Search Results (4,353)

Forests in the Beijing–Tianjin–Hebei region have played an important role in wind prevention, sand fixation, and carbon emission reduction in China. This study uses scenario analysis to assess the region’s potential for carbon emission reduction through forest carbon sinks under low-carbon development scenarios. The findings suggest that, by 2030, when carbon emissions are expected to peak, the maximum projected cumulative carbon reduction from forest carbon sinks in the Beijing–Tianjin–Hebei region will be 25.572 million tons, contributing 6.26% to carbon emission reduction. By 2060, when the region aims to achieve carbon neutrality, the maximum projected cumulative carbon reduction from forest carbon sinks will be 366.207 million tons, with a contribution to carbon neutrality exceeding 17%. In the medium-to-long term, the forest carbon sink mechanism is anticipated to become a primary pathway for carbon emission reduction in the Beijing–Tianjin–Hebei region. This study expands the analytical framework for carbon emission reduction pathways under various scenarios and recommends that relevant government departments in the Beijing–Tianjin–Hebei region enhance coordination of “carbon-related” policies across cities and actively explore cross-regional ecological compensation models for forest carbon sinks, etc. Full article

In order to investigate the influence of different tire textures, pavement types, and vehicle parameters on the tire/road noise level and its spectrum characteristics, 19 kinds of asphalt pavement main structures of RIOHTrack full-scale test track were tested by the close-proximity trailer (CPXT) tire/road noise detection method. Considering investigated parameters such as tire texture, vehicle speed, and trailer axle weight, and relying on multi-functional road condition rapid detection vehicle and laboratory tests to collect a variety of road surface information and material parameters, a multiple-linear-regression model of tire/road surface noise level of RIOHTrack (Research Institute of Highway Full-scale Test Track) asphalt pavement was constructed. Finally, the causes of noise level differences among different influencing factors were further analyzed through spectrum characteristics. The results show that vehicle speed is the most important factor affecting tire/road noise. The noise level of different tires varies due to different textures, but the noise level among different trailer axle weights is roughly the same. Vehicle speed (v), FWD center deflection (D₀), surface asphalt mixture air voids (VV), sensor-measured texture depth (SMTD) and international roughness index (IRI) were selected to establish the noise prediction models of different tire textures. Noise spectrum analysis shows that the spectrum of different vehicle speeds is significantly wide in the full frequency range, and the spectrum variation of differently textured tires is mainly concentrated in a certain range of the peak frequency. The noise spectrum curve of porous asphalt concrete (PAC13) is significantly lower than that of other asphalt mixtures in the full frequency range above 800Hz, indicating a greater noise reduction effect. Full article

This study evaluates the technical, economic, and environmental feasibility of grid-connected and off-grid hybrid energy systems designed to meet the energy demands of a greenhouse facility. Various system configurations were developed based on combinations of solar, wind, diesel, and battery storage technologies. The analysis considers a daily electricity consumption of 369.52 kWh and a peak load of 52.59 kW for the greenhouse complex. Among the grid-connected systems, the grid/PV configuration was identified as the most optimal, offering the lowest Net Present Cost (NPC) of USD 282,492, the lowest Levelized Cost of Energy (LCOE) at USD 0.0401/kWh, and a reasonable emissions reduction of 54.94%. For off-grid scenarios, the generator/PV/battery configuration was the most cost-effective option, with a total cost of USD 1.19 million and an LCOE of USD 0.342/kWh. Environmentally, this system showed a strong performance, achieving a 64.58% reduction in CO₂ emissions; in contrast, fully renewable systems such as PV/wind/battery and wind/battery configurations succeeded in reaching zero-emission targets but were economically unfeasible due to their very high investment costs and limited practical applicability. Sensitivity analyses revealed that economic factors such as inflation and energy prices have a critical effect on the payback time and the Internal Rate of Return (IRR). Full article

This study investigates the financial and operational feasibility of deploying electric vehicle (EV) charging infrastructure within high-density residential buildings, utilizing empirical operational data combined with comprehensive financial modeling. A 14-day monitoring period conducted at a residential complex comprising 958 units revealed distinct charging behaviors, with demand peaking during weekday evenings between 19:00 and 22:00 and displaying more dispersed yet lower overall utilization during weekends. Energy efficiency emerged as a significant operational constraint, as standby power consumption contributed substantially to total energy losses. Specifically, while total energy consumption reached 248.342 kW, only 138.24 kW were directly delivered to users, underscoring the necessity for energy-efficient hardware and intelligent load management systems to minimize idle consumption. The financial analysis identified pricing as the most critical determinant of project viability. Under current cost structures, financial break-even was attainable only at a profit margin of 0.2286 USD (8 THB) per kWh, while lower margins resulted in persistent financial deficits. Sensitivity analysis further demonstrated the considerable vulnerability of the project’s financial performance to small fluctuations in profit share and utilization rate. A 10% reduction in either parameter entirely eliminated the project’s ability to reach payback, while variations in energy costs, capital expenditures (CAPEX), and operational expenditures (OPEX) exerted comparatively limited influence. These findings emphasize the importance of precise demand forecasting, adaptive pricing strategies, and proactive government intervention to mitigate financial risks associated with residential EV charging deployment. Policy measures such as capital subsidies, technical regulations, and transparent pricing frameworks are essential to incentivize private sector investment and support sustainable expansion of EV infrastructure in residential sectors. Full article

Bolted connections are extensively utilized in aerospace, civil, and mechanical systems for structural assembly. However, inevitable structural vibrations can induce bolt loosening, leading to preload reduction and potential structural failure. Early-stage preload degradation, particularly during initial loosening, is often undetectable by conventional monitoring methods due to limited sensitivity and poor noise resilience. To address these limitations, this study proposes an intelligent bolt preload monitoring framework that combines electromechanical impedance (EMI) signal analysis with a parallel deep learning architecture. A multiphysics-coupled model of flange joint connections is developed to reveal the nonlinear relationships between preload degradation and changes in EMI conductance spectra, specifically resonance peak shifts and amplitude attenuation. Based on this insight, a parallel convolutional neural network (P-CNN) is designed, employing dual branches with 1 × 3 and 1 × 7 convolutional kernels to extract local and global spectral features, respectively. The architecture integrates dilated convolution to expand frequency–domain receptive fields and an enhanced SENet-based channel attention mechanism to adaptively highlight informative frequency bands. Experimental validation on a flange-bolt platform demonstrates that the proposed P-CNN achieves 99.86% classification accuracy, outperforming traditional CNNs by 20.65%. Moreover, the model maintains over 95% accuracy with only 25% of the original training samples, confirming its robustness and data efficiency. The results demonstrate the feasibility and scalability of the proposed approach for real-time, small-sample, and noise-resilient structural health monitoring of bolted connections. Full article

Lithium plating (LP), as a specific degradation mechanism in lithium-ion batteries (LIBs), has been thoroughly investigated regarding formation conditions and potential safety hazards, but it is yet unknown how this effect influences the mechanical properties of batteries in the case of mechanical deformation. To address this issue, pouch cells used in EVs were artificially aged (AA) to a state of health of 80–82% in conditions that predominantly cause the formation of LP. These cells were subjected to a mechanical abuse load, and safety-relevant parameters, such as tolerated deformation level, failure force, and the process of thermal runaway (TR), were analyzed and compared with respective fresh (F) and aged cells of the same type. Complementary microscopy analyses were carried out to compare the found changed mechanical response with the different layer morphology caused by LP. The tests did exhibit a significantly different mechanical response of cells in the three states but also clearly altered short-circuiting behavior. The tolerated peak force at discharge state dropped by −28% and at charge state by −37% compared to fresh cells, while the deformation at failure slightly increased by +6% for the AA cells. A clear reduction in stiffness (−16%) of the LP cells was attributed to the formed layer, identified as mossy LP. The significantly stronger voltage drop at failure, seen for the LP cells, was associated with severe exothermal reactions of LP in contact with air and moisture during TR. This study revealed the strong influence of LP on the mechanical properties of LIBs. However, the transferability of the findings to other cell chemistries or formats is unclear, emphasizing the need for further investigations in this research field. Full article

In the present study, the biofilm formation and ultraviolet-C (UVC) resistance characteristics of Escherichia coli isolated from an occluded biliary stent were compared with those of four E. coli O157:H7 strains (ATCC 35150, 43889, 43890, and 43895). To evaluate biofilm formation, the E. coli isolated from a stent and four E. coli O157:H7 strains were incubated at 37, 25, and 15 °C for 7 days, revealing that peak biofilm formation occurred at 37 °C (day 1), 25 °C (day 3), and 15 °C (day 5), with the stent-isolated strain consistently exhibiting significantly higher biofilm cell counts than the others (p < 0.05). The UVC treatment was less effective at reducing viable biofilm cells as the formation temperature decreased, with the stent-isolated E. coli biofilm formed at 15 °C showing the lowest reduction levels. Exopolysaccharide quantification revealed that all E. coli strains produced more extracellular polymeric substances (EPSs) at lower temperatures, with the stent-isolated E. coli biofilm formed at 15 °C showing significantly higher EPS levels than the other strains (p < 0.05), potentially explaining its greater UVC resistance. Based on these results, it was confirmed that the biofilm formed by the E. coli isolated from the stent at 15 °C exhibited the highest resistance to UVC, which can be attributed to its elevated exopolysaccharide production. This study demonstrates that both temperature and maturation period significantly influence E. coli biofilm characteristics and provides valuable insights into E. coli isolated from the stent, which may pose a risk of cross-contamination in food-related environments. Full article

With the increasing intensity of resource development in alpine regions, numerous geotechnical engineering problems in cold regions have become increasingly prominent. In order to explore the damage and deterioration laws of rocks caused by freeze–thaw action, this paper takes the biotite granulite on the eastern slope of Yanshan Iron Mine as the research object. By analyzing the changes in mechanical and acoustic emission parameters of rock samples after freeze–thaw, and combining with existing freeze–thaw damage theories, the suitable freeze–thaw damage mechanism for this rock is further explored, and a freeze–thaw damage model for biotite granulite with low and high freeze–thaw cycles is established. The results of this study demonstrate that biotite granulite subjected to a lower number of freeze–thaw cycles exhibits significantly greater reductions in peak strength, elastic modulus, acoustic emission (AE) hit counts, cumulative ringing counts, and cumulative energy compared with specimens exposed to a higher number of cycles. As the freeze–thaw cycles increase, the formation of newly generated large-scale fractures during failure becomes progressively less pronounced, leading to a diminished resistance to deformation and a gradual increase in plastic deformation during loading. A coupled damage variable relationship was established for biotite granulite under both low and high freeze–thaw regimes based on cumulative AE ringing counts. In the early three stress stages, specimens subjected to fewer cycles exhibited fewer microcracks, with no clear spatial correlation between their distribution and the eventual fracture coalescence zones, whereas specimens exposed to a higher number of cycles showed a distinct sequential relationship between microcrack initiation sites and subsequent crack coalescence. Building upon existing freeze–thaw damage theories, the freeze–thaw damage mechanism specific to biotite granulite was further elucidated. Accordingly, a freeze–thaw damage model for low- and high-cycle conditions was developed and preliminarily validated. Full article

One of the most important applications of solar energy is electricity generation using photovoltaic (PV) panels. Yet, as the temperature of PV modules rises, both their efficiency and service life decline. A common approach to mitigate this issue is cooling with fins, a design that is now widely adopted. However, traditional fin-based cooling systems often fail to deliver adequate performance in hot regions with strong solar radiation. In particular, passive cooling alone shows limited effectiveness under conditions of high ambient temperatures and intense sunlight, such as those typical in Malaysia. To address this limitation, hybrid cooling strategies, especially those integrating both air and water, have emerged as promising solutions for enhancing PV performance. In this study, an experimental and economic investigations were carried out on a PV cooling system combining copper tubes and aluminium fins, tested under Malaysian climatic conditions. The economic feasibility was evaluated using the Simple Payback Period (SPP) method. An outdoor test was conducted over four consecutive days (10–13 June 2024), comparing a conventional PV module with one fitted with the hybrid cooling system (active and passive). The cooled module achieved noticeable surface temperature reductions of 2.56 °C, 2.15 °C, 2.08 °C, and 2.58 °C across the four days. The system also delivered a peak power gain of 66.85 W, corresponding to a 2.82% efficiency improvement. Economic analysis showed that the system’s payback period is 4.52 years, with the total energy value increasing by USD 477.88, representing about a 2.81% improvement compared to the reference panel. In summary, the hybrid cooling method demonstrates clear advantages in lowering panel temperature, enhancing electrical output, and ensuring favorable economic performance. Full article

In this study, the impact resistance of WUF-B steel frame beam–column joints under fire was investigated using ABAQUS finite element software through a sequential thermal–mechanical coupling approach. By integrating a room-temperature impact model with a single-sided fire field applied to the lower flange of the steel beam, the multi-parameter influence mechanisms—including temperature (150–750 °C), fire area distribution, and impact momentum—were systematically analyzed. Results indicate that elevated temperatures significantly degrade structural impact resistance. At 750 °C, the peak impact force decreases by 73.3% compared to room temperature, while the mid-span bending moment increases by 63.3%. When the fire zone is near the impact point, localized thermal softening further reduces the peak impact force. Under constant impact energy, lower momentum (i.e., higher velocity) accelerates the rebound of the falling mass, revealing the role of momentum transfer efficiency in governing the transient response of high-temperature structures. Additionally, an analytical prediction model based on Timoshenko beam theory and thermo-mechanical stiffness degradation is developed. By introducing a segmented temperature reduction function, the model significantly enhances the accuracy of mid-span displacement predictions for steel structures under fire. Full article

Pharmaceutical formulations, in addition to the medicinal substance(s), contain added excipients that make it possible to create a pharmaceutical product that exhibits required properties in terms of mechanical, physical, chemical, and microbiological stability. Additionally, these substances can act as release modifiers or improve bioavailability parameters. Literature data indicate that excipients, especially polymeric ones, can also affect the polymorphism of the active substance, resulting in drug bioavailability enhancement or reduction. This influence can be evaluated using thermal and spectroscopic methods. In the study, differential scanning calorimetry (DSC), vibrational spectroscopic studies (Fourier transform infrared spectroscopy, FTIR), Raman spectroscopy, and X-ray diffraction (XRD) assay of ibuprofen, naproxen, and naproxen sodium standards and pharmaceutical preparations containing these medicinal substances in their compositions were carried out. DSC results indicated that a sharp melting peak was observed on the DSC curves of the standards, confirming their crystalline form. DSC results obtained for pharmaceutical formulations also indicated that the enthalpy of melting is sometimes lower than calculated from the percentage of active ingredients in the formulations. In addition, the melting peak is often broadened and shifted toward lower temperatures, suggesting the influence of excipients on the polymorphism of drug substances. The FTIR and Raman spectra of pharmaceutical formulations contained all characteristics of the active substances. XRD analysis was also performed. Therefore, possible chemical interactions between the components of the preparations have been excluded. At the same time, FTIR and Raman spectroscopy results as well as XRD assay showed a reduction in the height of signals corresponding to the crystalline API form, confirming the possibility of reducing API crystallinity in pharmaceutical formulations. Full article

Staining variability in histopathological images compromises automated diagnostic systems by affecting the reliability of computational pathology algorithms. Existing normalization methods prioritize color consistency but often sacrifice critical morphological details essential for accurate diagnosis. This work proposes a novel deep learning framework, integrating enhanced residual learning with multi-scale attention mechanisms for structure-preserving stain normalization. The approach decomposes the transformation process into base reconstruction and residual refinement components, incorporating attention-guided skip connections and progressive curriculum learning. The method was evaluated on the MITOS-ATYPIA-14 dataset containing 1420 paired H&E-stained breast cancer images from two scanners. The framework achieved exceptional performance with a structural similarity index (SSIM) of 0.9663 ± 0.0076, representing 4.6% improvement over the best baseline (StainGAN). Peak signal-to-noise ratio (PSNR) reached 24.50 ± 1.57 dB, surpassing all comparison methods. An edge preservation loss of 0.0465 ± 0.0088 demonstrated a 35.6% error reduction compared to the next best method. Color transfer fidelity reached 0.8680 ± 0.0542 while maintaining superior perceptual quality (FID: 32.12, IS: 2.72 ± 0.18). The attention-guided residual learning framework successfully maintains structural integrity during stain normalization, with superior performance across diverse tissue types, making it suitable for clinical deployment in multi-institutional digital pathology workflows. Full article

This study examines the impact of using eco-friendly biodiesel blends with Jet A fuel in aviation microturbine engines, both with and without an ejector. Three biodiesel concentrations (10%, 20%, and 30%) were evaluated under three different operating conditions. Key performance indicators, including combustion temperature, fuel consumption, propulsive force, specific fuel consumption, and emissions, were analyzed. Results indicate that fuel consumption increases with higher biodiesel content, reaching a peak rise of 3.05% at idle for a 30% biodiesel blend. However, the ejector helps offset this increase, reducing fuel consumption by 3.82% for Jet A. A similar trend is observed for specific fuel consumption (SFC), which decreases by up to 19.67% when using Jet A with the ejector at idle. The addition of an ejector significantly enhances propulsive force, achieving improvements of up to 36.91% for a 30% biodiesel blend at idle. At higher operating regimes, biodiesel alone slightly reduces thrust, but the ejector effectively compensates for these losses. Emission analysis reveals that using biodiesel leads to a cleaner combustion process, significantly reducing CO and SO₂ emissions. The ejector further enhances this effect by improving airflow and combustion efficiency. Additionally, noise measurements conducted using five microphones demonstrate that the ejector contributes to noise reduction. Overall, this study concludes that integrating an ejector with sustainable biodiesel blends not only enhances engine performance but also significantly reduces the environmental footprint of aviation microturbine engines. Full article

Background: Obesity affects over one billion people globally. Bariatric surgery is the most effective long-term intervention for severe obesity. However, postoperative outcomes can vary considerably, with such factors as baseline fitness and cardiorespiratory reserve influencing surgical outcomes. This systematic review aimed to evaluate the effects of preoperative exercise or physical activity, compared to standard care or no intervention, on preoperative fitness parameters and perioperative surgical outcomes in adults with obesity undergoing metabolic and bariatric surgery. Methods: A systematic review was conducted in accordance with the recommendations of the Cochrane Handbook and the PRISMA guidelines. Randomized controlled trials, non-randomized controlled trials, and cohort studies with control groups evaluating preoperative exercise interventions were included. Two independent reviewers conducted study selection, data extraction, and risk of bias assessment using Cochrane tools. Meta-analyses were performed using random effects models, with standardized mean differences calculated for continuous outcomes. Evidence certainty was assessed using the GRADE approach. Results: A total of 15 studies, including 1378 participants, were identified for qualitative synthesis, with 12 contributing data for quantitative meta-analysis. Preoperative exercise interventions significantly improved six-minute walk test distance (SMD 2.01; 95% CI: 0.51 to 3.50; p = 0.009) and VO₂ peak (SMD 1.02; 95% CI: 0.52 to 1.51; p < 0.0001). BMI reduction was significant (SMD −0.96; 95% CI: −1.75 to −0.16; p = 0.02), while weight change was not statistically significant (SMD −0.81; 95% CI: −1.72 to 0.09; p = 0.08). One study reported a reduction in hospital length of stay of 0.64 days (95% CI: −0.86 to −0.42; p < 0.00001). Evidence certainty was rated as very low to low across all outcomes. Conclusions: Preoperative exercise interventions have been shown to significantly improve cardiorespiratory fitness in bariatric surgery candidates, with large effect sizes for functional capacity measures. Despite the low certainty of the evidence, these findings suggest that supervised exercise programs should be incorporated into the preoperative care of bariatric surgery patients. Full article

The Western Reef Heron (Egretta gularis) has a wide geographic distribution, ranging from the coasts of West Africa to Southwest Asia, including the Arabian Peninsula. Despite this extensive range, detailed information on its incubation behavior remains scarce. To address this gap, we investigated the 24 h incubation behavior of Western Reef Herons on Al-Fanateer Island, Eastern Saudi Arabia, during early summer—a period characterized by pronounced diurnal fluctuations in ambient temperature. Using trail cameras and temperature loggers, we found that adults maintained nearly continuous attendance at the nest throughout the day, with incubation coverage exceeding 97% across all two-hour intervals. A slight reduction in nest attendance was observed during nighttime (lowest at 86.8% between 20:00–21:59). Incubating adults exhibited behavioral plasticity in response to ambient temperature: a sitting posture was predominant during cooler periods, while a shading posture was more frequent during peak heat. Incubating adults also adjusted their orientation with the solar angle, actively avoiding southern and western exposures during the hottest parts of the day. Despite substantial variation in ambient temperature, the temperature beneath the clutch ranged from 29.4 to 37.8 °C, which may indicate effective thermoregulation. These findings suggest that a combination of near-continuous nest attendance, posture adjustment, and solar orientation avoidance allows Western Reef Herons to mitigate thermal stress and maintain optimal conditions for embryo and chick development. We recommend long-term monitoring of incubation behavior in this species to further evaluate its adaptability to environmental changes, particularly those driven by climate variability. Full article