18 research outputs found

    Adaptive-SMC Based Output Impedance Shaping in DC Microgrids Affected by Inverter Loads

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    Preliminary study on antiulcer effect of agomelatine and its potentiation with pyridoxine

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    Background: Agomelatine is a synthetic analogue of melatonin and a potent agonist of melatonin receptors. Agomelatine has Hepatoprotective as well as antioxidant activity. The aim of study was to evaluate the antiulcer activity of Agomelatine and its potentiation through the pyridoxine on ethanol induced gastric ulcer in rats.Methods: Thirty number of rats were divided in to five groups contro, standard, Agomelatine low dose, Agomelatine high dose and Agomelatine with Pyridoxine groups. Ethanol was used to induced gastric ulcer in rats. ulcer index and also the other biochemical parameters like free Acidity, total Acidity, gastric pH, volume of gastric juice was determined. Statistically analysis was done by ANOVA P value less than 0.05 was considered Statistically significant.Results: In the present study, an attempt has been made to investigate the gastric antisecretory, antiulcer and cytoprotective properties of agomelatine. The results are statistically significant by ANOVA test. Ranitidine showed a statistically significant decrease in the volume of gastric juice by free acidity and total acidity. when compared to control. Agomelatine shows a showed similar response to the volume of gastric juice. A significant difference in pH was observed between the agomelatine-treated, agomelatine with pyridoxine treated group and the control groups.Conclusions: Pretreated rats with Agomelatine (40mg/kg) showed protective effect against ethanol induce gastric ulcer. Agomelatine (40mg/kg) showed the ameliorative effect with Pyridoxine (0.3mg/kg), on gastric ulcer

    Advance Approach for Detection of DNS Tunneling Attack from Network Packets Using Deep Learning Algorithms

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    Domain Name System (DNS) is a protocol for converting numeric IP addresses of websites into a human-readable form. With the development of technology, to transfer information, a method like DNS tunneling is used which includes data encryption into DNS queries. The ability of the DNS tunneling method of transferring data attracts attackers to establish bidirectional communication with machines infected with malwares. This can lead to sending instructions in an obfuscated way or can lead to data exfiltration. Since firewalls and intrusion detection systems detect only specific types of tunneling, were as the Machine Learning Algorithms can analyze and predict based on previous data provided to it, it is being adopted by researchers to detect and predict the occurrence of DNS Tunneling. The identification of anomalies in Network packets can be done by using Natural Language Processing (NLP) technique. The experimental test accuracy showed that the feature extraction method in NLP for detecting DNS tunneling in network packets was found to be 98.42% on the generated Dataset. This paper makes a comparative study of 1 Dimensional Convolution Neural Network (1-D CNN), Simple Recurrent Neural Network (Simple RNN), Long Short-Term Memory (LSTM) algorithm, Gated Recurrent Unit (GRU) algorithm for detecting DNS Tunneling over the generated dataset. To detect this threat of DNS tunneling attack, good quality of the dataset is required. This paper also proposes the generation of a good quality dataset that contains network packets, by the recreation of DNS Tunneling attack using tool dnscat2

    Role of imaging in the management of thyroglossal duct cyst carcinomas (TGC-TIRADS): a single centre retrospective study over 16 years

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    IntroductionThyroglossal duct cyst (TGDC) is the most frequently encountered developmental anomaly in thyroid genesis with a reported incidence of 7% in the adult population. The cyst is known to develop anywhere along the pathway of thyroid descent but is more frequently seen in the infrahyoid neck in the midline. The incidence of malignancy in a TGDC is approximately 1%; a majority of these are papillary carcinomas. This study was conducted at a single tertiary care centre which spanned over a decade which adds practice changing evidence-based knowledge to existing literature on this rare entity. A comprehensive study which conclusively establishes the imaging features predictive of malignancy in TGDC carcinomas (TGDCa), the protocol for optimal management, clinical outcome and long-term survival of these patients is not available. Although TGDC carcinoma is thought to have an excellent prognosis, there is not enough data available on the long-term survival of these patients. The aim of this study was to identify whether neck ultrasound (US) can serve as an accurate imaging tool for the preoperative diagnosis of TGDC carcinomas.MethodsWe accessed the electronic medical records of 86 patients with TGDC between January 2005 to December 2021. Of these, 22 patients were detected with TGDC papillary carcinoma on histopathologic examination. Relevant imaging, treatment and follow up information for all cases of TGDC carcinoma were retrospectively reviewed. We compared US characteristics predictive of malignancy across outcomes groups; malignant vs benign using the Chi-square test. Based on the results, a TGC-TIRADS classification was proposed with calculation of the percentage likelihood of malignancy for each category.ResultsCompared to benign TGDCs, malignant TGDCs were more likely to present with following US characteristics: irregular or lobulated margins (90.40 vs. 38.10%), solid-cystic composition (61.90 vs. 17.07%), internal vascularity (47.62 vs. 4.88 %), internal calcification (76.19 vs. 7.32 %) (each p value < 0.005). Calcifications and internal vascularity were the most specific while irregular/lobulated margins were the most sensitive feature for malignancy. AUC under the ROC curve was 0.88. Allpatients were operated and were disease free at the end of 5 years or till the recent follow up.DiscussionUS is the imaging modality of choice for pre-operative diagnosis of TGDC carcinoma. Thepre-operative diagnosis and risk stratification of thyroglossal lesions will be aided by the application of the proposed TGC-TIRADS classification, for which the percentage likelihood of malignancy correlated well with the results in our study. Sistrunk procedure is adequate for isolated TGDC carcinoma; suspicious neck nodes on imaging also necessitates selective nodal dissection. Papillary carcinomas have an excellent prognosis with low incidence of disease recurrence

    Grid-Connected Converters: A Brief Survey of Topologies, Output Filters, Current Control, and Weak Grids Operation

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    Grid-connected converters (GCCs) are used extensively for the integration of DC power sources with AC power sources. However, since it is a complex topic, there are many possibilities for regulating grid-injected currents, as well as different modulation techniques for generating full-bridge PWM voltages. The control techniques are directly related to the type of output filter, as well as to the topology of the converter, since a complex plant can require more sophisticated controllers to keep the system stable, and with good regulation performance. Furthermore, a discussion of the applicability of these converters in weak and very weak grids with high inductance content has recently been growing, which adds a greater degree of complexity to the control structure of the converter. In this brief overview are outlined some topics about topologies, output filters, and control, focusing on the current regulation of grid-connected converters. In addition, a discussion of the main challenges and critical areas in operating on weak and very weak grids is also presented

    Control Methodologies to Mitigate and Regulate Second-Order Ripples in DC–AC Conversions and Microgrids: A Brief Review

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    Second-order ripples occur in the voltage and current during any DC–AC power conversion. These conversions occur in the voltage source inverters (VSIs), current source inverters (CSIs), and various single-stage inverters (SSIs) topologies. The second-order ripples lead to oscillating source node currents and DC bus voltages when there is an interconnection between the AC and DC microgrids or when an AC load is connected to the DC bus of the microgrid. Second-order ripples have various detrimental effects on the sources and the battery storage. In the storage battery, they lead to the depletion of electrodes. They also lead to stress in the converter or inverter components. This may lead to the failure of a component and hence affect the reliability of the system. Furthermore, the second-order ripple currents (SRCs) lead to ripple torque in wind turbines and lead to mechanical stress. SRCs cause a rise in the temperature of photovoltaic panels. An increase in the temperature of PV panels leads to a reduction in the power generated. Furthermore, the second-order voltage and current oscillations lead to a varying maximum power point in PV panels. Hence, the maximum power may not be extracted from it. To mitigate SRCs, oversizing of the components is needed. To improve the lifespan of the sources, storage, and converter components, the SRCs must be mitigated or kept within the desired limits. In the literature, different methodologies have been proposed to mitigate and regulate these second-order ripple components. This manuscript presents a comprehensive review of different effects of second-order ripples on different sources and the methodologies adopted to mitigate the ripples. Different active power decoupling methodologies, virtual impedance-based methodologies, pulse width modulation-based signal injection methodologies, and control methods adopted in distributed power generation methods for DC microgrids have been presented. The application of ripple control methods spans from single converters such as SSIs and VSIs to a network of interconnected converters. Furthermore, different challenges in the field of virtual impedance control and ripple mitigation in distributed power generation environments are discussed. This paper brings a review regarding control methodologies to mitigate and regulate second-order ripples in DC–AC conversions and microgrids

    A novel study on the effect lemon peel oil as a fuel in CRDI engine at various injection strategies

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    Lemon peel oil is one of the renewable and biodegradable biofuel for diesel engine applications due to its low viscous nature. This study aims to observe the performance and emission characteristics of a common rail direct injection diesel engine at various fuel injection strategies under different loading conditions. An open type electronic control unit is used to control the fuel injection timing, injection rate and split injection at various injection pressures. In this research work, 20% lemon peel oil-diesel blend (by volume) is injected at a pressure of 400 bar, 500 bar and 600 bar with 10% pilot injection by volume and the results are compared with diesel fuel at same injection conditions. Further, pilot injection quantity of lemon peel oil blend is varied by 20% and 30% of total volume of fuel injected at 600 bar injection pressure. Finally, the experimental work is carried out in common rail direct injection diesel engine fuelled with lemon peel oil blend under 10% cooled exhaust gas recirculation condition. The study reveals that the brake thermal efficiency is improved with increase in injection pressures and pilot injection rates. However, this trend has been changed during 10% EGR addition for lemon peel oil blend operation at 30% pilot injection rate. The combustion characteristics are improved for lemon peel oil blend for 600 bar injection pressure with 20% and 30% pilot injection rates compared to 10% pilot injection rate. The higher pilot injection rate has shown significant reductions in carbon monoxide, hydrocarbon and smoke emissions. However, the emission results are reversed with 10% exhaust gas recirculation at 600 bar injection pressure of lemon peel oil blend. There is a significant reduction in NOx emission for low injection pressure of lemon peel oil blend at 10% pilot injection rate

    An RMRAC With Deep Symbolic Optimization for DC–AC Converters Under Less-Inertia Power Grids

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    This paper presents a novel approach for grid-injected current control of DC-AC converters using a robust model reference adaptive controller (RMRAC) with deep symbolic optimization (DSO). Grid voltages are known to be time-varying and can contain distortions, unbalances, and harmonics, which can lead to poor tracking and high total harmonic distortion (THD). The proposed adaptive control structure addresses this issue by enabling or disabling harmonics compensation blocks based on the grid voltage’s characteristics. The DSO framework is implemented to generate an equivalent mathematical expression of the grid voltages, which is then incorporated into the RMRAC-based controller. The controller is then able to reconfigure itself to adequately compensate for high harmonics present in the grid, reducing computational complexity and improving performance. A controller-hardware-in-the-loop (C-HIL) environment with a Typhoon HIL 604 and a TSM320F28335 DSP is implemented to demonstrate that the proposed RMRAC-based structure with DSO outperforms both the same adaptive structure without DSO and a superior RMRAC-based controller. The proposed approach has potential applications in less-inertia power grids, where efficient and accurate control of grid-connected converters is crucial

    Progress of children with severe acute malnutrition in the malnutrition treatment centre rehabilitation program: evidence from a prospective study in Jharkhand, India

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    Abstract Background In Jharkhand, Malnutrition Treatment Centres (MTCs) have been established to provide care to children with severe acute malnutrition (SAM). The study examined the effects of facility- and community based care provided as part the MTC program on children with severe acute malnutrition. Method A cohort of 150 children were enrolled and interviewed by trained investigators at admission, discharge, and after two months on the completion of the community-based phase of the MTC program. Trained investigators collected data on diet, morbidity, anthropometry, and utilization of health and nutrition services. Results We found no deaths among children attending the MTC program. Recovery was poor, and the majority of children demonstrated poor weight gain, with severe wasting and underweight reported in 52 and 83% of the children respectively at the completion of the community-based phase of the MTC program. The average weight gain in the MTC facility (3.8 ± 5.9 g/kg body weight/d) and after discharge (0.6 ± 2.1 g/kg body weight/d) was below recommended standards. 67% of the children consumed food that met less than 50% of the recommended energy and protein requirement. Children experienced high number of illness episodes after discharge: 68% children had coughs and cold, 40% had fever and 35% had diarrhoea. Multiple morbidities were common: 50% of children had two or more episodes of illness. Caregiver’s exposure to MTC’s health and nutrition education sessions and meetings with frontline workers did not improve feeding practices at home. The take-home ration amount distributed to children through the supplementary food program was inadequate to achieve growth benefits. Conclusions Recovery of children during and after the MTC program was suboptimal. This highlights the need for additional support to strengthen MTC program so that effective care to children can be provided

    Biapenem, a Carbapenem Antibiotic, Elicits Mycobacteria Specific Immune Responses and Reduces the Recurrence of Tuberculosis

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    ABSTRACT Tuberculosis (TB) still tops the list of global health burdens even after COVID-19. However, it will sooner transcend the current pandemic due to the prevailing risk of reactivation of latent TB in immunocompromised individuals. The indiscriminate misuse and overuse of antibiotics have resulted in the emergence of deadly drug-resistant variants of Mycobacterium tuberculosis (M.tb). This study aims to characterize the functionality of the carbapenem antibiotic-Biapenem (BPM) in generating long-lasting immunity against TB. BPM treatment significantly boosted the activation status of the innate immune arm-macrophages by augmenting p38 signaling. Macrophages further primed and activated the adaptive immune cells CD4+ and CD8+ T-cells in the lung and spleen of the infected mice model. Furthermore, BPM treatment significantly amplified the polarization of T lymphocytes toward inflammatory subsets, such as Th1 and Th17. The treatment also helped generate a long-lived central memory T-cell subset. The generation of central memory T lymphocyte subset upon BPM treatment in the murine model led to a significant curtailing in the recurrence of TB due to reactivation and reinfection. These results suggest the potentiality of BPM as a potent adjunct immunomodulator to improve host defense against M.tb by enriching long-term protective memory cells. IMPORTANCE Tuberculosis (TB) caused by Mycobacterium tuberculosis (M.tb) tops the list of infectious killers around the globe. The emergence of drug-resistant variants of M.tb has been a major hindrance toward realizing the “END TB” goal. Drug resistance has amplified the global burden toward the quest for novel drug molecules targeting M.tb. Host-directed therapy (HDT) offers a lucrative alternative to tackle emerging drug resistance and disease relapse by strengthening the host’s immunity. Through our present study, we have tried to characterize the functionality of the carbapenem antibiotic-Biapenem (BPM). BPM treatment significantly augmented long-lasting immunity against TB by boosting the innate and adaptive immune arms. The generation of long-lived central memory T lymphocyte subset significantly improved the disease outcome and provided sterilizing immunity in the murine model of TB. The present investigation's encouraging results have helped us depict BPM as a potent adjunct immunomodulator for treating TB
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