Search Results (30,685)

A corporate carbon information disclosure strategy is essentially an environmental responsibility manifestation of “inconsistency between words and deeds”. It has two forms:, green “silence” and green “catering”, both of which restrict the externalization of green productivity and affect the high-quality development of enterprises. This study shows that ① there is a U-shaped relationship between carbon information disclosure strategies and the high-quality development of enterprises. Green “silence” positively affects the high-quality development of enterprises, and the impact of green “catering” on the high-quality development of enterprises changes from negative to positive. ② Green “silence” affects the high-quality development of enterprises by increasing R&D investment, reducing tax burdens, and intensifying financing constraints, while green “catering” affects the high-quality development of enterprises by decreasing R&D investment, increasing the tax burden, and easing financing constraints. ③ If the competition in the industry is fierce, the green “silence” strategy should be adopted. When there is monopoly in the industry, the green “catering” strategy is dominant. The findings of this study not only provide management suggestions for enterprises on how to correctly treat the carbon information disclosure strategies that have been implemented or planned to promote their own high-quality development, but also provide policy inspiration for relevant regulatory authorities to complete the transition from voluntary disclosure to mandatory disclosure. Full article

Background: This study investigates the application of Machine Learning techniques to predict clinical outcomes in microsurgical clipping treatments of cerebral aneurysms, aiming to enhance healthcare processes through informed clinical decision making. Methods: Relying on a dataset of 344 patients’ preoperative characteristics, various ML classifiers were trained to predict outcomes measured by the Glasgow Outcome Scale (GOS). The study’s results were reported through the means of ROC-AUC scores for outcome prediction and the identification of key predictors using SHAP analysis. Results: The trained models achieved ROC-AUC scores of 0.72 ± 0.03 for specific GOS outcome prediction and 0.78 ± 0.02 for binary classification of outcomes. The SHAP explanation analysis identified intubation as the most impactful factor influencing treatment outcomes’ predictions for the trained models. Conclusions: The study demonstrates the potential of ML for predicting surgical outcomes of ruptured cerebral aneurysm treatments. It acknowledged the need for high-quality datasets and external validation to enhance model accuracy and generalizability. Full article

China’s Yunnan Province, known for its tea plantations, faces significant challenges in smart pest management due to its ecologically intricate environment. To enable the intelligent monitoring of pests within tea plantations, this study introduces a novel image recognition algorithm, designated as YOLOv8n-WSE-pest. Taking into account the pest image data collected from organic tea gardens in Yunnan, this study utilizes the YOLOv8n network as a foundation and optimizes the original loss function using WIoU-v3 to achieve dynamic gradient allocation and improve the prediction accuracy. The addition of the Spatial and Channel Reconstruction Convolution structure in the Backbone layer reduces redundant spatial and channel features, thereby reducing the model’s complexity. The integration of the Efficient Multi-Scale Attention Module with Cross-Spatial Learning enables the model to have more flexible global attention. The research results demonstrate that compared to the original YOLOv8n model, the improved YOLOv8n-WSE-pest model shows increases in the precision, recall, mAP50, and F1 score by 3.12%, 5.65%, 2.18%, and 4.43%, respectively. In external validation, the mAP of the model outperforms other deep learning networks such as Faster-RCNN, SSD, and the original YOLOv8n, with improvements of 14.34%, 8.85%, and 2.18%, respectively. In summary, the intelligent tea garden pest identification model proposed in this study excels at precise the detection of key pests in tea plantations, enhancing the efficiency and accuracy of pest management through the application of advanced techniques in applied science. Full article

This study addresses the issue of unsatisfactory smoothness in the movement of integrated internal and external cross roller bearings post-assembly, which compromises the movement flexibility of the finished bearing and fails to meet index requirements. Focusing on a specific type of precision cross roller bearing, this paper establishes a finite element explicit dynamic simulation model that takes into account the plugging position and matching relationship. A transient dynamic simulation of the roller blockage process was conducted, yielding insights into the contact pressure and deformation experienced by the roller and plug during this blockage. The results indicate that when both the taper pin are positioned centrally, and the plug matching clearance, plug sag and protruding amount, and plug rotation offset degrees are all set to 0 μm, the contact pressure between the roller and raceway, as well as the roller deformation displacement, are minimized. The plugging position and fit were subsequently validated through testing, which also measured the impact of these parameters on the roundness of the raceway surface and the bearing’s friction torque. The test findings corroborate that when the taper and pin are centrally aligned, and the stopper clearance is 5 μm, with the plug sag, protrusion, and offset all at 0 μm, the roundness of the raceway surface and the bearing’s friction torque reach their lowest values, thereby optimizing the stability of bearing motion. By comparing the simulation and experimental results, it is concluded that during bearing assembly, it is crucial to maintain the taper pin in a central position, control the plug matching clearance to approximately 5 μm, and ensure the plug sag, protrusion, and rotation offset amount are both at 0 μm. This approach guarantees optimal contact conditions and motion stability during operation. The findings of this research offer valuable design guidance for the selection of appropriate plugging positions and fits in precision cross roller bearings. Full article

Objectives: Pharmacokinetic issues were the leading cause of drug attrition, accounting for approximately 40% of all cases before the turn of the century. To this end, several high-throughput in vitro assays like microsomal stability have been developed to evaluate the pharmacokinetic profiles of compounds in the early stages of drug discovery. At NCATS, a single-point rat liver microsomal (RLM) stability assay is used as a Tier I assay, while human liver microsomal (HLM) stability is employed as a Tier II assay. We experimentally screened and collected data on over 30,000 compounds for RLM stability and over 7000 compounds for HLM stability. Although HLM stability screening provides valuable insights, the increasing number of hits generated, along with the time- and resource-intensive nature of the assay, highlights the need for alternative strategies. One promising approach is leveraging in silico models trained on these experimental datasets. Methods: We describe the development of an HLM stability prediction model using our in-house HLM stability dataset. Results: Employing both classical machine learning methods and advanced techniques, such as neural networks, we achieved model accuracies exceeding 80%. Moreover, we validated our model using external test sets and found that our models are comparable to some of the best models in literature. Additionally, the strong correlation observed between our RLM and HLM data was further reinforced by the fact that our HLM model performance improved when using RLM stability predictions as an input descriptor. Conclusions: The best model along with a subset of our dataset (PubChem AID: 1963597) has been made publicly accessible on the ADME@NCATS website for the benefit of the greater drug discovery community. To the best of our knowledge, it is the largest open-source model of its kind and the first to leverage cross-species data. Full article

The investigation of the central and external zones of ten industrial and artisanal Maroilles cheeses showed differences in their physicochemical parameters, namely fat, pH, moisture content, ash, and color. This difference significantly impacted the rheological properties of the investigated cheeses, which depended on the protein network englobing lipid and water and its interaction with the other components. Overall, Maroilles cheeses had an elastic-like behavior, with the central zones exhibiting the greatest viscoelastic modules (G′ and G″). The mid-infrared (MIR) spectra highlighted the presence of lipids, proteins, and sugars. A significant difference in α-helix and β-sheet levels in the central zones was noted between artisanal and industrial Maroilles cheeses. It is suggested that the difference between artisanal and industrial Maroilles cheeses observed at the macroscopic level, due to the cheese-making procedure and ripening stage, affects the structure at the molecular level, which can be determined by MIR spectroscopy. This trend was confirmed by the FDA when applied to the MIR spectra, since 96.67% correct classification was noted between artisanal and industrial cheeses. The present study indicates that MIR spectroscopy can be used successfully to study Maroilles cheese samples belonging to different production chains. Full article

The aim of this work was to investigate the combustion of biochar in a fluidised bed and determine the intrinsic kinetic parameters for combustion: pre-exponential constant $A_i$ and activation energy $E_i$. When analysing the rates of reaction, Regimes I, II and III were demonstrated, with values for the activation energy of 155, 57 and 9 kJ/mol, respectively, when combustion was limited by different factors: intrinsic kinetics, intraparticle and external mass transport phenomena. These mass transport phenomena were decoupled from a set of ‘apparent’ kinetics incorporating effectiveness factors, which we used as a starting point in the determination of the intrinsic kinetic parameters. We also investigated a simple approach to model the evolution of the char structure over the course of oxidation using an empirical function, $f\left(X\right)$, fitted with an O(7) polynomial. We then reassessed the division into three combustion regimes by exploring the changes in $f\left(X\right)$ and the intraparticle effectiveness factor that occurred upon increasing the combustion temperature. Overall, we demonstrate that experiments in a fluidised bed can be used to determine biochar kinetics in a simplified but trustworthy way. Full article

Traditional door mechanisms in public spaces, such as knob locks and standard handles, require manual contact, making them prone to contamination and posing significant health risks. To address the critical need for a safer and more hygienic solution, this study aimed to develop an innovative foot-operated door mechanism that is accessible and intuitive for all users. The study applies the Theory of Inventive Problem Solving (TRIZ), ergonomic principles, and universal design to develop the foot-operated mechanism, while using Importance–Performance Analysis (IPA) and the Kano model to evaluate user satisfaction and identify design improvements. The foot-operated mechanism developed in this study features internal and external pedals for seamless door operation, a secure locking system, and color-coded indicators for clear occupancy status communication, ensuring both ease of use and privacy. The design significantly enhances hygiene by minimizing manual contact and improves user convenience, as confirmed through the IPA-Kano analysis. This mechanism not only provides a practical and effective solution to contamination risks but also demonstrates versatility, making it suitable for various public spaces and accessible to a wide range of users. This study represents a significant contribution to public infrastructure by providing a safer, more hygienic, and sustainable solution for door operation in public spaces. Full article

Bio-oil produced via fast pyrolysis, irrespective of the biomass source, faces several limitations, such as high water content, significant oxygenated compound concentration (35–40 wt.%), a low heating value (13–20 MJ/kg), and poor miscibility with fossil fuels. These inherent drawbacks hinder the bio-oil’s desirable properties and usability, highlighting the necessity for advanced processing techniques to overcome these challenges and improve the bio-oil’s overall quality and applicability in energy and industrial sectors. To address the limitations of bio-oil, a magnetic bimetallic oxide catalyst supported on activated rice straw biochar (ZrO₂-Fe₃O₄/AcB), which has not been previously employed for this purpose, was developed and characterized for upgrading rice straw bio-oil in supercritical butanol via esterification. Furthermore, the silica in the biochar, combined with the Lewis acid sites provided by ZrO₂ and Fe₃O₄, offers Brønsted acid sites. This synergistic combination enhances the bio-oil’s quality by facilitating esterification, deoxygenation, and mild hydrogenation, thereby reducing oxygen content and increasing carbon and hydrogen levels. The effects of variables, including time, temperature, and catalyst load, were optimized using response surface methodology (RSM). The optimal reaction conditions were determined using a three-factor, one-response, and three-level Box-Behnken design (BBD). The ANOVA results at a 95% confidence level indicate that the results are statistically significant due to a high Fisher’s test (F-value = 37.07) and a low probability (p-value = 0.001). The minimal difference between the predicted R² and adjusted R² for the ester yield (0.0092) suggests a better fit. The results confirm that the optimal reaction conditions are a catalyst concentration of 1.8 g, a reaction time of 2 h, and a reaction temperature of 300 °C. Additionally, the catalyst can be easily recycled for four reaction cycles. Moreover, the catalyst demonstrated remarkable reusability, maintaining its activity through four consecutive reaction cycles. Its magnetic properties allow for easy separation from the reaction mixture using an external magnet. Full article

Chronic kidney disease (CKD) is a progressive condition characterized by a continuous decline in renal function, independent of the initial cause of damage or external factors such as infection, inflammation, or toxins. The accurate measurement of renal function, typically assessed using the glomerular filtration rate (GFR), is crucial for managing CKD. The most accepted hypothesis for CKD progression is glomerular damage caused by hyperfiltration. Various factors can accelerate CKD progression, and several biomarkers have been identified to monitor this progression. Numerous studies have explored the risk factors associated with CKD progression, and some of these factors can be modified. Additionally, several drugs are now available that can reduce CKD progression. This review summarizes recent publications and highlights potential future research directions in CKD progression. It discusses the evolution of GFR measurement methods, the mechanisms driving CKD progression, and the latest findings on biomarkers and risk factors. Furthermore, it explores therapeutic strategies, including dietary modifications and pharmacological interventions, to slow CKD progression. Understanding these mechanisms and interventions is crucial for developing effective therapeutic strategies to prevent or slow CKD progression. Full article

This paper deals with the experimental procedures of lock-in thermography (LIT) for polyetheretherketone (PEEK), which is used as a lightweight material in various industrial fields. The LIT has limitations due to non-uniform heating by external optic sources and the non-uniformity correction (NUC) of the infrared (IR) camera. It is generating unintended contrast in the IR image in thermal imaging inspection, reducing detection performance. In this study, the non-uniformity effect was primarily improved by producing an equivalent array halogen lamp. Then, we presented absolute temperature compensation (ATC) and temperature ratio compensation (TRC) techniques, which can equalize the thermal contrast of the test samples by compensating for them using reference samples. By applying compensation techniques to data acquired from the test samples, defect detectability improvement was quantitatively presented. In addition, binarization was performed and detection performance was verified by evaluating the roundness of the detected defects. As a result, the contrast of the IR image was greatly improved by applying the compensation technique. In particular, raw data were enhanced by up to 54% using the ATC compensation technique. Additionally, due to improved contrast, the signal-to-noise ratio (SNR) was improved by 7.93%, and the R² value of the linear trend equation exceeded 0.99, demonstrating improved proportionality between the defect condition and SNR. Full article

The European Community has prioritized reducing energy consumption and improving energy efficiency in the building sector, along with ensuring increasingly high standards of thermal comfort, as key goals over recent decades. Given the impact of climate change, the rising frequency of extreme weather events, and the rapid shifts in peak demand during both winter and summer, buildings must efficiently respond to sudden and extreme temperature fluctuations while maintaining optimal indoor comfort. Phase-change materials (PCMs), which can adapt their thermophysical properties in response to external conditions, may offer a solution for enhancing building resilience to climate change. This paper evaluates the benefits of integrating various PCMs with plasterboard in the energy retrofit of a multi-family complex in a Mediterranean climate. The study examines the application of a PCM with a melting temperature of 25 °C at three different thicknesses (74.2 mm, 37.1 mm, and 20.8 mm) to external walls, ceilings, and both walls and ceilings simultaneously. Among the various applications, using the PCM on walls alone maximized heating savings as thickness increased (26.6%), while ceiling application maximized cooling energy savings (17.5%). Combined solutions offered the most balanced seasonal benefits, leading to the greatest overall energy reductions (24.1%). Full article

The methods of increasing the efficiency of internal combustion engines through heat utilization are examined. A proposed classification of heat utilization systems for mobile energy vehicles is presented. External utilization harnesses the heat generated by a diesel engine to fulfill the needs of consumers not directly related to the engine, such as interior heating and air conditioning systems. Internal recycling focuses on enhancing the power, environmental performance, and economic performance of an engine and its related systems. Various heat utilization schemes are compared. For the economic conditions of the European Union (EU), a turbocompounding diesel engine is acceptable if its agricultural tractor rated power is more than 275 kW and its combine harvester rated power is more than 310 kW. Steam injection into the combustion chamber is utilized to improve the technical and economic performance of gas turbine engines. This technology is also produced in Ukraine and is proposed for use in internal combustion engines. It is suggested to inject water vapor into a turbocharger turbine. This approach reduces the number of components in the heat recovery system, thereby lowering its cost. A recycling chiller can be employed to cool the air after it passes through the air cleaner, enhance the efficiency of the air cooler, and improve the performance of the thermoelectric generators. This device is particularly effective at relatively high air temperatures and can be recommended for agricultural machinery that operates in such conditions, such as combines. With the application of this new technology, it is possible to increase the power of diesel engines by 15…20% and reduce fuel consumption by up to 14%. Further research will focus on substantiating the parameters of recycling systems for different classes of vehicles. Developing a methodology to justify the effective application of heat utilization systems in agricultural mobile energy vehicles is advisable. Full article

The role of the respiratory microbiome has been deeply explored for at least two decades. Its characterization using modern methods is now well-defined, and the impacts of many microorganisms on health and diseases have been elucidated. Moreover, the acquired knowledge in related fields enables patient stratification based on their risk for disease onset, and the microbiome can play a role in defining possible phenotypes. The interplay between the lung and gut microbiomes is crucial in determining the microbial composition and immuno-inflammatory reaction. Asthma is still not a well-defined condition, where hyperreactivity and the immune system play important roles. In this disease, the microbiome is mostly represented by Proteobacteria, Streptococcus, and Veillonella, while Cytomegalovirus and Epstein–Barr viruses are the most prevalent viruses. A mycobiome may also be present. The passage from infancy to adolescence is examined by evaluating both the clinical picture and its relationship with possible variations of the microbiome and its effects on asthma. Otherwise, asthma is considered a heterogeneous disease that often starts in childhood and follows a particular personalized track, where adolescence plays a pivotal role in future prognosis. Under this point of view, the microbiota, with its possible variations due to many factors, both internal and external, can modify its composition; consequently, its inflammatory action and role in the immunological response has obvious consequences on the clinical conditions. Full article

This paper presents novel chattering-free robust control strategies for addressing disturbances and uncertainties in a two-degree-of-freedom (2-DOF) unmanned aerial vehicle (UAV) dynamic model, with a focus on the highly nonlinear and strongly coupled nature of the system. The novelty lies in the development of sliding mode control (SMC), integral sliding mode control (ISMC), and terminal sliding mode control (TSMC) laws specifically tailored for the twin-rotor MIMO system (TRMS). These strategies are validated through both simulation and real-time experiments. A key contribution is the introduction of a uniform robust exact differentiator (URED) to recover rotor speed and missing derivatives, combined with a nonlinear state feedback observer to improve system observability. A feedback linearization approach, using lie derivatives and diffeomorphism principles, is employed to decouple the system into horizontal and vertical subsystems. Comparative analysis of the transient performance of the proposed controllers, with respect to metrics such as settling time, overshoot, rise time, and steady-state errors, is provided. The ISMC method, in particular, effectively mitigates the chattering issue prevalent in traditional SMC, improving both system performance and actuator longevity. Experimental results on the TRMS demonstrate the superior tracking performance and robustness of the proposed control laws in the presence of nonlinearities, uncertainties, and external disturbances. This research contributes a comprehensive control design framework with proven real-time implementation, offering significant advancements over existing methodologies. Full article