Search Results (10,471)

Plant growth, a fundamental biological process that underpins terrestrial ecosystem function, is susceptible to nutrient availability. Despite extensive research on lowland ecosystems, the responses of alpine plant growth to nutrient addition remain poorly understood, particularly given the heightened sensitivity of alpine ecosystems to global change. To investigate the effects of nitrogen (N) and phosphorus (P) additions on the growth rates of alpine plants and the underlying mechanisms of how these nutrient additions influence plant growth rates, we conducted an experiment in an alpine grassland on the Qinghai–Tibet Plateau, targeting 14 common plant species. Growth rates were measured using biomass and height, with plant height and soil physicochemical properties recorded biweekly during the growing season. We assessed the effects of nitrogen and phosphorus additions on growth rates, their seasonal dynamics, and their relationships with soil physicochemical properties. Results showed that phosphorus addition and combined nitrogen-phosphorus additions significantly increased the relative growth rate based on height (RGR_H). In contrast, nutrient additions had no significant effect on the relative growth rate based on biomass (RGR_B). RGR_H decreased from June and early July to August, exhibiting species-specific responses to nutrient additions. Additionally, RGR_H was significantly influenced by the interaction of nitrogen and phosphorus additions, species, and seasonal dynamics (p < 0.05). Soil available N, available P, and moisture were significantly positively correlated with RGR_H (p < 0.05), while soil temperature (ST), total nitrogen (TN), and soil organic carbon (SOC) exhibited significant negative correlations (p < 0.05). Nutrient additions altered the hierarchy, as well as the direct and indirect factors that influence RGR_H, revealing the opposing regulatory effects of total and available nitrogen. These findings highlight the critical roles of nitrogen and phosphorus, suggesting phosphorus is a potential limiting factor for plant growth in this alpine region. This study offers a comprehensive analysis of how nitrogen and phosphorus additions affect alpine plant growth rates and clarifies the underlying mechanisms in these sensitive ecosystems. Full article

Preseason temperature has always been considered the most critical factor influencing vegetation phenology in the northern hemisphere. While numerous studies have examined the impact of daytime and nighttime warming on vegetation phenology in this region, the specific influence of day and night warming on deciduous broad-leaved forests (DBFs) in Northern China, where significant temperature variations occur between day and night, remains unclear. Furthermore, the sensitivity of daytime and nighttime warming during different preseason periods to phenology has not been quantitatively understood. We analyzed GIMMS3g NDVI data from 1985 to 2015 and employed a double logistic regression model to determine the phenological start of the season (SOS) for DBF in Northern China. To control for monthly precipitation effects, we conducted partial correlation analysis between monthly mean maximum daytime temperature (T_{day_max}), monthly mean minimum nighttime temperature (T_{night_min}), diurnal temperature variation (DTR), and SOS. Our findings over the past 31 years indicate that 75.98% of the area exhibited an advanced trend, with an overall advance of 1.7 days per decade. Interestingly, regardless of T_{day_max}, T_{night_min}, or DTR, most areas had a preseason length of 1 month, accounting for 50.26%, 34.45%, and 44.39%, respectively. Furthermore, approximately 50.68% of the area exhibited a significant negative correlation between preseason temperature and SOS for T_{day_max}, 34.02% for T_{night_min}, and 35.80% for DTR. It can be found that the response of the SOS advance to T_{day_max} in DBFs in Northern China is more obvious than that to T_{night_min} and DTR. Our study revealed that the difference in day and night temperature warming on DBFs in Northern China is not pronounced. Specifically, SOS advanced by 1.8 days, 1.98 days, and 1.95 days for every 1 °C increase in T_{day_max}, T_{night_min}, and DTR, respectively. However, it is important to note that the distribution of advanced days resulting from the warming of these three preseason temperature indicators exhibited spatial heterogeneity. Although many studies have already established the influence of various meteorological indicators on spring phenology, determining which meteorological indicators should be employed to quantify their impact on phenology in different regions and vegetation types remains a subject for further exploration and investigation in the future. Full article

In this work, YF₃:Nd³⁺ powder was synthesized using the microwave-assisted hydrothermal method at a low temperature (140 °C) and short synthesis time (1 h). The photoluminescence and optical temperature sensing properties of YF₃:Nd³⁺ were examined using 800 nm laser excitation, focusing on the emission corresponding to the ⁴F_3/2 → ⁴I_9/2 transition of Nd³⁺. The performance of YF₃:Nd³⁺ as an optical temperature sensor was evaluated using the full width at half maximum (FWHM), band broadening at 30% of maximum intensity (Δλ_30%), and valley-to-peak intensity ratio (VPR) techniques. All techniques demonstrated good repeatability and reproducibility. The best results were obtained using the VPR (V1/P1) method, which exhibited the highest relative sensitivity and the lowest temperature uncertainty, with values of 0.69 ± 0.02% K⁻¹ and 0.46 ± 0.09 K at 303 K, respectively. YF₃:Nd³⁺ shows promise as an optical temperature sensor operating entirely within the first biological window. Full article

Changes in microRNA (miRNA) levels are closely associated with the pathological processes of many diseases. The sensitive and fast detection of miRNAs is critical for diagnosis and prognosis. Here, we report a platform employing CRISPR/Cas12a to recognize and report changes in miRNA levels while avoiding complex multi-thermal cycling procedures. A non-enzyme-dependent hybridization chain reaction (HCR) was used to convert the miRNA signal into double-stranded DNA, which contained a Cas12a activation sequence. The target sequence was amplified simply and isothermally, enabling the test to be executed at a constant temperature of 37 °C. The detection platform had the capacity to measure concentrations down to the picomolar level, and the target miRNA could be distinguished at the nanomolar level. By using photonic crystal microarrays with a stopband-matched emission spectrum of the fluorescent-quencher modified reporter, the fluorescence signal was moderately enhanced to increase the sensitivity. With this enhancement, analyzable fluorescence results were obtained in 15 min. The HCR and Cas12a cleavage processes could be conducted in a single tube by separating the two procedures into the bottom and the cap. We verified the sensitivity and specificity of this one-pot system, and both were comparable to those of the two-step method. Overall, our study produced a fast and sensitive miRNA detection platform based on a CRISPR/Cas12a system and enzyme-free HCR amplification. This platform may serve as a potential solution for miRNA detection in clinical practice. Full article

Citrus alternaria brown spot, caused by the tangerine pathotype of Alternaria alternata, is one of the most severe fungal diseases affecting citrus crops. Currently, there is a critical need for rapid and visual detection techniques to identify the tangerine pathotype of A. alternata. In this study, a novel detection system was developed by combining recombinase polymerase amplification (RPA) with CRISPR/Cas12a technology, targeting the ACTT3 gene specific to the tangerine pathotype of A. alternata. Through optimization of reaction time and component concentrations, the assay demonstrated a detection sensitivity of 1 pg μL⁻¹ within 40 min at a constant temperature of 37 °C. The results can be visually interpreted using nucleic acid test strips, offering advantages in specificity, sensitivity, and speed. This system has been successfully validated for the rapid detection of the pathogen within plant tissues, including leaves and fruits, providing an efficient and practical solution for real-time field detection of the tangerine pathotype of A. alternata. Full article

In this study, the particle swarm optimization (PSO) and back propagation neural network (BPNN) surrogate model in combination with a multi-objective genetic algorithm are developed for the design optimization of a bionic liquid cooling plate with a spider-web channel structure. The single-factor sensitivity analysis is first conducted based on the numerical simulation approach, identifying three key factors as design variables for optimizing design objectives such as maximum temperature (T_max), maximum temperature difference (ΔT_max), and pressure drop (ΔP). Subsequently, the PSO algorithm is used to optimize the parameters of the BPNN structure, thereby constructing the PSO-BPNN surrogate model. Next, the non-dominated sorting genetic algorithm II (NSGA-II) is employed to obtain the Pareto optimal set, and the TOPSIS with the entropy weight method is used to determine the optimal solution, eliminating subjective preferences in decision-making. The results show that the PSO-BPNN model outperforms the traditional BPNN in prediction accuracy for all three objectives. Compared to the initial structure, the T_max and ΔT_max are reduced by 1.09 °C and 0.41 °C in the optimized structure, respectively, with an increase in ΔP by 21.24 Pa. Full article

As environmental pollution has become a global concern, regulations on carbon emissions from maritime activities are being implemented, and interest in using renewable energy as fuel for ships is growing. Hydrogen, which does not release carbon dioxide and has a high energy density, can potentially replace fossil fuels as a renewable energy source. Notably, storage of hydrogen in a liquid state is considered the most efficient. In this study, a 0.7 m³ liquid hydrogen fuel tank suitable for small vessels was designed, and a structural analysis was conducted to assess its structural integrity. The extremely low liquefaction temperature of hydrogen at −253 °C and the need for spatial efficiency in liquid hydrogen fuel tanks make vacuum insulation essential to minimize the heat transfer due to convection. A composite insulation system of sprayed-on foam insulation (SOFI) and multilayer insulation (MLI) was applied in the vacuum annular space between the inner and outer shells, and a tube-shaped supporter made of a G-11 cryogenic (CR) material with low thermal conductivity and high strength was employed. The material selected for the inner and outer layers of the tank was STS 316L, which exhibits sufficient ductility and strength at cryogenic temperatures and has low sensitivity to hydrogen embrittlement. The insulation performance was quantitatively assessed by calculating the boil-off rate (BOR) of the designed fuel tank. Structural integrity evaluations were conducted for nine load cases using heat transfer and structural analyses in accordance with the IGF code. Full article

The accurate prediction of moisture content is crucial for controlling the drying process of agricultural products. While existing studies on drying models often rely on laboratory-scale experiments with limited data, real-time and high-frequency data collection under industrial conditions remains underexplored. This study collected and constructed a multi-dimensional dataset using an industrial-grade data acquisition system specifically designed for heat pump low-temperature circulating dryers. An artificial neural network (ANN) prediction model for moisture content during the rice drying process was developed. To prevent model overfitting, K-fold cross-validation was utilized. The model’s performance was evaluated using the mean squared error (MSE) and the coefficient of determination (R²), which also helped determine the preliminary structure of the ANN model. Bayesian regularization (trainbr) was then employed to train the network. Furthermore, optimization was conducted using neural network weights (RI) analysis and Sobol variance contribution analysis of the input variables to simplify the model structure and improve predictive performance. The experimental results showed that optimizing the model through RI sensitivity analysis simplified its topology to a 5-14-1 structure. The optimized model exhibited not only simplicity but also high prediction accuracy, achieving R² values of 0.969 and 0.966 for the training and testing sets, respectively, with MSEs of 5.6 × 10⁻³ and 6.3 × 10⁻³. Additionally, the residual errors followed a normal distribution, indicating that the predictions were reliable and realistic. Statistical tests such as t-tests, F-tests, and Kolmogorov–Smirnov tests revealed no significant differences between the predicted and actual values of rice moisture content, confirming the high consistency between them. Full article

Gas chromatography–ion mobility spectrometry (GC-IMS) is a powerful technique in the field of food and flavor analysis specifically, as well as for the determination of volatile organic compounds (VOCs) in general. It offers high sensitivity and selectivity, combined with a robust design. Sample preparation is typically not required, and operating principles under ambient conditions facilitate routine analysis and usage at points of care. As of now, a plethora of applications of GC-IMS exist in the fields of food analysis, primarily for determining flavors and evaluating the authenticity of food. However, the general issue of peak tailing has, so far, not been addressed in IMS. Typical drift tube applications (DTIMS) are designed with emphasis to high detection sensitivities and feature large void volumes. This study aimed to develop an optimized IMS instrument design (“focus IMS”) which allows for signal mapping of eluting compounds. Due to an optimized flow architecture of sample and drift gases, in combination with an increased drift tube temperature, peak tailing is decreased significantly. In this study, the influence of drift gas flow and IMS cell temperature on the peak shape of several relevant allergenic terpenes was investigated. The peak quality optimization of DTIMS approaches for especially high-boiling substances facilitates the analysis of complex matrices, such as cosmetics, Citrus peel, and essence oils, as well as terpenes and terpenoids in general. Full article

Ground-source heat pump (GSHP) systems with medium-depth and deeply buried pipes in cold regions are highly important for addressing global climate change and the energy crisis because of their efficient, clean, and sustainable energy characteristics. However, unique geological conditions in cold climates pose serious challenges to the heat transfer efficiency, long-term stability, and adaptability of systems. This study comprehensively analyses the effects of various factors, including well depth, inner-to-outer tube diameter ratios, cementing material, the thermal conductivity of the inner tube, the flow rate, and the start–stop ratio, on the performance of a medium-depth coaxial borehole heat exchanger. Field tests, numerical simulations, and sensitivity analyses are combined to determine the full-cycle thermal performance and heat-transfer properties of medium-depth geological formations and their relationships with system performance. The results show that the source water temperature increases by approximately 4 °C and that the heat transfer increases by 50 kW for every 500 m increase in well depth. The optimization of the inner and outer pipe diameter ratios effectively improves the heat-exchange efficiency, and a larger pipe diameter ratio design can significantly reduce the flow resistance and improve system stability. When the thermal conductivity of the cementing cement increases from 1 W/(m·K) to 2 W/(m·K), the outlet water temperature at the source side increases by approximately 1 °C, and the heat transfer increases by 13 kW. However, the improvement effect of further increasing the thermal conductivity on the heat-exchange efficiency gradually decreases. When the flow rate is 0.7 m/s, the heat transfer is stable at approximately 250 kW, and the system economy and heat-transfer efficiency reach a balance. These findings provide a robust scientific basis for promoting medium-deep geothermal energy heating systems in cold regions and offer valuable references for the green and low-carbon transition in building heating systems. Full article

Fiber Bragg grating (FBG) sensors have emerged as advanced tools for monitoring a wide range of physical parameters in various fields, including structural health, aerospace, biochemical, and environmental applications. This review provides a comprehensive overview of FBG sensor technology, focusing on their operating principles, key advantages such as high sensitivity and immunity to electromagnetic interference, and common challenges like temperature-strain cross-sensitivity and the high cost of interrogation systems. Additionally, this review compares FBG sensors with other sensing technologies and highlights recent innovations in design, packaging, and implementation techniques. Finally, future research directions are discussed to enhance the performance, scalability, and long-term reliability of FBG-based sensing systems. Full article

Chemiresistive sensors integrated with functionalized conductive polymers have emerged as promising candidates for wearable applications, offering adequate protection against highly toxic and widely prevalent organophosphate compounds, due to their high sensitivity, room-temperature operation, and straightforward fabrication process. However, these chemiresistive sensors exhibit poor resistance to water vapor due to the intrinsic properties of these conducting polymers, likely leading to false sensor alarms. In this study, we engineered a series of water-vapor-resistant, yet organophosphate-sensitive, conducting polymers by electro-copolymerizing hexafluoroisopropanol (HFIP)-grafted 3,4-ethylenedioxythiophene (EDOT-HFIP) with EDOT comonomers bearing hydrophobic alkyl groups of varying lengths (ethyl, butyl, and hexyl). The typical results indicated that increasing the alkyl length and alkyl-bearing EDOT comonomer composition significantly enhanced the water resistance of the EDOT-HFIP copolymers and the copolymer-integrated chemiresistive sensor, but this improvement came at the unacceptable cost of compromising the organophosphate sensitivity. To address this issue, we developed a surface-driven phase-segregation strategy to enrich the alkyl chains on the surface while concentrating the HFIP groups beneath it by treating the silica substrates using oxygen plasma before polymer spin coating, thus decoupling and optimizing the two mutually competing characteristics. Finally, the chemiresistive sensor integrated with the EDOT-HFIP copolymer containing 10% hexyl-grafted EDOT comonomer exhibited an organophosphate (DMMP) resistive response 657 times higher than that to water vapor, and more than two times that of a PEDOT-HFIP sensor, while preserving the original specific sensitivity of the PEDOT-HFIP sensor. Furthermore, it demonstrated a markedly improved shelf storage stability, being directly exposed to air for 14 days without any special protection. We envision that this surface-driven phase-segregation strategy could offer a promising solution to the significant challenge of air moisture interference in highly sensitive polymer sensors, promoting their practical use in real-world applications. Full article

This study’s field observations of Light Source Efficiency (LSE) in the Taklamakan Desert have unveiled significant daily average variations across different wavelengths, with LSE values ranging from 0.827 at 9.1 μm to a peak of 0.969 at 12.1 μm, and notably, a substantial daily variation (DV) of Δε = 0.080 in the 14.3 μm band. These findings underscore the necessity for wavelength-specific analysis in LSE research, which is crucial for enhancing the precision of remote sensing applications and climate models. This study’s high-temporal-resolution FTIR field observations systematically reveal the diurnal dynamics of infrared surface emissivity in the desert for the first time, challenging existing satellite-based inversion products and highlighting the limitations of traditional temperature–emissivity separation algorithms in arid regions. The diurnal fluctuations are governed by three primary mechanisms: the amplification of lattice vibrations in quartz minerals under high daytime temperatures, changes in the surface topography due to thermal expansion and contraction, and nocturnal radiative cooling effects. The lack of a significant correlation between environmental parameters and the emissivity change rate suggests that microclimate factors play a dominant indirect regulatory role. Model comparisons indicate that sinusoidal functions outperform polynomial fits across most wavelengths, especially at 12.1 μm, confirming the significant influence of diurnal forcing. The high sensitivity of the 14.3 μm band makes it an ideal indicator for monitoring desert surface–atmosphere interactions. This study provides three key insights for remote sensing applications: the development of dynamic emissivity correction schemes, the prioritization of the long-wave infrared band for surface temperature inversion in arid regions, and the integration of ground-based observations with geostationary high-spectral data to construct spatiotemporally continuous emissivity models. Future research should focus on multi-angle observation experiments and the exploration of machine learning’s potential in cross-scale emissivity modeling. Full article

Background/Objectives: Mask-wearing-induced discomfort often leads to unconscious loosening of the mask to relieve the discomfort, thereby compromising protective efficacy. This study investigated how leakage flows affect mask-associated thermoregulation and vapor trapping to inform better mask designs. An integrated ambience–mask–face–airway model with various mask-wearing misfits was developed. Methods: The transient warming/cooling effects, thermal buoyancy force, tissue heat generation, vapor phase change, and fluid/heat/mass transfer through a porous medium were considered in this model, which was validated using Schlieren imaging, a thermal camera, and velocity/temperature measurements. Leakages from the top and side of the mask were analyzed in comparison to a no-leak scenario under cyclic respiration conditions. Results: A significant inverse relationship was observed between mask leakage and facial temperature/humidity. An equivalent impact from buoyancy forces and exhalation flow inertia was observed both experimentally and numerically, indicating a delicate balance between natural convection and forced convection, which is sensitive to leakage flows and critical in thermo-humidity regulation. For a given gap, the leakage fraction was not constant within one breathing cycle but constantly increased during exhalation. Persistently higher temperatures were found in the nose region throughout the breathing cycle in a sealed mask and were mitigated during inhalation when gaps were present. Vapor condensation occurred within the mask medium during exhalation in all mask-wearing cases. Conclusions: The thermal and vapor temporal variation profiles were sensitive to the location of the gap, highlighting the feasibility of leveraging temperature and relative humidity to test mask fit and quantify leakage fraction. Full article

Effects of low temperature (LT, 20 °C) combined with nitrogen-modified atmosphere (MA, 95% N₂) storage (LT + MA) on quality, microstructure, and metabolome characteristics of high moisture content (15.5%) during 180 days of storage were investigated to explore a potential preservation technique for high moisture rice. The results showed that after 180 days of storage, the fatty acid value, malondialdehyde content, and amylose content of rice under LT + MA storage were 53.33%, 72.93%, and 91.85% of those under conventional storage (CS, conventional atmosphere, 30 °C, RH 65%), respectively. The color, pasting properties, and scanning electron microscopy (SEM) of the LT + MA treatment were found to be markedly superior to those of the CS treatment. In addition, the differential metabolites sucrose, trehalose-6P, trehalose, 3,7-Di-O-methylquercetin (DMQ), rutin, and vitexin 2″-O-rhamnoside (VOR) were screened to assess for sensitivity to changes in storage conditions. The study demonstrated that the LT + MA effectively suppressed the escalation of FAV, MDA content, and amylose content. In addition, it was observed to inhibit the deterioration of color and pasting properties while concurrently maintaining the polygonal shape of rice starch granules. Furthermore, the differential metabolites of non-targeted metabolomics indicated that the LT + MA group exhibited superior efficacy in retarding rice aging. Full article