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Developing cost-effective and stable materials for the electrocatalysis of hydrogen evolution reaction (HER) remains challenging. In this study, efficient catalysts for HER were synthesized by integrating the cobalt and molybdenum oxides via electrodeposition, followed by subsequent sulfurization of the as-prepared oxides using chemical vapor deposition (CVD). This methodology allowed the incorporation of both cobalt and molybdenum components into the catalyst in a single step. The as-synthesized CoSx@MoSx/MoOx-based catalysts exhibited excellent hydrogen production performance in acidic media owing to the presence of Co-S and Mo-S bonds in the hybrid structure. Particularly, CoSx@MoSx/MoOx(90@360) and MoSx@CoOx(180@180) displayed the best HER performances with low overpotentials of 80 mV and 150 mV, respectively. The catalysts were highly stable, with their stability preserved for over 1000 cycles with marginal reduction in overall efficiency. Therefore, these findings suggest the potential of CoSx@MoSx/MoOx and MoSx@CoOx composites as ideal candidates for developing low-cost catalysts for electrochemical hydrogen production. [ABSTRACT FROM AUTHOR]

Integrating more active components into a catalyst material could facilitate the development of multifunctional electrocatalysts for energy conversion and storage applications. In this study, we developed a multifunctional electrocatalyst, namely, Pd alloyed with Co-Fe deposited on N-doped mesoporous carbon derived from tissue paper (Pd@Co-Fe/N-TDC). The synergism in Pd@Co-Fe/N-TDC, stemming from the interatomic alloy between Pd and Co-Fe, N-doped mesoporous carbon with defective surfaces, distribution of polyhedral Pd nanoparticles, and strong metal-support interfacial interaction, resulted in significantly high electrocatalytic performance for both oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Pd@Co-Fe/N-TDC was found to be an efficient bifunctional oxygen electrocatalyst, and this was evidenced by a high onset potential (1.01 V) and kinetic current density (2.6 mA/cm2) for the ORR and by a low overpotential (296 mV) and a low Tafel slope value (38 mV/dec) for the OER, along with a small Δ E of 736 mV. The catalyst also exhibited high durability for both ORR and OER, even after 10000 and 5000 cycles, respectively. Theoretical assessment provides an insight into the synergism of active metal sites in Pd@Co-Fe/N-TDC, which showed its potential for use as a non-Pt electrocatalyst for energy applications. [ABSTRACT FROM AUTHOR]

The increasing environmental consideration and the growth of instability of the energy market call for methods that can process the organic fraction of municipal solid waste (OFMSW) into fuel instead of disposal. Due to the pyrolysis and gasification that are efficient procedures to achieve valuable products, gasification of OFMSW with different particle sizes and compositions was carried out in the presence of Ni and Ni-Ce-loaded Y-zeolite in a multizone tubular kiln reactor. During the experiments, 500°C was applied in the first reactor zone, while the 2nd zone was at an elevated temperature of 600°C or 900°C in the presence of steam. The combined pyrolysis and gasification experiments were also carried out without a catalyst with the same operating conditions. The feedstock was collected from the organic fraction of a Hungarian mechanical-biological treatment (MBT) plant and was separated into four different fractions based on particle size: <1 cm dry biomass and fine particles, 1-2 cm paper-rich, 2-6 cm paper and plastic-rich feedstocks, and <6 cm mixture of these fractions. During the experimental work, product yields; gaseous product composition; the ratio of H2/CO, CO2/CO, and CH4/CO; and lower heating value were determined in the function of feedstock composition, the applied temperature, and catalysts. It was found that the hydrogen content and H2/CO ratio of gaseous products were increased due to catalyst application and temperature elevation in the 2nd reactor zone. The addition of Ce to the Ni/Y-zeolite catalyst was advantageous in the case of hydrogen formation at a lower temperature (600°C). The hydrogen and methane content of products obtained from the catalytic pyrolysis-gasification of paper and plastic-rich OFMSWs on elevated temperatures were higher, which increased the lower heating value of those products. Based on the elemental analysis of the obtained solid residues, it was found that paper/plastic-rich feedstock released hydrogen and carbon with a higher extent. 1-2 cm feedstock-related solid residues had the highest H/C ratio which caused a 12.5-12.8 MJ/kg gross heating value. As a result, combined pyrolysis and gasification appear to be an efficient method to attain valuable outputs from OFMSW not only in gas but also in solid products. [ABSTRACT FROM AUTHOR]

This paper explores the need for establishing a microwave link between Bahir Dar and Woretta as an alternative communication solution to the existing optical fiber infrastructure. Microwave links offer an effective way to overcome challenges posed by rugged terrains and unfavorable environmental conditions that hinder the deployment of fiber optics. As Woretta emerges as a key economic and investment hub within the Amhara Region, demand for reliable and efficient communication is expected to grow significantly. The study encompasses various aspects of planning and designing the microwave link, including site surveys, consideration of fade margins, frequency planning, link budget calculations, and assessing the feasibility and reliability of the proposed link. The paper employs LINKPlanner 5.4.1 software to simulate and validate the results. Due to terrain constraints, a direct link between Bahir Dar and Woretta is not feasible. Instead, a two-hop link is proposed, involving transmission from Bahir Dar to Zege, and then from Zege to Woretta. This alternative configuration ensures optimal connectivity while addressing the terrain limitations. By presenting a comprehensive analysis and simulation of the microwave link, this paper provides valuable insights into the planning and implementation of a robust communication infrastructure. The proposed microwave link will offer a reliable and efficient alternative to the existing optical fiber network, ensuring uninterrupted connectivity to support the region's growth and development. [ABSTRACT FROM AUTHOR]

Aiming at solving trajectory planning problem with complex distributed no-fly zone constraints, this paper proposed a novel obstacle avoidance strategy. For longitudinal motion, an angle of attack adjustment method is employed to adjust lift and design the angle of attack profile, while adjusting the bank angle for range and altitude correction to meet terminal constraints. For lateral motion, this paper developed enhanced attractive, repulsive, and velocity potential fields. Combined with the proposed repulsive force reconstruction method, this effectively resolves the overmaneuvering problem of traditional artificial potential field methods (APFMs) for vehicle. In order to avoid mismatched magnitudes of attractive and repulsive forces, a complementary no-fly zone avoidance strategy based on minimum turn radius is introduced, updating the bank angle command during no-fly zone avoidance. Simulation results indicate that the proposed strategy can address the avoidance of sudden threat, proving to be feasible and effective for handling complex distributed no-fly zone avoidance problems. [ABSTRACT FROM AUTHOR]

Ceramic matrix composites (CMCs) are a category of advanced materials which have gained significant interest recently due to their remarkable mechanical and thermal characteristics. These composites are composed of ceramic fibers, particles, or other types of ceramics incorporated in a ceramic matrix and have shown the capability to be implemented in several sectors, including aerospace, energy, and biomedical engineering. This review paper will provide a synopsis of the current scenario and recent progress in CMCs, including materials and processing techniques, characterization methods, and applications. The paper discusses the advantages and limitations of CMCs, recent advancements, and future trends in research. The microstructural and mechanical properties of CMCs are also reviewed, highlighting their potential for various applications. The paper's conclusion delivers a summary of the essential findings and a discussion of future directions for CMC research. [ABSTRACT FROM AUTHOR]

Optimal sizing and management of hybrid wind turbine-diesel-battery system for reverse osmosis seawater desalination in NEOM city is the objective of the paper. Therefore, the paper explored the different factors to optimize and introduce a technoeconomic evaluation and energy management of a stand-alone wind turbine (WT) system, diesel generator (DG), and battery storage (BS). The suggested WT/DG/BS system is implemented to feed seawater reverse osmosis (SWRO) unit in NEOM. The necessitated desalinated water per day is 100 m3. To determine the optimal size of WT/DG/BS corresponding to the minimum cost of energy (COE) and net present cost, two different ratings of the SWRO units (SWRO-100 and SWRO-150), three control dispatch strategies (load following, cycle charging, and combined dispatch), and five types of batteries are considered. HOMER software is performed to simulate and optimize the WT/DG/BS. The optimization results indicated that the best battery storage is the Trojan SAGM battery. In this case, the COE ranged between $0.337/kWh and $0.564/kWh. The lowest COE of $0.377/kWh is obtained when using a combined control strategy and SWRO-100 unit, whereas the worst COE of $0.564/kWh is obtained when using load following control strategy and SWRO-150 unit. The best option of the WT/DG/BS system to supply the SWRO unit is option number 26. This system includes one wind turbine of 90 kW, DG of 25 kW, 47 Trojan SAGM batteries, a 23.8 kW converter, a SWRO-100 unit, and a combined control strategy. The net present cost and the initial cost are $950,725 and $221,495, respectively. The annual operating cost and annual consumed fuel are $56,409 and 36,396 L, respectively. Compared with using only a 25 kW diesel generator, the COE reduced from $0.373/kWh (using only DG/BS) to $0.337/kWh (using the best option) by around 9.65%. Under this condition, the values for the internal rate of return, return on investment, and simple payback are 11%, 7.8%, and 8.3 years, respectively. [ABSTRACT FROM AUTHOR]

Objective. The aim of this study was to examine the characteristics of scientific production related to the use of filtered water in the field of dentistry. Material and Methods. A quantitative and descriptive observational study was carried out with a scientometric approach. Data were collected from the Web of Science (WOS) database during the period January 1991 to December 2023. A search strategy incorporating a combination of MeSH terms, including terms and thesauri related to "filtered water" and "dentistry", was used. R Studio version 4.3.2 and CiteSpace 6.2.R7 were used for data analysis. Results. Over the 32-year study period, 227 scholarly papers from 134 different sources were reviewed. The literature in this field has shown an annual growth rate of 10.44%. During the year 2010, a steady movement in the number of publications and authors was observed, with considerable collaborative interaction. In the year 2020, a large interaction between publications and their citations was found. The "Citation Burst" graph identified three references that have experienced the largest "burst" of citations in an evaluated period. Lotka's law described the productivity of authors, finding that most authors have published only one paper, while a smaller number of authors have published two papers. Most authors contributed a small number of articles, while a few authors contributed a large amount of the existing literature. Conclusion. A comprehensive overview of the scientific production related to the use of filtered water in dentistry over a span of 32 years is provided. The results highlight the growing interdisciplinarity and international collaboration in this field. Finally, the importance of filtered water in dentistry and its growing relevance in the scientific literature are emphasized. [ABSTRACT FROM AUTHOR]

Aim. To systematically map and identify key knowledge on organizational support for nurses' career planning and development. Design. Scoping review. Methods. Systematic electronic searches were carried out with the CINAHL, PubMed, Scopus, and Web of Science databases in May 2022. The searches were limited to scientific, peer-review papers that were published in English from January 2012 to May 2022. Data were extracted and synthetized and are presented in tables and text. The review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Results. We identified 1,400 papers and 28 met the inclusion criteria. Organizations recognized nurses' career planning and development in relation to the individual's professional development and the organization's need to promote high-quality services and workforce engagement. The organizational support included strategic work to ensure there were adequate resources and purposeful vacancies and a structured framework based on objective qualification criteria and equal assessment. Organizations focused on sharing knowledge, structured career planning, and interpersonal support. Support within the nursing profession and multilayered interprofessional collaboration were also important. Conclusion. Nurses' career planning and development was linked to their personal development and the organization's aims and required support from both fellow nurses and other professionals. Implications for the Nursing Management. Identifying the organizational structures and methods that are needed to support nurses' career planning and development can help nursing management to evaluate and develop strategies that improve the attractiveness of a nursing career and nurses' engagement. [ABSTRACT FROM AUTHOR]

Nowadays, most of the works are based on electric vehicle usage for sustainable transportation using traditional energy storage device, such as battery. Usage of batteries in electric vehicles is having several disadvantages, for example, life span, temperature, and charge estimation. In this paper, a novel control scheme for battery and supercapacitor- (SC-) based hybrid energy storage system (HESS) using hybrid proportional and integral- (PI-) sliding mode control (SMC) for electric vehicle (EV) applications is introduced and implemented. This HESS with hybrid controller proves the usage of batteries in EVs to its fullest potential. The conventional control strategy for HESS follows two-loop voltage and current PI controllers with low-pass filter (LPF) and involves tuning of multiple control parameters with variations of source and load disturbances. Performance of the system is affected by tuning PI controller constants. A slow response time with linear PI controllers is long which is not advisable for starting and sudden jerk conditions of EVs. Moreover, the PI controller performance is affected by the system parameter variations during load changes. And these parameters are dynamic in nature due to nonideal conditions. In this paper, a hybrid PI-sliding mode controller (SMC) scheme is designed to control the bidirectional DC-DC converters to overcome the drawbacks of aforementioned issues. The combined PI-SMC controller reduces the tuning effort and reduces the effect of shift in operating point in controller performance. Linear modeling is done using small signal analysis for each subsystems. Permanent magnet synchronous machine (PMSM) is used as electric vehicle. The entire system and its controllers are simulated using MATLAB-Simulink, and detailed comparison is carried between conventional PI and proposed hybrid PI-SMC scheme to regulate the DC link voltage. The results are tabulated and show that the hybrid PI-SMC scheme outperforms in transient and steady-state conditions than the traditional PI controller. A scaled hardware prototype of 48 W set-up is developed using dSPACE-1104, and the experimental results have been carried out to verify the proposed system's feasibility. [ABSTRACT FROM AUTHOR]

In this paper, a ground-based experimental system for solar array active vibration suppression has been established. Firstly, in order to establish an accurate model of the solar array, the solar array is regarded as a flexible cantilevered thin plate, and the corresponding dynamical equations are derived using the absolute nodal coordinate method. In addition, in this paper, the more advanced MFC piezoelectric patch is used instead of the traditional PZT piezoelectric ceramic patch. The electromechanical coupling finite element model of the P1-type MFC patch is established and substituted into the kinetic equation of the solar array. Finally, the accuracy of the electromechanical coupling modeling and the control effect of active vibration suppression were verified using the PID control. A set of experimental frameworks for evaluating the active vibration suppression effect, including the free vibration test, sinusoidal perturbation test, and white noise perturbation test, as well as the analysis strategy of the test data, are established. [ABSTRACT FROM AUTHOR]

Unlike conventional single-phase seepage monitoring methods, monitoring multiphase flow in porous media is more complex. This paper addresses this complexity by analyzing the heat transfer in porous media models under multiphase seepage conditions. It introduces a set of theories, methods, and devices to effectively monitor the flow velocity in multiphase seepage processes. Utilizing a self-developed single-point self-heating temperature-sensing device combined with saturation testing at monitoring points, we establish a method to determine the relationship between different saturation and resistivity, as well as the saturation and thermal conductivity of the reservoir model, which provides essential parameter support for the calculation of results during flow velocity monitoring. The effectiveness of the flow velocity monitoring method was confirmed through a one-dimensional constant velocity multiphase seepage experiment. Furthermore, oil-water two-phase seepage simulation experiments were conducted based on the sandpack model. By comparing the real oil-water flow velocity with the monitored velocity, the accuracy can reach over 95%, validating the accuracy and reliability of the method proposed in this paper. The seepage flow velocity monitoring theory and technology established herein offer corresponding theories and methods for obtaining fluid seepage velocity in porous media with multiphase fluids. [ABSTRACT FROM AUTHOR]

Farm biosecurity has gained increasing attention worldwide during the last decades because of its role in reducing the occurrence of diseases and improving animal performance. Recently, recommendations to reinforce the concept of farm biosecurity in lower- and middle-income countries have been advised. Therefore, this review aims to provide a comprehensive description of the methods and tools used to assess biosecurity compliance in livestock farms in Africa and formulate recommendations. The present review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for scoping reviews guidelines. Peer-reviewed studies reporting biosecurity assessment in poultry, cattle, pig, goat, or sheep farms in Africa were included. Five databases were searched with no date restrictions. A total of 41 studies across 17 countries were finally selected. Selected studies were all published after 2008, and an increasing trend in the number of papers published per year was noticed. In total, 41 different methods for biosecurity assessment were found to be used in African countries, meaning that even within the same country, the same animal species, and the same farming system, different methods were utilized. In many papers, the methods used for biosecurity evaluation were poorly described. In addition, during the biosecurity assessment, measures related to the purchase of laying hens, egg transport and management, calves, calving and dairy management, and nursery units were almost not considered. These measures should be contemplated in future studies since they are related to important risk factors for the introduction and dissemination of infectious diseases. Interestingly, some measures not considered in European biosecurity tools were identified in the selected studies. The observed high difference in methods used may be due to the lack of regulations on biosecurity in African countries; therefore, the authors recommend the development and implementation of a harmonized and contextualized method for the assessment of biosecurity in livestock farms in Africa. [ABSTRACT FROM AUTHOR]

This paper is aimed at performing a comprehensive review of the approaches employed in nanosatellite platforms, specifically 1 U and 3 U, for electrical power systems (EPS). Moreover, it seeks to develop a robust maximum power point tracking (MPPT) controller using the sliding mode control (SMC) method. The proposed control strategy is intended to monitor the solar panel's maximum power point (MPP) and adapt to changes in temperatures and solar irradiance in low Earth orbit (LEO). The EPS model, designed with the proposed sizing method, is built in MATLAB-Simulink and integrates a solar panel, battery storage, and power converters controlled by diverse MPPT methods. Then, simulation results demonstrate the effectiveness of the proposed SMC approach compared to other conventional control methods for the designed EPS under varying LEO conditions. To achieve a robust validation of the most appropriate MPPT control method under steady-state conditions, this paper presents an experimental investigation into the proposed EPS hardware design. The proposed SMC method achieved an increase in power generation from 10% to 12% for buck and boost power converters, respectively, compared to traditional control methods. [ABSTRACT FROM AUTHOR]

This paper introduces a novel concept of a TRISO-fueled salt-cooled reactor (TFSCR). The core contains circulating pipes filled with molten salt carrying TRISO particles. The reactor achieves online refueling by slowly circulating the molten salt through the pipeline. The reactor utilizes the same molten salt as the coolant and graphite as the moderator. The reactor design has the characteristics of safety, economy, and nonproliferation. TRISO particles exhibit greater resistance to neutron irradiation, corrosion, oxidation, and high temperatures compared to conventional fuels. A molten salt-cooled reactor can also operate at higher temperatures, consequently enhancing power generation efficiency. Furthermore, lower operating pressures can mitigate the risk of significant damages and loss of coolant caused by accidents, thereby enhancing reactor safety. This paper presents the basic nuclear design of TFSCR under the assumptions concerning the average fuel power density, the volumetric core power density, and the core temperature. At the same time, the feasibility of online refueling and long-life operation was evaluated by fuel burnup calculation. [ABSTRACT FROM AUTHOR]

Contemporary healthcare for those experiencing mental illness requires healthcare practitioners (HCPs) to effectively incorporate the prescription of exercise in their treatment, in accordance with clinical guidelines. However, there has been a lack of effective implementation of such recommendations. The purpose of this review was to identify barriers to exercise prescription in the treatment of people diagnosed with mental illness as perceived by HCPs. APA PsycINFO, CINAHL, MEDLINE, and PubMed electronic databases were searched for relevant articles published in the period from January 2005 to September 2023. A total of 18 papers were included for thematic synthesis. Four key themes were identified across the qualitative (8), quantitative (6), and mixed method (4) papers, including a lack of knowledge and confidence of HCPs in prescribing exercise; role and responsibility; HCPs' misconceptions of client barriers; and systemic issues impacting exercise prescription practices. A lack of knowledge or confidence was the most common barrier. Some HCPs indicated a desire to develop their skills in exercise prescription, while others indicated a preference for an exercise professional to take responsibility for this aspect of treatment. Systemic barriers were spread across a range of issues, with lack of time, excessive workload, and difficulties accessing qualified staff most commonly cited. This review provides further insight into the barriers to exercise prescription faced by HCPs and makes recommendations regarding how to address these barriers in order to better implement clinical guidelines and thus improve the quality of treatment provided to people diagnosed with a mental illness. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) constitutes a sophisticated network that interconnects devices, optimizing functionality across various domains of human activity. Recent literature projections anticipate a significant increase, with estimates exceeding 50 billion connected devices by 2025. Despite its transformative potential, the IoT landscape confronts formidable privacy and security challenges, encompassing intricate issues such as data acquisition, anonymization, retention, sharing practices, and behavioural profiling. Effectively addressing these challenges mandates the development of scalable solutions, innovative management strategies, and adaptable policy frameworks. In this paper, we conduct an exhaustive examination of major IoT applications, alongside associated privacy and security concerns. We systematically categorize prevalent privacy, security, and interoperability issues within the context of the IoT layered architecture. The review highlights current research initiatives focused on developing energy-efficient devices, optimizing microprocessors, and fostering interdisciplinary collaborations to address the challenges in the IoT landscape. To efficaciously manage risks in this dynamic landscape, stakeholders must implement comprehensive strategies that span stringent data protection legislation, extensive user education initiatives, and the deployment of robust authorization and authentication frameworks. This paper aims to empower industry leaders, policymakers, and researchers by providing actionable solutions, not just insights, to navigate the complexities of the IoT landscape effectively. Future research initiatives should prioritize the fortification of security measures for large-scale IoT deployments, the formulation of user-centric privacy solutions, and the standardization of interoperability protocols. By establishing a robust foundational framework, our paper endeavours to spearhead the discourse on IoT applications, privacy paradigms, and security frameworks, paving the way towards a resilient and interconnected future. [ABSTRACT FROM AUTHOR]

This paper presents a performance analysis and optimization of heat exchanger fin shapes in a thermoelectric power generation system for ship waste heat recovery. It proposes a new curved fin design aimed at enhancing heat transfer efficiency and maximizing thermoelectric power generation capacity. Numerical analysis and response surface methodology (RSM) focused on 225 parameters to identify the optimal fin shape. Computational analysis using CFX was conducted on the thermoelectric module system with curved fins. The methodology was verified by comparing and analyzing CFD and PIV experimental results for a curved fin. The paper comprehensively compares the fluid dynamics of curved fins and straight fins, highlighting how curved fins improve heat exchange by creating a tip leak vortex. The results demonstrate the superiority of the curved fin design in terms of heat transfer efficiency and net power generation over the conventional straight fin design. [ABSTRACT FROM AUTHOR]

In the process of long-term water flooding in the Gaoqian Southern Area with an average porosity of 30% and an average permeability of 1333.5 × 10 − 3 μm2, the fluid-solid interaction among oil, water, and rock has a great influence on the pore structure. It has resulted in changes in reservoir parameters with the extension of time. This paper used electron microscopy scanning, mercury injection, X-ray diffraction, physical properties, and oil-water relative permeability curves to study the variation of clay mineral content, pore throat structure, porosity, permeability, and relative permeability curves of high-permeability sandstone after high-pressure water flooding. The results showed that clay minerals such as montmorillonite and kaolinite were dissolved, hydrated, and migrated after long-term water flooding, which resulted in the decrease of clay mineral content in fine sandstone and medium sandstone, the increase of pore throat radius, and the decrease of displacement pressure, median pressure, and separation coefficient. The saturation of the isotonic point of the oil-water relative permeability curve was obviously shifted to the right, the hydrophilicity was significantly enhanced, and the porosity and permeability were effectively improved, but there was a blockage of the throat less than 2 μm in the fine sandstone. In addition, this paper established the equations of water injection, permeability, irreducible water saturation, residual oil saturation, and oil-water relative permeability curve coefficient and establishes the initial permeability model with the well data before water flooding. The logging interpretation results of development wells in the process of water flooding as verification data were used, and the relative error of permeability far lower than the general requirement of permeability error within an order of magnitude was less than 30%, which verified the rationality of the method. [ABSTRACT FROM AUTHOR]

China, situated in the circum-Pacific seismic belt, experiences frequent seismic activity and faces diverse geological conditions, making structural stability of paramount importance, especially under seismic conditions. The majority of current earthquake generation methods do not consider the nonstationary nature of earthquakes. This paper introduces a spectral representation-random function model for generating nonstationary earthquakes, effectively simulating stochastic seismic ground motion. Furthermore, traditional slope stability analysis methods are deterministic and incapable of providing probabilistic assessments of slope instability. Therefore, this paper proposes a unified framework for static and dynamic structural reliability analysis based on the direct probability integration method, quantifying the impact of stochastic seismic ground motion on the dynamic reliability of slope stability. Finally, the proposed methods are applied to an excavation slope in Nanjing, using sliding displacement and safety factors as evaluation criteria to study the reliability of the slope under the influence of stochastic seismic events. [ABSTRACT FROM AUTHOR]

In the context of the rapid advancements in space technology and the increasing complexity of space missions, there is a growing need for efficient and effective approaches to tackle the multifaceted challenges faced by space systems. Traditional methods often fall short in providing comprehensive support throughout the entire life cycle of space systems. To address these challenges, this paper presents a novel parallel space system architecture based on ACP (artificial systems, computational experiments, and parallel execution) and explores its applications in the design, development, and operation of space systems. The proposed architecture integrates artificial systems with actual space systems and employs computational experiments to generate extensive sample data. This approach enhances the accuracy of the artificial systems' model and optimizes the performance of the real systems, facilitating parallel advancements between the two. The design, development, and operation processes of Q-Sat, implemented using the ACP framework, serve as a case study to illustrate the advantages of parallel space systems. Following adjustments made to the discrepancies between parallel systems under the ACP-based space system framework, the accuracy of missing orbit compensation improved by 86.5%, and the 24-hour forecast positional error was reduced by approximately 65 m. Furthermore, this paper discusses future trends, emphasizing the increasing efficiency and reliability of digitized, integrated, and adaptive space systems. The findings contribute to the understanding of parallel space systems and provide valuable insights for further advancements in the field. [ABSTRACT FROM AUTHOR]

Meat is a widely consumed food globally; however, variations in storage conditions along its supply chain can pose a potential food safety risk for consumers. Addressing this concern, we have developed freshness indicators designed to monitor the condition of packaged chicken. In this study, anthocyanins were infused with cellulose paper measuring 2 × 2 cm, and subsequent analysis focused on examining color changes concerning deteriorating chicken stored at 30°C for 48 h, with varying sample sizes being considered. The rise in total volatile nitrogen (TVB-N) compounds from an initial value of 3.64 ± 0.39 mg/100 g to 28.17 ± 1.46 mg/100 g acted as the stimulus for the color change in the indicator, simultaneously influencing the pH from the initial 7.03 ± 0.16 to 8.12 ± 0.39. The microbial load (aerobic plate count) of the chicken samples was also significantly increased. This collective shift in various parameters strongly suggests the occurrence of spoilage in chicken meat. The pH indicators exhibited a dark pink to red color for fresh chicken. As the chicken meat turned towards spoilage, the indicators changed to a dark blue and then a pale green color. FTIR spectroscopy results confirmed the presence of cellulose and anthocyanins. The FTIR analysis also validated the immobilization of plum anthocyanins within the cellulose paper and assessed their stability after 8 months of storage. Notably, the indicators demonstrated rapid sensitivity, showing a 20.5% response within one minute of ammonia exposure, which further increased to 29.5% after 3 min of exposure. The total color difference (ΔE) steadily rose in all the examined samples and also under various storage conditions. Overall, the indicators developed in this study exhibited a highly pronounced color transition, capable of distinguishing between fresh and spoiled chicken samples depending on the extent of spoilage and the specific day of observation. [ABSTRACT FROM AUTHOR]

The axial deployment force is an indispensable parameter of a lanyard-deployed coilable mast, which reflects its load capacity in practical applications. However, research on the axial deployment force in the literature is very limited, and there are no mature numerical methods to determine this parameter in the design stage of coilable masts. In this paper, a numerical method for determining the axial deployment force of a lanyard-deployed coilable mast in the local coil mode is presented. Through this method, the designer can quickly obtain the estimated value of the axial deployment force in the design stage, which is convenient for the quantitative design of parameters. To verify the correctness of the proposed method, a dynamic simulation of the coilable mast is carried out, and a microgravity test is performed. The comparison results show that the error between the numerical method and the simulation and experimental results is less than 5%, which proves the correctness of the proposed method. In addition, the coilable mast studied in this paper has been verified by an actual microsatellite deployment in orbit. [ABSTRACT FROM AUTHOR]

Background. Lactobacillus acidophilus is lactic acid bacteria that produce bacteriocins. Bacteriocins are antimicrobial peptides or proteins that exhibit activity against closely related bacteria. The aim of this study was to determine the effect of L. acidophilus ATCC 4356 bacteriocin against Staphylococcus aureus. Material and Methods. We used four different phenotypic methods for antimicrobial activities against two standard strains: methicillin-resistant S. aureus (MRSA) ATCC 33591 and methicillin-susceptible S. aureus (MSSA) ATCC 25923. The methods were (1) agar well diffusion, (2) overlay soft agar, (3) paper disk, and (4) modification of punch hole. The ammonium sulfate method was used to concentrate crude bacteriocin, and ultrafiltration and dialysis tubes were used to remove ammonium sulfate from the bacteriocins. Each method was repeated in triplicate. Result. L. acidophilus ATCC 4356 showed antimicrobial activity against both MRSA and MSSA standard strains only by the overlay soft agar method and not by the agar well diffusion, punch hole modification, and paper disk methods. No antimicrobial effects were observed in crude bacteriocins concentrated. Conclusion. The growth inhibition of S. aureus in overlay soft agar method may be due to the production of bacteriocin-like substances. The overlay soft agar method is a qualitative test, so there is a need for further study to optimize the conditions for the production of bacteriocin-like substances in the culture supernatant and precise comparison between the inhibitory activity and pheromone secretion of different strains. [ABSTRACT FROM AUTHOR]

In this paper, the reentry phase of the Aerospaceplane is taken as the research object, and the performance parameters of the reusable rocket of a private company are analyzed. Aiming at the guidance and control scheme of the spacecraft returning to the reentry trajectory in the real environment, the original natural algorithm is optimized by considering various reentry flight constraints, and the improved original natural algorithm is used to optimize the reentry trajectory of the Aerospaceplane. We obtained two types of reentry trajectories in the presence of large flight-restricted areas, the "S-type" trajectory and the "spiral-type" trajectory, and obtained data on various influencing factors. The results showed that the basic state parameters of the spiral trajectory optimized using the improved original natural algorithm after adding constraints met the constraint conditions. The aerodynamic heating rate and overload of the spiral reentry trajectory were to some extent greater than those of the S-type trajectory. Under the increasingly stringent requirements of the aerospace environment, new requirements were put forward for the thermal protection system to meet the wider environmental situation. This paper uses the improved original natural algorithm for the first time and applies it to the field of aerospace reentry and entry and adds more constraints to this algorithm for computation. Besides, for the first time, the macroscopic nature of trajectory types is used as a comparative element for parameter comparison, providing a reference basis for selecting trajectory optimization directions from the macroscopic perspective of trajectory types. [ABSTRACT FROM AUTHOR]

This paper proposes a model predictive speed control strategy for a surface-mounted permanent magnet synchronous motor by applying Laguerre functions. The model predictive controller (MPC) incorporates an integrator. A quadratic programming procedure is applied to solve the constrained optimization problem online. The paper also provides a solution for stability. The performance efficiency of the proposed scheme is validated by comparing the results with the performance of an optimal linear quadratic regulator, conventional state-space model predictive control, and a simple MPC algorithm with integral action. Extensive simulation results confirm the efficacy of the proposed scheme, showing that it achieves good steady-state performance while maintaining a fast dynamic response. [ABSTRACT FROM AUTHOR]

In order to further study the cushioning performance of concave hexagonal cores (CHCs) and expand their application range, the in-plane finite element model of CHCs is established in this paper. A dynamic cushioning coefficient method was proposed to characterize the cushioning performance of CHCs. The dynamic cushioning coefficient curve and minimum dynamic cushioning coefficient (MDCC) of CHCs with different impact velocities and structural parameters are obtained. The influence rules of structural parameters and impact velocities on the MDCC are analyzed; the deformation mode and transformation empirical formula are also obtained. The results show that when other parameters are constant, the MDCC of CHCs decreases with the increase of impact velocity, increases with the increase of wall thickness and side length ratio, and decreases with the increase of expansion angle. The theoretical analysis is consistent with the finite element results, which further verifies the reliability of the model. This paper provides a solid theoretical basis for the industrial application of the cushioning performance of CHCs and forms a key technical support. [ABSTRACT FROM AUTHOR]

Background. Coal washing is a complicated process and difficult to control, which has many controlling parameters with strong coupling relationship. It is still a challenge to realize the self-perception, self-adjustment, and self-evaluation of coal washing machine, improve the quality of coal washing, ensure production safety, and reduce labor cost. Methods. Through the intelligent transformation of jig, this paper proposes an intelligent washing method with cooperated deep reinforcement learning and evolutionary computation. First, it designs a fault warning method based on statistical analysis, helping to recover the normal running state of jig with manual maintenance. Then, it constructs a regulation strategy generation method with deep reinforcement learning supported by the fusion of artificial experience and historical data. Last, for the lack of monitoring data caused by poor communication quality and environment, the regulation strategy prediction method with evolutionary computation and surrogate model is proposed. Results. In practice, this method shows accurate fault warning accuracy and rapid cleaned coal ash adjustment response ability. Conclusions. This shows that the method proposed in this paper is of great significance for intelligent washing and can better cope with the special situation when the washing equipment sensing data are missing. [ABSTRACT FROM AUTHOR]

Vehicle antilock systems play a very important role in the stability and reliability during vehicle braking. Due to the complexity of the braking process, antilock braking system (ABS) usually face the problems such as nonlinearity, time-varying, and uncertain parameter modeling. Thus, aiming at the parameter model uncertainty problem of ABS, an adaptive neural network sliding mode controller (ADRBF-SMC) is designed in this paper. On this basis, establishing the quarter-vehicle model and the seven-degree-of-freedom vehicle model, and treating the difference between the two models as a kind of disturbance, carrying out vehicle braking performance simulation experiments to analyze the variation of braking performance parameters such as vehicle and wheel speeds, slip ratio, braking distance, braking torque, under the three cases of adaptive neural network sliding mode controller, traditional sliding mode controller, and no control. Simulation results show that the adaptive neural network sliding mode controller (ADRBF-SMC) proposed in this paper can play an effective control role in both vehicle dynamics models. In addition, the control method proposed in this paper has stronger anti-interference capability and higher robustness compared with the sliding mode controller (SMC). [ABSTRACT FROM AUTHOR]

Sustainable concepts for on-demand transportation, such as ridesharing or ridehailing, require advanced technologies and novel dynamic planning and prediction methods. In this paper, we consider the prediction of taxi trip durations, focusing on the problem of the estimated time of arrival (ETA). ETA can be used to compute and compare alternative taxi schedules and to provide information to drivers and passengers. To solve the underlying hard computational problem with high precision, machine learning (ML) models for ETA are the state of the art. However, these models are mostly black box neural networks. Hence, the resulting predictions are difficult to explain to users. To address this problem, the contributions of this paper are threefold. First, we propose a novel stacked two-level ensemble model combining multiple ETA models; we show that the stacked model outperforms state-of-the-art ML models. However, the complex ensemble architecture makes the resulting predictions less transparent. To alleviate this, we investigate explainable artificial intelligence (XAI) methods for explaining the first- and second-level models of the ensemble. Third, we consider and compare different ways of combining first-level and second-level explanations. This novel concept enables us to explain stacked ensembles for regression tasks. The experimental evaluation indicates that the considered ETA models correctly learn the importance of those input features driving the prediction. [ABSTRACT FROM AUTHOR]

In recent years, the proportion of wind power in new energy generation has gradually increased. The natural wind in wind farms is subject to velocity attenuation by the wake effect, so improving the efficiency of wind farm power generation has become a problem that must be solved for wind power generation. Considering the uncertainty of wind farms, we regard wind farm layout optimization (WFLO) as a strongly nonlinear problem. In this paper, we improve the sparrow search algorithm (SSA) using dynamic opposite learning (DOL) strategy. Twenty-eight benchmark test results prove that compared with other algorithms, the improved algorithm DOLSSA has excellent robustness and the ability of searching for a better solution when solving a strongly nonlinear optimization problem, and the DOL strategy effectively improves the shortcomings of the original algorithm which is prone to local optimization and space limitation. In this paper, the authors establish the dynamic rotational coordinates of wind farms and set six different physical scenarios by considering the wind direction and wind speed variables, and the results prove that the performance of DOLSSA is optimal. [ABSTRACT FROM AUTHOR]

Aiming at the sound source localization of mechanical faults in a strong reverberation scenario with multiple sound sources, this paper investigates a mechanical fault source localization method using the U-net deep convolutional neural network. The method utilizes the SRP-PHAT algorithm to calculate the response power spectra of the collected multichannel fault signals. Through the utilization of the U-net neural network, the response power spectra containing spurious peaks are transformed into "clean" estimated source distribution maps. By employing interpolation search, the estimated source distribution maps are processed to obtain location estimations for multiple fault sources. To validate the effectiveness of the proposed method, this paper constructs an experimental dataset using mechanical fault data from electromechanical equipment relays and conducts sound source localization experiments. The experimental results show that the U-net network under 0.2 s/0.5 s/0.7 s reverberation time can effectively eliminate spurious peak interference in the response power spectrum. As the signal-to-noise ratio decreases, it can still distinguish the sound sources with a distance of 0.2 m. In the context of multifault source localization, the method is capable of simultaneously locating the positions of four fault sources, with an average localization error of less than 0.02 m. The method in this paper effectively eliminates spurious peaks in the response power spectra under conditions of multisource strong reverberation. It accurately locates multiple mechanical fault sources, thereby significantly enhancing the efficiency of mechanical fault detection. [ABSTRACT FROM AUTHOR]

In a democratic regime, voting is crucial to making collective decisions. Unfortunately, although this activity has great significance and value, little effort has been made to improve the way we vote. Paper ballots are still the most used method, although this method is relatively simple, brings many inconveniences, and represents a contradiction to the modern world and its advances. This paper mostly focuses on a review study of blockchain-based voting systems. It aims at identifying the strategies and the guidelines as well as provides a comprehensive end-to-end electronic voting system based on blockchain, with the help of cryptographic techniques such as zero-knowledge proofs to improve privacy. The novelty of this paper is that we tackle the limitations of electronic voting systems found in the literature, including cost, identity management, and scalability problems. Our purpose is to provide key elements for organizations on how to design their proper electronic voting system based on blockchain technology. [ABSTRACT FROM AUTHOR]

Localization is an important method for autonomous indoor robots to recognize their positions. Generally, the navigation of a mobile robot is conducted using a camera, Lidar, and global positioning system. However, for an indoor environment, GPS is unavailable. Therefore, a, state-trajectory tracking method is utilized based on a Lidar map. This paper presents the path following of an autonomous indoor mobile robot, that is, a shuttle robot, using a state-flow method via a robot operating system network. MATLAB and Linux high-level computers and an inertial measurement unit sensor are used to obtain the Cartesian coordinate information of a bicycle-type mobile robot. The path following problem can be solved in the state-flow block by setting appropriate time and linear and angular velocity variables. After the predetermined time, the linear and angular velocities are set based on the length of the path and radius of the quarter-circle of the left and right turns in the state-flow block, path planning, which can execute the work effectively, is established using the state-flow algorithm. The state-flow block produces time-series data that are sent to Linux system, which facilitates real-time mobile platform path following scenario. Several cases within the path-following problem of the mobile robot were considered, depending on the linear and angular velocity settings: the mobile robot moved forward and backward, turned in the right and left directions on the circular path. The effectiveness of the method was demonstrated using the desktop-based indoor mobile robot control results. Thus, the paper focuses on the application of the state-flow algorithm to the shuttle robot specifically in the narrow indoor environment. [ABSTRACT FROM AUTHOR]

The last three census data highlighted that UK Bangladeshi communities have the worst health outcomes. This includes a higher risk of type two diabetes and heart diseases; both are risk factors for developing vascular dementia. However, little is known about Bangladeshi community members' understandings of dementia, including cultural myths. This paper focuses on the cultural myths, superstitions, and stigma surrounding dementia in an English Bangladeshi community from the direct experiences of people living with dementia, their caregivers, and the views of dementia service providers/stakeholders. This qualitative research was undertaken with three distinct participant groups using semistructured interviews (n = 25), who were recruited from community settings. The first and second participant groups explored the experiences of people with dementia (n = 10) and their family caregivers (n = 10). The third group examined stakeholders'/service providers' views (n = 5). Interviews were recorded digitally and transcribed verbatim. Findings were reached using an interpretive approach, emphasising the sense people make in their own lives and experiences and how they frame and understand dementia. The study revealed that participants with dementia and their caregivers have "alternative" knowledge about dementia and do not necessarily understand dementia in a Westernised scientific/biomedical context. Misconceptions about dementia and belief in various myths and superstitions can lead people to go to spiritual healers or practice traditional remedies rather than to their GPs, delaying their dementia diagnosis. This paper concludes that there is a lack of awareness among the Bangladeshi participants and a need for targeted awareness about dementia to help dispel cultural myths and combat the stigma surrounding dementia within the Bangladeshi community. [ABSTRACT FROM AUTHOR]

This paper is an attempt to establish the existence and multiplicity results of nontrivial solutions to singular systems with sign-changing weight, nonlinear singularities, and critical exponent. By using variational methods, the Nehari manifold, and under sufficient conditions on the parameter η which represent some physical meanings, we prove some existing results by researching the critical points as the minimizers of the energy functional associated with the proposed problem (2) on the constraint defined by the Nehari manifold, which are solutions of our system, under some sufficient conditions on the parameters α , β , μ , and η. To the best of our knowledge, this paper is one of the first contributions to the study of singular systems with sign-changing weight, nonlinear singularities, and critical exponent. [ABSTRACT FROM AUTHOR]

In seismic data processing, data recovery including reconstruction of the missing trace and removal of noise from the recorded data are the key steps in improving the signal-to-noise ratio (SNR). The reconstruction of seismic data and removal of noise becomes a sparse optimization problem that can be solved by using sparse regularization. Sparse regularization is a key tool in the solution of inverse problems. They are used to introduce prior knowledge and make the approximation of ill-posed inverses feasible. It deals with ill-posedness by replacing an ill-posed inverse problem with a well-posed problem that has a solution close to the true solution. In the last 2 decades, interest has shifted from linear toward nonlinear regularization methods even for linear inverse problems. In inverse problems, regularizations serve as stabilizing the solution of ill-posed inverse problems and give a solution that adequately fits measurements without producing unjustifiably complex artifacts. In this paper, we present a novel sparse regularization based on a tensor-based dictionary method for inverse problems (seismic data interpolation and denoising). This regularization avoids the vectorization step for sparse representation of seismic data during the reconstruction process. The key step in sparsifying signals is the choice of sparsity-promoting dictionary learning. The learning-based approach can adaptively sparsify datasets but has high computational complexity and involves no prior-constraint pattern information for the dataset. Many existing dictionary learning methods would be computationally infeasible for the high dimensional seismic data processing. These methods also destroy the essential information as well as it reduces the discriminability and expressibility of the signal, since they deal with vectorization. In this paper, the orthogonal tensor dictionary learning that learns a dictionary from the input data by employing orthogonality and separability is proposed as sparse regularization for the inverse problems. The performance of the proposed method was validated in seismic data interpolation and denoising individually as well as simultaneously. Numerical examples of synthetic and real seismic datasets demonstrate the validity of the proposed method. The SNR of the recovered data confirms that the proposed method is the most effective method than K-singular value decomposition and orthogonal dictionary learning methods. [ABSTRACT FROM AUTHOR]

Transverse synchronization of vertical displacements of all jacking-up points is an important monitoring indicator to replace bearings in assembled multigirder bridges during the jacking phase. Currently, using target paper to identify the 3D coordinates of control points reduces the complexity of monitoring operations and improves the stability of data precision. However, the existing planar target locating methods have low accuracy, inefficiency, and subjectivity, which seriously hinders the construction process of bearing replacement. Accurately obtaining the center coordinates of multiple targets from a point cloud in a short monitoring period remains a challenge. This study proposes a high-precision automated algorithm to extract target center points in low-density point clouds to quickly calculate real target center points. First, we construct a standard point cloud model of the target papers for scanning, including color and geometric features. Then, we extract the measured point cloud of the typical jacking operation phase based on the reflection intensity and size information. Next, we map the intensity values of the measured point cloud into the color channel and register the measured point cloud with its standard point cloud model using the normal vector estimation and colored ICP algorithms. Finally, we extract the center point of the measured targets. Numerical experiments and engineering test results show that the proposed method converges quickly with high precision and good robustness, which saves 91.4% of the time compared with the traditional method. In general, this research can provide effective technical support for 3D laser scanning in monitoring the operation phase of bridge jacking. [ABSTRACT FROM AUTHOR]

Why Hydrogen. Nowadays, the energy industry and research laboratories are heavily working on developing ideas and methods to reduce and/or eliminate the carbon dioxide emission to control the problem of global warming. The solution relies on finding alternative green energy resources to reduce the world's dependence on conventional fossil hydrocarbon energy. Green hydrogen gas from water stands on the top of the alternative resources since it does not produce carbon dioxide when burned and in return does not add to global warming. Since seawater is the largest resource on earth, this makes the hydrogen production from seawater the most economically attractive solution. It is very important to avoid using fresh water as a source of hydrogen energy due to the dependence of all living creatures, humans, animals, plants, etc., on such very limited resources. In this paper, the applications of the proposed novel solution of green hydrogen production directly from seawater relies on solving one of the major problems, electrode corrosion. Generating Hydrogen. The direct method to produce green hydrogen from seawater is the electrolysis technique. This technique requires a direct current power supply for the positive and the negative electrodes. The outcome of the electrolysis is decomposing the saltwater to its positively charged hydrogen and sodium ions at the negative electrode and its negatively charged oxygen and chlorine ions at the positive electrode. The Real Challenge. Traditionally in the electrolysis analysis of water, both electrodes are made of metals. At the positive electrode, both the oxygen and the chlorine cause a high rate of corrosion to that electrode. This results in the interruption of the electrolysis process, bad water condition due to the corrosion deposits, and cost burden due to the need to periodically replace the corroded electrodes and/or use high-cost corrosion-resistant alloys. The Novel Solution. A low-cost but powerful solution to the corrosion problem is introduced, tested, and experimentally proved. The novelty of the solution relies on replacing the classic special high-cost metallic positive electrode with a nonmetallic, no-cost, one. The nonmetallic electrode is made of surface rock portions that have high porosity and pore volume and high permeability and pore connectivity and is saturated with saline water. Surface rocks with the above properties exhibit very low resistivity and hence conduct electricity like metallic electrodes. The voltage and the current conducted by such electrode are controlled by the electrode geometry, connectivity, and physical properties. Results and Discussions. Multiple experiments using the proposed nonmetallic high-porosity and high-permeability positive electrode are conducted and presented in this paper. The experimental work is based on testing multiple rock electrodes with different rock properties, sizes, and connectivity in comparison to the metallic ones. The comparison showed that the novel solution solved the corrosion challenges of the metallic electrodes with excellent efficiency. [ABSTRACT FROM AUTHOR]

Mesoporous materials are special nanoporous materials containing well-defined mesochannels with a pore diameter between 2 and 50 nm. The high surface area, ordered structure, tunable pore size, and easiness of functionalization have made mesoporous silica powder and thin films interesting materials for a wide range of applications including drug delivery, absorption, separation, catalysis, energy conversion, and storage. The sol–gel process has emerged as a promising technique for the synthesis of nanostructured mesoporous silica materials as it provides the advantages of low-temperature processing and easy control of the synthesis parameters. Although it offers several advantages over other synthesis techniques, it also has the drawbacks of high sensitivity to processing conditions. Hence, this review paper aims to give critical insights into the sol–gel process, the chemistry of sol–gel silica, the formation mechanism of mesoporosity, and the effects of the reaction parameters. A good understanding of these phenomena is essential to better control and optimize the properties of the final material for specific needs and applications. Additionally, this review paper discusses the different methods applied to the synthesis of nanostructured ordered mesoporous thin film silica, including the Electrochemically Assisted Self-Assembly method of synthesis. The EASA method is a novel and promising technique for the synthesis of well-ordered and vertically aligned pore channels of mesoporous thin films as it is required for mass transport applications. Moreover, the effects of sol composition, pH, applied potential, and deposition time on the final thickness of the thin film are elaborated on in detail. Furthermore, this comprehensive review highlights the potential and opportunities for future research and development in the area to further advance and use its full potential advantages. [ABSTRACT FROM AUTHOR]

Modelica is a very powerful language to simulate a very large set of systems, including electrical, thermal, mechanical, fluidic, control, and has already been used very extensively for several purposes, as the several Modelica conferences testify. Despite of this large literature, no paper seems to be available regarding the use of Modelica for real-time applications or hardware-in-the loop (HIL). This is a field where applications may be very fruitful. In this paper, the possibility of creating mixed software–hardware experiences (i.e., HIL), through combination of a Modelica program, the related simulation tool, a LabVIEW program, and the corresponding hardware is demonstrated. This demonstration is made using as an example a partial simulator of an electric vehicle running in a stand-alone PC, which communicates via User Datagram Protocol (UDP) packets with another PC running the LabVIEW program, which in turn is physically connected with the hardware-under-test. The obtained results are satisfying, given the inherent delay times due to the UDP communication. [ABSTRACT FROM AUTHOR]

In the wake of the COVID-19 pandemic, prioritizing indoor air quality has emerged as a crucial measure for preventing infections. Effective ventilation is vital in mitigating airborne pathogen transmission and maintaining a healthy indoor environment by diluting and removing infectious particles from enclosed spaces. However, increasing the supply of pathogen-free air to enhance infection control can lead to a rise in energy consumption. Nevertheless, evaluating the overall efficacy of ventilation-based infection prevention strategies while considering their energy requirements has posed challenges. This scientific paper introduces the ICEE (Infection Control's Energy Efficiency) index, a newly developed simple integrated index to assess the effectiveness of ventilation strategies in reducing infection risks while accounting for associated energy demands. The paper reviews the current understanding of ventilation strategies, their impact on infection prevention, and their corresponding energy consumption. By employing a straightforward analytical approach, this metric offers a comprehensive framework to optimize ventilation systems for both infection prevention and energy efficiency. To quantify infection risk, a simplified equation model is utilized, incorporating factors such as ventilation effectiveness and filter efficiency, in case of recirculation. Energy demand is determined using approximations and relevant values from existing literature. Reference cases are defined, distinguishing between natural and mechanically ventilated scenarios, as these reference situations influence the energy-related effects of any implemented measures. The paper outlines the methodology employed to develop the index and illustrates its applicability through exemplary measures. The proposed index yields valuable insights for the design, operation, and retrofitting of ventilation systems, enabling informed decision-making towards fostering a healthier and more sustainable built environment. [ABSTRACT FROM AUTHOR]

As network technology advances and more people use devices, data storage has become a significant challenge due to the explosive growth of information and the threat of data leaks. In traditional medical institutions, most medical data is stored centrally through cloud computing technology in the institution's data center. This centralized storage method has many security risks, and once the central server is attacked, it will lead to the loss of medical data, which will lead to the leakage of patients' private data. At the same time, electronic medical records are the most critical data in the current medical field. In the traditional centralized healthcare service system (HSS), there are data leakage problems and tampering with electronic medical records due to human factors. At the same time, each hospital is built independently, resulting in the current centralized healthcare service system having a data silo problem, making it difficult to share medical data between institutions securely. With the increase in the number of users in the system, the electronic medical record data in the system also increases gradually, resulting in the increasing overhead of decryption calculation. Therefore, this paper proposes a blockchain-based access control scheme with multiparty authorization to ensure the security of electronic medical records. The scheme uses an SM encryption algorithm to encrypt the medical data in the system. It adds the patient's signature to ensure the confidentiality and security of the data, and the encrypted electronic medical records (EMRs) are stored in the InterPlanetary File System (IPFS) to realize the distributed storage of EMR. In addition, role-based multiauthorization access control is implemented through smart contract-based to ensure the security of EMR. We have analyzed the security of this paper's solution and compared its performance with the existing schemes based on other cryptographic algorithms. The experimental results show that the proposed solution significantly improves the secure sharing of EMR and provides system performance. [ABSTRACT FROM AUTHOR]

Aircraft engine icing caused by supercooled large droplets (SLD) poses a significant threat to flight safety. In this paper, the SLD impingement characteristics of the rotating spinner were investigated using FLUENT UDS and the governing equations for water droplet motion were solved based on the Eulerian method. The droplet breakup was simulated using the number density equation, while the droplet rebound and splashing were simulated using a semiempirical model. The effects of rotational speed, droplet diameter, and inflow velocity on the SLD impingement characteristics of the rotating spinner were studied. Some new valuable insights have been found for the SLD impingement. The results indicated that as the rotational speed increases, the local collection efficiency of the rotating spinner decreases. Higher rotational speed results in reduced droplet impingement angle and stronger droplet rebound and splashing. For the droplets with diameters smaller than 111 μm, the local collection efficiency increases with the increase of the droplet diameter. However, when the droplet diameter exceeds 111 μm, the local collection efficiency decreases near the leading edge of the rotating spinner. Additionally, the local collection efficiency decreases as the inflow velocity increases near the leading edge of the rotating spinner. However, higher inflow velocities lead to larger droplet impingement angles, resulting in higher local collection efficiency near the tail of the rotating spinner. The critical impingement angle increases with the increase of the inflow velocity, leading to a more pronounced rebound and splashing of SLD. The research in this paper provides useful help for ice shape prediction and anti-icing system design of rotating spinner in SLD environment. [ABSTRACT FROM AUTHOR]

The bioeconomy model provides an alternative view of global economic systems by putting sustainable practices combined with digital approaches at the forefront to tackle issues such as climate change. To address this new business trends, financial institutions began to set up the environmental, social, and governance (ESG) business units to evaluate their business strategies. This paper is aimed at examining the nonfinancial effect created by the digital transformation (DT) activities, highlighting the role of enterprise heterogeneity after the implementation of Environmental Protection Law (EPL) in China. We employ the panel data of A-share listed companies from 2010 to 2020, selecting DT and ESG indicators as the important representations of "Industry 5.0." Our empirical results demonstrate a positive impact of EPL on the ESG performance in sight of resource enterprises (REs), environmental enterprises (EEs), and polluting enterprises (PEs), but a negative impact of EPL on the DT indicators among those environmental related industries. Additional causal relationship regression reveals that enterprise DT has an intrinsic promoting effect on the ESG performance, emphasizing on the high risk of digitization process being the shock transmitters to enterprise nonfinancial indices. Notably, the connectedness of environmental policy illustrates dynamic patterns by parallel trend test and propensity score matching (PSM) DID regression. This paper is prone to benefit lawmakers, regulators, and firm executives responsible for analyzing and assessing enterprise digitization behavior by exploring the influence of macrolevel environmental policy. [ABSTRACT FROM AUTHOR]

Unpredictable variations in load demand and unanticipated component failures are progressively impacting the operation of modern power systems, making system evaluation more stochastic in nature. Although deterministic approaches were formerly the norm for determining system status, probabilistic approaches have greatly improved the capacity to capture the stochastic behavior characteristic of power system operations. The presented work in the paper recommends the use of probabilistic modelling approaches with deterministic approaches, highlighting their crucial function in augmenting the reliability and security of contemporary power systems to unanticipated failures. In this paper, N − 1 security criteria based reliability of the composite power system (CPS) is proposed using an integrated deterministic and probabilistic framework (D-P) considering outage of the transmission line. For the deterministic approach (DA), line overloading on available lines is determined using the static security index (SSI). For the probabilistic approach (PA), reliability indices such as expected loss of power (ELOP), expected frequency of contingency (EFOC), expected loss of load (ELOL), probability of load curtailment (PLC), and expected duration of load curtailments (EDLC) are calculated. Further, for each contingency, a performance index is determined using both approaches to assess the severity of the contingency that occurred on the power system. Based on the N − 1 security criteria based reliability analysis using an integrated D-P framework, a credible critical set of transmission lines is obtained, which can serve as important information to system operators. The proposed techniques have been tested on IEEE 24 bus reliability test system (RTS). [ABSTRACT FROM AUTHOR]

As a commonly used mode of transportation in people's daily lives, the normal operation of railway transportation is crucial. The track circuit, as a key component of the railway transportation system, is prone to malfunctions due to environmental factors. However, the current method of inspecting track circuit faults still relies on the experience of on-site personnel. In order to improve the efficiency and accuracy of fault diagnosis, we propose to establish an intelligent fault diagnosis system. Considering that the fault data are a one-dimensional time series, this paper presents a fault diagnosis method based on the UNet-LSTM network (ULN). The LSTM network is established on the basis of fault data and used for ZPW-2000A track circuit fault diagnosis. However, the use of a single LSTM network has a high error rate in the common fault diagnosis of track circuits. Therefore, this paper proposes a feature extraction method based on the UNet network. This method is used to extract the features of the original data and then input them into the LSTM network for fault diagnosis. Through experiments with on-site fault data, it has been verified that this method can accurately classify seven common track circuit faults. Finally, the superiority of the method is verified by comparing it with other commonly used fault classification methods. [ABSTRACT FROM AUTHOR]

In the realm of structural health monitoring (SHM), understanding the expected behavior of a structure is vital for the timely identification of anomalous activities. Existing methods often model only the physical quantities of monitoring data, neglecting the corresponding temporal information. To address this, this paper presents an innovative deep learning framework that synergistically combines a BiLSTM model, fortified by a temporal pattern attention (TPA) mechanism, with time-encoded temperature and traffic-induced deflection-temporal patterns. The arithmetic optimization algorithm (AOA) is employed for optimal hyperparameter tuning, and incremental learning was implemented to enable real-time updates of the model. Based on the proposed framework, an anomaly detection method was subsequently developed. This method is bidirectional: it uses quantile loss to provide expected ranges for structural behavior, identifying isolated anomalies, while the windowed normalized mutual information (WNMI) based on multivariate kernel density estimation (MKDE) helps detect trend variability caused by decreases in structural stiffness. This framework and the anomaly detection method were validated using data from an operational cable-stayed bridge. The results demonstrate that the method effectively predicts structural behavior and detects anomalies, highlighting the critical role of temporal information in SHM. [ABSTRACT FROM AUTHOR]

The security of communication networks can be compromised through both known and novel attack methods. Protection against such attacks may be achieved through the use of an intrusion detection system (IDS), which can be designed by training machine learning models to detect cyberattacks. In this paper, the KOMIG (knapsack optimization and mutual information gain) IDS was developed to detect network intrusions. The KOMIG IDS combined the strengths of optimization and machine learning together to achieve a high intrusion detection performance. Specifically, KOMIG IDS comprises a 2-stage feature selection procedure; the first was accomplished with a knapsack optimization algorithm and the second with a mutual information gain filter. In particular, we developed an optimization model for the selection of the most important features from a network intrusion dataset. Then, a new set of features was synthesized from the selected features and combined with the selected features to form a candidate features set. Next, we applied an information gain filter to the candidate features set to prune out redundant features, leaving only the features that possess the maximum information gain, which were used to train machine learning models. The proposed KOMIG IDS was applied to the UNSW-NB15 dataset, which is a well-known network intrusion evaluation dataset, and the resulting data, after optimization operation, were used to train four machine learning models, namely, logistic regression (LR), random forest (RF), decision tree (DT), and K-nearest neighbors (KNN). Simulation experiments were conducted, and the results revealed that our proposed KNN-based KOMIG IDS outperformed comparative schemes by achieving an accuracy score of 97.14%, a recall score of 99.46%, a precision score of 95.53%, and an F1 score of 97.46%. [ABSTRACT FROM AUTHOR]

Nowadays, construction industries are using flyash as a potential alternative for cement. Due to its improved mechanical properties, ecofriendly nature, and low cost, geopolymer technology makes use of flyash as a promising future binder material. In this paper, 7 factors such as liquid-to-flyash ratio, silicate-to-hydroxide ratio, curing temperature, curing period, concentration of NaOH (molarity), rest period prior to curing, and dosage of superplasticizer that influence the compressive strength and temperature drop are screened using the Plackett–Burman method for optimization. Here, compressive strength and temperature drop are taken as the main indices of response to analyze the parameters. The significant variables determined from the Plackett–Burman design are further considered for the process of optimization using the response surface methodology. From the analysis, the optimum values of 0.4071 liquid-to-flyash ratio, 2.5 silicate-to-hydroxide ratio, and 6 hours curing period give maximum compressive strength and temperature drop of 28.87 MPa and 5.3°C under the optimized medium in the validation experiment which varies by only 3.93% and 1.85% from the observed value of 27.20 MPa and 5.4°C. [ABSTRACT FROM AUTHOR]