Abstract: This article identifies, using a zero-shot method (Gen6d), the 3D-bounding box of a target far-distanced from a UAV. Furthermore, it infers the attached camera’s pose to the drone, based on the underlying training on the visual data. These visual data are used in a YOLO-framework to identify targets belonging to a class. The vertices of the orthogonal 3D-box are used in a visual-servoing scheme on the attached gimbal on UAV. The camera has a varying focal length (zoom) and the indirect objective is to move the UAV close to the target while reducing the zoom factor. Initially, the UAV starts with a large zoom-factor (36×) at a far distance (100m) from the target. The UAV approaches the target using the visual servoing scheme, while reducing its zoom at discrete steps and maintaining its focus. Experimental results indicate the efficiency of the proposed method.

Abstract: Environmental governance in the Global South increasingly unfolds within complex socio-technical systems characterized by fragmented institutional capacities, distributed sensing infrastructures, and high socio-ecological uncertainty. In this context, Digital Twins have emerged as a promising paradigm for integrating cyber-physical systems with decision intelligence, yet most implementations remain limited to industrial optimization or urban infrastructure management. This article proposes an architectural framework for Digital Twins oriented toward environmental governance by integrating Artificial Intelligence of Things (AIoT) monitoring networks with complex systems modeling and cybernetic governance principles. Methodologically, the study combines conceptual development grounded in systems science and the Viable System Model (VSM) with an illustrative empirical case study from the Caribbean Mining Corridor in Colombia, where a distributed AIoT environmental monitoring network operates within the Hub Ambiental del Caribe initiative. The proposed architecture links real-time environmental sensing, predictive analytics, and recursive governance structures to enable anticipatory environmental decision-making. The results demonstrate how Digital Twin infrastructures can function as cybernetic platforms that transform fragmented environmental data into actionable decision intelligence across institutional levels. By embedding feedback mechanisms, open environmental data governance, and participatory monitoring capacities, the framework supports adaptive management in highly dynamic socio-ecological contexts. The study concludes that Digital Twins designed as governance infrastructures—rather than purely technical replicas—can significantly enhance environmental decision support systems and foster climate justice-oriented transitions in vulnerable territories of the Global South.

Abstract: The production of biosolids in Brazil has increased due to the expansion of Sewage Treatment Plants, making these materials a sustainable alternative for agricultural use. Composed of high organic matter and nutrients such as nitrogen, phosphorus, calcium, and magnesium, biosolids have the potential to improve the physical, chemical, and biological properties of tropical soils, contributing to greater fertility, water retention, and microbial activity. National literature demonstrates that these materials can par-tially replace mineral fertilizers and assist in the recovery of degraded areas. On the other hand, the presence of contaminants still represents a challenge. Heavy metals such as Cd, Pb, Ni, and Hg generally appear in low concentrations, while Cu and Zn tend to approach the maximum limits established by CONAMA Resolution No. 498/2020. Regarding pathogens, the efficiency of sanitization depends on the treatment method employed. Emerging organic pollutants, including pharmaceuticals and hor-mones, have been detected, but still lack specific regulations in Brazil. Thus, although biosolids present high agronomic potential, their safe use requires adequate monitor-ing, improvement in controlling the origin of sewage, and advances in legislation, es-pecially regarding emerging organic pollutants.

Abstract: The fabrication of complex architectures remains a central challenge in 3D bioprinting, where low mechanical properties of hydrogels restrict the range of feasible geometries. Four-dimensional (4D) bioprinting can mitigate these limitations by introducing programmed structure shape-morphing in response to external stimuli. However, in most existing approaches, shape-morphing behavior is introduced after hydrogel formation, limiting the complexity of the resulting deformation. Here, a proof-of-concept strategy is presented, in which shape-morphing is directly encoded during fabrication. By modulating light exposure time layer-by-layer in vat photopolymerization, spatial variations in crosslinking density are introduced in situ within GelMA hydrogel constructs. Upon immersion in aqueous media, these variations generate differential swelling, leading to controlled bending of the printed structures. This approach enables the programming of deformation pathways at the printing stage, without requiring additional materials or post-processing steps. The morphing behavior was further supported by finite element simulations, which reproduced the experimentally observed deformation and enabled prediction of the shape change. Overall, this study demonstrates that swelling-driven actuation can be encoded during fabrication. Although demonstrated on simplified geometries, this approach provides a versatile framework for process-driven shape morphing programming and represents a step toward more spatially resolved and potentially volumetric 4D bioprinting strategies.

Abstract: The development of supersonic aircraft presents significant challenges in ensuring safety during early design stages, particularly for fuel tank systems exposed to extreme thermal and structural loads. Conventional document-based zonal safety analysis methods are limited in their capacity to identify hazards at the conceptual design phase. This study proposes an integrated framework combining computer-aided design (CAD) and model-based systems engineering (MBSE) to support early-stage zonal hazard analysis. The framework links spatial subsystem modelling with functional system architecture to enable iterative hazard identification and mitigation. Applied to the SA-24 Phoenix conceptual supersonic aircraft, the approach identifies critical risks, including fuel vaporization, over-pressurization, and structural fatigue, and evaluates mitigation strategies such as thermal insulation and redundant venting. Functional hazard analysis and fault tree analysis are used to assess failure scenarios and ensure compliance with EASA CS-25 requirements. Results indicate an estimated 40% reduction in risk priority number values for key thermal hazard pathways and a 25% reduction in conceptual design iteration time compared with conventional approaches. The findings demonstrate that CAD–MBSE integration offers a scalable and efficient methodology for early hazard identification, contributing to safer and more reliable supersonic aircraft design.

Abstract: Wire Arc Additive Manufacturing (WAAM) is a cost-effective and scalable technique for producing large metallic components; however, coarse columnar microstructures, strong crystallographic texture, and significant residual stresses limit its widespread adoption. In recent years, hybrid WAAM processes integrating deformation-based techniques have been developed to address these limitations. This review provides a comprehensive analysis of deformation-assisted WAAM, encompassing interlayer rolling, friction stir processing (FSP), hammer peening, laser shock peening, and ultrasonic vibration-assisted approaches. These hybrid techniques introduce additional thermomechanical parameters—strain, strain rate, and applied stress—that significantly influence microstructure evolution. The governing physical metallurgy mechanisms are discussed in detail, including dislocation accumulation, recovery, static and dynamic recrystallization, and severe plastic deformation. Studies from 2022 to 2025 are critically reviewed, highlighting the effectiveness of hybrid WAAM in promoting columnar-to-equiaxed grain transformation, reducing anisotropy, mitigating defects, and improving mechanical properties across aluminum, titanium, steels, and nickel-based alloys. The integration of auxiliary processes such as in-situ machining and heat treatment is also discussed. This review establishes a process-structure-property framework for hybrid WAAM and provides guidance for the development of advanced additive manufacturing systems capable of delivering near-net-shape components with microstructures and properties approaching those of wrought or forged counterparts.

Abstract: Rapid solidification by melt‑spinning produces aluminum alloys with extremely refined microstructures but also introduces strong structural gradients across the ribbon thickness. In this work, the microstructural evolution of a rapidly solidified Al‑Cu‑Li‑Mg‑Sc‑Zr alloy was investigated during model homogenization using in‑situ STEM heating experiments and correlated with bulk electrical‑resistivity measurements. The as‑cast ribbons exhibit two distinct solidification zones: a near‑contact region consisting of columnar cells containing fine Cu‑rich spherical precipitates, and a central region composed of larger eutectic cells enriched in Al₂Cu and Al₇Cu₂Fe phases. Stepwise in‑situ annealing between 200 °C and 550 °C reveals a sequence of transformations, including matrix depletion due to precipitation of strengthening phases, coarsening and dissolution of primary phases, and the formation of Al₃(Sc,Zr) dispersoids. Above 500 °C, rapid dissolution of primary phases followed by their coagulation into a limited number of stable grain‑boundary particles eliminates the original two‑zone structure and results in a fully homogenized ribbon. Ex‑situ annealing confirms that the resulting microstructure is uniform across the ribbon thickness and enables consistent precipitation strengthening during artificial aging. Microhardness measurements from both ribbon surfaces reveal identical peak‑aged hardness, validating the effectiveness of the short‑time homogenization strategy for rapidly solidified Al‑Cu‑Li‑Mg-based alloys.

Abstract: Einstein's principle of the invariance of the speed of light in a vacuum is a core of modern physics, but the ISO 13690:2008 standard is only applicable to the visible light band, and traditional measurements have not verified the universality of vacuum permittivity and permeability across all bands. This study combs the limitations of historical precision measurements of the speed of light, derives the wavelength dependence of and in the interstellar medium based on quantum electrodynamics (QED) and Maxwell's equations, and proposes a micro-scale measurement scheme of "three-stage path splitting + two-dimensional compensation". Taking the 2026 Jupiter occultation as the carrier, a multi-band synchronous observation experiment is designed to predict the multi-band arrival sequence and time difference, providing theoretical and technical support for the refinement of light speed measurement and the expansion of the applicable boundary of relativity.This study provides a feasible precision metrology framework for high-accuracy light speed measurement in complex media, with potential engineering applications in astronomical observation and electromagnetic parameter calibration.

Abstract: One of the most promising approaches for replacing conventional power plants during the transition to clean energy is the conversion of existing coalfired power plants (CPPs) into nuclear power plants. This strategy offers numerous ecological and economic advantages. However, integrating a nuclear reactor with a steam turbine originally designed for a coal plant is far from trivial and involves significant technical challenges. The purpose of this work is to analyze and evaluate various options for coupling a HighTemperature GasCooled Small Modular Reactor (HTGR SMR) with a potentially suitable subcritical steam turbine from an existing CPP, thereby creating several repowering configurations. The main difficulties stem from the fact that the turbine was designed to operate with live steam at lower flow rates, temperatures, and pressures than those typically provided by an HTGR SMR. In addition, the feedwater temperature and pressure requirements for the HTGR SMR steam generator differ substantially from those in a CPP, leading at best to additional efficiency losses. Moreover, the overall thermal cycle layouts of the two systems are fundamentally different. Despite these challenges, technically feasible combinations can be achieved. However, determining which option is the most economically viable depends on numerous additional factors, including the specific characteristics of the individual CPP and the regulatory framework of the country in which it operates.

Abstract: Acoustoelasticity describes the relationship between elastic wave velocities and the initial stress present in media. Most of the current research in this area is focused on elastic waves propagating in naturally isotropic media with initially uniaxial stress and confined the solution of acoustoelastic problem to the Cartesian coordinate system, which limits the application for the acoustoelasticity theory. In this paper, to make up for this deficiency, an acoustoelastic formulation, i.e. the equation of motion for incremental displacement with explicit dependency on initial stress or strain, is developed based on the general theory of incremental deformation. This formulation can be applied to material with any symmetricity, initial stress with any number of principle axis. Also, it can be expressed in any form of coordinate system for its tensorial nature. Furthermore, to the knowledge of authors, there is no integrated cylindrical expression for acoustoelastic theory, an expansion of the formulation in a cylindrical system for an orthotropic material is given in detail for the convenience of application, such as cylindrical waves.

Abstract: Globally, the burden of breast cancer remains high as it is the most prevalent malignancy among women and a major contributor to cancer mortality, with therapeutic success often limited by drug resistance, treatment toxicity, and tumor heterogeneity. Cold atmospheric plasma (CAP), a partially ionized gas enriched in reactive oxygen and nitrogen species (RONS) electromagnetic waves and ultraviolet radiation, has emerged as a selective antitumor therapy, inducing cancer-specific cytotoxicity while sparing normal tissue. Here, we review the mechanisms of CAP action against breast cancer, including RONS-mediated oxidative stress, mitochondrial disruption, apoptosis, immunogenic cell death, and suppression of metastatic and angiogenic pathways. Notably, This approach selectively targets therapy-resistant breast cancer stem cells and sensitizes the highly aggressive forms, particularly triple-negative breast cancer (TNBC). Its synergy with drug therapy, radiotherapy, immunotherapy and surgery further broadens therapeutic potential. Advances in delivery platforms, such as plasma-activated media, nanoparticles, and hydrogels, address CAPs instability and enhance tumor penetration. Despite promising preclinical results, clinical translation faces barriers such as the short half-life of RONS, device standardization, and unresolved immunomodulatory effects. Overcoming these challenges through interdisciplinary collaboration and optimized protocols may unlock the potential of CAP for precision oncology.

Abstract: Structural reanalysis involves repeated evaluation of structural responses under iterative design changes. It is a major computational burden in structural optimization, sensitivity analysis, and health monitoring. The three-layer architecture, which comprises the stiffness, displacement, and force layers, is motivated by the governing structural mechanics relationship F=K·U, which establishes stiffness and displacement as natural intermediate quantities for predicting internal forces. This physics-informed hierarchy reduces dependence on large training datasets while preserving predictive accuracy across all response quantities. The framework predicts member-level stiffness statistics, nodal displacements, and internal forces through three sequential layers: stiffness, displacement, and force. Each layer enriches the feature set of the layer above. Sensitivity-based secondary inputs are derived analytically from closed-form expressions relating cross-sectional dimensions to stiffness and displacement changes. This embeds structural mechanics knowledge directly into the feature engineering process without additional analyses. Member stiffness matrices are recovered as submatrices of the global stiffness matrix, encoding inter-member structural context into each member’s representation. The framework is implemented on a six-floor, three-bay reinforced concrete frame of 42 members. Training uses 1,890 data points from 45 finite element iterations. The Random Forest model achieves R² scores of 0.99, 0.98, and 0.91 for axial force, shear force, and bending moment respectively on unseen validation data. Once trained, the framework predicts any number of design iterations in a single inference pass. This substantially reduces the computational cost of reanalysis-based workflows. The proposed framework offers a scalable, interpretable, and physics-consistent alternative to both classical reanalysis methods and purely data-driven surrogate models, with direct applicability to structural size optimization and structural health monitoring workflows.

Abstract: Currently, the applications of Large Language Models (LLMs) have expanded to diverse areas, from code generation to the medical diagnosis of various pathologies. This work aims to explore what LLMs can achieve using information from CFD simulations of turbulent flow in a manifold, and to determine whether users or students can employ them as a guide for conducting this type of analysis. Through a case study, it is intend to investigate the following aspects of LLMs: 1) the type of information they handle regarding the behavior of turbulent flow within a manifold, 2) whether they identify the boundary conditions necessary to perform a CFD simulation in a manifold, 3) their capacity to provide recommendations for improving CFD simulations based on the results obtained, 4) whether they can predict the results of CFD simulations based on previous results, and 5) whether users or students can use them as a guiding tool for performing CFD simulations. Among the findings, it was discovered that the LLM used has sufficient information on turbulent flows within a manifold and can make recommendations to improve the results of CFD simulations. It was also identified that LLMs offer a user-friendly environment and that it is possible to predict CFD simulation results by varying the manifold boundary conditions.

Abstract: In bipedal stance the central nervous system implements a pre-programmed ankle strategy to maintain upright balance and respond to internal perturbations. This strategy comprises a synchronized common neural drive delivered to synergistically grouped muscles. This study evaluated the normalized mutual information (MI) between surface electromyographic (EMG) signals of unilateral and bilateral homologous muscle pairs of the lower legs during various quiet standing tasks in normal healthy adults. The leg muscles examined included the right and left tibialis anterior (TA), medial gastrocnemius (MG), and soleus (S). MI, an information-theoretic measure that quantifies the reduction in uncertainty in predicting a signal from another known signal,, was estimated using MATLAB toolbox Mutual Information Distance and Entropy Reduction (MIDER). This method for inferring network structures from shared information between two signals was applied to pairs of filtered EMG signals in the alpha (8 – 13 Hz), beta (13 – 30 Hz), and gamma (30 – 100 Hz) neural frequency bands for feet together and feet tandem stances, under eyes open and eyes closed conditions. Results showed that normalized MI was greater in the medial gastrocnemius and soleus muscle pairs across the beta, lower gamma, and upper gamma frequency bands in the tandem standing posture under both eyes open and eyes closed conditions, and generally increased in antagonistic muscle pairs in less stable standing positions. It appears that functional muscle synergies are more important than limb dominance in tandem standing. Significant inter-trial and inter-participant variability is consistent with biological differences and control of a complex system. Our results suggest that the use of MI analyses in the clinical testing of tandem standing tasks might be a useful adjunct for persons with standing balance impairments.

Abstract: Just energy transitions in the Global South unfold under conditions of institutional fragmentation, fiscal constraints, and high socio-ecological turbulence, making governance capacity a critical bottleneck for effective decarbonization and climate justice. This study proposes the Cybernetic Environmental Hub (CEH) framework, which extends the Viable System Model (VSM) to sustainability governance by integrating AIoT-enabled environmental monitoring, Early Warning Systems, decentralized data governance, and justice-centered institutional design. Methodologically, the research adopts a hybrid conceptual–empirical approach combining theoretical development with participatory territorial diagnostics. Empirical validation is illustrated through a case study in the Caribbean Mining Corridor, where socio-ecological challenges were collected through participatory innovation workshops, thematically coded, and mapped onto the five VSM subsystems to identify systemic “variety gaps.” The analysis demonstrates that fragmented operational initiatives coexist with weak meta-systemic coordination, limiting adaptive capacity in energy transition processes. The CEH architecture addresses these deficiencies by embedding AIoT sensing, federated learning, blockchain-based coordination, and Early Warning Systems within recursive governance structures. Additionally, the study introduces a Territorial Governance Maturity Model (H1–H3) to diagnose systemic learning capacities and transition readiness across technological, institutional, data governance, and justice dimensions. The findings suggest that cybernetic environmental hubs can function as socio-technical infrastructures enabling coordinated, adaptive, and justice-centered energy transitions in the Global South.

Abstract: Robotic assistance in minimally invasive surgery has significantly improved precision and dexterity; however, many supportive tasks, such as blood aspiration, still rely on manual operation. This work presents the design and implementation of an autonomous robotic aspirator capable of detecting and removing intraoperative bleeding without continuous human intervention. The proposed system integrates a perception module based on a convolutional neural network for real-time blood segmentation, a task planner for high-level actions execution, and a control strategy based on artificial potential fields for autonomous navigation. Additionally, a mixed-reality human–robot interaction interface is incorporated to enable system supervision and seamless transition to teleoperation when required. The system was experimentally validated with a set of in-vitro experiments under three representative bleeding scenarios, evaluating four suction strategies based on the computation method for the target selection. Results demonstrate fast reaction times (below 0.04 s) and high blood removal rates (above 80% in all cases). The comparative analysis reveals that the performance of the suction strategies is scenario-dependent and highlights a trade-off between suction efficiency and removed area. These findings support the feasibility of autonomous robotic aspiration and provide insights into the design of adaptive strategies for surgical assistance, contributing toward increased autonomy and improved workflow efficiency in minimally invasive procedures.

Abstract: Reliable assessment of small-strain soil stiffness is essential for geotechnical site characterization and for analysing the behaviour of embankments and other earth structures. Surface-wave methods provide an efficient non-destructive means of estimating shear-wave velocity profiles; however, their application is limited by the non-uniqueness of the inversion process. This paper presents a multimodal inversion procedure for Rayleigh-wave dispersion curves based on the particle swarm optimization algorithm. The procedure involves the calculation of theoretical dispersion curves for a horizontally layered medium and their matching with experimental data through a global search scheme. The proposed procedure was first verified using two synthetic soil profiles, and its robustness was further assessed by considering perturbations of the theoretical dispersion curve of up to 10%. Particular attention was given to the influence of higher modes on the inversion results. The results show that including higher modes leads to a more accurate and reliable determination of shear-wave velocity profiles than an inversion based solely on the fundamental mode. The procedure was subsequently validated on a transverse embankment profile using an experimental MASW dispersion curve and comparison with SCPT results. Good agreement was obtained, and the eight-layer model proved to be a good compromise between accuracy and model complexity. The proposed multimodal approach therefore represents a reliable tool for the geotechnical characterization of layered soil profiles.

Abstract: This paper presents a comprehensive experimental and simulation study on the stick–slip characteristics of pneumatic cylinders operating at low velocities. A pneumatic servo experimental system is constructed to systematically investigate stick–slip motion by measuring piston position, piston velocity, pressures in the two-cylinder chambers, and friction force. Extensive experiments are conducted on three pneumatic cylinders of different types and sizes to examine the influences of airflow rate, air source pressure, external load, and initial piston position on stick–slip behavior. Based on experimental observations, a complete mathematical model of the pneumatic servo system is developed. Unlike conventional approaches that simulate stick–slip motion using friction models driven solely by piston velocity, the proposed system-level model explicitly describes the entire dynamic process from valve control inputs to airflow, pressure evolution in the cylinder chambers, piston motion, and friction force. In addition, a new dynamic friction model is proposed by improving the revised LuGre friction model through the incorporation of a dwell-time-dependent static friction force, which is experimentally observed to play a critical role in governing stick–slip motion. Simulation studies are performed using both the proposed friction model and the revised LuGre friction model. The simulated results are systematically compared with experimental data for all tested cylinders. The results demonstrate that the proposed system model with the new friction formulation significantly improves the prediction of stick–slip characteristics, including the number of stick–slip cycles and the evolution of pressure and friction force, compared with conventional friction-model-based simulations.

Abstract: Introduction: Portable non-enzymatic electrochemical glucose sensors offer potential for decentralized healthcare and medical education; however, their integration into clinically meaningful teleconsultation workflows remains limited. This study presents the functional integration of a portable copper-modified electrochemical glucose sensor into a rural web- and Android-based telemedicine platform within a simulation-based medical education framework. Materials and Methods: Screen-printed carbon electrodes were electrochemically activated and modified via copper electrodeposition. Electrochemical characterization was performed using cyclic voltammetry to identify the glucose oxidation region and chronoamperometry for quantitative detection. Glucose solutions in PBS (pH 10) were measured using 70 µL samples, and the resulting signals were converted into glucose values (mg/dL) through a calibration model and incorporated into simulated gynecological teleconsultation workflows. Results: The sensor exhibited a stable amperometric response at +0.60 V, with a linear range of 3.125–50 mM (R2 = 0.9822), an area-normalized sensitivity of 0.061 µA·mM−1·cm−2, and a limit of detection of 1.39 mM. Implementation within the simulation scenario (n = 26) demonstrated 69% high/very high perceived usability and 88% high/very high educational value. Conclusion: These results support the feasibility of integrating portable electrochemical sensing into teleconsultation-based training environments and establishing a practical framework for future validation and deployment in rural telemedicine applications.

Abstract: To address the demanding requirements for high gain, wide bandwidth, and stable circularly polarized (CP) radiation in Wireless Local Area Network (WLAN) applications, this paper proposes and implements a broadband circularly polarized array antenna operating in the 2.4 GHz ISM band. The design employs a coplanar waveguide (CPW)-fed broadband CP monopole antenna as the radiating element. A sequential rotation (SR) technique is utilized to form a four-element array. Furthermore,​ a windmill-shaped defected ground structure (DGS) is innovatively introduced to further extend the bandwidth. The antenna is fabricated on a low-cost FR4 substrate with overall dimensions of 126 mm × 126 mm × 1 mm. Simulation and measurement results show that the array antenna achieves a -10 dB impedance bandwidth of 1.22–2.78 GHz (87.1% relative bandwidth) and a 3-dB axial ratio (AR) bandwidth of 1.85–2.66 GHz (35.0% relative bandwidth), completely covering the target band. At the center frequency of 2.2 GHz, the antenna exhibits left-hand circular polarization (LHCP) radiation, with a measured peak gain of 8.2 dBi and a cross-polarization isolation better than 15 dB. To verify its performance advantages in practical systems, the designed antenna was integrated into a ZigBee wireless communication system for data transmission testing. The results indicate that, in a complex multipath environment, the system employing the proposed antenna achieves a significantly lower packet loss rate (approximately 3.0%) compared to using a traditional linear-polarized whip antenna (19.0%), effectively optimizing the wireless link quality. The designed antenna features wide bandwidth, high gain, and strong anti-interference capability, making it suitable for WLAN, Internet of Things (IoT), and other wireless communication systems.