Ni(II) Butylmethyldithiocarbamate: Physico-Chemical Properties, X-Ray Crystallography, DFT and Anti-Corrosion Screening in Different Acids

In industrial sectors, pickling and acid cleaning are mutual processes where acid solutions, such as hydrochloric acid (HCl) and sulfuric acid (H2SO4), are used to eliminate the corrosion products yielded on metal surfaces; thus, improving the performance of the machineries. However, the usage of the acid could lead to another metal deterioration. Dithiocarbamate inhibitor is defined as an organic compound that has good corrosion inhibition properties that can work as an inhibitor in an acid environment. Dithiocarbamate (DTC) assists by reducing acid reactiveness which prohibits metal dissolution in the acid. In this study, the Ni(II) N-butylmethyldithiocarbamate (Ni[BuMedtc]2) complex was synthesised by using an in-situ method and characterised by elemental analyser, attenuated total reflection Fourier transform infrared (ATR-FTIR), ultraviolet-visible (UV-Vis) spectroscopy and X-ray crystallographic study, and the chemical properties of the Ni[BuMedtc]2 complex was successfully calculated by the Discrete Fourier Transform (DFT) approach. The experimental results which were obtained through the weight-loss analysis method in two different acids – 1 M HCl and 1 M H2SO4 – indicated that the inhibition efficiency increased as the inhibitor concentration increased. The outcome showed that the Ni[BuMedtc]2 performed better as an inhibitor in 1 M HCl as compared to in1 M H2SO4 to protect the metal exterior because H2SO4 is more corrosive due to the excessive presence of H+.

Interaction Mechanism and Loss Analysis of Mixing between Film Cooling Jet and Passage Vortex

The interaction between the film-cooling jet and vortex structures in the turbine passage plays an important role in the endwall cooling design. In this study, a simplified topology of a blunt body with a half-cylinder is introduced to simulate the formation of the leading-edge horseshoe vortex, where similarity compared with that in the turbine cascade is satisfied. The shaped cooling hole is located in the passage. With this specially designed model, the interaction mechanism between the cooling jet and the passage vortex can therefore be separated from the crossflow and the pressure gradient, which also affect the cooling jet. The loss-analysis method based on the entropy generation rate is introduced, which locates where losses of the cooling capacity occur and reveals the underlying mechanism during the mixing process. Results show that the cooling performance is sensitive to the hole location. The injection/passage vortex interaction can help enhance the coolant lateral coverage, thus improving the cooling performance when the hole is located at the downwash region. The coolant is able to conserve its structure in that, during the interaction process, the kidney vortex with the positive rotating direction can survive with the negative-rotating passage vortex, and the mixture is suppressed. However, the larger-scale passage vortex eats the negative leg of the kidney vortices when the cooling hole is at the upwash region. As a result, the coolant is fully entrained into the main flow. Changes in the blowing ratio alter the overall cooling effectiveness but have a negligible effect on the interaction mechanism. The optimum blowing ratio increases when the hole is located at the downwash region.

Retention, Fasting Patterns, and Weight Loss With an Intermittent Fasting App: A Large-scale, 52-week Observational Study (Preprint)

BACKGROUND Intermittent Fasting (IF) is an increasingly popular approach to dietary control that focuses on the timing of eating rather than the quantity and content of caloric intake. IF practitioners typically seek to improve their weight and other health factors. Millions of practitioners have turned to purpose-built mobile applications to help them track and adhere to their fasts and monitor changes in their weight and other biometrics. OBJECTIVE This study aimed to quantify user retention, fasting patterns, and weight loss by users of two commonly used IF mobile apps. We aimed to describe starting BMI, amount of fasting, frequency of weight tracking, and other demographics as correlates of retention and weight change. METHODS We assembled height, weight, fasting and demographic data for adult users (age 18-100yo) of the LIFE Fasting Tracker and LIFE Extend apps from 2018-2020. Retention up to 52 weeks was quantified based on recorded fasts and correlated with user demographics. Users who provided height and at least two weights and whose first fast and weight records were contemporaneous were included in the weight loss analysis. Fasting was quantified as Extended Fasting Hours (hours beyond 12 in a fast) averaged per Day (EFH/Day). RESULTS 792,692 users were followed for retention based on 26 million recorded fasts. 132,775 (16.7%) of users were retained at 13 weeks, 54,881 (6.9%) at 26 weeks, and 16,478 (2.1%) at 52 weeks, allowing 4 consecutive weeks of inactivity. Weight loss in the qualifying cohort (n=161,346) was strongly correlated with starting BMI and EFH/Day. Users with BMI ≥ 40 lost 11.3% of their starting weight by 52 weeks versus a slight weight gain on average for users with starting BMI <23. Additionally, EFH/Day was an approximately linear predictor of weight loss for a given time point and starting BMI. By week 26, users lost over 1% of their starting weight per EFH/Day on average. Furthermore, users who recorded their weight monthly lost considerably more weight than those who did not (eg, 8.5% vs 3.7% weight loss at week 13 for users with BMI ≥25). By 26 weeks, 69.2% (2985/4313) of users with starting BMI ≥ 25 who recorded monthly weights lost at least 5% of their starting weight, and 39.9% (1722/4313) lost at least 10% body weight. CONCLUSIONS Intermittent Fasting with the LIFE mobile apps appears to be a sustainable approach to weight reduction in the overweight and obese population. Healthy weight and underweight individuals do not lose much weight on average, even with extensive fasting. Obese users lose substantial weight over time, with more weight loss in those who fast more and who record their weight more frequently.

Cluster analysis of time series K-Means line loss based on DWT distance

This paper constructs an indicator system composed of inherent attributes and time characteristics of the line based on the line loss, and proposes a K-Means line loss cluster analysis model based on this indicator system. The line is classified according to the clustering results. The result is 314.51 on the CH index (Calinski Harabasz Index), 0.19 on the Silhouette Cofficient (Silhouette Cofficient), and a running time of 0.508s. Compared with the traditional algorithm, it is greatly improved. The field of line loss analysis has guiding significance.