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A networked microgrid is composed of multiple nearby microgrids linked together to gain additional flexibility for resilient operations. Networked microgrids collaborate to prevent power shortages in microgrid clusters by sharing critical renewable and energy storage resources. However, controlling the local resources of each microgrid, including the energy storage systems' charging and discharging, maintaining the DC bus voltage, and even overseeing the power shared by multiple microgrids, is challenging. Therefore, a microgrid control technique and distributed energy management are used cooperatively in this study to handle the shared power between a system of networked microgrids incorporating photovoltaics and battery energy storage systems. Numerical simulation results from a networked microgrid system verify the accuracy and soundness of the suggested distributed energy management under several operating conditions, including renewable uncertainties and sequential load variations in different zones. The applicability of the suggested technique is confirmed by hardware implementation, and several operational scenarios further evaluate the proposed system on a practical two-microgrid system located in the Florida International University (FIU) testbed. [ABSTRACT FROM AUTHOR]

The impact of communication disturbances on microgrids (MGs) needs robust and scalable Information Communication Technology (ICT) infrastructure for efficient MG control. This work builds on advances in the Internet of Things (IoT) to provide a practical platform for testing the impact of various cyber-attacks on a distributed control scheme for a Multi-Agent System (MAS). This paper presents a Controller Hardware-in-the-Loop (CHIL) testbed to investigate the impact of various cyber-attacks and communication disruptions on MGs. A distributed consensus secondary control scheme for a MAS within an MG cyber-physical system (CPS) is proposed. The proposed cyber-physical testbed integrates a real-time islanded AC microgrid on RT-Lab, secondary controllers implemented on single-board computers, and an attacker agent on another single-board computer. Communication occurs via a UDP/IP network between OPAL-RT and controller agents, as well as between the agents. Through meticulous experimentation, the efficacy of the proposed control strategy using the developed platform is validated. Various attacks were modeled and launched including deception attacks on sensors, actuators, and their combinations, as well as disruption attacks. The ramifications of both deception and disruption cyber-attacks on system performance are analyzed. [ABSTRACT FROM AUTHOR]

Energy storage systems are essential in modern energy infrastructure, addressing efficiency, power quality, and reliability challenges in DC/AC power systems. Recognized for their indispensable role in ensuring grid stability and seamless integration with renewable energy sources. These storage systems prove crucial for aircraft, shipboard systems, and electric vehicles, addressing peak load demands economically while enhancing overall system reliability and efficiency. Recent advancements and research have focused on high-power storage technologies, including supercapacitors, superconducting magnetic energy storage, and flywheels, characterized by high-power density and rapid response, ideally suited for applications requiring rapid charging and discharging. Hybrid energy storage systems and multiple energy storage devices represent enhanced flexibility and resilience, making them increasingly attractive for diverse applications, including critical loads. This paper provides a comprehensive overview of recent technological advancements in high-power storage devices, including lithium-ion batteries, recognized for their high energy density. In addition, a summary of hybrid energy storage system applications in microgrids and scenarios involving critical and pulse loads is provided. The research further discusses power, energy, cost, life, and performance technologies. [ABSTRACT FROM AUTHOR]

Batteries have been considered a key element in several applications, ranging from grid-scale storage systems through electric vehicles to daily-use small-scale electronic devices. However, excessive charging and discharging will impair their capabilities and could cause their applications to fail catastrophically. Among several diagnostic indices, state-of-charge estimation is essential for evaluating a battery's capabilities. Various approaches have been introduced to reach this target, including white, gray, and black box or data-driven battery models. The main objective of this work is to provide an extensive comparison of currently highly utilized machine learning-based estimation techniques. The paper thoroughly investigates these models' architectures, computational burdens, advantages, drawbacks, and robustness validation. The evaluation's main criteria were based on measurements recorded under various operating conditions at the Energy Systems Research Laboratory (ESRL) at FIU for the eFlex 52.8 V/5.4 kWh lithium iron phosphate battery pack. The primary outcome of this research is that, while the random forest regression (RFR) model emerges as the most effective tool for SoC estimation in lithium-ion batteries, there is potential to enhance the performance of simpler models through strategic adjustments and optimizations. Additionally, the choice of model ultimately depends on the specific requirements of the task at hand, balancing the need for accuracy with the complexity and computational resources available and how it can be merged with other SoC estimation approaches to achieve high precision. [ABSTRACT FROM AUTHOR]

The integration of communication infrastructures into traditional power systems, transforming them into cyber-physical power systems (CPPS), accentuates the significance of communication in influencing system performance and sustainability. This paper presents a versatile, innovative cyber-physical co-simulation framework that integrates the physical power system and communication networks, uniting OPAL-RT, a network simulator (ns3), and Docker containers into a sophisticated platform, facilitating intensive studies into CPPS dynamics. The proposed experimental study provides an innovative way to assess the frequency control response of a cyber-physical inverter-based microgrid (MG), addressing the MG sustainability challenges. We consider diverse real-world scenarios, focusing on communication delays and distributed denial of service (DDoS) attacks within the communication channels. We propose a precise ns3-based communication model that bridges the MG's primary and secondary control layers, an aspect often overlooked in previous studies; this is a noteworthy contribution to elucidating the adverse impacts of communication latency on MG frequency performance. The experimental results demonstrate the effectiveness of the centralized secondary controller in eliminating the frequency deviations. Furthermore, the findings offer insights into stable and unstable regions, revealing how the communication delay value affects the frequency stability under different operating conditions. In addition, the developed real-time DDoS attacks model within the proposed communication surface unveils crucial insights into the MG's resilience to cyber threats. This work's revelations offer a foundational awareness of MG vulnerabilities, paving the way for designing robust and resilient communication networks and control strategies within the cyber-physical inverter-based microgrids. [ABSTRACT FROM AUTHOR]

Multi-microgrids (MMGs) revolutionize integrating and managing diverse distributed energy resources (DERs), significantly enhancing the overall efficiency of energy systems. Unlike traditional power systems, MMGs comprise interconnected microgrids that operate independently or collaboratively. This innovative concept adeptly addresses challenges posed by pulsed load effects, capitalizing on the cooperative nature of interconnected microgrids. A coordinated MMG system effectively redistributes and shares the impact of pulsed loads, mitigating voltage fluctuations and ensuring sustained system stability. The proposed cooperative MMG scheme optimizes power distribution and load prioritization, facilitating the seamless allocation of surplus energy from neighboring microgrids to meet sudden surges in demand. This study focuses on DC standalone multi-microgrid systems, showcasing their inherent adaptability, resilience, and operational efficiency in managing pulse, variable, and unpredictable generation deficits. Several experiments on a laboratory-scale DC multi-microgrid validate the system's robust performance. Notably, transient current fluctuations during pulse loads are promptly stabilized through the effective collaboration of microgrids. Variable load experiments reveal distinct behaviors, shedding light on the profound influence of control strategies. This research reveals the transformative potential of MMGs in addressing energy challenges, with a particular focus on DC standalone multi-microgrid systems. The findings underscore the adaptability and resilience of the proposed cooperative scheme, marking a significant stride in the evolution of modern power systems. [ABSTRACT FROM AUTHOR]

With the deployment of numerous innovative smart grid technologies in modern power systems, more real-time communication and control are required due to the complexity and proliferation of grid-connected systems, making a power system a typical cyber-physical system (CPS). However, these systems are also exposed to new cyber vulnerabilities. Therefore, understanding the intricate interplay between the cyber and physical domains and the potential effects on the power system of successful attacks is essential. For cybersecurity experimentation and impact analysis, developing a comprehensive testbed is needed. This paper presents a state-of-the-art Hybrid Physical Co-simulation SG testbed at FIU developed for in-depth studies on the impact of communication system latency and failures, physical events, and cyber-attacks on the grid. The Hybrid SGTB is designed to take full advantage of the benefits of both co-simulation-based and physical-based testbeds. Based on this testbed, various attack strategies are tested, including man-in-the-middle (MitM), denial-of-service (DoS), data manipulation (DM), and setting tampering (change) on various power system topologies to analyze their impacts on grid stability, power flow, and protection reliability. Our research, which is based on extensive testing on several testbeds, shows that using hybrid testbeds is justified as both practical and effective. [ABSTRACT FROM AUTHOR]

Simple Summary: Over the years, diverse therapeutic protocols have been employed for cardiac tissue engineering (CTE) and improvement of the heart functions. Among them are stem cells which possess a high tissue-regeneration potential. However, the optimum delivery protocol with effective cell retention and homing at the target site is still challenging. Hence, a wide range of natural and synthetic biomaterials have been utilized as cell delivery cargoes to address these limitations. Natural decellularized biomaterials could provide successful biocompatible, biodegradable, elastic, and strong platforms that avoid the drawbacks of synthetic ones. Hence, in the present study, we have prepared a decellularized porcine pericardium (DPP) patch to provide successful tailored cell discharge, retention, and homing at the site of the myocardial infarction (MI) with an outstanding ability to restore the damaged heart activity. Moreover, we have provided for the first time a novel echocardiographic-derived imaging modality called the intraventricular pressure gradient (IVPG) to evaluate the process. The IVPG provides a precise, non-invasive, and facile tool to assess cardiac functions. This speeds up the accumulation of knowledge and opens new avenues to objectively evaluate diagnosis and treatment, which encourages the implementation of such a cutting-edge strategy in clinical practices in the near future. Myocardial infarction (MI) is a serious cardiovascular disease as the leading cause of death globally. Hence, reconstruction of the cardiac tissue comes at the forefront of strategies adopted to restore heart functions following MI. In this investigation, we studied the capacity of rat adipose-derived mesenchymal stem cells (r-AdMSCs) and decellularized porcine pericardium (DPP) to restore heart functions in MI animals. MI was induced in four different groups, three of which were treated either using DPP (MI-DPP group), stem cells (MI-SC group), or both (MI-SC/DPP group). Cardiac functions of these groups and the Sham group were evaluated using echocardiography, the intraventricular pressure gradient (IVPG) on weeks 2 and 4, and intraventricular hemodynamics on week 4. On day 31, the animals were euthanized for histological analysis. Echocardiographic, IVPG and hemodynamic findings indicated that the three treatment strategies shared effectively in the regeneration process. However, the MI-SC/DPP group had a unique synergistic ability to restore heart functions superior to the other treatment protocols. Histology showed that the MI-SC/DPP group presented the lowest (p < 0.05) degeneration score and fibrosis % compared to the other groups. Conclusively, stem cell-seeded DPP is a promising platform for the delivery of stem cells and restoration of heart functions post-MI. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive review of wide and ultrawide bandgap power electronic semiconductor devices, comparing silicon (Si), silicon carbide (SiC), gallium nitride (GaN), and the emerging device diamond technology. Key parameters examined include bandgap, critical electric field, electron mobility, voltage/current ratings, switching frequency, and device packaging. The historical evolution of each material is traced from early research devices to current commercial offerings. Significant focus is given to SiC and GaN as they are now actively competing with Si devices in the market, enabled by their higher bandgaps. The paper details advancements in material growth, device architectures, reliability, and manufacturing that have allowed SiC and GaN adoption in electric vehicles, renewable energy, aerospace, and other applications requiring high power density, efficiency, and frequency operation. Performance enhancements over Si are quantified. However, the challenges associated with the advancements of these devices are also elaborately described: material availability, thermal management, gate drive design, electrical insulation, and electromagnetic interference. Alongside the cost reduction through improved manufacturing, material availability, thermal management, gate drive design, electrical insulation, and electromagnetic interference are critical hurdles of this technology. The review analyzes these issues and emerging solutions using advanced packaging, circuit integration, novel cooling techniques, and modeling. Overall, the manuscript provides a timely, rigorous examination of the state of the art in wide bandgap power semiconductors. It balances theoretical potential and practical limitations while assessing commercial readiness and mapping trajectories for further innovation. This article will benefit researchers and professionals advancing power electronic systems. [ABSTRACT FROM AUTHOR]

Idiopathic pulmonary fibrosis (IPF) is an irreversible and life-threatening lung disease of unknown etiology presenting only a few treatment options. TGF-β signaling orchestrates a cascade of events driving pulmonary fibrosis (PF). Notably, recent research has affirmed the augmentation of TGF-β receptor (TβR) signaling via HSP90 activation. HSP90, a molecular chaperone, adeptly stabilizes and folds TβRs, thus intricately regulating TGF-β1 signaling. Our investigation illuminated the impact of alvespimycin, an HSP90 inhibitor, on TGF-β-mediated transcriptional responses by inducing destabilization of TβRs. This outcome stems from the explicit interaction of TβR subtypes I and II with HSP90, where they are clients of this cellular chaperone. It is worth noting that regulation of proteasome-dependent degradation of TβRs is a critical standpoint in the termination of TGF-β signal transduction. Oleuropein, the principal bioactive compound found in Olea europaea, is acknowledged for its role as a proteasome activator. In this study, our aim was to explore the efficacy of a combined therapy involving oleuropein and alvespimycin for the treatment of PF. We employed a PF rat model that was induced by intratracheal bleomycin infusion. The application of this dual therapy yielded a noteworthy impediment to the undesired activation of TGF-β/mothers against decapentaplegic homologs 2 and 3 (SMAD2/3) signaling. Consequently, this novel combination showcased improvements in both lung tissue structure and function while also effectively restraining key fibrosis markers such as PDGF-BB, TIMP-1, ACTA2, col1a1, and hydroxyproline. On a mechanistic level, our findings unveiled that the antifibrotic impact of this combination therapy likely stemmed from the enhanced degradation of both TβRI and TβRII. In conclusion, the utilization of proteasomal activators in conjunction with HSP90 inhibitors ushers in a promising frontier for the management of PF. [ABSTRACT FROM AUTHOR]

Liver fibrosis is a progressive condition characterized by the build-up of fibrous tissue resulting from long-term liver injury. Although there have been advancements in research and treatment, there is still a need for effective antifibrotic medication. HSP90 plays a crucial role in the development of fibrosis. It acts as a molecular chaperone that assists in the proper folding and stability of TβRII, potentially regulating the signaling of TGF-β1. It has been established that TβRII can be degraded through the proteasome degradation system, either via ubiquitination-dependent or -independent pathways. In the present study, STA9090 demonstrated promising effects in both in vitro and in vivo models. It reduced LDH leakage, prolonged the survival rate of hepatocytes in rats with liver fibrosis, and improved liver function. Importantly, STA9090 exerted pleiotropic effects by targeting proteins involved in limiting collagen production, which resulted in improved microscopic features of the rat livers. Our findings suggest that STA9090-induced inhibition of HSP90 leads to the degradation of TβRII, a fibrogenic client protein of HSP90, through the activation of the 20S proteasomal degradation system. We also revealed that this degradation mechanism is not dependent on the autophagy–lysosomal pathway. Additionally, STA9090 was found to destabilize HIF-1α and facilitate its degradation, leading to the reduced transcription of VEGF. Moreover, STA9090's ability to deactivate the NFκB signaling pathway highlights its potential as an anti-inflammatory and antifibrotic agent. However, further research is necessary to fully elucidate the underlying mechanisms and fully capitalize on the therapeutic benefits of targeting HSP90 and associated pathways. [ABSTRACT FROM AUTHOR]

Networked microgrids (NMGs) are developing as a viable approach for integrating an expanding number of distributed energy resources (DERs) while improving energy system performance. NMGs, as compared to typical power systems, are constructed of many linked microgrids that can function independently or as part of a more extensive network. This allows NMGs to be more flexible, dependable, and efficient. The present study comprehensively investigates architecture, communication, and cybersecurity issues in NMGs. This comprehensive study examines various aspects related to networked microgrids (NMGs). It explores the architecture of NMGs, including control techniques, protection, standards, and the challenges associated with their adoption. Additionally, it investigates communication in NMGs, focusing on the technologies, protocols, and the impact of communication on the functioning of these systems. Furthermore, this study addresses cybersecurity challenges specific to NMGs, such as diverse cyberattack types, detection and mitigation strategies, and the importance of awareness training. The findings of this study offer valuable insights for NMG researchers and practitioners, emphasizing critical aspects that must be considered to ensure the safe and efficient operation of these systems. [ABSTRACT FROM AUTHOR]

Ulcerative colitis is a chronic and incurable form of inflammatory bowel disease that can increase the risk of colitis-associated cancer and mortality. Limited treatment options are available for this condition, and the existing ones often come with non-tolerable adverse effects. This study is the first to examine the potential benefits of consuming (R,R)-BD-AcAc2, a type of ketone ester (KE), and intermittent fasting in treating chronic colitis induced by dextran sodium sulfate (DSS) in rats. We selected both protocols to enhance the levels of β-hydroxybutyrate, mimicking a state of nutritional ketosis and early ketosis, respectively. Our findings revealed that only the former protocol, consuming the KE, improved disease activity and the macroscopic and microscopic features of the colon while reducing inflammation scores. Additionally, the KE counteracted the DSS-induced decrease in the percentage of weight change, reduced the colonic weight-to-length ratio, and increased the survival rate of DSS-insulted rats. KE also showed potential antioxidant activities and improved the gut microbiome composition. Moreover, consuming KE increased the levels of tight junction proteins that protect against leaky gut and exhibited anti-inflammatory properties by reducing proinflammatory cytokine production. These effects were attributed to inhibiting NFκB and NLRP3 inflammasome activation and restraining pyroptosis and apoptosis while enhancing autophagy as revealed by reduced p62 and increased BECN1. Furthermore, the KE may have a positive impact on maintaining a healthy microbiome. To conclude, the potential clinical implications of our findings are promising, as (R,R)-BD-AcAc2 has a greater safety profile and can be easily translated to human subjects. [ABSTRACT FROM AUTHOR]

Emerging electric vehicle (EV) technology requires high-voltage energy storage systems, efficient electric motors, electrified power trains, and power converters. If we consider forecasts for EV demand and driving applications, this article comprehensively reviewed power converter topologies, control schemes, output power, reliability, losses, switching frequency, operations, charging systems, advantages, and disadvantages. This article is intended to help engineers and researchers forecast typical recharging/discharging durations, the lifetime of energy storage with the help of control systems and machine learning, and the performance probability of using AlGaN/GaN heterojunction-based high-electron-mobility transistors (HEMTs) in EV systems. The analysis of this extensive review paper suggests that the Vienna rectifier provides significant performance among all AC–DC rectifier converters. Moreover, the multi-device interleaved DC–DC boost converter is best suited for the DC–DC conversion stage. Among DC–AC converters, the third harmonic injected seven-level inverter is found to be one of the best in EV driving. Furthermore, the utilization of multi-level inverters can terminate the requirement of the intermediate DC–DC converter. In addition, the current status, opportunities, challenges, and applications of wireless power transfer in hybrid and all-electric vehicles were also discussed in this paper. Moreover, the adoption of wide bandgap semiconductors was considered. Because of their higher power density, breakdown voltage, and switching frequency characteristics, a light yet efficient power converter design can be achieved for EVs. Finally, the article's intent was to provide a reference for engineers and researchers in the automobile industry for forecasting calculations. [ABSTRACT FROM AUTHOR]

A real-time, metadata-driven electric vehicle routing optimization to reduce on-road energy requirements is proposed in this work. The proposed strategy employs the state–action–reward–state–action (SARSA) algorithm to learn the EV's maximum travel policy as an agent. As a function of the received reward signal, the policy model evaluates the optimal behavior of the agent. Markov chain models (MCMs) are used to estimate the agent's energy requirements on the road, in which a single Markov step represents the average energy consumption based on practical driving conditions, including driving patterns, road conditions, and restrictions that may apply. A real-time simulation in Python with TensorFlow, NumPy, and Pandas library requirements was run, considering real-life driving data for two EVs trips retrieved from Google's API. The two trips started at 4.30 p.m. on 11 October 2021, in Los Angeles, California, and Miami, Florida, to reach EV charging stations six miles away from the starting locations. According to simulation results, the proposed AI-based energy minimization framework reduces the energy requirement by 11.04% and 5.72%, respectively. The results yield lower energy consumption compared with Google's suggested routes and previous work reported in the literature using the DDQN algorithm. [ABSTRACT FROM AUTHOR]

Mapping fire risk accurately is essential for the planning and protection of forests. This study aims to map fire risk (probability of ignition) in Marivan County of Kurdistan province, Iran, using the data mining approaches of the evidential belief function (EBF) and weight of evidence (WOE) models, with an emphasis placed on climatic variables. Firstly, 284 fire incidents in the region were randomly divided into two groups, including the training group (70%, 199 points) and the validation group (30%, 85 points). Given the previous studies and conditions of the region, the variables of slope percentage, slope direction, altitude, distance from rivers, distance from roads, distance from settlements, land use, slope curvature, rainfall, and maximum annual temperature were considered for zoning fire risk. Then, forest fire risk maps were prepared using the EBF and WOE models. The performance of each model was examined using the Relative Operating Characteristic (ROC) curve. The results showed that WOE and EBF are effective tools for mapping forest fire risks in the study area. However, the WOE model shows a slightly higher Area Under the Curve value (0.896) compared to that of the EBF model (0.886), indicating a slightly better performance. The results of this study can provide valuable information for preventing forest fires in the study area. [ABSTRACT FROM AUTHOR]

A high share of distributed energy resources (DERs) in power distribution grids has posed many challenges for system operation and control. Microgrid (MG) application with different distributed control approaches for DERs has been drawn a lot of attention from the research community to provide more flexibility, reliability and resilience for the system. This paper develops a distributed secondary control for DERs in MGs and on top of that using synchronous condenser (SC) participating in the secondary control for voltage support. The proposed distributed secondary control framework of MGs is designed to obtain four objectives as follows: (i) frequency restoration, (ii) average voltage restoration, (iii) arbitrary active power sharing among SGs and BESSs and (iv) arbitrary reactive power sharing among all SGs, BESSs and SCs. The comparison results under different scenarios show that with SC participating in the distributed secondary control in MGs, the system frequency and voltage response are much improved and quickly recovered to the nominal values thanks to the natural inertia response and fast reactive power control of SC sharing with other DERs in the MGs. Additionally, a multi-agent system is implemented to realize the proposed control method in hardware environment. [ABSTRACT FROM AUTHOR]

In this paper, a data-centric communication framework is proposed for multicast routable generic object-oriented substation event (GOOSE) messages (MRGM) over the wide area network (WAN) for effective substation-to-substation (SS2SS) and substation to control center (SS2CC) communications. In this structure, the IEC 61850 GOOSE message is transmitted over the WAN using the data distribution service (DDS) as a fast, reliable, and secure data-centric communication middleware. The main feature of this framework is its multicast capability, where several authorized subscribers can receive a published message simultaneously. This can significantly improve the system monitoring and control of the protection systems in modern smart grids, where intelligent schemes can be applied. The effectiveness of the proposed platform, in terms of total end-to-end delay between participants, is evaluated through experimental results obtained from the actual hardware-based test setup developed at the Florida International University (FIU) smart grid testbed. The results demonstrate that the latency between sending and receiving a GOOSE message among participants is within its maximum time span defined by the IEC 61850-90-5 working group for communications over the WAN. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of a communication and control infrastructure for smart grid operation. The proposed infrastructure enhances the reliability of the measurements and control network. The advantages of utilizing the data-centric over message-centric communication approach are discussed in the context of smart grid applications. The data distribution service (DDS) is used to implement a data-centric common data bus for the smart grid. This common data bus improves the communication reliability, enabling distributed control and smart load management. These enhancements are achieved by avoiding a single point of failure while enabling peer-to-peer communication and an automatic discovery feature for dynamic participating nodes. The infrastructure and ideas presented in this paper were implemented and tested on the smart grid testbed. A toolbox and application programing interface for the testbed infrastructure are developed in order to facilitate interoperability and remote access to the testbed. This interface allows control, monitoring, and performing of experiments remotely. Furthermore, it could be used to integrate multidisciplinary testbeds to study complex cyber-physical systems (CPS). [ABSTRACT FROM AUTHOR]

Acinetobacter baumanni (A. baumannii), a nonfermenting Gram-negative bacterium, has recently been associated with a broad range of nosocomial infections. To gain more meaningful insight into the problem of nosocomial illnesses caused by the multidrug-resistant (MDR) A. baumannii, as well as the factors that increase the risk of catching these infections, this investigation included a total of 86 clinical A. baumannii infections. Repetitive extragenic palindromic (REP)-PCR was used to investigate imipenem-resistant A. baumannii isolates for dynamic gene clusters causing carbapenem resistance. Four distinct A. baumannii lineages were found in the REP-PCR-DNA fingerprints of all isolates, with 95% of the samples coming from two dominant lineages. Imipenem, amikacin, and ciprofloxacin were less effective against genotype (A) isolates because of enhanced antibiotic tolerance. Lastly, to gain more insight into the mode of action of imipenem, we explored the binding affinity of imipenem toward different Acinetobacter baumannii OXA beta-lactamase class enzymes. [ABSTRACT FROM AUTHOR]

Simple Summary: Like plants, animal-based remedies are being utilized traditionally in different cultures around the globe. We explored the traditional usage of wild animals by the local inhabitants in Ladakh area of Trans-Himalayan region, India, using questionnaires and interviews. Furthermore, associations between ethnozoological usage and animal species were also evaluated through multivariate ecological community analysis. The highest priority of local inhabitants was for food followed by medicinal usage. We documented therapeutic uses of 48% of the reported species. Among these Alectoris chukar (chukar), Cuon alpinus (Asiatic wild dog), Lepus oiostolus (hares), Marmota himalayana (marmots), Ovis aries vignei (Ladakh urial), Pantholops hodgsonii (Tibetan antelope), Procapra picticaudata (Tibetan gazelle), Pseudois nayaur (blue sheep), Tetraogallus himalayensis (Himalayan snow), Tetraogallus tibetanus (Tibetan snow cock), and Lutra lutra (common otter) were reported for the first time from this region and are being used for medicinal purpose. Our findings could be valuable as reference data for policymakers, researchers, land managers, common public, and the other stakeholders to develop logical and scientific approaches for sustainable use of faunal diversity in biodiversity hotspot regions. Zootherapy is accepted all around the globe not only in ancient cultures but different animal derived medicines are also part of the practice in the modern health care systems. The present study assessed the traditional ethnozoological usage of wild animals by local inhabitants in Ladakh region, India, and the reference data for scientific approaches for protection of faunal diversity in trans-Himalayas. The ethnozoological documentation of the animals in Ladakh was carried out through semistructured and close-ended questionnaire surveys and interviews. Multivariate ecological community analysis was used to elucidate the relationship between ethnozoological usage and animal species. Our results showed three animal usage clusters with 32% similarity. Moreover, the similarity in animal usage between digging tools, trophy, handle of tools, decoration, and matting, showed less than 32% of similarity. The highest priority of local people was for food followed by decoration and medicinal usage. The most frequently used animal parts were meat followed by fur and horn. Medicinal uses of 48% of the reported species, i.e., Alectoris chukar (chukar), Cuon alpinus (Asiatic wild dog), Lepus oiostolus (hares), Marmota himalayana (marmots), Ovis aries vignei (Ladakh urial), Pantholops hodgsonii (Tibetan antelope), Procapra picticaudata (Tibetan gazelle), Pseudois nayaur (blue sheep), Tetraogallus himalayensis (Himalayan snow), Tetraogallus tibetanus (Tibetan snow cock), and Lutra lutra (common otter) were reported for the first time from this region. Our study provides innovative information regarding the ethnozoological knowledge in the Ladakh region and reference data for policymakers, researchers, land managers, common public, and the other stakeholders to develop logical and scientific approaches for sustainable use of faunal diversity in hotspot regions like trans-Himalayas and other similar biodiversity-rich sites. [ABSTRACT FROM AUTHOR]

With the emergence of distributed energy resources (DERs), with their associated communication and control complexities, there is a need for an efficient platform that can digest all the incoming data and ensure the reliable operation of the power system. The digital twin (DT) is a new concept that can unleash tremendous opportunities and can be used at the different control and security levels of power systems. This paper provides a methodology for the modelling of the implementation of energy cyber-physical systems (ECPSs) that can be used for multiple applications. Two DT types are introduced to cover the high-bandwidth and the low-bandwidth applications that need centric oversight decision making. The concept of the digital twin is validated and tested using Amazon Web Services (AWS) as a cloud host that can incorporate physical and data models as well as being able to receive live measurements from the different actual power and control entities. The experimental results demonstrate the feasibility of the real-time implementation of the DT for the ECPS based on internet of things (IoT) and cloud computing technologies. The normalized mean-square error for the low-bandwidth DT case was 3.7%. In the case of a high-bandwidth DT, the proposed method showed superior performance in reconstructing the voltage estimates, with 98.2% accuracy from only the controllers' states. [ABSTRACT FROM AUTHOR]

Energy management and control of hybrid microgrids is a challenging task due to the varying nature of operation between AC and DC components which leads to voltage and frequency issues. This work utilizes a metaheuristic-based vector-decoupled algorithm to balance the control and operation of hybrid microgrids in the presence of stochastic renewable energy sources and electric vehicles charging structure. The AC and DC parts of the microgrid are coupled via a bidirectional interlinking converter, with the AC side connected to a synchronous generator and portable AC loads, while the DC side is connected to a photovoltaic system and an electric vehicle charging system. To properly ensure safe and efficient exchange of power within allowable voltage and frequency levels, the vector-decoupled control parameters of the bidirectional converter are tuned via hybridization of particle swarm optimization and artificial physics optimization. The proposed control algorithm ensures the stability of both voltage and frequency levels during the severe condition of islanding operation and high pulsed demands conditions as well as the variability of renewable source production. The proposed methodology is verified in a state-of-the-art hardware-in-the-loop testbed. The results show robustness and effectiveness of the proposed algorithm in managing the real and reactive power exchange between the AC and DC parts of the microgrid within safe and acceptable voltage and frequency levels. [ABSTRACT FROM AUTHOR]

The reliable performance of the smart grid is a function of the configuration and cyber–physical nature of its constituting sub-systems. Therefore, the ability to capture the interactions between its cyber and physical domains is necessary to understand the effect that each one has on the other. As such, the work in this paper presents a co-simulation platform that formalizes the understanding of cyber information flow and the dynamic behavior of physical systems, and captures the interactions between them in smart grid applications. Power system simulation software packages, embedded microcontrollers, and a real communication infrastructure are combined together to provide a cohesive smart grid cyber–physical platform. A data-centric communication scheme, with automatic network discovery, was selected to provide an interoperability layer between multi-vendor devices and software packages, and to bridge different protocols. The effectiveness of the proposed framework was verified in three case studies: (1) hierarchical control of electric vehicles charging in microgrids, (2) International Electrotechnical Committee (IEC) 61850 protocol emulation for protection of active distribution networks, and (3) resiliency enhancement against fake data injection attacks. The results showed that the co-simulation platform provided a high-fidelity design, analysis, and testing environment for cyber information flow and their effect on the physical operation of the smart grid, as they were experimentally verified, down to the packet, over a real communication network. [ABSTRACT FROM AUTHOR]

The operation of the smart grid is anticipated to rely profoundly on distributed microprocessor-based control. Therefore, interoperability standards are needed to address the heterogeneous nature of the smart grid data. Since the IEC 61850 emerged as a wide-spread interoperability standard widely accepted by the industry, the Sampled Measured Values method has been used to communicate digitized voltage and current measurements. Realizing that current and voltage measurements (i.e., feedback measurements) are necessary for reliable and secure noperation of the power grid, firstly, this manuscript provides a detailed analysis of the Sampled Measured Values protocol emphasizing its advantages, then, it identifies vulnerabilities in this protocol and explains the cyber threats associated to these vulnerabilities. Secondly, current efforts to mitigate these vulnerabilities are outlined and the feasibility of using neural network forecasters to detect spoofed sampled values is investigated. It was shown that although such forecasters have high spoofed data detection accuracy, they are prone to the accumulation of forecasting error. Accordingly, this paper also proposes an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed methods is experimentally verified in a laboratory-scale smart grid testbed. [ABSTRACT FROM AUTHOR]

The real-time operation of the energy management system (RT-EMS) is one of the vital functions of Microgrids (MG). In this context, the reliability and smooth operation should be maintained in real time regardless of load and generation variations and without losing the optimum operation cost. This paper presents a design and implementation of a RT-EMS based on Multiagent system (MAS) and the fast converging T-Cell algorithm to minimize the MG operational cost and maximize the real-time response in grid-connected MG. The RT-EMS has the main function to ensure the energy dispatch between the distributed generation (DG) units that consist in this work on a wind generator, solar energy, energy storage units, controllable loads and the main grid. A modular multi-agent platform is proposed to implement the RT-EMS. The MAS has features such as peer-to-peer communication capability, a fault-tolerance structure, and high flexibility, which make it convenient for MG context. Each component of the MG has its own managing agent. While, the MG optimizer (MGO) is the agent responsible for running the optimization and ensuring the seamless operation of the MG in real time, the MG supervisor (MGS) is the agent that intercepts sudden high load variations and computes the new optimum operating point. In addition, the proposed RT-EMS develops an integration of the MAS platform with the Data Distribution Service (DDS) as a middleware to communicate with the physical units. In this work, the proposed algorithm minimizes the cost function of the MG as well as maximizes the use of renewable energy generation; Then, it assigns the power reference to each DG of the MG. The total time delay of the optimization and the communication between the EMS components were reduced. To verify the performance of our proposed system, an experimental validation in a MG testbed were conducted. Results show the reliability and the effectiveness of the proposed multiagent based RT-EMS. Various scenarios were tested such as normal operation as well as sudden load variation. The optimum values were obtained faster in terms of computation time as compared to existing techniques. The latency from the proposed system was 43% faster than other heuristic or deterministic methods in the literature. This significant improvement makes this proposed system more competitive for RT applications. [ABSTRACT FROM AUTHOR]

The optimal reactive power dispatch (ORPD) problem represents a noncontinuous, nonlinear, highly constrained optimization problem that has recently attracted wide research investigation. This paper presents a new hybridization technique for solving the ORPD problem based on the integration of particle swarm optimization (PSO) with artificial physics optimization (APO). This hybridized algorithm is tested and verified on the IEEE 30, IEEE 57, and IEEE 118 bus test systems to solve both single and multiobjective ORPD problems, considering three main aspects. These aspects include active power loss minimization, voltage deviation minimization, and voltage stability improvement. The results prove that the algorithm is effective and displays great consistency and robustness in solving both the single and multiobjective functions while improving the convergence performance of the PSO. It also shows superiority when compared with results obtained from previously reported literature for solving the ORPD problem. [ABSTRACT FROM AUTHOR]

Recent public disclosures on attacks targeting the power industry showed that savvy attackers are now capable of occulting themselves from conventional rule-based network intrusion detection systems (IDS), bringing about serious threats. In order to leverage the work of rule-based IDS, this paper presents an artificially intelligent physical-model-checking intrusion detection framework capable of detecting tampered-with control commands from control centers of power grids. Unlike the work presented in the literature, the work in this paper utilizes artificial intelligence (AI) to learn the load flow characteristics of the power system and benefits from the fast responses of the AI to decode and understand contents of network packets. The output of the AI is processed through an expert system to verify that incoming control commands do not violate the physical system operational constraints and do not put the power system in an insecure state. The proposed content-aware IDS is tested in simulation on a 14-bus IEEE benchmark system. Experimental verification on a small power system, with an IEC 61850 network architecture is also carried out. The results showed the accuracy of the proposed framework in successfully detecting malicious and/or erroneous control commands. [ABSTRACT FROM AUTHOR]

Electric Vehicles (EVs) and hybrid Electric vehicles (HEVs) are going to reshape the future of the transportation sector. However, adopting large numbers of EVs and HEVs will impact the electric utilities as well. Managing the charging/discharging of substantial numbers of distributed batteries will be critical for the successful adoption of EVs and HEVs. Therefore, this paper presents a review study about the recent control and optimization strategies for managing the charging/discharging of EVs. The paper covers different control and operation strategies reported in the literature as well as issues related to the real time dispatching of EVs in the smart grids. In addition, challenges related to the stochastic nature of the driving characteristics of EVs are considered. Finally, some open problems related to the energy management of EVs will be presented. [ABSTRACT FROM AUTHOR]

In this paper, a smart distributed DC/DC converter synchronization advanced technique and phase angle optimization algorithm are proposed using to reduce the DC bus overall ripple. A global positioning system-based scheme is used to synchronize the carrier among the distributed converters. The carrier phase angle optimization among the different converters is inspired by Carrier-Sense Multiple Access protocol. The proposed system is simulated and analyzed using Matlab/Simulink program. As a proof of concept of the proposed technique, two case studies have been investigated under equal and unequal load sharing among the distributed generators. The proposed algorithm shows a significant reduction in the DC bus voltage ripple. To prove the concept, a laboratory test-bed has been built and the proposed algorithm has been implemented to validate the theoretical and simulation results. The close agreement between the experimental and simulation results demonstrates the effectiveness and validity of the proposed algorithm. [ABSTRACT FROM AUTHOR]