Abstract: This review aims to place open, laparoscopic, robotic and image-guided robotic surgical interventions in the context of complex medical surgeries, taking into account patient well-being, staff effort and task reliability. It deduces the specificities of each technique and subsequently focuses on image-guided interventions and their practice in staff training, preparation and implementation of a possible autonomous intervention. These complex interventions are intended to be minimally invasive (MI), precise and safe therapies. The accuracy of robotic positioning could be improved by reductions in complexity and un-certainty involved in the intervention procedure. These can be achieved by matching the real controlled procedure and its virtual replica. The contribution discusses considera-tions for staff training and/or planning of surgical interventions using real and virtual phantoms, and the use of augmented matched digital twins (DT) for real interventions. The different topics presented in the article, although explicit, are reinforced by examples from the literature to facilitate a deeper understanding. The results of this review highlight the importance of robotic imaging-assisted procedures involving MI, nonionizing and precise interventions. Moreover, DTs currently integrated in different health applications, combined with digital tools, could provide an effective solution for the management of such interventions.

Abstract: The global campaign to reach net zero will necessitate the use of hydrogen as an effi-cient way to store renewable electricity at large scale. Methane pyrolysis is rapidly gaining traction as an enabling technology to produce low-cost hydrogen without di-rectly emitting carbon dioxide. It offers a scalable and sustainable alternative to steam reforming, whilst being compatible with existing infrastructure. The process most commonly uses thermal energy to decompose methane (CH4) into hydrogen gas (H2) and solid carbon (C). The electrification of this reaction is of great significance, allow-ing it to be driven by excess renewable electricity rather than fossil fuels, and elimi-nating indirect emissions. This review discusses the most recent technological ad-vances in electrified methane pyrolysis and the relative merits of the mainstream re-actor technologies in this space (plasma, microwave, fluidised bed, and direct resistive heating). The study also examines the economic viability of the process, considering energy costs, and the market potential of both turquoise hydrogen and solid carbon products. Whilst these technologies offer emissions-free hydrogen production, chal-lenges such as carbon deposition, reactor stability, and high energy consumption must be addressed for large-scale adoption. Future research should focus on process opti-misation, advanced reactor designs, and policy frameworks to support commercialisa-tion. With continued technological innovation and sufficient investment, electrified methane pyrolysis has the potential to become the primary route for sustainable pro-duction of hydrogen at industrial scale.

Abstract: Mulberry silk production in West Bengal and north-eastern India, primarily involving bivoltine and multi-bi hybrid silkworm varieties, is a cornerstone of the sericulture industry. However, seasonal climatic variations, characterized by elevated temperatures and humidity, significantly affect cocoon quality, posing challenges for silk reeling efficiency and productivity. This study examines the influence of seasonal variations on the quality and reeling performance of bivoltine and multi-bi hybrid silk cocoons in these regions. Key parameters, including filament length (FL), non-broken filament length (NBFL), and shell ratio, were analysed over five seasons. Results indicate a marked decline in cocoon quality during unfavourable seasons (June–July, August–September), with bivoltine cocoons exhibiting greater sensitivity through reductions in FL, NBFL, and reelability compared to the more resilient multi-bi hybrids. These seasonal impacts undermine reeling efficiency and silk yarn quality. The findings emphasize the importance of adaptive rearing practices and technological innovations, such as multi-end reeling machines with enhanced speed and evenness control, to bolster productivity and address climatic challenges. This research provides critical insights for improving the sustainability and economic viability of sericulture in West Bengal and north-eastern India.

Abstract: This study presents a methodology for integrating Asset Performance Managements (APM) and Asset Investment Planning (AIP) platforms for Joint Optimization of Productivity and Reliability using simulation experiments. This research combines data from an APM, which provides information on equipment reliability, and a simulation module of an AIP software that offers detailed technical data of a set of alternative equipment in a sort of catalog. Criteria such as availability, criticality, utilization levels, and the number of failures, based on historic stored data, is used to evaluate different equipment configurations in the APM platform, while productivity and efficiency of existing equipment is captured from the configuration module on the AIP platform. Key aspects of this work point to the possibility of applying it in two main stages of a system life cycle: the initial stage, where the project is in its conceptual design phase, and the analyses and optimization efforts are performed without any economic or budgetary limitations, ensuring an efficient selection of equipment before its actual implementation. And the second stage, in which the plant is already in operation, where newer strategies or configurations are considered to prioritize operational adjustments and minor optimizations due to the inherent constraints of reliability, failure rates, and maintainability aspects. Through the development of a specifically developed model, which is applied to ensure optimal selection of equipment and configurations, the proposed system suggests combinations of equipment that ensure operational continuity and efficient production performance without exceeding energy consumption limits or compromising productivity. The result is a system capable of generating configurations that maintain or improve productivity while simultaneously ensuring an increase in reliability.

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Environmental monitoring refers to the tools and techniques designed to observe an environment, characterize its quality, and establish environmental parameters, to accurately quantify the impact an activity has on an environment. A warmer climate may result in lower thermal efficiency and reduced load-including shutdowns in thermal power plants. It is found in research that a rise in temperature of 1°C reduces the supply of nuclear power by about 0.5% through its effect on thermal efficiency. A drastic change in air pressure also indicates there could be a significant climate change. In the event of a radiological release accident, environmental data is required to reduce radiation exposure to humans. That’s why environmental monitoring is very important for a nuclear power plant. It can be a crucial matter for the industries also because environmental monitoring helps industries operate responsibly, minimize negative impacts on the planet, and contribute to a more sustainable future. An IoT-based system can do environmental monitoring. Anyone using an IoT-based system can get environmental data like temperature, pressure, humidity, etc. Here the projected system delivers sensor data which are got from the environment to an API called ThingSpeak over an HTTP protocol and allows storing of data. The proposed system works well and it shows reliability. The prototype has been used to monitor and analyse real-time data using graphical information of the environment.

Abstract: This paper comprehensively reviews research on the buckling failure performance of curved shell structures. It covers various aspects, including industrial applications, the development of buckling theory and guidelines, common failure modes, and recent advancements in experimental and numerical analysis. The paper also discusses the role of imperfections in triggering buckling and outlines potential future research directions to enhance the design and safety of lightweight structures. The study identifies research directions and future tasks concerning curved shells by suggesting several areas (such as experimental, numerical, analytical, and control variables) that require further investigation and utilisation.

Abstract: The article deals with the creation of water engines for mobile micro-hydroelectric power plants and pumps with a capacity of 1-10 kW, operating at the expense of the energy of naturally flowing water, i.e. development of methods of using the energy of flowing water, without the construction of hydraulic structures and dams, without causing harm to the environment. Also, an experimental model of a water engine and the results of experimental studies are presented.

Abstract: This work presents the design of a system of a highly flexible pseudorandom number generator system (PRNG) incorporating both conventional and neuro-generators. The system integrates four internal generators with different conditions, to produce new output sequences with an adequate bits distribution and complexity. Two generators function at a frequency of 100 MHz with adjustable frequency settings, while two neuro-generators employ impulse neurons with distinct behaviours at 4 kHz, also modifiable. The proposed, system meets 12 statistical randomness based on NIST’s National Institute of Standards and Technology of U. S. test suite, including the Frequency test, Binary Matrix Rank test, Linear Complexity test, Random Excursion test, among others. Each resulted in a P-Value greater than 0.01, confirming the pseudo-randomness of the generated sequences. The system is implemented on an FPGA Field Programmable Gate Array Virtex 7xc7vx485t-2ffg1761, with a low occupancy percentage, demonstrating its feasibility for various applications.

Abstract: Natural surfaces offer valuable insights into the mechanisms of hydrophobicity. Characterizing these surfaces through the contact angle of droplets provides a direct quantification. The widely used but debated Cassie-Baxter model attempts to relate contact angle with surface topography and liquid wetting properties. Surface tension establishes an initial chemical affinity in wetting, and surface roughness is known to enhance hydrophobicity. However, research lacks standardized metrics to explain how topography influences this behavior. In this study, we introduce a new model for droplet balance that complements the Cassie-Baxter model by considering the latest research findings on the significant effect of the triple line on droplet contact angle. We characterized the surfaces of accessible leaves using ISO standard roughness parameters, contact angle measurements, and surface topography analysis through confocal microscopy. Statistical screening of roughness parameters identified those with high correlation to contact angle model parameters, enabling the quantification of the effect of standard metrics of surface topography on contact angle through the model. Our results provide an enriched contact angle model that incorporates parameters capable of linking contact angle with the assessment of surface topography measured through engineering metrics, paving the way to emulate natural hydrophobicity on engineered surfaces.

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This manuscript presents a real-time monitoring system for urban garbage levels using Time-of-Flight (ToF) sensing technology. The experiment employs the VL53L8CX sensor, which accurately measures distances, along with an ESP32-S3 microcontroller that enables IoT connectivity. The ToF-Node IoT system, consisting of the VL53L8CX sensor connected to the ESP32-S3, communicates with an IoT gateway (Raspberry Pi 3) via Wi-Fi, which then connects to an IoT cloud. ToF-Node communicates with IoT gateway using Wi-Fi and after with IoT cloud, also using Wi-Fi. This setup provides real-time data on waste container capacities, facilitating efficient waste collection management. By integrating sensor data and network communication, the system supports informed decision-making for optimizing collection logistics, contributing to cleaner and more sustainable cities. The ToF-Node was tested in four scenarios, with a PCB measuring 40 x 18 x 4 mm and an enclosure of 65 x 40 x 30 mm. Results demonstrate the effectiveness of ToF technology in environmental monitoring and the potential of IoT to enhance urban services. For detailed monitoring, additional ToF sensors may be required. Data collected is displayed in the IoT cloud to better monitoring and can be view level and volume. The ToF-Node and the IoT gateway have a combined power consumption of 153.8 mAh

Abstract: In the context of global carbon peak and carbon neutrality, this work proposes a carbon accounting method for construction engineering based on life-cycle assessment (LCA) and construction cost quota. By incorporating China’s national standards, relevant databases and publications, three major global carbon accounting databases—ICE, EU-EFDB, and IPCC-EFDB—were expanded to enable each database to independently perform full life-cycle carbon accounting for specific construction projects in China. The method is capable of flexibly selecting different databases and quantifying the carbon emissions of construction projects, by directly importing bill of quantities. Finally, a web-based carbon accounting tool was developed, and three databases were used to conduct full life-cycle carbon accounting on three real-world construction projects, to verify the feasibility of the proposed method and compare the carbon accounting results across different databases. Our study showed that, although there were discrepancies in carbon emission results across different stages and processes for the construction projects, the proportions of carbon emissions at each stage and process were relatively consistent.

Abstract: This paper presents a comprehensive review of advancements in road surface classification technology utilizing automotive microwave sensors, covering both active radar and passive radiometer, along with data analysis techniques. Accurate knowledge of road surface type and condition plays an important role in enhancing driving safety, particularly in the goal of achieving fully autonomous driving across various terrains. The paper begins with a comparative analysis of different sensing technologies, including microwave, optical, LIDAR, and sonar sensors. It subsequently highlights the distinct advantages of microwave sensors, particularly in scenarios with low visibility, where other sensing methods are not sufficiently effective. The analysis of road surface classification methods using radar or radiometer data includes both technical aspects (signal parameters, sensor type, position and number of antennas, signal polarization, etc.) and classification algorithms. These include analyzing backscattered or emitted signal parameters based on specific criteria and making decisions based on this analysis or using statistical classification methods (e.g., k-nearest neighbors, support vector machines, neural networks). The paper also discusses the current state of the field and proposes assumptions about the future development of surface classification technology.

Abstract: The rapid advancement of technology has led to an increasing demand for enhanced communication systems, particularly in the realm of cellular networks. With diverse applications such as real-time video streaming, online gaming, critical operations, and Internet-of-Things (IoT) services relying more on cellular connectivity, optimizing the cellular networks to meet evolving requirements while mitigating the associated power consumption challenges is crucial. This paper provides a comprehensive overview of initiatives undertaken by industry, academia, and researchers to reduce the power consumption of cellular network systems. Special emphasis is placed on emerging technologies like Software-Defined Networking (SDN), Network Function Virtualization (NFV), and Cloud-Radio Access Network (C-RAN), which hold promise for reshaping cellular infrastructure. Additionally, the paper delves into the convergence challenges and solutions associated with SDN, NFV, and C-RAN. The paper proposes a novel cellular architecture grounded in SDN, NFV, and C-RAN paradigms. This proposed framework offers a blueprint for developing energy-efficient cellular networks capable of meeting the diverse demands of modern communication applications and able to reduce power consumption by approximately 40% to 50% with careful placement of virtual network functions.

Abstract: Free-space optical communications have emerged as a powerful solution for inter-satellite links, playing a crucial role in next-generation satellite networks. This paper introduces a comprehensive model that enables the dynamic evaluation of optical power requirements for realistic low Earth orbit satellite constellations, throughout the orbital period. Our approach incorporates the constellation architecture, link budget analysis and optical transceiver design, to accurately estimate the power required for sustaining connectivity for both intra- and inter-orbit links. We apply the model considering Walker delta-type constellations of varying densities. We show that in dense constellations, even at high data rates, the required transmission power can be low enough to mitigate the need of optical amplification. Dynamically estimating the power requirements is vital when evaluating energy savings in adaptive scenarios where terminals adaptively change the emitted power depending on link status. Our model is implemented in Python and is openly available under an open-source license. It can be easily adapted to various alternative constellation configurations.

Abstract: Historic infrastructure preservation demands innovative and sustainable methodologies that safeguard structural integrity while minimizing environmental impact. This study explores the application of Remotely Piloted Aircraft Systems (RPAS) for the non-invasive inspection of the Requejo Bridge, a centennial metallic arch bridge that spans the Duero River within a protected natural environment in Spain. Through high-resolution aerial surveys, RPAS technology enabled the exhaustive assessment of areas traditionally difficult to access, identifying localized corrosion and material degradation critical for preventive conservation planning. By eliminating the need for scaffolding and heavy machinery—elements that pose significant ecological risks to sensitive landscapes—the drone-based inspections substantially reduced carbon emissions and resource consumption, while optimizing operational costs and minimizing workplace hazards. The findings confirm that RPAS not only enhance the accuracy and efficiency of structural diagnostics but also embody a sustainable maintenance strategy aligned with multiple Sustainable Development Goals (SDGs), including climate action, responsible resource use, and occupational safety. This research advocates for the widespread adoption of drone-assisted methodologies in heritage infrastructure management, offering an environmentally responsible, economically viable, and safer alternative that extends the service life of historic structures through proactive and minimally invasive interventions.

Abstract: Methanol is of rising interest as a potential hydrogen storage molecule and chemical building block producible from green hydrogen and captured carbon dioxide. Although the reaction kinetics have been studied for decades and numerous models are available, new recent insights reveal that a so far not quantitatively considered autocatalytic reaction pathway is of large relevance in heterogeneously catalyzed methanol synthesis over Cu/ZnO/Al2O3 catalysts. Inspired by these recent reports, an extended kinetic model was derived and parameterized exploiting the same data base used to parameterize earlier derived models. Thus, we provide the first model for quantifying the kinetics of the heterogeneously catalyzed methanol synthesis from CO/CO2/H2 which includes a methanol-assisted autocatalytic reaction pathway. Various reduced model variants were derived from the suggested model. A comparison with these reduced models and also with recalibrated further literature models reveals that the incorporation of the autocatalytic reaction pathway is beneficial. This finding encourages further assessment and validation considering a broader data base.

Abstract:

In smart grids, magnetic-sensitive sensors encounter reliability issues due to transient electromagnetic interference (EMI) and elevated temperatures. This study employs the finite-element method, focusing on current-testing sensors used in gas-insulated substations. By utilizing a damping oscillation wave as the excitation source, a simulation analysis compares the epoxy-molding compound's performance both with and without a copper shielding layer. Findings reveal that, in the absence of a shielding layer, the electric field, magnetic field, and current density responses at the detection points of the chip and bonding wires exhibit damping oscillations correlating with the excitation source. However, introducing the copper shielding layer substantially diminishes these metrics, suggesting its effective role in obstructing interference. Furthermore, a temporal correlation exists between the sensor's electromagnetic field and current density and the excitation source's waveform. When simulating in a high-temperature environment, the sensor's internal stress distribution becomes notably uneven, with pronounced stress concentrations at the gold wire-chip bonding points and solder joints. Notably, deformation is primarily observed in the center of the epoxy-molding compound and at the bonding wires. To mitigate these challenges, a novel packaging structure is introduced. Its shielding body, crafted from 3D-printed resin and filled with electromagnetic shielding materials, offers both electromagnetic shielding and a reduction in thermal expansion-induced stress and strain. Concurrently, a multi-layered shielding design is suggested to amplify the shielding efficacy, serving as a benchmark for sensor optimization.

Abstract: This study investigates the influence of pressure pulse characteristics on the noise level generated by a swashplate axial piston pump. Axial piston pumps are widely used in hydraulic systems, but their inherent pulsating flow can lead to significant noise and vibration, affecting system performance and operator comfort. This research focuses on understanding the relationship between pressure pulses generated within the pump and the resulting airborne noise. Experiments were conducted by varying key pump operating parameters, such as rotation speed and discharge pressure, and measuring the pressure pulses at the pump outlet and the noise levels emitted.

Abstract: The intensified global focus on energy transition and sustainability has increased the drive to leverage electric vehicle (EV) batteries as virtual power plant (VPP) resources. However, uncertainties and governance factors associated with this integration have not been systematically researched. This study aimed to identify and evaluate the key uncertainties surrounding the deployment of EV batteries in VPPs and propose strategic responses from an ESG perspective. We adopted a mixed-methods approach using scenario planning to identify critical uncertainties. The approach included quantitative assessments using Monte Carlo simulations and a scenario matrix to incorporate ESG elements into future projections. The findings highlighted economic value volatility (E) and employment creation potential and sustainability (S) as key uncertainties, with transparency requirements (G) as a subfactor. Four distinct scenarios were identified. By proposing tailored response strategies for each scenario, this study suggests that the long-term sustainability of EV batteries and VPP industries can be bolstered in various potential future environments. Integrating ESG factors into scenario analysis helps decision-making in industries characterized by high uncertainty. The study offers strategies that embed ESG considerations to support the sustainability of EV batteries and VPP sectors and provides valuable insights for shaping policies, industrial strategies, and corporate ESG initiatives.Keywords: virtual power plant (VPP); scenario planning; Monte Carlo simulation; ESG; uncertainty prediction; sustainability strategy; EV batteries

Abstract: Recent findings have demonstrated that the desalination and purification of contaminated water, and the separation of ions and gases, besides solutions to other related issues, may all be achieved with the use of membranes based on artificial nanoporous materials. Before the expensive stages of production and experimental testing, the optimum size and form of membrane nanopores could be determined using computer-aided modeling. The notion that rectangular nanopores created in a multilayered hexagonal boron nitride (h-BN) membrane in a way that results in different inner lining atoms would exhibit unique property in terms of water penetration rate is put forth and examined in the current study. Nanopores in Boron nitride sheets can be generated with the inner lining of boron atoms (B-edged), nitrogen atoms (N-edged), or both boron and nitrogen atoms (BN-edged). In this study, we compared the three different inner-lined nanopores of boron nitride nanosheets to a comparable-sized graphene nanopore and evaluated the water conduction.