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most exciting work published in the various research areas of the journal.
Soft-wing kites for airborne wind-energy harvesting function as flying tensile membrane structures, each of whose shape depends on the aerodynamic load distribution and vice versa. The strong two-way coupling between shape and loading poses a complex fluid–structure interaction problem. Since computational models for
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Soft-wing kites for airborne wind-energy harvesting function as flying tensile membrane structures, each of whose shape depends on the aerodynamic load distribution and vice versa. The strong two-way coupling between shape and loading poses a complex fluid–structure interaction problem. Since computational models for such problems do not yet meet the requirements of being accurate and at the same time fast, kite designers usually work on the basis of intuition and experience, combined with extensive iterative flight testing. This paper presents a fast aero-structural model of leading-edge inflatable kites for the design phase of airborne wind-energy systems. The fluid–structure interaction solver couples two fast and modular models: a particle system model to capture the deformation of the wing and bridle-line system and a 3D nonlinear vortex step method coupled with viscous 2D airfoil polars to describe the aerodynamics. The flow solver was validated with several wing geometries and proved to be accurate and computationally inexpensive for pre-stall angles of attack. The coupled aero-structural model was validated using experimental data, showing good agreement in the deformations and aerodynamic forces. Therefore, the speed and accuracy of this model make it an excellent foundation for a kite design tool.
Full article
This article introduces a new method for identifying anchor damage faults in fiber composite submarine cables. The method combines the Volterra model of Variation Mode Decomposition (VMD) with singular value entropy to improve the accuracy of fault identification. First, the submarine cable vibration
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This article introduces a new method for identifying anchor damage faults in fiber composite submarine cables. The method combines the Volterra model of Variation Mode Decomposition (VMD) with singular value entropy to improve the accuracy of fault identification. First, the submarine cable vibration signal is decomposed into various Intrinsic Mode Functions (IMFs) using VMD. Then, a Volterra adaptive prediction model is established by reconstructing the phase space of each IMF, and the model parameters are used to form an initial feature vector matrix. Next, the feature vector matrix is subjected to singular value decomposition to extract the singular value entropy that reflects the fault characteristics of the submarine cable. Finally, singular value entropy is used as a feature value to input into the Support Vector Machine (SVM) for classification. Compared with Empirical Mode Decomposition (EMD) and Ensemble Empirical Mode Decomposition (EEMD), the proposed method achieves a higher fault identification accuracy and effectively identifies anchor damage faults in submarine cables. The results of this study demonstrate the feasibility and practicality of the proposed method.
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Body mass index (BMI) and blood biomarkers are not enough to predict cardiovascular disease risk. Apolipoprotein B was identified to be associated with cardiovascular disease (CVD) progression. The Dual-energy X-ray Absorption (DXA) results could be considered as a predictor for cardiovascular disease in
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Body mass index (BMI) and blood biomarkers are not enough to predict cardiovascular disease risk. Apolipoprotein B was identified to be associated with cardiovascular disease (CVD) progression. The Dual-energy X-ray Absorption (DXA) results could be considered as a predictor for cardiovascular disease in a more refined way based on fat distribution. The prediction of CVD risk by simple indicators still cannot meet clinical needs. The association of ApoB with specific fat depot features remains to be explored to better co-predict cardiovascular disease risk. An amount of 5997 adults from National Health and Nutrition Examination Survey (NHANES) were enrolled. Their demographic information, baseline clinical condition, blood examination, and DXA physical examination data were collected. Multivariate regression was used to assess the correlation between ApoB and site-specific fat characteristics through different adjusted models. Smooth curve fittings and threshold analysis were used to discover the turning points with 95% confidence intervals. ApoB is positively correlated with arms percent fat, legs percent fat, trunk percent fat, android percent fat, gynoid percent fat, arm circumference and waist circumference after adjustment with covariates for age, gender, race, hypertension, diabetes, hyperlipidemia, coronary heart disease, smoking status and vigorous work activity. The smooth curve fitting and threshold analysis also showed that depot-specific fat had lower turning points of ApoB in both males and females within the normal reference range of ApoB. Meanwhile, females have a lower increase in ApoB per 1% total percent fat and android percent fat than males before the turning points, while females have a higher growth of ApoB per 1% gynoid percent fat than males. The combined specific fat-depot DXA and ApoB analysis could indicate the risk of CVD in advance of lipid biomarkers or DXA alone.
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Jordan’s water scarcity prompted a national plan whereby treated wastewater is utilized to amend agricultural irrigation water so as to reallocate freshwater to urban/domestic uses. The policy, however, has engendered farmers’ resistance in the Northern Jordan Valley (NJV), causing a stalemate in putting
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Jordan’s water scarcity prompted a national plan whereby treated wastewater is utilized to amend agricultural irrigation water so as to reallocate freshwater to urban/domestic uses. The policy, however, has engendered farmers’ resistance in the Northern Jordan Valley (NJV), causing a stalemate in putting new infrastructure into operation. This research investigated the socio-economic causes of farmer resistance and contestation, and examined the government’s institutional approach to overcome the challenges. We found that the perceived risks of wastewater reuse such as salinization and restrictions from international markets figure prominently in the farmers resistance. As yet, farmers have managed to avoid the shift to treated wastewater use by using the political agency of elite farmers who control the Water Users Associations. These same farmers have adopted informal water access practices to overcome freshwater shortages. At the same time, small producers who don’t have possibilities to access extra water and with less political clout seem more willing to irrigate with treated wastewater. We conclude that understanding the heterogeneous context in which the envisioned wastewater users operate is key to predicting and solving conflicts that arise in treated wastewater reuse projects.
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Research on the links between thermal and visual perception is an ever-evolving field aimed at exploring how one modifies the other. The findings can enhance buildings’ energy performance and the occupants’ well-being. Based on a screening methodology on a substantial article database, this
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Research on the links between thermal and visual perception is an ever-evolving field aimed at exploring how one modifies the other. The findings can enhance buildings’ energy performance and the occupants’ well-being. Based on a screening methodology on a substantial article database, this review article provides an overview of the current state of knowledge by examining studies related to the thermo-photometric perception hypothesis between 1926 and 2022. It analyzes the limitations and contributions of these studies, identifies the most recent advancements, and highlights remaining scientific hurdles. For example, we demonstrate that the “hue-heat” hypothesis appears to be verified for specific experimental conditions conducive to measuring subtle parameter variations.
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High-power electronic devices with multiple heat sources often require temperature uniformity and to operate within their functional temperature range for optimal performance. Micro-channel cooling could satisfy the heat dissipation requirements, but it may cause temperature non-uniformity. In this paper, simulations are performed for
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High-power electronic devices with multiple heat sources often require temperature uniformity and to operate within their functional temperature range for optimal performance. Micro-channel cooling could satisfy the heat dissipation requirements, but it may cause temperature non-uniformity. In this paper, simulations are performed for different geometric parameters of the channel and the position of the heat source. The results show that a flattened channel can effectively reduce the heat source temperature, broadening the straight channel can reduce the flow resistance and enhance heat transfer, while widening the channel at the bend may lead to local dryness. Meanwhile, a thermal model is established to analyze the influence of the position of the heat source. The results also show that with the increase in the curved channel radius, the phenomenon of vapor–liquid separation becomes more obvious, the pressure drop decreases, but the heat transfer effect worsens.
Full article
Despite the well-known cutaneous beneficial effect of thermal water on the skin, no data exist regarding the potential biological effect of orally consumed water on healthy skin. Thus, in this single-center, double-blind, randomized controlled clinical trial conducted on age and menstrual cycle timing-matched
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Despite the well-known cutaneous beneficial effect of thermal water on the skin, no data exist regarding the potential biological effect of orally consumed water on healthy skin. Thus, in this single-center, double-blind, randomized controlled clinical trial conducted on age and menstrual cycle timing-matched healthy female volunteers (24 + 24) consuming water A (oligo-mineral) or water B (medium-mineral) for 1 month (T1), the cutaneous lipidomics were compared. Interestingly, only water A consumers had a statistically significant (p < 0.001) change in cutaneous lipidomics, with 66 lipids different (8 decreased and 58 increased). The cutaneous lipidomics of consumers of water A vs water B were statistically different (p < 0.05). Twenty cutaneous lipids were necessary to predict the water type previously consumed (AUC ~ 70). Our study suggests that drinking oligo-mineral water may change skin biology and may influence the cutaneous barrier, so future dermatological clinical trials should also account for the water type consumed to avoid potential confounders.
Full article
Container terminal automation offers many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A novel lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation.
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Container terminal automation offers many potential benefits, such as increased productivity, reduced cost, and improved safety. Autonomous trucks can lead to more efficient container transport. A novel lane detection method is proposed using score-based generative modeling through stochastic differential equations for image-to-image translation. Image processing techniques are combined with Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and Genetic Algorithm (GA) to ensure fast and accurate lane positioning. A robust lane detection method can deal with complicated detection problems in realistic road scenarios. The proposed method is validated by a dataset collected from the port terminals under different environmental conditions; in addition, the robustness of the lane detection method with stochastic noise is tested.
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This article presents a review of research on smartphone usage in educational science settings published between January 2015 and August 2022, and aims to provide an overview of the constructs evaluated and to identify potential gaps in current research for researchers working on
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This article presents a review of research on smartphone usage in educational science settings published between January 2015 and August 2022, and aims to provide an overview of the constructs evaluated and to identify potential gaps in current research for researchers working on this topic. Specifically, the search for publications in the relevant years was narrowed down to such studies that provided empirical evidence for the impact of smartphone usage on teaching and learning in natural science education. The databases used for the search were ERIC, Scopus, and Web of Science. In total, 100 articles were surveyed. The study findings were categorized regarding the type of smartphone usage, as well as the type of educational institution and constructs investigated. Overall, the results from this review show that smartphone usage in educational science environments has the potential for rather positive effects, such as an increase in learning achievements or an increase in motivation, and smartphone usage rarely leads to detrimental effects. Despite the substantial amount of studies to date, more research in these areas would allow for more generalized statistical results and analyses and is therefore desirable.
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Most bubble breakage models have been developed for multiphase simulations using Euler-Euler (EE) approaches. Commonly, they are linked with population balance models (PBM) and are validated by making use of Reynolds-averaged Navier-Stokes (RANS) turbulence models. The latter, however, may be replaced by alternate
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Most bubble breakage models have been developed for multiphase simulations using Euler-Euler (EE) approaches. Commonly, they are linked with population balance models (PBM) and are validated by making use of Reynolds-averaged Navier-Stokes (RANS) turbulence models. The latter, however, may be replaced by alternate approaches such as Large Eddy simulations (LES) that play a pivotal role in current developments based on lattice Boltzmann (LBM) technologies. Consequently, this study investigates the possibility of transferring promising bubble breakage models from the EE framework into Euler-Lagrange (EL) settings aiming to perform LES. Using our own model, it was possible to reproduce similar bubble size distributions (BSDs) for EL and EE simulations. Therefore, the critical Weber (Wecrit) number served as a threshold value for the occurrence of bubble breakage events. Wecrit depended on the bubble daughter size distribution (DSD) and a set minimum time between two consecutive bubble breakage events. The commercial frameworks Ansys Fluent and M-Star were applied for EE and EL simulations, respectively. The latter enabled the implementation of LES, i.e., the use of a turbulence model with non-time averaged entities. By properly choosing Wecrit, it was possible to successfully transfer two commonly applied bubble breakage models from EE to EL. Based on the mechanism of bubble breakage, Wecrit values of 7 and 11 were determined, respectively. Optimum Wecrit were identified as fitting the shape of DSDs, as this turned out to be a key criterion for reaching optimum prediction quality. Optimum Wecrit values hold true for commonly applied operational conditions in aerated bioreactors, considering water as the matrix.
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In order to handle their regulatory and legal responsibilities and to retain trustworthy strategic partnerships, enterprises need to be dedicated to guaranteeing the privacy, accessibility, and authenticity of the data at their disposal. Companies can become more resilient in the face of information
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In order to handle their regulatory and legal responsibilities and to retain trustworthy strategic partnerships, enterprises need to be dedicated to guaranteeing the privacy, accessibility, and authenticity of the data at their disposal. Companies can become more resilient in the face of information security threats and cyberattacks by effectively integrating security strategies. The goal of this article is to describe a plan that a corporation has implemented in the information technology industry in order to ensure compliance with International Organization for Standardization (ISO) 27001. This research demonstrates an examination of the reasons that force enterprises to make a investment in ISO 27001 in addition to the incentives that might be acquired from having undergone this process. In addition, the research examines the reasons that push firms to make an investment in ISO 27001. More particularly, the research investigates an international IT consulting services institution that is responsible for the implementation of large-scale business assistance insertion and projects. It demonstrates the risk management framework and the administrative structure of the appropriate situations so that its procedures are adequate and also in line with the guidelines founded by ISO 27001. In conclusion, it discusses the problems and difficulties that were experienced.
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Obesity, currently defined as a disease, is associated with a number of metabolic disorders, and oxidative stress is discussed as the link between them. The aim of this study was to analyze the plasma markers reflecting oxidative modification of lipids and lipoproteins, oxidized
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Obesity, currently defined as a disease, is associated with a number of metabolic disorders, and oxidative stress is discussed as the link between them. The aim of this study was to analyze the plasma markers reflecting oxidative modification of lipids and lipoproteins, oxidized LDL (oxLDL) and thiobarbituric acid reactive substances (TBARS), under the influence of the 75 g of oral glucose during oral glucose tolerance test (OGTT), in patients with increased body mass. One hundred twenty individuals of both genders (46 women and 74 men) aged 26 to 75 years with increased body mass (BMI > 25 kg/m2) were recruited for the study. OGTT was performed in each of the qualified persons, and glycemia, insulinemia, and concentrations of oxLDL and TBARS were measured fasting and at 120 min of OGTT. The homeostasis model assessment of insulin resistance (HOMA-IR) was used to assess the degree of insulin resistance (IR). In order to assess the changes of the investigated parameters under the influence of 75 g glucose, the index ROGTT = [120’]/[0’] was calculated to obtain oxLDL-ROGTT and TBARS-ROGTT. The statistical analysis was performed in the entire study population and subsequent groups from H1 to H4, defined by HOMA-IR quartiles. In the entire study population and the subgroups, oxidative stress markers changed during OGTT. From H1 to H4 group, increasing oxLDL and TBARS were observed both in the fasting state and at 120 min of OGTT, and the oxLDL-ROGTT index decreased from the H2 to the H4 group. The intensification of IR in people with increased body mass may predispose them to enhanced oxidative modification of lipoproteins. Individual reduction in the concentration of oxLDL during OGTT, in reference to fasting value (decreased oxLDL-ROGTT), suggests increased uptake of modified lipoproteins by scavenger receptor-presenting cells or increased migration to the vascular wall.
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The interest in radiation protection in industrial sectors involving Naturally Occurring Radioactive Materials (NORM) is increasingly growing. This is due also to the recent implementation of the European Council Directive 59/2013/Euratom which in Italy and in the other European Union Member States extends
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The interest in radiation protection in industrial sectors involving Naturally Occurring Radioactive Materials (NORM) is increasingly growing. This is due also to the recent implementation of the European Council Directive 59/2013/Euratom which in Italy and in the other European Union Member States extends the field of application to industrial sectors never involved before. This paper reports main results of a research project on radiation protection in industries involving NORM carried out in Italy aimed to provide useful tools for stakeholders to comply new legal obligations. The project activities were mainly focused on different aspects relevant to the NORM involving industries, accounting for the positive list reported in the Italian law. Firstly, the inventory of the industries currently operating in Italy in order to identify the industrial sectors with an important radiological impact on population and workers was updated. Based on this information, a general methodology was elaborated taking into account a graded approach. The first phase consists in the identification and characterization of the most critical exposure scenarios and of the radiological content of NORMs involved in the different phases of the industrial processes. In the second phase calculation methods were developed for dose estimation for workers and members of public. These tools require the use of existing and well tested calculation codes, and the development of a dedicated user-friendly software.
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African swine fever (ASF) is a viral haemorrhagic disease found in domestic and wild boars caused by the African swine fever virus (ASFV). A highly virulent strain was used to evaluate the efficacy of newly developed vaccine candidates. The ASFV strain SY18 was
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African swine fever (ASF) is a viral haemorrhagic disease found in domestic and wild boars caused by the African swine fever virus (ASFV). A highly virulent strain was used to evaluate the efficacy of newly developed vaccine candidates. The ASFV strain SY18 was isolated from the first ASF case in China and is virulent in pigs of all ages. To evaluate the pathogenesis of ASFV SY18 following intraoral (IO) and intranasal (IN) infections, a challenge trial was conducted in landrace pigs, with intramuscular (IM) injection as a control. The results showed that the incubation period of IN administration with 40–1000 50 % tissue culture infective dose (TCID50) was 5–8 days, which was not significantly different from that of IM inoculation with 200 TCID50. A significantly longer incubation period, 11–15 days, was observed in IO administration with 40–5000 TCID50. Clinical features were similar among all infected animals. Symptoms, including high fever (≥40.5 °C), anorexia, depression, and recumbency, were observed. No significant differences were detected in the duration of viral shedding during fever. There was no significant difference in disease outcome, and all animals succumbed to death. This trial showed that IN and IO infections could be used for the efficacy evaluation of an ASF vaccine. The IO infection model, similar to that of natural infection, is highly recommended, especially for the primary screening of candidate vaccine strains or vaccines with relatively weak immune efficacy, such as live vector vaccines and subunit vaccines.
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The northern Songnen Plain in China is one of the most important areas for grain production in China, which has been increasingly affected by wind erosion in recent years. This study analyzed the dynamic spatiotemporal distribution of wind erosion in the northern Songnen
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The northern Songnen Plain in China is one of the most important areas for grain production in China, which has been increasingly affected by wind erosion in recent years. This study analyzed the dynamic spatiotemporal distribution of wind erosion in the northern Songnen Plain from 2010 to 2018 using the Revised Wind Erosion Equation model. The ecological service function of the study area was evaluated by constructing a spatial visualization map of windbreak and sand-fixation service flow. Wind erosion worsened from 2010 to 2018. The gravity center of different categories of wind erosion intensity moved to the northeast, indicating a risk of spreading from south to north. The amount of wind erosion in 2018 increased by 50.78% compared with 2010. The increase of wind force and temperature and the decrease of precipitation may have contributed to these trends. Long-term wind erosion led to soil coarsening, decreased soil organic matter, soil organic carbon, and total nitrogen contents, and increased soil CaCO3 and pH, which may be one reason for slight soil salinization observed in some regions. Therefore, windbreak and sand-fixation management and eco-environmental protection are urgently required. This study is the first detailed assessment of wind erosion in the northern Songnen Plain on a regional scale and the first to propose measures for ecological restoration and desertification control.
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Enhanced drought, more frequent rainfall events and increased inter-annual variability of precipitation are the main trends of climate expected for the Mediterranean. Drought is one of the most important stressors for plants and significantly impacts plant communities causing changes in plant composition and
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Enhanced drought, more frequent rainfall events and increased inter-annual variability of precipitation are the main trends of climate expected for the Mediterranean. Drought is one of the most important stressors for plants and significantly impacts plant communities causing changes in plant composition and species dominance. Through an experiment under controlled conditions, we assessed the response of Mediterranean species from different functional groups (annual grass, annual forb, annual legume, and perennial shrub) to moderate and severe water deficit. Changes in plant traits (leaf dry matter), biomass and physiology (water status, photosynthesis, pigments, and carbohydrate) were evaluated. The studied species differed in their response to water deficit. Ornithopus compressus, the legume, showed the strongest response, particularly under severe conditions, decreasing leaf relative water content (RWC), pigments and carbohydrates. The grass, Agrostis pourreti and the forb, Tolpis barbata, maintained RWC, indicating a higher ability to cope with water deficit. Finally, the shrub, Cistus salviifolius, had the lowest response to stress, showing a higher ability to cope with water deficit. Despite different responses, plant biomass was negatively affected by severe water deficit in all species. These data provide background for predicting plant diversity and species composition of Mediterranean grasslands and Montado under climate change conditions.
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Self-consumption of the energy generated by photovoltaics (PV) is playing an increasingly important role in the power grid. “Prosumer” systems consume part of the produced energy directly to meet the local demand, which reduces the feed-in into as well as the demand from
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Self-consumption of the energy generated by photovoltaics (PV) is playing an increasingly important role in the power grid. “Prosumer” systems consume part of the produced energy directly to meet the local demand, which reduces the feed-in into as well as the demand from the grid. In order to analyse the effects of PV self-consumption in the power grid, we introduce a stochastic bottom-up model of PV power generation and local consumption in the control area of the German transmission system operator TransnetBW. We set up a realistic portfolio of more than 100,000 PV/prosumer systems to generate representative time series of PV generation and consumption as a basis to derive self-consumption and feed-in. This model allows for the investigation of the time-dependent behaviour in detail for the full portfolio whereas measurements are presently only available as aggregated feed-in time series over a nonrepresentative subset of systems. We analyse the variation of self-consumption with PV generation and consumption at the portfolio level and its seasonal, weekly and diurnal cycles. Furthermore, we study a scenario of 100% prosumers as a limiting case for a situation without subsidized feed-in tariffs and local energy storage.
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Fe-20Cr-25Ni-Nb steel is an important material for developing highly compact and efficient nuclear power systems by using the supercritical CO2 Brayton cycle. The in-core materials should possess excellent oxidation resistance in a high-temperature CO2 environment. In this work, a new 20Cr-25Ni-Nb
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Fe-20Cr-25Ni-Nb steel is an important material for developing highly compact and efficient nuclear power systems by using the supercritical CO2 Brayton cycle. The in-core materials should possess excellent oxidation resistance in a high-temperature CO2 environment. In this work, a new 20Cr-25Ni-Nb steel with a minor Mo addition was developed, and its oxidation behavior was investigated in a pure CO2 environment at 650 °C under 3.5 MPa. The experimental results show that the oxidation kinetics of the steels followed the parabolic law with the test time, and the oxidation process was controlled by diffusion. The 20Cr-25Ni-Nb steel showed better oxidation resistance after Mo addition, which was attributed to the synergistic effects of Nb and Mo during the oxide scale formation process. In a high-temperature environment, the volatilization of Mo promoted the outward diffusion of Nb, resulting in the formation of an Nb-rich layer at the oxide/metal interface, which slowed the outward diffusion of Fe for the formation of the outermost Fe-oxide layer. Although the volatile nature of Mo at high temperatures promoted the outward diffusion of Nb, the addition of Mo had no significant influence on the overall structure of the oxide scales, which consisted of an outer Cr-rich oxide layer and an inner spinel oxide layer.
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Human–computer interaction (HCI) research involves the design and use of computer technology, focusing in particular on the interfaces between people (users) and computers. HCI researchers observe the ways in which humans interact with computers and design technologies that allow them to
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Human–computer interaction (HCI) research involves the design and use of computer technology, focusing in particular on the interfaces between people (users) and computers. HCI researchers observe the ways in which humans interact with computers and design technologies that allow them to interact in novel ways. As HCI evolves into HCI 2.0, user experiences and feedback become ever more relevant. This Special Issue, “Human Computer Interactions 2.0”, presents 11 excellent papers about topics related to human–computer interactions. It aims to provide a broad international forum for world researchers, engineers and professionals in human–computer interaction research for the discussion and exchange of various scientific, technical and management discoveries across the world.
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Degradation of lake ecosystem is a common problem existing in many countries. Remediation of degraded lake is urgently needed in order to maintain water safety and lake ecosystem health. Restoration of submerged macrophyte is considered as an important measure of ecological remediation of
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Degradation of lake ecosystem is a common problem existing in many countries. Remediation of degraded lake is urgently needed in order to maintain water safety and lake ecosystem health. Restoration of submerged macrophyte is considered as an important measure of ecological remediation of shallow lakes after pollution loading get effectively controlled. Nowadays, enclosures resembling those used in aquaculture historically are widely used for submerged macrophyte restoration. Although submerged macrophyte can be successfully restored in enclosure, it’s contribution to the whole lake ecological remediation is limited. Fish manipulation, which reduces fish stock and adjusts fish community structure, was found able to improve water quality and promote submerged macrophyte restoration in many lakes. However, the role of fish in ecological restoration do not receive enough attention in many ecological remediation projects. Future studies are required to better understand the role of fish in lake nutrient cycle and the influence on submerged macrophyte to help develop theory that better guide the fish manipulation for the ecological remediation in shallow lakes. In the end, we want to point out that manipulation of fish community structure following by natural restoration and/or artificial planting of submerged macrophyte could be an effective strategy for whole lake ecological remediation of shallow lakes, and suggest that fish manipulation measure should be tested in more ecological remediation projects of shallow lakes worldwide.
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Renewable power generation has increased in recent years, which has led to a decrease in the use of synchronous generators (SGs). These power plants are mainly connected to the power system through electronic converters. One of the main differences between electronic converters connected
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Renewable power generation has increased in recent years, which has led to a decrease in the use of synchronous generators (SGs). These power plants are mainly connected to the power system through electronic converters. One of the main differences between electronic converters connected to power systems and SGs connected to the grid is the current contribution during faults, which can have an impact on protection systems. New grid codes set requirements for fast current injection, but the converters’ maximum current limitation during faults make it challenging to develop control strategies for such current contribution. This paper presents a positive and negative sequence current injection strategy according to the new Spanish grid code requirements for the novel grid-forming converter control algorithm based on virtual-flux orientation. The behavior of the proposed strategy is tested in a hardware in the loop (HiL) experimental set-up under balanced faults, meaning that the fault is symmetrically distributed among the three phases, and unbalanced faults, where the fault current is distributed asymmetrically between the phases.
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In rehabilitation settings that exploit Mixed Reality, a clinician risks losing empathy with the patient by being immersed in different worlds, either real and/or virtual. While the patient perceives the rehabilitation stimuli in a mixed real–virtual world, the physician is only immersed in
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In rehabilitation settings that exploit Mixed Reality, a clinician risks losing empathy with the patient by being immersed in different worlds, either real and/or virtual. While the patient perceives the rehabilitation stimuli in a mixed real–virtual world, the physician is only immersed in the real part. While in rehabilitation, this may cause the impossibility for the clinician to intervene, in skill assessment, this may cause difficulty in evaluation. To overcome the above limitation, we propose an innovative Augmented Reality (AR) framework for rehabilitation and skill assessment in clinical settings. Data acquired by a distributed sensor network are used to feed a “shared AR” environment so that both therapists and end-users can effectively operate/perceive it, taking into account the specific interface requirements for each user category: (1) for patients, simplicity, immersiveness, engagement and focus on the task; (2) for clinicians/therapists, contextualization and natural interaction with the whole set of data that is linked with the users’ performances in real-time. This framework has a strong potential in Occupational Therapy (OT) but also in physical, psychological, and neurological rehabilitation. Hybrid real and virtual environments may be quickly developed and personalized to match end users’ abilities and emotional and physiological states and evaluate nearly all relevant performances, thus augmenting the clinical eye of the therapist and the clinician-patient empathy. In this paper, we describe a practical exploitation of the proposed framework in OT: setting-up the table for eating. Both a therapist and a user wear Microsoft HoloLens 2. First, the therapist sets up the table with virtual furniture. Next, the user places the corresponding real objects (also in shape) to match them as closely as possible to the corresponding virtual ones. The therapist’s view is augmented during the test with motion, balance, and physiological estimated cues. Once the training is completed, he automatically perceives deviations in the position and attitude of each object and the elapsed time. We used a camera-based localization algorithm achieving a level of accuracy of 5 mm with a confidence level of 95% for position and 1° for rotation. The framework was designed and tested in collaboration with clinical experts of Villa Rosa rehabilitation hospital in Pergine (Italy), involving both a set of patients and healthy users to demonstrate the effectiveness of the designed architecture and the significance of the analyzed parameters between healthy users and patients.
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Herein, we prepared Pt2CeO2 heterojunction nanocluster (HJNS) on multiwalled carbon nanotubes (MWCNTs) in deep eutectic solvents (DESs) which is a special class of ionic liquids. The catalyst was then heat-treated at 400 °C in N2 (refer to Pt2 [...] Read more.
Herein, we prepared Pt2CeO2 heterojunction nanocluster (HJNS) on multiwalled carbon nanotubes (MWCNTs) in deep eutectic solvents (DESs) which is a special class of ionic liquids. The catalyst was then heat-treated at 400 °C in N2 (refer to Pt2CeO2/CNTs-400). The Pt2CeO2/CNTs-400 catalyst showed remarkably improved electrocatalytic performance towards methanol oxidation reaction (MOR) (839.1 mA mgPt−1) compared to Pt2CeO2/CNTs-500 (620.3 mA mgPt−1), Pt2CeO2/CNTs-300 (459.2 mA mgPt−1), Pt2CeO2/CNTs (641.6 mAmg−1) (the catalyst which has not been heat-treated) and commercial Pt/C (229.9 mAmg−1). Additionally, the Pt2CeO2/CNTs-400 catalyst also showed better CO poisoning resistance (onset potential: 0.47 V) compared to Pt2CeO2/CNTs (0.56 V) and commercial Pt/C (0.58 V). The improved performance of Pt2CeO2/CNTs-400 catalyst is attributed to the addition of appropriate CeO2, which changed the electronic state around the Pt atoms, lowered the d-band of Pt atoms, formed more Ce-O-Pt bonds acting as new active sites, affected the adsorption of toxic intermediates and weakened the dissolution of Pt; on the other hand, with the assistance of thermal treatment at 400 °C, the obtained Pt2CeO2 HJNS expose more new active sites at the interface between Pt and CeO2 to enhance the electrochemical active surface area (ECSA) and the dehydrogenation process of MOR. Thirdly, DES is beneficial to the increase of the effective component Pt(0) in the carbonization process. The study shows a new way to construct high-performance Pt-CeO2 catalyst for the direct methanol fuel cell (DMFC).
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Amino derivatives of purine (2-, 6-, 8-, and N-NH2) have found many applications in biochemistry. This paper presents the results of a systematic computational study of the substituent and solvent effects in these systems. The issues considered are the electron-donating properties
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Amino derivatives of purine (2-, 6-, 8-, and N-NH2) have found many applications in biochemistry. This paper presents the results of a systematic computational study of the substituent and solvent effects in these systems. The issues considered are the electron-donating properties of NH2, its geometry, π-electron delocalization in purine rings and tautomeric stability. Calculations were performed in ten environments, with 1 < ε < 109, using the polarizable continuum model of solvation. Electron-donating properties were quantitatively described by cSAR (charge of the substituent active region) parameter and π-electron delocalization by using the HOMA (harmonic oscillator model of aromaticity) index. In aminopurines, NH2 proximity interactions depend on its position and the tautomer. The results show that they are the main factor determining how solvation affects the electron-donating strength and geometry of NH2. Proximity with the NH∙∙∙HN repulsive interaction between the NH2 and endocyclic NH group results in stronger solvent effects than the proximity with two attractive NH∙∙∙N interactions. The effect of amino and nitro (previously studied) substitution on aromaticity was compared; these two groups have, in most cases, the opposite effect, with the largest being in N1H and N3H purine tautomers. The amino group has a smaller effect on the tautomeric preferences of purine than the nitro group. Only in 8-aminopurine do tautomeric preferences change: N7H is more stable than N9H in H2O.
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Recently, a novel approach in the field of Industry 4.0 factory operations was proposed for a new generation of automated guided vehicles (AGVs) that are connected to a virtualized programmable logic controller (PLC) via a 5G multi-access edge-computing (MEC) platform to enable remote
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Recently, a novel approach in the field of Industry 4.0 factory operations was proposed for a new generation of automated guided vehicles (AGVs) that are connected to a virtualized programmable logic controller (PLC) via a 5G multi-access edge-computing (MEC) platform to enable remote control. However, this approach faces a critical challenge as the 5G network may encounter communication disruptions that can lead to AGV deviations and, with this, potential safety risks and workplace issues. To mitigate this problem, several works have proposed the use of fixed-horizon forecasting techniques based on deep-learning models that can anticipate AGV trajectory deviations and take corrective maneuvers accordingly. However, these methods have limited prediction flexibility for the AGV operator and are not robust against network instability.To address this limitation, this study proposes a novel approach based on multi-horizon forecasting techniques to predict the deviation of remotely controlled AGVs. As~its primary contribution, the work presents two new versions of the state-of-the-art transformer architecture that are well-suited to the multi-horizon prediction problem. We conduct a comprehensive comparison between the proposed models and traditional deep-learning models, such as the long short-term memory (LSTM) neural network, to evaluate the performance and capabilities of the proposed models in relation to traditional deep-learning architectures.The results indicate that (i) the transformer-based models outperform LSTM in both multi-horizon and fixed-horizon scenarios, (ii) the prediction accuracy at a specific time-step of the best multi-horizon forecasting model is very close to that obtained by the best fixed-horizon forecasting model at the same step, (iii) models that use a time-sequence structure in their inputs tend to perform better in multi-horizon scenarios compared to their fixed horizon counterparts and other multi-horizon models that do not consider a time topology in their inputs, and (iv) our experiments showed that the proposed models can perform inference within the required time constraints for real-time decision making.
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Fish freshness and quality can be measured through several indices that can be both chemical and physical. The storage temperature and the time that elapses following the catching of the fish are fundamental parameters that define and influence both the degree of freshness
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Fish freshness and quality can be measured through several indices that can be both chemical and physical. The storage temperature and the time that elapses following the catching of the fish are fundamental parameters that define and influence both the degree of freshness and nutritional quality. Moreover, they particularly effect the kind of fish we considered. In this research, it was observed how different temperatures of storage and shelf-life (+4 °C and 0 °C) may affect the metabolic profile of red mullet (Mullus barbatus) and bogue (Boops boops) fish samples over time, specifically observing the alteration of freshness and quality. In particular, a High-Resolution Nuclear Magnetic Resonance (HR-NMR)-based metabolomics approach was applied to study the metabolic profile changes that occur in fish spoilage. The HR-NMR spectroscopy data were useful for calculating a kinetic model that was able to predict the evolution of different compounds related to fish freshness, such as trimethylamine (TMA-N) and adenosine-5′-triphosphate (ATP) catabolites for the K-index. Furthermore, NMR in combination with chemometrics allowed us to estimate a further kinetic model able to represent the spoilage evolution by considering the entire metabolome. In this way, it was also possible to detect further biomarkers characterizing the freshness and quality status of both red mullets and bogues.
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Chitosan is a promising naturally derived polysaccharide to be used in hydrogel forms for pharmaceutical and biomedical applications. The multifunctional chitosan-based hydrogels have attractive properties such as the ability to encapsulate, carry, and release the drug, biocompatibility, biodegradability, and non-immunogenicity. In this review,
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Chitosan is a promising naturally derived polysaccharide to be used in hydrogel forms for pharmaceutical and biomedical applications. The multifunctional chitosan-based hydrogels have attractive properties such as the ability to encapsulate, carry, and release the drug, biocompatibility, biodegradability, and non-immunogenicity. In this review, the advanced functions of the chitosan-based hydrogels are summarized, with emphasis on fabrications and resultant properties reported in literature from the recent decade. The recent progress in the applications of drug delivery, tissue engineering, disease treatments, and biosensors are reviewed. Current challenges and future development direction of the chitosan-based hydrogels for pharmaceutical and biomedical applications are prospected.
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The process of human exploration of the universe has accelerated, and aerospace technology has developed rapidly. The health management and prognosis guarantee of spacecraft systems has become an important basic technology. However, with thousands of telemetry data channels and massive data scales, spacecraft
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The process of human exploration of the universe has accelerated, and aerospace technology has developed rapidly. The health management and prognosis guarantee of spacecraft systems has become an important basic technology. However, with thousands of telemetry data channels and massive data scales, spacecraft systems are increasingly complex. The anomaly detection that relied on simple threshold judgment and expert manual annotation in the past is no longer applicable. In addition, the particularity of the anomaly detection task leads to the lack of fault data for training. Therefore, a data-driven deep transfer learning-based approach is needed for rapid analysis and accurate detection of large-scale data. The control moment gyroscope (CMG) is a significant inertial actuator in the process of large-scale, long-life spacecraft in-orbit operation and mission execution. Its anomaly detection plays a major role in the prevention and elimination of early failures. Based on the research of SincNet and Long Short-Term Memory (LSTM) networks, this paper proposed a Sinc-LSTM neural network based on transfer learning and working condition classification for CMG anomaly detection. First, a two-stage pre-training method is proposed to alleviate the data imbalance, using the Mars Reconnaissance Orbiter (MRO) dataset and a satellite dataset from NASA. Second, the Sinc-LSTM network is designed to enhance the local fitting and long-period memory ability of the model for CMG time series data. Finally, a dynamic threshold judgment anomaly detection method based on working condition classification is designed to accommodate threshold changes for CMG full-cycle anomaly detection. The method is validated on the spacecraft CMG dataset.
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