Search Results (3,044)

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

This study designs a novel modular prefabricated concrete foundation for cable termination supports in the power industry. This foundation is composed of prefabricated components including concrete segmented foundations, strut and connector via bolted connections, featuring convenient construction and a reduction of nearly 40% in concrete consumption. The finite element model was established using FEA software (Version ABAQUS 2020), and an economical and stable mesh size was selected through mesh convergence analysis. The settlement and bearing capacity of the foundation under axial compression were analyzed. Results show that this prefabricated foundation remains in the elastic stage under service load, with uniform settlement and excellent integrity. The stress of reinforcement bars and bolts is much lower than the material yield strength, and the concrete has ignorable damage. In addition, the safety margin is sufficient, and the force transfer path is clear. The research results can improve the prefabricated system for power facilities and provide technical support for the green and efficient construction of cable termination support foundations. Full article

This study investigates modular low-rise shear walls by designing and fabricating four in-plane loaded specimens at a scale ratio of 1:2.7. Quasi-static low-cycle reversed loading tests combined with numerical simulations were systematically conducted to examine the effects of the type and location of post-cast strips on the seismic performance of shear walls. The experimental program comparatively analyzed crack development patterns, failure modes, and seismic performance indices of specimens with four construction configurations: without post-cast strips, with only a horizontal post-cast strip, with a horizontal post-cast strip combined with an eccentrically placed vertical post-cast strip, and with a horizontal post-cast strip combined with a centrally placed vertical post-cast strip. The results indicate that specimens without post-cast strips exhibit uniformly distributed and highly penetrative cracks, characterized by typical global shear failure. The horizontal post-cast strip restricts downward crack propagation, leading to crack concentration above the post-cast strip, whereas the combined arrangement of horizontal and vertical post-cast strips promotes dispersed crack development and significantly alleviates excessive local damage concentration. The specimen with a centrally located vertical post-cast strip exhibited the best overall seismic performance, characterized by full hysteretic curves, the largest cumulative energy dissipation, and the most gradual stiffness degradation, whereas the specimen with only a horizontal post-cast strip showed relatively poor energy dissipation capacity and ductility. The finite element model established based on the experimental results accurately reproduces the mechanical responses and failure characteristics of all specimens, validating the mechanism by which post-cast strips improve wall performance through stress dispersion and crack development regulation. The findings demonstrate that a rational arrangement of post-cast strips, particularly the adoption of a centrally placed vertical post-cast strip, can effectively enhance the seismic performance of modular low-rise shear walls. Full article

Current national-scale building stock models mainly focus on structural materials, overlooking the significant resource potential of Mechanical, Electrical, and Plumbing (MEP) systems. These systems are resource-intensive and contain standardized components with high-value materials such as copper and steel, yet their potential remains largely untapped due to fragmented data. This study introduces the novel systematic framework to estimate MEP components at high granularity and national scale. It integrates harmonized public data, machine-learning imputation (>90% accuracy under sparse conditions), and parametric rules reflecting building type, energy system, and construction decade. A Swiss case study yields scalable material stock estimates and lifespan-based turnover projections, showing strong consistency with existing GHG benchmarks. The framework highlights contrasting patterns across regions and building types, indicating where policy and industry can upscale reuse and recovery. Its modular design enables transferability and integration with circular economy planning and material-efficiency targets. Full article

High-fidelity 3D reconstruction of human-sized objects typically requires multi-sensor scanning systems that are expensive, complex, and rely on proprietary hardware configurations. Existing low-cost approaches often rely on handheld scanning, which is inherently unstructured and operator-dependent, leading to inconsistent coverage and variable reconstruction quality. This limitation necessitates the need for a controlled, repeatable, and affordable scanning method that can generate high-quality data without requiring multi-sensor hardware or external tracking markers. This study presents a marker-less scanning platform designed for human-scale reconstruction. The system consists of a single structured-light sensor mounted on a vertical linear actuator, synchronised with a motorised turntable that rotates the subject. This constrained kinematic setup ensures a repeatable cylindrical acquisition trajectory. To address the geometric ambiguity often found in vertical translational symmetry (i.e., where distinct elevation steps appear identical), the system employs a sensor-assisted initialisation strategy, where feedback from the rotary encoder and linear drive serves as constraints for the registration pipeline. The captured frames are reconstructed into a complete model through a two-step Iterative Closest Point (ICP) procedure that eliminates the vertical drift and model collapse (often referred to as “telescoping”) common in unconstrained scanning. To evaluate system performance, a modular anthropometric benchmark object representing a human-sized target (1.6 m) was scanned. The reconstructed model was assessed in terms of surface coverage and volumetric fidelity relative to a CAD reference. The results demonstrate high sampling stability, achieving a mean surface density of $0.760{\mathrm{points}/\mathrm{mm}}^2$ on front-facing surfaces. Geometric deviation analysis revealed a mean signed error of −1.54 mm ($\sigma =$ 2.27 mm), corresponding to a relative volumetric error of approximately 0.096% over the full vertical span. These findings confirm that a single-sensor system, when guided by precise kinematics, can mitigate the non-linear bending and drift artefacts of handheld acquisition, providing an accessible yet rigorously accurate alternative to industrial multi-sensor systems. Full article

The Support System with Vertical Retractable Mechanism (SSVRS) is an advancement in telescopic technology that replaces continuous threaded or fluid-dependent interfaces with an internal stepped mechanism based on geometric mechanical interference. This coaxial design uses an integrated pin that engages with discrete grooves, enabling rapid height adjustments and positioning speeds that are significantly faster than those of traditional mechanisms. Unlike friction-based systems that are prone to slipping under dynamic loads, the SSVRS provides millimeter-level precision and exceptional stability, even in vibrational environments. The SSVRS’s versatility stems from its parametric modular design, which scales from lightweight domestic fixtures to heavy-duty industrial machinery by customizing material selection—ranging from high-strength steel to glass fiber-reinforced nylon—and slot configuration. Specifically, vertical slot arrangements facilitate rapid movement, and spiral geometries allow for high-precision alignment. Furthermore, the SSVRS optimizes long-term operational efficiency and sustainability through low maintenance requirements, minimal moving parts, and the use of recyclable materials. By combining high-speed positioning, robust structural integrity, and adaptive modularity, the SSVRS provides a high-performance, concrete alternative to current mainstream linear modules and traditional support structures. Full article

Design of large-scale power systems is getting increasingly complex nowadays from an operational and reliability standpoint due to the uncertainties associated with the injection of renewables and consumption of load. These uncertainties pose a great challenge in gauging and subsequently obtaining reliable system-level assurances from subsystem-level guarantees, particularly in mission-critical systems such as those seen in data centers. We propose a formal and modular framework of probabilistic assume–guarantee contracts (PAGCs) for compositional reasoning and control of uncertain power systems, motivated by the need for resilient and verifiable operation in data center power networks. In contrast to classical contracts, which require absolute satisfaction of assumptions and guarantees, PAGCs allow for high-probability satisfaction under system uncertainty and variability. We formalize the syntax and semantics of PAGCs, develop soundness and compositionality theorems, and demonstrate their applicability to power grid components such as generators, transformers, circuit breakers, and loads. Given the current approval bottlenecks in interconnection requests, a growing number of data center operators are opting for islanded generation configuration. A case study on such a modular islanded data center power system is presented to validate the proposed theory. The proposed PAGC application in power networks is promising in several aspects to solve several existing open problems in distributed systems, particularly in future large-scale smart power networks. Full article