Prediction of Fracture Parameters of High Strength and Ultra-High Strength Concrete Beams using Minimax Probability Machine Regression and Extreme Learning Machine

This paper deals with the development of models for prediction of facture parameters, namely, fracture energy and ultimate load of high strength and ultra high strength concrete based on Minimax Probability Machine Regression (MPMR) and Extreme Learning Machine (ELM). MPMR is developed based on Minimax Probability Machine Classification (MPMC). ELM is the modified version of Single Hidden Layer Feed Foreword Network (SLFN). MPMR and ELM has been used as regression techniques. Mathematical models have been developed in the form of relation between several input variables such as beam dimensions, water cement ratio, compressive strength, split tensile strength, notch depth, and modulus of elasticity and output is fracture energy and ultimate load A total of 87 data sets (input-output pairs) are used, 61 of which are used to train the model and 26 are used to test the models. The data-sets used in this study are derived from experimental results. A comparative study has been presented between the developed MPMR and ELM models. The results showed that the developed models give reasonable performance for prediction of fracture energy and ultimate load.     

Acoustic of monolithic dome structures

Monolithic dome structures were built in the 1970s in Europe and America. These dome structures share common benefits of being cost-efficient, earth-friendly, extremely durable, and easily maintained. Monolithic shells are easily constructed and are extremely cost-effective. Monolithic domes respond efficiently to any climate, even to extremely cold or hot temperatures. In terms of utility savings, monolithic domes can cut electricity consumption by up to one-third, thereby saving 60–70% of total energy costs. Moreover, monolithic structures provide the highest survivability rates from destructions. The interior of monolithic domes have perfect, concave shapes to ensure that sound travels through the dome and perfectly collected at different vocal points. These dome structures are utilized for domestic use because the scale allows the focal points to be positioned across daily life activities, thereby affecting the soni ccomfort of the internal space. This study examines the various acoustic treatments and parametric configurations of monolithic dome sizes. A geometric relationship of acoustic treatment and dome radius is established to provide architects guidelines on the correct selection of absorption needed to maintain the acoustic comfort of these special spaces.     

Effect of hydrogen addition using on-board alkaline electrolyser on SI engine emissions and combustion

In this study, an electrolyser was used to supply hydrogen to the SI engine. Firstly, the appropriate operation point for the electrolyser was determined by adjusting the amount of KOH in the electrolyte to 5%, 10%, 20% and 30% by mass, and applying 12 V, 16 V, 20 V, 24 V and 28 V voltages. Tests were first carried out with the gasoline without the use of an electrolyser, followed by operating the electrolyser at the appropriate point and sending obtained H₂ and O₂ to the engine in addition to the gasoline. The SI engine was operated between 2500 rpm and 3500 rpm engine speeds with and without hydrogen addition. Cylinder pressure, the amount of gasoline, H₂ and O₂ consumed by the engine and the emission data were collected from the test system at the aforementioned engine speeds. Furthermore, indicated engine torque, indicated specific energy consumption, specific emissions and HRR values were calculated. According to the results obtained, improvement in ISEC values was observed, and CO and THC values were improved by up to 21.3% and 86.1% respectively. Even though the dramatic increase in NO_x emissions cannot be averted, they can be controlled by equipment such as EGR three-way catalytic converter.     

Effect of pretreatments and drying methods on physico‐chemical,sensory characteristics and nutritional value of oyster mushroom

This study was aimed to evaluate the effect of pretreatments and drying methods on the chemical, physico‐chemical, sensory characteristics and nutritional value of oyster mushroom. Chemical analysis of oyster mushroom (OM) showed that the values content were increased by many times when calculated on dry weight basis. Nine treatments of dried mushroom powders (DMP) were prepared using three drying methods (hot air drying, vacuum drying, and sun drying). Also, three pretreatments of each method of drying were used (untreated, blanching by steaming without or with steeped in 0.5% citric acid solution for 30 min).The results and statistical analysis revealed that, sun dried oyster mushroom samples (without pretreatments) were found to be the best. The DMP samples resulting of the sun drying had a highest physico‐chemical properties, sensory evaluation scores, and contents of the mineral elements and amino acids as compared to other pretreatments and drying methods.

Practical applications

Fresh mushrooms have high water content, high enzymatic activity and hence are highly perishable. Thus, in this study nine treatments of dried mushroom powders (DMP) were prepared using three drying methods (hot air drying, vacuum drying and sun drying).Also, three pretreatments of each method of drying were used (untreated, blanching by steaming without or with steeped in citric acid).The DMP samples (untreated) resulting of the sun drying were better than other pretreatments and drying methods regarding quality attributes.     

Classification of Hydrogels Based on Their Source: A Review and Application in Stem Cell Regulation

Stem cells are recognized by their self-renewal ability and can give rise to specialized progeny. Hydrogels are an established class of biomaterials with the ability to control stem cell fate via mechanotransduction. They can mimic various physiological conditions to influence the fate of stem cells and are an ideal platform to support stem cell regulation. This review article provides a summary of recent advances in the application of different classes of hydrogels based on their source (e.g., natural, synthetic, or hybrid). This classification is important because the chemistry of substrate affects stem cell differentiation and proliferation. Natural and synthetic hydrogels have been widely used in stem cell regulation. Nevertheless, they have limitations that necessitate a new class of material. Hybrid hydrogels obtained by manipulation of the natural and synthetic ones can potentially overcome these limitations and shape the future of research in application of hydrogels in stem cell regulation.     

A chemometric approach for the quantification of free fatty acids in cottonseed oil by Fourier transform infrared spectroscopy

The aim of this study was to quantify free fatty acid in cottonseed oil (Gossypium) variety by a chemometric approach using Fourier transform infrared spectroscopy. Calibration standards were prepared by gravimetrical mixing of oleic acid (0.1–40 g/100 g) in neutralized cottonseed oil containing <0.1% free fatty acids. Fourier transform infrared technique coupled with partial least square and principle component regression models were used to develop calibrations in the specific absorption region of carbonyl between 1690–1727 cm^?1. On the basis of regression coefficient and evaluated free fatty acids results with comparison to titration method, partial least square was found to be more accurate than principle component regression calibration model. All the analyzed cottonseed oil varieties showed high content of free fatty acids in the range of 17.1–38.5%. The results of the present study indicated that Fourier transform infrared method in combination with partial least square or principle component regression could be used as a greener alternative to the standard titration method.