRA-55 reanalysis datasets and the NIWA-BS merged satellite dataset, in terms of interannual variation and long-term trend, using the correlation coefficient (R), root-mean-square error (RMSE), interannual variability skill score (IVS), and linear trend bias (TrBias). The results show that for interannual variation, C3S-MSR performs well at multiple stations, while JRA-55 performs poorly at most stations, especially Marambio, Rothera, and Faraday/Vernadsky, which are located at lower latitudes on the Antarctic Peninsula. Additionally, all datasets show significantly higher RMSE at Dumont D’Urville and Arrival Heights, which generally are located around the edge of the Antarctic stratospheric vortex where total column ozone values are more variable and on average larger than in the core of the vortex. The comprehensive ranking results show that C3S-MSR performs the best, followed by ERA5 and NIWA-BS, with MERRA-2 and JRA-55 ranking lower. For the long-term trend, each of the datasets has large bias values at Arrival Heights, and the absolute TrBias values of JRA-55 are larger at three stations on the Antarctic Peninsula. The overall averaged results show that C3S-MSR and NIWA-BS have the smallest absolute TrBias, and perform best in reflecting the Antarctic ozone trends, while ERA5 and JRA-55 significantly overestimate the Antarctic ozone recovery trend and perform poorly. Based on our analysis, the C3S-MSR dataset can be recommended to be prioritized when analyzing the interannual variations in Antarctic stratospheric ozone, and both the C3S-MSR reanalysis and NIWA-BS datasets should be prioritized for trend analysis. Full article

Background: MSLQ is a self-report instrument that measures motivational orientations and learning strategies of college students and is widely used to measure self-regulated learning. MSLQ has not been translated into Spanish and validated in the Spanish-speaking Latin American population. Objective: The objective of the study is to adapt, validate, and perform a factorial reduction of 9 out of 15 scales of the MSLQ instrument and correlate the scales with the grade point average (GPA) of a sample of health sciences university students. Methods: Nine scales (48 items) of the MSLQ were translated into Spanish and adapted to the Mexican population. Students were invited directly in their classrooms and filled out an electronic questionnaire with personal variables and these nine scales of the MSLQ instrument. We performed exploratory and confirmatory factor analysis (EFA and CFA) and based on the EFA a reduced version of the instrument was proposed. Results: A total of 439 students were included. The CFA showed unacceptable fit parameters with the original scale, therefore an item reduction and rearrangement were performed according to the EFA, and this yielded a reduced version with six scales and 25 items which showed acceptable fit parameters. This new reduced version rearranged the items of the effort regulation scale (ERE) into two different scales newly created in this version: time regulation (TRE) and self-regulation (SRE). The scales that disappeared in the reduced version were: intrinsic goal orientation (IGO), meta-cognitive self-regulation (MSR), and elaboration (ELA). Conclusions: The reduced version showed acceptable fit parameters that included the creation of two new scales (TRE and SRE). In addition, two scales were reduced (TVA and CTH), three scales were modified (MSE, TSE and ERE), two were unmodified (RHE and ORG), and two scales were eliminated (IGO and ELA). Full article

Nuclear energy cogeneration, which integrates electricity generation with thermal energy utilization, presents a transformative pathway for enhancing energy efficiency and decarbonizing industrial and urban sectors. This comprehensive review synthesizes advancements in technological stratification, economic modeling, and sectoral practices to evaluate the viability of nuclear cogeneration as a cornerstone of low-carbon energy transitions. By categorizing applications based on temperature requirements (low: <250 °C, medium: 250–550 °C, high: >550 °C), the study highlights the adaptability of reactor technologies, including light water reactors (LWRs), high-temperature gas-cooled reactors (HTGRs), and molten salt reactors (MSRs), to sector-specific demands. Key findings reveal that nuclear cogeneration systems achieve thermal efficiencies exceeding 80% in low-temperature applications and reduce CO₂ emissions by 1.5–2.5 million tons annually per reactor by displacing fossil fuel-based heat sources. Economic analyses emphasize the critical role of cost allocation methodologies, with exergy-based approaches reducing levelized costs by 18% in high-temperature applications. Policy instruments, such as carbon pricing, value-added tax (VAT) exemptions, and subsidized loans, enhance project viability, elevating net present values by 25–40% for district heating systems. Case studies from Finland, China, and Canada demonstrate operational successes, including 30% emission reductions in oil sands processing and hydrogen production costs as low as USD 3–5/kg via thermochemical cycles. Hybrid nuclear–renewable systems further stabilize energy supply, reducing the levelized cost of heat by 18%. The review underscores the necessity of integrating Generation IV reactors, thermal storage, and policy alignment to unlock nuclear cogeneration’s full potential in achieving global decarbonization and energy security goals. Full article

To enhance scene perception and comprehension, infrared and visible image fusion (IVIF) integrates complementary data from two modalities. However, many existing methods fail to explicitly separate modality-specific and modality-shared features, which compromises fusion quality. To surmount this constraint, we introduce a novel hierarchical dual-branch fusion (HDF-Net) network. The network decomposes the source images into low-frequency components, which capture shared structural information, and high-frequency components, which preserve modality-specific details. Remarkably, we propose a pin-wheel-convolutional transformer (PCT) module that integrates local convolutional processing with directional attention to improve low-frequency feature extraction, thereby enabling more robust global–local context modeling. We subsequently introduce a hierarchical feature refinement (HFR) block that adaptively integrates multiscale features using kernel-based attention and dilated convolutions, further improving fusion accuracy. Extensive experiments on four public IVIF datasets (MSRS, TNO, RoadScene, and M3FD) demonstrate the high competitiveness of HDF-Net against 12 state-of-the-art methods. On the RoadScene dataset, HDF-Net achieves top performance across six key metrics—EN, SD, AG, SF, SCD, and SSIM—surpassing the second-best method by 0.67%, 1.85%, 17.67%, 5.26%, 3.33%, and 1.01%, respectively. These findings verify the generalization and efficacy of HDF-Net in practical IVIF scenarios. Full article

In order to solve the problems of low efficiency and accuracy in the traditional detection of tunnel cracks, this paper proposes a tunnel crack detection method based on a UAV (unmanned aerial vehicle) equipped with a high-speed camera and a crack recognition algorithm using the improved multi-scale Retinex (MSR) algorithm and the Prewitt–Otsu algorithm, aiming to improve the accuracy and efficiency of detection. The tunnel crack detection method, based on a UAV equipped with a high-speed camera to acquire tunnel surface images, significantly improves the detection efficiency. The recognition method employs an improved multi-scale Retinex algorithm to process the acquired images, enhancing the details of the crack images and improving the contrast between cracks and the background. The enhanced images are input to the Prewitt–Otsu algorithm, which segments the crack image by combining Prewitt edge detection and Otsu thresholding. Finally, the pseudo-crack and isolated edges are removed by the minimum bounding rectangle principle. Using the UAV-collected tunnel surface images as targets, the tunnel crack recognition algorithm proposed in this paper is compared with other existing methods. The experimental results show that the method proposed in this paper improves the recognition ability of the small-texture features of the tunnel’s surface, and the overall crack recognition accuracy is higher than the existing methods. The proposed method not only enhances the efficiency of tunnel crack detection but also significantly improves the recognition accuracy, demonstrating substantial practical significance for tunnel maintenance and safety management. Full article

Inconel 617 is a nickel-based superalloy that is a primary candidate for use in next-generation nuclear applications such as the Gen IV Molten Salt Reactor (MSR) and Very-High-Temperature Reactor (VHTR) due to its corrosion and oxidation resistance and high strength in elevated temperatures. However, Inconel 617 machinability is poor due to its hardness and tendency to work harden during manufacturing. While the machinability of its sister grade, Inconel 718, has been widely studied and understood due to its applications in aerospace, there is a lack of knowledge regarding the behaviour of Inconel 617 in machining. To address this gap, this paper investigates the influence of cutting parameters in the turning of Inconel 617 and compares the impact of Minimum Quantity Lubrication (MQL) turning against conventional coolant. This investigation was performed through three distinct studies: Study A compared the performance of commercial coatings, Study B investigated the influence of cutting parameters on the surface finish, and Study C compared the performance of MQL to flood coolant. This work demonstrated that AlTiN coatings performed the best and doubled the tool life of a standard tungsten carbide insert compared to its uncoated form. Additionally, the feed rate had the largest impact on the surface roughness, especially at high feeds, with the best surface quality found at the lowest feed rate of 0.075 mm/rev. The utilization of MQL had mixed results compared to a conventional flood coolant in the machining of Inconel 617. Surface finish was improved as high as 47% under MQL conditions compared to the flood coolant; however, work hardening at the surface was also shown to increase by 10–20%. Understanding this, it is possible that MQL can completely remove the need for a conventional coolant in the machining of Inconel 617 components for the manufacturing of next-generation reactors. Full article

Bifidobacterium animalis is a widely used probiotic with significant health benefits, but its application is limited by oxygen sensitivity. Our laboratory previously developed an oxygen-tolerant B. animalis AR668-R1 using adaptive laboratory evolution under aerobic culture, but the molecular mechanism remains unclear. In this work, compared to the wild-type parental strain B. animalis AR668, 212 upregulated and 390 downregulated proteins were identified in AR668-R1 under aerobic conditions through comparative proteomic analysis. Enrichment analysis of the differentially expressed proteins between AR668 and AR668-R1 identified the potential oxygen-tolerant related pathways, including the translation process, transmembrane transport system, and carbohydrate metabolism. Furthermore, five potential oxygen-tolerance proteins (DapE, Mth2, MutT, Eno, and MsrAB) were validated by RT-qPCR that may contribute to the aerobic growth of AR668-R1. Through gene overexpression validation, Mth2 (7,8-dihydro-8-oxoguanine triphosphatase) was found to enhance the growth of AR668-R1 by 19.8% compared to the empty plasmid control under aerobic conditions. Our finding provides valuable insights into the oxygen-tolerant mechanisms of B. animalis at the protein level. Full article