Browse Articles

Harnessing prebiotic formamide chemistry: a novel platform for antiviral exploration

Abstract Viruses and host cells are intricately connected through a shared “chemical language” that may trace back to the prebiotic chemistry of early Earth. In this study, we present an innovative platform for antiviral exploration inspired by this primordial chemical framework. By “doping” the formamide-based prebiotic chemistry model with orotic acid derivatives, we generated complex, non-natural chemical mixtures capable of disrupting the replication of multiple viruses with minimal or no toxicity for eukaryotic cells. This strategy underscores the potential of an evolution-inspired approach in antiviral discovery, offering a novel avenue for identifying new agents with unconventional mechanisms that might elude traditional discovery methods.

A novel ultra-steep subthreshold swing iTFET with control gate and control source biasing

Neural correlates and dynamical brain states of creative insight in a spatial problem task

Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles

Establishment of THTT derivatives as potential antileishmanial and anti-inflammatory agents through in vitro and in silico investigations

Multiscale performance analysis and optimization of a composite clamp plate for leaf spring assembly considering fiber orientation distribution

Abstract The growing demand for lightweight solutions in automotive engineering has propelled the adoption of fiber-reinforced thermoplastic composites, necessitating precise characterization of their process-induced mechanical properties. This study develops an integrated multiscale methodology addressing injection-molding-induced fiber orientation heterogeneity in structural components. Through synergistic integration of injection molding simulation, mesoscopic constitutive modeling, and macroscopic structural analysis, we systematically investigated failure mechanisms in automotive leaf spring clamp plates. The proposed framework successfully identifies gravitational segregation during vertical molding as the root cause of terminal fracture under operational loads. Subsequent design optimization implements (1) reorientation of the injection direction to horizontal and (2) localized wall thickness reduction from 37 mm to 19.86 mm. These interventions collectively reduce the maximum principal stress by 19% (from 231 MPa to 187 MPa) while achieving a 12.8% mass reduction (from 780 g to 680 g), demonstrating the concurrent enhancement of structural reliability and lightweighting efficacy.

Research on quantitative prediction method of structural fractures in metamorphic rock reservoirs

Evidence based consensus statements for digital tools to address youth mental health literacy

Abstract Mental health disorders typically emerge in early life and can be modified through prompt intervention. Mental health literacy is the multi-dimensional knowledge of mental health disorders to recognize, manage, or prevent mental health disorders. Enhancing youth mental health literacy through information communication technologies already adopted by youth may be an accessible and effective approach to address the ongoing mental health crisis. We used an interconnected, three phase process following co-design methods to determine evidence-based consensus statements to conceptualize and develop the Youth MindTrack and to inform future digital tools to support youth mental health literacy. In Phase I, a scientific team (N = 21; 24% youth) adhered to deliberative dialogue and priority setting methods to develop strategic priorities. Phase II consisted of a modified Delphi consensus process to determine evidence-based consensus statements (N = 352 (13% youth) Round 1; N = 87 (33% youth) Round 2). Semi-structured focus groups in Phase III were conducted to refine the consensus statements (N = 16, 25% youth) and design the digital mental health literacy tool (N = 24, 33% youth). Twenty-one consensus statements encompassing four domains were produced: (1) Understanding mental health (N = 4); (2) Exercising mental health (N = 6); (3) Engaging with digital support (N = 8); and (4) Evaluating digital support (N = 3). Content analysis of discussions identified 16 themes mapped to the domains of mental health literacy and user-interface, design considerations for digital tools on mental health literacy more broadly. The resulting design of the Youth MindTrack tool to support mental health literacy included four main interactive sections designed to be downloaded and completed by youth on a digital device. We determined 21 evidence-based consensus statements that underpinned the conceptualization and development of the Youth MindTrack: a downloadable digital tool to support youth mental health literacy. The data supports proceeding to pilot testing to assess the tool’s usability, acceptability, and perceived effectiveness prior to implementation, and provides evidence that an iterative and participatory research-based process with youth can help adapt health technology to their needs.

Association between cholecystectomy and the risk of new-onset metabolic dysfunction-associated steatotic liver disease: a risk-stratified cohort study

Study on the mechanism of anchoring parameters of anchor rods in cemented broken surrounding rock

EDM-based analysis of Fe-based shape memory alloys using Cu-W electrodes with multiple output optimization and microstructural validation

Abstract Shape Memory Alloys (SMAs) are pivotal in diverse industrial applications due to their exceptional properties, including actuation, biocompatibility, and adaptability in aerospace, biomedical, and military domains. However, their complex machinability often leads to high costs and suboptimal surface quality when processed using traditional methods. Using Response Surface Methodology (RSM) with a Central Composite Design (CCD), this study evaluated the effects of input parameters, including pulse on time (Ton), pulse off time (Toff), peak current (Ip), and gap voltage (GV), on material wear responses during Electrical Discharge Machining (EDM). Fe-based Shape Memory Alloys (SMAs) were machined using a Cu-tungsten electrode to investigate the wear characteristics of both workpieces and tool electrodes. Results revealed that Workpiece Material Removal Rate (WOW) ranged from 11.30 to 65.17 mm³/min, and Tool Wear Rate (WOTE) varied from 0.0062 to 0.01127 g/min. Scanning Electron Microscopy (SEM) of machined surfaces showcased craters, micro-cracks, and recast layers, elucidating the correlation between process parameters and surface integrity. Multi-objective optimization using the desirability approach identified optimal conditions for balancing machining efficiency and surface quality. This research provides a comprehensive understanding of the EDM process for Fe-based SMAs, paving the way for improved machinability and expanded industrial applications.

Chitosan pre- and post-treatment modulates molecular and physiological responses to salinity in Brassica Napus L

Echocardiographic assessment of left atrial structural and functional changes after catheter ablation in paroxysmal atrial fibrillation with preserved ejection fraction

Temporal and spatial response of agricultural drought to meteorological drought in inner Mongolia plateau inland river basin

Seasonal and interannual variations in material transport in the Korea Strait originating from the Taiwan Strait

Working-age patients with medically unexplained oral symptoms who receive public assistance in Japan

Open pit design for improved gold recovery at Ula-Ulo placer deposit in Guji, southern Ethiopia

Study on the influence of peripheral eye on over-excavation during mountain tunnel blasting construction

Integrated electrodes for the nutrient removal from municipal wastewater using electrocoagulation technology

Electrochemical performance of a novel 1-(benzo[d]thiazol-2-yl)-3-methylguanidine as effective corrosion inhibitor for carbon steel in 1 M hydrochloric acid

Abstract Guanidine benzothiazole (G) and 1-(benzo[d]thiazol-2-yl)-3-methylguanidine (AG) were successfully synthesized and characterized by infrared (FT-IR) and nuclear magnetic resonance (NMR) spectroscopy. Both compounds act as novel corrosion inhibitors for carbon steel in 1.0 M hydrochloric acid solution. Their inhibition efficiency was evaluated using potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS). Surface analysis via scanning electron microscope (SEM) and energy dispersive X-ray (EDX) confirmed the formation of a protective film on the steel surface. PDP results indicate that G and AG function as mixed-type inhibitors, with inhibition efficiency increasing with concentrations, reaching a maximum of 80% for G and 91.4% AG. The AG compound was seen to retard the rate of corrosion of carbon steel more effective than PP compound. Adsorption followed the Langmuir isotherm, suggesting monolayer adsorption on the metal surface. The high inhibition efficiencies were attributed to strong adsorption and the formation of a dense, protective barrier film. The corrosion inhibition performance of the synthesized molecule was evaluated using density functional theory (DFT). Quantum chemical parameters, including highest occupied molecular orbital (HOMO) and lowest occupied molecular orbital (LUMO), energy gap, hardness, and dipole moment, and other quantum descriptors were analyzed. Density functional theory (DTF) calculation supported the experimental finding, showing that the high efficiency correlates with a low energy gap and high dipole moment, which promote electron transfer and adsorption strength. Theoretical and experimental results showed strong agreement, confirming the potential of G and AG as effective inhibitors for carbon steel.