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Cave dwellings in the Loess Plateau and western Henan region are ancient architectural forms that offer significant potential for rural revitalization and cultural heritage preservation. This study examines their role in Mogou Village through field surveys and mathematical analysis, highlighting their contributions to urban–rural integration, rural tourism, and cultural sustainability. Key findings include the mean radiant temperature (MRT) in cave dwellings remaining stable between 22.7–25.9 °C, facilitating lower indoor temperatures in summer. These dwellings maintain an APMV within the Class I thermal environment (−0.5 ≤ APMV ≤ 0.5), achieving a 90% satisfaction rate for thermal comfort. Despite excellent thermal insulation, improvements in ventilation design are necessary. Moreover, cave dwellings attract urban residents, fostering urban–rural integration and rural tourism development. They also preserve cultural heritage through traditional construction techniques and philosophical thought. Preserving local characteristics while protecting traditions is essential for social harmony, economic development, and cultural inheritance, supporting sustainable urban–rural integration.

This paper reports on the development of a resource-efficient FPGA-based neural network regression model for potential applications in the future hardware muon trigger system of the ATLAS experiment at the Large Hadron Collider (LHC). Effective real-time selection of muon candidates is the cornerstone of the ATLAS physics programme. With the planned ATLAS upgrades for the High Luminosity LHC, an entirely new FPGA-based hardware muon trigger system will be installed that will process full muon detector data within a 10 μs latency window. The large FPGA devices planned for this upgrade should have sufficient spare resources to allow deployment of machine learning methods for improving identification of muon candidates and searching for new exotic particles. Our neural network regression model promises to improve rejection of the dominant source of background trigger events in the central detector region, which are due to muon candidates with low transverse momenta. This model was implemented in FPGA using 157 digital signal processors and about 5000 lookup tables. The simulated network latency and deadtime are 122 and 25 ns, respectively, when implemented in the FPGA device using a 320 MHz clock frequency. Two other FPGA implementations were also developed to study the impact of design choices on resource utilisation and latency. The performance parameters of our FPGA implementation are well within the requirements of the future muon trigger system, therefore opening a possibility for deploying machine learning methods for future data taking by the ATLAS experiment.

With the intensification of population aging in rural areas, it becomes increasingly important to analyze the post-retirement migration intention of rural residents and the variables influencing these intentions. However, there is a lack of research on this point. In this study, we focused on rural residents aged 45 to 60 and used the logistic regression model to investigate the demographic and personal variables influencing their post-retirement migration intention. The data used in this study were collected from one hundred sixty-four households in three rural areas of Inner Mongolia in 2011. From the results of this study, we found that gender, part-time employment, savings level, children’s residence and occupational stability, and interest in urban living positively affect migration intention. In contrast, the number of rural close friends, relationships with others in rural areas, and evaluation of rural living all have negative effects. In addition, we employed age and the proportion of mobile income as control variables to examine the variables that influence the post-retirement migration intention in different age groups and mobile income groups. The analysis reveals that the variables influencing post-retirement migration intention varied across age groups and mobile income groups, and this variation can be attributed to the differences between groups’ characteristics.

Salinized soil often exhibits high salt content and low nutrient availability, leading to the reduction of soil ecosystem function and crop productivity. Although straw return has profound effects on saline soil improvement, how soil quality index (SQI), soil ecosystem multifunctionality (EMF), and crop yield respond to different organic ameliorants remain unclear. Herein, a field experiment was established to explore the influence of various straw management strategies (no organic ameliorant, CK; corn straw return, CS; and corn straw biochar return; CB) on the saline soil functions and crop productivity. In relation to CK and CB, CS significantly improved SQI by 52% and 35%, respectively. This may be due to the decreased soil salt (especially soluble Na + ) and increased available nutrients under corn straw return. Furthermore, CS increased soil EMF than CK by 71% and CB by 39%, which was caused by the increased activities of 1,4-β-glucosidase, β-1,4- N -acetyl-glucosaminidase, and leucine aminopeptidase. The linear model further supported that soil enzyme activities are positively related to available nutrient contents and negatively correlated with salt content. Moreover, the crop yield under CS significantly increased by 22% compared to CK. Also, soil quality positively influenced crop yield, with soil salt and available phosphorus being the primary influencing factors. However, crop yield was not sensitive to soil EMF. In summary, straw return was more beneficial to improving soil quality and crop productivity than biochar in the short term in saline soils.

Yutu-2 rover conducted an exciting expedition on the 41st lunar day to investigate a fin-shaped rock at Longji site (45.44°S, 177.56°E) by extending its locomotion margin on perilous peaks. The varied locomotion encountered, especially multi-form wheel slippage, during the journey to the target rock, established unique conditions for a fin-grained lunar regolith analysis regarding bearing, shear and lateral properties based on terramechanics. Here, we show a tri-aspect characterization of lunar regolith and infer the rock’s origin using a digital twin. We estimate internal friction angle within 21.5°−42.0° and associated cohesion of 520-3154 Pa in the Chang’E-4 operational site. These findings suggest shear characteristics similar to Apollo 12 mission samples but notably higher cohesion compared to regolith investigated on most nearside lunar missions. We estimate external friction angle in lateral properties to be within 8.3°−16.5°, which fills the gaps of the lateral property estimation of the lunar farside regolith and serves as a foundational parameter for subsequent engineering verifications. Our in-situ spectral investigations of the target rock unveil its composition of iron/magnesium-rich low-calcium pyroxene, linking it to the Zhinyu crater (45.34°S, 176.15°E) ejecta. Our results indicate that the combination of in-situ measurements with robotics technology in planetary exploration reveal the possibility of additional source regions contributing to the local materials at the Chang’E-4 site, implying a more complicated geological history in the vicinity. Digital twins can be used to support planetary operations and analysis. Here, the authors show tri-aspect characterization of lunar far side regolith and investigate the origin of a fin-shaped rock via digital twin of Yutu-2 rover.

Fungal bioaerosols play a critical ecological and health role in intensive poultry production systems. However, their dynamic characteristics and community succession patterns in confined cage environments during winter remain poorly understood. This study investigated a typical confined broiler house in Hebei Province, China, during winter. A combined approach of Andersen six-stage sampling, colony counting, and Internal Transcribed Spacer (ITS) high-throughput sequencing was employed to comprehensively analyze the concentration, particle size distribution, diversity, and community composition of fungal bioaerosols across three key growth stages: 7 days (brooding phase), 21 days (growing phase), and 35 days (finishing phase). The results revealed a significant increasing trend in fungal aerosol concentration as the rearing cycle progressed, increasing from 1125 ± 125 CFU/m3 at day 7 to 3872 ± 565 CFU/m3 at day 35 (p < 0.001), reaching high-risk exposure levels in the later stages. Small-sized fungal bioaerosols (<4.7 μm) were dominant across all stages (54.35–65.50%), with the highest proportion observed at day 21, indicating their potential for deep respiratory deposition and long-distance airborne transmission. The number of Operational Taxonomic Units (OTUs), along with Chao1 and Shannon indices, increased significantly with bird age (p < 0.001), demonstrating a clear community succession from early-stage yeast-dominated forms (e.g., Diutina, Blumeria) to mid- and late-stage assemblages dominated by filamentous fungi (e.g., Aspergillus, Cladosporium, Alternaria). Notably, several zoonotic pathogenic genera were detected throughout all rearing stages, highlighting the potential risks of airborne fungi to animal health, occupational exposure, and environmental safety under winter ventilation restrictions. This study characterizes a stage-dependent pattern of increasing airborne fungal concentrations accompanied by shifts in particle size distribution and community composition under winter confined conditions. The findings provide a crucial scientific basis for optimizing winter ventilation and environmental management strategies, improving environmental control technologies, establishing airborne biosafety standards, and developing targeted fungal monitoring and prevention technologies.

Bioaerosols are a major source of airborne microbial contamination in intensive poultry production systems. Their concentration and community structure can profoundly influence animal health, public health, and the overall safety of the farming environment. However, the dynamic characteristics of bacterial aerosols in enclosed poultry houses during winter remain insufficiently studied. Using Taihang chickens as a model, this study investigated three key production stages—brooding (15 days), growing (60 days), and laying (150 days)—under winter cage-rearing conditions. A six-stage Andersen sampler was employed alongside culture-dependent enumeration and 16S rRNA high-throughput sequencing to analyze variations in bacterial aerosol concentration, particle size distribution, and community succession patterns. The results revealed a significant increase in the concentration of culturable airborne bacteria with bird age, rising from 8.98 × 103 colony-forming unit (CFU)/m3 to 2.89 × 104 CFU/m3 (p < 0.001). The particle size distribution progressively shifted from larger, settleable particles (≥4.7 μm) toward smaller, respirable particles (<4.7 μm). Microbial sequencing indicated a continuous increase in bacterial alpha diversity across the three stages (Chao1 and Shannon indices, p < 0.05), while beta diversity exhibited stage-specific clustering, reflecting clear differences in community assembly. The composition of dominant bacterial genera transitioned from potentially pathogenic taxa such as Acinetobacter and Corynebacterium during the brooding stage to a greater abundance of beneficial genera, including Bacteroides, Lactobacillus, and Ruminococcus, in later stages. This shift suggests a potential ecological link between aerosolized bacterial communities and host development, possibly related to the aerosolization of gut microbiota. Notably, several zoonotic bacterial species were detected in the poultry house air, indicating potential public health and occupational exposure risks under winter confinement conditions. This study is the first to elucidate the ecological succession patterns of airborne bacterial aerosols in Taihang chicken houses across different growth stages during winter. The findings provide a scientific basis for optimizing winter ventilation strategies, implementing stage-specific environmental controls, and reducing pathogen transmission and occupational hazards.

Marginal land conversion to perennial energy crops can provide biomass feedstocks and climate change mitigation. However, the effect of perennial energy crop cultivation on soil organic carbon (SOC) sequestration and its underlying mechanism in marginal land still remains incomplete. Here, SOC turnover, stability, and its potential sequestration were evaluated based on 10 years of land use change from C3 grass‐dominated marginal land to C4 energy crops Miscanthus and switchgrass cultivation. The naturally occurring 13C signature down to 60 cm depth was used to determine the energy crops‐derived C. Compared to reference marginal land, Miscanthus plantation increased the SOC stock at 0–60 cm depth by 17.8% and 64.3% in bulk and root zone, respectively. Similarly, the SOC stock under switchgrass was also 16.5% and 93.0% higher in bulk and root zone than in reference marginal land, respectively. The higher SOC stock in the root zone of switchgrass relative to Miscanthus was supported by the higher contribution of C4‐derived C to SOC (44.5% vs. 32.4%). The mean residence time of old C was higher under switchgrass than Miscanthus in the bulk zone across 0–60 cm (p < 0.05) but remained the same at 0–20 cm in the root zone. Specific SOC mineralization and temperature sensitivity were lower in soils under Miscanthus and switchgrass compared to reference marginal land. The partial least squares path model revealed that perennial energy crop cultivation enhances soil C stock via increased C4‐derived C input and reduced mineralization. In conclusion, marginal land conversion to perennial energy crops is a win–win strategy for C sequestration to mitigate climate change and support the growing bioenergy sector with biomass supply. Marginal land conversion to perennial energy crops increased soil C stocks. Switchgrass had a higher soil C sequestration potential than Miscanthus. New C4‐C input exceeds old C3‐C losses via mineralization leading to C sequestration.

Ebola virus (EBOV) infection constitutes a significant global public health threat, and no curative treatment is currently available for it. Rapid and accurate detection of EBOV nucleic acid is crucial for controlling the spread of Ebola virus disease (EVD). The gold standard for EBOV diagnosis is real-time reverse transcription polymerase chain reaction (RT-qPCR), which requires costly equipment and skilled personnel, potentially hindering its application for rapid detection, especially in resource-limited settings. Consequently, there is an urgent need to develop a simple, accurate, and rapid diagnostic method for EVD. In this study, a real-time reverse transcription recombinase-aided amplification (RT-RAA) assay was developed for the specific visual detection of the conserved region of the EBOV nucleoprotein (NP) gene. The RT-RAA assay can be completed within 30 min at 42 °C, and results can be visualized using a portable blue light imager. The assay exhibited strong analytical specificity toward EBOV. No cross-reactivity was observed with any of the other public-health-relevant viruses tested. The visual RT-RAA assay demonstrated sensitivity comparable to RT-qPCR, detecting 52 copies per reaction at a 95% probability level, whereas RT-qPCR required 74 copies per reaction. The RAA method demonstrated excellent repeatability and stability, with intra-assay and inter-assay CVs less than 5% and 7%, respectively. These results clearly indicate that the visual RT-RAA method is specific, accurate, simple, rapid, and reliable for EBOV detection.

Fungal aerosols are critical yet understudied bioaerosol components in enclosed poultry environments, particularly during winter when ventilation is restricted. This study investigated stage-specific variations in fungal aerosol concentration, size distribution, and community composition in Taihang chicken houses across three growth stages (15, 60, and 150 days). Culturable fungal concentrations significantly increased from 3.16 × 103 CFU/m3 to 1.24 × 104 CFU/m3 with bird age (p < 0.001, ANOVA). Respirable particles (<4.7 μm) consistently dominated the fungal size distribution. ITS sequencing revealed progressive increases in fungal richness and distinct community shifts among stages. Several fungi with zoonotic potential, including Aspergillus, Cladosporium, Cryptococcus, and Fusarium, were detected across all stages. These findings demonstrate that wintertime enclosed ventilation, while thermally beneficial, promotes the accumulation of respirable fungal aerosols and elevates occupational and environmental health risks. From a One Health perspective, stage-specific mitigation strategies—such as ventilation optimization, reduction in organic dust sources, and routine monitoring of respirable fungal fractions—are essential for reducing exposure risks in cold-season poultry production.