Search Results (651)

The COVID-19 pandemic exposed critical vulnerabilities in single-target antiviral strategies, highlighting the urgent need for multi-mechanism therapeutic approaches against emerging viral threats. Here, we present an integrated computational framework systematically evaluating natural fatty acids as potential dual ACE2 (Angiotension Converting Enzyme 2)-inflammatory modulators; compounds simultaneously disrupting SARS-CoV-2 viral entry through allosteric ACE2 binding while suppressing host inflammatory cascades; through allosteric binding mechanisms rather than conventional competitive inhibition. Using molecular docking across eight ACE2 regions, 100 ns molecular dynamics simulations, MM/PBSA free energy calculations, and multivariate statistical analysis (PCA/LDA), we computationally assessed nine naturally occurring fatty acids representing saturated, monounsaturated, and polyunsaturated classes. Hierarchical dynamics analysis identified three distinct binding regimes spanning fast (τ < 50 ns) to slow (τ > 150 ns) timescales, with unsaturated fatty acids demonstrating superior binding affinities (ΔG = −6.85 ± 0.27 kcal/mol vs. −6.65 ± 0.25 kcal/mol for saturated analogs, p = 0.002). Arachidonic acid achieved optimal SwissDock affinity (−7.28 kcal/mol), while oleic acid exhibited top-ranked predicted binding affinity within the computational hierarchy (ΔG_bind = −24.12 ± 7.42 kcal/mol), establishing relative prioritization for experimental validation rather than absolute affinity quantification. Energetic decomposition identified van der Waals interactions as primary binding drivers (65–80% contribution), complemented by hydrogen bonds as transient directional anchors. Comprehensive ADMET profiling predicted favorable safety profiles compared to synthetic antivirals, with ω-3 fatty acids showing minimal nephrotoxicity risks while maintaining excellent intestinal absorption (>91%). Multi-platform bioactivity analysis identified convergent anti-inflammatory mechanisms through eicosanoid pathway modulation and kinase inhibition. This computational investigation positions natural fatty acids as promising candidates for experimental validation in next-generation pandemic preparedness strategies, integrating potential therapeutic efficacy with sustainable sourcing. The framework is generalizable to fatty acids from diverse biological origins. Full article

Many emerging economies seek to lower carbon intensity while remaining heavily dependent on fossil fuels. This paper examines how sustainable finance, eco-innovation, and the energy mix shape Tunisia’s low-carbon transition. We use quarterly data for 2000–2023 and an econometric environmental-impact model that links carbon intensity to green finance, innovation, renewable and fossil energy, openness, income, and demographic factors. The results show that sustainable finance consistently reduces carbon intensity across all emission states, with stronger effects when emissions are high. The energy mix is crucial: a larger share of renewable energy lowers carbon intensity, while higher fossil energy use increases it and reinforces fossil carbon lock-in. Eco-innovation has its strongest mitigation effects in high-intensity situations, suggesting delayed effects linked to limited absorptive capacity and technology diffusion. Openness and demographic pressure tend to raise emissions through scale and consumption channels. Overall, the findings depict a finance-anchored but energy-constrained transition. They indicate that Tunisia and similar MENA economies can accelerate decarbonization by scaling credible sustainable finance instruments, speeding up renewable deployment, and strengthening the innovation and governance framework that supports green investment, innovation policy, and energy sector reform in semi-industrialized economies. Full article

Despite decades of structural and kinetic characterization, the full spectral molecular vibrations that accompany the catalysis in alkaline phosphatase (ALP) have remained largely unexplored. In this study, we combine in situ real-time attenuated total reflection Fourier transform infrared (ATR-FTIR) measurements over a large energy range to track the hydrolysis of p-nitrophenyl phosphate (PNPP) and inorganic phosphate (Pi) over a large range of enzyme concentrations. From the static spectra of the pure components (ALP, PNPP, PNP, Pi), we identify their characteristic vibrational frequencies and use them as reference points for the time-resolved spectra. The reaction reveals a monotonic growth of the inorganic-phosphate band at 1077 cm⁻¹. At the highest alkaline phosphatase concentration, we resolve two blue shifts in the nitro/aromatic region (1510 → 1518 cm⁻¹; 1494 → 1499 cm⁻¹), two red shifts in the fingerprint region (1345 → 1340 cm⁻¹; 1294 → 1290 cm⁻¹), and a splitting of the ~1592 cm⁻¹ band into 1595 and 1583 cm⁻¹. In conclusion, by anchoring the time-resolved spectra to the static spectra of individual constituents, we were able to resolve the infrared readout of the enzymatic reaction, offering a generalizable approach for FTIR-based tracking of catalytic processes. Full article

Maintaining the stability of the mine roadway is of paramount importance, as it is critical in ensuring the daily operational continuity, personnel safety, long-term economic viability, and sustainability of the entire mining operation. Significant instability can trigger serious disruptions—such as production stoppages, equipment damage, and severe safety incidents—which ultimately compromise the project’s financial returns and future prospects. Therefore, the proactive assessment and rigorous control of roadway stability constitute a foundational element of successful and sustainable resource extraction. In China, thick and extra-thick coal seams constitute over 44% of the total recoverable coal reserves. Consequently, their safe and efficient extraction is considered vital in guaranteeing energy security and enhancing the efficiency of resource utilization. The surrounding rock of gob-side roadways in typical coal seams is often fractured due to high ground stress, intensive mining disturbances, and overhanging goaf roofs. Consequently, asymmetric failure patterns such as bolt failure, steel belt tearing, anchor cable fracture, and shoulder corner convergence are common in these entries, which pose a serious threat to mine safety and sustainable mining operations. This deformation and failure process is associated with several parameters, including the coal seam thickness, mining technology, and surrounding rock properties, and can lead to engineering hazards such as roof subsidence, rib spalling, and floor heave. This study proposes countermeasures against asymmetric deformation affecting gob-side entries under intensive mining pressure during the fully mechanized caving of extra-thick coal seams. This research selects the 8110 working face of a representative coal mine as the case study. Through integrated field investigation and engineering analysis, the principal factors governing entry stability are identified, and effective control strategies are subsequently proposed. An elastic foundation beam model is developed, and the corresponding deflection differential equation is formulated. The deflection and stress distributions of the immediate roof beam are thereby determined. A systematic analysis of the asymmetric deformation mechanism and its principal influencing factors is conducted using the control variable method. A support approach employing a mechanical constant-resistance single prop (MCRSP) has been developed and validated through practical application. The findings demonstrate that the frequently observed asymmetric deformation in gob-side entries is primarily induced by the combined effect of the working face’s front abutment pressure and the lateral pressure originating from the neighboring goaf area. It is found that parameters including the immediate roof thickness, roadway span, and its peak stress have a significant influence on entry convergence. Under both primary and secondary mining conditions, the maximum subsidence shows an inverse relationship with the immediate roof thickness, while exhibiting a positive correlation with both the roadway span and the peak stress. Based on the theoretical analysis, an advanced support scheme, which centers on the application of an MCRSP, is designed. Field monitoring data confirm that the peak roof subsidence and two-side closure are successfully limited to 663 mm and 428 mm, respectively. This support method leads to a notable reduction in roof separation and surrounding rock deformation, thereby establishing a theoretical and technical foundation for the green and safe mining of deep extra-thick coal seams. Full article

Ocean internal waves occur in stably stratified seawater and play a crucial role in energy cascade, material transport, and military activities. However, the complex and irregular spatial patterns of internal waves pose significant challenges for accurate detection in SAR images when using conventional convolutional neural networks, which often lack adaptability to geometric variations. To address this problem, this paper proposes a refined Faster R-CNN detection framework, termed “rFaster R-CNN”, and adopts a transfer learning strategy to enhance model generalization and robustness. In the feature extraction stage, a backbone network called “ResNet50_CDCN” that integrates the CBAM attention mechanism and DCNv2 deformable convolution is constructed to enhance the feature expression ability of key regions in the images. Experimental results show that in the internal wave dataset constructed in this paper, this network improves the detection accuracy by approximately 3% compared to the original ResNet50 network. At the region proposal stage, this paper further adds two small-scale anchors and combines the ROI Align and FPN modules, effectively enhancing the spatial hierarchical information and semantic expression ability of ocean internal waves. compared with classical object detection algorithms such as SSD, YOLO, and RetinaNet, the proposed “rFaster R-CNN” achieves superior detection performance, showing significant improvements in both accuracy and robustness. Full article

Soil compaction in grassland and agricultural soils reduces water infiltration, root growth and ecosystem services. Conventional deep tillage and coring can alleviate compaction but are energy intensive and strongly disturb the turf. This study proposes an earthworm-inspired subsurface robot as a low-disturbance loosening tool for compacted grassland soils. Design principles are abstracted from earthworm body segmentation, anchoring–propulsion peristaltic locomotion and corrugated body surface, and mapped onto a robotic body with anterior and posterior telescopic units, a flexible mid-body segment, a corrugated outer shell and a brace-wire steering mechanism. Kinematic simulations evaluate the peristaltic actuation mechanism and predict a forward displacement of approximately 15 mm/cycle. Using the finite element method and a Modified Cam–Clay soil model, different linkage layouts and outer-shell geometries are compared in terms of radial soil displacement and drag force in cohesive loam. The optimised corrugated outer shell combining circumferential and longitudinal waves lowers drag by up to 20.1% compared with a smooth cylinder. A 3D-printed prototype demonstrates peristaltic locomotion and steering in bench-top tests. The results indicate the potential of earthworm-inspired subsurface robots to provide low-disturbance loosening in conservation agriculture and grassland management, and highlight the need for field experiments to validate performance in real soils. Full article

Integrated energy cyber-physical systems (IECPS) face escalating cyber-attack threats due to their deep cyber-physical coupling, while traditional resilience models relying solely on fixed resources exhibit rigidity and limited adaptability. This review investigates IECPS attack mechanisms through the lens of the confidentiality, integrity, and availability framework, revealing their cross-layer propagation characteristics. We explicitly distinguish between fixed and mobile resources. Fixed resources include energy sources, transmission and distribution network facilities, coupling and conversion devices, fixed energy storage systems, and communication and control infrastructure. Mobile resources are grouped into five categories: mobile electricity resources, mobile gas resources, mobile heat resources, mobile hydrogen resources, and mobile communication resources. Fixed resources provide geographically anchored capacity and structural redundancy, and they offer static operational flexibility. Mobile resources, in contrast, provide spatially reconfigurable and rapidly deployable support for sensing, temporary multi-energy supply, and emergency communications. Building on this distinction, this review proposes a full-cycle resilience enhancement framework that encompasses pre-event prevention, in-progress response, and post-event recovery, with a particular focus on collaborative mechanisms between fixed and mobile resources. Furthermore, this review examines the foundational theories and key supporting technologies for such coordination, including fixed-mobile resource scheduling, intelligent perception and data fusion, communication security, and collaborative scheduling optimization. Key technical gaps and challenges in fixed-mobile resource collaboration are identified. Ultimately, this review aims to provide theoretical insights and practical guidance for developing resilient, adaptive, and secure integrated energy systems in the face of evolving cyber-physical threats. Full article

The rapid advancement of high-performance electronics has intensified the demand for wide-bandgap semiconductor materials capable of operating under high-power and high-temperature conditions. Among these, silicon carbide (SiC) has emerged as a leading candidate due to its superior thermal conductivity, chemical stability, and mechanical strength. However, the high cost and complexity of SiC wafer fabrication, particularly in slicing and exfoliation, remain significant barriers to its widespread adoption. Conventional methods such as wire sawing suffer from considerable kerf loss, surface damage, and residual stress, reducing material yield and compromising wafer quality. Additionally, techniques like smart-cut ion implantation, though capable of enabling thin-layer transfer, are limited by long thermal annealing durations and implantation-induced defects. To overcome these limitations, ultrafast laser-based processing methods, including laser slicing and stealth dicing (SD), have gained prominence as non-contact, high-precision alternatives for SiC wafer exfoliation. This review presents the current state of the art and recent advances in laser-based precision SiC wafer exfoliation processes. Laser slicing involves focusing femtosecond or picosecond pulses at a controlled depth parallel to the beam path, creating internal damage layers that facilitate kerf-free wafer separation. In contrast, stealth dicing employs laser-induced damage tracks perpendicular to the laser propagation direction for chip separation. These techniques significantly reduce material waste and enable precise control over wafer thickness. The review also reports that recent studies have further elucidated the mechanisms of laser–SiC interaction, revealing that femtosecond pulses offer high machining accuracy due to localized energy deposition, while picosecond lasers provide greater processing efficiency through multipoint refocusing but at the cost of increased amorphous defect formation. The review identifies multiphoton ionization, internal phase explosion, and thermal diffusion key phenomena that play critical roles in microcrack formation and structural modification during precision SiC wafer laser processing. Typical ultrafast-laser operating ranges include pulse durations from 120–450 fs (and up to 10 ps), pulse energies spanning 5–50 µJ, focal depths of 100–350 µm below the surface, scan speeds ranging from 0.05–10 mm/s, and track pitches commonly between 5–20 µm. In addition, the review provides quantitative anchors including representative wafer thicknesses (250–350 µm), typical laser-induced crack or modified-layer depths (10–40 µm and extending up to 400–488 µm for deep subsurface focusing), and slicing efficiencies derived from multi-layer scanning. The review concludes that these advancements, combined with ongoing progress in ultrafast laser technology, represent research opportunities and challenges in transformative shifts in SiC wafer fabrication, offering pathways to high-throughput, low-damage, and cost-effective production. This review highlights the comparative advantages of laser-based methods, identifies the research gaps, and outlines the challenges and opportunities for future research in laser processing for semiconductor applications. Full article

Underwater Wireless Sensor Networks (UWSNs) are widely used technologies in aquatic environments. However, these types of networks face several constraints caused by the mobility of nodes, energy consumption, and constraints due to acoustic communication. In light of this, the location of nodes appears as a promising axis for improving the services expected from these networks. To address these, we suggest the LUCOTED approach—a Linear Constraint Optimization Technique for estimating unknown node positions by selecting anchor nodes with the highest energy and shortest distance, based on randomly initialized conditions. It achieves 98% accuracy, exceeding Gradient Descent and Trilateration methods. Moreover, our method LUCOTED outperforms the DEEC algorithm in terms of error when the number of anchor nodes is below 80 and achieves higher accuracy than the EPRP technique when the number exceeds 100. Full article

DFT study of graphene functionalized via carbene was performed to identify the preferred –OH adsorption sites and to assess how hydroxylation affects adsorption of NH₃ gas. The carbene attaches to the graphene basal plane through a [2+1] cycloaddition, producing a local cyclopropane-like motif with a C–C bond. This modification introduces localized mid-gap states and asymmetric charge redistribution that create chemically active anchoring sites for –OH groups. We systematically scanned possible –OH adsorption sites and identified site-dependent binding energies. NH₃ preferentially anchors at the carbene center and is further stabilized by multidentate hydrogen bonding with neighboring –OH groups. Calculated NH₃ adsorption energies range from moderate values (single –OH and some two –OH symmetric sites, E_ads ≈ −0.64 to −0.75 eV) to strong interaction for selected through-plane two –OH pairs (E_ads ≈ −1.78 to −1.83 eV), where synergistic hydrogen bonding amplifies the NH₃ interaction. Charge density difference and Bader analyses indicate polarization-dominated binding with minimal net charge transfer, consistent with hydrogen bonding rather than covalent bond formation. Desorption time estimation shows that moderate binding motifs provide rapid recovery at room temperature. We conclude that targeted placement of paired –OH groups on carbene-functionalized graphene offers a tunable route to balance sensitivity and reusability for NH₃ sensing. Full article

The advancement of floating offshore wind energy demands innovative and robust mooring and shared infrastructure solutions to enable scalable, cost-effective deployment of future wind farms. This review provides a comprehensive overview of shared mooring systems for floating offshore wind applications, with a focus on system configurations, environmental load considerations, modelling methods and mooring cost estimations. Existing concepts of shared mooring and shared anchoring are summarized and discussed. Drawing on insights from numerical studies, industrial practices, and academic research, the paper identifies key technical challenges and gaps in current design methodologies, validation requirements, and regulatory frameworks. Recommendations are proposed to guide future research aimed at improving system reliability, optimizing mooring layouts, and lowering the levelized cost of energy for large-scale floating wind projects. Full article

Installing shear walls in a load-bearing system is one of the most rational, economical, and effective strengthening methods for improving a building system that is vulnerable to seismic effects. One of the most significant points to consider in a reinforced concrete building strengthened with a shear wall is the sufficiency and reliability of anchorage elements in the shear wall–foundation joints, where significant bending moments will occur due to the impact of lateral loads. This study investigated the behaviour of different foundation anchorage methods, including internal anchorage (anchor bars) and external anchorage (steel angle and carbon-fibre-reinforced polymer (CFRP)) applied at the wall–foundation interface in retrofitted weak reinforced concrete frames, which were multi-span, multi-storey, lacking sufficient seismic detailing, and strengthened using wing-type shear walls, under quasi-static lateral loading. It was also aimed to determine the most effective anchorage method for improving the structural performance. A total of six undamaged, but seismically deficient, two-storey, two-span reinforced concrete frames were strengthened with added shear walls that incorporated different anchorage details at the shear wall–foundation joint. According to the test results, the addition of wing-shaped reinforced concrete rehabilitative walls significantly increased the lateral load-carrying capacity, lateral stiffness, and energy dissipation capacity of reinforced concrete frames with poor seismic behaviour. It was observed that additional strengthening was not required in the edge columns of frames with rehabilitative walls of a sufficient length, but that additional measures were required in the foundation anchors at the base of the strengthening wall due to the further increase in the rehabilitative wall capacity. Consequently, the most suitable shear wall foundation anchorage arrangement was achieved with test specimens where one internal anchor bar was used for each vertical shear reinforcement, independently of the shear wall length, and the development length was the highest. Full article

Liquid crystals (LCs) with fluid-like flow and solid-like molecular orientation find important applications in optical display and sensor technologies. Predicting the mean steady-state polar angle and refractive index is crucial for optimizing LC performance. While conventional predictive models such as those based on continuum theories require complex and computationally intensive numerical simulations, this study employs artificial neural networks (ANNs). In particular, they are developed to predict the mean steady state polar angle and refractive index from surface viscosity and anchoring energy. Using the train, validation, test method, ANN_A4 (R² = 0.9995) and ANN_B2 (R² = 0.9969) are found to have the highest predictive accuracy. On the other hand, using the K-Fold cross-validation, the results significantly differ, with the best performance shown in ANN_A5* (R² = 0.40767) and ANN_B4* (R² = 0.93799). Coupled with the low latency of ANNs, these results indicate that ANNs have significant potential in LC modeling, especially for use in the computationally intensive optimization of LC-based technologies. Full article

The global shift towards low-carbon economies underscores the critical role of new energy (NE) technologies in addressing climate change and ensuring energy security. China’s renewable energy sector serves as a prime example of this transition. However, the sector faces significant challenges, including technological fragmentation characterized by isolated R&D efforts that impede knowledge diffusion, and regional disparities that marginalize firms in inland and western regions within innovation networks. This study examines the spatiotemporal evolution of China’s new energy technological correlation networks across 208 firms (2006–2023) using social network analysis. The findings reveal a four-stage progression from fragmentation (2006–2010) to regional clustering (2011–2015), followed by core–periphery differentiation (2016–2020), culminating in multipolar synergy (2021–2023). Policy cycles are closely associated with structural shifts, with coastal hubs leveraging policy-industrial advantages whilst inland areas grow via technology diffusion. This study proposes the policy-driven effect, where subsidies anchor scale expansion, whereas phase-outs are linked to quality enhancement. Phase-adaptive strategies are recommended to transition from scale-driven to innovation-quality paradigms. Full article

Plasma membrane Ca²⁺-ATPases (PMCA) are activated by calmodulin (CaM) via a C-terminal calmodulin-binding domain, CaMBD. Although specific mutations in this domain have been linked to disease, the broader impact of alternative substitutions across the interface remains unexplored. We applied an integrative in silico workflow to test six substitutions within CaMBD positions 1–18, L5R, N6I, I8T, V14E/D, and F18S, across PMCA isoforms 1–4. CaMBD sequences were aligned across isoforms, and candidates for substitutions were selected by conservation and nucleotide feasibility, prioritizing conserved or co-evolutionarily relevant sites, with substitutions possible by single-nucleotide change. PolyPhen-2 screened the impact of the substitutions on the protein functionality, the DisGeNET database was used to contextualize ATP2B genes with clinical phenotypes, and structural models plus binding free energy changes were estimated with AlphaFold3, FoldX, and MutaBind2. Effects were isoform and subregion dependent, with the strongest weakening toward the CaMBD C-terminus. V14E/D and F18S showed the largest and consistent predicted destabilization, consistent with disruption of conserved hydrophobic anchors. I8T and L5R had mixed outcomes depending on isoform, while N6I presented various scenarios with no clear effect. PolyPhen-2 classified most tested substitutions as damaging. Gene-disease evidence linked ATP2B to neurological, endocrine, and oncologic phenotypes, consistent with roles in Ca²⁺ homeostasis. Overall, CaMBD appears highly sensitive to perturbation, with distal positions 14–18 particularly vulnerable to substitutions that can destabilize CaM binding and potentially impair PMCA-mediated Ca²⁺ clearance in susceptible tissues. Full article