Search Results (3,050)

Following the growing interest in small-scale unmanned aerial vehicles (UAVs), this paper presents a comprehensive conceptual design methodology for a modular ducted-fan aerial vehicle intended for research applications. Although ducted-fan configurations offer significant advantages over conventional multirotor platforms, particularly in urban, indoor, and human-interaction scenarios, the availability of affordable and customizable ducted-fan UAVs platforms suitable for scientific research remains limited. To address this gap, the paper details the complete design of the vehicle, including propeller aerodynamics and duct design, mechanical structure, actuation system, dynamic modeling, and control strategy. All major structural and aerodynamic components are fabricated using low-cost additive manufacturing, enabling rapid prototyping and high modularity. The vehicle’s performance is experimentally assessed through bench tests and indoor flight experiments, demonstrating stable flight and satisfactory attitude control. The presented work shows that a fully functional ducted-fan UAVs can be realized using commercial off-the-shelf electronics and exclusively 3D-printed components, and provides practical guidelines to replicate and adapt the proposed platform for advanced research in UAVs control, navigation, and autonomy. Full article

This study presents a case-specific joining method for modular, large-scale components manufactured using Selective Laser Sintering (SLS). A T-slot joint reinforced with a pultruded carbon fiber rod was developed to enable the segmental assembly of polymer fan blades that exceed the build volume of common SLS printers. Through an iterative design process, five joint variations were investigated, focusing on the optimization of slot geometry (fillet radii and wall thickness) and the integration of carbon fiber reinforcements to create a high-strength hybrid connection. The experimental findings were validated using a non-linear finite element analysis (FEA) utilizing an iteratively calibrated Young’s modulus of 710 MPa, which accounts for the 50/50 virgin-to-reused PA2200 powder ratio employed in the study. The numerical model identified that the primary sites for crack initiation were the fillet radii of the female slot, where localized equivalent plastic strains reached critical levels of up to 84% in tension and 78% in bending. The final design achieved an average tensile strength of 27.6 MPa, exceeding the design threshold of 21.9 MPa with a safety factor of 2.5. While unreinforced joints showed a 73.4% reduction in bending strength compared to solid specimens, the addition of an 8 mm carbon rod increased performance by 238.7%, restoring over 90% of the monolithic material’s strength. Numerical results confirmed that the reinforcement assumed the primary load-bearing role, effectively mitigating stresses in the polymer matrix below the ultimate tensile strength. Failure analysis clarified that the observed audible failure originated from internal fiber breakage within the rod at stresses between 900–1050 MPa. This work demonstrates that a segmental, reinforcement-based joining method can effectively overcome size constraints in polymer additive manufacturing, providing a robust and repeatable solution for rotating components subject to complex loading conditions. Full article

The paper is focused on broader considerations regarding the commissioning process of the 3rd Unit of nuclear power plant VVER-440 type in Mochovce (Slovakia). The new nuclear plant built in Europe is getting much more slowly than expected, declared or scheduled. Besides the nuclear power plant in Olkiluoto (Finland) and also Flamanville (France), the 3rd Mochovce Unit has finally been in full operation since 6 November 2024. Nevertheless, the more than 30 years of construction process, which was intermittently stopped and frozen, make this success story exceptional. Lessons learned from commissioning are every time specific for different countries but commissioning of nuclear power plant without presence of general designer, respecting all safety requirements and taking full responsibility for this process is unique. Still, in general, the actual Slovak experiences and knowledge could help optimise new buildings in Europe, including dreams about small modular reactor deployment or the building of other clean and sustainable use of advanced nuclear facilities in the future. Full article

This work introduces Hybrid Membrane–Neural P systems (HMN P systems), a computational model that integrates principles from membrane computing and spiking neural P systems. The resulting framework offers a versatile foundation for the development of bio-inspired arithmetic architectures. Within this setting, we propose a compact family of arithmetic kernels capable of executing signed addition, subtraction, multiplication, and division in both modular and non-modular arithmetic domains. By leveraging intrinsic spike aggregation, spike–anti-spike annihilation, and exhaustive rule application, the proposed designs achieve efficient and reliable arithmetic computation in a constant number of simulation steps under exhaustive semantics and assuming synchronized input, independent of operand values. Addition and subtraction are executed intrinsically upon spike arrival, requiring no internal computation steps, while multiplication and division are completed in a single simulation step by one neuron. Furthermore, we introduce a modular-reduction kernel that operates in two simulation steps with a single neuron, and leverage its modular structure to construct modular multiplication and division through composition with non-modular arithmetic modules. Comparative evaluations against representative SNP and SNQ arithmetic designs demonstrate that HMN kernels achieve operand-independent execution time while requiring fewer neurons. Distinct from most existing approaches, the HMN framework natively supports signed operands through a dual-spike representation, thereby eliminating the need for auxiliary sign-handling mechanisms. Asynchronous spike arrivals can be managed by an optional synchronization membrane; since this mechanism is decoupled from the arithmetic kernels, its overhead is excluded from kernel performance and reported separately. Collectively, these results establish HMN systems as an efficient and modular platform for constant-time arithmetic computation, offering reusable arithmetic kernels that serve as a foundation for higher-level constructions, including those arising in elliptic-curve and modular arithmetic. Full article

This study presents a modular outdoor vertical farming system integrated into building façades to address urban food security and sustainability challenges in Singapore. The design integrates passive climate control, hydroponics and soil-based irrigation, with active monitoring of the vapor pressure deficit (VPD) and photosynthetically active radiation (PAR). Continuous visual imaging is used to support growth monitoring and predictive harvesting, reducing labor needs. Under experimental conditions, deployment of UCNP-coated light-conversion films improved crop yield by 30% and reduced plant heat stress. Photovoltaic arrays and battery storage enabled energy self-sufficiency and microclimate management in the modular farm. The results demonstrated that building-integrated vertical farms can enhance urban food resilience and resource efficiency, offering a scalable model for sustainable agriculture in land-constrained cities. Full article

Avionics systems are evolving from Integrated Modular Avionics (IMA) to Distributed Integrated Modular Avionics (DIMA), where distributed computing nodes are interconnected through real-time networks to support flexible resource sharing and latency-critical services. This architecture is highly consistent with the paradigm of Mobile Edge Computing (MEC), in which distributed edge resources collaboratively process computation workloads close to users to meet stringent real-time requirements. However, efficient task scheduling and migration remain key challenges in such distributed MEC platforms, since many existing approaches are designed for traditional centralized architectures and lack effective support for runtime workload dynamics and migration overheads. In this paper, we abstract the computing resource and task models for DIMA-oriented MEC systems and propose two algorithms: an Efficient Workload Scheduling Algorithm (EWSA) for workload placement and a Workload Migration Algorithm (WMA) for adaptive task relocation. CloudSim-based simulations show that the proposed methods significantly outperform the benchmark JIT-C approach in scheduling performance and migration efficiency, demonstrating their effectiveness for real-time distributed edge computing environments. Full article

This paper presents the design, construction, and calibration of a modular low-cost 3D printer based on open-source technologies, developed as part of an academic research project. The printer utilises fused filament fabrication (FFF) and is built using locally available materials and components, including a T-slot aluminium frame, NEMA 23 stepper motors, and an Arduino Mega 2560 with RAMPS 1.4 control board. The system integrates Marlin firmware and CURA slicing software, enabling autonomous operation via an LCD panel and encoder interface. A detailed methodology is provided for mechanical assembly, electronic integration, firmware configuration, and calibration procedures. Special attention is given to the challenges encountered during the initial testing phase, including filament feeding issues, thermal inconsistencies, and mechanical misalignments. Solutions such as replacing inadequate components (e.g., fibreglass bushings with PTFE), adjusting spring tension, and refining firmware parameters are discussed. The results demonstrate successful printing of complex geometries after iterative calibration, validating the printer’s performance and replicability. This work contributes to the democratisation of additive manufacturing by offering a replicable, open-source solution for educational and prototyping purposes. The findings are relevant to machine design, automation, and robotics communities seeking practical insights into low-cost fabrication systems. Full article

The article examines how framing and actor identity structure attention in short-video politics using a country-level corpus from Ecuador. It assembles 4612 public TikTok videos from official accounts and politically salient hashtags, extracts multimodal text via automatic speech recognition and on-screen OCR, and constructs two continuous indices: a quality index (programmatic, efficacy-oriented content) and a populism index (antagonistic, people-versus-elite cues). Engagement is modeled as a fractional response (binomial GLM with logit link), with robustness checks using OLS on logit(ER) and Poisson counts with an offset for log(plays + 1). Models include affect (positive sentiment and anger), hour/day controls, and actor fixed effects (leader, creator, institution, party, and media). The indices display construct validity: quality aligns with positive/joyful tone and populism with anger. Net of controls, populism is positively and consistently associated with engagement across estimators; quality is small and often null or negative. Effects are heterogeneous: leaders gain under both frames, creators primarily under populism, and media modestly under populism, while institutions face penalties under both, and parties show limited returns. Monthly series reveal event-linked intensification of populism, and hashtag networks are modular, mapping onto institutional, partisan, and creator ecosystems. A design analysis identifies a non-populist pathway—benefit-first micro-explanations, concise captions, targeted hashtags, and joyful/efficacy affect—that raises engagement without antagonism. The study contributes a reproducible, open-source pipeline for survey-free, multimodal framing measurement and clarifies how persona × frame interactions and meso-level discursive structure jointly organize attention in short-video politics. Full article

Background/Objectives: Strain-level detection of bacteria is essential for applications such as diagnostics, food safety, and microbial monitoring. While 16S rRNA gene sequencing provides genus- or species-level resolution, it cannot reliably discriminate closely related strains. Whole-genome sequencing (WGS) offers high-resolution strain differentiation but remains impractical for routine detection due to cost and analytical complexity. This study aims to enable the translation of WGS data into accurate and cost-effective strain-specific PCR assays. Methods: We developed Erimin, a modular, shell-based bioinformatics pipeline for the automated identification of strain-specific genomic regions from short-read WGS data. Erimin systematically analyzes all available reference genomes for a given bacterial species in combination with sequencing data from a target strain. The workflow integrates reference-based read alignment, extraction of unmapped reads, de novo assembly, contig filtering and validation, genome annotation, and in silico PCR primer design and specificity evaluation. Results: Erimin was applied to Lactiplantibacillus pentosus whole-genome sequencing data to identify genomic regions specific to strain L33 through comparative analysis against a comprehensive set of reference genome assemblies representing multiple Lactiplantibacillus species. These regions were used for in silico PCR primer design and computational specificity assessment against non-target bacterial genomes, supporting discrimination of closely related strains. Conclusions: Erimin provides a structured computational approach for identifying strain-specific genomic regions from WGS data and for supporting the in silico design of PCR primers. This framework facilitates strain-level discrimination using targeted molecular assays. Full article

Digital transformation in public administration is shaped not only by technology but also by institutional expectations, legitimacy concerns and uneven local capacities. However, existing qualitative instruments rarely support structured reflection on how these conditions influence digital change. This study develops a modular, theory-informed focus group guide designed to help practitioners articulate institutional influences on municipal digital transformation. Using an Action Design Research framework, institutional concepts were embedded into the guide and iteratively refined across six focus groups with municipal actors. Through recursive Alpha and Beta cycles, the artifact evolved via authentic and concurrent evaluation, integrating practitioner feedback, visual scaffolds and accessible translations of theoretical constructs. Results show that the guide enabled participants to identify coercive, mimetic and normative pressures, surface assumptions across administrative roles and externalize institutional relationships. These patterns point to an institutionally dominant mode of artifact development in which interpretive engagement and legitimacy dynamics shape refinement. The study demonstrates that institutional theory can serve as a productive kernel for qualitative instrument design and offers transferable design principles for developing tools that support reflective, inclusive and socially aware digital transformation in public sector contexts. The resulting artifact, referred to as the Modular Institutional Instrument (MII), is made publicly available to support application in similar governance contexts. Full article

Agrivoltaics offer a sustainable solution to the growing competition between food and energy production. However, their adoption is often constrained by the design and operation challenges associated with optimising the complex trade-off between crop yield and photovoltaic (PV) output. Digital twins can mitigate these risks, yet most agricultural digital twins operate as fragmented digital shadows, lacking high-fidelity modelling, advanced simulation, and bidirectional control capabilities. This study presents a comprehensive, end-to-end digital twin framework to address these limitations. The framework integrates a high-resolution 3D orchard model, reconstructed via UAV photogrammetry, with a CesiumJS-based web interface linked to a modular IoT architecture built on Node-RED, Message Queuing Telemetry Transport (MQTT) protocol and InfluxDB for real-time monitoring and control. A PV simulation engine supports the design, simulation and optimisation of agrivoltaic systems. Bidirectional communication was validated through remote actuation of a physical solar tracker, demonstrating integration among the 3D environment, sensor data and control systems to achieve a closed-loop digital twin. Simulation analyses suggested that panel orientation and row spacing exert a dominant influence on crop-level light distribution. Simulation results demonstrated that a 90° azimuth configuration achieved the highest daily energy yield of 53.97 kWh but reduced peak crop-level irradiance to 205 W/m². In contrast, the baseline 0° configuration offered a balanced output of 40.86 kWh with a peak light availability of 338 W/m². The validated, interoperable digital twin architecture provides a reference model for the design, simulation, monitoring and control of an agrivoltaic system, reducing investment uncertainty and supporting sustainable food–energy co-production. Full article

The immersive, multisensory experiences offered by virtual reality have been transformative across multiple disciplines, enhancing practical and theoretical skills while increasing user motivation and learning. On the other hand, multi-agent systems have proven to be effective in facilitating the expansion and modularity of computer systems. This paper presents an application developed in a virtual reality environment based on multi-agent systems for the conceptual design of mechanical assemblies from primitives. As a main novelty, the primitives can be defined by the user of the application from a set of models and images, and an Excel document, without the need for programming knowledge, taking advantage of the possibilities offered by multi-agent systems. In addition, for each primitive, it is possible to define a set of geometric and dimensional modifications, as well as a set of position relations with respect to other primitives to generate mechanical assemblies. Full article

We present GANimate, a lightweight method for animating talking faces that leverages recent advances in latent-space manipulation of Generative Adversarial Networks (GANs). Unlike existing approaches based on computationally intensive diffusion models, transformers, or complex 3DMM representations, which are impractical for mobile and other low-resource edge devices due to high memory and compute demands, GANimate is designed for efficient operation on low-memory, low-compute edge devices. The model operates on 2D lip landmarks extracted from standard mobile vision-sensor inputs and requires no pre-training, making it easily integrable with any lip-landmark generator. Through an optimization process in the GAN feature latent space, these landmarks act as geometric constraints to animate a static portrait, producing realistic and expressive lip movements. To maintain stability and visual coherence across frames, we employ a Kalman filter to detect and track lip landmarks during video synthesis, enabling adaptive refinement and improved temporal consistency. The result is a compact and modular framework that bridges the gap between performance and accessibility in talking face synthesis, delivering high-quality and stable animations with minimal computational overhead. GANimate represents an important step toward lifelike, real-time avatars suitable for sensor-enabled and mobile human–computer interaction. Full article

DC–DC converters have become a key component in the structure of renewable energy systems, where an interface to increase and regulate the output voltage is required. This paper presents a modular non-isolated topology that achieves high voltage gain through interconnected switched-inductor cells. For the proposed converter, the design rules for sizing the energy storage elements for n number of cells are obtained, considering continuous, discontinuous, and boundary operation modes. Therefore, design equations are provided to support the precise selection of passive components according to voltage and power specifications. A nonlinear dynamic model is developed, and a model-based control scheme with inner current and outer voltage loops ensures robust regulation and fast transient response. Experimental validation on a 200 W prototype confirms theoretical predictions under steady-state and real-life dynamic conditions. Full article

Post-disaster reconstruction in resource-constrained contexts is often delayed by limited material supply, skilled labor, and planning capacity. Following the Mw 7.7 earthquake that struck near Mandalay, Myanmar, in March 2025, extensive housing damage and displacement underscored the need for economical and rapidly constructible reconstruction housing that can also support longer-term recovery. This study proposes a progressive and resident-modifiable housing scheme based on light-gauge steel framing, integrating the seismic design principle of strong-column–weak-beam to improve structural reliability during aftershocks and future events. The proposed system combines a standardized light-gauge steel framing (LGSF) structural frame with locally accessible enclosure and infill materials, allowing rapid assembly of an initial modular unit to meet urgent shelter needs while enabling progressive upgrading of façades and interior space over time to enhance habitability and resilience. Validation analyses focusing on construction efficiency and mechanical performance indicate that the strong-column–weak-beam LGSF scheme, when paired with local materials, offers favorable applicability in terms of buildability, cost-effectiveness, and seismic behavior under realistic conditions in Mandalay. The study provides a feasible technical solution and design approach for progressive post-disaster reconstruction housing in the region. Full article