533 research outputs found

    Modelling and performance analysis of improved incremental conductance MPPT technique for water pumping system

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    Utilization of Solar Photo Voltaic Cell (SPVC) has significantly increased in residential, commercial, and industrial due to freely available. From the power-voltage (P–V) curve, fluctuation has been revealed over an hour because of varying irradiance, and temperature of sun rays. Maximum power point tracking (MPPT) has been essential to track power and maximize the output from SPVC constantly. In this study, a novel Improved Incremental Conductance (IIC) MPPT technique is proposed, and integrated with a boost converter to take out the maximum power from SPVC. The output power has been provided to a brushless DC motor (BLDC). Pulse Width Modulation (PWM) commutation system has been employed to control the BLDC motor through the 3-level bridge converter. The proposed study has been implemented in MATLAB/Simulink. The complete analysis has been examined at different irradiation conditions. Power consumption, loss, and efficiency have been estimated. Simulation results have been compared with conventional incremental conductance (IC). The proposed IIC MPPT has an improved 5% of tracking efficiency than conventional MPPT techniques. The results show that the effectiveness of the proposed IIC technique has attained a steady state in varying irradiation levels. In spite of the low irradiation level of 250 W/m2, the system remains effective

    Integrating Machine Learning Algorithms for Predicting Solar Power Generation

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    In recent years, there has been a growing interest in using artificial intelligence (AI) techniques to predict solar power generation. One such technique is the use of an artificial neural network (ANN) with a genetic algorithm (GA) to optimize its parameters. This approach involves training an ANN to predict solar power generation based on historical data and using a GA to optimize the ANN’s architecture and activation function. The GA searches for the best combination of hidden layers and activation functions to minimize the error between the predicted and actual solar power generation. This paper presents an algorithm for implementing an ANN-GA for predicting solar power generation. The algorithm involves preprocessing the data, defining the ANN architecture, defining the fitness function, and implementing the GA to optimize the ANN’s parameters. The results of this approach can be useful for predicting future solar power generation and optimizing the performance of solar power systems

    A combination of metformin and epigallocatechin gallate potentiates glioma chemotherapy in vivo

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    Glioma is the most devastating high-grade tumor of the central nervous system, with dismal prognosis. Existing treatment modality does not provide substantial benefit to patients and demands novel strategies. One of the first-line treatments for glioma, temozolomide, provides marginal benefit to glioma patients. Repurposing of existing non-cancer drugs to treat oncology patients is gaining momentum in recent years. In this study, we investigated the therapeutic benefits of combining three repurposed drugs, namely, metformin (anti-diabetic) and epigallocatechin gallate (green tea-derived antioxidant) together with temozolomide in a glioma-induced xenograft rat model. Our triple-drug combination therapy significantly inhibited tumor growth in vivo and increased the survival rate (50%) of rats when compared with individual or dual treatments. Molecular and cellular analyses revealed that our triple-drug cocktail treatment inhibited glioma tumor growth in rat model through ROS-mediated inactivation of PI3K/AKT/mTOR pathway, arrest of the cell cycle at G1 phase and induction of molecular mechanisms of caspases-dependent apoptosis.In addition, the docking analysis and quantum mechanics studies performed here hypothesize that the effect of triple-drug combination could have been attributed by their difference in molecular interactions, that maybe due to varying electrostatic potential. Thus, repurposing metformin and epigallocatechin gallate and concurrent administration with temozolomide would serve as a prospective therapy in glioma patients

    Behaviour of Aluminium Undergoing Cold Extrusion: A Review

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    Aluminium is widely used metal. Aluminium alloy is used in mechanical industries for bolts, nuts, rivets and many other things. Aluminium is cold extruded because of its benefits like very less oxidation, high strength because of working in cold temperatures, very closer tolerances, surface finish is good, and higher speeds of extrusion when specimen is intended to hot shortness. The main objective of this research is to perform cold extrusion on aluminium rods by considering different parameters, to obtain a superior product. Different parameters like the die angle, oils and ram speeds are considered for performing this experiment. The extruded products are compared and various tests like tensile, hardness, surface roughness are performed on the extruded products and the results are compared to decide better parameters for obtaining superior product. This paper is a summary of scholarly sources on cold extrusion and aluminium alloys. This research provides a clear view of the present knowledge and helps identify relevant*theories, methods, and gaps in existing research. It also describes the results of the research, and the conclusions are drawn from them

    A simple robust mechanism of PV-supported dynamic voltage restorer using interval type-2 fuzzy logic controller

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    Power electronic devices and variable speed drives solve a power quality issue. To increase the power quality, the distribution side must be compensated by concurrently infusing actual and reactive power. A cost-effective method of preventing voltage sag and swell in power electronic loads is the use of a dynamic voltage restorer. To enhance the power quality for end users, a DC-link component will be combined with the DVR. Ratings for DC-Link elements and inverters are more challenging when constructing a DVR. To simplify things, the Distributed Energy Source (DES) is combined with the DC-Link and the Inverter. The PV-integrated DVR is under the supervision of the Interval type-2 Fuzzy Logic Controller using Synchronous Reference Frame Theory. Reactive power is injected and absorbed under defective situations using a variety of injection techniques with various controllers. The suggested controller enhances power quality and provides exact results under different fault scenarios. Matlab is used to compare the proposed IT2-FLC to a type-1 fuzzy-adjusted PI controller and a traditional mathematical PI controller. The results of the simulations showed that the suggested methodology provided a better outcome on the Distribution side. To validate the simulation results, a scaled-down rating prototype model is created

    Biosynthesis of Silver Nanoparticles Using <i>Azadirachta indica</i> and Their Antioxidant and Anticancer Effects in Cell Lines

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    In the present study, silver nanoparticles (Ag-NPs) were synthesized using Azadirachta indica extract and evaluated for their in vitro antioxidant activity and cytotoxicity efficacy against MCF-7 and HeLa cells. The silver nanoparticles (Ag-NPs) were formed within 40 min and after preliminary confirmation by UV-visible spectroscopy (peak observed at 375 nm), they were characterized using a transmission electron microscope (TEM) and dynamic light scattering (DLS). The TEM images showed the spherical shape of the biosynthesized Ag-NPs with particle sizes in the range of 10 to 60 nm, and compositional analysis was carried out. The cytotoxicity and antioxidant activity of various concentrations of biosynthesized silver nanoparticles, Azadirachta indica extract, and a standard ranging from 0.2 to 1.0 mg/mL were evaluated. The 2,2-Diphenyl-1-picrylhydrazyl (DPPH) activity of the biosynthesized Ag-NPs and aqueous leaf extract increased in a dose-dependent manner, with average IC50 values of the biosynthesized Ag-NPs, aqueous leaf extract, and ascorbic acid (standard) of 0.70 ± 0.07, 1.63 ± 0.09, and 0.25 ± 0.09 mg/mL, respectively. Furthermore, higher cytotoxicity was exhibited in both the MCF-7 and HeLa cell lines in a dose-dependent manner. The average IC50 values of the biosynthesized Ag-NPs, aqueous leaf extract, and cisplatin (standard) were 0.90 ± 0.07, 1.85 ± 0.01, and 0.56 ± 0.08 mg/mL, respectively, with MCF-7 cell lines and 0.85 ± 0.01, 1.76 ± 0.08, 0.45 ± 0.10 mg/mL, respectively, with HeLa cell lines. Hence, this study resulted in an efficient green reductant for producing silver nanoparticles that possess cytotoxicity and antioxidant activity against MCF-7 and HeLa cells

    Validation and utility of ARDS subphenotypes identified by machine-learning models using clinical data: an observational, multicohort, retrospective analysis

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    International audienceTwo acute respiratory distress syndrome (ARDS) subphenotypes (hyperinflammatory and hypoinflammatory) with distinct clinical and biological features and differential treatment responses have been identified using latent class analysis (LCA) in seven individual cohorts. To facilitate bedside identification of subphenotypes, clinical classifier models using readily available clinical variables have been described in four randomised controlled trials. We aimed to assess the performance of these models in observational cohorts of ARDS. Methods: In this observational, multicohort, retrospective study, we validated two machine-learning clinical classifier models for assigning ARDS subphenotypes in two observational cohorts of patients with ARDS: Early Assessment of Renal and Lung Injury (EARLI; n=335) and Validating Acute Lung Injury Markers for Diagnosis (VALID; n=452), with LCA-derived subphenotypes as the gold standard. The primary model comprised only vital signs and laboratory variables, and the secondary model comprised all predictors in the primary model, with the addition of ventilatory variables and demographics. Model performance was assessed by calculating the area under the receiver operating characteristic curve (AUC) and calibration plots, and assigning subphenotypes using a probability cutoff value of 0·5 to determine sensitivity, specificity, and accuracy of the assignments. We also assessed the performance of the primary model in EARLI using data automatically extracted from an electronic health record (EHR; EHR-derived EARLI cohort). In Large Observational Study to Understand the Global Impact of Severe Acute Respiratory Failure (LUNG SAFE; n=2813), a multinational, observational ARDS cohort, we applied a custom classifier model (with fewer variables than the primary model) to determine the prognostic value of the subphenotypes and tested their interaction with the positive end-expiratory pressure (PEEP) strategy, with 90-day mortality as the dependent variable. Findings: The primary clinical classifier model had an area under receiver operating characteristic curve (AUC) of 0·92 (95% CI 0·90–0·95) in EARLI and 0·88 (0·84–0·91) in VALID. Performance of the primary model was similar when using exclusively EHR-derived predictors compared with manually curated predictors (AUC=0·88 [95% CI 0·81–0·94] vs 0·92 [0·88–0·97]). In LUNG SAFE, 90-day mortality was higher in patients assigned the hyperinflammatory subphenotype than in those with the hypoinflammatory phenotype (414 [57%] of 725 vs 694 [33%] of 2088; p<0·0001). There was a significant treatment interaction with PEEP strategy and ARDS subphenotype (p=0·041), with lower 90-day mortality in the high PEEP group of patients with the hyperinflammatory subphenotype (hyperinflammatory subphenotype: 169 [54%] of 313 patients in the high PEEP group vs 127 [62%] of 205 patients in the low PEEP group; hypoinflammatory subphenotype: 231 [34%] of 675 patients in the high PEEP group vs 233 [32%] of 734 patients in the low PEEP group). Interpretation: Classifier models using clinical variables alone can accurately assign ARDS subphenotypes in observational cohorts. Application of these models can provide valuable prognostic information and could inform management strategies for personalised treatment, including application of PEEP, once prospectively validated. Funding: US National Institutes of Health and European Society of Intensive Care Medicine

    Phylogenetic classification of the world's tropical forests

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    Knowledge about the biogeographic affinities of the world’s tropical forests helps to better understand regional differences in forest structure, diversity, composition, and dynamics. Such understanding will enable anticipation of region-specific responses to global environmental change. Modern phylogenies, in combination with broad coverage of species inventory data, now allow for global biogeographic analyses that take species evolutionary distance into account. Here we present a classification of the world’s tropical forests based on their phylogenetic similarity. We identify five principal floristic regions and their floristic relationships: (i) Indo-Pacific, (ii) Subtropical, (iii) African, (iv) American, and (v) Dry forests. Our results do not support the traditional neo- versus paleotropical forest division but instead separate the combined American and African forests from their Indo-Pacific counterparts. We also find indications for the existence of a global dry forest region, with representatives in America, Africa, Madagascar, and India. Additionally, a northern-hemisphere Subtropical forest region was identified with representatives in Asia and America, providing support for a link between Asian and American northern-hemisphere forests.</p

    Mechanical ventilation in patients with cardiogenic pulmonary edema: a sub-analysis of the LUNG SAFE study

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    Abstract Background Patients with acute respiratory failure caused by cardiogenic pulmonary edema (CPE) may require mechanical ventilation that can cause further lung damage. Our aim was to determine the impact of ventilatory settings on CPE mortality. Methods Patients from the LUNG SAFE cohort, a multicenter prospective cohort study of patients undergoing mechanical ventilation, were studied. Relationships between ventilatory parameters and outcomes (ICU discharge/hospital mortality) were assessed using latent mixture analysis and a marginal structural model. Results From 4499 patients, 391 meeting CPE criteria (median age 70 [interquartile range 59–78], 40% female) were included. ICU and hospital mortality were 34% and 40%, respectively. ICU survivors were younger (67 [57–77] vs 74 [64–80] years, p &lt; 0.001) and had lower driving (12 [8–16] vs 15 [11–17] cmH2O, p &lt; 0.001), plateau (20 [15–23] vs 22 [19–26] cmH2O, p &lt; 0.001) and peak (21 [17–27] vs 26 [20–32] cmH2O, p &lt; 0.001) pressures. Latent mixture analysis of patients receiving invasive mechanical ventilation on ICU day 1 revealed a subgroup ventilated with high pressures with lower probability of being discharged alive from the ICU (hazard ratio [HR] 0.79 [95% confidence interval 0.60–1.05], p = 0.103) and increased hospital mortality (HR 1.65 [1.16–2.36], p = 0.005). In a marginal structural model, driving pressures in the first week (HR 1.12 [1.06–1.18], p &lt; 0.001) and tidal volume after day 7 (HR 0.69 [0.52–0.93], p = 0.015) were related to survival. Conclusions Higher airway pressures in invasively ventilated patients with CPE are related to mortality. These patients may be exposed to an increased risk of ventilator-induced lung injury. Trial registration Clinicaltrials.gov NCT02010073 </jats:sec
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