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The growing demand for sustainable energy has fueled advancements in bio-fuel cells. Pencil graphite–based electrodes, known for their electrochemical properties and affordability, are increasingly valued. The major aim of the study is to develop an eco-friendly, cost-effective for modifying pencil graphite electrodes (PGE) using plant-based iron nanoparticles, targeting advancements in biofuel cells. Iron nanoparticles synthesized via green methods were analyzed using UV–visible spectroscopy (UV–Vis), X-ray photon spectroscopy (XPS), scanning electron microscopy (SEM), and energy dispersive X-ray analyzer (EDX). Their electrochemical properties, when coated on PGL from various plant extracts, were analyzed using cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and open circuit potential (OCP). This study also involves optimization of iron nanoparticle–coated pencil graphite electrodes (FeNP/PGE) using a central composite design (CCD) model. Independent variables were selected and optimized, with their effects correlated to the current density and the effective surface area (ESA) of the modified PGEs. The R2 and adjusted R2 values, 0.9992 and 0.9984, respectively, demonstrate that the model is significant. The optimum conditions for maximum current density were obtained at temperature (70 °C), Rosa centifolia flower as an extract, thickness of graphite electrode (0.7 mm), and scan rate (50 mV/s). The maximum current density of 2790.13 μA cm−2 with an effective surface area of 0.3991 cm2 (0.7 mm HB-grade) clearly shows the model predicted was accurate resulting in higher potential in biofuel cells. [ABSTRACT FROM AUTHOR]

Influential spreaders are key nodes in networks that maximize or control the spreading processes. Many real-world systems are represented as weighted networks, and several indexing methods, such as weighted betweenness, closeness, k-shell decomposition, voterank, and mixed degree decomposition, among others, have been proposed to identify these influential nodes. However, these methods often face limitations such as high computational cost, non-monotonic rankings, and reliance on tunable parameters. To address these issues, this paper introduces a new tunable parameter-free method, Normalized Strength-Degree Centrality (nsd), which efficiently combines a node's normalized degree and strength to measure its influence across various network structures. Experimental results on eleven real and synthetic weighted networks show that nsd outperforms the existing methods in accurately identifying influential spreaders, strongly correlating to the Weighted Susceptible-Infected-Recovered (WSIR) model. Additionally, nsd is a parameter-free method that does not require time-consuming preprocessing to estimate rankings. [ABSTRACT FROM AUTHOR]

Oral cancer often presents in advanced stages, requiring complex surgical interventions. The bipedal pectoralis major myocutaneous (PMMC) flap is a commonly used alternative to the gold standard free flaps for reconstruction in resource-constrained settings. However, large donor sites may necessitate split-thickness skin grafting (STSG), leading to aesthetic challenges. This study explores using the thoracoabdominal flap (TA) for a large donor site closure following PMMC flap harvest in advanced oral cancer reconstruction. A retrospective analysis was conducted on twelve patients with advanced oral cancer with extensive skin involvement. The TA flap was utilised to achieve tension-free closure of the donor site. Patient demographics, clinical features, treatment stage, operative details, and postoperative complications were meticulously recorded. All patients had advanced oral cancer, with seven having left-sided disease and five having right-sided disease. The TA flap closure resulted in minimal complications, with two patients developing seromas and one experiencing marginal necrosis during the postoperative period. The innovative TA flap technique is useful in closing extensive donor sites following PMMC flap harvest for advanced oral cancer cases. It offers advantages such as improved cosmetic outcomes and fewer complications than split-thickness skin grafting. [ABSTRACT FROM AUTHOR]

Quantum architecture Search (QAS) is a promising direction for optimization and automated design of quantum circuits towards quantum advantage. Recent techniques in QAS emphasize Multi-Layer Perceptron (MLP)-based deep Q-networks. However, their interpretability remains challenging due to the large number of learnable parameters and the complexities involved in selecting appropriate activation functions. In this work, to overcome these challenges, we utilize the Kolmogorov-Arnold Network (KAN) in the QAS algorithm, analyzing their efficiency in the task of quantum state preparation and quantum chemistry. In quantum state preparation, our results show that in a noiseless scenario, the probability of success is 2× to 5× higher than MLPs. In noisy environments, KAN outperforms MLPs in fidelity when approximating these states, showcasing its robustness against noise. In tackling quantum chemistry problems, we enhance the recently proposed QAS algorithm by integrating curriculum reinforcement learning with a KAN structure. This facilitates a more efficient design of parameterized quantum circuits by reducing the number of required 2-qubit gates and circuit depth. Further investigation reveals that KAN requires a significantly smaller number of learnable parameters compared to MLPs; however, the average time of executing each episode for KAN is higher. [ABSTRACT FROM AUTHOR]

Abstract Pompe disease is a severe disorder caused by loss of acid α‐glucosidase (GAA), leading to glycogen accumulation in tissues and neuromuscular and cardiac dysfunction. Enzyme replacement therapy is the only available treatment. AT845 is an adeno‐associated viral vector designed to express human GAA specifically in skeletal muscle and heart. Systemic administration of AT845 in Gaa−/− mice led to a dose‐dependent increase in GAA activity, glycogen clearance in muscles and heart, and functional improvement. AT845 was tolerated in cynomolgus macaques at low doses, while high doses caused anti‐GAA immune response, inflammation, and cardiac abnormalities resulting in unscheduled euthanasia of two animals. Conversely, a vector expressing the macaque GAA caused no detectable pathology, indicating that the toxicity observed with AT845 was an anti‐GAA xenogeneic immune response. Western blot analysis showed abnormal processing of human GAA in cynomolgus muscle, adding to the species‐specific effects of enzyme expression. Overall, these studies show that AAV‐mediated GAA delivery to muscle is efficacious in Gaa−/− mice and highlight limitations in predicting the toxicity of AAV vectors encoding human proteins in non‐human species.

Electric vehicles (EVs) are expected to surpass conventional vehicles as a preferred means of transportation due to their improved energy efficiency and diminished ecological footprint. The performance of electric vehicles (EVs) can be negatively impacted if electric vehicle charging stations (EVCS) are not properly positioned and connected to the distribution network. The current research introduces a reliability, availability, and operability (RAO-3) methodology that employs a fuzzy classification technique to identify the most efficient dimensions and locations for electric vehicle charging stations (EVCS), distributed generators, and super capacitors in 69 radial bus distribution systems with network reconfiguration. Load flow analysis is a numerical technique employed to construct mathematical representations for the charging loads of electric vehicle (EV) batteries. This is achieved by leveraging the characteristic curves of Li-ion battery charging. The proposed approach of fuzzified RAO-3 aims to enhance the power factor of the substation by incorporating all relevant factors into the distribution network. The fuzzy multiobjective function is utilised to simultaneously optimise the positioning of electric vehicle charging stations (EVCS), distributed generators (DGs), and storage capacities (SCs), with or without network reconfiguration. Based on the outcomes of the simulation, the concurrent placement technique enhances performance through the reduction of power loss, enhancement of the voltage profile, and optimisation of electric vehicle (EV) utilisation. [ABSTRACT FROM AUTHOR]

In this paper, a strain-modified Si/Si0.97C0.03 asymmetrical superlattice exotic type (p + -i-p-n +) avalanche photodetector has been designed for applications on the infrared wavelength region. The photoelectric characteristics of the device are studied by developing a self-consistent quantum phenomena-based drift–diffusion model in conjunction with PSpice simulator. The overall performance of the device has been boosted significantly by introducing strain engineering which enhances the out-plane mobility of the charge particles in the intrinsic/active region of the device. The strain is produced in the intrinsic/active region by inclusion of small amount of carbon (C) into the pure Si material. The proposed strain-modified exotic avalanche photodetector exhibits better performance in terms of quantum efficiency (0.671) and photo-responsivity (0.645 A/W) compared to its planer unstrained Si counterpart (quantum efficiency: 0.481, photo-responsivity: 0.524A/W) at 1800 nm wavelength. Additionally, a 3 × 4 array of photodetectors has been designed using this device and its optoelectronic properties are studied in the IR wavelength region. The superiority of the performance of the 3 × 4 array of photodetectors is established in terms of better quantum efficiency (0.872) and better photo-responsivity (0.851 A/W). The validity of quantum phenomena-based drift–diffusion model is established by comparing the simulated data with experimental findings under similar operating conditions. The developed device can be used in defense as well as biomedical industries for sensing applications. [ABSTRACT FROM AUTHOR]

Rotor turn short circuit fault of permanent magnet synchronous machines (PMSMs) in the distribution system has a significant issue caused by unbalance loading. This fault has a significant electromagnetic impact on the rotor winding in relation to the machine's external equipment. As a result, while designing the power system distribution network, the PMSMs rotor winding short circuit current limitation receives majority of attention. For simulation a 3-phase short-circuit model of synchronous generator is developed here by using MATLAB/SIMULINK software. Therefore, a method is used to determine a PMSM's internal winding quantity in the event of a short circuit, as well as its location within the distribution network. The PMSM is energized with a small sinusoidal voltage at standstill situation in this suggested approach to compute the synchronous inductance and winding resistance through the output current. It has been demonstrated that the number of shorted windings may be calculated using the variation of output current caused by an internal winding short circuit event under zero fault resistance condition. Except for intricate machine modelling or investigation of machine internal winding short circuit models comprising several tappings, this useful technique can be used to determine fault intensity for a specific synchronous machine. This paper primarily addressed on fault extremity protection strategies using before-fault and after-fault activities by employing harmonic filters. A three-phase synchronous machine model with a protective system is implemented in the distribution network using MATLAB/SIMULINK is taken into consideration in order to verify the findings. The results presented in this work are vital to a complete solution that includes fault reduction techniques. Harmonics elimination and instant fault mitigation techniques with load unbalancing are analyzed based on effective outcomes to judge the system stability and feasibility of the short circuit current intensity assessment. [ABSTRACT FROM AUTHOR]

The importance of strengthening grid resilience has grown with the increase in environmental destruction and modern power grid complexity, as a consequence of power outages inflicted by human intrusion and extreme weather events. Micro-grids (MGs) have proven to be a viable alternative in such circumstances. However, these occurrences are highly unpredictable, resulting in unintended islands of MGs with negative consequences. As a response, alerting its distributed generations about unintended island is indeed a crucial issue for enhancing grid resilience with MG. Therefore, it is essential to develop a technique for the efficient and accurate detection of unintended islands. There has been an increase in the use of micro-phasor measurement units (µ-PMUs) in MG. In the perspective of this, using an efficient µ-PMU, the research provides a method for finding unintended islands in a MG. The µ-PMU analyses the solar generator bus voltage and analyzes it with symmetrical components for island identification. This study introduces a µ-PMU based Fortescue-transform and random forest algorithm method for rapid detection of unintended islanding in distribution generation system. The approach monitors voltage phasor of zero and negative sequence, calculating angular sum over time to distinguish islanding event from other disturbance. Using Matlab/Simulink, the proposed method is evaluated on the IEEE-34 node distribution network. Multiple simulations provide validation for the method's resilient performance. The methodology proposed has a detection time of 20 ms. [ABSTRACT FROM AUTHOR]

In this work, a nine level (9-L) asymmetrical switched-capacitor multilevel inverter (ASCMLI) based induction heated (IH) autoclave for sterilization in medical applications is proposed. Due to the several benefits of multilevel inverter such as controlling of voltage magnitude and hence uniformity of heat is maintained at the load side as compared to conventional heating of autoclave. It has two common ground-connected dc voltage sources, which makes it ideal for usage in medical applications. Moreover, the development of a compact autoclave is carried out in this work that has a much reduced running time without sacrificing the quality of its sterilization. Further, the sterilization schedule for conventional and IH autoclave is presented in different temperature and pressure condition. The distributions of magnetic flux density and induced eddy current density in the multilevel inverter based IH autoclave were also exhibited. Finally, the performance of the proposed system are validated by simulation and experimental results obtained from a laboratory prototype setup. [ABSTRACT FROM AUTHOR]

This paper introduces a comprehensive three-step framework for fault classification in underground cable systems. The first step involves the implementation of the Cumulative Sum (CUSUM) technique to detect the fault instances, which will help in precisely tracking the affected portions. The second step focuses on parameter estimation techniques, followed by the third step, which incorporates classification techniques. The study employs a range of evolutionary optimization algorithms, including Ant Colony Optimization, Bacteria Foraging Optimization, Simulated Annealing, Genetic Algorithm, and Particle Swarm Optimization. These algorithms are effectively employed to track and estimate parameters like amplitude, phase, frequency, and damping factor associated with various types of permanent faults, such as L-G fault, L-L fault, L-L-G fault, and L-L-L-G fault generated in the underground cable. The optimized parameters extracted through these algorithms are utilized as features within a Support Vector Classifier for fault classification. The overall accuracy of the classifier using these features is reported to be 0.944, which is quite high and indicates a strong performance in classifying faults. The study includes a brief comparison of the performance of these bio-inspired algorithms. The effectiveness of the tracking algorithms is validated through the use of laboratory-tested current signals. In addition, the signals are subjected to varying signal-to-noise ratios to evaluate the robustness of the tracking algorithm. A comparative analysis is performed to estimate the accurate parameters and highlights the significant tracking ability of the Particle Swarm Optimization (PSO) algorithm, which outperforms other algorithms.The Root Mean Squared Percentage Error (RMSPE) for the L-G fault in PSO is 0.3082, showing superior performance compared to other algorithms. [ABSTRACT FROM AUTHOR]

Solar photovoltaics have emerged as an economic source of renewable electricity generation for regions with high solar irradiation. Still, the installation of utility-scale PV systems is often disrupted due to the unavailability of land. Sparsely populated areas with a hot, dry climate can mitigate the land-energy conflict as they experience higher solar irradiation. In arid areas, the PV systems incur more losses due to dust deposition on PV modules and reduced energy conversion efficiency at higher temperatures. The shortage of water makes the module cleaning procedures cost-prohibitive. Floating Solar photovoltaic (FSPV) systems resolve these problems due to their reduced land footprint, higher efficiency, and reduce evaporative water loss. This study estimates the energy generation of a 4.8 MW FSPV-based microgrid in a hot, semi-arid urban area. By utilizing 5% area of the waterbody, the FSPV system yields 8.876 GWh of electricity annually, to meet 41.7% electricity demand of the study area. The system generates 16.7% more power compared to the land-based PV system. The performance ratio of 82%, and a DC capacity utilization factor of 20.3% is achieved. The system saves 52,810.32 m3 of water per year, compensating for the water requirement of 786.99 m3. for cleaning and dust removal of PV modules. The weekly cleaning procedure limits the soiling loss to 2.79%, compared to 8.47% after a month without cleaning. The FSPV-based microgrid reduces annual CO2 emissions by 2.93 tonnes. This study shall enable engineers, urban planners, and policymakers to develop clean energy-based, sustainable microgrid solutions for urban areas. [ABSTRACT FROM AUTHOR]

The grid connected photovoltaic system (GCPVS) faces several difficulties due to their intermittent natures such as solar irradiance variations, grid voltage distortions and unbalanced load distributions. These complications interrupt the functioning of power system to attain maximum probable power output. Therefore, to address these problems, this article proposes a robust super twisting sliding mode-incremental conductance-instantaneous power theory (STSM-IC-IPT) based control mechanism for 3-phase GCPVS. The super twisting sliding mode (STSM) controller is introduced to reduce the difference between actual inverter current and reference inverter current of GCPVS when it is subject to various uncertainties and nonlinearities. The modified incremental conductance (IC) maximizes the solar power output generated from the photovoltaic panels. In addition, the instantaneous power theory (IPT) is applied to enhance the active power and reactive power transmission between grid-connected PV systems. The proposed STSM-IC-IPT method is examined under two different experimental procedures namely simulation setup and experimental setup. The efficiency of the proposed STSM-IC-IPT control mechanism is evaluated by comparing its performance with existing ASMC-IC-IPT control scheme. The experimental results illustrate that the proposed STSM-IC-IPT control mechanism achieves superior performance efficiency under dynamic loading, steady and transient conditions. [ABSTRACT FROM AUTHOR]

India is now one of the top five countries in the world for PV and solar thermal power generation. At the same time, we must develop a plan for recycling these massive numbers of solar panels in the future. This article has contributed to proposing the resulting regulatory system. The PV waste management sector is extremely neglected, leaving it entirely to the scrap trading underground. There is not enough of a system in place to collect and reuse the solar panels' components for recycling. In addition, a solid institution to manage this procedure on a commercial scale has yet to be established. As a result, the purpose of this work was to use cost–benefit analysis to determine the economic viability of a solar module recycling project in India. The benefit–cost ratio (BCR) and net present value (NPV) were calculated to be 1.64 and 25.22 million USD, respectively. According to the sensitivity study, the most delicate issues impacting the project's economy were the selling benefits of recycled materials and tax. Finally, this analysis offered strategies for the government and linked businesses to enhance the economy. [ABSTRACT FROM AUTHOR]

Floating solar photovoltaic (FSPV) is an emerging type of solar energy that aims to help the environment by supplying green and clean energy. Since the technology is new and in its initial stage of development, evaluating the long-term performance, effective control, and feasibility studies of FSPV facilities are necessary for optimization of output and accuracy. The effective analysis and calculation of FSPV panel performances are crucial in determining actual performance, long-term operation, feasibility, and carbon-saving capacity of FSPV systems. This paper presents an analysis and comparison of floating solar power plant installed in saline water under salty humid weather with respect to FSPV plant installed on general lake water and investigates the output for its lifecycle and efficiency. The findings of this research can be useful for policymakers, investors, and engineers involved in the planning and implementation of FSPV projects. A 10 MW capacity floating solar plant is simulated on the brackish water of Chilika Lake covering three districts of Odisha state of India. Factors like wind speed, albedo, temperature, and soiling is considered for better accuracy. The proposed model is simulated in the system advisor model. The payback period and energy outcomes for various soiling conditions along with varied degradations are analyzed, and it is found that the total loss in energy outcome is 4.075 percent annually with a 5.8% increment in the payback time of the installed solar power plant. [ABSTRACT FROM AUTHOR]

Dimethoate, an organophosphate insecticide, was initially developed in 1962 for broad-spectrum management of a variety of insects such as mites, aphids, flies, and plant hoppers. It suppresses the acetylcholinesterase activity, resulting in nerve damage and death of that organism. Many organisms are observed to be harmed by dimethoate. Among them, aquatic organisms are highly affected due to their exposure to the pesticide by run-off. As a result of this, it might show oxidative stress, neurotoxic effects, and behavioural anomalies. Many of these aquatic organisms are part of the staple diet of humans. Thus, the accumulated pesticide residues in these organisms enter the human body. It also might enter human body through the groundwater (used as drinking water) where the residues were also obtained due to leaching. In this review, we emphasised the toxic effects of dimethoate on various aquatic organisms and humans. It also highlights the various methods by which dimethoate is degraded. [ABSTRACT FROM AUTHOR]

This paper addresses the urgent challenges posed by limited energy resources and environmental degradation, focusing on the critical issue of excessive energy consumption and advocating for sustainable practices. The study explores the viability of utilizing solar-powered electric vehicles with induction cooking systems as a sustainable, long-term solution for India's travel and tourism sector. The implementation of such systems in urban and suburban regions presents numerous advantages, including decreased dependence on conventional energy sources, reduced greenhouse gas emissions, and financial benefits derived from more affordable transportation and lower fuel costs. Identifying a literature gap in the deployment of electric vehicles within the travel and tourism domain, the research is motivated by environmental considerations, sustainability goals, economic factors, health standards, innovation, system reliability, and regulatory incentives. The authors contribute significantly by meticulously demonstrating the practicality of the electric vehicle mobile food court (EVMFC) model. This demonstration highlights the model's adeptness in harnessing solar energy for both vehicular propulsion and culinary operations. The study's unique approach, characterized by a substantial reduction in total energy consumption and an application-based energy management strategy, presents an innovative solution for mobile food services. The comprehensive recommendations offered by the authors serve as a guide for the widespread adoption of solar-powered EVMFCs, providing a transformative solution that is not only economically viable, but also environmentally conscious. This research signifies a pivotal step toward revolutionizing the mobile food industry, with the authors contributing valuable insights that bridge the gap between sustainability, efficiency, and gastronomic innovation. Each Archetype (actual + projected) during 2013–2032 for EVMFCS, DVMFC NIC, DVMFCG and GVMFCG. [ABSTRACT FROM AUTHOR]

Unplanned islanding of micro-grids is a significant barrier to supplying continuous power to key customers. The identification of the islanding moments must be rapid to enable the distributed generators (DG) to perform control measures in the shortest possible period. Micro phasor measuring units (µ-PMU) are gaining popularity in distribution systems and micro grids as a result of their ability to produce high-quality data at a high speed. These µ-PMUs can be utilized to detect islands. However, the µ-PMU relies heavily on the communication system for transmission of data, which is vulnerable to cyberattacks. In consideration of the previous technique, this research provides a smart island detection application with µ-PMU having lowered cyberattack probabilities. This representation is equipped with a µ-PMU implemented on the relevant DG's bus. The voltage data acquired from these µ-PMUs are processed using the sequence transformation in order to simulate the sequence component angle. The angular sum of the negative and positive sequence components is evaluated and the maximum value is deployed for detection of islanding. MATLAB/Simulink tests the proposed approach through an IEEE-34 node distribution network. Multiple simulations demonstrate the robustness of the technique. [ABSTRACT FROM AUTHOR]

The Distributed power flow controller can be considered as advance power flow controller which is combination of series and shunt compensator without DC link. In this paper Space vector Pulse width Modulation employs in Distributed power flow Controller for Harmonics Reduction and power quality improvement. A new technique SVPWM adopted which reduces the harmonics and the same time improves power quality and increase transient stability. In this paper a new technique of Multi objective Grey wolf algorithm used to optimize the controller parameter of DPFC. For the design of PI controller GWO algorithm can be used for better optimistic performance of DPFC. As a result of that power quality and voltage profile improves drastically and the same time harmonics also reduced remarkable level of 4.62% of Voltage THD and 1.8% of current THD. The simulation result and hardware model Prove the feasibility of proposed Configuration. [ABSTRACT FROM AUTHOR]

In this study, analysis of a high-efficiency grid-connected pump hydro energy storage (PHES) system that uses a bidirectional brushless DC (BLDC) machine is presented. The proposed layout is substantially less complicated since it uses an electronic power conditioning system to make all necessary modifications before connecting to the power grid, which removes the need for any mechanical components. This allows for the power plant's reliability to be improved while simultaneously reducing costs. An exhaustive model of the PHES system is created, and a two-tiered synchronous reference control technique for a grid side converter and a simple PI controller for the machine side converter is developed. Hardware data from a compact experimental setup are used to analyse the efficacy of the proposed PHES system. [ABSTRACT FROM AUTHOR]

Structural elements undergo multiple levels of damage at various locations due to environments and critical loading conditions. The level of damage and its location can be predicted using acoustic emission (AE) waveforms that are captured from the generation of inherent microcracks. Existing AE methods are reliant on the feature selection of the captured waveforms and may be subjective in nature. To automate this process, this paper proposes a deep-learning model to predict the damage severity and its expected location using AE waveforms. The model is based on a densely connected convolutional neural network (CNN) that offers superior feature extraction and minimal training data requirements. Time-domain AE waveforms are used as inputs of the proposed model to automate the process of predicting the severity of damage and identifying the expected location of the damage in structural elements. The proposed approach is validated using AE data collected from a concrete beam and a wooden beam and plate. The results show the capability of the proposed method for predicting the level of damage with an accuracy range of 92-95% and identifying the approximate location of damage with 90-100% accuracy. Thus, the proposed method serves as a robust technique for damage severity prediction and localization in civil structures. [ABSTRACT FROM AUTHOR]

In the present manuscript, we report the synthesis of Zn-BDC MOF using a modified solvothermal method. As synthesized Zn-BDC MOF is exposed to gamma (γ) radiation doses, the dose exposure is between 0 and 50 kGy. It is observed that γ radiations are probably absorbed by zinc metal, and due to adsorption of γ the structure of the MOF is not changing, which suggests that the MOF structure regains its structural stability at higher γ radiation doses. Further, for the first time, we reported that the stability of Zn-BDC MOF is up to 35 kGy, it has been observed that, there is an irradiation effect on the higher porosity of MOF. The present findings strongly suggest the radiation-sensitive nature of Zn-BDC MOF. [ABSTRACT FROM AUTHOR]

In this paper, we develop a method of analyzing long transient dynamics in a class of predator–prey models with two species of predators competing explicitly for their common prey, where the prey evolves on a faster timescale than the predators. In a parameter regime near a singular zero-Hopf bifurcation of the coexistence equilibrium state, we assume that the system under study exhibits bistability between a periodic attractor that bifurcates from the singular Hopf point and another attractor, which could be a periodic attractor or a point attractor, such that the invariant manifolds of the coexistence equilibrium point play central roles in organizing the dynamics. To find whether a solution that starts in a vicinity of the coexistence equilibrium approaches the periodic attractor or the other attractor, we reduce the equations to a suitable normal form, and examine the basin boundary near the singular Hopf point. A key component of our study includes an analysis of the long transient dynamics, characterized by their rapid oscillations with a slow variation in amplitude, by applying a moving average technique. We obtain a set of necessary and sufficient conditions on the initial values of a solution near the coexistence equilibrium to determine whether it lies in the basin of attraction of the periodic attractor. As a result of our analysis, we devise a method of identifying early warning signals, significantly in advance, of a future crisis that could lead to extinction of one of the predators. The analysis is applied to the predator–prey model considered in Sadhu (Discrete Contin Dyn Syst B 26:5251–5279, 2021) and we find that our theory is in good agreement with the numerical simulations carried out for this model. [ABSTRACT FROM AUTHOR]

Technology Enabled Learning (TEL) has a major impact on the learning adaptability of the learners. During the COVID-19 pandemic, there has been a drastic change in the learning methodology. The adaptability of learners from the various domains, levels and age has been a significant component of research in context to education. In this paper, the authors have proposed a machine learning and explainable AI based solution to identify critical learning parameters for students' adaptability level in online education. In this research the authors have employed various explainable AI (XAI) algorithms namely Local Interpretable Model-agnostic Explanations (LIME), SHapley Additive exPlanations (SHAP), FEature iMportance based eXplanable AI algorithm (FAMeX) for identifying the critical learning parameters to decide the adaptability level of a student. To test the efficacy of the solution, a dataset of students of several education levels of Bangladesh, collected from both online and offline surveys has been used. The results revealed are quite interesting, and counter intuitive. [ABSTRACT FROM AUTHOR]

This research paper presents a new approach to address power quality concerns in microgrids (MGs) by employing a superconducting fault current limiter (SFCL) and a fuzzy-based inverter. The integration of multiple power electronics converters in a microgrid typically increases total harmonic distortion (THD), which in turn results in power quality issues. Moreover, the intrinsic variability of solar and wind power sources gives rise to fluctuations in power generation, which consequently leads to power oscillations and voltage sag within microgrids that rely on renewable energy. This research paper introduces a technical approach to achieve power balance in renewable-based microgrids (MGs) by utilizing a fuzzy logic-controlled (FLC) pulse width modulation (PWM) inverter. The Microgrid (MG) consists of a hybrid photovoltaic (PV) system and a wind energy conversion system (WECS) that utilizes a permanent magnet synchronous generator (PMSG). The system employs an optimal torque-controlled maximum power point technique (MPPT) algorithm to optimize power output. The battery energy storage system (BESS) is employed to facilitate power provision during critical scenarios or to ensure a stable power output for fluctuating loads. The SFCL is utilized as a device for voltage compensation in cases of voltage sag incidents. The effectiveness of the suggested control strategy is assessed by performing a comparative analysis of total harmonic distortion (THD) in the load voltage, with and without the utilization of a SFCL. The results suggest that the incorporation of an FLC inverter-SFCL-BESS system effectively mitigates THD and voltage sag, according to the requirements set by the IEEE 519 standards. The research study is carried out by using the MATLAB/SIMULINK software environment. [ABSTRACT FROM AUTHOR]

In recent years, the growth spurt of medical imaging data has led to the development of various machine learning algorithms for various healthcare applications. The MedMNISTv2 dataset, a comprehensive benchmark for 2D biomedical image classification, encompasses diverse medical imaging modalities such as Fundus Camera, Breast Ultrasound, Colon Pathology, Blood Cell Microscope etc. Highly accurate classifications performed on these datasets is crucial for identification of various diseases and determining the course of treatment. This research paper presents a comprehensive analysis of four subsets within the MedMNISTv2 dataset: BloodMNIST, BreastMNIST, PathMNIST and RetinaMNIST. Each of these selected datasets is of diverse data modalities and comes with various sample sizes, and have been selected to analyze the efficiency of the model against diverse data modalities. The study explores the idea of assessing the Vision Transformer Model's ability to capture intricate patterns and features crucial for these medical image classification and thereby transcend the benchmark metrics substantially. The methodology includes pre-processing the input images which is followed by training the ViT-base-patch16-224 model on the mentioned datasets. The performance of the model is assessed using key metrices and by comparing the classification accuracies achieved with the benchmark accuracies. With the assistance of ViT, the new benchmarks achieved for BloodMNIST, BreastMNIST, PathMNIST and RetinaMNIST are 97.90%, 90.38%, 94.62% and 57%, respectively. The study highlights the promise of Vision transformer models in medical image analysis, preparing the way for their adoption and further exploration in healthcare applications, aiming to enhance diagnostic accuracy and assist medical professionals in clinical decision-making. [ABSTRACT FROM AUTHOR]

Global electricity demand is increasing with the rising population and rapid urbanization. Building Integrated photovoltaic (BIPV) system is a new method of renewable energy generation where solar photovoltaic (PV) modules are integrated into the building surfaces such as façade, shades, windows, roofs, and tiles. BIPV systems reduce the urban energy demand. Utilization of vertical surfaces makes the BIPV system a preferable choice where land scarcity affects the implementation of large PV systems. The economic viability depends on the maximum power generated by the BIPV array. In urban environments, the BIPV arrays experience severe partial shading conditions (PSCs). The PSCs cause mismatch losses, reducing the global maximum power of the BIPV array and efficiency. Fixed array configurations such as series-parallel (SP), total-cross-tied (TCT), triple-tied (TT), and quarter-tied (QT) are designed to solve this issue. The cross ties across the rows of the BIPV array improve the performance at the expense of more wiring. Researchers proposed various optimal array configurations with different shading patterns. This research attempts to generalize the design of the BIPV array configurations by considering the trade-off between wiring requirements and shading losses. The performance of SP, TT, QT, and TCT configurations under four different shading conditions is simulated with the proposed BIPV array design algorithm. A 9 × 8 BIPV array of 3.6 kW is considered. QT configuration reduces the wiring requirement by 10.45% compared to TCT and improves up to 8.43% maximum power than SP. The fill factor is improved to 48.49%, and the mismatch loss is limited to 34.10%. Therefore, QT and TCT are considered favorable configurations for BIPV array design. [ABSTRACT FROM AUTHOR]

This paper presents the MPPT algorithm for the proposed hybrid energy system, i.e., PV and wind systems, and is tested for grid-connected and standalone utilities. This study's major objective is to maximize the power output and enhance the power quality of the hybrid renewable energy technologies that have been created. In the literature, many research scholars have worked in the field of MPPT calculations for PV and wind systems, which increases the number of publications in the field of control calculations for hybrid power systems. This study pays attention to designing a controller based on MPPT for extracting maximum energy from wind and PV energy systems. The suggested algorithm is tested in grid and standalone modes, considering variable weather conditions. The proposed system is designed for 500 W solar and wind plants with the usual step-up converter and tested in MATLAB software to judge the efficacy of the suggested controller designed for MPPT. In this work, the suggested radial basis function network is implemented in wind and PV facilities via MPPT technique-based ANN control to obtain the maximum power by using fuzzy controllers. [ABSTRACT FROM AUTHOR]

Phenoxazines have sparked a lot of interest owing to their numerous applications in material science, organic light-emitting diodes, photoredox catalyst, dye-sensitized solar cells and chemotherapy. Among other things, they have antioxidant, antidiabetic, antimalarial, anti-alzheimer, antiviral, anti-inflammatory and antibiotic properties. Actinomycin D, which contains a phenoxazine moiety, functions both as an antibiotic and anticancer agent. Several research groups have worked on various structural modifications over the years in order to develop new phenoxazines with improved properties. Both phenothiazines and phenoxazines have gained prominence in medicine as pharmacological lead structures from their traditional uses as dyes and pigments. Organoelectronics and material sciences have recently found these compounds and their derivatives to be quite useful. Due to this, organic synthesis has been used in an unprecedented amount of exploratory alteration of the parent structures in an effort to create novel derivatives with enhanced biological and material capabilities. As a result, it is critical to conduct more frequent reviews of the work done in this area. Various stages of the synthetic transformation of phenoxazine scaffolds have been depicted in this article. This article aims to provide a state of the art review for the better understanding of the phenoxazine derivatives highlighting the progress and prospects of the same in medicinal and material applications. [ABSTRACT FROM AUTHOR]

FSPV (Floating Solar Photovoltaic) is an emerging type of solar energy that aims to help the environment. Since the technology is new, it is not easy to examine the long-term performance, effective control, and feasibility studies of FSPV facilities. The calculation of FSPV panel parameters is crucial in evaluating the actual performance, long-term operation, feasibility, and carbon-saving capacity of FSPV systems. The algorithm of war strategy optimization is used for the parameter estimation of the single-diode model of FSPV. Furthermore, FSPV decreases the environmental impacts of land-based PV (LBPV) plants, such as deforestation for land clearance to install panels. The WSO method outperforms war gradient-based optimization (GBO) and Harris Hawks Optimization (HHO) regarding effectiveness and accuracy. The WSO method is more effective and accurate than gradient-based optimization (GBO) and Harris Hawks optimization (HHO), with a standard deviation of 3.74387E–17 and a mean of 7.72985E–04. [ABSTRACT FROM AUTHOR]

In this article, we show that for a quasicompact scheme X and n > 0 , the n-th K-group K n (X) is a λ -module over a λ -ring K 0 (X) in the sense of Hesselholt. [ABSTRACT FROM AUTHOR]

The use of electrical vehicles is increasing day by day to favor sustainability and mitigate energy crisis and provide an eco-friendly environment for the society. Transport in rural areas mainly depends on battery operated three wheeled vehicles (BoTV). Such vehicles are most reliable source of conveyance in rural India, especially in rural Bengal, mainly due to their lower road space requirement, easy navigation through narrow roads. Convenience of movement on any type of road with door-to-door transport. However, the charging of the batteries used in a BoTV system is becoming an alarming issue these days. Lead acid batteries are used in BoTV system because of its lower cost, but the main drawback is its longer charging period. To address such issues, the authors have proposed a modified fast charging topology in this paper. A solar powered asymmetrical half bridge rectifier with DC–DC energy recovery cell has been designed to minimize the charging time. Besides that, frequent shut down of electricity is the major problem of rural Bengal which hampers the battery charging as well as reduces the daily income of the BoTV operator. By using PV based fast charging techniques this problem can be solved leading to better sustainability. Zero-voltage switching (ZVS) technique is implemented in asymmetrical half bridge (AHB) to increase the charger power density to enhance the quality of charging. ZVS technology of AHB with energy recovery cell makes the charging method faster. According to the analysis and the results, it has been found that the overall charging time of the battery has been reduced by around 2.5 h per day and the savings of a BoTV operator has increased by at least ₹2350 ($28.23) per month. [ABSTRACT FROM AUTHOR]

In this communication, a hybrid MIMO antenna (combination of graphene and ceramic) is designed and investigated in THz frequency range. Circular Polarization is achieved by feeding the cylindrical ceramic using moon shaped aperture with L-shaped Microstrip line. Mutual coupling between the antenna ports has been reduced to − 25 dB by using the concept of polarization diversity. Graphene material is used to introduce the re-configurability in the proposed radiator. For avoiding the difficulty of simulation of radiator at THz regime (very high simulation time), machine learning algorithms i.e. Artificial Neural Network (ANN), Random Forest and XGBoost are utilized to predict the reflection coefficient and axial ratio of designed antenna. The designed radiator works from 2.4 to 3.1 THz with 3-dB axial ratio from 2.6 to 3.0 THz. Good value of diversity parameters and stable radiation features make the designed radiator appropriate for various wireless applications in THz frequency band. [ABSTRACT FROM AUTHOR]

Concrete structures are subjected to various levels of damage during their life cycle due to exposure to different environmental and loading conditions. Hence, damage severity prediction and localization in concrete elements remain critical tasks to provide optimal maintenance in a timely manner, leading to reduced maintenance costs and avoiding any catastrophic failure that may cause serious loss and danger to the infrastructure owners. The Acoustic Emission (AE) technique is one of the powerful nondestructive testing (NDT) methodologies that can be used to predict the severity of damage and localize it in different systems. This paper proposes a damage identification approach by combining Multivariate Empirical Mode Decomposition (MEMD) and the Gaussian Mixture Model (GMM). Unlike existing methods that rely on a single AE measurement, MEMD is used to extract the key AE components that belong to cracks using AE data collected from multiple sensors. MEMD is an extended version of EMD that can analyze multichannel AE signals collected from different sensors. The statistical features (e.g., mean, root mean square, kurtosis, skewness, and crest factor) of AE components obtained from MEMD are then subsequently estimated. The selected features are used in the GMM model to predict the severity and qualitative location of the damage. The proposed method is validated using a suite of experimental studies and AE data collected from a full-scale concrete dam located in Ontario, Canada. The results show that the proposed approach can accurately predict the severity of damage and identify the potential location of damage and prove that the proposed method can be suitable for robust damage identification in concrete structures. [ABSTRACT FROM AUTHOR]

The incidence of pulmonary arterial hypertension (PAH) has significantly increased in the past few decades and therefore requires immediate attention. The applications of drug-loaded nano-systems have shown considerable improvements in controlling PAH compared to plain drugs. The purpose of this current investigation was to prepare and characterize sildenafil-encapsulated polyethylene glycol (PEGylated) liposomes for effective treatment of pulmonary arterial hypertension. Liposomes were prepared using thin film hydration method by varying the concentrations of sildenafil, Phospholipon 90-G, cholesterol, mPEG-DSPE2000 to optimize the formulation. The optimized liposomal formulation had mean hydrodynamic diameter, polydispersity index (PDI), zeta potential (ZP) and %EE of 155.3 ± 3.2 nm, 0.19 ± 0.1, − 42.2 ± 0.3 mV and 75.89 ± 0.5%. Transmission electron microscopy (TEM) revealed that liposomes were spherical and homogenously dispersed. FTIR (Fourier transform infrared spectroscopy) and DSC (Differential scanning calorimetry) confirmed that there was no covalent interaction between the drug and excipients. The release of sildenafil from PEGylated liposomes was found to be sustained compared to free drug. Ex vivo study in the rats showed improved vasorelaxant response for sildenafil loaded liposomes (132. 7 ± 0.7%) compared to pure sildenafil (108.2 ± 0.06%) and marketed Revatio® (113.2 ± 0.8%). In summary, sildenafil loaded PEGylated liposomes produced an impressive vasorelaxant response in rat aortic stip assay and require validation to bring the formulation available for clinical studies in the management of PAH. [ABSTRACT FROM AUTHOR]

Nanostructured integrated polymeric coatings have been transpired to preserve vegetables and fruits' quality attributes. Edible nanocoating packaging can significantly prolong the shelf life of fruits by preventing moisture loss and maintaining their freshness. This is because the coating acts as a barrier, preventing water vapor and gases from escaping or entering the fruit, which helps to maintain its firmness, color, and texture. These coatings facilitate barrier properties on the surface of fruits and vegetables and generate a conducive micro-environment by optimizing the concentration and obstructing the ripening process. A bio-nano hybrid based on guava extract intercalated nanoparticles were synthesized using a chemical reduction method for applications in fruit coating. The fabrication of resultant nanocomposites was confirmed by the shifts observed in vibrational frequencies and basal peaks observed by using an X-Ray diffraction pattern. The prepared nanohybrid further elucidates better thermal stability and their hydrotalcite-like structure examined by Field Emission Electron Spectroscopy displayed plate-like structure and homogeneous distribution of nanoparticles into the matrix. The CuO/guava extract nanocomposite has shown 37.79% of weight loss contrary to pristine extract which has 64.92% evaluated using thermogravimetric analysis. The edible nanocoating was developed using the dip-coating method on fresh papaya. To evaluate the efficacy of developed nanocoating, various attributes such as pH, acidity, sensory analysis, weight loss, and water activity coefficient for 18 days were investigated. In addition, the role of dietary sugar with the increase in the shelf life of nanoparticles coating was synchronized. The obtained results revealed that the shelf life of papaya increased with the application of copper nanohybrid coating which propounds its application in food preservation. Illustrating the development of ripened fruit-based biodegradable guava derived edible nanocoating to preserve the shelf life of papaya [ABSTRACT FROM AUTHOR]

Chlorophyll b is synthesized from chlorophyllide a, catalyzed by chlorophyllide a oxygenase (CAO). To examine whether reduced chlorophyll b content regulates chlorophyll (Chl) synthesis and photosynthesis, we raised CAO transgenic tobacco plants with antisense CAO expression, which had lower chlorophyll b content and, thus, higher Chl a/b ratio. Further, these plants had (i) lower chlorophyll b and total Chl content, whether they were grown under low or high light; (ii) decreased steady-state levels of chlorophyll biosynthetic intermediates, due, perhaps, to a feedback-controlled reduction in enzyme expressions/activities; (iii) reduced electron transport rates in their intact leaves, and reduced Photosystem (PS) I, PS II and whole chain electron transport activities in their isolated thylakoids; (iv) decreased carbon assimilation in plants grown under low or high light. We suggest that reduced synthesis of chlorophyll b by antisense expression of CAO, acting at the end of Chl biosynthesis pathway, downregulates the chlorophyll b biosynthesis, resulting in decreased Chl b, total chlorophylls and increased Chl a/b. We have previously shown that the controlled up-regulation of chlorophyll b biosynthesis and decreased Chl a/b ratio by over expression of CAO enhance the rates of electron transport and CO2 assimilation in tobacco. Conversely, our data, presented here, demonstrate that-antisense expression of CAO in tobacco, which decreases Chl b biosynthesis and increases Chl a/b ratio, leads to reduced photosynthetic electron transport and carbon assimilation rates, both under low and high light. We conclude that Chl b modulates photosynthesis; its controlled down regulation/ up regulation decreases/ increases light-harvesting, rates of electron transport, and carbon assimilation. [ABSTRACT FROM AUTHOR]

Protrusions at the leading-edge of a cell play an important role in sensing the extracellular cues during cellular spreading and motility. Recent studies provided indications that these protrusions wrap (coil) around the extracellular fibers. However, the physics of this coiling process, and the mechanisms that drive it, are not well understood. We present a combined theoretical and experimental study of the coiling of cellular protrusions on fibers of different geometry. Our theoretical model describes membrane protrusions that are produced by curved membrane proteins that recruit the protrusive forces of actin polymerization, and identifies the role of bending and adhesion energies in orienting the leading-edges of the protrusions along the azimuthal (coiling) direction. Our model predicts that the cell's leading-edge coils on fibers with circular cross-section (above some critical radius), but the coiling ceases for flattened fibers of highly elliptical cross-section. These predictions are verified by 3D visualization and quantitation of coiling on suspended fibers using Dual-View light-sheet microscopy (diSPIM). Overall, we provide a theoretical framework, supported by experiments, which explains the physical origin of the coiling phenomenon. The leading edges of cellular protrusions coil around extracellular fibers and other fibrous structures such as axons. Combining 3D imaging with theoretical models, the authors show that coiling occurs naturally on curved surfaces due to energy minimization. [ABSTRACT FROM AUTHOR]

The objective of the present research was intended to formulate multigrain premix powder which could be utilized for the development of nutritional rich products. The multigrain premix was prepared by blending the seeds of pumpkin, jackfruit, and mango with barley, pearl millet, finger millet, sorghum, and other ingredients such as cardamom, and sugar. Before optimizing the composition of premix flour, around 8 combinations of each flour and seed powders were made to obtain the preeminent quality premix with high nutritional value. The formulation of flour was optimized on the basis of sensory analysis done by using 9-hedonic scale. The formulated multigrain premix was analysed for its nutritional and sensorial characteristics. Multigrain premix resulted in protein content of 5.35 g, carbohydrate 80.25 g, fat 6.88 g, ash 3.87 g, dietary fibres 8.67 g, calcium 73.25 mg, and iron 2.94 mg per 100 g of the mixture and many more minerals were also estimated in the given premix. Total energy was noted as 404.32 kcal. The GC–MS analysis was also performed to identify the composition of fat in terms of their saturation. Moreover, the shelf life study of multigrain premix was carried out for a period of 45 days at a temperature and relative humidity of 25 °C and 91% respectively. The overall quality of the multigrain premix was accepted in term of overall acceptability. The optimized premix was also taken for its microbiological analysis, and sensorial quality attributes to understand the shelf life study of the product when stored for longer period of time. [ABSTRACT FROM AUTHOR]

The Floating Solar Photovoltaic System (FSPV) is emerging as a favorable technology to policymakers for economically harvesting renewable energy. The implementation of large-scale photovoltaic (PV) systems is often disrupted due to the unavailability of land. The FSPV systems, where the PV modules are floated in water bodies facilitate optimal utilization of water resources and land assets. The FSPV provides higher power output compared to land-based PV systems of the equal area because of improved energy conversion efficiency at a lower temperature. Another opportunity for the FSPV system is integration with hydropower stations, storage systems, and the electric grid. This paper explores the flood duration curve-based optimal sizing of the FSPV System with the objective of electrification of rural micro-grid. A comparison of energy output and module temperature rise has been made for the FSPV system and its equivalent land-based PV system of equal area. The system generates 18.08 GWh, which is 10.04% more than the land-based PV system. The DC Capacity factor is 17.2%. The Demand Supply Factor (DSF) for a particular day in winter, spring, summer, and monsoon is 37.55%, 41.7%, 45.9%, and 25% respectively. The results indicate that the FSPV system is a sustainable alternative to power renewable energy-based mini micro-grid and provide cost effective electricity to all. [ABSTRACT FROM AUTHOR]

A recently emerged sub-lineage of Omicron, BA.5, together with BA.4, caused a fifth wave of coronavirus disease (COVID-19) in South Africa and subsequently emerged as a predominant strain globally due to its high transmissibility. The lethality of BA.5 infection has not been studied in an acute hACE2 transgenic (hACE2.Tg) mouse model. Here, we investigated tissue-tropism and immuno-pathology induced by BA.5 infection in hACE2.Tg mice. Our data show that intranasal infection of BA.5 in hACE2.Tg mice resulted in attenuated pulmonary infection and pathology with diminished COVID-19-induced clinical and pathological manifestations. BA.5, similar to Omicron (B.1.1.529), infection led to attenuated production of inflammatory cytokines, anti-viral response and effector T cell response as compared to the ancestral strain of SARS-CoV-2, Wuhan-Hu-1. We show that mice recovered from B.1.1.529 infection showed robust protection against BA.5 infection associated with reduced lung viral load and pathology. Together, our data provide insights as to why BA.5 infection escapes previous SARS-CoV-2 exposure induced-T cell immunity but may result in milder immuno-pathology and alleviated chances of re-infectivity in Omicron-recovered individuals. Intranasal infection of SARS-CoV-2 BA.5 in an acute hACE2 transgenic (hACE2.Tg) mouse model provides insights into BA.5 infection pathology. [ABSTRACT FROM AUTHOR]

While the genetics of MS risk susceptibility are well-described, and recent progress has been made on the genetics of disease severity, the genetics of disease progression remain elusive. We therefore investigated the genetic determinants of MS progression on longitudinal brain MRI: change in brain volume (BV) and change in T2 lesion volume (T2LV), reflecting progressive tissue loss and increasing disease burden, respectively. We performed genome-wide association studies of change in BV (N = 3401) and change in T2LV (N = 3513) across six randomized clinical trials from Biogen and Roche/Genentech: ADVANCE, ASCEND, DECIDE, OPERA I & II, and ORATORIO. Analyses were adjusted for randomized treatment arm, age, sex, and ancestry. Results were pooled in a meta-analysis, and were evaluated for enrichment of MS risk variants. Variant colocalization and cell-specific expression analyses were performed using published cohorts. The strongest peaks were in PTPRD (rs77321193-C/A, p = 3.9 × 10–7) for BV change, and NEDD4L (rs11398377-GC/G, p = 9.3 × 10–8) for T2LV change. Evidence of colocalization was observed for NEDD4L, and both genes showed increased expression in neuronal and/or glial populations. No association between MS risk variants and MRI outcomes was observed. In this unique, precompetitive industry partnership, we report putative regions of interest in the neurodevelopmental gene PTPRD, and the ubiquitin ligase gene NEDD4L. These findings are distinct from known MS risk genetics, indicating an added role for genetic progression analyses and informing drug discovery. [ABSTRACT FROM AUTHOR]

SARS-CoV-2 infection is known for causing broncho-alveolar inflammation. Interleukin 9 (IL-9) induces airway inflammation and bronchial hyper responsiveness in respiratory viral illnesses and allergic inflammation, however, IL-9 has not been assigned a pathologic role in COVID-19. Here we show, in a K18-hACE2 transgenic (ACE2.Tg) mouse model, that IL-9 contributes to and exacerbates viral spread and airway inflammation caused by SARS-CoV-2 infection. ACE2.Tg mice with CD4+ T cell-specific deficiency of the transcription factor Forkhead Box Protein O1 (Foxo1) produce significantly less IL-9 upon SARS-CoV-2 infection than the wild type controls and they are resistant to the severe inflammatory disease that characterises the control mice. Exogenous IL-9 increases airway inflammation in Foxo1-deficient mice, while IL-9 blockade reduces and suppresses airway inflammation in SARS-CoV-2 infection, providing further evidence for a Foxo1-Il-9 mediated Th cell-specific pathway playing a role in COVID-19. Collectively, our study provides mechanistic insight into an important inflammatory pathway in SARS-CoV-2 infection, and thus represents proof of principle for the development of host-directed therapeutics to mitigate disease severity. Interleukin 9 (IL-9) is a cytokine that plays causative role in airway inflammation of both infectious and allergic origin. Here authors show in a mouse model of SARS-CoV-2 infection that IL-9, predominantly produced by helper T cells, plays a critical pathogenic role in COVID-19 via an inflammatory pathway involving the transcription factor Foxo1. [ABSTRACT FROM AUTHOR]