Search Results (1,142)

Environmental risk assessment (ERA) for pesticide approval in the context of predatory insects remains inadequate as it often overlooks the influence of agricultural practices. An increasing number of studies have shown that prolonged and synergistic pesticide exposure can elevate insect mortality. However, such effects remain largely unstudied in non-target predatory carabid beetles. The carabid beetle Platynus assimilis was subjected to repeated oral and continuous contact exposure to low doses of prothioconazole (20 g ha⁻¹), lambda-cyhalothrin (0.4 g ha⁻¹), or their combination over a 64-day period. The food consumption rate, body mass, locomotor activity, and mortality were monitored throughout the experiment. All pesticide-treated groups showed significantly increased final mortality, with median lethal times (LT₅₀) of 51.6 days for prothioconazole, 60.3 days for lambda-cyhalothrin, and 12.2 days for their combination. A significant synergistic effect on mortality was observed in the combined treatment group, with the highest synergistic ratio detected 20 days after the first exposure. Pesticide-treated beetles exhibited significant abnormalities in locomotor activity and body mass compared to the untreated group. These findings demonstrate that both time-cumulative mortality and potential synergistic interactions, reflecting field-realistic conditions, must be considered in ERA. Failure to do so may lead to an underestimation of pesticide toxicity to predatory carabids. Full article

A computational fluid dynamics (CFD) numerical simulation methodology was implemented to model transient heating processes in steel industry reheating furnaces, targeting combustion efficiency optimization and carbon emission reduction. The effects of oxygen concentration (O₂%) and different fuel types on the flow and heat transfer characteristics were investigated under both oxygen-enriched combustion and MILD oxy-fuel combustion. The results indicate that MILD oxy-fuel combustion promotes flue gas entrainment via high-velocity oxygen jets, leading to a substantial improvement in the uniformity of the furnace temperature field. The effect is most obvious at O₂% = 31%. MILD oxy-fuel combustion significantly reduces NOx emissions, achieving levels that are one to two orders of magnitude lower than those under oxygen-enriched combustion. Under MILD conditions, the oxygen mass fraction in flue gas remains below 0.001 when O₂% ≤ 81%, indicating effective dilution. In contrast, oxygen-enriched combustion leads to a sharp rise in flame temperature with an increasing oxygen concentration, resulting in a significant increase in NOx emissions. Elevating the oxygen concentration enhances both thermal efficiency and the energy-saving rate for both combustion modes; however, the rate of improvement diminishes when O₂% exceeds 51%. Based on these findings, MILD oxy-fuel combustion using mixed gas or natural gas is recommended for reheating furnaces operating at O₂% = 51–71%, while coke oven gas is not. Full article

Biocatalysis is one of the oldest fields that has been used in industrial applications, with one of the earliest purposeful examples being the mass production of acetic acid from an immobilized Acinetobacter strain in the year 1815. Efficiency, specificity, reduced reaction times, lower overall costs, and environmental friendliness are some advantages biocatalysis has over conventional chemical synthesis, which has made biocatalysis increasingly used in industry. We highlight three necessary fields that are fundamental to advancing industrial biocatalysis, including biocatalyst engineering, solvent engineering, and mechanistic engineering. However, the fundamental mechanism of enzyme function is often overlooked or given less attention, which can limit the engineering process. In this review, we describe how mechanistic enzymology benefits industrial biocatalysis by elucidating key fundamental principles, including the k_cat and k_cat/K_m parameters. Mechanistic enzymology presents a unique field that provides in-depth insights into the molecular mechanisms of enzyme activity and includes areas such as reaction kinetics, catalytic mechanisms, structural analysis, substrate specificity, and protein dynamics. In line with the objective of protein engineering to optimize enzyme activity, we summarize a range of strategies reported in the literature aimed at improving the product release rate, the chemical step of catalysis, and the overall catalytic efficiency of enzymes. Further into this review, we delineate kinetic solvent viscosity effects (KSVEs) as a very efficient, cost-effective, and easy-to-perform method to probe different aspects of enzyme reaction mechanisms, including diffusion-dependent kinetic steps and rate-limiting steps. KSVEs are cost-effective because simple kinetic enzyme assays, such as the Michaelis–Menten kinetic approach, can be combined with them without the need for specialized and costly equipment. Other techniques in protein engineering and genetic engineering are also covered in this review. Additionally, we provide information on solvent systems in enzymatic reactions, details on immobilized biocatalysts, and common misconceptions that misguide enzyme design and optimization processes. Full article

In order to study the problem of obvious wall thinning in the wellbore caused by proppant backflow and sand production under throttling conditions in tight gas wells. Based on the gas-phase control equation, particle motion equation, and erosion model, the wellbore erosion model is established. The distribution law of pressure, temperature, and velocity trace fields under throttling conditions is analyzed, and the influences of different throttling pressures, particle diameters, and particle mass flows on wellbore erosion are analyzed. The flow field at the nozzle changes drastically, and there is an obvious pressure drop, temperature drop, and velocity rise. When the surrounding gas is completely mixed, the physical quantity gradually stabilizes. The erosion shape of the wellbore outlet wall has a point-like distribution. The closer to the throttle valve outlet, the more intense the erosion point distribution is. Increasing the inlet pressure and particle mass flow rate will increase the maximum erosion rate, and increasing the particle diameter will reduce the maximum erosion rate. The particle mass flow rate has the greatest impact on the maximum erosion rate, followed by the particle diameter. The erosion trend was predicted using multiple regression model fitting of the linear interaction term. The research results can provide a reference for the application of downhole throttling technology and wellbore integrity in tight gas exploitation. Full article

Background/Objectives: Global warming and rising CO₂ concentrations pose significant challenges to plant systems. Amid these pressures, this study contributes to understanding how tropical species respond by simultaneously evaluating reproductive and genetic traits. It specifically investigates the effects of maternal exposure to warming and elevated CO₂ on progeny physiology, genetic diversity, and population structure in Stylosanthes capitata, a resilient forage legume native to Brazil. Methods: Maternal plants were cultivated under controlled treatments, including ambient conditions (control), elevated CO₂ at 600 ppm (eCO₂), elevated temperature at +2 °C (eTE), and their combined exposure (eTEeCO₂), within a Trop-T-FACE field facility (Temperature Free-Air Controlled Enhancement and Free-Air Carbon Dioxide Enrichment). Seed traits (seeds per inflorescence, hundred-seed mass, abortion, non-viable seeds, coat color, germination at 32, 40, 71 weeks) and abnormal seedling rates were quantified. Genetic diversity metrics included the average (A) and effective (Ae) number of alleles, observed (Ho) and expected (He) heterozygosity, and inbreeding coefficient (Fis). Population structure was assessed using Principal Coordinates Analysis (PCoA), Analysis of Molecular Variance (AMOVA), number of migrants per generation (Nm), and genetic differentiation index (Fst). Two- and three-way Analysis of Variance (ANOVA) were used to evaluate factor effects. Results: Compared to control conditions, warming increased seeds per inflorescence (+46%), reduced abortion (−42.9%), non-viable seeds (−57%), and altered coat color. The germination speed index (GSI +23.5%) and germination rate (Gr +11%) improved with warming; combined treatments decreased germination time (GT −9.6%). Storage preserved germination traits, with warming enhancing performance over time and reducing abnormal seedlings (−54.5%). Conversely, elevated CO₂ shortened GSI in late stages, impairing germination efficiency. Warming reduced Ae (−35%), He (−20%), and raised Fis (maternal 0.50, progeny 0.58), consistent with the species’ mixed mating system; A and Ho were unaffected. Allele frequency shifts suggested selective pressure under eTE. Warming induced slight structure in PCoA, and AMOVA detected 1% (maternal) and 9% (progeny) variation. Fst = 0.06 and Nm = 3.8 imply environmental influence without isolation. Conclusions: Warming significantly shapes seed quality, reproductive success, and genetic diversity in S. capitata. Improved reproduction and germination suggest adaptive advantages, but higher inbreeding and reduced diversity may constrain long-term resilience. The findings underscore the need for genetic monitoring and broader genetic bases in cultivars confronting environmental stressors. Full article

The synergistic development of low-permeability reservoirs such as deep coalbed methane (CBM) and tight gas has emerged as a key technology to reduce development costs, enhance single-well productivity, and improve gas recovery. However, due to fundamental differences between coal seams and tight sandstones in their pore structure, permeability, water saturation, and pressure sensitivity, significant variations exist in their flow capacities and fluid production behaviors. To address the challenges of production allocation and main reservoir identification in the co-development of CBM and tight gas within deep gas-bearing basins, this study employs the transient multiphase flow simulation software OLGA to construct a representative dual-gas co-production well model. The regulatory mechanisms of the gas–liquid distribution, deliquification efficiency, and interlayer interference under two typical vertical stacking relationships—“coal over sand” and “sand over coal”—are systematically analyzed with respect to different tubing setting depths. A high-precision dynamic production allocation method is proposed, which couples the wellbore structure with real-time monitoring parameters. The results demonstrate that positioning the tubing near the bottom of both reservoirs significantly enhances the deliquification efficiency and bottomhole pressure differential, reduces the liquid holdup in the wellbore, and improves the synergistic productivity of the dual-reservoirs, achieving optimal drainage and production performance. Building upon this, a physically constrained model integrating real-time monitoring data—such as the gas and liquid production from tubing and casing, wellhead pressures, and other parameters—is established. Specifically, the model is built upon fundamental physical constraints, including mass conservation and the pressure equilibrium, to logically model the flow paths and phase distribution behaviors of the gas–liquid two-phase flow. This enables the accurate derivation of the respective contributions of each reservoir interval and dynamic production allocation without the need for downhole logging. Validation results show that the proposed method reliably reconstructs reservoir contribution rates under various operational conditions and wellbore configurations. Through a comparison of calculated and simulated results, the maximum relative error occurs during abrupt changes in the production capacity, approximately 6.37%, while for most time periods, the error remains within 1%, with an average error of 0.49% throughout the process. These results substantially improve the timeliness and accuracy of the reservoir identification. This study offers a novel approach for the co-optimization of complex multi-reservoir gas fields, enriching the theoretical framework of dual-gas co-production and providing technically adaptive solutions and engineering guidance for multilayer unconventional gas exploitation. Full article

Studying the nutritional ecology of Neoseiulus cucumeris (Oudemans) at different temperatures is a fundamental tool for improving mass production for use in biological control of pest mites. The current research studied the impact of both food types and temperatures on the life history and demographic parameters of the predator mite N. cucumeris. Mite cultures in the laboratory were developed using Tetranychus urticae Koch, and N. cucumeris was collected from field plants. The developmental stages of N. cucumeris fed on date palm pollen and the immature stages of T. urticae were investigated in a laboratory setting at different temperatures. Our research revealed that N. cucumeris readily accepted both food types at all the tested temperatures. The developmental stages and adult longevity of N. cucumeris, both female and male, decreased dramatically when the temperature increased from 18 °C to 34 °C. The net reproductive rate (R₀) reached its greatest values of 22.52 and 9.72 offspring/individual at 26 °C, and the intrinsic rate of increase (r_m) reached its maximum values of 0.17 and 0.13 day⁻¹ at 34 °C and minimum of 0.12 and 0.10 day⁻¹ at 18 °C, when fed on date palm pollen and immature stages of T. urticae, respectively. Conversely, the average generation time (T) showed a notable reduction from 22.48 to 16.48 and 20.88 to 16.76 days, accompanied by an upsurge in temperature from 18 °C to 34 °C, when fed on date palm pollen and immature stages of T. urticae, respectively. The finite rate of growth (λ) exhibited distinct variations, reaching its highest value at 34 °C, 26 °C, and 18 °C when fed on date palm pollen and immature stages of T. urticae, respectively. From these results, we can conclude that N. cucumeris was successfully fed date palm pollen as an alternate source of nourishment. In addition, the immature stages of T. urticae are suitable as food sources for N. cucumeris because they shorten the mean generation time. Therefore, the success of mass-rearing the predator mite N. cucumeris on a different, less expensive diet, such as date palm pollen, and determining the most suitable temperature for it has increased its spread as a biocontrol agent. Full article

Convective updrafts are one of the main characteristics of convective clouds, responsible for the convective mass flux and the redistribution of energy and condensate in the atmosphere. During the early stages of their lifecycle, convective clouds experience rapid cloud-top ascent manifested by a decrease in the geostationary IR brightness temperature ($T{B}_{IR}$). Under the assumption that the convective cloud top behaves like a black body, the ascent rate of the convective cloud top can be estimated as (${\displaystyle \frac{\partial T{B}_{IR}}{\partial t}}$), and it can be used to infer the near cloud-top convective updraft. The temporal resolution of the geostationary IR measurements and non-uniform beam-filling effects can influence the convective updraft estimation. However, the main shortcoming until today was the lack of independent verification of the strength of the convective updraft. Here, Doppler radar observations from the ESCAPE and TRACER field experiments provide independent estimates of the convective updraft velocity at higher spatiotemporal resolution throughout the convective core column and can be used to evaluate the updraft velocity estimates from the IR cooling rate for limited samples. Isolated convective cells were tracked with dedicated radar (RHIs and PPIs) scans throughout their lifecycle. Radial Doppler velocity measurements near the convective cloud top are used to provide estimates of convective updrafts. These data are compared with the geostationary IR and VIS channels (from the GOES satellite) to characterize the convection evolution and lifecycle based on cloud-top cooling rates. Full article

Considering the serious hazard of respiratory dust in underground coal mines and the low efficiency of traditional dust-reduction technology, this study optimizes the atomisation parameters of the gas–liquid two-phase flow nozzle through numerical simulation and experimental testing, and designs an on-board dust-reduction system. Based on the Fluent software (version 2023 R2), a flow field model outside the nozzle was established, and the effects of the air supply pressure, gas-phase inlet velocity, and droplet mass flow rate on the atomisation characteristics were analyzed. The results show that increasing the air supply pressure can effectively reduce the droplet particle size and increase the range and atomisation angle, and that the dust-reduction efficiency is significantly improved with the increase in pressure. The dust-reduction efficiency reached 69.3% at 0.6 MPa, which was the economically optimal operating condition. Based on the parameter optimization, this study designed an annular airborne gas–liquid two-phase flow dust-reduction system, and a field test showed that the dust-reduction efficiency of this system could reach up to 86.0%, which is 53.5% higher than that of traditional high-pressure spraying, and that the dust concentration was reduced to less than 6 mg/m³. This study provides an efficient and reliable technical solution for the management of underground coal mine dust and guidance for promoting the development of the coal industry. Full article

This paper presents the flow field reconstruction and prediction of powder fuel transport systems based on representative feature extraction from scattering images using deep learning techniques. A laboratory-built powder fuel supply system was used to conduct scattering spectroscopy experiments on boron-based fuel under various flow rate conditions. Based on the acquired scattering images, a prediction and reconstruction method was developed using a deep network framework composed of a Stacked Autoencoder (SAE), a Backpropagation Neural Network (BP), and a Long Short-Term Memory (LSTM) model. The proposed framework enables accurate classification and prediction of the dynamic evolution of flow structures based on learned representations from scattering images. Experimental results show that the feature vectors extracted by the SAE form clearly separable clusters in the latent space, leading to high classification accuracy under varying flow conditions. In the prediction task, the feature vectors predicted by the LSTM exhibit strong agreement with ground truth, with average mean square error, mean absolute error, and r-square values of 0.0027, 0.0398, and 0.9897, respectively. Furthermore, the reconstructed images offer a visual representation of the changing flow field, validating the model’s effectiveness in structure-level recovery. These results suggest that the proposed method provides reliable support for future real-time prediction of powder fuel mass flow rates based on optical sensing and imaging techniques. Full article

Atmospheric climate science lacks the capacity to integrate thermodynamics with the gravitational potential of air in a classical quantum theory. To what extent can we identify Carnot’s ideal heat engine cycle in reversible isothermal and isentropic phases between dual temperatures partitioning heat flow with coupled work processes in the atmosphere? Using statistical action mechanics to describe Carnot’s cycle, the maximum rate of work possible can be integrated for the working gases as equal to variations in the absolute Gibbs energy, estimated as sustaining field quanta consistent with Carnot’s definition of heat as caloric. His treatise of 1824 even gave equations expressing work potential as a function of differences in temperature and the logarithm of the change in density and volume. Second, Carnot’s mechanical principle of cooling caused by gas dilation or warming by compression can be applied to tropospheric heat–work cycles in anticyclones and cyclones. Third, the virial theorem of Lagrange and Clausius based on least action predicts a more accurate temperature gradient with altitude near 6.5–6.9 °C per km, requiring that the Gibbs rotational quantum energies of gas molecules exchange reversibly with gravitational potential. This predicts a diminished role for the radiative transfer of energy from the atmosphere to the surface, in contrast to the Trenberth global radiative budget of ≈330 watts per square metre as downwelling radiation. The spectral absorptivity of greenhouse gas for surface radiation into the troposphere enables thermal recycling, sustaining air masses in Lagrangian action. This obviates the current paradigm of cooling with altitude by adiabatic expansion. The virial-action theorem must also control non-reversible heat–work Carnot cycles, with turbulent friction raising the surface temperature. Dissipative surface warming raises the surface pressure by heating, sustaining the weight of the atmosphere to varying altitudes according to latitude and seasonal angles of insolation. New predictions for experimental testing are now emerging from this virial-action hypothesis for climate, linking vortical energy potential with convective and turbulent exchanges of work and heat, proposed as the efficient cause setting the thermal temperature of surface materials. Full article

Dynamic Line Rating (DLR) technology is presented as a key solution to optimize the transmission capacity of power lines without the need to make investments in new infrastructure. Unlike traditional methods based on static estimates, DLR allows the thermal capacity of conductors to be evaluated in real time, considering the environmental and operational conditions. This article presents a state-of-the-art analysis of this technology, including a review of the main solutions currently available on the market. Likewise, the influence of variables such as ambient temperature, wind speed and direction or solar radiation in the determination of dynamic load capacity is discussed. It also reviews various pilot and commercial projects implemented internationally, evaluating their results and lessons learned. Finally, the main technological, regulatory, and operational challenges faced by the mass adoption of DLR are identified, including aspects such as the prediction of the dynamic capacity value, combination with other flexibility options, or integration with network management systems. This review is intended to serve as a basis for future developments and research in the field. Full article

Subsurface drainage and biochar application are conventional measures for improving saline–alkali soils. However, their combined effects on the fate of nitrogen (N) fertilizers remain unclear. This study investigated the combined effects of subsurface drainage and biochar amendment on the fate of nitrogen (N) in coastal saline–alkali soils, where these conventional remediation measures’ combined impacts on fertilizer N dynamics remain seldom studied. Using ¹⁵N-labeled urea tracing in an alfalfa–soil system, we examined how different drainage spacings (0, 6, 12, and 18 m) and biochar application rates (5, 10, and 15 t/ha) influenced N distribution patterns. Results demonstrated decreasing in drainage spacing and increasing in biochar application; these treatments enhanced ¹⁵N use efficiency on three harvested crops. Drainage showed more sustained effects than biochar. Notably, the combination of 6 m drainage spacing with 15 t/ha biochar application achieved optimal performance of ¹⁵N use, showing N utilization efficiency of 46.0% that significantly compared with most other treatments (p < 0.05). ¹⁵N mass balance analysis revealed that the plant absorption, the soil residual and the loss of applied N accounted for 21.6–46.0%, 38.6–67.5% and 8.5–18.1%, respectively. These findings provide important insights for optimizing nitrogen management in coastal saline–alkali agriculture, demonstrating that strategic integration of subsurface drainage (6 m spacing) with biochar amendment (15 t/ha) can maximize N use efficiency, although potential N losses warrant consideration in field applications. Full article

Acid deposition, a major environmental issue causing soil acidification and microbial suppression, impacts forest nutrient cycling. Meanwhile, nitrogen (N) fertilization is widely applied in subtropical forests, yet its interaction with acid deposition on litter decomposition is unclear. We conducted a field experiment using two common tree species, Cunninghamia lanceolata and Cinnamomum camphora, and applied three acid deposition levels (0, 0.25, and 0.50 g H⁺ m⁻² month⁻¹) and four N fertilization levels (0, 3, 6, and 9 g N m⁻² year⁻¹) in a factorial design. Our results showed that acid deposition alone significantly reduced litter decomposition rates, with maximum mass loss decreasing by 23.6% for Cunninghamia and 36.3% for Cinnamomum (p < 0.05). Urea fertilization alone also suppressed decomposition, reducing maximum mass loss by 27.3% for Cunninghamia and 37.3% for Cinnamomum (p < 0.05). However, when combined, urea fertilization mitigated the suppressive effect of acid deposition, particularly under severe acid conditions, where maximum mass loss increased by 18.5% for Cunninghamia and 43.1% for Cinnamomum (p < 0.05). Acid deposition reduced microbial respiration and enzyme activities related to carbon cycling, while urea fertilization showed both positive and negative effects depending on the acid levels (p < 0.05). Urea can enhance the litter layer’s acid-buffering capacity, offering potential management insights for acid deposition-affected forests. Further research on microbial mechanisms across ecosystems is recommended. Full article

Micro-nano bubbles (MNBs) are tiny bubbles with diameters ranging from 200 nm to 30 µm. They possess unique physicochemical properties such as a large specific surface area, slow rising velocity, high gas dissolution rate, high mass transfer efficiency, and strong interfacial zeta potential. These properties endow MNBs with great potential in various fields, including water treatment, enhanced oil recovery, medical and health care, and agriculture. This paper systematically reviews the physicochemical properties, generation methods, and applications of micro-nano bubbles. The main production methods include the mechanical stirring, pressurized dissolved gas release, ultrasonic cavitation, venturi injection, electrolysis, etc. The principles, advantages and disadvantages, and optimization strategies of these methods are comprehensively analyzed. In terms of applications, the mechanisms and typical cases of MNBs in enhanced oil recovery, water treatment, mineral flotation, medical drug delivery, and crop yield enhancement are thoroughly discussed. Extensive research has shown that MNB technology is highly efficient, energy-saving, and environmentally friendly. However, improving bubble stability, generation efficiency, and large-scale application remain key directions for future research. Full article