Design and Development of Hybrid Converter for Marine Applications

Recently, there has been an increase in the growth and advancement of electric propulsion in marine electrical drives. A maximum amount of energy is utilized by ships for propulsion drives. To be aware of it and develop an optimized structure to improve the effectiveness of the propulsion system with power consumption is necessary. The proposed paper aims to develop a model and perform functional analysis as per the above understanding and requirements. The factors considered include greenhouse gas emissions, CO2 emissions, environmental aspects, and the availability of non-renewable resources, which leads to the introduction of renewable energy as a replacement method of power generation. For this work, two different renewable sources, such as solar and wind energy, were chosen. The combination of these two resources can manipulate the voltage and satisfy the load in a desirable way. For voltage improvement, a high gain converter with a minimal number of active and passive components is selected. This system adopts a storage system to meet the needs in the future. The inverter switches are controlled by the recommended control algorithm, which can balance and provide adequate power towards the drive by a feedback control loop. The speed of propulsion in the drive is adjusted by the induction motor coupled with the propeller. The analytical study of the proposed system is carried out in MATLAB software. The simulation study revealed the effectiveness of this modern optimization technique.

Noise in the process: an assessment of the evidential value of mediation effects in marketing journals

Mediation analysis plays a central role in marketing research due to its usefulness in helping to explain complex processes. Like other forms of inference, mediation analyses are susceptible to false positive results. This is particularly true when analytic decisions are based on the data, rather than a priori hypotheses. To assess the collective evidential value of mediation analyses in marketing, we used an approach first implemented by Götz and colleagues (2021) that (1) measures the relative proximity of confidence intervals to zero (RP) and (2) aggregates a related set of RP scores into a single distribution. For our analysis, we compared the RP distribution of top marketing journals (2018-20) to simulations of low power, adequate power, and null effects. We also compared the marketing journals to real-world data from Journal of Personality and Social Psychology (JPSP) (2018-20). We found that, in terms of evidential value, mediation analyses in marketing substantially deviated from simulations of adequate power and JPSP but were similar to simulations of low power and null effects. We propose study preregistration, corrections for multiple testing, and increased statistical power as solutions to increase evidence quality going forward.

Leveling up: improving power in fMRI by moving beyond cluster-level inference

Inference in neuroimaging commonly occurs at the level of "clusters" of neighboring voxels or connections, thought to reflect functionally specific brain areas. Yet increasingly large studies reveal effects that are shared throughout the brain, suggesting that reported clusters may only reflect the "tip of the iceberg" of underlying effects. Here, we empirically compare power of traditional levels of inference (edge and cluster) with broader levels of inference (network and whole-brain) by resampling functional connectivity data from the Human Connectome Project (n=40, 80, 120). Only network- and whole brain-level inference attained or surpassed "adequate" power (β =80%) to detect an average effect, with almost double the power for network- compared with cluster-level procedures at more typical sample sizes. Likewise, effects tended to be widespread, and more widespread pooling resulted in stronger magnitude effects. Power also substantially increased when controlling FDR rather than FWER. Importantly, there may be similar implications for task-based activation analyses where effects are also increasingly understood to be widespread. However, increased power with broader levels of inference may diminish the specificity to localize effects, especially for non-task contexts. These findings underscore the benefit of shifting the scale of inference to better capture the underlying signal, which may unlock opportunities for discovery in human neuroimaging.

Assessing Measurement Invariance Across Multiple Groups: When Is Fit Good Enough?

Complex research questions often need large samples to obtain accurate estimates of parameters and adequate power. Combining extant data sets into a large, pooled data set is one way this can be accomplished without expending resources. Measurement invariance (MI) modeling is an established approach to ensure participant scores are on the same scale. There are two major problems when combining independent data sets through MI. First, sample sizes will often be large leading to small differences becoming noninvariant. Second, not all data sets may include the same combination of measures. In this article, we present a method that can deal with both these problems and is user friendly. It is a combination of generating random normal deviates for variables missing completely in combination with assessing model fit using the root mean square error of approximation good enough principle, based on the hypothesis that the difference between groups is not zero but small. We demonstrate the method by examining MI across eight independent data sets and compare the MI decisions of the traditional and good enough approach. Our results show the approach has potential in combining educational data.

Probiotic therapy for periodontal and peri-implant health – silver bullet or sham?

Probiotics are thought to be beneficial microbes that influence health-related outcomes through host immunomodulation and modulation of the bacteriome. Its reported success in the treatment of gastrointestinal disorders has led to further research on its potential applicability within the dental field due to similarities such as a polymicrobial aetiology and disease associated microbial-shifts. Although the literature is replete with studies demonstrating its efficacy, the use of probiotics in dentistry continues to polarise opinion. Here, we explore the evidence for probiotics and its effect on periodontal and peri-implant health. MEDLINE, EMBASE, and CENTRAL were systemically searched from June 2010 to June 2020 based on a formulated search strategy. Of 1,956 potentially relevant articles, we selected 27 double-blinded randomised clinical trials in the areas of gingivitis, periodontitis, residual pockets during supportive periodontal therapy, and peri-implant diseases, and reviewed their efficacy in these clinical situations. We observed substantial variation in treatment results and protocols between studies. Overall, the evidence for probiotic therapy for periodontal and peri-implant health appears unconvincing. The scarcity of trials with adequate power and follow-up precludes any meaningful clinical recommendations. Thus, the routine use of probiotics for these purposes are currently unsubstantiated. Further multi-centre trials encompassing a standardised investigation on the most promising strains and administration methods, with longer observation times are required to confirm the benefits of probiotic therapy for these applications.

Xueshuantong Injection in Treating Deep Venous Thrombosis: A Systematic Review and Trial Sequential Analysis

Aims. In recent years, the incidence of deep venous thrombosis (DVT) presents an increasing trend year by year. The current evidence regarding the efficacy and safety of Xueshuantong injection for DVT is controversial. This systematic review (SR) aimed to assess the efficacy and safety of Xueshuantong injection in the treatment of DVT systematically and provide an evidence-based reference for clinical treatment. Methods. Nine electronic databases were used to identify the literature consisting of randomized controlled trials (RCTs) with a date of search of 1 November 2020. Clinical effective rate and incidence rate of adverse events were investigated as primary outcomes. Patency rate of femoral vein, patency rate of popliteal vein, patency rate of posterior tibial vein, circumference difference, activated partial thromboplastin time (APTT), and D-dimer (D-D) were investigated as secondary outcomes. Revman 5.4.1 was used to analyze the results. Analysis of the power of evidence was performed with Trial Sequential Analysis (TSA). Results. A total of 12 articles including 1018 patients were included. The results of the meta-analysis showed that the clinical effective rate in the experimental group was higher than that in the control group, the incidence rate of adverse events in the experimental group was higher than that in the control group; after the operation, the patency rate of femoral vein, patency rate of popliteal vein, patency rate of posterior tibial vein, circumference difference, APTT, and D-D in the experimental group were significantly improved compared with those in the control group, and the difference between the groups was statistically significant. TSA suggested that the meta-analysis concerning the clinical effectiveness of Xueshuantong injection in the treatment of DVT was of adequate power to reach firm conclusions. Conclusion. Based on the current analysis, Xueshuantong injection as an add-on treatment provided better treatment effect for DVT with adequate power but this benefit should be considered with caution because of the small number of studies included in the meta-analysis and the high or unclear risk of bias of the included trials, suggesting that further studies are needed.

Mapping and 3D modelling using quadrotor drone and GIS software

Background The main obstacle for local and daily or weekly time-series mapping using very high-resolution satellite imagery is the high price and availability of data. These constraints are currently obtaining solutions in line with the development of improved UAV drone technology with a wider range and imaging sensors that can be used. Findings Research conducted using Inspire 2 quadcopter drones with RGB cameras, developing 3D models using photogrammetric and situation mapping uses geographic information systems. The drone used has advantages in a wider range of areas with adequate power support. The drone is also supported by a high-quality camera with dreadlocks for image stability, so it is suitable for use in mapping activities. Conclusions Using Google earth data at two separate locations as a benchmark for the accuracy of measurement of the area at three variations of flying height in taking pictures, the results obtained were 98.53% (98.68%), 95.2% (96.1%), and 94.4% (94.7%) for each altitude of 40, 80, and 100 m. The next research is to assess the results of the area for more objects from the land cover as well as for the more varied polygon area so that the reliability of the method can be used in general

Effect size, sample size and power of forced swim test assays in mice: Guidelines for investigators to optimize reproducibility

A recent flood of publications has documented serious problems in scientific reproducibility, power, and reporting of biomedical articles, yet scientists persist in their usual practices. Why? We examined a popular and important preclinical assay, the Forced Swim Test (FST) in mice used to test putative antidepressants. Whether the mice were assayed in a naïve state vs. in a model of depression or stress, and whether the mice were given test agents vs. known antidepressants regarded as positive controls, the mean effect sizes seen in the experiments were indeed extremely large (1.5–2.5 in Cohen’s d units); most of the experiments utilized 7–10 animals per group which did have adequate power to reliably detect effects of this magnitude. We propose that this may at least partially explain why investigators using the FST do not perceive intuitively that their experimental designs fall short—even though proper prospective design would require ~21–26 animals per group to detect, at a minimum, large effects (0.8 in Cohen’s d units) when the true effect of a test agent is unknown. Our data provide explicit parameters and guidance for investigators seeking to carry out prospective power estimation for the FST. More generally, altering the real-life behavior of scientists in planning their experiments may require developing educational tools that allow them to actively visualize the inter-relationships among effect size, sample size, statistical power, and replicability in a direct and intuitive manner.

Assessing Measurement Invariance Across Multiple Groups: When is Fit Good Enough?

Complex research questions often need large samples to obtain accurate estimates of parameters and adequate power. Combining extant datasets into a large, pooled dataset is one way this can be accomplished without expending resources. Measurement invariance modeling (MI) is an established approach to ensure participant scores are on the same scale. There are two major problems when combining independent data sets through MI. First, sample sizes will often be large leading to small differences becoming non-invariant. Second, not all datasets may include the same combination of measures. In this paper, we present a method that can deal with both these problems and is user friendly. It is a combination of generating random normal deviates for variables missing completely in combination with assessing model fit using the RMSEA good enough principle, based on the hypothesis that the difference between groups is not zero, but small. We demonstrate the method by examining MI across eight independent data sets and compare the MI decisions of the traditional and good enough approach. Our results show the approach has potential in combining educational data.

Blood omega-3 fatty acids and death from COVID-19: A Pilot Study

Very-long chain omega-3 fatty acids (EPA and DHA) have anti-inflammatory properties that may help reduce morbidity and mortality from COVID-19 infection. We conducted a pilot study in 100 patients to test the hypothesis that RBC EPA+DHA levels (the Omega-3 Index, O3I) would be inversely associated with risk for death by analyzing the O3I in banked blood samples drawn at hospital admission. To have adequate power (>80%) in this pilot study, we pre-specified a significance level of 0.10. Fourteen patients died, one of 25 in quartile 4 (Q4) (O3I ≥5.7%) and 13 of 75 in Q1-3. After adjusting for age and sex, the odds ratio for death in patients with an O3I in Q4 vs Q1-3 was 0.25, p=0.07. Thus, we have suggestive evidence that the risk for death from COVID-19 was lower in those with the highest O3I levels. These preliminary findings need to be confirmed in larger studies.