Clinical correlates of CT imaging-derived phenotypes among lean and overweight patients with hepatic steatosis.

The objective of this study is to define CT imaging derived phenotypes for patients with hepatic steatosis, a common metabolic liver condition, and determine its association with patient data from a medical biobank. There is a need to further characterize hepatic steatosis in lean patients, as its epidemiology may differ from that in overweight patients. A deep learning method determined the spleen-hepatic attenuation difference (SHAD) in Hounsfield Units (HU) on abdominal CT scans as a quantitative measure of hepatic steatosis. The patient cohort was stratified by BMI with a threshold of 25 kg/m2 and hepatic steatosis with threshold SHAD ≥ - 1 HU or liver mean attenuation ≤ 40 HU. Patient characteristics, diagnoses, and laboratory results representing metabolism and liver function were investigated. A phenome-wide association study (PheWAS) was performed for the statistical interaction between SHAD and the binary characteristic LEAN. The cohort contained 8914 patients-lean patients with (N = 278, 3.1%) and without (N = 1867, 20.9%) steatosis, and overweight patients with (N = 1863, 20.9%) and without (N = 4906, 55.0%) steatosis. Among all lean patients, those with steatosis had increased rates of cardiovascular disease (41.7 vs 27.8%), hypertension (86.7 vs 49.8%), and type 2 diabetes mellitus (29.1 vs 15.7%) (all p < 0.0001). Ten phenotypes were significant in the PheWAS, including chronic kidney disease, renal failure, and cardiovascular disease. Hepatic steatosis was found to be associated with cardiovascular, kidney, and metabolic conditions, separate from overweight BMI.

Overview of the Important Factors Influencing the Performance of Eco-Friendly Brake Pads.

The braking system is a crucial element in automotive safety. In order for the braking mechanism to function effectively, the brake pads' durability as well as quality are crucial aspects to take into account. A brake pad is a part of a vehicle that holds the wheel rotation so that braking can occur. Asbestos, which is harmful to human health, is a raw material that is recently being widely used as a material mixture for the manufacturing of brake pads. Many efforts have been made by researchers to find other natural alternative materials to replace the use of asbestos. Natural materials that have received much attention and research include coconut fiber, wood powder or flour, bamboo fiber, shell powder, etc. This review paper focuses on analyzing the main parameters that affect brake pad performance. The composition of filler and fiber types of reinforcement for polymer composites is discussed. Previous studies' information on the fabrication and testing of brake pads are also highlighted. Furthermore, the findings of this review can provide researchers and academicians with useful information and points to consider for further research.

Biodegradation of Polylactic Acid-Based Bio Composites Reinforced with Chitosan and Essential Oils as Anti-Microbial Material for Food Packaging.

This study aims to produce and investigate the potential of biodegradable Polylactic Acid (PLA)-based composites mixed with chitosan and Turmeric Essential Oil (TEO) as an anti-microbial biomaterial. PLA has good barrier properties for moisture, so it is suitable for use as a raw material for making packaging and is included in the GRAS (Generally Recognized As Safe). Chitosan is a non-toxic and antibacterial cationic polysaccharide that needs to be improved in its ability to fight microbes. TEO must be added to increase antibacterial properties due to a large number of hydroxyl (-OH) and carbonyl functional groups. The samples were prepared in three different variations: 2 g of chitosan, 0 mL TEO and 0 mL glycerol (Biofilm 1), 3 g of chitosan, 0.3 mL TEO and 0.5 mL of glycerol (Biofilm 2), and 4 g of chitosan, 0.3 of TEO and 0.5 mL of glycerol (Biofilm 3). The final product was characterized by its functional group through Fourier transform infrared (FTIR); the functional groups contained by the addition of TEO are C-H, C=O, O-H, and N-H with the extraction method, and as indicated by the emergence of a wide band at 3503 cm-1, turmeric essential oil interacts with the polymer matrix by creating intermolecular hydrogen bonds between their terminal hydroxyl group and the carbonyl groups of the ester moieties of both PLA and Chitosan. Thermogravimetric analysis (TGA) of PLA as biofilms, the maximum temperature of a biofilm was observed at 315.74 °C in the variation of 4 g chitosan, 0.3 mL TEO, and 0.5 mL glycerol (Biofilm 3). Morphological conditions analyzed under scanning electron microscopy (SEM) showed that the addition of TEO inside the chitosan interlayer bound chitosan molecules to produce solid particles. Chitosan and TEO showed increased anti-bacterial activity in the anti-microbial test. Furthermore, after 12 days of exposure to open areas, the biofilms generated were able to resist S. aureus and E. coli bacteria.

The Effect of Hybridisation on Mechanical Properties and Water Absorption Behaviour of Woven Jute/Ramie Reinforced Epoxy Composites.

Recently, the most critical issue related to the use of natural fibre-reinforced polymer composites (NFRPC) is the degradation properties of composites exposed to the environment. NFRPC's moisture absorption behaviour has adverse effects on the composite's mechanical properties and dimensional stability. The purpose of this study is to analyse the mechanical properties of epoxy composites reinforced by jute-ramie hybridisation. This study also analysed the effect of stacking sequence hybridisation of the jute-ramie composite on water absorption behaviour. A five-layer different type of stacking sequence of single and hybrid jute-ramie is produced with the hand lay-up method. The results obtained from this study found that the mechanical properties and water absorption behaviour of a single jute fibre are lower compared to a single ramie fibre. The hybrid of jute-ramie has been able to increase the performance of composite compared to pure jute composites. The mechanical properties of the hybrid jute-ramie composite show a reduction effect after exposure to an aqueous environment due to the breakdown of fibre matrix interfacial bonding. However, after 28 days of immersion, all types of the stacking sequence's mechanical properties are still higher than that of pure epoxy resin. In conclusion, the appropriate sequence of stacking and selecting the material used are two factors that predominantly affect the mechanical properties and water absorption behaviour. The hybrid composites with the desired and preferable properties can be manufactured using a hand-lay-up technique and used in the various industrial applications.

Application of Micromechanical Modelling for the Evaluation of Elastic Moduli of Hybrid Woven Jute-Ramie Reinforced Unsaturated Polyester Composites.

Woven laminated composite has gained researchers' and industry's interest over time due to its impressive mechanical performance compared to unidirectional composites. Nevertheless, the mechanical properties of the woven laminated composite are hard to predict. There are many micromechanical models based on unidirectional composite but limited to the woven laminated composite. The current research work was conducted to evaluate elastic moduli of hybrid jute-ramie woven reinforced unsaturated polyester composites using micromechanical effectiveness unidirectional models, such as ROM, IROM, Halpin-Tsai, and Hirsch, which are based on stiffness. The hybrid jute-ramie laminated composite was fabricated with different layering sizes, and the stacking sequence was completed via hand lay-up with the compression machine. Tensile modulus values for hybrid composites are between those for single jute and single ramie. Obtained p-values less than 0.05 prove the relationship between layering size and tensile modulus. This study showed that several micromechanical models, such as Halpin-Tsai's predicted value of homogenized mechanical properties, were in good agreement with the experimental result. In the case of the hybrid composite, the micromechanical model deviates from the experimental result. Several modifications are required to improve the current existing model. A correlation function was calculated based on the differences between the elastic modulus values determined experimentally and those derived from each micromechanical model calculation.

Detecting opinion spams through supervised boosting approach.

Product reviews are the individual's opinions, judgement or belief about a certain product or service provided by certain companies. Such reviews serve as guides for these companies to plan and monitor their business ventures in terms of increasing productivity or enhancing their product/service qualities. Product reviews can also increase business profits by convincing future customers about the products which they have interest in. In the mobile application marketplace such as Google Playstore, reviews and star ratings are used as indicators of the application quality. However, among all these reviews, hereby also known as opinions, spams also exist, to disrupt the online business balance. Previous studies used the time series and neural network approach (which require a lot of computational power) to detect these opinion spams. However, the detection performance can be restricted in terms of accuracy because the approach focusses on basic, discrete and document level features only thereby, projecting little statistical relationships. Aiming to improve the detection of opinion spams in mobile application marketplace, this study proposes using statistical based features that are modelled through the supervised boosting approach such as the Extreme Gradient Boost (XGBoost) and the Generalized Boosted Regression Model (GBM) to evaluate two multilingual datasets (i.e. English and Malay language). From the evaluation done, it was found that the XGBoost is most suitable for detecting opinion spams in the English dataset while the GBM Gaussian is most suitable for the Malay dataset. The comparative analysis also indicates that the implementation of the proposed statistical based features had achieved a detection accuracy rate of 87.43 per cent on the English dataset and 86.13 per cent on the Malay dataset.