Search Results (93)

Aberrant activation of innate immunity promotes the development of pulmonary arterial hypertension (PAH); however, the role of pattern recognition by Toll-like receptors (TLRs) within the pulmonary vasculature remains unclear. To consolidate knowledge (as of June 2025) about TLRs and their interactions with viruses in PAH and to identify therapeutic implications. A narrative review of experimental and clinical studies investigating ten TLRs in the context of the pulmonary vascular microenvironment and viral infections. Activation of TLR1/2, TLR4, TLR5/6, TLR7/8, and TLR9 converges on the MyD88–NF-κB/IL-6 axis, thereby enhancing endothelial-mesenchymal transition, smooth muscle proliferation, oxidative stress, thrombosis, and maladaptive inflammation, ultimately increasing pulmonary vascular resistance. Conversely, TLR3, through TRIF–IFN-I, preserves endothelial integrity and inhibits vascular remodeling; its downregulation correlates with PAH severity, and poly (I:C) restitution has been shown to improve hemodynamics and right ventricular function. HIV-1, EBV, HCV, endogenous retrovirus K, and SARS-CoV-2 infections modulate TLR circuits, either amplifying pro-remodeling cascades or attenuating protective pathways. The “TLR rheostat” is shaped by polymorphisms, ligand biochemistry, compartmentalization, and biomechanical forces. The balance between MyD88-dependent signaling and the TRIF–IFN-I axis determines the trajectory of PAH. Prospective therapeutic strategies may include TLR3 agonists, MyD88/NF-κB inhibitors, modulation of IL-6, and combination approaches integrating antiviral therapy with targeted immunomodulation in a precision approach. Full article

Runoff simulation and forecasting is of great significance for flood control, disaster mitigation, and water resource management. Alpine regions are characterized by complex terrain, diverse precipitation patterns, and strong snow-and-ice melt influences, making accurate runoff simulation particularly challenging yet crucial. To enhance predictive capability and model applicability, this study takes the Upper Jinsha River as a case study and comparatively evaluates the performance of a physics-based hydrological model BTOP and the data-driven deep learning models LSTM and BiLSTM in runoff simulation and short-term forecasting. The results indicate that for daily-scale runoff simulation, the LSTM and BiLSTM models demonstrated superior simulation capabilities, achieving Nash–Sutcliffe efficiency coefficients (NSE) of 0.82/0.81 (Zhimenda Station) and 0.87/0.86 (Gangtuo Station) during the test period. These values are significantly better than those of the BTOP model, which achieved a validation NSE of 0.57 at Zhimenda and 0.62 at Gangtuo. However, the hydrology-based structure of the BTOP model endowed it with greater stability in water balance and long-term simulation. In short-term forecasting (1–7 d), LSTM and BiLSTM performed comparably, with the bidirectional architecture of BiLSTM offering no significant advantage. When it came to flood events, the data-driven models excelled at capturing peak timing and hydrograph shape, whereas the physical BTOP model demonstrated superior stability in flood peak magnitude. However, forecasts from the data-driven models also lacked hydrological consistency between upstream and downstream stations. In conclusion, the present study confirms that deep learning models achieve superior accuracy in runoff simulation compared to the physics-based BTOP model and effectively capture key flood characteristics, establishing their value as a powerful tool for hydrological applications in alpine regions. Full article

The safety and reliability of modern power systems are increasingly challenged by adverse environmental conditions. (1) Background: Ice accumulation on power transmission lines is recognized as a severe threat to grid stability, as tower collapse, conductor breakage, and large-scale outages may be caused, thereby making accurate monitoring essential. (2) Methods: A rule-driven and interpretable stereo vision framework is proposed for three-dimensional (3D) detection and quantitative measurement of transmission line icing. The framework consists of three stages. First, adaptive preprocessing and segmentation are applied using multiscale Retinex with nonlinear color restoration, graph-based segmentation with structural constraints, and hybrid edge detection. Second, stereo feature extraction and matching are performed through entropy-based adaptive cropping, self-adaptive keypoint thresholding with circular descriptor analysis, and multi-level geometric validation. Third, 3D reconstruction is realized by fusing segmentation and stereo correspondences through triangulation with shape-constrained refinement, reaching millimeter-level accuracy. (3) Result: An accuracy of 98.35%, sensitivity of 91.63%, specificity of 99.42%, and precision of 96.03% were achieved in contour extraction, while a precision of 90%, recall of 82%, and an F1-score of 0.8594 with real-time efficiency (0.014–0.037 s) were obtained in stereo matching. Millimeter-level accuracy (Mean Absolute Error: 1.26 mm, Root Mean Square Error: 1.53 mm, Coefficient of Determination = 0.99) was further achieved in 3D reconstruction. (4) Conclusions: Superior accuracy, efficiency, and interpretability are demonstrated compared with two existing rule-based stereo vision methods (Method A: ROI Tracking and Geometric Validation Method and Method B: Rule-Based Segmentation with Adaptive Thresholding) that perform line icing identification and 3D reconstruction, highlighting the framework’s advantages under limited data conditions. The interpretability of the framework is ensured through rule-based operations and stepwise visual outputs, allowing each processing result, from segmentation to three-dimensional reconstruction, to be directly understood and verified by operators and engineers. This transparency facilitates practical deployment and informed decision making in real world grid monitoring systems. Full article

This study investigated the differences in key volatile organic compounds (VOCs) and flavor characteristics between essential oils (CEOs) from cinnamon bark and leaf. The volatile compounds of essential oils extracted from Cinnamomum cassia (Xijiang) bark (CEOP) and leaf (CEOY) by hydrodistillation were identified using GC-MS. The results showed that the extraction rates of CEOP and CEOY were 1.56% ± 0.02 and 0.83% ± 0.01 (n = 3), respectively. CEOP and CEOY consisted of 45 and 50 compounds, respectively. Odor activity value (OAV) analysis indicated that cinnamaldehyde (OAV = 935), α-caryophyllene (OAV = 77), and borneol (OAV = 4) played key roles in shaping the aroma of CEOP. Meanwhile, cinnamaldehyde (OAV = 849), nerolidol (OAV = 107), and α-caryophyllene (OAV = 58) were the major contributors to the flavor of CEOY. Electronic nose (E-nose) analysis revealed that sensors W5S and W1W were important for detecting aromatic compounds. Sensory evaluation showed that CEOs differed significantly in spicy, floral, and grassy aromas. These differences may be related to the concentrations of compounds such as cinnamaldehyde, α-caryophyllene, and nerolidol, as well as their interactions with olfactory receptors such as OR2W1 and OR1D2. Cinnamaldehyde activates TRPA1 and TRPV1 to elicit the perception of spiciness. Thus, CEOP may be suitable for baked goods, and CEOY may be suitable for ice cream and beverages. In conclusion, this study provides a theoretical foundation for the precise application of CEOs as condiments in food. Full article

This work presents a low-power photoplethysmography (PPG) readout integrated circuit (IC) that achieves a wide dynamic range (DR) through the direct integration of a voltage-controlled oscillator (VCO)-based quantizer into the photodiode driver. Conventional PPG readout circuits rely on either transimpedance amplifier (TIA) or light-to-digital converter (LDC) topologies, both of which require auxiliary DC suppression loops. These additional loops not only raise power consumption but also limit the achievable DR. The proposed design eliminates the need for such circuits by embedding a linear regulator with a mirroring scale calibrator and a time-domain quantizer. The quantizer provides first-order noise shaping, enabling accurate extraction of the AC PPG signal while the regulator directly handles the large DC current component. Post-layout simulations show that the proposed readout achieves a signal-to-noise-and-distortion ratio (SNDR) of 40.0 dB at 10 µA DC current while consuming only 0.80 µW from a 2.5 V supply. The circuit demonstrates excellent stability across process–voltage–temperature (PVT) corners and maintains high accuracy over a wide DC current range. These features, combined with a compact silicon area of 0.725 mm² using TSMC 250 nm bipolar–CMOS–DMOS (BCD) process, make the proposed IC an attractive candidate for next-generation wearable and biomedical sensing platforms. Full article

This work presents the design and fabrication of microstructured hydrophobic surfaces via fused filament fabrication (FFF) 3D printing with polylactic acid (PLA). Three geometric patterns—triangular-based prisms (TG), truncated pyramids (TP), and truncated ellipsoidal cones (CET)—were developed to modify the surface wettability. Morphological analysis revealed that the printer resolution limits the accurate reproduction of sharp CAD-defined features. Despite this, TG structures exhibited superhydrophobic behavior evaluated through static water contact angles (WCAs), reaching up to 164° along the structured direction and so representing a 100% increase relative to flat PLA surfaces (WCA = 82°). To improve print fidelity, TP and CET geometries with enlarged features were introduced, resulting in contact angles up to 128°, corresponding to a 56% increase in hydrophobicity. The truncated shapes enable the fabrication of the smallest features achievable via the FFF technique, while maintaining good resolution and obtaining higher contact angles. In addition, surface functionalization with fluoropolymer-coated SiO₂ nanoparticles, confirmed by SEM and Raman spectroscopy, led to a further slight enhancement in wettability up to 18% on the structured surfaces. These findings highlight the potential of FFF-based microstructuring, combined with surface treatments, for tailoring the wetting properties of 3D-printed polymeric parts with promising applications in self-cleaning, de-icing, and anti-wetting surfaces. Full article

Background/Objectives: This article reports pyrrolidine iminosugars of L-gulose absolute stereochemical configuration that are functionalised via N-alkylation to bear boronate ester and boronic acid pharmacophores. Inclusion of boron pharmacophores has been shown to reduce toxicity profiles of drugs and can expand the range of interactions between drugs and target enzymes. Methods: The synthetic development, detailed spectroscopic analysis, and biological investigation against glycosidase enzymes and cancer cell lines of these novel five-membered ring iminosugars are reported. Results: This family of iminosugars displays selective, moderate-to-weak inhibition (IC₅₀s = 133–501 μM) of β-d-galactosidase (bovine liver) and emerging inhibition of β-d-glucosidases (almond) and (bovine liver). The boronic acid pharmacophore may be suitable for the management of lysosomal storage disorders to support the restoration of biological activity of mutant enzymes via the chaperone-mediated therapy approach. From a structure–activity perspective, the cancer screening revealed slight growth inhibition in a panel of cancer cell lines, with A2780 ovarian carcinoma cells showing the strongest response across all compounds. Beyond the growth inhibition capabilities, the real therapeutic potential of these borylated drugs lies in their switch-on/switch-off activation under BNCT radiotherapeutic conditions. Conclusions: This is an important novel family of drug leads capable of interacting with drug targets via intermolecular and intramolecular interactions, changing shape and electronics. Introduction of organic boron atoms to organic molecules presents significant synthetic and purification challenges, as well as analysis of the equilibria that arise in aqueous systems. We provide a methodology to achieve all this and introduce boron pharmacophores onto carbohydrate scaffolds in a systematic manner to facilitate a more widespread adoption of boron pharmacophores. Full article

Facing the pressure of green transformation, studying the relationship between government subsidies and the environmental performance of agricultural enterprises has significant theoretical value and practical significance for achieving sustainable agricultural development. Based on the micro data of 283 A-share listed agricultural enterprises in China from 2013 to 2023, this paper empirically analyzes the impact of government subsidies on the environmental performance of agricultural enterprises and its mechanism. The results show that there is an inverted U-shaped relationship between government subsidies and the environmental performance of agricultural enterprises, that is, when the government subsidies are within a certain scale, increasing government subsidies will have a positive impact on the environmental performance of agricultural enterprises. When the government subsidy reaches a certain scale, increasing the government subsidy will have a negative impact on the environmental performance of agricultural enterprises. External media attention (EMA) and internal control level (IC) play mediating roles in the impact of government subsidies on the environmental performance of agricultural enterprises. Heterogeneity analysis showed that for different types of subsidies, R&D subsidies and environmental protection subsidies had an inverted U-shaped impact on the environmental performance of agricultural enterprises. This study provides useful implications for improving methods of issuing government subsidies and enhancing the driving force of agricultural enterprises to carry out sustainable development actions. Full article

An accurate analysis of the dynamic process of ice melting in an optical fiber composite overhead ground wire (OPGW) is of great reference significance for the selection of an ice melting current and the formulation of an ice melting strategy. Existing analytical models for the dynamic process of DC ice melting in an OPGW ignore the gap convective heat transfer after the formation of the air gap between the ground wire and the ice layer, and lack the study of the dynamic process of the phase transition of the ice layer. To this end, a finite element model of the DC ice melting process of OPGW was established by introducing the mushy zone constant to consider the influence of the convective heat transfer in the gap, and at the same time, the apparent heat capacity method was used to simulate the changes of the physical property parameters of the melted ice layer. The dynamic process of the ice layer phase transition and OPGW temperature rise during ice melting are calculated, and the effects of the half-width of phase transition interval dT and the mushy zone constant A_m on the DC ice melting process are summarized and analyzed. The accuracy of the OPGW DC ice melting model is verified by conducting DC ice melting experiments. The results show that during the ice melting process, the gap convection heat transfer mainly affects the temperature distribution of the air gap between the ice layer and the OPGW as well as the location of the phase transition interface, and the width of the air gap at the same height below the OPGW increases by about 3 mm after considering the gap convection; the half-width of phase transition interval, dT, mainly affects the location of the phase transition interface and the temperature rise of the modeled heat source, OPGW, while the mushy zone constant, A_m, mainly affects the temperature distribution in the mushy zone, the air gap region. The elliptical phase transition cross-section formed by the OPGW DC ice melting experiment is consistent with the shape of the ice melting simulation model results, and the measured temperature rise curves of the OPGW during DC ice melting are in good agreement with the simulation results, with a maximum difference of about 3.5 K in temperature and 10 min in ice melting time, but the overall trend is consistent, all showing as increasing first and then decreasing. Full article

Electrothermal anti-/de-icing systems are widely used in aircraft, and the structures of these systems generally consist of multiple layers laminated together. In service, laminated structures are prone to structural deformation and delamination, which can significantly affect heat conduction. Therefore, it is essential to study the temperature field of these electrically heated anti-icing structures during operation and analyse the impact of delamination damage on the temperature distribution. In this thesis, a dynamic multiphysical field study of an electric heating anti-icing structure is conducted using a thermal expansion layer-by-layer/3D solid element method. By studying the electric heating process of composite plates experiencing pre-positioned delamination, the thermal expansion layer-by-layer/3D solid element method considers the thermal convection boundary conditions as well as a constant heat source. In addition, to considering the influences of the geometric shape and delamination damage, we apply the thermal expansion layer-by-layer/3D solid element method to the electric heating anti-icing process of aerofoil structures using a coordinate transformation matrix. The calculations show that when delamination damage is located above the heating layer, the maximum temperature of the structure reaches 450 °C at 50 s, which severely affects the normal functioning of the structure. Additionally, the surface temperature of the anti-icing system decreases to the ambient temperature at the delamination. In contrast, delamination damage located below the heating layer has a minimal effect on the surface temperature distribution. Moreover, the damage caused by multiple types of damage is greater than that caused by a single type of damage. Full article

Untapped bioactive compounds from microbial endophytes offer a promising solution to counter antimicrobial and chemotherapeutic drug resistance when complexed as silver nanoparticles (AgNPs). AgNPs were biosynthesized using cell-free supernatants from endophytic Streptomyces sp. KE4D and Bacillus safensis KE4K isolated from the Kenyan medicinal plant Teclea nobilis, following fermentation in three different media. Bacterial extracts were analyzed using gas chromatography–mass spectrometry. AgNPs were characterized using Fourier-transform infrared spectroscopy and high-resolution transmission electron microscopy. Antimicrobial activity was assessed using agar well diffusion assays, and quorum sensing inhibition (QSI) was investigated using Chromobacterium violaceum. Anti-cancer potential was evaluated against breast (MCF-7) and prostate cancer (DU-145) cell lines using MTT assays. AgNPs were 5–55 nm in size, with KE4D AgNPs being spherical and KE4K AgNPs exhibiting various shapes. Cyclopropane acetic acids and fatty acids were identified as possible capping agents. Medium-dependent antimicrobial activity was observed, with medium Mannitol and medium 5294 AgNPs displaying stronger activity, particularly against Gram-negative indicators. KE4D medium 5294 AgNPs demonstrated 85.12% violacein inhibition at 140 µg/mL and better QSI activity, whilst KE4K AgNPs were better antimicrobials. The AgNPs IC₅₀ values were <3.5 µg/mL for MCF-7 and <2.5 µg/mL for DU-145 cells. The bioactivity of biosynthesized AgNPs is influenced by the bacterial isolate and fermentation medium, suggesting that AgNP synthesis can be tailored for specific bioactivity. Full article

A new radio frequency (RF) probe using pogo pin tips for integrated chip (IC) measurement up to 50 GHz is proposed. It offers high durability due to the pogo pins and meets three key design criteria for general IC measurement: (1) a 45° tilted shape with a 70 μm tip protrusion for easy microscope inspection, (2) linear pogo pin alignment for commercial chip pad contact, and (3) a 250 μm pitch compatible with standard IC pad pitches. This design is distinct from traditional pogo pin probe cards which place pogo pins in vertical form, in a diagonal arrangement, and at wide intervals. The probe exhibits a low insertion loss of 1.6 dB at 45 GHz. A printed circuit board (PCB)-based calibration standard for the calibration of the designed probe is constructed, which is adjusted to inductance and capacitance values using a simulation to form the Vector Network Analyzer (VNA) calibration set. The measurements of a commercial amplifier IC using this probe show a nearly identical performance to commercial RF probes, confirming its accuracy and reliability. Full article

Diplotaxis muralis (L.) DC (Brassicaceae) is an edible plant commonly used in Mediterranean diets. This study investigates its nutritional composition, secondary metabolites, and antioxidant activity. The results show that this plant is rich in fibre and essential minerals. Analysis of amino acids shows a diverse profile, with glutamic acid and aspartic acid being the most abundant. Regarding fatty acids, α-linolenic acid was identified as predominant. Importantly, levels of toxic metals such as cadmium, lead, and mercury were found to be within established safety limits, confirming the plant’s suitability for consumption. A leaf decoction using 80% methanol exhibited the highest concentrations of total phenolic compounds (68.36 mg eq. gallic acid g⁻¹), total flavonoids (3.50 mg eq. quercetin g⁻¹), and antioxidant activity (IC₅₀ of 78.87 µg mL⁻¹ for ABTS, 392.95 µg mL⁻¹ for DPPH, and a FRAP value of 731.20 µmol Fe(II) g⁻¹). HPLC-PDA-ESI-MSⁿ characterization identified flavonols as the main polyphenols. Additionally, several glucosinolates were identified. These compounds, along with their hydrolysis products, not only contribute to the health benefits of D. muralis, but also impart its distinctive pungent and spicy notes, playing a crucial role in shaping its unique sensory profile. These findings highlight the contribution of phenolic compounds and glucosinolates to the health benefits of D. muralis, reinforcing its potential as a promising plant for the development of new functional foods. Full article

The habits of cloud particles are a significant factor impacting microphysical processes in clouds. The accurate identification of cloud particle shapes within clouds is a fundamental requirement for calculating various cloud microphysical parameters. In this study, we established a cloud particle image dataset encompassing nine distinct habit categories, totaling 8100 images. These images were captured using three probes with varying resolutions: the Cloud Particle Imager (CPI), the Two-Dimensional Stereo Probe (2D-S), and the High-Volume Precipitation Spectrometer (HVPS). Furthermore, this study performs a comparative analysis of ten different transfer learning (TL) models based on this dataset. It was found that the VGG-16 model exhibits the highest classification accuracy, reaching 97.90%. This model also demonstrates the highest recall, precision, and F1 measure. The results indicate that the VGG-16 model can reliably classify the shapes of ice crystal particles measured by both line scan imagers (2D-S, HVPS) and an area scan imager (CPI). Full article

This study presents an experimental investigation for the galloping performance of the transmission line system with rime under wind excitation. A full aeroelastic model wind-tunnel test is conducted to investigate the dynamic response of a two-bundled transmission line system with rime under different conditions. The time histories of the displacement of the conductor and the acceleration of the tower are measured in detail to analyze the characteristic of the wind-induced response. A comprehensive parametric experiment is performed to explore the effects of wind speed, wind direction, the number of conductor spans and the coupling between the conductor and the tower on the galloping performance of the transmission line system with rime. The results showed that the wind speed, wind direction and the number of conductor spans have significant influence on the galloping performance of conductor. The zero-degree wind direction is the most dangerous direction for the conductor. The multi-span conductor has different galloping initiation wind speed and vibration characteristics compared to the single-span conductor. The coupling effect between the conductor and the tower has trivial influence on the response of tower. This study uses 3D-printing models to simulate the aerodynamic shape of ice-covered wires with different thicknesses for wind-tunnel tests and obtains the influence of a series of parameters on the galloping vibration of transmission tower line systems. Full article