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The Space Radiobiological Exposure Facility (SREF) is a general experimental facility at the China Space Station for scientific research in the fields of space radiation protection, space radiation biology, biotechnology, and the origin of life. The facility provides an environment with controllable temperatures for experiments with organic molecules and model organisms such as small animals, plant seeds, and microorganisms. The cultivation of small animals can be achieved in the facility with the use of microfluidic chips and images and videos of such experiments can be captured by microscopy. SREF also includes a linear energy transfer (LET) detector, neutron detectors, and a solar ultraviolet (UV) detector to measure the LET spectrum of the charged particles, energy spectrum and dose equivalent of neutrons, and fluence of solar UV radiation, respectively. The facility is reusable, and the model organisms from the first exposure experiment were recovered in orbit and returned to the ground for further study.

Industrial heat sources (IHSs) are major contributors to energy consumption and environmental pollution, making their accurate detection crucial for supporting industrial restructuring and emission reduction strategies. However, existing models either focus on single-class detection under complex backgrounds or handle multiclass tasks for simple targets, leaving a gap in effective multiclass detection for complex scenarios. To address this, we propose a novel multiclass IHS detection model based on the YOLOv8-FC framework, underpinned by the multiclass IHS training dataset constructed from optical remote sensing images and point-of-interest (POI) data firstly. This dataset incorporates five categories: cement plants, coke plants, coal mining areas, oil and gas refineries, and steel plants. The proposed YOLOv8-FC model integrates the FasterNet backbone and a Coordinate Attention (CA) module, significantly enhancing feature extraction, detection precision, and operational speed. Experimental results demonstrate the model’s robust performance, achieving a precision rate of 92.3% and a recall rate of 95.6% in detecting IHS objects across diverse backgrounds. When applied in the Beijing–Tianjin–Hebei (BTH) region, YOLOv8-FC successfully identified 429 IHS objects, with detailed category-specific results providing valuable insights into industrial distribution. It shows that our proposed multiclass IHS detection model with the novel YOLOv8-FC approach could effectively and simultaneously detect IHS categories under complex backgrounds. The IHS datasets derived from the BTH region can support regional industrial restructuring and optimization schemes.

N6-methyladenosine (m6A) plays a role in the development of tumors. However, the specific role of VIRMA, an RNA methyltransferase, in pancreatic ductal adenocarcinoma (PDAC) remains unclear. This study shows that VIRMA expression is elevated in PDAC. Increased VIRMA levels promoted PDAC growth and spread, while reducing VIRMA expression slowed these processes. VIRMA facilitated SLC43A2 mRNA degradation through an m6A-YTHDF2 pathway. The resulting decrease in SLC43A2 reduced phenylalanine absorption and oxidative stress, further driving PDAC progression. Furthermore, alcohol increased C/EBP β expression, which bound to VIRMA's promoter, enhancing its transcription. These findings suggest a connection between alcohol consumption, m6A modifications, and phenylalanine absorption in PDAC progression, offering a new approach to combat this disease.

Understanding how species respond to climate change can facilitate species conservation and crop breeding. Current prediction frameworks about population vulnerability focused on predicting range shifts or local adaptation but ignored genetic load, which is also crucial for adaptation. By analyzing 1115 globally distributed Arabidopsis thaliana natural accessions, we find that effective population size (Ne) is the major contributor of genetic load variation, both along genome and among populations, and can explain 74-94% genetic load variation in natural populations. Intriguingly, Ne affects genetic load by changing both effectiveness of purifying selection and GC biased gene conversion strength. In particular, by incorporating genetic load, genetic offset and species distribution models (SDM), we predict that, the populations at species' range edge are generally at higher risk. The populations at the eastern range perform poorer in all aspects, southern range have higher genetic offset and lower SDM suitability, while northern range have higher genetic load. Among the diverse natural populations, the Yangtze River basin population is the most vulnerable population under future climate change. Overall, here we deciphered the driving forces of genetic load in A. thaliana, and incorporated SDM, local adaptation and genetic load to predict the fate of populations under future climate change.

The potential risk for CO2 leakage from carbon capture and storage (CCS) systems has raised significant concerns. While numerous studies have explored how crops respond to elevated soil CO2 levels, relatively few have examined the impacts on vegetables. Tomatoes (Solanum lycopersicum) are a key vegetable crop, and this study sought to investigate how CO2 leakage affects their yield and quality. We conducted pot experiments comparing tomatoes grown under control conditions (no added CO2) with those exposed to elevated soil CO2 levels (1500 g m-2d-1). Our findings indicate that under CO2 leakage conditions, the overall biomass of tomato plants, average fruit weight, and fruit size decreased by 47.42%, 47.65%, and 20.2%, respectively. Notably, the titratable acid content in the tomatoes increased by 27.5%, resulting in a sourer taste. The tomato fruit grades and sugar acid ratio declined leading to a seriously commercial value loss of tomatoes in response to elevated soil CO2 levels. This study provides a more quantitative understanding of how vegetables like tomatoes respond to CO2 leakage, which is crucial for CCS decision-makers to comprehend the adverse effects of CO2 leaks on agriculture.

Solar energy, the most promising renewable energy, suffers from intermittency and discontinuity. Phase change material (PCM)-based energy storage technology can mitigate this issue and substantially improve the utilization efficiency of solar energy. However, most PCMs have a low photothermal conversion capacity and are prone to leaks. To address these two key issues of PCMs, fine modification and mineral encapsulation have been employed and demonstrated to be effective methods. This review summarizes the structure of mineral materials and discusses the corresponding encapsulation techniques and preparation methods for mineral-based composite PCMs. Based on this, we focus on reviewing methods for enhancing the photothermal conversion performance of mineral-based PCMs and explore their underlying mechanisms. Furthermore, we present practical application cases of photothermal mineral-based composite PCMs, analyzing their potential in photothermal applications. Finally, we discuss the challenges encountered during the synthesis, modification, and application processes of photothermal mineral-based composite PCMs, providing insights into future directions for the efficient utilization of solar energy.

La transferencia de energía no lineal se representa a través de la viscosidad de Foucault y el forzamiento estocástico en el marco del análisis de disolventes. Investigaciones previas estiman la contribución del operador de resolvente mejorado con viscosidad parásita a la transferencia de energía no lineal. El presente artículo estima la contribución del forzamiento estocástico a la transferencia de energía no lineal y demuestra que la contribución del forzamiento estocástico no puede ignorarse. Estos resultados se logran comparando numéricamente el operador de resolvente mejorado con viscosidad parásita y el forzamiento estocástico con la transferencia de energía no lineal en flujos de canales turbulentos. Además, los resultados numéricos indican que los operadores de resolventes compuestos pueden mejorar la predicción de la transferencia de energía no lineal. Le transfert d'énergie non linéaire est représenté par la viscosité tourbillonnaire et le forçage stochastique dans le cadre de l'analyse des résolvants. Des investigations antérieures ont estimé la contribution de l'opérateur résolvant à viscosité de Foucault améliorée au transfert d'énergie non linéaire. Le présent article estime la contribution du forçage stochastique au transfert d'énergie non linéaire et démontre que la contribution du forçage stochastique ne peut être ignorée. Ces résultats sont obtenus en comparant numériquement l'opérateur résolvant à viscosité de Foucault améliorée et le forçage stochastique avec le transfert d'énergie non linéaire dans les écoulements de canaux turbulents. En outre, les résultats numériques indiquent que les opérateurs de résolvant composite peuvent améliorer la prédiction du transfert d'énergie non linéaire. Nonlinear energy transfer is represented through eddy viscosity and stochastic forcing within the framework of resolvent analysis. Previous investigations estimate the contribution of eddy-viscosity-enhanced resolvent operator to nonlinear energy transfer. The present article estimates the contribution of stochastic forcing to nonlinear energy transfer and demonstrates that the contribution of stochastic forcing cannot be ignored. These results are achieved by numerically comparing the eddy-viscosity-enhanced resolvent operator and stochastic forcing with nonlinear energy transfer in turbulent channel flows. Furthermore, the numerical results indicate that composite resolvent operators can improve the prediction of nonlinear energy transfer. يتم تمثيل نقل الطاقة غير الخطية من خلال اللزوجة الدوامية والتأثير العشوائي في إطار التحليل المحلل. تقدر التحقيقات السابقة مساهمة مشغل المحلول المعزز بالدوامة واللزوجة في نقل الطاقة غير الخطية. تقدر هذه المقالة مساهمة التأثير العشوائي في نقل الطاقة غير الخطية وتوضح أنه لا يمكن تجاهل مساهمة التأثير العشوائي. يتم تحقيق هذه النتائج من خلال المقارنة العددية لمشغل المحلول المحسن باللزوجة الدوامية والتأثير العشوائي مع نقل الطاقة غير الخطية في تدفقات القنوات المضطربة. علاوة على ذلك، تشير النتائج العددية إلى أن مشغلي المحلول المركب يمكنهم تحسين التنبؤ بنقل الطاقة غير الخطية.

This paper summarizes the research progress and applications of oxygen-reduced-air-assisted gravity drainage (OAGD) in enhanced oil recovery (EOR). The fundamental principles and key technologies of OAGD are introduced, along with a review of domestic and international field trials. Factors influencing displacement performance, including low-temperature oxidation reactions, injection rates, and reservoir dip angles, are discussed in detail. The findings reveal that low-temperature oxidation significantly improves the recovery efficiency through the dynamic balance of light hydrocarbon volatilization and fuel deposition, coupled with the synergistic optimization of the reservoir temperature, pressure, and oxygen concentration. Proper control of the injection rate stabilizes the oil–gas interface, expands the swept volume, and delays gas channeling. High-dip reservoirs, benefiting from enhanced gravity segregation, demonstrate superior displacement efficiency. Finally, the paper highlights future directions, including the optimization of injection parameters, deepening studies on reservoir chemical reaction mechanisms, and integrating intelligent gas injection technologies to enhance the effectiveness and economic viability of OAGD in complex reservoirs.

We have previously reported that high-alcohol-producing Klebsiella pneumoniae (HiAlc Kpn) in the gut can cause endo-alcoholic fatty liver disease. Here, we discover that 91.2% of Kpn isolates from pulmonary disease samples also produce excess ethanol, which may be associated with respiratory disease severity. To further explore the potential mechanism, a murine model is established with high-dose bacteria. Kpn stimulates granular neutrophils (G0), subsequently transforming them into phagocytic neutrophils (G1). HiAlc Kpn also causes dysfunction of pyrimidine metabolism, leading to neutrophil apoptosis. These changes inhibit phagocytosis of neutrophils and possibly suppress inflammasome-dependent innate immunity. In a persistent infective murine model, HiAlc Kpn induces lung fibrosis and production of reactive oxygen species (ROS), possibly affecting epithelial cell apoptosis and lung function. The results suggest that the subtype of neutrophil is a potential biomarker for the severity of lung injury caused by HiAlc Kpn.