Search Results (4,235)

A facile method was employed to impregnate activated carbon, a commonly used water treatment medium, with nanostructured magnesium oxide for fluoride removal. Batch adsorption tests were conducted to evaluate the adsorption performance of the nanostructured magnesia-impregnated activated carbon (nMgO@AC) for fluoride removal. The results demonstrated that this composite material exhibited a good adsorption capacity, with a maximum equilibrium uptake of approximately 121.1 mg/g for fluoride. Kinetic studies revealed that the adsorption process followed the pseudo-second-order adsorption kinetic model, reaching equilibrium in about 100 min. Within the initial pH range of 3 to 11, the adsorption efficiency of nMgO@AC for fluoride remained above 95%, indicating that the initial solution pH had a minimal effect on the material’s fluoride removal capability. The adsorption mechanism was elucidated by characterizing the material properties before and after adsorption using SEM, TEM, XRD and XPS. Initially, magnesium oxide reacted with water and rapidly transformed into magnesium hydroxide. Subsequently, a ligand exchange occurred between the hydroxide groups in magnesium hydroxide and fluoride ions in the aqueous solution, resulting in the effective removal of fluoride. The findings of this study suggest that nanostructured magnesia-impregnated activated carbon holds significant potential for the treatment of fluoride-containing wastewater, particularly for highly alkaline wastewater. Full article

Consumer attitude shift and green transport advocacy in the sharing economy highlight shared two-wheeled electric scooters (STWESs) for short-distance commuting. Current designs often overlook user emotions and aesthetic alignment with product characteristics. A product design methodology is proposed in this study, constructing optimization models from both the functional experiential and perceptual visual layers. Utilizing context analysis theory (CAT) and the KANO model, an STWES contextual requirements optimization model is formulated. The expert method is then applied to identify five key design elements, generating a category diagram based on typical samples, followed by Kansei evaluation. Using quantitation theory type I (QT-1), regression equations are fitted to determine the impact of different design categories on Kansei evaluation. Illustrated in a campus setting, this approach optimizes the shared mobility experience, meeting college students’ aesthetic preferences. This method serves as a valuable reference for product design in diverse contexts. Full article

Study Objectives: This review aims to explore the epidemiology, pathophysiology, risk factors, and diagnostic approaches of obstructive sleep apnea syndrome and small airway disease, emphasizing their interrelationship and implications for clinical management. Methods: A comprehensive analysis of the literature was conducted to examine shared and distinct characteristics of obstructive sleep apnea syndrome and small airway disease. Risk factors, clinical presentations, diagnostic tools, and management strategies were reviewed to identify potential areas for improvement in care. Results: Obstructive sleep apnea syndrome, characterized by intermittent upper airway obstruction during sleep, contributes to fragmented sleep and systemic diseases. Small airway disease involves inflammation and obstruction of the small airways, impairing airflow and gas exchange. Shared risk factors, such as obesity, smoking, and age, were identified as contributors to the development and progression of both conditions. The co-occurrence of obstructive sleep apnea syndrome and small airway disease exacerbates respiratory symptoms and increases the risk of comorbidities, such as pulmonary hypertension, heart failure, and respiratory failure. Recognition of their interplay highlights the need for integrated diagnostic and therapeutic strategies. Conclusions: The interrelationship between obstructive sleep apnea syndrome and small airway disease underscores the importance of integrated management approaches to improve patient outcomes. Addressing shared risk factors and understanding the interplay between these conditions are crucial for optimizing care. This review identifies key knowledge gaps, including the need for precise diagnostic tools and targeted therapies, which are essential for advancing personalized treatment strategies for individuals with obstructive sleep apnea syndrome and small airway disease. Full article

Environmental DNA (eDNA) is DNA isolated from environmental samples. It is distinctly different from genomic DNA, which is extracted directly from biological specimens. eDNA metabarcoding technology is a novel surveillance tool combining eDNA and second-generation high-throughput sequencing technology. Different from conventional approaches and biomonitoring techniques, eDNA metabarcoding technology (eMT) has many advantages, such as promising timeliness and accuracy, lower time consumption, and low cost, and thus is widely used in ecological and environmental monitoring, including that in rivers, lakes, oceans, soils, and sediments. As a tool, eDNA metabarcoding technology supplements the evaluation of environmental qualities by monitoring both the diversity of aquatic biology communities and target species. In addition, it is essential to understand the limitations of eDNA metabarcoding technology in practical applications. As a tool, eDNA metabarcoding technology features high efficiency, providing indicators of environmental health and allowing for the indirect estimation of the impact and extent of water pollution with respect to aquatic ecosystems. It provides new insights for aquatic environment protection. Full article

The irregular outer boundaries of reservoirs and the associated heterogeneous high-permeability zones formed by complex geological environment pose significant challenges in reservoir characterization and performance prediction. These irregular geometries, which are commonly encountered in field applications but often oversimplified in conventional models, can substantially influence fluid flow dynamics and transient pressure behavior. To solve this critical issue, this paper presents a semi-analytical model for studying the transient pressure behavior of irregular heterogeneous reservoirs, focusing on the dynamic interactions between hydraulic fractures and the surrounding matrix. The model integrates Green’s function solutions for matrix flow with finite difference methods to simulate fluid flow within complex fracture networks, capturing the heterogeneity of the reservoir and the irregularity of its boundaries. Specifically, the reservoir is divided into locally homogeneous blocks, and the flow within each block is solved using bounded Green’s functions, while the fracture networks are discretized and solved using finite difference methods. This proposed model significantly reduces computational complexity compared to traditional numerical simulations, while maintaining high accuracy. Subsequently, we conducted comprehensive parameter sensitivity analyses. The calculational results show that a multi-fractured horizontal well in an irregular heterogeneous reservoir can observe the following flow regimes: bilinear flow, elliptical flow, and boundary-dominated flow. Longer fractures and higher conductivity enhance fracture flux by increasing the contact area and reducing flow resistance, respectively. However, these positive impacts are constrained by drainage area limitations as production progresses. Full article

Hyperspectral (HS) and multispectral (MS) image fusion is the most favorable way to obtain a hyperspectral image that has high resolution in terms of spatial and spectral information. This fusion problem can be accomplished by formulating a mathematical model and solving it either analytically or iteratively. The mathematical solutions class has serious challenges, e.g., computation cost, manually tuning parameters, and the absence of imaging models that laboriously affect the fusion process. With the revolution of deep learning, the recent HS-MS image fusion techniques gained good outcomes by utilizing the power of the convolutional neural network (CNN) for feature extraction. Moreover, extracting intrinsic information, e.g., non-local spatial and global spectral features, is the most critical issue faced by deep learning methods. Therefore, this paper proposes an Extensive Feature-Inferring Deep Network (EFINet) with extensive-scale feature-interacting and global correlation refinement modules to improve the effectiveness of HS-MS image fusion. The proposed network retains the most vital information through the extensive-scale feature-interacting module in various feature scales. Moreover, the global semantic information is achieved by utilizing the global correlation refinement module. The proposed network is validated through rich experiments conducted on two popular datasets, the Houston and Chikusei datasets, and it attains good performance compared to the state-of-the-art HS-MS image fusion techniques. Full article

Benzo[a]pyrene, as the primary component of air pollutants, has been implicated in the pathogenesis of non-small-cell lung cancer (NSCLC). As an m6A reader that facilitates mRNA translation, YTHDF1 serves as a crucial regulator in tumor progression. Therefore, we established Benzo[a]pyrene(B[a]P)-induced bronchial epithelial malignant transformed cells (HBE-P35) to simulate the precancerous lesions of NSCLC and investigated the regulatory axis of YTHDF1 in both HBE-P35 and A549 lung cancer cells. A high level of m6A expression was detected in both HBE-P35 and A549 cells. Over-expression of YTHDF1 was observed in NSCLC tissues and correlated with poor overall survival in NSCLC patients. TMT labeling-based proteomic analysis and clinical lung tissue microarray assays demonstrated that CDK6 and MAP3K6 were positively correlated with YTHDF1 expression. MeRIP and RIP analyses revealed that YTHDF1 mediates the m6A-dependent regulation of CDK6 and MAP3K6 protein expression. The acquisition and deletion of miR-139/145-5p, along with luciferase reporter gene assays, demonstrated that miR-139-5p can target YTHDF1. Therefore, we conclude that YTHDF1 regulates CDK6 and MAP3K6 through m6A in B[a]P-induced HBE-P35 and A549 cells, providing a potential target for lung cancer treatment. Full article

In this paper, the inverse problem of identifying the source term of the time fractional diffusion-wave equation is studied. This problem is ill-posed, i.e., the solution (if it exists) does not depend on the measurable data. Under the priori bound condition, the condition stable result and the optimal error bound are all obtained. The fractional Landweber iterative regularization method is used to solve this inverse problem. Based on the priori regularization parameter selection rule and the posteriori regularization parameter selection rule, the error estimation between the regularization solution and the exact solution is obtained. Moreover, the error estimations are all order optimal. At the end, three numerical examples are given to prove the effectiveness and stability of this regularization method. Full article

Exploring the diversity and community structure of darkling beetles (Tenebrionidae) and the associated environmental factors on an alluvial fan provides useful insights into the ecology of these landscape features. This study investigated Chaqikou in the Helan Mountains, which features unique alluvial fan landforms. Sample plots (200 × 200 m) were established at three positions: the fan top, fan middle, and fan edge. From May to October 2023, pitfall traps were used to survey beetle community composition and its relationship with environmental factors. Significant variations were observed in species composition and diversity indices across different months and sample plots. Strongly xerophilous species exhibited broader ecological niche breadth, while moderately xerophilous species tended to distribute in the mid-to-upper segments of alluvial fans. Non-metric multidimensional scaling analysis revealed temporal shifts in community composition, with beta diversity analysis showing that species nestedness dominated from June to August, while species replacement was prominent in May, September, and October. Redundancy analysis indicated that environmental factors affecting species distribution varied by plot. On the landscape scale, altitude was the primary factor affecting beetle distribution. Variance partitioning analysis showed that topographic, soil, and vegetation factors explained 51.7%, 20.2%, and 9.4% of the variation in the beetle community, respectively. It is evident that altitudinal gradients shape ecological filtering pressures by creating multidimensional heterogeneity in topography, soil properties, and vegetation coverage. The adaptive matching between Tenebrionid species’ biological traits and environmental factors ultimately governs the spatial distribution patterns of darkling beetle diversity in alluvial fan desert grasslands. Full article

Frequent salt tectonic activities within the Perdido fold belt complicate hydrocarbon accumulation, severely constraining hydrocarbon exploration. In this paper, the characteristics and differences of hydrocarbon accumulation in the Wilcox and Frio Formations in the central and eastern regions of the Perdido fold belt are analyzed through geochemical analysis, hydrocarbon generation simulation, and regional tectonic restoration. The results indicate the following: (1) Hydrocarbon in the Wilcox and Frio Formations in both the central and eastern regions of the Perdido fold belt originates from the Jurassic Tithonian source rocks. (2) Source rocks in the central and eastern regions entered the oil generation threshold in the late Paleocene and reached the oil generation peak in the late Eocene. Compared with the central region, the eastern region reached the gas generation threshold earlier, which is influenced by the activities and differential distribution of salt in the Perdido fold belt. (3) Hydrocarbon accumulation in central and eastern regions is divided into four stages, showing a “terraced single-layer” and “dual-layer” accumulation pattern in the central and eastern regions of the Perdido fold belt, respectively. (4) Central and eastern regions represent discrepancies in the petroleum systems elements of reservoirs, caprocks, traps, generation, charging, and preservation of hydrocarbon. Full article

The steel manufacturing industry is a major source of global air pollution, with sintering processes contributing over 70% of emissions, primarily carbon monoxide (CO), a significant uncontrolled pollutant. This study explores Mn-Cu bimetallic catalysts as a cost-effective and environmentally friendly alternative to noble metal-based systems, addressing the urgent need for efficient CO oxidation catalysts. Mn-Cu catalysts with different Mn/Cu molar ratios were synthesized via hydrothermal methods and systematically characterized using XRD, XPS, BET, H₂-TPR, etc., to assess their physicochemical properties and catalytic performance. The Mn₄Cu₁ catalyst demonstrated the highest CO oxidation activity, achieving complete conversion at 175 °C. This performance is attributed to its optimal Mn/Cu molar ratio, high specific surface area, abundant oxygen vacancies, and superior redox properties. The catalyst’s enhanced performance is further supported by its low reduction temperature and high Mn³⁺ and Cu⁺ content, which promote efficient electron transfer and oxygen activation. These findings highlight the crucial role of Mn/Cu molar ratios in optimizing catalytic performance and offer valuable insights for designing high-efficiency, low-cost catalysts to reduce CO emissions in industrial applications. Full article

Chronic obstructive pulmonary disease (COPD) is a prevalent respiratory disorder characterized by persistent airway inflammation and progressive airflow limitation, resulting in a significant global health burden and high mortality. This narrative review synthesizes the current evidence on the roles of leukocyte subtypes—including neutrophils, monocytes, lymphocytes, eosinophils, and basophils—in the pathogenesis and clinical management of COPD. Relevant original studies and reviews are included, providing data on leukocyte functions, associated biomarkers, and therapeutic implications. Neutrophils contribute to airway damage and remodeling by releasing proteases and reactive oxygen species, particularly in response to environmental exposure such as cigarette smoke or air pollution. Lymphocytes, especially CD8⁺ T cells, drive chronic inflammation and immune dysregulation. Monocytes differentiate into macrophages that promote airway fibrosis and persistent inflammation, further impairing lung function. Eosinophils, though classically linked to asthma, are now recognized for their role in eosinophilic COPD, where they are associated with an increased exacerbation risk and corticosteroid responsiveness. Basophils, though less studied, may influence airway inflammation through interactions with eosinophils and cytokine release. Understanding these immune cell dynamics provides insights into the heterogeneity of COPD and highlights potential targets for precision therapy. Tailored interventions based on inflammatory phenotypes may improve clinical outcomes and advance personalized treatment strategies. Full article

In an effort to accomplish the real-time acquisition of the laser ranging results of space debris during the daylight and enhance the observation success rate, this paper establishes a joint distribution model of noise and echo signals grounded on the intensity distribution law of the daylight background noise. Through an in-depth analysis of the measurement characteristics of single-photon detectors, a real-time recognition algorithm based on the disparity in statistical distribution is put forward. This algorithm partitions the observation data into intervals of equal length. It then employs the goodness-of-fit test of the geometric distribution to ascertain the data distribution law. Subsequently, it locates the interval in which the echo signal resides by analyzing the contribution degree of the chi-square statistic. The experimental outcomes indicate that under the circumstances of a laser frequency of 400 Hz and a background noise photon rate of 2 × 10⁷ photons per second, the algorithm is capable of achieving real-time recognition of the echo interval for an intensity of 0.09 echo photons per single pulse within 1 s. This breakthrough resolves the critical challenge of daylight echo discrimination in high-noise environments. This method overcomes the constraints of the traditional signal intensity threshold and offers a novel technical approach for the tracking and precise orbit determination of space debris in a low signal-to-noise ratio environment. Full article

Background and Objectives: Robotic exoskeletons show potential in PD gait rehabilitation. But the optimal assistive force and its equivalence to clinical gold standard assessments are unclear. This study aims to explore the clinical equivalence of the lower limb exoskeleton in evaluating PD patients’ gait disorders and find the best assistive force for clinical use. Methods: In this prospective controlled trial, 60 PD patients (Hoehn and Yahr stages 2–4) and 60 age-matched controls underwent quantitative gait analysis using a portable exoskeleton (Relink-ANK-1BM) at four assistive force levels (0 N, 40 N, 80 N, 120 N). Data from 57 patients and 57 controls were analyzed with GraphPad Prism 10. Different statistical tests were used based on data distribution. Results: ROC analysis showed that exoskeleton-measured velocity had the strongest power to distinguish PD patients from controls (AUC = 0.9198, p < 0.001). Other parameters also had high reliability and validity. There was a strong positive correlation between UPDRS-III lower extremity sub-score changes and gait velocity changes in PD patients (r = 0.8564, p < 0.001). The 80 N assistive force led to the best gait rehabilitation, with a 58% increase in gait velocity compared to unassisted walking (p < 0.001). Conclusions: 80 N is the optimal assistive threshold for PD gait rehabilitation. The wearable lower limb exoskeleton can be an objective alternative biomarker to UPDRS-III, enabling personalized home-based rehabilitation. Full article