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The emergence of antibiotic-resistant Acinetobacter baumannii (A. baumannii) is a pressing threat in clinical settings. Colistin is currently a widely used treatment for multidrug-resistant A. baumannii, serving as the last line of defense. However, reports of colistin-resistant strains of A. baumannii have emerged, underscoring the urgent need to develop alternative medications to combat these serious pathogens. To resist colistin, A. baumannii has developed several mechanisms. These include the loss of outer membrane lipopolysaccharides (LPSs) due to mutation of LPS biosynthetic genes, modification of lipid A (a constituent of LPSs) structure through the addition of phosphoethanolamine (PEtN) moieties to the lipid A component by overexpression of chromosomal pmrCAB operon genes and eptA gene, or acquisition of plasmid-encoded mcr genes through horizontal gene transfer. Other resistance mechanisms involve alterations of outer membrane permeability through porins, the expulsion of colistin by efflux pumps, and heteroresistance. In response to the rising threat of colistin-resistant A. baumannii, researchers have developed various treatment strategies, including antibiotic combination therapy, adjuvants to potentiate antibiotic activity, repurposing existing drugs, antimicrobial peptides, nanotechnology, photodynamic therapy, CRISPR/Cas, and phage therapy. While many of these strategies have shown promise in vitro and in vivo, further clinical trials are necessary to ensure their efficacy and widen their clinical applications. Ongoing research is essential for identifying the most effective therapeutic strategies to manage colistin-resistant A. baumannii. This review explores the genetic mechanisms underlying colistin resistance and assesses potential treatment options for this challenging pathogen. [ABSTRACT FROM AUTHOR]

Acinetobacter baumannii , a predominant nosocomial pathogen, represents a grave threat to public health due to its multiple antimicrobial resistance. Managing patients afflicted with severe infections caused by multiple drug-resistant A. baumannii is particularly challenging, given the associated high mortality rates and unfavorable prognoses. The diminishing efficacy of antibiotics against this superbug underscores the urgent necessity for novel treatments or strategies to address this formidable issue. Bacteriophage-derived polysaccharide depolymerase enzymes present a potential approach to combating this pathogen. These enzymes target and degrade the bacterial cell's exopolysaccharide, capsular polysaccharide, and lipopolysaccharide, thereby disrupting biofilm formation and impairing the bacteria's defense mechanisms. Nonetheless, the narrow host range of phage depolymerases limits their therapeutic efficacy. Despite the benefits of these enzymes, phage-resistant strains have been identified, highlighting the complexity of phage-host interactions and the need for further investigation. While preliminary findings are encouraging, current investigations are limited, and clinical trials are imperative to advance this treatment approach for broader clinical applications. This review explores the potential of phage-derived depolymerase enzymes against A. baumannii infections. [ABSTRACT FROM AUTHOR]

Although single‐stage inverters are popular for simpler design they face difficulties in shoot‐through mode operation. Insufficient DC voltage regulation and complicated LC network are principal drawbacks of these topologies. A new split source inverter (SSI) can solve problems with single‐stage inverters. In this paper, SSI replaced the voltage source inverter (VSI) of a shunt active power filter (SAPF) which alleviates power quality (PQ) issues in power system. Furthermore, a VSI‐based SAPF faces challenges to maintain consistent voltage across DC‐link capacitor, exactly compensating current generation, and switching loss reduction in inverter. This study examined efficacy of two inverter‐based SAPFs considering a modified synchronous reference frame approach for generating reference current; fuzzy logic controller for regulating DC‐link voltage; and adaptive fuzzy hysteresis current controller for generating switching pulses. Ideal and non‐ideal sources were considered when running the simulations for various load circumstances. The proposed SSI‐based SAPF with an advanced control approach can eradicate source current harmonics to 0.52% and 0.45% under ideal source conditions, and 0.65% and 0.54% under non‐ideal source conditions for non‐linear loads. Similarly, the ripples in the DC‐link voltage are also reduced to 2–3 V for the ideal case and 4–5 V for non‐ideal case. [ABSTRACT FROM AUTHOR]

Through complex interactions with the host's immune and physiological systems, gut bacteria play a critical role as etiological agents in a variety of human diseases, having an impact that extends beyond their mere presence and affects the onset, progression, and severity of the disease. Gaining a comprehensive understanding of these microbial interactions is crucial to improving our understanding of disease pathogenesis and creating tailored treatment methods. Correcting microbial imbalances may open new avenues for disease prevention and treatment approaches, according to preliminary data. The gut microbiota exerts an integral part in the pathogenesis of numerous health conditions, including metabolic, neurological, renal, cardiovascular, and gastrointestinal problems as well as COVID-19, according to recent studies. The crucial significance of the microbiome in disease pathogenesis is highlighted by this role, which is comparable to that of hereditary variables. This review investigates the etiological contributions of the gut microbiome to human diseases, its interactions with the host, and the development of prospective therapeutic approaches. To fully harness the benefits of gut microbiome dynamics for improving human health, future research should address existing methodological challenges and deepen our knowledge of microbial interactions. [ABSTRACT FROM AUTHOR]

In recent years, the importance of deregulated power systems has grown significantly, resulting in positive effects on stability, reliability, innovation, and investment in new energy grid technology. The competitive landscape among energy providers and distributors has empowered consumers to not only save money on their energy bills but also incorporate sustainable energy sources into the grid. To efficiently manage electricity distribution, deregulated power systems must include a smart grid and microgrid (MG). Herein, the potential for sustainable expansion of these systems, as well as their economic and environmental implications, are examined. A comprehensive grid system that integrates smart grids and MGs can offer a complete solution, catering to the evolving energy needs of communities and businesses. The advantages of establishing such a system, including improved grid stability, reliability, and increased utilization of renewable energy sources (RES), are highlighted. Furthermore, the integration of MGs and smart grids enhances the management of distributed generation, allowing power companies to optimize system operations for profitability and efficiency. By following these suggestions, businesses and stakeholders in the power sector can enhance the efficiency and responsibility of their systems, resulting in benefits for both the economy and the environment. [ABSTRACT FROM AUTHOR]

Mycotoxins, derived from fungi, pose significant threats to both human health and livestock well‐being. Their contamination of food and feed supplies results in substantial economic losses annually. Various chemical and physical methodologies are employed to mitigate the toxicity associated with these toxins. However, the utilization of microorganism‐mediated biotransformation presents a particularly promising and actively researched avenue for addressing the challenges posed by mycotoxins and enhancing food safety protocols. The intestinal microbiota engages in a dynamic interplay with mycotoxins, wherein mycotoxins disrupt the microbial equilibrium within the intestines and elevate epithelial barrier permeability, thereby impacting the intestinal ecosystem. Conversely, beneficial gut microbes possess the capacity to enzymatically degrade or sequester mycotoxins, thereby converting them into metabolites of reduced or negligible toxicity. This review encapsulates significant advancements in the biological detoxification of mycotoxins as evidenced by prior research endeavors. The discussion encompasses the repercussions of mycotoxin exposure on both human and animal health, alongside an examination of gut microbial‐based strategies for mycotoxin detoxification. [ABSTRACT FROM AUTHOR]

A battery energy storage system (BESS), due to its very fast dynamic response, plays an essential role in improving the transient frequency stability of a grid. The performance of the BESS varies with the system's installation site. Hence, the optimal location of the BESS is of utmost importance for improving transient frequency stability. Therefore, this paper presents a hierarchical approach for optimizing the BESS placement to improve a grid's transient frequency stability. In most research, frequency nadir and rate of change of frequency (ROCOF) have been considered for studying frequency stability. This paper considers two more parameters, along with frequency nadir and ROCOF, to study the transient frequency stability, settling time, and decay ratio. A novel frequency stability index (FSI) using the four transient frequency parameters has been developed. After a significant disturbance in a benchmarked test system, the FSI was used to identify the optimal location of the BESS for stabilizing the frequency. It has been observed that, after a sudden generator outage, the ROCOF and the frequency nadir improve the best when the BESS is located at the bus closest to the generator experiencing the outage. However, considering the other two parameters as well, the value of the FSI is the minimum; that is, the optimum solution is when the BESS is located at the bus that is the second closest to the generator experiencing the outage. Results of similar studies validate the proposed FSI in indicating the optimal location of the BESS in improving the transient frequency behavior of the system. [ABSTRACT FROM AUTHOR]

This study proposes an optimal energy management strategy for dual‐source fuel cell hybrid electric vehicles (FCHEV) utilizing the support vector machine (SVM) classifier. The goal is to optimize power distribution between fuel cells and batteries to enhance vehicle's performance and efficiency. The SVM classifier is trained using a dataset of driving conditions and corresponding optimal power distribution (OPD) values obtained through simulation. The trained classifier predicts real‐time OPD based on driving conditions. In comparison to existing literature, this study conducts a comparative analysis of energy management control strategies like model predictive control (MPC), fuzzy, equivalent consumption minimization strategy (ECMS), proportional‐integral (PI) control, and state machine control (SMC) strategy for FCHEVs using the MATLAB/SIMULINK platform and real‐world driving dataset. The proposed strategy is then tested in a real‐time EV simulator to verify its efficacy. Additionally, this study introduces the SVM classifier technique for selecting the optimal energy management strategy for FCHEVs. Performance analysis using SVM reveals that the MPC control strategy offers the highest efficiency compared to other techniques based on selected features, achieving an average performance of 95% through cross‐validation. This analysis demonstrates the most cost‐effective and fuel‐efficient utilization of electricity flow in a modern energy‐efficient environment. [ABSTRACT FROM AUTHOR]

In the present market scenario, energy cost has been increased and also restrictions have been faced in fossil fuels energy sources. This leads to evolvement of combined heat and power generating units having higher efficiency as compared to the existing systems. The optimal dispatch of CGUs involves a number of intricate constraints, making it a practical optimization problem. So, an improved heap‐based optimizer algorithm has been implemented in this work for solving optimal dispatch problem by accomplishing a proper balance between initial and final stages of global search and convergence, respectively. This problem provides optimal scheduling of heat and power generating units and seeks to minimize the overall fuel cost supply of combined units considering their operational limits. Here, three test systems, that is, 7‐units, 24‐units and 48 units system have been taken into consideration to verify the performance of proposed IHBO algorithm. The impact of prohibited zones on power dispatch has been analysed for both the system in an electricity market. In addition, the valve‐point loading effect, mutual dependency of produced heat and power of combined units and also transmission power losses in transmission lines have been studied. Comparisons among different methods have been made based on their respective solutions obtained and from that it manifests the robustness and superior performance of the proposed technique. Verification studies showed that impact of prohibited zones on generating units, increases the production cost with respect to without prohibited zones. However the proposed technique yields least production cost among other techniques. [ABSTRACT FROM AUTHOR]

This research work emphasizes proposing a hybrid social grouping algorithm (SGA) and perturb and observe (P&O) scheme for tracking the global power peak in a partially shaded photovoltaic (PV) array. PV panels getting shaded, even partially, exhibits multiple power peaks, and hence conventional maximum power point tracking (MPPT) algorithms fail in tracking the maximum power peak as it gets deceived by local maxima. Most of the prevailing global search algorithms suffer in performance due to the stochastic search which consumes time even after nearing the global power peak. Therefore, a hybridization of the global search algorithm and the conventional algorithm will be a prudent solution. SGA, a global search algorithm based on individual and group cognizant behaviour, has been hybridized with a well-entrenched P&O algorithm that complements each other in achieving the global power peak swiftly. The hybridized algorithm achieves the global power peak in 0.4 seconds faster than the stand-alone SGA algorithm during complex shading conditions. The proposed scheme has been implemented for an 800 W PV array in a MATLAB simulation and validated experimentally in a hardware setup using a SAS1000L solar array simulator-programmable source, a DC-DC converter, and a dSPACE 1104 controller. The simulation and experimental results reveal that the proposed search scheme is very competent in converging towards the global maximum through SGA first and achieving the peak point through P&O. The proposed scheme has also been tested for a dynamic shading pattern, and it is evident that the proposed scheme outperforms its counterparts in terms of convergence time. [ABSTRACT FROM AUTHOR]

To install a new infrastructure of a power transmission line is not only costly but also time-consuming, and it also have some harmful impact on our environment and therefore existing transmission infrastructure is important to use effectively. FACTS is a popular solution to utilize this existing power transmission system by using series compensation by means of the series capacitor to enhance the power transmission capacity as well as voltage stability. This paper explores the utilization of series capacitor applying to the power grid of Eastern part of Bangladesh. For doing this we have considered the analytical calculation of 10% to 85% compensation of that power line. As a result, we have observed that the power transfer capacity has been enhanced about 37 times and it also improve the voltage stability, when the compensation ration is 85%. We consider our calculation mathematically and represent the load curve and voltage profile by plotting in Matlab. [ABSTRACT FROM AUTHOR]

Despite the potential protective role of the gut microbiome against COVID-19, specific microbes conferring resistance to COVID-19 have not yet been identified. In this work, we aimed to identify and validate gut microbes at the species level that provide protection against SARS-CoV-2 infection. To identify gut microbes conferring protection against COVID-19, we conducted a fecal microbiota transplantation (FMT) from an individual with no history of COVID-19 infection or immunization into a lethal COVID-19 hamster model. FMT from this COVID-19-resistant donor resulted in significant phenotypic changes related to COVID-19 sensitivity in the hamsters. Metagenomic analysis revealed distinct differences in the gut microbiome composition among the hamster groups, leading to the identification of two previously unknown bacterial species: Oribacterium sp. GMB0313 and Ruminococcus sp. GMB0270, both associated with COVID-19 resistance. Subsequently, we conducted a proof-of-concept confirmation animal experiment adhering to Koch's postulates. Oral administration of this gut microbe pair, Oribacterium sp. GMB0313 and Ruminococcus sp. GMB0270, to the hamsters provided complete protection against SARS-CoV-2 infection through the activation of CD8+ T cell mediated immunity. The prophylactic efficacy of the gut microbe pair against SARS-CoV-2 infection was comparable to, or even superior to, current mRNA vaccines. This strong prophylactic efficacy suggests that the gut microbe pair could be developed as a host-directed universal vaccine for all betacoronaviruses, including potential future emerging viruses.