Search Results (407)

(1) Chronic heart failure (CHF) is a typical component of the polymorbid profile of an elderly patient. The aim of this systematic review was to search for data from pharmacokinetic (PK) studies of any drugs in patients with CHF to systematize information on changes in PK parameters depending on the physicochemical properties (PCPs) of the drug and route of its administration. (2) A systematic review of PK studies in patients with CHF was performed using Elibrary.ru, United States National Library of Medicine (PubMed), China National Knowledge Infrastructure (CNKI), and Directory of Open Access Journals (DOAJ). The final number of included articles was 106. A descriptive and correlation analysis of PK data and PCPs of drugs included in the study was carried out. Inclusion criteria: PK study, available PK parameters, demographic data, and diagnosed CHF. Risk of bias was assessed using ROBINS-I. (3) Evaluation of correlations between PCPs of drugs and their PK revealed a link between (i) plasma protein binding (PPB) and volume of distribution for lipophilic drugs; (ii) PCPs, half-life, and clearance for drugs with high PPB; and (iii) PPB and clearance for hydrophilic and amphiphilic drugs. (4) Hypoalbuminemia associated with CHF may lead to an increased volume of distribution of lipophilic drugs; lipophilic drugs used in CHF patients may be associated with prolongation of the half-life period and reduction in clearance; highly protein-bound drugs may manifest with reduced clearance. PK characteristics identified in this review should guide modifications to dosing regimens in CHF patients receiving medications from different groups. Full article

This work provides a systematic evaluation of the performance and regulated emissions of binary n-pentanol–diesel blends under steady-state conditions, thereby clarifying condition-dependent efficiency–emission trade-offs across multiple loads and speeds. A single-cylinder, air-cooled diesel engine was operated at two speeds (1700 and 2700 rpm) and four brake mean effective pressure (BMEP) levels (0.25–0.49 MPa) using commercial diesel (D100) and three n-pentanol–diesel blends at volume ratios of 10%, 30%, and 50% (designated D90P10, D70P30, and D50P50, respectively). Brake thermal efficiency (BTE), brake specific energy consumption (BSEC), and brake specific fuel consumption (BSFC) were measured alongside exhaust emissions of nitrogen oxides (NO_x), carbon monoxide (CO), hydrocarbon (HC), carbon dioxide (CO₂), and smoke opacity. The results show that due to a lower cetane number, high latent heat of vaporization, and reduced heating value, n-pentanol blends incur efficiency and fuel consumption penalties at light to moderate loads. However, these disadvantages diminish or reverse at high loads and speeds: D50P50 surpasses D100 in BTE and matches or improves BSEC and BSFC at 2700 rpm and 0.49 MPa. Emission data reveal that the blend’s fuel-bound oxygen and enhanced mixing provide up to 16% NO_x reduction; 35% and 45% reductions in CO and HC, respectively; and a 74% reduction in smoke opacity under demanding conditions, while CO₂ per unit work output aligns with or falls below D100 at high load. These findings demonstrate that optimized n-pentanol–diesel blends can simultaneously improve efficiency and mitigate emissions, offering a practical pathway for low-carbon diesel engines. Full article

Electrochemical energy storage technology, primarily lithium-ion batteries, has been widely applied in large-scale energy storage systems. However, differences in assembly structures, manufacturing processes, and operating environments introduce parameter inconsistencies among cells within a pack, producing complex, high-volume datasets with redundant and fragmented charge–discharge records that hinder efficient and accurate system monitoring. To address this challenge, we propose a hybrid ASW-UKF-TRF framework for the classification and compression of battery data collected from energy storage power stations. First, an adaptive sliding-window Unscented Kalman Filter (ASW-UKF) performs online data cleaning, imputation, and smoothing to ensure temporal consistency and recover missing/corrupted samples. Second, a temporally aware TRF segments the time series and applies an importance-weighted, multi-level compression that formally prioritizes diagnostically relevant features while compressing low-information segments. The novelty of this work lies in combining deployment-oriented engineering robustness with methodological innovation: the ASW-UKF provides context-aware, online consistency restoration, while the TRF compression formalizes diagnostic value in its retention objective. This hybrid design preserves transient fault signatures that are frequently removed by conventional smoothing or generic compressors, while also bounding computational overhead to enable online deployment. Experiments on real operational station data demonstrate classification accuracy above 95% and an overall data volume reduction in more than 60%, indicating that the proposed pipeline achieves substantial gains in monitoring reliability and storage efficiency compared to standard denoising-plus-generic-compression baselines. The result is a practical, scalable workflow that bridges algorithmic advances and engineering requirements for large-scale battery energy storage monitoring. Full article

The experimental study has been carried out using advanced computer vision methods in order to visualize the moment of excitation and further propagation of a non stationary isotropic domain in a hybrid aligned nematic (HAN) microsized volume under the effect of a laser beam focused on a bounding liquid crystal surface. It has been shown that, when the laser power exceeds a certain threshold value, in bulk of the HAN microvolume, an isotropic circular domain is formed. We also observed a structure of alternating concentric rings around the isotropic circular region, which increases with distance from the center of the isotropic domain. The formation of a sequence of rings in a polarizing microscopic image indicates the formation of a complex topology of the director field in the HAN cell under study. The following evolution of the texture can be represented by two modes. Firstly, the “fast” heating mode, which is responsible for the formation and explosive expansion of an isotropic zone in bulk of the HAN microvolume with characteristic time ${\tau }_1$ due to a laser spot heating on the upper indium tin oxide (ITO) layer. Secondly, the “slow” heating mode, when an isotropic zone and concentric rings slowly expand with characteristic time ${\tau }_2$ mainly due to the finite thermoconductivity of ITO layer. When the laser power significantly exceeds the threshold value, damped oscillations of the isotropic domain are observed. We also introduced the metrics that allows quantitatively estimate the behavior of texture observed. The results obtained form an experimental basis for further investigation of thermomechanical force appearing in the LC system with coupled gradients of temperature and director fields. Full article

The Central Mindoro Fault (CMF) is a major active oblique, sinistral strike-slip fault within the Philippine archipelago that accommodates the oblique convergence between the Philippine Sea Plate (PSP) and the Sunda Plate (SP). This study focused on assessing the spatial distribution of relative uplift rates along the CMF by calculating multiple geomorphic indices (elongation ratio, volume-to-area-ratio, valley floor width-to-height ratio, hypsometric integral, and normalized steepness index) and interpreting these values in the context of any along-strike variations in geology and climate, as well as the context of the CMF’s kinematics. We observed 2 characteristics of spatial distributions of relative uplift rates: (1) at least 20–30 km-long high uplift rate sections in the northwestern end of the CMF-bound mountain range (CMF segment I), and (2) at most, CMF-wide moderate to high uplift rates. This trend matches the geomorphic-based cumulative fault offset measurements distribution, possibly indicating consistent kinematics and an overall nearly-uniform stress-field since at least the Pleistocene. Based on the spatial distribution of areas with high relative uplift rates highlighted by this study, future efforts to assess the CMF’s seismogenic capability should focus on segments I and III. Full article

Seasonal temperature variations significantly impact biological wastewater treatment performance, particularly affecting extracellular polymeric substance (EPS) composition and sludge settling characteristics in activated sludge systems. This study investigated the temperature-induced EPS response mechanisms and their effects on nitrogen removal efficiency in a full-scale modified Bardenpho wastewater treatment plant, combined with laboratory-scale evaluation of EPS-optimizing microbial agents for performance enhancement. Nine-month seasonal monitoring revealed that when the wastewater temperature dropped below 15 °C, the total nitrogen (TN) removal efficiency decreased from 86.5% to 80.6%, with a trend of significantly increasing polysaccharides (PS) in dissolved organic matter (DOM) and loosely-bound EPS (LB-EPS) and markedly decreasing tightly-bound EPS (TB-EPS). During the low-temperature periods, when the sludge volume index (SVI) exceeded 150 mL/g, deteriorated settling performance could primarily be attributed to the reduced TB-EPS content and increased LB-EPS accumulation. Microbial community analysis showed that EPS secretion-promoting genera of Trichococcus, Terrimonas, and Defluviimonas increased during the temperature recovery phase rather than initial temperature decline phase. Laboratory-scale experiments demonstrated that EPS-optimizing microbial agents dominated by Mesorhizobium (54.2%) effectively reduced protein (PN) and PS contents in LB-EPS by 70.2% and 54.5%, respectively, while maintaining stable nutrient removal efficiency. These findings provide mechanistic insights into temperature–EPS interactions and offer practical technology for improving winter operation of biological wastewater treatment systems. Full article

This study employed quarterly data spanning from 2005 to 2024 to investigate the factors affecting China’s tea exports to Malaysia using demand theory. The Autoregressive Distributed Lag (ARDL) approach and Granger causality test were applied to examine the long-run and short-run impacts of key variables, including the prices of China’s tea and coffee imported by Malaysia, Malaysia’s GDP, Malaysia’s tea production, and the international oil price. The ARDL bounds testing confirmed the existence of a long-run equilibrium among these variables. The empirical findings revealed that an increase in the price of China’s tea significantly reduced export volumes, whereas Malaysia’s GDP exerted a strong positive influence. The price of coffee exhibited a significantly negative effect, suggesting an unconventional substitution relationship with tea. Both Malaysia’s domestic tea production and the international oil price imposed downward pressures on China’s tea exports. Furthermore, the Granger causality analysis indicated that the price of China’s tea, the price of coffee, and Malaysia’s GDP all exerted short-run effects on China’s tea exports to Malaysia. These findings contribute to the export demand literature and offer implications for policies aiming to enhance bilateral tea trade between China and Malaysia. Full article

Agricultural trade not only facilitates the exchange of final products but also leads to the indirect transfer of arable land resources involved in their production processes across countries. These indirect flows are commonly referred to in the literature as virtual land flows or virtual land trade. An in-depth understanding of the factors influencing virtual land flows is crucial for both the management of these flows and the sustainable and efficient allocation of limited arable land resources on a global scale. The objective of this study is to identify the key determinants that influence virtual land flows in Türkiye’s trade of plant-based agricultural products. To achieve this, the virtual land trade balance for Türkiye was computed by estimating the import and export volumes of virtual land from 1986 to 2019, based on crop, year, and country-specific yield values. Subsequently, the relationship between Türkiye’s virtual land trade balance and macroeconomic and environmental variables—such as Gross Domestic Product (GDP), the real effective exchange rate, annual total precipitation, per capita arable land, and fertilizer usage—was investigated using the ARDL bounds testing approach. The findings of this study indicate that the most significant factors influencing Türkiye’s virtual land flows are per capita arable land endowment and fertilizer usage. This result highlights the strong relationship between virtual land flows and variables related to productivity and natural resource endowment, while also emphasizing the importance of integrating sustainability considerations and environmental impacts into contemporary agricultural policy frameworks. Elucidating the dynamics of virtual land trade is a pivotal step toward ensuring the long-term sustainability of international agricultural trade, as well as the equitable and efficient allocation of arable land resources. Furthermore, it represents a fundamental strategy for global agricultural production, offering critical insights for shaping future agricultural policy and practice at the global level. Full article

Municipal sewage sludge represents a significant environmental challenge due to its large-scale production and limited disposal options. Pyrolysis, a thermal decomposition process, offers a promising approach for converting sewage sludge into biochar, a carbon-rich material with diverse environmental applications. Sewage sludge-derived biochars were prepared at pyrolysis temperatures of 300 °C, 500 °C, 700 °C, and 900 °C (denoted as B300 to B900) and evaluated for their structural, adsorption, and catalytic performance. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), Brunauer-Emmett-Teller (BET), and energy dispersive X-ray spectrometry (EDS) analyses revealed a distinct temperature-dependent morphological evolution and mineral exposure. The B900 biochar exhibited a BET surface area of 83.8 m²/g and the highest pore volume of 0.101 cm³/g, indicating a well-developed mesoporous structure. In catalytic degradation tests using 20 mg/L persulfate and 500 mg/L B900, rapid oxidation was observed, achieving 91% methylene blue (MB) degradation in 30 min, highlighting its role in activating persulfate via surface-bound Fe and Al species. Optimization studies confirmed that MB removal efficiency was highest at 500 mg/L biochar and 40 mg/L persulfate, and the system was not significantly affected by the tap and synthetic wastewater matrices. This work demonstrates that biochar obtained from sewage sludge can serve as an eco-friendly and multifunctional material for resource recovery and environmental cleanup. Full article

Most metal plates are orthorhombic aggregates of cubic crystallites. First, we discuss the representations of the stress tensor, the strain tensor, the elasticity tensor, and the rotation tensor under the Kelvin notation. Then, we give the decomposition of determining the material constants and the mesostructure tensors on the metal plate of cubic crystallites. Under the Voigt model and the Reuss model, we derive the volume average stiffness tensor and the volume average flexibility tensor’s inverse, respectively, of cubic crystallites based on the decomposition. The elasticity tensors of the Voigt model and the Reuss model are upper and lower bounds of the effective elasticity tensor, respectively. We make use of an FEM example to check the decomposition of the elasticity tensor on the material constants and the mesostructures. The results of our decomposition are consistent with the FEM simulation’s results. Full article

Detection of defects on steel surface is crucial for industrial quality control. To address the issues of structural complexity, high parameter volume, and poor real-time performance in current detection models, this study proposes a lightweight model based on an improved YOLOv11. The model first reconstructs the backbone network by introducing a Reversible Connected Multi-Column Network (RevCol) to effectively preserve multi-level feature information. Second, the lightweight FasterNet is embedded into the C3k2 module, utilizing Partial Convolution (PConv) to reduce computational overhead. Additionally, a Group Convolution-driven EfficientDetect head is designed to maintain high-performance feature extraction while minimizing consumption of computational resources. Finally, a novel WISEPIoU loss function is developed by integrating WISE-IoU and POWERFUL-IoU to accelerate the model convergence and optimize the accuracy of bounding box regression. The experiments on the NEU-DET dataset demonstrate that the improved model achieves a parameter reduction of 39.1% from the baseline and computational complexity of 49.2% reduction in comparison with the baseline, with an mAP@0.5 of 0.758 and real-time performance of 91 FPS. On the DeepPCB dataset, the model exhibits reduction of parameters and computations by 39.1% and 49.2%, respectively, with mAP@0.5 = 0.985 and real-time performance of 64 FPS. The study validates that the proposed lightweight framework effectively balances accuracy and efficiency, and proves to be a practical solution for real-time defect detection in resource-constrained environments. Full article

Whispering-gallery-mode (WGM) microresonators are amongst the most promising optical sensors for detecting bio-chemical targets. A number of laser interrogation methods have been proposed and demonstrated over the last decade, based on scattering and absorption losses or resonance splitting and shift, harnessing the high-quality factor and ultra-small volume of WGMs. Actually, regardless of the sensitivity enhancement, their practical sensing operation may be hampered by the complexity of coupling devices as well as the signalprocessing required to extract the WGM response. Here, we use a silica microsphere immersed in an aqueous environment and efficiently excite optical WGMs with a free-space visible laser, thus collecting the relevant information from the transmitted and back-scattered light without any optical coupler, fiber, or waveguide. We show that a 640-nm diode laser, actively frequency-locked on resonance, provides real-time, fast sensing of dielectric nanoparticles approaching the surface with direct analog readout. Thanks to our illumination scheme, the sensor can be kept in water and operate for days without degradation or loss of sensitivity. Diverse noise contributions are carefully considered and quantified in our system, showing a minimum detectable particle size below 1 nm essentially limited by the residual laser microcavity jitter. Further analysis reveals that the inherent laserfrequency instability in the short, -mid-term operation regime sets an ultimate bound of 0.3 nm. Based on this work, we envisage the possibility to extend our method in view of developing new viable approaches for detection of nanoplastics in natural water without resorting to complex chemical laboratory methods. Full article

Cancer remains one of the most pressing global health challenges, driving the need for innovative treatment strategies. Boron neutron capture therapy (BNCT) offers a highly selective approach to destroying cancer cells while sparing healthy tissues. To improve boron delivery, Fe₃O₄@Au nanoparticles were developed and functionalized with a boron-containing carborane compound. Fe₃O₄ nanoparticles were synthesized and covered by gold, followed by (3-Aminopropyl)triethoxysilane (APTES) modification to introduce amino groups for carborane immobilization. Comprehensive characterization using SEM, DLS, FTIR, EDX, Brunauer–Emmett–Teller (BET), and XRD confirmed successful functionalization at each stage. TEM confirmed the final structure and elemental composition of the nanoparticles. BET analysis revealed a surface area of 94.69 m²/g and a pore volume of 0.51 cm³/g after carborane loading. Initial release studies in PBS demonstrated the removal of only loosely bound carborane within 48 h, with FTIR confirming stable retention of the compound on the nanoparticle surface. The modified nanoparticles achieved a stable zeta potential of −20 mV. The particles showed low toxicity within a range of concentrations (0–300 μg Fe/mL) and were efficiently accumulated by U251MG cells. These results demonstrate the potential of the obtained nanoparticles to carry boron and gold for their possible application as a theranostic agent. Full article

In this study, a multi-objective shape optimization framework was established for photovoltaic-powered underwater vehicles (PUVs) to systematically investigate multidisciplinary coupled design methodologies. Specifically, a global sensitivity analysis was conducted to identify four critical design parameters with 24 h energy consumption and cabin volume serving as dual optimization objectives. An integrated automated optimization workflow was constructed by incorporating parametric modeling, computational fluid dynamics (CFD) simulations, and dynamic surrogate models. Additionally, a new phased hybrid adaptive lower confidence bound (PHA-LCB) infill criterion was designed under the consideration of error-driven mechanisms, improvement feedback loops, and iterative attenuation factors to develop high-precision dynamic surrogate models. Coupled with the NSGA-II multi-objective genetic algorithm, this framework generated Pareto-optimal front solutions possessing significant engineering value. Furthermore, an optimal design configuration was ultimately determined through multi-criteria decision analysis. Compared to the initial form, it generates an additional 1148.12 Wh of electrical energy within 24 h, with an 22.36% increase in sailing range and a 2.77% improvement in cabin volume capacity. The proposed closed-loop “modeling–simulation–optimization” framework realized multi-objective optimization of PUV shape parameters, providing methodological paradigms and technical foundations for the engineering design of next-generation autonomous underwater vehicles. Full article

Petroleum hydrocarbon (PH) contamination in groundwater necessitates sustainable remediation solutions. This study develops a novel co-encapsulated composite by embedding steel slag (SS) and sodium persulfate (SPS) within an ethyl cellulose (EC) matrix ((SS + SPS)/EC) for permeable reactive barrier applications. The EC matrix enables controlled release of SPS oxidant and gradual leaching of alkaline components (Ca²⁺/OH⁻) and Fe²⁺/Fe³⁺ activators from SS, synergistically sustaining radical generation while buffering pH extremes. Optimized at a 10:7 SS:SPS mass ratio, the composite achieves 66.3% PH removal via dual pathways: (1) sulfate radical (${\mathrm{S}\mathrm{O}}_4^{-}$•) oxidation from Fe²⁺-activated persulfate (S₂${\mathrm{O}}_8^{2-}$ + Fe²⁺→${\mathrm{S}\mathrm{O}}_4^{-}$• + ${\mathrm{S}\mathrm{O}}_4^{2-}$ + Fe³⁺), and (2) direct electron transfer by surface-bound Fe³⁺. In situ material evolution enhances functionality—nitrogen physisorption reveals a 156% increase in surface area and 476% pore volume expansion, facilitating contaminant transport while precipitating stable sulfate minerals (Na₂SO₄, Na₃Fe(SO₄)₃) within pores. Crucially, the composite maintains robust performance under groundwater-relevant conditions: 54% removal at 15 °C (attributed to pH-buffered activation) and >55% efficiency with common interfering anions (Cl⁻, ${\mathrm{H}\mathrm{C}\mathrm{O}}_3^{-}$, 50 mg·L⁻¹). This waste-derived design demonstrates a self-regulating system that concurrently addresses oxidant longevity (≥70 h), geochemical stability (pH 8.5→10.4), and low-temperature activity, establishing a promising strategy for sustainable groundwater remediation. Continuous-flow column validation (60 d, 5 mg·L⁻¹ gasoline) demonstrates sustained >80% removal efficiency and systematically stable effluent pH (9.8–10.2) via alkaline leaching. Full article