An empirical model has been developed for the successful prediction of the melt index (MI) during grade change operations in a high density polyethylene plant. To efficiently capture the nonlinearity and grade-changing characteristics of the polymerization process, the plant operation data is treated with the recursive partial least square (RPLS) scheme combined with model output bias updating. In this work two different schemes have been proposed. The first scheme makes use of an arbitrary threshold value which selects one of the two updating methods according to the process requirement so as to minimize the root mean square error (RMSE). In the second scheme, the number of RPLS updating runs is minimized to make the soft sensor time efficient, while reducing, maintaining or normally increasing the RMSE obtained from first scheme up to some extent. These schemes are compared with other techniques to exhibit their superiority.

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Introduction:The prevalence of childhood obesity has increased over the last two decades. Obesity is a major risk factor for chronic diseases and plays a central role in insulin resistance or metabolic syndrome.Methods:The aim of the study was to assess the prevalence of obesity and abdominal obesity by means of body mass index (BMI) and waist-to-height ratio (WHtR) in adolescent girls in a district school in Bangladesh. Based on age and sex specific BMI percentiles, the students were classified as normal weight (5th–<85th percentile), overweight (85th–<95th percentiles), and obese (≥95th percentile). Central obesity was categorized as WHtR ≥ 0.5. Adolescent girls (aged 9–17 years) attending the sixth to twelfth grades (n = 501) in a Bengali medium school participated in the study.Results:The prevalence of obesity and overweight were 23% and 14% among the girls. The prevalence of central obesity was 26%. Around 14% of girls in the normal weight group were centrally obese. There was a significant relationship between WHtR and BMI status (P = 0.0001).Conclusion:Our study provides evidence showing a high prevalence of overall and central obesity in adolescent girls in our population. We emphasize the need for further large scale surveillance programs and preventive strategies in our population to reduce the incidence of obesity.

Graphene-based materials have attracted considerable interest owing to their distinctive characteristics, such as their biocompatibility in terms of both their physical and intrinsic chemical properties. The use of nanomaterials with graphene as a biocompatible agent has increased due to an uptick in dedication from biomedical investigators. Here, GO-ZnO was characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), ultraviolet-visible (UV-Vis) spectroscopy, energy dispersive X-ray analysis (EDAX), and Raman spectroscopy for structural, morphological, and elemental analysis. The toxic extent of GO-ZnO was noted by a methyl-thiazole-tetrazolium (MTT), while cellular morphology was observed towards the MCF-7 cells using an inverted microscope at magnification 40×. The cytotoxic effect of GO-ZnO investigated the cell viability reduction in a dose-dependent manner, as well as prompted the cell demise/destruction in an apoptotic way. Moreover, statistical analysis was performed on the experimental outcomes, with p-values < 0.05 kept as significant to elucidate the results. The generation of reactive oxygen species (ROS) demonstrated the potential applicability of graphene in tumor treatment. These key results attest to the efficacy of GO-ZnO nanocomposites as a substantial candidate for breast malignancy treatment.