Search Results (2,385)

Thailand’s goal of becoming carbon-neutral by 2050 and producing no emissions by 2065 requires their reliable renewable energy means to be expanded upon quickly. Biomass is an important resource for this. Even though there are many biomass power plants in Thailand, the further expansion of biomass energy is being held back by several problems, such as unclear rules and feedstock instability, which is worsening because of climate change. This study formulates an investor-focused Analytic Hierarchy Process (AHP) framework to rank the policy instruments that bolstered investor confidence in 2024–2025. Expert opinions were gathered through a Delphi-validated process and examined via eigenvector-based weighting and consistency checks. The findings indicate that law and regulatory policy is the most successful intervention (0.31), followed by economic incentives (0.24) and R&D support (0.18). Sub-criteria analysis reveals that regulatory clarity and the stability of feedstock supply—aggravated by climate-induced yield risks—are the predominant factors influencing investment decisions. Sensitivity analysis substantiates this ranking, indicating that fundamental regulatory reform is necessary to realize the full efficacy of financial or technological incentives. These results provide policymakers with a clear method to make decisions about how to align biomass roadmaps with the needs of the private sector. This will help emerging economies make a smooth and long-lasting transition to clean energy. Full article

Collagen and gelatin are promising cell scaffold materials, but their structural instability under physiological conditions necessitates crosslinking treatment. This study evaluated UV crosslinking (254 nm, 0–180 min) as a non-toxic alternative to chemical crosslinking for collagen sheets (CS) and gelatin sheets (GS). Physicochemical properties were characterized by gel fraction analysis, atomic force microscopy (AFM) in PBS, and Fourier transform infrared spectroscopy (FT-IR), while NIH-3T3 fibroblast proliferation was evaluated by CCK-8 assay. UV crosslinking dramatically improved GS water resistance (gel fraction increased from 22% to 80% at 60 min) while maintaining smooth nanoscale surfaces (R_q: 1–4 nm), whereas CS exhibited inherent high stability (90% gel fraction without UV treatment, reaching 95–98% after irradiation). Both materials achieved maximum elastic modulus at 60 min (CS: 2.0 MPa; GS: 1.5 MPa). UV irradiation significantly enhanced cell proliferation on both substrates compared to untreated controls (p < 0.05). CS showed consistently high proliferation across all UV-treated conditions (day 3 absorbance: ~2.5–2.7), while GS exhibited progressive increases reaching a maximum at 180 min (absorbance: ~2.9). The continued GS enhancement despite slightly decreased elastic modulus suggests that chemical factors, possibly related to RGD motif accessibility, contribute beyond mechanical optimization. UV crosslinking effectively establishes structural stability essential for cell scaffold function, with both materials representing effective, biocompatible scaffolds for tissue engineering applications. Full article

To address the collaborative optimization of efficiency, stability, and energy consumption in container part-handling operations of material-handling robots, this paper proposes a multi-objective trajectory-planning method. First, the kinematic and dynamic models of the robot are established based on the improved D-H parameter method and Lagrange method, with the coordinates of key interpolation points and joint angles in handling operations clarified. Subsequently, the 3-5-3 hybrid polynomial interpolation method is adopted to generate the trajectory. Optimizing the objectives of minimum time, minimum jerk, and minimum energy consumption, an improved particle swarm optimization (IPSO) algorithm dynamically adjusts the inertia weight and learning factor for trajectory optimization. The results show that the convergence speed of the IPSO algorithm increases by 39.6% on average, and the fitness value reduces by 12.7% on average. Experimental validation of joint trajectory optimization demonstrated maximum positional errors of approximately 0.0049 rad, 0.0005 rad, 0.005 rad, and 0.0049 rad for the four joints, with the experimental trajectory closely matching the planned trajectory. Finally, the effectiveness of the scheme is verified by MATLAB 2019 and Adams simulation. Under the time–jerk–energy optimization strategy, the joint trajectory is continuous and smooth, with the peak jerk reduced by 30–40% and the peak torque reduced by 5–10%. The comprehensive performance is superior to the single-objective and dual-objective optimization strategies. This research provides technical support for the efficient and stable operation of the handling robot and provides a reference for the trajectory planning of similar robots. Full article

Background: Vascular leiomyosarcoma (LMS) is an exceptionally rare and aggressive soft tissue sarcoma arising from the smooth muscle cells of the vascular wall. They account for approximately 0.5–2% of adult soft-tissue sarcomas and are the most frequent primary malignancy of vascular origin. Among venous sites, the inferior vena cava (IVC) is the most frequently involved, accounting for more than half of reported vascular LMS cases, with rarer occurrences in peripheral veins, including the internal saphenous vein and the external iliac vein. Case Presentation: We report a case series comprising two distinct presentations of vascular LMS involving the internal saphenous vein and the inferior vena cava, respectively. Each case highlights unique clinical manifestations, radiologic features, histopathologic diagnosis, and therapeutic challenges inherent to the involved vascular territory. Surgical resection with clear margins was the primary treatment modality, complemented by adjuvant therapies tailored according to tumor grade and extent. Literature Review: An updated literature review contextualizes these findings, detailing epidemiology, diagnostic challenges, prognostic factors, and current management approaches. It emphasizes the rarity of leiomyosarcomas originating from major venous pathways and highlights variability in clinical presentation, tumor size, growth patterns, and outcomes. Achieving complete surgical removal with negative margins continues to be the primary treatment goal and the most significant prognostic factor. Conclusions: Given the paucity of cases, our series contributes valuable insights into the clinical spectrum and multidisciplinary approach necessary for optimal outcomes in vascular LMS. Early recognition and aggressive treatment remain paramount to improving survival in this rare malignancy. Full article

Infrared small target detection under complex backgrounds remains challenging due to the extremely small target size and low contrast with the surrounding background. These factors make contour information difficult to extract and often cause target features to attenuate or disappear during deep feature learning. To address these issues, this paper proposes a Gradient-Compensation-based Feature Learning Network (GCFLNet). GCFLNet adopts a multi-module collaborative design to enhance feature representation and fusion. First, an Edge Enhancement Module (EEM) is introduced to accurately capture fine-grained edge information of infrared small targets while suppressing background noise through smoothing operations. This provides reliable structural cues for subsequent feature extraction. Second, the extracted edge features are embedded into a Global–Local Feature Interaction (GLFI) module, which is inspired by self-attention mechanisms with dilated convolutions to strengthen global semantic dependencies and local detail representation, enabling effective enhancement of target features. In addition, a Multi-Scale Information Compensation (MSIC) module is designed to exploit the complementary characteristics of multi-scale features across spatial and channel dimensions, guiding efficient fusion of high-level and low-level information. Experimental results on the NUDT and IRSTD-1K datasets demonstrate that GCFLNet outperforms existing state-of-the-art methods, achieving higher detection accuracy and robustness for infrared small targets in complex backgrounds. Full article

To effectively prevent and control coal spontaneous combustion, a novel heat-sensitive hydrogel for mine fire prevention and extinguishment was developed using hydroxypropyl methylcellulose (HPMC) and the organic flame-retardant, sodium alginate (SA). The hydrogel was prepared through single-factor variable control and material compounding. First, the optimal formulation of the hydrogel was determined using analytical instruments and techniques, including a viscometer, vacuum drying oven, and the inverted test tube method. Subsequently, its microstructural characteristics were examined using scanning electron microscopy (SEM) and infrared spectroscopy (FTIR). Finally, a fire suppression test platform was established to perform comparative experiments, verifying the hydrogel’s fire prevention, extinguishing, and cooling performance. Experimental results demonstrated that the optimal hydrogel formulation consists of 2.5 wt% HPMC and 0.3 wt% SA. At this ratio, the hydrogel exhibits excellent fluidity and water retention, ensuring prolonged coverage and wetting of coal surfaces. The gel undergoes a sol–gel phase transition at 58 °C, enabling it to fill voids, bind and reinforce coal particles, and reduce exposed surface area. After drying, the hydrogel forms a uniformly smooth surface capable of both coating the coal body and encapsulating individual coal particles. Following the hydrogel treatment, the coal sample retains its original functional groups, indicating that no chemical reactions occur during mixing. Compared with traditional inhibitors, the hydrogel demonstrates superior fire suppression performance, more effectively covering and encapsulating burning coal. It rapidly reduces the temperature to 28 °C by the cooling effect of water evaporation from the hydrogel, and it maintains thermal stability, achieving outstanding fire-extinguishing efficiency. Full article

Monitoring the freshness of Salmo salar within cold chain logistics is paramount for ensuring food safety. However, conventional physicochemical and microbiological assays are impeded by inherent limitations, including destructiveness and significant time latency, rendering them inadequate for the real-time, non-invasive inspection demands of modern industry. Here, we present a novel detection framework synergizing hyperspectral imaging (400–1000 nm) with the Transformer deep learning architecture. Through a rigorous comparative analysis of twelve preprocessing protocols and four feature wavelength selection algorithms (Lasso, Genetic Algorithm, Successive Projections Algorithm, and Random Frog), prediction models for Total Volatile Basic Nitrogen (TVB-N) and Total Viable Count (TVC) were established. Furthermore, the capacity of the Transformer to capture long-range spectral dependencies was systematically investigated. Experimental results demonstrate that the model integrating Savitzky-Golay (SG) smoothing with the Transformer yielded optimal performance across the full spectrum, achieving determination coefficients (R²) of 0.9716 and 0.9721 for the Prediction Sets of TVB-N and TVC, respectively. Following the extraction of 30 characteristic wavelengths via the Successive Projections Algorithm (SPA), the streamlined model retained exceptional predictive precision (R² ≥ 0.95) while enhancing computational efficiency by a factor of approximately six. This study validates the superiority of attention-mechanism-based deep learning algorithms in hyperspectral data analysis. These findings provide a theoretical foundation and technical underpinning for the development of cost-effective, high-efficiency portable multispectral sensors, thereby facilitating the intelligent transformation of the aquatic product supply chain. Full article

We develop a PDE and boundary integral framework for quaternion-valued fields on product domains $\Omega \subset \mathbb{H}\times \mathbb{H}$ governed by the mixed left/right Cauchy–Fueter system We identify the natural compatibility condition and prove local solvability with quantitative $H^1$ estimates, as well as global weak solvability on admissible products $U_x\times U_y$. Motivated by these estimates, we introduce domains of hyperholomorphy and hyper-conjugates for data that are harmonic in each factor (${\Delta }_{x}u={\Delta }_{y}u=0$), and we establish Carleman-type quantitative unique continuation tools (boundary blow-up, three-balls, and doubling), including a propagation-of-smallness principle across the two factors. On the potential-theoretic side, we construct a double boundary integral representation for biregular fields with kernel $K(\xi ,\eta ;x,y)=E(\xi -x)E(y-\eta )$, establish mapping and jump relations for the associated layer potentials on Lipschitz boundaries, and obtain a Fredholm boundary integral equation for the boundary density in the smooth admissible regime. Finally, we prove a constructive Runge approximation theorem on admissible products and outline a practical discretization workflow consistent with the analysis. Full article

Background: Mesenchymal stem cells (MSCs) exhibit a high capacity for differentiation, possess anti-inflammatory and proangiogenic properties, and stimulate the growth and proliferation of neighboring cells. MSCs are a promising tool in regenerative medicine. However, the molecular mechanisms underlying the properties of these cells are not yet fully understood. Gene expression in MSCs influences their characteristics and differentiation potential. Therefore, it is essential to investigate factors affecting gene expression as well as those activating signaling pathways, which will enable more effective and individualized applications of MSCs. In this study, we aimed to identify signaling pathways involved in gene expression in umbilical cord-derived MSCs (UC-MSCs) that may be altered by maternal diabetes and hypothyroidism during pregnancy. Methods: The research material consisted of UC-MSCs. Samples obtained from nine participants were analyzed. UC-MSCs were isolated and cultured, and RNA was extracted. The isolated RNA was used for microarray-based gene expression analysis. Subsequently, pathway enrichment analysis was performed to identify the signaling pathways involved. Results: In the diabetes group, 340 genes (0.71%) were upregulated, while 268 genes (0.56%) were downregulated compared with UC-MSCs from the control group. In the diabetes group, the most compact module was composed of proteins associated with WNT/planar cell polarity (WNT/PCP) signaling. The second module included genes related to smooth muscle activity. In the hypothyroidism group, an association was identified between the extracellular matrix organization pathways (GO:0030198) and the extracellular structure organization (GO:0043062) pathways. Moreover, in this group, increased expression of MMP1, MMP10, and GREM1 was observed. Conclusions: In summary, our study demonstrated the impact of diabetes and hypothyroidism on gene expression in UC-MSCs. We also observed the activation of distinct signaling pathways depending on the presence of these conditions. However, this work represents a preliminary screening, and the results should be validated by PCR in a larger cohort. Full article

We evaluated the contributions of ten intrinsic and extrinsic factors readily available from website data to individual home sale prices for three major U.S. cities using a P-spline generalized additive model (GAM). We identified the relative significance of each factor by evaluating the change in the adjusted $R^2$ value resulting from its removal from the model. We combined this with information from correlation matrices to identify the added predictive value of a factor. For these three cities, the tests revealed that living area and location (latitude, longitude) had the strongest impact on explained variance, and each factor independently added predictive value. Relative impacts of the other factors were city-dependent. We utilized this information to develop an improved GAM with superior concurvity values. The improved GAM required the use of linear orthogonalization of factors combined with smoothing functions based on tensor products of correlated factors. Full article

In complex, semi-structured orchard environments, mobile inspection robots often suffer from excessive turning points, low search efficiency, limited trajectory-tracking accuracy, and poor adaptability to dynamic obstacles. To address these issues, this study proposes an integrated autonomous navigation method that employs an improved A* algorithm for global path planning, a Fuzzy-Weighted Dynamic Window Approach (FW-DWA) for local path optimization, and a model predictive control (MPC)-based trajectory-tracking controller. First, a dynamic heuristic-weight adjustment strategy is introduced into the conventional A* algorithm, in which a correction factor adaptively tunes the heuristic weight; a two-stage node optimization procedure then removes hazardous and redundant nodes to improve path smoothness and safety. Second, the FW-DWA, grounded in fuzzy control theory, uses goal distance and obstacle distance to update the weights of the heading, clearance, and velocity evaluation functions in real time, thereby enhancing obstacle avoidance in dynamic environments. Finally, a discrete kinematic model is established to design the MPC Controller, which achieves high-precision tracking through receding-horizon optimization and feedback correction. Experiments conducted in real orchards demonstrate that the proposed method reduces path length by 5.79%, shortens planning time by 3.64%, and increases the minimum safety distance by 50%. Comparative results further show that the MPC Controller attains a mean position error of 0.032 m and a mean heading error of 3.14°, clearly outperforming a conventional Proportional–Integral–Derivative (PID) controller. These findings provide an effective solution for reliable autonomous navigation of orchard inspection robots and offer a valuable reference for smart agricultural robotics applications. Full article

The sphincter of Oddi (OS) is a small group of smooth muscles that plays a crucial role in the regulation of the flow of biliopancreatic secretions into the duodenal lumen. Its motility, including phasic contractions and relaxation, is under complex neurohumoral control. Organic or functional obstruction of the OS is an important factor in severe diseases, such as cholangitis and pancreatitis, as well as in functional disorders and recurrent abdominal pain. In this review, we summarize the function of the OS, its disorders, and their diagnostic methods and potential therapeutics. While organic diseases of the papilla often require invasive, mainly endoscopic, treatment, functional disorders should be managed with conservative, individualized treatment, and involve the patient and their family in decision-making. Full article

The rapid increase in electric vehicle (EV) adoption necessitates advanced charging infrastructures that are compact, efficient, and capable of bidirectional power flow for both vehicle-to-grid (V2G) and grid-to-vehicle (G2V) operation. Unlike traditional silicon and SiC-based chargers, this work introduces a Ga₂O₃-based bidirectional smart charging system integrated with a hybrid energy storage system to deliver superior performance. A coordinated control strategy is developed to regulate power sharing between a supercapacitor and a lithium-ion battery pack, thereby extending battery life, reducing current stress, and providing effective transient support. This hybrid system employs PI-based control and advanced modulation techniques to minimize current ripple, maintain the unity power factor, and ensure stable DC-link voltage regulation. MATLAB/Simulink simulation results demonstrate robust DC-link stability, smooth bidirectional power transfer, and very low total harmonic distortion. Comparative loss analysis shows that Ga₂O₃ MOSFETs offer significantly lower conduction and switching losses, enabling efficiencies up to 98% across the rated operating range. These results confirm that the proposed charger is highly suitable for next-generation EV infrastructures requiring high power density, reliable grid interfacing, and enhanced operational longevity. A hardware prototype was also developed and tested, with experimental results validating reliable grid-side performance and efficient energy sharing under typical operating conditions. Full article

In-stent restenosis (ISR) remains a clinically relevant cause of recurrent ischemia and repeat revascularization despite progressive refinements in stent design and implantation technique. Contemporary data indicate that restenosis-related target lesion revascularization (TLR) has declined from bare-metal stent (BMS) to early- and newer-generation drug-eluting stents (DESs), yet ISR continues to accumulate over long-term follow-up and is associated with worse outcomes than PCI for de novo lesions. Mechanistically, ISR is a time-dependent, heterogeneous process dominated early by neointimal hyperplasia—triggered by mechanical endothelial injury, delayed re-endothelialization, inflammation/oxidative stress, vascular smooth muscle cell phenotypic switching, and extracellular matrix deposition—and later by in-stent neoatherosclerosis, which may confer a higher-risk plaque substrate and overlap with thrombotic complications. Clinically, ISR frequently presents as an acute coronary syndrome (ACS) rather than stable symptoms, underscoring the prognostic relevance of prompt recognition and mechanism-informed management. Patient-level risk determinants repeatedly reported across cohorts include diabetes mellitus, chronic kidney disease, dyslipidemia, hypertension, and smoking, while lesion/procedural factors include small vessel caliber, long/complex or bifurcation lesions, multiple stent layers, and suboptimal stent expansion. Intravascular imaging (OCT/IVUS) is central to phenotyping ISR mechanisms (e.g., underexpansion, calcific neoatherosclerosis, stent fracture, homogeneous hyperplasia) and can guide targeted prevention and therapy. This review synthesizes current evidence on ISR biology and risk factors to support risk stratification, preventive strategies, and individualized management. Full article

Vascular remodeling is a characteristic pathological feature of various vascular diseases, including atherosclerosis, restenosis following vascular injury, hypertension, and aneurysms. The phenotypic switching of vascular smooth muscle cells (VSMCs) acts as a key driver of vascular remodeling. Under specific pathological stimuli, VSMCs rapidly transition from a contractile to a dedifferentiated phenotype, characterized by enhanced proliferation, migration, and secretory activity. Chromatin remodeling, a core mechanism of epigenetic regulation, orchestrates dynamic changes in chromatin structure and function through ATP-dependent remodeling complexes, histone-modifying enzymes, and DNA methyltransferases. These components collectively translate mechanical stress, metabolic disturbances, and inflammatory signals into reversible epigenetic modifications, thereby precisely regulating VSMC phenotypic switching. As such, chromatin remodeling represents a critical node for therapeutic intervention in vascular remodeling-related diseases. In recent years, a growing body of research has focused on the role of chromatin remodelers in regulating VSMC phenotype. In this review, we focus on the roles of ATP-dependent chromatin-remodeling factors and chromatin-modifying enzymes in the control of gene expression of VSMC phenotype switching. Firstly, we summarize the latest insights into chromatin remodeling and VSMC phenotypic switching, and then discuss recent advances in the identification and functional characterization of chromatin remodeling molecules, emphasizing their implications for VSMC behavior. Finally, we highlight the translational potential of targeting chromatin remodelers in the development of clinical therapies for vascular remodeling diseases and outline future directions for research in this field. Full article