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Recycled waste materials obtained from industrial and agricultural processes are becoming promising thermal and acoustic insulating solutions in building applications; their use can play an important role in the environmental impact reduction. The aim of the present paper is the evaluation of the thermal performance of recycled waste panels consisting of cork scraps, rice husk, coffee chaff, and end-life granulated tires, glued in different weight ratios and pressed. Six panels obtained from the mixing of these waste materials were fabricated and analyzed. In particular, the scope is the selection of the best compromise solutions from the thermal and environmental points of view. To this aim, thermal resistances were measured in laboratory and a Life Cycle Assessment (LCA) analysis was carried out for each panel; a cross-comparative examination was performed in order to optimize their properties and find the best panels solutions to be assembled in the future. Life Cycle Analysis was carried out in terms of primary Embodied Energy and Greenhouse Gas Emissions, considering a ‘‘cradle-to-gate” approach. The obtained thermal conductivities varied in the 0.055 to 0.135 W/mK range, in the same order of magnitude of many traditional systems. The best thermal results were obtained for the panels made of granulated cork, rice husk, and coffee chaff in this order. The rubber granulate showed higher values of the thermal conductivity (about 0.15 W/mK); a very interesting combined solution was the panel composed of cork (60%), rice husk (20%), and coffee chaff (20%), with a thermal conductivity of 0.08 W/mK and a Global Warming Potential of only 2.6 kg CO2eq/m2. Considering the Embodied Energy (CED), the best solution is a panel composed of 56% of cork and 44% of coffee chaff (minimum CED and thermal conductivity).

The growth of energy consumption has led to the depletion of fossil energy and the increasing greenhouse effect. In this case, low carbonization has become an important trend in the world’s energy development, in which clean energy occupies an important position. The uncertainties brought by the large-scale integration of wind power, photovoltaic and other renewable energy sources into the grid pose a serious challenge to system dispatch. The participation of demand response (DR) resources can flexibly cooperate with renewable energy, optimizing system dispatch and promoting renewable energy consumption. Thus, we propose a flexible DR scheduling strategy based on multiple response modes in this paper. We first present a DR resource operation model based on multivariate response modes. Then, the uncertainties are considered and dealt with by scenario generation and reduction technology. Finally, a day-head dispatch strategy considering flexible DR operation and wind power uncertainties is established. The simulation results show that the proposed strategy promotes wind power consumption and reduces system operation costs.

In actual mining situations, the advancing speed of the working face is usually accelerated, which may affect the failure and seepage characteristics of gas-bearing coal, and may even induce dynamic disasters. In order to discover the effects of such accelerated advancement of the working face, an experimental study on the failure and seepage characteristics of gas-bearing coal under accelerated loading and unloading conditions was carried out in this work. The results showed that the energy release was more violent and impactful under accelerated loading and unloading paths. The time required for the failure of the sample was significantly shortened. After being destroyed, the breakup of the sample was more severe, and the magnitude of the permeability was greater. Accordingly, the acceleration of the loading and unloading had significant control effects on the failure and permeability of coal and it showed a significant danger of inducing coal and gas dynamic disasters. Meanwhile, the degree of influence of the acceleration on the coal decreased with an increase in the gas pressure and increased significantly with an increase in the initial confining pressure. It was found that for a deep high-gas mine, the accelerated advancement of the working face under a high in situ stress condition would greatly increase the risk of coal and gas dynamic disasters. Then, the permeability evolution model of gas-bearing coal in consideration of changes in the loading and unloading rates was theoretically established in this work, and this permeability model was validated by experimental data. The permeability model was found to be relatively reasonable. In summary, the effects of accelerated loading and unloading on the failure and seepage characteristics of gas-bearing coal were obtained through a combination of experimental and theoretical studies, and the intrinsic relationship between the accelerated advancement of the working face and the occurrence of coal and gas dynamic disasters was discovered in this work.

Production system flexibility has become an important factor to meet the needs of diversified markets in an ever-changing and turbulent market environment. Thus, this paper addresses the problems of flexibility evaluation for decision making by evaluation method driven by digital twin, which models, predicts, and evaluates the flexibility of a given production system design scheme (PSDS). Based on the definition and characteristic analysis of flexibility in the production system design phase, and combined with data modelling (static function model (SFM) and dynamic prediction model (DPM)) and data analysis (AHP-based and simulation-based analysis), the proposed framework evaluates system flexibility from the static and dynamic levels, helps enterprises quickly obtain the system’s comprehensive flexibility evaluation index, realizing the rapid screening of the production system design scheme (PSDS). The successful application of the evaluation framework in case enterprise has fully proved the feasibility and effectiveness of the method.

As a key component in overhead cables, insulators play an important role. However, in the process of insulator inspection, due to background interference, small fault area, limitations of manual detection, and other factors, detection is difficult, has low accuracy, and is prone to missed detection and false detection. To detect insulator defects more accurately, the insulator defect detection algorithm based on You Only Look Once version 5 (YOLOv5) is proposed. A backbone network was built with lightweight modules to reduce network computing overhead. The small-scale network detection layer was increased to improve the network for small target detection accuracy. A receptive field module was designed to replace the original spatial pyramid pooling (SPP) module so that the network can obtain feature information and improve network performance. Finally, experiments were carried out on the insulator image dataset. The experimental results show that the average accuracy of the algorithm is 97.4%, which is 7% higher than that of the original YOLOv5 network, and the detection speed is increased by 10 fps, which improves the accuracy and speed of insulator detection.

This paper proposes a device of sensing that could be integrated into the instruments of any surgical robot. Despite advances in robot-assisted laparoscopic surgery, the tools currently supplied to surgical robots have limited functions, due to the absence of sensorization. With this motivation, we present a preliminary work based on the design, development, and early stages of experimentation with smart and multifunctional devices of sensing for surgical tools. The proposed device of sensing has a proximity sensor, colorimetric sensor, and BLE connection for different surgical instruments to connect to each other. The proximity feedback allows the surgeon to know the distance of the instrument from a particular tissue, to operate in conditions of greater safety. With the colorimetric feedback, on the other hand, we intend to proceed to the identification of specific tissue areas with characteristics that are not typical of the physiological tissue. The results show that the device is promising and can be further developed for multiple clinical needs in robotic procedures. This system can effectively increase the functionality of surgical instruments by overcoming the sensing limitations introduced by using robots in laparoscopic surgery.

In this article, we comprehensively reviewed Argentina’s Vaca Muerta formation, which encompasses a geological overview, advances in extraction technologies, the potential environmental impact, and economic analysis. Detailed geological analysis is discussed, emphasizing the stratigraphy, lithology, and depositional environments of the formation, which is crucial for understanding the distribution and quality of hydrocarbon resources. The latest advancements in hydraulic fracturing and horizontal drilling are explored, which have significantly improved efficiency and increased recoverable resources. The environmental implications of these extraction methods are critically examined. This includes a discussion of the necessity of sustainable practices in hydrocarbon extraction, highlighting the balance between resource development and environmental stewardship. The economic viability of the Vaca Muerta formation is analyzed, with a focus on cost-effectiveness, market trends, and investment patterns. This section assesses the formation’s potential as a profitable venture and its impact on the global energy market. Finally, the review anticipates future technological and policy developments. The strategic importance of the Vaca Muerta formation in the global energy sector is underscored, and its potential role in shaping future hydrocarbon exploration and production strategies is examined. In short, this essay not only presents data and findings, but also contextualizes them within the broader scope of energy production, environmental sustainability, and economic viability. This comprehensive approach provides a multi-faceted understanding of the Vaca Muerta formation’s significance in the global energy landscape.

Energy consumption is a critical evaluation index of embedded systems, and it has impacts on battery-life, thermal design, as well as device security and reliability. Since energy is the time integral of power, power consumption should be considered, along with the impact of “time”; thus, we propose two designs of automatic energy consumption measuring platforms utilizing General Purpose Input/Output (GPIO). Using these designs, we developed software and introduced auxiliary hardware for solutions with better timing and synchronization. A series of test sets were designed to verify our designs’ capabilities and accuracy levels. Both of our designs showed an accuracy similar to that of traditional measuring methods, which can satisfy the needs of different occasions. In addition, our designs provide real-time energy consumption data, as well as unattended automated measurements.