Retraction: Are conjugated linoleic acid (CLA) isomers good or bad trans fats?

Even though trans fatty acids (TFAs) are present in natural sources such as foods from ruminant origins, the development of partially hydrogenated vegetable oil contributed to a significant increase in total TFAs consumption in humans. Currently, TFA consumption is considered to be a risk factor for coronary heart diseases. Researchers are now starting to discover that not all TFAs behave in a similar manner, that is, isomer specificity may be found. Among non‐conjugated TFAs, plant originated TFAs (mainly elaidic and linolelaidic acids) are particularly linked to increased risk for coronary heart diseases, while animal originated TFAs (mainly vaccenic acid) are not. Among conjugated TFAs, two major isomers of conjugated linoleic acid (CLA), cis‐9, trans‐11 and trans‐10, cis‐12, show distinctive biological activities. A number of clinical trials of CLA with effects on body composition have been reported, but effects on coronary heart disease risk factors have been inconsistent. Meanwhile, safety concerns regarding CLA, in particular isomer specificity, have also been raised. Thus, it is critical to identify isomer specific effects of TFAs on particular risk factors, to determine their health impact.     

Improving the Performance of HF Radio Networks in the Presence of Interference through Automatic Link Establishment with Frequency Hopping Technique

In the cement industry, a rotary kiln is a pyro-processing device that is used to measure temperature. Measuring and maintaining a certain range of temperature in the rotary kiln is important to ensure the production of quality clinker granules. The assessment of consuming zone temperature is acquired using radiation pyrometers from the temperature of a hotspot. However, it is a difficult task to measure the burning zone temperature due to the very high temperature developed in the turning furnace sintering process. Existing pyrometer and camera based techniques are not able to provide accurate temperature and temperature variations developed in the burning zone. This research work considers flame image processing using region of interest (ROI), fuzzy logic, and neural networks for efficient temperature measurement. Various temperature measurement and control techniques are utilized in the existing conventional (Prasanna and Bojja in ESCI (helix—the scientific explorer) 4843–4849, 2019) rotary kiln control techniques. In pyrometer-based measurements, the standard of radiation may lead to errors and inaccurate readings. Hence, the consuming zone temperature estimation got from the radiation pyrometer isn't solid and it is hard to get temperature data for a particular location. A colorimetric device-based intelligent control system measures the burning temperature of a specific point, but reading fluctuations are seen because of smoke and dust developed in the combustion process. In ROI based flame image processing, many factors, such as turbulent flame, brightness of flame zone, and dust, affect identifying the boundary for ROI based flame image analysis. In neural network models, variable selection plays a crucial role in designing effective systems with learning capabilities, but it is not an easy task to accomplish without certain rules. Hence, it is highly necessary to develop an improved control system. In view of the issues in variable and feature selection, a few neuro fuzzy systems are adopted in measurement and control. The consuming zone temperature estimation needs a lot of attention due to the very high temperature developed in the rotary kiln sintering process. Existing techniques have to be improved upon using advanced algorithms and intelligent approaches. A sintering state recognition system has been developed with features of flame images and fusion methodologies. In this approach, various flame image features and texture (Ren and Wang in Int J Autom Compu 11(1):72–77, 2014) features are extracted from the burning zone region. Though these methods address a few issues in flame image processing, the acquired image is largely affected by blurring and internal parameters of the sintering process. Charge coupled device (CCD) camera images and videos are applied to many image processing algorithms for better feature extraction and region extraction. The region of interest-based analysis is mainly focused on temperature assessment in this work. Intelligent control techniques are applied to measure the burning zone temperature in a rotary kiln. Fuzzy logic-based inference systems are combined with neural network algorithms in the development of neuro-fuzzy systems. The fuzzy surmising framework in light of mathematical models is the successful manner to anticipate the temperature esteems utilizing power measures. The fire pictures caught by the CCD cameras are handled utilizing fluffy rule-based picture investigation, which estimates temperature from a fire picture by contemplating RGB power planes. The arrangement of result temperature esteems is wanted to be a participation work. The Mamdani fluffy induction model is used to give planning of fluffy fire temperature. Exact temperature planning of fire pictures is performed to control the temperature inside the going stove to make top notch clinker. The fire picture examination is completed in different edges of three unique datasets, and temperature is estimated for various crude supper feed rates and coal feed rates. However there is a slight distinction in the acquired temperature, the general temperature evaluation process doesn't show a huge contrast as per the dataset.

     

An Improved UTD Based Model for the Multiple Building Diffraction of Plane Waves in Urban Environments by Using Higher Order Diffraction Coefficients

This paper describes an improved model for multiple building diffraction modeling based on the uniform theory of diffraction. A well-known problem in conventional uniform theory of diffraction (CUTD) is multiple edge transition zone diffraction. Here, higher order diffracted fields are used in order to improve the result. Hence, we use higher order diffraction coefficients to improve a hybrid physical optics (PO)-CUTD model, the results show that the new model can correct errors of the PO-CUTD model. Therefore, the proposed model can find application in the development of theoretical models to predict more realistic path loss in urban environments, when multiple building diffraction is considered.     

RETRACTED ARTICLE: Investigation of Frying Oil Quality Using VIS/NIR Hyperspectral Analysis

Traditional chemical methods of analyzing frying oil quality are time-consuming and not amenable to on-line measurement. The main objective of this study was to evaluate quality changes of heated oils based on visible/near infrared spectral analysis using a hyperspectroradiometer. The reflectance spectra of the heated oils were analyzed within the range 400–1,750 nm. Acid value, total polar component, and viscosity of oil samples were used as indicators of different quality levels of oil. Partial least squares calibration models were developed for quantitative evaluations of these parameters. The R ² and root mean square error for each prediction were calculated to assess the prediction capability of calibration models. The study demonstrated that using the established calibration models, quality parameters could be predicted with R ² values over 0.92.     

Synthesis and characterization of conductive neural tissue engineering scaffolds based on urethane-polycaprolactone

Polymeric biomaterials play a key role in enhancement of lengthy nerve regeneration and various types of scaffolds were used to pave the way for nerve regeneration. Electrospun fibrous scaffolds have special potential applicability in controlling the cell behaviors such as adhesion, growth, proliferation and function. This study attempted to design a conductive and porous fibrous scaffold containing polycaprolactone (PCL) and polyaniline (PANI) with controllable degradation rate by adding urethane groups in scaffold structures. FTIR and NMR analysis was used to characterize the chemical bonds. Morphology, porosity, conductivity and degradation rate of scaffolds were also evaluated. To assess the cell–scaffold interaction, PC-12 cell line was cultured on the scaffolds. Results showed that the degradation rate of composite samples significantly increased in 50 time period. It seems that these results suggest that the composite fibrous scaffolds having proportions of UPCL/PCL/PANI45:20:35 exhibit the most balanced properties that meet all of the required specifications for neural cells and possess a potential application in neural tissue engineering.