Seven Level Modified Cascaded Inverter for Induction Motor Drive Applications

In this paper, an H-bridge inverter topology with reduced switch count technique is introduced. This technique reduces the number of controlled switches used in conventional multilevel inverter. To establish a single phase system, the proposed multilevel inverter requires one H-bridge and a multi conversion cell. A multi conversion cell consists of three equal voltage sources with three controlled switches and three diodes. In conventional method, twelve controlled switches are used to obtain seven levels. Due to involvement of twelve switches the harmonics, switching losses, cost and total harmonic distortion are increased. This proposed topology also increases the level to seven with only seven controlled switches. It dramatically reduces the complexity of control circuit, cost, lower order harmonics and thus effectively reduces total harmonic distortion. Keywords: Cascaded Multilevel Inverter, H-bridge Inverter, Total Harmonic Distortion, Sinusoidal Pulse Width Modulation, Insulated Gate Bipolar Transisto

In vitro antioxidant activity of Vetiveria zizanioides root extract

Free radicals induce numerous diseases by lipid peroxidation and DNA damage. It has been reported that some of the extracts from plants possess antioxidant properties capable of scavenging free radicals in vivo. Vetiveria zizanioides belonging to the family Gramineae, is a densely tufted grass which is widely used as a traditional plant for aromatherapy, to relieve stress, anxiety, nervous tension and insomnia. In this regard, the roots of V. zizanioides was extracted with ethanol and used for the evaluation of various in vitro antioxidant activities such as reducing power ability, superoxide anion radical scavenging activity, deoxyribose degradation assay, total antioxidant capacity, total phenolics and total flavonoid composition. The various antioxidant activities were compared with suitable antioxidants such as butyl hydroxy toluene, ascorbic acid, quercetin, alpha tocopherol, pyrocatechol and curcumin respectively. The generation of free radicals O2-, H2O2, OH and NO were effectively scavenged by the ethanolic extract of V.zizanioides. In all these methods, the extract showed strong antioxidant activity in a dose dependent manner. The results obtained in the present study clearly indicates that V. zizanioides scavenges free radicals, ameliorating damage imposed by oxidative stress in different disease conditions and serve as a potential source of natural antioxidant. The study provides a proof for the ethnomedical claims and reported biological activities. The plant has, therefore, very good therapeutic and antioxidant potential

nSeP: immune and metabolic biomarkers for early detection of neonatal sepsis-protocol for a prospective multicohort study

Introduction Diagnosing neonatal sepsis is heavily dependent on clinical phenotyping as culture-positive body fluid has poor sensitivity, and existing blood biomarkers have poor specificity. A combination of machine learning, statistical and deep pathway biology analyses led to the identification of a tripartite panel of biologically connected immune and metabolic markers that showed greater than 99% accuracy for detecting bacterial infection with 100% sensitivity. The cohort study described here is designed as a large-scale clinical validation of this previous work. Methods and analysis This multicentre observational study will prospectively recruit a total of 1445 newborn infants (all gestations)—1084 with suspected early—or late-onset sepsis, and 361 controls—over 4 years. A small volume of whole blood will be collected from infants with suspected sepsis at the time of presentation. This sample will be used for integrated transcriptomic, lipidomic and targeted proteomics profiling. In addition, a subset of samples will be subjected to cellular phenotype and proteomic analyses. A second sample from the same patient will be collected at 24 hours, with an opportunistic sampling for stool culture. For control infants, only one set of blood and stool sample will be collected to coincide with clinical blood sampling. Along with detailed clinical information, blood and stool samples will be analysed and the information will be used to identify and validate the efficacy of immune-metabolic networks in the diagnosis of bacterial neonatal sepsis and to identify new host biomarkers for viral sepsis

Pooled Rates of Adenoma Detection by Colonoscopy in Asymptomatic Average Risk Individuals with Positive Fecal Immunochemical Test: A Systematic Review and Meta-Analysis

Background & aims: Current adenoma detection rate (ADR) benchmarks for colonoscopy in individuals positive for a fecal immunochemical test (FIT), are ≥45% in males and ≥35% in females. These are based on weak, low-quality evidence. We performed a meta-analysis to ascertain the pooled ADR in FIT-positive colonoscopy. Methods: Major databases like PubMed, EMBASE and Web-of-Science were searched in Oct-2021 for studies reporting on ADR of colonoscopy in FIT-positive population. Meta-analysis was performed by standard methodology using the random-effects model. Heterogeneity was assessed by I2% and 95% prediction-interval statistics. Results: 34 high-quality studies that included more than 6-million asymptomatic average risk individuals were analyzed. 2,655,345 individuals completed a screening FIT test. The pooled FIT screening rate was 69.8% (95% CI [62.8-76.1]), the pooled FIT positivity rate was 5.4%[4.3-6.9], and the colonoscopy completion rate was 85%[82.8-86.9]. The pooled ADR was 47.8%[44.1-51.6], pooled aADR was 25.3%[22-29], and the pooled CRCDR was 5.1%[4.4-5.9]. The pooled ADR in males was 58.3%[52.8-63.6] and in females was 41.9%[36.4-47.6]. The pooled ADR with qualitative FIT assessment was 67.7%[50.7-81], with 1-stool sample FIT was 52.8%[48.8-56.8] and at a cut-off threshold of 100ngHb/ml was 52.1%[47-57.1]. Based on time-period cumulative analysis, the ADR improved over time from 30.5%[24.6-37.2] to 47.8%[44.1-51.6]. Conclusion: This meta-analysis supports the current ADR benchmarks for colonoscopy in FIT-positive individuals. Excellent pooled ADR parameters were demonstrated with qualitative assessment of one stool sample at a test cut-off value of 100ng Hb/ml, and ADR per endoscopist improved over time

Perception modelling by invariant representation of deep learning for automated structural diagnostic in aircraft maintenance: A study case using DeepSHM

Predictive maintenance, as one of the core components of Industry 4.0, takes a proactive approach to maintain machines and systems in good order to keep downtime to a minimum and the airline maintenance industry is not an exception to this. To achieve this goal, practices in Structural Health Monitoring (SHM) complement the existing Non-Destructive-Testing (NDT) have been established in the last decades. Recently, the increasing computational capability such as utilization of a graphical processing unit (GPU) in combination with advanced machine learning techniques such as deep learning has been one of the main drivers in the advancement of predictive analytics in condition monitoring. In our previous work, we proposed a novel approach using deep learning for guided wave based structural health called DeepSHM. As a study case, we treated an ultrasonic signal from guided Lamb wave SHM with a convolutional neural network (CNN). In that work, we only considered a single central frequency excitation. This led to a single governing wavelength which is normally good for the detection of a single damage size. In classical signal processing, applying a broader excitation frequency poses an analysis and interpretation nightmare because it contains more complex information and thus is difficult to understand. This problem can be overcome with deep learning; however, it creates another problem: while deep learning typically results in a more accurate result prediction, it is specifically made for solving only certain types of tasks. While many papers have already introduced deep learning for diagnostics, many of these works are only proposing novel predictive techniques, however the mathematical formalization is lacking, and we are not informed about why we should treat acoustic signal with deep learning. So, the basis of ‘explainable AI’ for SHM and NDT is currently lacking. For this reason, in this paper, we would like to extend our previous work into a more generalized. Rather than focusing on a novel technique, we propose a plausible theoretical perspective inspired from neuroscience for signal representation of deep learning framework to model machine perception in structural health monitoring (SHM), especially because SHM typically involves multiple sensory input from different sensing locations. To do this, we created a set of artificial data from a finite element model (FEM) and represented DeepSHM in two different ways: 1). Perpetual representation of observation and 2). Hierarchical structure of entities that is decomposable in a smaller sub-entity. Consequently, we assume two plausible models for DeepSHM: 1). Either it behaves as a single deciding actor since the observation is regarded as perpetual, and 2). Or it acts as a multiple actor with independent outputs since multiple sensors can form different output probabilities. These artificial data were split into several different input representations, classified into several damage scenarios and then trained with commonly used deep learning training parameters. We compare the performance metrics of each perception model to describe the training behavior of both representations.Structural Integrity & Composite

Efficacy and Safety of Intragastric Balloon (IGB) in Non-alcoholic Fatty Liver Disease (NAFLD): a Comprehensive Review and Meta-analysis

Intragastric balloon (IGB) therapy has shown efficacy in weight loss but its role in NAFLD remains unknown. We conducted a systematic review and meta-analysis to evaluate the efficacy of IGB in NAFLD. Meta-analysis was performed to estimate the pooled proportion of patients with improvement in steatosis as determined by imaging and histology following IGB placement. Nine studies were included in our analysis. Four hundred forty-two IGBs were placed. Improvement in steatosis was seen in 79.2% of patients and NAS in 83.5% of patients, and HOMA-IR score improved in 64.5% of patients. A reduction in liver volume by CT scan was noticed in 93.9% of patients undergoing IGB placement. IGB is an effective and safe short-term therapeutic modality for patients with NAFLD