Search Results (472)

Antiviral peptides (AVPs) are promising therapeutic candidates, yet the rapid growth of sequence data and the field’s emphasis on predictors have left a gap: the lack of an integrated view linking peptide chemistry with biological context. Here, we map the AVP landscape through interactive data mining using Half-Space Proximal Networks (HSPNs) and Metadata Networks (MNs) in the StarPep toolbox. HSPNs minimize edges and avoid fixed thresholds, reducing computational cost while enabling high-resolution analysis. A threshold-free HSPN resolved eight chemically and biologically distinct communities, while MNs contextualized AVPs by source, function, and target, revealing structural–functional relationships. To capture diversity compactly, we applied centrality-guided scaffold extraction with redundancy removal (90–50% identity), producing four representative subsets suitable for modeling and similarity searches. Alignment-free motif discovery yielded 33 validated motifs, including 10 overlapping with reported AVP signatures and 23 apparently novel. Motifs displayed category-specific enrichment across antimicrobial classes, and sequences carrying multiple motifs (≥4–5) consistently showed higher predicted antiviral probabilities. Beyond computational insights, scaffolds provide representative “entry points” into AVP chemical space, while motifs serve as modular building blocks for rational design. Together, these resources provide an integrated framework that may inform AVP discovery and support scaffold- and motif-guided therapeutic design. Full article

Personnel selection represents a two-sided matching problem in which firms compete for qualified candidates by designing job-offer packages. While traditional models assume fully rational agents, real-world decision-makers often face bounded rationality due to limited information and cognitive constraints. This study develops a matching framework that incorporates bounded rationality through the Quantal Response Equilibrium, where firms and candidates act as probabilistic rather than perfect optimizers under uncertainty. Using Maximum Likelihood Estimation and organizational hiring data, we validate that both sides display bounded rational behavior and that rationality increases as the selection process advances. Building on these findings, we propose a two-stage stochastic optimization approach to determine optimal job-offer packages that balance organizational policies with candidate competencies. The optimization problem is solved using particle swarm optimization, which efficiently explores the solution space under uncertainty. Data analysis reveals that only 23.10% of low-level hiring decisions align with rational choice predictions, compared to 64.32% for high-level positions. In our case study, bounded rationality increases package costs by 26%, while modular compensation packages can reduce costs by up to 25%. These findings highlight the cost implications of bounded rationality, the advantages of flexible offers, and the systematic behavioral differences across job levels. The framework provides theoretical contributions to matching under bounded rationality and offers practical insights to help organizations refine their personnel selection strategies and attract suitable candidates more effectively. Full article

The accurate assessment of Chinese bayberry (Myrica rubra) maturity is critical for intelligent harvesting. This study proposes a novel cascaded framework combining instance segmentation and multi-feature regression for accurate maturity detection. First, a lightweight SOLOv2-Light network is employed to segment each fruit individually, which significantly reduces computational costs with only a marginal drop in accuracy. Then, a multi-feature extraction network is developed to fuse deep semantic, color (LAB space), and multi-scale texture features, enhanced by a channel attention mechanism for adaptive weighting. The maturity ground truth is defined using the a*/b* ratio measured by a colorimeter, which correlates strongly with anthocyanin accumulation and visual ripeness. Experimental results demonstrated that the proposed method achieves a mask mAP of 0.788 on the instance segmentation task, outperforming Mask R-CNN and YOLACT. For maturity prediction, a mean absolute error of 3.946% is attained, which is a significant improvement over the baseline. When the data are discretized into three maturity categories, the overall accuracy reaches 95.51%, surpassing YOLOX-s and Faster R-CNN by a considerable margin while reducing processing time by approximately 46%. The modular design facilitates easy adaptation to new varieties. This research provides a robust and efficient solution for in-field bayberry maturity detection, offering substantial value for the development of automated harvesting systems. Full article

Urban agriculture in space-constrained cities requires compact, reproducible propagation systems. Therefore, the aim of this Technical Note is to design, implement, and functionally validate a low-cost, modular hydroponic chamber (SSHG) for early-stage vegetative propagation. This system couples DHT11-based temperature/RH monitoring with rule-based actuation—irrigation 4×/day and temperature-triggered ventilation—under the control of an Arduino Uno microcontroller; LED lighting was not controlled nor analyzed. Two 15-day trials with basil (Ocimum basilicum L.) yielded rooting rates of 61.7% (37/60) and 43.3% (26/60) under a deliberate minimal-input configuration without nutrient solutions or rooting hormones. Environmental summaries and spatial survival maps revealed edge-effect patterns and RH variability that inform irrigation layout improvements. The chamber, bill of materials, and protocol are documented to support replication and iteration. Thus, the SSHG provides a transferable baseline for educators and researchers to audit, reproduce, and improve small-footprint, controlled-environment propagation. Beyond its technical feasibility, the SSHG contributes to sustainability by leveraging low-cost, readily available components, enabling decentralized seedling production in space-constrained settings, and operating under a minimal-input configuration. In line with widely reported hydroponic efficiencies (e.g., lower water use relative to soil-based propagation), this open and replicable platform aligns with SDGs 2, 11, 12, and 13. Full article

Climate change and urbanization are intensifying the urban heat island effect and negatively impacting outdoor thermal comfort in cities. Innovative planning strategies are required to design more livable and resilient urban spaces. Building on a state of the art of current Urban Digital Twins (UDTs) for outdoor thermal comfort analysis, this paper presents the design and implementation of a functional UDT prototype. Developed for a pilot area in Huelva, Spain, the system integrates real-time environmental data, spatial modeling, and simulation tools within an open-source architecture. The literature reveals that while UDTs are increasingly used in urban management, their application to outdoor thermal comfort remains limited and technically challenging, especially in terms of real-time data, modeling accuracy, and user interaction. The case study demonstrates the feasibility of a modular, open-source UDT capable of simulating mean radiant temperature and outdoor thermal comfort indexes at high resolution and visualizing the results in a 3D interactive environment. UDTs have strong potential for supporting microclimate-sensitive planning and improving outdoor thermal comfort. However, important challenges remain, particularly in simulation efficiency, model detail, and stakeholder accessibility. The proposed prototype addresses several of these gaps and provides a basis for future improvements. Full article

Gas monitoring and dust control in coal mine goafs are critical for ensuring safe and efficient production. To address the challenges posed by dust accumulation from mechanized mining and ventilation systems, this study designs a spiral-driven gas purification pipeline robot integrating a wet dust removal mechanism. The robot features a modular structure, including a spiral drive, a plugging and extraction system, and a wet dust removal unit, to enhance pipeline adaptability and dust removal performance. Dynamic modeling reveals that the robot’s speed increases with the deflection angle of the driving wheel, with optimal performance observed at a 45° angle. The analysis of the rolling friction, medium resistance, and deflection angle indicates that reducing the angle improves the obstacle-crossing ability. Numerical simulations of gas migration in the goaf identify a high dust concentration at the air outlet and show that flow velocity significantly affects dust removal efficiency. Simulation and prototype testing confirm stable robot operation at deflection angles of between 30° and 90° and effective crossing of 5 mm barriers. Optimal dust removal is achieved with a 5 m/s flow velocity, 0.6 MPa water mist pressure, and 400 mm chord grid spacing, providing both theoretical and practical guidance for gas monitoring and dust control in coal mine goafs. Full article

The development of a multifunctional invention requires several refinements for optimizing each function. This study presents a Theory of Inventive Problem Solving (TRIZ)-based conceptual framework for enhancing an innovative multifunctional assistive technology device that integrates the functionalities of a rollator walker, wheelchair, Pilates chair, and stepladder. The limitations of the multifunctional rollator walker were identified from the user feedback of a foundational work and were then addressed by identifying the engineering and physical contradictions and problem modeling using Su-field analysis. Through TRIZ Inventive Principles, the proposed design eliminates common trade-offs between portability, stability, and usability. The conceptual enhancement incorporates features such as deployable steps, the utilization of high strength–to–weight ratio material, foldability, a passive mechanical brake-locking system, retractable armrests, the incorporation of spring-assist hinges, and the use of large tires with vibration-dampening hubs. This study contributes a novel, user-focused, and space-saving mobility solution that aligns with the evolving demands of assistive technology, laying the groundwork for future iterations involving smart control, power assist, and modular enhancements. Full article

In response to the IMO’s decarbonisation strategy, hydrogen—especially green hydrogen—becomes a promising alternative fuel in shipping. This article provides a comparative analysis of two hydrogen propulsion technologies suitable for a service vessel (SOV) operating in offshore wind farms: hydrogen fuel cells and hydrogen-powered internal combustion engines. This study focuses on the use of liquid hydrogen (LH₂) stored in cryogenic tanks and fuel cells as an alternative to the previously considered solution based on compressed hydrogen (CH₂) stored in high-pressure cylinders (700 bar) and internal combustion engines. The research aims to examine the feasibility of a fully hydrogen-powered SOV energy system. The analyses showed that the use of liquefied hydrogen in SOVs leads to the threefold reduction in tank volume (1001 m³ LH₂ vs. 3198 m³ CH₂) and the weight of the storage system (243 t vs. 647 t). Despite this, neither of the technologies provides the expected 2-week autonomy of SOVs. LH₂ storage allows for a maximum of 10 days of operation, which is still an improvement over the CH₂ gas variant (3 days). The main reason for this is that hydrogen tanks can only be located on the open deck. Although hydrogen fuel cells take up on average 13.7% more space than internal combustion engines, they are lower (by an average of 24.3%) and weigh less (by an average of 50.6%), and their modular design facilitates optimal arrangement in the engine room. In addition, the elimination of the exhaust system and lubrication simplifies the engine room layout, reducing its weight and space requirements. Most importantly, however, the use of fuel cells eliminates exhaust gas emissions into the atmosphere. Full article

Background/Objectives: Synaptic plasticity is fundamental to learning and memory, yet classical models such as Hebbian learning and spike-timing-dependent plasticity often overlook the distributed and wave-like nature of neural activity. We present a computational framework grounded in Scale Relativity Theory (SRT), which describes neural propagation along fractal geodesics in a non-differentiable space-time. The objective is to link nonlinear wave dynamics with the emergence of structured memory representations in a biologically plausible manner. Methods: Neural activity was modeled using nonlinear Schrödinger-type equations derived from SRT, yielding complex wave solutions. Synaptic plasticity was coupled through a reaction–diffusion rule driven by local activity intensity. Simulations were performed in one- and two-dimensional domains using finite difference schemes. Analyses included spectral entropy, cross-correlation, and Fourier methods to evaluate the organization and complexity of the resulting synaptic fields. Results: The model reproduced core neurobiological features: localized potentiation resembling CA1 place fields, periodic plasticity akin to entorhinal grid cells, and modular tiling patterns consistent with V1 orientation maps. Interacting waveforms generated interference-dependent plasticity, modeling memory competition and contextual modulation. The system displayed robustness to noise, gradual potentiation with saturation, and hysteresis under reversal, reflecting empirical learning and reconsolidation dynamics. Cross-frequency coupling of theta and gamma inputs further enriched trace complexity, yielding multi-scale memory structures. Conclusions: Wave-driven dynamics in fractal space-time provide a hypothesis-generating framework for distributed memory formation. The current approach is theoretical and simulation-based, relying on a simplified plasticity rule that omits neuromodulatory and glial influences. While encouraging in its ability to reproduce biological motifs, the framework remains preliminary; future work must benchmark against established models such as STDP and attractor networks and propose empirical tests to validate or falsify its predictions. Full article

Cryptography stands out as a scientific methodology for safeguarding communication against unauthorized access. This article proposes a newly formulated graph termed the Index Difference Graph (IDG). The proposed graph model serves as the secret key in the encryption process. Furthermore, we present a new graph-based algorithm, the Index Difference Modular Cryptographic (IDMC) Algorithm, and analyze it using centipede and path graphs. The goal of this graph-based approach is to increase the encryption rate while maintaining computational efficiency. This research investigates different types of index difference graphs and analyzes the time and space complexity of the algorithm. IDMC exhibits a lower collision probability, thereby enhancing encryption security. When employing a graph that admits an Index Difference Graph structure in the cryptographic algorithm, both the sender and receiver must be aware of the graph’s precise structure, as this strengthens the robustness of the cryptographic key. The application of the index difference centipede graph $P_n\odot 2k_1$ in cryptography, examined through the IDMC algorithm, demonstrates exceptionally high brute-force resistance estimated at approximately $2.6\times {10}^{39}$ for smaller instances with $n\le 7$ and escalating to $6.93\times {10}^{163}$ for larger graphs with $n\ge 20$. This resistance underscores the algorithm’s efficiency and cryptographic resilience. Full article

Maintaining physiologically controlled conditions during the transport of biological experiments remains a long-standing but under-addressed challenge in spaceflight operations. Pre-launch thermal or mechanical stress induce artefacts that compromise the interpretation of biological responses to space conditions. Existing transport systems are limited to basic heating of small sample containers and lack the capability to power and protect full experimental hardware during mission-critical phases. A modular transport incubator was developed and validated that combines active thermal regulation, battery-buffered power management, and mechanical protection in a compact, field-deployable platform. It enables autonomous environmental conditioning of complex biological payloads and continuous operation of integrated scientific instruments during ground-based transport and recovery. Validation included controlled experiments under sub-zero ambient temperatures, demonstrating rapid warm-up, stable thermal regulation, and uninterrupted autonomous performance. A steady-state finite difference thermal model was experimentally validated across 21 boundary conditions, enabling predictive power requirement estimation for mission planning. Field deployments during multiple MAPHEUS^® sounding rocket campaigns confirmed functional robustness under wind, snow, and airborne recovery scenarios. The system closes a critical infrastructure gap in spaceflight logistics. Its validated performance, modular architecture, and proven operational readiness establish it as an enabling platform for standardized, reproducible ground handling of biological payloads and experiment hardware. Full article

The operation of microgravity research missions, such as sounding rockets, CubeSats, and small landers, typically relies on proprietary mission control infrastructures, which limit reproducibility, portability, and interdisciplinary use. In this work, we present an open-source blueprint for a distributed ground-segment architecture designed to support telemetry, telecommand, and mission operations across institutional and geographic boundaries. The system integrates containerized services, broker bridging for publish–subscribe communication, CCSDS-compliant telemetry and telecommand handling, and secure virtual private networks with two-factor authentication. A modular mission control system based on Yamcs was extended with custom plug-ins for CRC verification, packet reassembly, and command sequencing. The platform was validated during the MAPHEUS-10 sounding rocket mission, where it enabled uninterrupted remote commanding between Sweden and Germany and achieved end-to-end command–response latencies of ~550 ms under flight conditions. To the best of our knowledge, this represents the first open-source ground-segment framework deployed in a space mission. By combining elements from computer science, aerospace engineering, and systems engineering, this work demonstrates how interdisciplinary integration enables resilient, reproducible, and portable mission operations. The blueprint offers a practical foundation for future interdisciplinary research missions, extending beyond sounding rockets to CubeSats, ISS experiments, and planetary landers. This study is part two of a three-part series describing the apex Mk.2/Mk.3 experiments, open-source ground segment, and service module simulator. Full article

This article presents an experimental study on the hydrodynamics of coolant flow within the pressure vessel of a small modular reactor (SMR) cooled with water, including areas such as the annular downcomer, bottom chamber, and core-simulating channels that are being developed for use in land-based nuclear power plants. This paper describes the experimental setup and test model, measurement techniques used, experimental conditions under which this research was conducted, and results obtained. This study was conducted at the Nizhny Novgorod State Technical University (NNSTU) using a high-pressure aerodynamic testing facility and a scale model that included structural components similar to those found in loop-type reactors. Experiments were performed with Reynolds numbers (Re) ranging from 20,000 to 50,000 in the annular downcomer space of the test model. Two independent techniques were used to simulate the non-uniform flow field in the pressure vessel: passive impurity injection (adding propane to the airflow) and hot tracer (heating one of the reactor circulation loops). The axial velocity field at the inlet to the reactor core was also investigated. This study provided information about the spatial distribution of a tracer within the coolant flow in the annular downcomer and bottom chamber of the pressure vessel. Data on the distribution of the contrasting admixture are presented in plots. The swirling nature of the coolant flow within the pressurized vessel was analyzed. It was shown that the intensity of mixing within the bottom chamber of the pressure vessel is influenced by the presence of a central vortex. Parameters associated with the mixing of admixtures within the model for the pressure vessel were estimated. Additionally, the possibility for simulating flow with different temperature mixing processes using isothermal models was observed. Full article

As the global shift toward renewable energy accelerates, large-scale energy storage is essential to balance intermittent supply and growing demand. While conventional Pumped Hydro Storage remains dominant, Underground Pumped Hydro Storage (UPHS) offers a promising alternative, particularly in flat regions with ample subsurface space. Southern Ontario, Canada, underlain by thick salt formations and a history of salt mining, presents favorable conditions for UPHS development, yet relative studies remain limited. This work presents the first UPHS-specific geomechanical feasibility assessment in the Canadian Salina Group, introducing a paired-cavern layout tied to Units B and A2 and explicitly capturing both elasto-plastic and creep behavior. Using COMSOL Multiphysics 6.3, a three-dimensional numerical model was developed featuring two vertically separated cylindrical caverns located in Unit B and the lower part of Unit A2. A 24 h operating cycle was simulated over a 10-year period, incorporating elasto-plastic deformation and salt creep. Minimum working pressures were varied to evaluate long-term cavern stability. The results show that a minimum pressure of 0.3 σ_v balances structural integrity and operational efficiency, with creep strain and volumetric convergence remaining within engineering limits. Beyond previous salt-cavern studies focused on hydrogen or CAES, this study provides the first coupled elasto-plastic and creep simulation tailored to UPHS operations in bedded salt, establishing a safe operating-pressure guideline and offering site-relevant design insights for modular underground energy storage systems in sedimentary basins. Full article

Corrugated steel–concrete (CSC) composite arches, an innovative structural system with simplified construction and enhanced stiffness, are widely used in bridge and tunnel modular engineering. However, insufficient research on their shear performance limits prefabricated applications. Similarly to beams, their shear behavior is significantly affected by loading location. Specifically, as a parameter significantly affected by the loading location, the shear–compression ratio exerts a notable influence on the shear bearing capacity of CSC arches by altering the development pattern of cracks and the inclination angle of shear cracks. To investigate the influence mechanism of the loading location, this study is the first to systematically link shear–compression ratio variation to load location in CSC arches. In this context, shear performance tests were conducted on two CSC specimens with different loading locations (mid-span and quarter-point) to investigate the influence of loading locations on the shear behavior of CSC arches. To further investigate the impact of key parameters on the shear bearing capacity of CSC arches, a validated finite element model was employed to support the parametric analysis. The parameters involved include the span-to-rise ratio, shear connector spacing, strength and thickness of corrugated steel, as well as strength and thickness of concrete. Theoretical calculations for internal forces under varying rise-to-span ratios and loading methods are conducted, proposing an analytical solution method. Validation using 2 experiments and 96 finite element results show that a modified method is applicable, with a mean value of 1.066, corresponding to a standard deviation of 0.071, and all relative errors within 15%. By introducing the shear–compression ratio, this study extends existing methods to make them applicable under single-point loading, thereby enabling their use for guiding engineering. Similarly, the internal force analysis method proposed herein can serve as a theoretical foundation, providing a valuable reference for future research on shear capacity calculation methods for CSC arches with varying cross-sectional configurations and those where bending moments play a more significant role. Full article