Recent Advances in Transition Metal-Based Catalysts for Ethylene Copolymerization with Polar Comonomer.

The synthesis of polar functionalized polyolefin (PFP) offers improvement in mixing properties, polymer surface, and rheological properties with the potential of upgraded polyolefins for modern and ingenious applications. The synthesis of PFP from metal-based catalyzed olefin (non-polar in nature) copolymerization with polar comonomers embodies energy-efficient, atom-efficient, and apparently an upfront methodology. Despite their outstanding success during conventional polymerization of olefin, 3rd and 4th group (early transition metal)-based catalysts, owing to their electrophilic nature, face challenges mainly due to Lewis basic sites of the polar monomers. On the contrary, late transition metal-based catalysts have also made progress, in recent years, for PFP synthesis. The recent past has also witnessed several advancements in the development of dominating palladium-based catalysts while their lower resistance towards ligand functional groups has limited the practical application of abundant and cheaper nickel-based catalysts. However, the relentless efforts of the scientific community, during the past half-decade, have indicated rigorous progress in the development of nickel-based catalysts for PFP synthesis. In this review, we have abridged the recent research trends in both early as well as late transition metal-based catalyst development. Furthermore, we have highlighted the role of transition metal-based catalysts in influencing the polymer properties.

A Prediction Model Optimization Critiques through Centroid Clustering by Reducing the Sample Size, Integrating Statistical and Machine Learning Techniques for Wheat Productivity.

Machine learning algorithms are rapidly deploying and have made manifold breakthroughs in various fields. The optimization of algorithms got abundant attention of researchers being a core component for deploying the machine learning model (MLM) abled to learn the parameters in significant ways for the given data. Modeling crop productivity through innumerable agronomical constraints has become a crucial task for evolving sustainable agricultural policies. The cross-sectional datasets of 26430 (D1) crop-cut experiments are taken by 2nd-stage area frame sampling, collected from crop reporting service. This research is taken as follows: firstly three more effective numerical optimized datasets are generated (D1, D2, and D3) from D1 by taking the centroid points of features which decrease the sample size; secondly MLM is integrated with the traditional statistical models (TSMs) for multiple linear regression (MLR), and thirdly decision tree regression (DTR) and random forest regression (RFR) are deployed to get the optimized models able to predict the wheat productivity well with 75% datasets to train and 25% to test the model using the evaluation metrics (R 2, RMSE), information criterion (AIC) with weights (AICW), evidence ration (E.R), and decompositions of prediction error. The MLR outperformed for MLM than TSM. The performance capability of MLM and TSM got upswing for generated datasets. RFR got optimized and superperformed for D1, D2, D3, and D4. This study demonstrated strong evidences for deploying MLM for prediction of wheat productivity as an alternative of traditional statistical modeling.

Thermal Degradation Kinetics Analysis of Ethylene-Propylene Copolymer and EP-1-Hexene Terpolymer.

LLDPE is a less crystalline polymer with vast industrial and domestic applications. It is imperative to understand the synthesis, processing conditions, and thermal degradation mechanism of the co- as well as terpolymers. This paper reports the in-situ synthesis and thermal degradation studies of the ethylene-propylene copolymer and ethylene-propylene-1-hexene terpolymer and its nanocomposite with ZnAL LDH sheets. The 1-hexene dosing during the in-situ process influenced the product yield and immensely affected the thermal stability of the resultant polymer. One milliliter 1-hexene in-situ addition increased the product yield by 170 percent, while the temperature at 10 percent weight loss in TGA was dropped by about 60 °C. While only 0.3 weight percent ZnAL LDH addition in the terpolymer improved the thermal stability by 10 °C. A master plot technique and combined kinetics analysis (CKA) were deployed to access the thermal degradation mechanism of the synthesized polymers.

Establishing growth charts for proposed body shape and size index of the Pakistani population, using quantile regression approach.

BACKGROUND: Obesity leads to other fatal diseases like diabetes, cardiovascular diseases, depression, and some forms of cancer. Still, the well-known tool to measure obesity is the body mass index. But it usually failed in the measurement of adipose tissues. So, we present a novel anthropometric measure, called body shape and size index which is developed by the combination of major anthropometric determinants: body surface area, body mass index, weight, and height. METHODS: This study is based on cross-sectional data consisting of 7224 individuals that were taken from the city Multan, Punjab, Pakistan. All the individuals, both males, and females, of age 2 years and above were included in the study except the pregnant women. The variables included in this study are gender, area (urban and rural), age (years), weight (kg), and height (meters). Growth charts of quantile regression are used for the inferential analysis of data. Comparison of proposed body shape and size index at different obesity levels has also been made to access the relationship of proposed body shape and size index with obesity. RESULTS: The results show that the proposed body shape and size index has a great association with body surface area, body mass index, weight, height, and age. The proposed body shape and size index has a high negative association with body surface area, moderate negative association with body mass index and weight, and low negative association with height and age. According to growth charts of body shape and size index, after the age of 25 years, body shape and size index curves go upward while it smoothly goes downward at the age of 50 years but decreases in earlier ages. Body shape and size index showed a significant association with body shape and body size (body development) at the same time. CONCLUSION: Body shape and size index is found, generally linear with age, and increased with decreasing body mass index and body surface area. The proposed index has an indirect relationship with obesity. Body shape and size index with low values indicates a high risk of obesity. While, however, body shape and size index with high values indicates a low risk of obesity. Applications of the proposed body shape and size index are also presented in statistical modeling.

Magnetic surfactants: A review of recent progress in synthesis and applications.

Magnetic surfactants are a special class of surfactants with magneto-responsive properties. These surfactants possess lower critical micelle concentrations and are more effective in reducing surface tension as compared to conventional surfactants. Such surfactants' ability to manipulate self-assembly in a controlled way by tuning the magnetic field makes them an attractive choice for several applications, including drug delivery, catalysis, separation, oilfield, and water treatment. In this work, we reviewed the properties of magnetic surfactants and possible explanations of magnetic behavior. This article also covers the synthesis methods that can be used to synthesize different types of cationic, anionic, nonionic, and zwitterionic magnetic surfactants. The applications of magnetic surfactants in different fields such as biotechnology, water treatment, catalysis, and oilfield have been discussed in detail.

Optimization of HNO3 leaching of copper from old AMD Athlon processors using response surface methodology.

The present study investigates the optimization of HNO3 leaching of Cu from old AMD Athlon processors under the effect of nitric acid concentration (%), temperature (°C) and ultrasonic power (W). The optimization study is carried out using response surface methodology with central composite rotatable design (CCRD). The ANOVA study concludes that the second degree polynomial model is fitted well to the fifteen experimental runs based on p-value (0.003), R2 (0.97) and Adj-R2 (0.914). The study shows that the temperature is the most significant process variable to the leaching concentration of Cu followed by nitric acid concentration. However, ultrasound power shows no significant impact on the leaching concentration. The optimum conditions were found to be 20% nitric acid concentration, 48.89 °C temperature and 5.52 W ultrasound power for attaining maximum concentration of 97.916 mg/l for Cu leaching in solution.

Impact of nanoparticles on human and environment: review of toxicity factors, exposures, control strategies, and future prospects.

Nanotechnology has revolutionized the world through introduction of a unique class of materials and consumer products in many arenas. It has led to production of innovative materials and devices. Despite of their unique advantages and applications in domestic and industrial sectors, use of materials with dimensions in nanometers has raised the issue of safety for workers, consumers, and human environment. Because of their small size and other unique characteristics, nanoparticles have ability to harm human and wildlife by interacting through various mechanisms. We have reviewed the characteristics of nanoparticles which form the basis of their toxicity. This paper also reviews possible routes of exposure of nanoparticles to human body. Dermal contact, inhalation, and ingestion have been discussed in detail. As very limited data is available for long-term human exposures, there is a pressing need to develop the methods which can determine short and long-term effects of nanoparticles on human and environment. We also discuss in brief the strategies which can help to control human exposures to toxic nanoparticles. We have outlined the current status of toxicological studies dealing with nanoparticles, accomplishments, weaknesses, and future challenges.