Search Results (487)

Due to an insufficient understanding of the dynamic mechanisms underlying seasonal variations in Daqu fermentation quality, such as microbial community succession, enzyme activity, and metabolic regulation, precise control of Daqu quality and consistency across different seasons has not yet been achieved. Environmental factors, especially temperature and humidity, exert a significant influence on the microbial community structure and enzyme activity during the production process of Daqu. To this end, the recent research progress on changes in microbial community structure and succession, regulation of enzyme activity and metabolic pathways, and biosynthesis of flavor compounds in Daqu across different seasons was reviewed. Furthermore, we proposed strategies to leverage seasonal microbial patterns for precise control over Daqu production throughout varying seasons. This work aims to enhance the quality and consistency of Daqu across seasons and effectively improve the quality of Baijiu products. Full article

Alternariol (AOH) and alternariol monomethyl ether (AME) are major mycotoxins produced primarily by Alternaria alternata on cereal grains and fruits. A. alternata is a causative pathogen of strawberry black spot disease. However, little is known about the characteristics of A. alternata, which was isolated from strawberry products. In the present study, we evaluated the influence of temperature, pH, and relative humidity (RH) on the growth of A. alternata OM1 and its production of AOH and AME on different media including strawberry puree agar medium (SPAM) after its isolation from strawberry jam. The fungal strain showed the highest growth rate at 25 °C under pH 6.5 and RH 97%, while the highest amounts of AOH and AME were produced by the strain at 25 °C under pH 4.5 and RH 97%. Additionally, the strain did not produce AOH and AME on SPAM at 25 °C under RH 92% until 7 days. Moreover, RT-qPCR analysis exhibited that relative expression levels of 2 AOH or AME biosynthetic genes (pksI and omtI) in A. alternata OM1 were up-regulated in YES medium, while they were not in MEB medium. Our results demonstrated that the three key environmental parameters had a significant influence on the growth of A. alternata OM1 and its production of AOH and AME. These findings suggest that storage of strawberries below 25 °C under RH 92% could prevent the production of AOH and AME by A. alternata OM1 on them. Full article

An integrated analysis incorporating total organic carbon (TOC) content measurement, X-ray diffraction (XRD), scanning electron microscopy (SEM), and gas adsorption experiments was performed on core samples from Well FY1-4 of the upper-fourth Shahejie Formation (Es₄) in the Minfeng Sag. To address the lack of systematic research on the pore and fractal characteristics of organic-rich low-maturity shales in the Minfeng Sag (against the preponderance of studies on high-maturity shales), this study characterized the lithofacies, reservoir space and pore fractal features of the target low-maturity shale interval and clarified the sedimentary controls on lithofacies and key factors regulating pore fractal heterogeneity. The results reveal that the shale in the Es₄ of the study area exhibits low thermal maturity, with six distinct lithofacies identified. Organic-rich laminated calcareous shale lithofacies (RL-1) and organic-rich laminated calcareous/argillaceous mixed shale lithofacies (RL-2) represent the most favorable lithofacies, which are dominated by large mesopores and macropores. Their reservoir spaces were primarily composed of intergranular pores, intragranular pores, and organic pores, whereas the other lithofacies are dominated by small mesopores. The pore surface fractal dimension (D) was calculated using the Frenkel–Halsey–Hill (FHH) model based on low-temperature N₂ adsorption (LTNA) data. The meso-macropore system shows higher heterogeneity than the micropore system (D₂ > D₁). Both D₁ and D₂ exhibit a weak negative correlation with TOC and carbonate content and a positive correlation with clay content. In the initial depositional stage of the Es₄, the arid climate, weak terrigenous input, shallow lake depth, and high salinity resulted in the strongly reducing saline depositional environment with relatively low organic matter enrichment. As the climate became progressively humid in the middle and late stages, hydrodynamic conditions intensified, leading to a lithofacies transition from mixed shales to argillaceous calcareous shales. Increased TOC and carbonate contents reduce the pore fractal dimension of shale. Smaller fractal dimensions directly indicate a simple pore structure and regular pore surface in the shale oil reservoir of the Minfeng Sag, where reservoir space is dominated by large pores such as intercrystalline pores and dissolved pores. Such pore characteristics are more favorable for the enrichment of shale oil. Full article

Plantago lanceolata L. is increasingly incorporated in temperate pasture systems for its agronomic resilience and potential to reduce the environmental footprint of ruminant production through its specific secondary metabolites (SMs). However, how light intensity per se regulates P. lanceolata L. physiology, nutritive value and SM accumulation remains poorly understood due to confounding factors in field studies. This controlled-environment study evaluated the effects of three light intensities (200, 300, and 400 µmol photons m⁻² s⁻¹) on morphophysiological traits, forage quality, and SM concentrations in P. lanceolata L. cv. “Ceres Tonic”. Plants were grown in controlled-environment chambers under similar temperature, humidity and nutrient conditions. Morphological traits, biomass allocation, chlorophyll fluorescence, gas exchange, chemical composition, and root architecture were measured. Additionally, the most important secondary metabolites, aucubin, catalpol and acteoside, were also evaluated. Under the different light intensity treatments plants maintained stable physiological parameters, total biomass production, leaf dimensions or root architecture. However, moderate light intensity (300 µmol photons m⁻² s⁻¹) optimized nutritive value by minimizing fiber concentrations and maximizing metabolizable energy. Acteoside concentration, as well as the iridoid glycosides aucubin and catalpol, were not affected by the different light intensities. These findings demonstrate that P. lanceolata L. maintains morphophysiological stability across the tested light intensity range studied, while selectively modulating forage quality. Full article

To investigate concrete drying shrinkage in high-altitude environments, moisture evaporation and shrinkage rates were examined under combined curing regimes of four temperatures (40 °C, 20 °C, 0 °C, −10 °C) and three relative humidities (RH40%, RH60%, RH80%). Curing temperature and humidity primarily regulate shrinkage deformation by altering the internal moisture evaporation rate. Both evaporation and shrinkage rates exhibited a rapid initial increase, followed by deceleration, and finally stabilization with increasing age. A strong positive correlation was observed between these two parameters. The high-temperature and low-humidity condition (40 °C, RH40%) induced the most severe shrinkage. Four machine learning algorithms (XGBoost, RF, ANN, and KNN) were used to construct prediction models. After hyperparameter optimization and cross-validation, the RF models exhibited superior generalization and robustness (test set R² > 0.94). The model accurately captures the complex non-linear relationship between environmental parameters and shrinkage. SHAP analysis on the optimal models identified the moisture evaporation rate as the primary driving factor. The analysis quantified the non-linear contributions of temperature and age, alongside the inhibitory effect of humidity. The study verified the consistency between data-driven models and physical mechanisms. This study elucidates the shrinkage mechanism under extreme conditions. It provides a reliable reference for crack control and life prediction in high-altitude engineering. Full article

The building façade serves as the primary interface between the built environment and external climate, marking the transition from static regulation to dynamic response in climate-adaptive design. While existing research predominantly addresses periodic climatic elements such as temperature and solar radiation, the highly stochastic wind environment and its potential for internal acoustic problems remain systematically unexplored. This study investigates the acoustic modulation mechanism of building façades under dynamic wind conditions through a simulation-based methodology. The primary aim is to demonstrate the use of active control to mitigate the influence of fluctuating wind on the internal acoustic environment of buildings with open windows or semi-open boundaries, focusing on the coupling between stochastic wind fields and architectural acoustics in humid subtropical climates. We propose a wind-responsive adaptive acoustic façade system employing fractal geometry and configurable delay strategies, and develop a high-fidelity simulation framework to quantify how façade geometry and activation logic regulate acoustic parameters under varying wind conditions (1–8 m/s). Results indicate that: (1) support vector regression-based mapping of wind speed to delay strategies maintains key sound-field parameters (Lateral Fraction (LF), Speech Clarity (C₅₀), and Early Decay Time to Reverberation Time ratio (EDT/RT₃₀)) within 10% fluctuation across wind regimes; (2) fractal configurations achieve balanced wide-band (125 Hz–8 kHz) performance, with SPL fluctuation <3 dB, spectral tilt (+0.3 dB), and reverberation time slope <0.3; (3) configurational switching between column (high LF) and row (high C₅₀) arrangements enables dynamic trade-off between spatial impression and speech clarity. This work establishes an integrated framework coupling wind dynamics, façade morphology, and acoustic modulation to regulate objective indoor acoustic parameters. Based on the simulated omnidirectional point-source model, the results show that key acoustic indicators remain stable across varying wind conditions, providing a theoretical and quantifiable basis for climate-responsive acoustic envelope design. Future work will include empirical prototype testing and listening tests to determine whether these simulated acoustic parameters translate into improved comfort and well-being for occupants. Full article

Body temperature regulation in ectotherms is influenced by numerous environmental, morphological, and physiological factors, some of which operate in population-specific ways. Understanding how these factors shape thermal biology is important for species conservation. The nose-horned viper, an ecologically significant yet understudied mesopredator of southeastern Europe and Asia Minor, occupies diverse ecosystems facing ongoing degradation. Over five years, we investigated how 12 environmental, behavioral, morphological, and physiological variables influenced field body temperature across three climatically distinct populations of nose-horned vipers. Using an information-theoretic approach with model averaging, we identified important predictors and assessed population-specific effects. Air temperature at 5 cm above the snake’s position, humidity, and wind were highly important predictors across all populations, whereas physiological states (shedding and digestion) exerted weaker effects. Microhabitat type and time of day emerged as highly important population-specific predictors, while body size showed weaker, population-dependent effects. Neither sex, cloud cover, nor behavioral state contributed meaningfully to model fit. Mean body temperatures were similar across populations and sexes. By integrating environmental, behavioral, physiological, and morphological variables, this study comprehensively identifies predictors of body temperature in nose-horned vipers. Site-tailored maintenance of structurally diverse habitats is essential for preserving thermoregulatory opportunities and ensuring long-term persistence of nose-horned vipers. Full article

Under intensifying climate change and increasingly frequent extreme heat events, improving outdoor thermal environments has become critical for sustainable human settlements. While prior studies have mainly focused on urban contexts, systematic investigations of rural microclimates—particularly regarding the regulatory mechanisms of landscape configurations—remain limited. This study examines a mountain-adjacent village in the Loess Tableland region of China, integrating field measurements with ENVI-met simulations to analyze thermal characteristics of rural road spaces and the effects of vegetation and paving materials on human thermal comfort. The results show that village boundary areas experience the largest fluctuations in air temperature and relative humidity during midday and evening, indicating higher thermal sensitivity. Model validation demonstrates satisfactory accuracy, with RMSE values of 0.39–3.62 °C for air temperature, 1.32–3.22% for relative humidity, and 1.35–2.24 m/s for wind speed, and MAPE ranging from 0.80% to 9.05%. Furthermore, Basalt Brick and Populus alba show the best cooling performance, but when considering multiple factors such as temperature, humidity, and wind speed, Ligustrum lucidum has the most significant effects in improving thermal comfort and increasing humidity. Analysis based on Physiological Equivalent Temperature (PET) further indicates that vegetation configurations play a more substantial role in thermal comfort regulation than paving materials, and that different landscape elements exhibit synergistic and trade-off relationships in terms of cooling, humidification, and ventilation. This study provides quantitative reference for vegetation configuration and material selection in rural roads within the Loess Tableland region and similar semi-arid areas, enriches the research scope of rural microclimate studies, and offers scientific support for climate-adaptive rural planning and optimization of rural living environments. Full article

Microbial communities are the fundamental determinants of Nongxiang Daqu quality. In this study, we systematically investigated the assembly and succession mechanisms of microbial communities during Nongxiang Daqu fermentation. Our findings reveal that this ecological succession is primarily driven by deterministic processes, encompassing dynamic environmental variables and interspecific microbial interactions. Significant stage-specific temporal variations in the community structure were observed, and biomarkers identified via a random forest model further corroborated these dynamic successional patterns. Both the neutral community model and Modified Stochasticity Ratio (MST) tests demonstrated that community assembly is dominated by deterministic processes, the influence of which intensifies as fermentation progresses. Notably, the fungal community exhibited a more pronounced response to these deterministic environmental selections than the bacterial community. Furthermore, co-occurrence network analysis, Mantel tests, and redundancy analysis (RDA) collectively illustrated that microbial interactions and environmental factors—specifically temperature, humidity, oxygen, carbon dioxide, and acidity—synergistically regulate this succession. Crucially, the rates of change in these environmental parameters directly dictated the pace of microbial turnover. Among these, oxygen and acidity had the greatest influence: oxygen accounted for 17.32% and 29.05% of the effects on fungi and bacteria, respectively, while acidity accounted for 16.77% and 25.23%, respectively. Time-series forecasting indicated that community structural assembly and stabilization predominantly conclude within the initial 30 days of fermentation. Ultimately, this study uncovers the ecological driving forces shaping the Nongxiang Daqu microbiome, providing a vital theoretical foundation for the targeted regulation of Daqu microecology and the enhancement of product quality. Full article

To address the strong nonlinearity, coupling, and time-delay characteristics in greenhouse environmental regulation, as well as the large overshoot and limited robustness of conventional proportional–integral–derivative (PID) control, while considering the practical constraint that complex intelligent control methods are difficult to deploy directly on low-cost industrial controllers, this study proposes a predictive fuzzy PID control method for greenhouse environments under programmable logic controller (PLC)-based edge deployment. An integrated remote monitoring and control system with a “PLC–human–machine interface (HMI)–cloud–mobile” architecture was also developed. Based on the intelligent greenhouse experimental platform of Yunnan Agricultural University, the proposed method was validated for greenhouse temperature and air humidity regulation through MATLAB simulations, PLC deployment, and on-site operation tests. The results showed that all four control strategies were able to effectively track the setpoints of greenhouse temperature and humidity, while predictive PID and predictive fuzzy PID achieved better overall performance than conventional PID and fuzzy PID. Predictive fuzzy PID performed best in the humidity channel, whereas its performance in the temperature channel was close to that of predictive PID but with more stable disturbance recovery and better overall balance. On-site operation results further showed that, under typical operating conditions, the tracking error of the actual greenhouse temperature relative to the target temperature could be maintained within approximately ±1 °C, while the error of the actual air humidity relative to the target humidity remained within approximately −2% to 3% RH. These results verify the engineering feasibility of the proposed method on resource-constrained industrial PLC platforms. The proposed method can provide a useful reference for the lightweight and intelligent upgrading of small- and medium-sized greenhouse environmental control systems. Full article

This study presents a nanosensor network system for autonomous microclimate optimization in precision horticulture, leveraging a field-programmable gate array (FPGA)-based control architecture that is integrated with an edge-level machine learning inference. Unlike the conventional greenhouse automation systems, which exhibit thermal and hygroscopic hysteresis often exceeding 32 °C and 78% relative humidity, the proposed framework embeds a random forest regression (RFR) model directly within the Altera DE2-115 FPGA fabric to enable predictive environmental regulation. The model achieved an R² of 0.985 and root mean square error (RMSE) of 0.28 °C, allowing proactive compensation for the thermodynamic disturbances from the high-intensity light-emitting diode (LED) lighting with a 120 s predictive horizon. The real-time monitoring and remote supervision were supported via a NodeMCU-based IoT gateway, achieving a 140 ms mean communication latency and a 99.8% packet delivery reliability. The preliminary validation using lettuce (Lactuca sativa) optimized the environmental parameters, while the subsequent experiments with pepper (Capsicum annuum), a commercially important and environmentally sensitive crop, demonstrated system performance under real-world conditions. The control system maintained a temperature and humidity within ±0.3 °C and ±1.2% of the setpoints, respectively, and outperformed the baseline rule-based control with a 28% increase in fresh biomass, a 22% improvement in dry matter accumulation, a 25% reduction in actuator duty-cycle switching, and an 18% decrease in overall energy consumption. These results highlight the efficacy of FPGA-integrated edge intelligence combined with low-latency IoT telemetry as a scalable, energy-efficient, and high-fidelity solution for sub-degree environmental control in next-generation, controlled-environment, and vertical farming systems. Full article

Globally, the combined pollution of fine particulate matter (PM_2.5) and ground-level ozone (O₃) poses severe challenges to public health and sustainable urban development. Recent data indicate that the annual average PM_2.5 concentration in the vast majority of cities worldwide fails to meet World Health Organization safety standards, with air pollution causing millions of premature deaths annually. As a nature-based solution, the purification efficacy of vegetation remains poorly quantified due to unclear coupling mechanisms with local meteorological conditions. This study systematically reviewed and synthesized 229 empirical studies published between 2000 and 2025 from Web of Science and China National Knowledge Infrastructure (CNKI), aiming to clarify the quantitative relationships and regulatory mechanisms of plant–meteorological synergistic purification of PM_2.5–O₃. Following double-blind independent screening (κ = 0.85) and data extraction, a quantitative minimal feasible synthesis approach was adopted due to high data heterogeneity. The results indicated the following. (1) The median canopy purification efficiency of urban vegetation for PM_2.5 was 18.2% (IQR: 12.5–30.1%, n = 17), with a median dry deposition velocity (Vd–PM) of 0.05 cm s⁻¹ (0.02–30 cm s⁻¹, n = 15). The median dry deposition velocity (Vd–O₃) for O₃ was 0.55 cm s⁻¹ (0.12–1.82 cm s⁻¹, n = 8), with non-stomatal deposition contributing approximately 35%. (2) Meteorological factors exhibit nonlinear regulation: relative humidity (RH) > 70% significantly enhances PM_2.5 adsorption, wind speeds of 1.5–3.0 m s⁻¹ are optimal for PM_2.5 deposition, and temperatures > 30 °C generally inhibit plant uptake of both pollutants (n = 7). (3) Functional traits strongly correlate with purification efficacy: species with high leaf roughness (R² = 0.8), high stomatal conductance, and low BVOC emissions (e.g., Ginkgo biloba, Platycladus orientalis) exhibit optimal synergistic purification potential. Species with high BVOC emissions (Populus przewalskii, Eucalyptus robusta) can increase daily net O₃ pollution equivalents by up to 86 g and must be strictly avoided. Based on quantitative evidence, a green space planning decision matrix indexed by climate zone and pollution type was developed, specifying vegetation configuration patterns, functional group selection, and key design parameters (canopy closure, green belt width, etc.) for different scenarios. This study provides an actionable scientific basis for precision planning and climate-adaptive management of urban green infrastructure. Full article

Against frequent extreme heat, landscaped green spaces cool, humidify, and mitigate urban heat islands, also boosting thermal comfort. Classical Chinese garden “gray spaces” are transitional gathering zones with strong microclimate-regulating potential, yet systematic research on their mechanisms in Western Sichuan memorial gardens remains limited. This study first reveals their thermal characteristics; establishes a refined classification system; uncovers nonlinear links between garden elements, spatial form, and thermal comfort; and proposes optimization strategies. Key findings: (1) Gray spaces show notable microclimate regulation. Internal air temperatures drop by 0.8–4.3 °C, relative humidity rises by 2.2–22.33%, and average PET decreases by 3.1 °C, effectively relieving thermal stress. (2) Thermal comfort is closely related to gray space types, with open halls performing best due to their strong sense of enclosement and shading. (3) Plant-dominated and hybrid spaces are superior to water-dominated ones. PET is negatively correlated with 40–70% plant canopy and 20–30% water coverage, while excess water leads to stuffiness. Hybrid spaces reach ideal blue–green synergy at 50–60% canopy and 20–30% water. (4) The summer PET comfort threshold for Western Sichuan gray spaces is 29.1–31.5 °C (neutral at 30.2 °C), higher than European standards, reflecting local adaptation to a hot–humid climate and guiding microclimate-adaptive design. Full article

Background: This study deeply explores the influence of different dextrose equivalents (DE) values on room-temperature phosphorescence (RTP) properties of maltodextrin (MD) and its luminescence mechanism. The potential applications of MD tablets in non-destructive detection for afterglow visualizing are also explored. Methods: MD tablets with different DE values were prepared to investigate their RTP properties and afterglow effects. MD tablets were validated for afterglow signals and phosphorescence lifetimes under varying environmental conditions. Additionally, the unique afterglow effect of MD was used to detect the uniformity of tablets. Theoretical calculations of MD monomers and dimers were performed using time-dependent density functional theory. Results: The results demonstrated that MD with different DE values exhibited RTP properties, with phosphorescence lifetimes from 186.91 to 618.85 ms. The afterglow signals and phosphorescence lifetimes of MD tablets were influenced by multiple environmental conditions, i.e., relative humidity, temperature, oxygen, ultraviolet light, etc. Based on the afterglow effect of the MD, it is possible to non-destructively detect the uniform tablet. MD is an RTP material regulated by its DE value. Its phosphorescence mechanism is governed by a clustering-triggered emission mechanism, which is dominated by the rich hydrogen bond network. The material’s stimuli-responsive properties and pronounced afterglow effect make it a potential application for non-destructive detection. Conclusions: This study not only investigates the stimulus-responsive behavior of MD but also discovers a common, safe, and edible stimulus-responsive RTP material. These findings provide a new method for non-destructive detection of drugs and reducing the potential pharmacological risks during production, storage, and transportation. Full article

Against the backdrop of accelerated terrestrial hydrological cycling and the increasing concurrence of drought-heatwave compound extremes under global warming, regional land-atmosphere coupling has emerged as a central mechanism shaping climate feedbacks and trajectories of ecosystem carbon uptake. However, prior studies spanning climatic regimes, observational scales, and data sources have often yielded contradictory conclusions. Here, we challenge these fragmented perspectives by constructing an integrated LST-SM-ET-GPP chain that jointly represents land surface temperature, soil moisture, evapotranspiration, and gross primary productivity, thereby linking water availability, surface energy balance, and plant physiological processes within a unified framework. We synthesize a conceptual diagnostic roadmap for interpreting land-atmosphere coupling across observations and models. When ecosystems operate in humid, energy-limited environments, radiative and advective controls should be prioritized to diagnose system forcing. By contrast, as the system becomes water-depleted, attribution must shift to a nonlinear regime transition framework governed by a critical soil moisture threshold. This threshold mechanism implies that, once the system enters the moisture-limited regime, even modest declines in soil moisture can trigger a rapid weakening of evaporative cooling, substantially amplifying LST anomalies and strongly suppressing GPP. The competitive regulation of stomatal conductance by atmospheric demand (vapor pressure deficit, VPD) and terrestrial supply (rootzone soil moisture) further explains why the “dominant” controlling factor can dynamically reverse across hydrothermal states, timescales, and stages of extreme-event evolution. Notably, the steady-state coupling assumption may break down under flux “flooring” during extreme drought, or when structural buffering such as deep root water uptake is present, delineating strict applicability bounds for existing diagnostic frameworks. Finally, current assessments remain constrained by multiple uncertainties, particularly the lack of ET partitioning constraints, representativeness biases arising from clear-sky observations and sampling-depth limitations, and systematic errors in Earth system model simulations during the warm season. Full article