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We consider how the quasinormal spectrum for the conformal wave operator on the static patch of de Sitter changes in response to the addition of a small potential. Since the quasinormal modes and co-modes are explicitly known, we are able to give explicit formulae for the instantaneous rate of change of each frequency in terms of the perturbing potential. We verify these exact computations numerically using a novel technique extending the spectral hyperboloidal approach of Jaramillo et al. (2021). We propose a definition for a family of pseudospectra that we show capture the instability properties of the quasinormal frequencies. [ABSTRACT FROM AUTHOR]

Power quality is a crucial determinant for integrating wind energy into the electrical grid. This integration necessitates compliance with certain standards and levels. This study presents cascadedfuzzy power control (CFPC) for a variable-speed multi-rotor wind turbine (MRWT) system. Fuzzy logic is a type of smart control system already recognized for its robustness, making it highly suited and reliable for generating electrical energy from the wind. Therefore, the CFPC technique is proposed in this work to control the doubly-fed induction generator (DFIG)-based MRWT system. This proposed strategy is applied to the rotor side converter of a DFIG to improve the current/power quality. The proposed control has the advantage of being model-independent, as it relies on empirical knowledge rather than the specific characteristics of the DFIG or turbine. Moreover, the proposed control system is characterized by its simplicity, high performance, robustness, and ease of application. The implementation of CFPC management for 1.5 MW DFIG-MRWT was carried out in MATLAB environment considering a variable wind speed. The obtained results were compared with the direct power control (DPC) technique based on proportional-integral (PI) controllers (DPC-PI), highlighting that the CFPC technique reduced total harmonic distortion by high ratios in the three tests performed (25%, 30.18%, and 47.22%). The proposed CFPC technique reduced the response time of reactive power in all tests by ratios estimated at 83.76%, 65.02%, and 91.42% compared to the DPC-PI strategy. Also, the active power ripples were reduced by satisfactory proportions (37.50%, 32.20%, and 38.46%) compared to the DPC-PI strategy. The steady-state error value of reactive power in the tests was low when using the CFPC technique by 86.60%, 57.33%, and 72.26%, which indicates the effectiveness and efficiency of the proposed CFPC technique in improving the characteristics of the system. Thus this control can be relied upon in the future. [ABSTRACT FROM AUTHOR]

This paper studies the possibility of connecting Wind Farms (WF) to the electric grid with the use of finite space model predictive command (FS-MPC) to manage wind farms to improve the quality of the current output from the doubly-fed induction generator (DFIG) with considering fault ride-through technique. This proposed system can generate active power and enhance the power factor. Furthermore, the reduction of harmonics resulting from the connection of non-linear loads to the electrical grid is achieved through the self-active filtering mechanism in DFIGs-WF, facilitated by the now algorithm proposed. FS-MPC technique has the ability to improve system characteristics and greatly reduce active power ripples. Therefore, MATLAB software is used to implement and verify the safety, performance, and effectiveness of this designed technique compared to the conventional strategy. The results obtained demonstrated the effectiveness of the proposed algorithm in handling the four operational modes (Maximum power point tracking, Delta, Fault, and Filtering). Additionally, the suggested technique exhibited flexibility, robustness, high accuracy, and fast dynamic response when compared to conventional strategies and some recently published scientific works. On the other hand, the THD value of the current was significantly reduced, obtaining at one test time the values 56.87% and 0.32% before and after filtering, respectively 27.50% and 0.26% at another time of testing, resulting in an estimated THD reduction percentage of 99.43% and 99.05%, respectively. These high percentages prove that the quality of the stream is excellent after applying the proposed strategy. [ABSTRACT FROM AUTHOR]

Reactive and active power vector control of induction generators (IG) are essential requirements for generating high-quality electricity from wind power. These control objectives are challenging and difficult to achieve when using traditional strategies based on estimating reactive/active power, hysteresis comparators, and proportional-integral (PI) regulators due to load variations, changes in the value of rotor resistance, etc. So, to achieve these control objectives, this paper proposes a novel technique for the rotor side converter of IG-based contra-rotating wind power (CRWP) systems. The control based on the neural synergetic-super-twisting controller (NSSTC) is designed to minimize IG power ripples and improve the quality of current. The characteristics of the NSSTC-based strategy are presented, evaluated, and compared to the traditional direct field-oriented command (DFOC) based on traditional PI controllers and other reference techniques from the literature, highlighting that the NSSTC-based strategy is simpler to apply and more robust and performant than others classical nonlinear strategies. Comparative simulations are carried out on both the designed DFOC-NSSTC strategy and the DFOC technique to demonstrate the performance (good quality output power, low total harmonic distortion (THD) value of rotor currents, short response time and high robustness) and advantages of the suggested nonlinear technique. [ABSTRACT FROM AUTHOR]

One of the key environmental problems underlying climate change and global warming is the persistent increase in atmospheric carbon dioxide concentration. Carbon capture and storage (CCS) systems can be based on, among others, solid porous sorbents (e.g., zeolites). A promising alternative to traditionally used sorbents may be appropriately structured hybrid adsorbents. With the proper geometry and synergistic combination of the sorbent with another material, e.g., a catalyst or a substance with certain useful physical features, they can gain new properties. The present study examined the dynamics of CO2 sorption in core–shell particles and, as a reference, in particles with a uniform structure. It was assumed that the sorbent (zeolite 5A) incorporated in a single particle had the form of microcrystals, which implies a bidisperse particle structure. As a second particle-forming material, a nickel catalyst (behaving as an inert) was adopted. The computational results confirmed that particle structure can provide an additional design parameter for adsorption columns and adsorptive reactors. The sorption-inactive shell proved to play a protective role when thermal waves moved through the bed. In addition, an important element determining sorption dynamics in core–shell particles was revealed to be the structure (e.g., mean pore diameter) controlling intraparticle mass transport. [ABSTRACT FROM AUTHOR]

Purpose: What matters is that blockchain may be used to record anything of value, not only financial transactions. It is becoming increasingly clear that blockchain technology will drastically alter several industries, notably finance. Without a question, the financial industry is leading the way in the use of blockchain technology. Blockchain is quickly transforming the world economy. Given that distributed ledger technology, or blockchain, has the potential to always have a positive impact on society and the economy, this impact is crucial. Actually, there are more than just economic advantages to the blockchain, and some organizations have already begun to use its technological capabilities to solve issues in the real world. To determine the influence of applied blockchain on economic sustainability as well as the benefits and drawbacks of blockchain application for economy, this study will do so. Design/ methodology/ approach: The terms “blockchain” and “ economy” were used to find qualitative information in earlier work. Finally, 50 articles in the fields of business, management, and accounting that had undergone peer review as well as book chapters and conference proceedings were chosen. White papers and unreviewed books were removed as non-scientific sources. Qualitative data were collected from previous literature using the keywords “blockchain” and “economy”. Then, preliminary data were used, by conducting 15 interviews with experts and managers in the financial sector in Egypt about their opinion on the adoption of artificial intelligence and its impact on economic sustainability. Findings: From the interviews, the study collected more detailed information about the blockchain. This could be represented in three main themes: theme of blockchain advantages, theme of blockchain disadvantages and challenges and theme of blockchain opportunities. Finally, some recommendations were made to decision makers as well as future researchers in this field according to the study results. [ABSTRACT FROM AUTHOR]

The increasing use of solar energy for electricity production has led to a directly proportional growth in the production of solar cells. Photovoltaic (PV) performance of silicon solar cells can be improved by using more efficient technologies, optimizing processes, and changing behavior in order to reduce operational costs and greenhouse gas emissions. In order to propose solutions for commercial solar cell production with better performance, this article presents an experimental assessment on Supplementary Oxide Layers (SOLs) that are deposited on the surface of a solar cell absorber layer. SOLs are typically used to improve the performance of solar cells by passivating surface defects, reducing recombination losses, and improving the electrical contact between the absorber layer and the metal electrodes. The obtained solar cells are tested under natural sunlight conditions, following a variable dynamic electronic charge profile. The experimental results along with the corresponding I-V and P-V curves, are assessed according to the process parameters, the lighting parameters, and the dynamic load scenario. SOLs have been shown to improve the Power Conversion Efficiency (PCE) of solar cells considerably. The proposed method for increasing the energy efficiency of solar cells can be applied to any type of commercial solar cell and it is easy to implement at the industrial or research level by controlling process parameters. The integration of the whole process, i.e. development of precursor solutions, deposition of thin films, and testing of electrical properties is another contribution of the current study, along with its interdisciplinary character, which involves materials science, electronics, and software programming. [ABSTRACT FROM AUTHOR]

The rise of the renewable energy sources (RES) in microgrids has increased the impact of damping and low inertia on network stability. This gives rise to several issues in the power systems, including power fluctuations from variable RES, degradation of the frequency regulation, voltage surges, and oversupply from grid‐connected distributed generators. This paper presents a cascaded hybrid load‐frequency controller for an airport microgrid that addresses frequency fluctuations caused by load changes. It is combining a self‐adaptive fuzzy controller (SAF) and a classical two‐degree‐of‐freedom proportional integral derivative (PID) controller (2DOFPID) called CSAF‐2DOFPID. It is applied to the control section of a diesel generator, an electric aircraft energy storage system, and a demand response program. The controller parameters are optimized using a suggested hybrid differential artificial hummingbird algorithm (D‐AHA) to minimize frequency deviation. The proposed control framework is simulated on an airport microgrid comprising various components, and the impact of time delay on the controller's signals, system uncertainty is also examined. The simulation results demonstrate that the proposed self‐adaptive cascaded fuzzy controller outperforms other controllers such as PID, CF‐PID, and CF‐2DOFPID in reducing frequency fluctuations, and the D‐AHA algorithm achieves favourable results compared to other algorithms in the optimal tuning controller parameters. [ABSTRACT FROM AUTHOR]

The paper proposes a nonlinear controller called dual super-twisting sliding mode command (DSTSMC) for controlling and regulating the rotor side converter (RSC) of multi-rotor wind power systems that use doubly-fed induction generators. It was proposed that this controller be developed as an alternative to the direct power control (DPC), which makes use of a pulse width modulation (PWM) strategy to regulate the RSC's functioning. Overcoming the power/current quality issue with the proposed technique (DPC-DSTSMC-PWM) is characterized by great robustness and excellent performance. The designed strategy was contrasted with the standard method of control and other methods already in use. So, the unique proposed control strategy's robustness, performance, efficiency, and efficacy in enhancing system characteristics were tested and validated in Matlab/Simulink. In both tests, the proposed method resulted in significant improvements, reducing active power ripples by 83.33%, 57.14%, and 48.57% in the proposed tests. When compared with the traditional regulation method, the reduction rates of reactive power ripples are 64.06%, 52.47%, and 68.7% in the tests. However, in contrast to the conventional method, the proposed tests showed a decrease of between 72.46%, 50%, and 76.22% in the value of total harmonic distortion (THD) of the provided currents. These ratios show how effective the proposed plan is in ameliorating and enhancing aspects of the energy system. [ABSTRACT FROM AUTHOR]

Energy ripples are among the common problems in renewable energies as a result of using less efficient strategies. In this work, a new technique is suggested to control a doubly-fed induction generator (DFIG) using the pulse width modulation (PWM). The new technique is based on the combination of neural networks and fractional-order control to minimize the reactive and active power ripples of the DFIG-based variable speed dual-rotor wind turbine system. The suggested fractional-order neural control (FONC) with the PWM is a simple, robust and a high-performance strategy. Simulation is performed using Matlab software to validate the effectiveness of the designed control of 1.5 MW DFIG and the obtained results are compared with the traditional direct power control (DPC) in different working conditions. In addition, the comparison between the suggested control and the DPC is performed in the cases of changing or not changing the device parameters in terms of ripple ratio, dynamic response, steady-state error, current quality, and overshoot of active and reactive power of the DFIG. As compared to the DPC, the proposed FONC technique improves the active and reactive power ripples by 65.71% and 84.74%, respectively. Also, improves the overshoot of the active and reactive power by 71.33% and 91.72%, respectively. The simulation results demonstrate the high performance and robustness of the FONC technique for the parametric variations of the DFIG-based variable speed dual-rotor wind turbine system compared to the DPC control. [ABSTRACT FROM AUTHOR]

Motivation: The COVID-19 pandemic has had a significant impact on economic research, particularly in analyzing the effects of the virus on entire economies, specific sectors, and individual businesses. While there have been numerous studies on the pandemic's impact on the labor market, various economic sectors, and the environment, there remains a gap in research exploring the relationship between economics and linguistic aspects, such as language. Aim: The purpose of this article is to address this research gap by examining the connection between language and economics. Specifically, the authors focus on the influence of linguistic variables on economic categories. In this study, the authors adopt the perspective that language can affect economic activities and aim to analyze how the grammatical form used in communication influences the assessment of the effectiveness of economic policy. By exploring this aspect, the article aims to contribute to a deeper understanding of the interplay between language and economics. Results: Authors show that language may also be an essential framing instrument, while various grammatical moods affect the perception of messages that concern economic issues differently and are perceived differently depending on the level of identification with a given policy. [ABSTRACT FROM AUTHOR]

Although coastal ecosystems are naturally submitted to temporal variations of salinity, salinization has been increasing over time threatening coastal biodiversity. Species that exploit such habitats can thus be exposed to brackish water at different life stages. However, the impacts of variations of salinity on wildlife remain poorly understood. This is particularly true for coastal amphibians, due to the strong dependency of early life stages (embryos and larvae) on aquatic environments. In order to investigate the effect of salinity during egg laying and embryonic and larval development of coastal amphibians, we used a full-factorial design to expose reproductive adults, eggs, and larvae of coastal spined toads (Bufo spinosus) to fresh (0 g.l−1) or brackish water (4 g.l−1). At egg laying, we evaluated parental investment in reproduction. During embryonic and larval development, we assessed effects on survival, development, and growth. We highlighted strong effects of environmental salinity on reproduction (reduced egg laying time, marginally reduced egg size, and reduced investment in reproduction). Responses to salinity were highly dependent on the developmental stages of exposure (stronger effects when individuals were exposed during embryonic development). These effects carried over when exposure occurred at egg laying or during embryonic development, highlighting the importance of the environmental conditions during early life on ontogenetic trajectories. We also highlighted partial compensation when individuals were transferred back to freshwater. Whether the magnitude of these responses can allow coastal biodiversity to overcome the observed detrimental effects of salinization remain to be assessed. [ABSTRACT FROM AUTHOR]

Many individuals undergo mating and/or other aspects of reproductive experience at some point in their lives, and pregnancy and childbirth in particular are associated with alterations in the prevalence of several psychiatric disorders. Research in rodents shows that maternal experience affects spatial learning and other aspects of hippocampal function. In contrast, there has been little work in animal models concerning how reproductive experience affects cost-benefit decision making, despite the relevance of this aspect of cognition for psychiatric disorders. To begin to address this issue, reproductively experienced (RE) and reproductively naïve (RN) female Long-Evans rats were tested across multiple tasks that assess different forms of cost-benefit decision making. In a risky decision-making task, in which rats chose between a small, safe food reward and a large food reward accompanied by variable probabilities of punishment, RE females chose the large risky reward significantly more frequently than RN females (greater risk taking). In an intertemporal choice task, in which rats chose between a small, immediate food reward and a large food reward delivered after a variable delay period, RE females chose the large reward less frequently than RN females. Together, these results show distinct effects of reproductive experience on different forms of cost-benefit decision making in female rats, and highlight reproductive status as a variable that could influence aspects of cognition relevant for psychiatric disorders. [ABSTRACT FROM AUTHOR]

This paper proposes a new integral-synergetic controller for direct reactive and active powers control (DARPC) for a grid-connected doubly-fed induction generators (DFIGs) in dual-rotor wind power generation applications. The proposed DARPC strategy employs integral-synergetic control (ISC) to regulate the reactive and active powers of the DFIG-based variable speed dual-rotor wind turbine systems. The proposed ISC technique is the contribution of this work, where this strategy is a development of synergetic control and simplicity and robustness are the most prominent features. The main advantages of the proposed ISC-DARPC technique are ease of implement, good dynamic response, simple structure, and constant switching frequency operation. The Matlab software is used to validate the design of the ISC-DARPC technique, and the obtained results are compared with traditional DARPC. In addition, the ISC-DARPC technique is able to fully minimize ripples in both torque and active power during grid voltage imbalance or parametric changes on the DFIG. [ABSTRACT FROM AUTHOR]

Mercury (Hg) is a well know element due its toxicity to both environment and humans. Also, mercury has a high persistence in the environment, and therefore, it is essential to monitor its presence on environmental matrices, such as water, soils and sediments. Sediment cores can provide a useful tool when monitoring water bodies for the presence of mercury since, when coupled with geochronological techniques, it is possible to analyze the temporal variation of Hg during a certain period. Thus, the objective of this work was to perform a systematic review about papers that analyzed the presence of Hg in dated sediment cores in Brazil. The review was performed in the following databases: Scielo, PubMed, Science Direct and Scopus. We searched for papers published between 2011 and 2020. In total, we found 217 articles, that after the application of successive filtration criteria, were reduced to 13 articles. The majority of the papers showed a tendency of increase in the concentration of Hg. We also performed a risk assessment that indicates that some places have Hg concentrations above quality criteria established for sediments. Regarding the sources, all the papers that presented a tendency of increase in Hg concentrations considered this as consequence of anthropogenic activities, such as chlor-alkali industries and deforestation. [ABSTRACT FROM AUTHOR]

The purpose of this research is to identify the drivers of innovativeness in a furniture manufacturing company. The scenario is the business environment where the hybridization of Technology Management (TM) and Knowledge Management (KM) is operative to promote innovation. The elements of the Technology Acceptance Model (TAM) and Socialization-Externalization-Internalization-Externalization (SECI) Model of KM have been modeled and used for simulation for the identification of the role played by the factors influencing the furniture design information conversion rate. The research follows the case study method to research as it draws data from a single company. Data from a multinational furniture manufacturing company that has over 10,000 products and operates in 24 countries have been used for simulation purposes. Results have shown that among the five factors that influence information conversion rate, the company should focus on correction efficiency and calculation efficiency enhancement if the aim is to maximize product and process innovations; and enhance contextualization efficiency if the priority is immediate results of innovativeness improvement. The results have also shown that about 615 innovative products and processes can be produced in six months by improving the correction efficiency to 80%. The theoretical implication of the study is in the form of a model which can be used by innovative companies to identify the critical factors that influence innovativeness, and the practical implications are in the form of suggestions to the managers of the furniture manufacturing company to enhance their innovativeness so as to gain competitive advantage in business. [ABSTRACT FROM AUTHOR]

It is noted that the traditional direct filed-oriented control (DFOC) is widely used in the field of electric power generation from wind due to its fast response dynamic, ease of implementation and simplicity, but this strategy is characterized by the presence of large ripples at the level of both active and reactive powers. This work presents a new algorithm for DFOC strategy of an asynchronous generator (AG) in a wind power (WP) system, which is based on the use of a new nonlinear controller called fractional-order synergetic control–fractional-order proportional-integral (FOSC–FOPI) controller, where the proposed technique parameters are calculated using the particle swarm optimization (PSO) strategy. It has been observed that the DFOC–FOSC–FOPI–PSO strategy is robust and works well in case of changing generator parameters. Three tests were performed to study the behavior of the designed technique under different working conditions, where the behavior of the DFOC–FOSC–FOPI–PSO strategy was compared with the behavior of the traditional DFOC technique in terms of power ripple ratio, overshoot, steady-state error, response time, tracking reference, and current quality. The simulation of the designed technique based on the FOSC–FOPI–PSO strategy of the AG–WP system is carried out using Matlab software, where the simulation results showed that the suggested technique is better than the classical technique (with PI controller) in terms of improving response time of active power (33.33%) and reactive power (10%) in second test, reduction of the steady-state error of reactive power (96.95%) and active power (97.14) in first test, minimization of harmonic distortion of current (96.57%) in third test and significant minimization of ripples of active power (99.67%, 44.69%, and 98.95%) and reactive power (99.25%, 53.65%, and 70.50%) in the three tests. The effectiveness of the DFOC–FOSC–FOPI–PSO strategy is very high, so it can be a reliable solution for controlling various generators. [ABSTRACT FROM AUTHOR]

Summary Knowledge graphs are being increasingly used in biomedical research to link large amounts of heterogenous data and facilitate reasoning across diverse knowledge sources. Wider adoption and exploration of knowledge graphs in the biomedical research community is limited by requirements to understand the underlying graph structure in terms of entity types and relationships, represented as nodes and edges, respectively, and learn specialized query languages for graph mining and exploration. We have developed a user-friendly interface dubbed ExEmPLAR (Extracting, Exploring, and Embedding Pathways Leading to Actionable Research) to aid reasoning over biomedical knowledge graphs and assist with data-driven research and hypothesis generation. We explain the key functionalities of ExEmPLAR and demonstrate its use with a case study considering the relationship of Trypanosoma cruzi , the etiological agent of Chagas disease, to frequently associated cardiovascular conditions. Availability and implementation ExEmPLAR is freely accessible at https://www.exemplar.mml.unc.edu/. For code and instructions for the using the application, see: https://github.com/beasleyjonm/AOP-COP-Path-Extractor. [ABSTRACT FROM AUTHOR]

This prospective cohort study was conducted to evaluate the association between women's satisfaction with breastfeeding at 1 month post-partum and the risk of exclusive breastfeeding (EBF) interruption before 6 months. 287 mother–infant dyads randomly selected from two maternity hospitals were followed from birth to 24 months of infant's age. Women's satisfaction with breastfeeding was assessed using the Maternal Breastfeeding Evaluation Scale (MBFES) at 1 month. The association between women's satisfaction with breastfeeding and risk of EBF interruption before 6 months was estimated using Cox proportional hazards model. Kaplan–Meier survival curves for EBF were compared between women with lower satisfaction with breastfeeding (MBFES score < median 124) and those with higher satisfaction (MBFES score ≥ 124). Median EBF duration in women with higher satisfaction was 120 days (95%CI 109–131), vs. 26 days (95%CI 19–33) in less satisfied women. Each additional point on MBFES promoted a reduction of 2.0% in the risk of EBF interruption. Among women with satisfaction scores < 124, the risk of EBF interruption was 86% higher when compared with those ≥ 124 (adjusted hazard ratio 1.86; 95%CI 1.41–2.46). Lower maternal satisfaction with breastfeeding in the first month post-partum is associated with a higher risk of EBF interruption before 6 months. [ABSTRACT FROM AUTHOR]

Objectives: Stressful situations have an impact on progression of lichen sclerosus. The aim of the study was to investigate fears and complaints of patients with vulvar lichen sclerosus and progression of disease at the beginning of the COVID-19 pandemic. Material and methods: The analysis was based on 103 women with mean age was 64.81 ± 11.36 years divided into two groups. The first one comprised of patients with stabilization of disease during the pandemic with mean age 66.02 ± 10.01 (32-87), while the second one with progression of vulvar symptoms with mean age 63.49 ± 12.66 (25-87). Results: Delay of diagnosis was reported to be a problem for respectively 25.93% of women from both groups. Fear about COVID-19 was described respectively by 57.4% and 55.1%. Stabilization of disease was more frequent in patients after photodynamic therapy before pandemic. Progression of vulvar symptoms and features were observed more in patients who did not conduct PDT previously. All patients from the second group who underwent photodynamic therapy reported disappointment because of no access for continuation of treatment. On the other hand, 81.4% (43 women) regret that have no chance for trying photodynamic therapy. Conclusions: Photodynamic therapy seems to be a method of treatment with longer survival without progression of lichen sclerosus in times of pandemics. There has been no investigation until now about concerns of patients with vulvar lichen sclerosus. Better understanding of problems connected with the pandemic can help medical personnel in taking care of patients with vulvar lichen sclerosus. [ABSTRACT FROM AUTHOR]

This paper proposes a novel interleaved boost converter for renewable energy applications. The two-phase interleaved boost converter was improved with lossless passive snubber cells to ensure the Zero Voltage Switching (ZVS) condition. The ZVS condition is contributed by a resonant inductor, a resonant capacitor, and two diodes. The proposed converter was operated in continuous current mode on its primary side. The significant merits of this converter are reduced switching losses, better efficiency, and reduced input current ripples without auxiliary switches. The soft-switching ability of this converter is maintained under both light- and heavy-load conditions. This paper also presents the operating principles and design analysis of the proposed converter. Furthermore, a 50-320V prototype was operated at 250 W to validate the soft- switching operation and theoretical analysis, and the experimental results are presented. [ABSTRACT FROM AUTHOR]

This work designs a powerful new nonlinear control technique using synergetic control (SC), proportional-integral (PI) controller, and genetic algorithm (GA) for multi-rotor wind energy (MRWE) conversion systems, whereby an asynchronous generator (AG) is used to achieve optimal energy extraction. The direct power control (DPC) technique is used based on the proposed SC-PI-GA (SPI-GA) technique to control the AG-based MRWE system, where this new nonlinear control technique is used to achieve stable control characteristics under random changes in wind speed and to provide great robustness against modeling uncertainties. Moreover, the pulse width modulation (PWM) technique is used to control the AG inverter due to its simplicity and ease of implementation. In this proposed DPC-SPI-GA technique, we need to measure current and voltage to estimate the active power and the reactive power. Also, inner loops are not used in this proposed DPC-SPI-GA technique as is the case in the field-oriented control (FOC) technique, where the proposed system in this work is characterized by an integrated structure. Three different tests are proposed to study and verify the behavior of the designed DPC-SPI-GA strategy compared to the traditional DPC technique. [ABSTRACT FROM AUTHOR]

Because nontarget, beneficials, like insect pollinators, may be exposed unintentionally to insecticides, it is important to evaluate the impact of chemical controls on the behaviors performed by insect pollinators in field trials. Here we examine the impact of a portable mosquito repeller, which emits prallethrin, a pyrethroid insecticide, on honey bee foraging and recruitment using a blinded, randomized, paired, parallel group trial. We found no significant effect of the volatilized insecticide on foraging frequency (our primary outcome), waggle dance propensity, waggle dance frequency, and feeder persistency (our secondary outcomes), even though an additional deposition study confirmed that the treatment device was performing appropriately. These results may be useful to consumers that are interested in repelling mosquitos, but also concerned about potential consequences to beneficial insects, such as honey bees. [ABSTRACT FROM AUTHOR]

In this paper, a so-called return control technology applied to a feedback proportional-integral (FPI) controller is used to control a variable-speed multi-rotor wind turbine (VSMRWT) conversion system with a double-powered asynchronous generator (DPAG). This generator is controlled by direct vector control (DVC). However, the proposed DVC based on FPI controllers is a new strategy and is different from a traditional control, where the FPI controller was used for this purpose to improve the performance of the DPAG. The paper also indicates the importance of using the DVC-FPI in improving the efficiency and robustness of the DPAG used as a system for converting mechanical energy into electrical energy. Using the FPI controller to improve the power generated by the DPAG can allow for to minimization of power ripples and improve the quality of the current in the network. Also, using the DVC-FPI leads to an improvement in overshoot and steady-state error (SSE) compared to DVC. DPAG enables separate control of the interacting and active forces of the system in both the transient and SSE. The numerical results of the DVC-FPI are compared with the results of the DVC of the DPAG at different operating conditions using the MATLAB environment. Furthermore, the comparison is made in terms of power ripples, total harmonic distortion of current, dynamic response, SSE, and overshoot, and this is performed in the case of changing or not changing the DPAG parameters. The simulation results illustrate the robustness and efficiency of the DVC-FPI to the parametric variations of the DPAG. [ABSTRACT FROM AUTHOR]

This paper proposes a mixed‐integer non‐linear programming (MINLP) model for the multi‐period active low voltage (LV) distribution network expansion planning problem, which can be solved by off‐the‐shelf optimization solvers. In addition, the wide‐spread penetration of solar resources, optimal loading of transformers, and modeling of the multiple solar generation patterns are considered in the model. The solar resources are of roof‐top household‐scale photovoltaic panel type, developed using a host‐owned business model and are able to exchange energy with the distribution company (DISCO). This model enables the DISCO, as the owner of the network, to minimize the investment and operation costs while being able to determine the optimal location and capacity of the distribution transformers, the service zone of distribution transformers, the optimal route of the distribution lines, and the total and annual planning costs. In order to check the efficiency of the proposed model, a 0.4 kV distribution test network is considered to plan the LV network of a residential district over a planning horizon of 5 years. Results show the effectiveness of the proposed model in dynamic expansion planning of the active LV distribution network. Also, results illustrates that the penetration of solar sources can be a great tool to improve the technical, economic, and environmental criteria for planning studies. Specifically while reducing the billing costs of customers, it favors the government to reduce the pollution costs, and it enables the DISCO to reduce the loss costs and maintain the voltage in the standard boundaries. [ABSTRACT FROM AUTHOR]

Smart Grid 3.0 is the latest evolution of the smart grid and incorporates advanced computing and communication technologies. The synchrophasor communication system plays a critical role in wide-area measurement systems (WAMS) for real-time protection and control of power systems, supporting the objectives of Smart Grid 3.0. This system relies on synchrophasor communication technologies, where Phasor Measurement Units (PMUs) transmit synchrophasor data to Phasor Data Concentrators (PDCs) over the synchrophasor communication network. The communication infrastructure of this network is based on the TCP/IP protocol stack, which, unfortunately, is susceptible to cyberattacks, posing security threats such as data tampering and false data injection. These vulnerabilities undermine the intended benefits of synchrophasor applications in terms of situational awareness, observability, grid reliability, resiliency, and synchronized monitoring and control in the smart grid. To address these challenges, it is crucial to enhance the security, integrity, and confidentiality of synchrophasor data within the communication system. This paper proposes a blockchain-based synchrophasor communication system that preserves the security and integrity of synchrophasor data. In this paper, an architecture is proposed for a synchrophasor communication system based on blockchain technology. The proposed architecture aims to enhance the security and integrity of synchrophasor measurements. Furthermore, the architecture is developed as a peer-to-peer distributed blockchain network, leveraging the robustness of a distributed, decentralized, hierarchical PDC architecture. To evaluate the efficacy of the proposed architecture, two case studies, one using the IEEE 9 bus and the other using IEEE 14 bus systems are considered. Moreover, various challenges with potential solutions are also recommended. The proposed work is envisioned to contribute to the advancement of Smart Grid 3.0 by adopting blockchain technology for synchrophasor applications. [ABSTRACT FROM AUTHOR]

Increased use of cannabis and cannabinoids for recreational and medical purposes has led to a growth in research on their effects in animal models. The majority of this work has employed cannabinoid injections; however, smoking remains the most common route of cannabis consumption. To better model real-world cannabis use, we exposed mice to cannabis smoke to establish the pharmacokinetics of Δ9THC and its metabolites in plasma and brain. To determine the time course of Δ9THC and two major metabolites [11-hydroxy-delta-9-tetrahydrocannabinol (11-OH-THC) and 11-nor-9-carboxy-delta-9-tetrahydrocannabinol (11-COOH-THC)], male and female C57BL/6J mice were exposed to smoke from sequentially burning 5 cannabis cigarettes. Following smoke exposure, trunk blood and brains were collected at 6 time points (10–240 min). Plasma and brain homogenates were analyzed for Δ9THC and metabolites using a validated ultraperformance liquid chromatography-tandem mass spectrometry method. To assess effects of age, sex, and mouse strain, we exposed mice of four strains (C57BL/6J, FVB, Swiss Webster, and 129S6/SvEv, aged 4–24 months) to cannabis using the same smoke regimen. Samples were collected 10 and 40 min following exposure. Lastly, to assess effects of dose, C57BL/6J mice were exposed to smoke from burning 3 or 5 cannabis cigarettes, with samples collected 40 min following exposure. The pharmacokinetic study revealed that maximum plasma Δ9THC concentrations (Cmax) were achieved at 10 and 40 min for males and females, respectively, while Cmax for brain Δ9THC was observed at 20 and 40 min for males and females, respectively. There were no age or strain differences in plasma Δ9THC concentrations at 10 or 40 min; however, 129S6/SvEv mice had significantly higher brain Δ9THC concentrations than FVB mice. Additionally, 3 cigarettes produced significantly lower plasma 11-COOH-THC concentrations compared to 5 cigarettes, although dose differences were not evident in plasma or brain concentrations of Δ9THC or 11-OH-THC. Across all experiments, females had higher levels of 11-COOH-THC in plasma compared to males. The results reveal robust sex differences in Δ9THC pharmacokinetics, and lay the groundwork for future studies using mice to model the pharmacodynamics of smoked cannabis. [ABSTRACT FROM AUTHOR]

Current research with Vehicular Ad-hoc Networks (VANETs) has focused on adapting an efficient consensus mechanism and reducing the blockchain size while maintaining security. Care must be taken when implementing blockchains within VANET applications to leverage the chains' strengths while mitigating their weaknesses. These chains can serve as distributed ledgers that provide storage for more than financial transactions. The security provided by longer blockchains constitutes a nearly immutable, decentralized data structure that can store any data relevant to the applications. However, these chains must be adapted to the ad-hoc, resource-constrained environments found in VANETs. In the absence of abundant resources and reliable network connections, chain operation and maintenance must address the challenges presented by highly mobile nodes in novel ways, including situations such as emergency messaging that require real-time responses. Researchers have included different mechanisms to realize lightweight blockchains, such as adding reputation to existing consensus mechanisms, condensing the consensus committees, using geographical information, and monitoring a nodes behavior in attempts to adapt blockchains to these domains. This paper analyzes the challenges and gives solutions for these different mechanisms to realize lightweight blockchains for VANETs. [ABSTRACT FROM AUTHOR]

Fluidized-bed spray granulation (FBSG) enables manufacturing particles with desired characteristics, including particle size distribution (PSD), density, or dust content. This study investigated the effect of selected factors on the granules obtained in a continuous FBSG of chelated fertilizers for foliar applications. The effect of surfactant addition to the solution sprayed into the bed and perturbations of operating parameters on PSD and granules morphology was studied. The experiments were supplemented with calculations based on a population balance equation (PBE). It was shown that granules manufactured with the tenside addition are more regular in shape, and thus less prone to mechanical wear. It was demonstrated that increasing rotational mill speed does contribute to a slight increase in the amount of dust, but in the long term, it does not disturb the regular agglomeration process. The computational results confirm that, despite the complexity of the process, its description with PBE is feasible. [ABSTRACT FROM AUTHOR]

Summary: This study develops a novel DC‐DC converter with an extremely high voltage conversion ratio that utilizes just one switch, a voltage multiplier circuit (VMC), and a coupled‐inductor. Two diodes and two capacitors comprise the VMC, employed to reach high voltage gain. Consequently, the conduction loss is minimized by using a low voltage rated switch with lower RDS(on). Due to the coupled inductor's leakage inductance, the output diodes' reverse recovery trouble is solved. Moreover, the passive clamp technique stores and recycles leakage energy at the output. The proposed DC‐DC converter features are high conversion ratio, low maximum voltage on semiconductors, remarkable efficiency, the existence of only one active low voltage switch, and simple circuit topology with common ground between the input and the output. This paper outlines CCM, BCM, and DCM's operating concept and steady‐state analysis in great detail. Furthermore, the suggested structure's capability is indicated by mathematical analysis and comparative findings with other earlier structures. Eventually, experimental findings with 210 W output power and 25 kHz switching frequency demonstrates that the proposed converter can be used successfully. [ABSTRACT FROM AUTHOR]

This work designs a powerful new nonlinear control technique using synergetic control (SC), proportional-integral (PI) controller, and genetic algorithm (GA) for multi-rotor wind energy (MRWE) conversion systems, whereby an asynchronous generator (AG) is used to achieve optimal energy extraction. The direct power control (DPC) technique is used based on the proposed SC-PI-GA (SPI-GA) technique to control the AG-based MRWE system, where this new nonlinear control technique is used to achieve stable control characteristics under random changes in wind speed and to provide great robustness against modeling uncertainties. Moreover, the pulse width modulation (PWM) technique is used to control the AG inverter due to its simplicity and ease of implementation. In this proposed DPC-SPI-GA technique, we need to measure current and voltage to estimate the active power and the reactive power. Also, inner loops are not used in this proposed DPC-SPI-GA technique as is the case in the field-oriented control (FOC) technique, where the proposed system in this work is characterized by an integrated structure. Three different tests are proposed to study and verify the behavior of the designed DPC-SPI-GA strategy compared to the traditional DPC technique. [ABSTRACT FROM AUTHOR]

This paper deals with the optimal design of different VLSI circuits, namely, the CMOS voltage reference circuit and the CMOS ring oscillator (RO). The optimization technique used here is the multiobjective differential evolution algorithm (MDEA). All the circuits are designed for 90 nm technology. The main objective of the CMOS voltage reference circuit is to minimize the voltage variation at the output. The targeted value of the reference voltage is 550 mV. A CMOS ring oscillator (RO) is designed depending on the performance parameters such as power consumption and phase noise. The optimal transistor sizing of each circuit is obtained from MDEA. Each circuit is implemented in SPICE by taking the optimal dimensions of the transistors, and the performance parameters are achieved. The designed voltage reference circuit achieves a reference voltage of 550 mV with 600 nW power dissipation. The reference voltage variation of 8.18% is observed due to temperature variation from −40°C to + 125°C. The MDEA-based optimal design of RO oscillates at 2.001 GHz frequency, has a phase noise of −87 dBc/Hz at 1 MHz offset frequency, and consumes 71 μW power. This work mainly aims to optimize the MOS transistors' sizes using MDEA for better circuit performance parameters. SPICE simulation has been carried out by using the optimal values of MOS transistor sizes to exhibit the performance parameters of the circuit. Simulation results establish that design specifications are closely met. SPICE results show that MDEA is a better technique for the optimal design of the above-mentioned VLSI circuits. [ABSTRACT FROM AUTHOR]

Modern electrical power system design will increase renewable energy sources (RES) dominance. Rotating masses, the main source of inertia in power systems, have been greatly decreased in renewable energy producing systems. Thus, load–frequency equilibrium is an important indicator of these systems' performance and safety. This work introduces a fractional‐order (FO) operator‐based cascade control structure for islanded microgrid (μG) load‐frequency control (LFC). The structure utilizes a tilt–FO derivative with filter (TFODn) in the first level to reduce noise. The second level implements the proportional integral (PI) controller's FO form (FOPI), making it a tilt–FO derivative with a filter cascaded to the FOPI controller (TOFDn‐FOPI). The optimal controller parameters for quick dynamic responses with low frequency fluctuation are determined using a unique cost function and prairie dog optimization (PDO) algorithm. The LFC control loops have frequency deviation‐based responsive loads (RL). Control signal delays, RES output changes, parameter uncertainties, and cyber vandalism are examined. Laboratory‐scale tests also assessed the controller's practicality. The proposed controller outperforms standard and FO type proportional integral derivative (PID) and PD‐PI controllers. The TFODn‐FOPI controller is suitable for complicated closed‐loop systems like islanded μGs due to its faster error clearing, reduced RL capacity, and superior time and frequency domain indicators. [ABSTRACT FROM AUTHOR]

With the penetration of distributed energy resources (DERs), new network challenges arise that limit the hosting capacity of the network, which consequently makes the current expansion-planning models inadequate. Smart inverters as a promising tool can be utilized to enhance the hosting capacity. Therefore, in response to technical, economic, and environmental challenges, as well as government support for renewable resources, especially domestic solar resources located at the point of consumption, this paper is an endeavor to propose a smart-inverter-based low-voltage (LV) distribution expansion-planning model. The proposed model is capable of dynamic planning, where multiple periods are considered over the planning horizon. In this model, a distribution company (DISCO), as the owner of the network, intends to minimize the planning and operational costs. Optimal loading of transformers is considered, which is utilized to operate the transformers efficiently. Here, to model the problem, a mixed-integer nonlinear programming (MINLP) model is utilized. Using the GAMS software, the decision variables of the problem, such as the site and size of the installation of distribution transformers, and their service areas specified by the LV lines over the planning years, and the reactive power generation/absorption of the smart inverters over the years, seasons, and hours are determined. To tackle the operational challenges such as voltage control in the points of common coupling (PCC) and the limitations in the hosting capacity of the network for the maximized penetration level of PV cells, a smart-inverter model with voltage control capability in PCC points is integrated into the expansion-planning problem. Then, a two-stage procedure is proposed to integrate the reactive power exchange capability of smart inverters in the distribution expansion planning. Based on the simulations of a residential district with PV penetration, results show that by a 14.7% share of PV energy generation, the loss cost of LV feeders is reduced by 28.3%. Also, it is observed that by optimally making use of the reactive power absorption capability of the smart inverters, the hosting capacity of the network is increased by 50%. [ABSTRACT FROM AUTHOR]

In this work, a model-order reduction methodology based on proper orthogonal decomposition (POD) and Galërkin projection is presented and applied to the simulation of the self-ignition of a stockpile of solid fuel. Self-ignition is a phenomenon associated with steep changes in space and time, yielding high gradients of state variables which demand grid refinement and, thus, increase of the computational burden. To cope with this difficulty, first, a full order model (FOM), generated by finite-difference discretisation of the PDEs constituting the differential model, is employed to generate reference solutions. Two different POD-based formulations are proposed: the classical POD-Galërkin is employed to generate reduced order models (ROM), then discrete empirical interpolation method (DEIM) is employed to deal with nonlinearities in a more efficient manner. These reduction techniques are further supplemented with an innovative sampling approach based on k-means clustering. The resulting agile ROM is validated against the FOM. Both model-order reduction strategies, particularly the POD-DEIM model, reproduce the FOM solutions with high accuracy and much lower computational cost: The results of the application of a combination of the DEIM algorithm and k-means clustering show that the computational time for the calculation of one solution reduces up to 1020 times, while remaining able to reproduce all bifurcation points found with the FOM, thus demonstrating quantitative and qualitative agreement. [ABSTRACT FROM AUTHOR]

Decision making is a complex cognitive process that recruits a distributed network of brain regions, including the basolateral amygdala (BLA) and nucleus accumbens shell (NAcSh). Recent work suggests that communication between these structures, as well as activity of cells expressing dopamine (DA) D2 receptors (D2R) in the NAcSh, are necessary for some forms of decision making; however, the contributions of this circuit and cell population during decision making under risk of punishment are unknown. The current experiments addressed this question using circuit-specific and cell type-specific optogenetic approaches in rats during a decision making task involving risk of punishment. In experiment 1, Long-Evans rats received intra-BLA injections of halorhodopsin or mCherry (control) and in experiment 2, D2-Cre transgenic rats received intra-NAcSh injections of Cre-dependent halorhodopsin or mCherry. Optic fibers were implanted in the NAcSh in both experiments. Following training in the decision making task, BLAfiNAcSh or D2R-expressing neurons were optogenetically inhibited during different phases of the decision process. Inhibition of the BLAfiNAcSh during deliberation (the time between trial initiation and choice) increased preference for the large, risky reward (increased risk taking). Similarly, inhibition during delivery of the large, punished reward increased risk taking, but only in males. Inhibition of D2R-expressing neurons in the NAcSh during deliberation increased risk taking. In contrast, inhibition of these neurons during delivery of the small, safe reward decreased risk taking. These findings extend our knowledge of the neural dynamics of risk taking, revealing sex-dependent circuit recruitment and dissociable activity of selective cell populations during decision making. [ABSTRACT FROM AUTHOR]

In this paper, a wind power system based on a doubly-fed induction generator (DFIG) is modeled and simulated. To guarantee high-performance control of the powers injected into the grid by the wind turbine, five intelligent super-twisting sliding mode controllers (STSMC) are used to eliminate the active power and current ripples of the DFIG. The STSMC controller is a high-order sliding mode controller which offers high robustness compared to the traditional sliding mode controller. In addition, it reduces the phenomenon of chattering due to the discontinuous component of the SMC technique. However, the simplicity, ease of execution, durability, and ease of adjusting response are among the most important features of this control compared to some other types. To increase the robustness and improve the response of STSMC, particle swarm optimization method is used for this purpose, where this algorithm is used for parameter calculation. The simulation results obtained using MATLAB software confirm the characteristics of the designed strategy in reducing chattering and ensuring good power control of the DFIG-based wind power. [ABSTRACT FROM AUTHOR]

This paper presents ocean wave energy control using the Aquila optimization (AO) technique. An oscillating water column (OWC)-type wave energy converter has been considered that is fitted with a Wells turbine and doubly fed induction generator (DFIG). To achieve maximum power point tracking (MPPT), the rotor speed of the DFIG must be controlled as per the MPPT law. The MPPT law is designed in such a way that the Wells turbine flow coefficient remains within the threshold limit. It avoids the turbine from stalling which generates the maximum power. The MPPT law provides the reference rotor speed which is followed by the actual rotor speed. For this, a backstepping controller (BSC)-based rotational speed control strategy has been designed using the Lyapunov stability theory. The BSC has unknown control parameters which should be selected such that tracking errors are minimum. Hence, the objective of this work is to find the unknown control parameters using an optimization approach. The optimization approach of selecting BSC control parameters for an OWC plant has not been explored yet. To achieve this, an integral square error (ISE)-type fitness function has been defined and minimized using the AO technique. The results achieved using the AO technique have been compared with particle swarm optimization (PSO) and a genetic algorithm (GA), validating its superior performance. The rotor speed error maximum peak overshoot is least for AO-BSC as compared to PSO-BSC and GA-BSC. The fitness function value for AO comes out to be least among all the optimization methods applied. However, all tested methods provide satisfactory results in terms of turbine flow coefficient, rotor speed and output power. The approach paves the way for future research on ocean wave energy control. [ABSTRACT FROM AUTHOR]

The electrification of public transport is an overwhelming trend, representing the first step in the energy transition of the transport sector. The transport sector is characterized by the prevalence of public ownership and the significant influence of the public sector. Accordingly, tendering procedures are widely utilized to identify the most efficient bus delivery options. This paper compares, evaluates, and identifies the differences in criteria used in tenders for battery electric buses and diesel buses in Poland based on a deep bus market analysis supported by in-depth individual interviews. The article also attempts to determine whether the weight of the "vehicle price" criterion corresponds to the share of the vehicle price in its life cycle cost or total cost of ownership. The results indicate no significant difference in the tender criteria between battery electric buses and diesel buses. In the vast majority of cases, institutions that had previously developed diesel bus acquisition patterns transferred these patterns to tenders for battery electric bus purchases. Therefore, the criteria and their weights used in tenders do not consider the advantages and disadvantages of both technologies. Tendering procedures are adapted to local conditions and operational requirements. Electric buses often replace conventionally powered vehicles on existing routes and schedules. Thus, operational requirements are known. As a result, the necessary number of vehicles and the basic technical and operational parameters (e.g., selection of the optimal charging method and battery capacity) can be determined. In turn, the charging method will influence the total cost of ownership, with overnight charging favored for shorter assignments and opportunity charging favored for longer mileages. [ABSTRACT FROM AUTHOR]

A new controller based on a fractional-order synergetic controller (FOSC) is proposed for a three-level T-type inverter using a shunt active power filter (SAPF). The SAPF is designed to compensate for the reactive power and eliminate the current harmonics caused by non-linear loads, in cases of distorted or unbalanced source voltages. The proposed FOSC technique with the designed parameters and defined macro-variable is a robust control technique that operates well in both transient and steady-state scenarios, ensuring fast convergence and closed-loop system stability. The FOSC technique utilizes a phase-locked loop (PLL) technique on a self-tuning filter (STF) to enhance the SAPF's ability to compensate current harmonics and reactive power in all situations involving non-linear loads and source voltage variations according to IEEE Std. 519. The proposed control was implemented and verified using Matlab software, where the obtained results were compared with the results of the conventional control based on proportional-integral (PI) controllers in different operating conditions. The results indicate that the proposed FOSC technique outperformed the traditional control in terms of DC voltage tracking and the minimization of the total harmonic distortion of the current. [ABSTRACT FROM AUTHOR]

In this article, the performance of n-type junctionless (JL) double-gate (DG) MOSFET-based biosensors with and without gate stack (GS) has been studied. Here, the dielectric modulation (DM) method is applied to detect biomolecules in the cavity. The sensitivity of n-type JL-DM-DG-MOSFET and n-type JL-DM-GSDG-MOSFET-based biosensors have also been evaluated. The sensitivity (ΔVth) improved in JL-DM-GSDG MOSFET/JL-DM-DG-MOSFET-based biosensors for neutral/charged biomolecules is 116.66%/66.66% and 1165.78%/978.94%, respectively, compared with the previously reported results. The electrical detection of biomolecules is validated using the ATLAS device simulator. The noise and analog/RF parameters are compared between both biosensors. A lower threshold voltage is observed in the GSDG-MOSFET-based biosensor. The Ion/Ioff ratio is higher for DG-MOSFET-based biosensors. The proposed GSDG-MOSFET-based biosensor demonstrates higher sensitivity than the DG-MOSFET-based biosensor. The GSDG-MOSFET-based biosensor is suitable for low-power, high-speed, and high sensitivity applications. [ABSTRACT FROM AUTHOR]

The system under study in this work is a self-igniting pile of solid material. To predict and understand the effect of steep changes of the state variables on such systems, a reaction-diffusion model is employed. These systems can exhibit complex oscillatory behaviour, and changes in ambient conditions over time may strongly impact the inherent oscillations. To simulate the unsteady evolution of the pile, both a classical numerical technique (method of lines) and a reduced order approach are employed in combination with a stiff ODE solver. To account for circadian fluctuations in temperature, time-variable boundary conditions are assumed upon formulating the problem. The reduced order model is introduced in view of understanding if an approximated formulation characterized by a much lower number of state variables can accurately predict the complex behaviour of the system even in the case of sudden, steep variations of the values of the state variables due to the phenomenon of self-ignition, intensified here by variable boundary conditions. The selected case studies have the goal of exploring the effect of stockpile properties on the self-ignition phenomenon. Numerical solutions show the anticipated coupling between the system intrinsic dynamics and the oscillating temperature imposed at the boundary. All of the analysed cases are accurately replicated by the reduced order model. [ABSTRACT FROM AUTHOR]

Particle swarm optimisation (PSO) is one of the widely adopted meta-heuristic methods for solving real-life problems. Its practical utility can be further enhanced by improving its performance. In order to acheive this, academics have presented several variants of the original PSO over the past few years, including the quantum PSO (QPSO), bare-bones PSO (BB-PSO), hybrid PSO, fuzzy PSO, etc. In this paper, the performance of PSO is improved by proposing a fragmented swarm optimisation approach known as the PSOα. The PSOα is tested and compared with PSOs over 14 different benchmarking cost functions to validate its efficacy. The analysis is also carried out to see the impact of α on its performance. It is observed that the average value of the cost function over 50 simulations obtained using the fragmented swarm approach is lower than that obtained using the standard PSO in 12 out of 14 benchmark functions. Similarly, the fragmented approach outperforms the standard PSO in 13 out of 14 benchmark functions when compared with the best fitness value achieved out of 50 simulations. Finally, the proposed approach is applied to solve the well-known real-life optimisation problem of load frequency control (LFC) in power systems. A test system comprising both renewable and traditional power sources is considered to evaluate the efficacy of the proposed technique. A fractional order proportional-integral-differential (FOPID) controller is used, whose parameters are optimised using the proposed PSO for achieving the LFC. The proposed fragmentation approach can be applied with other optimisation techniques to improve their performance. [ABSTRACT FROM AUTHOR]

In this study, a comparative sizing design for renewable power systems was developed based on HOMER (Hybrid Optimization of Multiple Energy Resources) and iHOGA (improved Hybrid Optimization by Genetic Algorithms) simulators. A comparative analysis of the solutions obtained with iHOGA and HOMER simulators for the same hybrid renewable power system (HRPS) is presented in detail. The system contained a new hybrid configuration that used fuel cell (FC) as a green energy source, replacing the polluting diesel generator system, as well as other renewable energy sources, namely, photovoltaic panels, wind turbine, a battery stack, power converters, and electric load. The same case study was carried out for the design of the hybrid system using HOMER and iHOGA simulators to perform a comparative analysis of the solutions obtained for potential investment. The analysis showed a higher share of renewable energy for iHOGA (92%) compared to HOMER (81%), so the first design produced 51.61 kg/year less carbon dioxide. Moreover, the operating costs (2134 RON/year for HOMER and 70.56 RON/year for iHOGA) and the cost of electricity were higher by 96% and 2.5%, respectively, for HOMER compared to iHOGA. Taking into account the need for high reliability, safe operation, and lower operation/exploitation costs, the design implemented in iHOGA is clearly more efficient and useful in practice, and this is supported by the three iHOGA case studies. [ABSTRACT FROM AUTHOR]

Social media is a platform where people communicate, share content, and build relationships. Due to the current pandemic, many people are turning to social networks such as Facebook, WhatsApp, Twitter, etc., to express their feelings. In this paper, we analyse the sentiments of Indian citizens about the COVID-19 pandemic and vaccination drive using text messages posted on the Twitter platform. The sentiments were classified using deep learning and lexicon-based techniques. A lexicon-based approach was used to classify the polarity of the tweets using the tools VADER and NRCLex. A recurrent neural network was trained using Bi-LSTM and GRU techniques, achieving 92.70% and 91.24% accuracy on the COVID-19 dataset. Accuracy values of 92.48% and 93.03% were obtained for the vaccination tweets classification with Bi-LSTM and GRU, respectively. The developed models can assist healthcare workers and policymakers to make the right decisions in the upcoming pandemic outbreaks. [ABSTRACT FROM AUTHOR]

Reconfigurable metamaterials have immense applications in sensing. A refractive index reconfigurable terahertz metamaterial absorber was investigated in this research for gas sensing applications. The absorption spectrum reconfigures with the changes in the surrounding medium's refractive index. The proposed absorber displays positive permittivity and negative permeability at the resonance frequency of 3.045 THz indicating magnetic resonance. The design consists of concentric U-shaped rings that were optimally designed to perform the parametric analysis using the finite element method (FEM). The absorption bands offered by the structure were found to be insensitive to variation in polarization angles up to 60°. The outcome of this design approach yields a 99.75% absorption rate with a Q-factor of 87. Additionally, the equivalent circuit model of this proposed absorber was analyzed to estimate the resonance frequency, which reveals good agreement with the simulated ones. Moreover, the structure was designed for a refractive index ranging between 1 and 1.03 to detect harmful gases such as methane, chloroform, etc., with a high sensitivity of 3.01 THz/RIU (Refractive Index Unit) and figure of merit (FoM) of 86. This research work is potentially suitable for biological sensing and chemical industry applications. [ABSTRACT FROM AUTHOR]

The transport sector generates more than 35% of total CO2 emissions. Electric vehicles are the future of transportation systems, and the demand for electric vehicles has grown considerably in the last few years due to government support. Companies worldwide are investing heavily in electric car charging stations based on renewable energy. This research study presents a complete design (including an appropriate energy management strategy) for a photovoltaic energy-based electric vehicle charging station (EVCS) with or without the support of a fuel cell and electrolyzer system. The parameters considered for designing the necessary capacity of the battery pack to support the required load are relative to the location-specific solar radiation (using RETScreen® Clean Energy Management Software, Version 9.0, Government of Canada, Toronto, Canada), the efficiency of the solar panel, the used strategy, etc. The battery capacity in the EVCS design based on a power-following strategy is about 20 times smaller than that resulting in the reference design. Additionally, the cost for an EVCS design based on a power-following strategy is almost half that resulting in the reference design. An analysis of the power-following strategy was carried out according to three EVCS operating scenarios. [ABSTRACT FROM AUTHOR]