Influence of accelerated curing on the compressive strength of polymer-modified concrete

In recent building practice, rapid construction is one of the principal requisites. Furthermore, in designing concrete structures, compressive strength is the most significant of all parameters. While 3-d and 7-d compressive strength reflects the strengths at early phases, the ultimate strength is paramount. An effort has been made in this study to develop mathematical models for predicting compressive strength of concrete incorporating ethylene vinyl acetate (EVA) at the later phases. Kolmogorov-Smirnov (KS) goodness-of-fit test was used to examine distribution of the data. The compressive strength of EVA-modified concrete was studied by incorporating various concentrations of EVA as an admixture and by testing at ages of 28, 56, 90, 120, 210, and 365 d. An accelerated compressive strength at 3.5 hours was considered as a reference strength on the basis of which all the specified strengths were predicted by means of linear regression fit. Based on the results of KS goodness-of-fit test, it was concluded that KS test statistics value (D) in each case was lower than the critical value 0.521 for a significance level of 0.05, which demonstrated that the data was normally distributed. Based on the results of compressive strength test, it was concluded that the strength of EVA-modified specimens increased at all ages and the optimum dosage of EVA was achieved at 16% concentration. Furthermore, it was concluded that predicted compressive strength values lies within a 6% difference from the actual strength values for all the mixes, which indicates the practicability of the regression equations. This research work may help in understanding the role of EVA as a viable material in polymer-based cement composites.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

Electrical and magnetic properties of lithium borate glass containing iron

Journal of Materials Science Letters -     

Effect of the addition of Fe2O3 and heat treatment duration on the magnetic susceptibility of V2O5-P2O5-B2O3 glass system

The effect of the addition of Fe₂O₃ and heat treatment duration on the magnetic susceptibility of vanadium borophosphate glass were studied. The magnetic susceptibility of glass samples was found to increase with increasing Fe₂O₃ content, which may be explained by the formation of the FeO₆ group and the change of Fe²⁺ to Fe³⁺ which has higher paramagnetic properties. No detectable changes in the magnetic susceptibility with heat treatment for the samples containing 0.0, 0.5 and 1.0 mol% Fe₂O₃ was observed. The magnetic susceptibility for the heat treated samples containing 2.5, 5.0 and 7.5 mol% Fe₂O₃ decreases sharply with increasing duration of heat treatment up to 6 h and then remains almost constant. The sharp decrease in magnetic susceptibility of 2.5 mol% Fe₂O₃ is attributed to the increase in the number of ferrous ions. The sharp decrease for samples containing 5.0 and 7.5 mol% Fe₂O₃ is attributed to the increase in the number of Fe³⁺ in tetrahedral co-ordination. The rate of crystallization owing to the heat treatment was calculated and was found to increase with increasing iron oxide content. The geometry of crystallization was found to be in three-, two-and one-dimension(s) for samples containing 2.5, 5.0 and 7.5 mol% Fe₂O₃, respectively.     

A panoramic view of Li7P3S11 solid electrolytes synthesis,structural aspects and practical challenges for all-solid-state lithium batteries

The development of an inorganic electrochemical stable solid-state electrolyte is essentially responsible for future state-of-the-art all-solid-state lithium batteries (ASSLBs). Because of their advantages in safety, working temperature, high energy density, and packaging, ASSLBs can develop an ideal energy storage system for modern electric vehicles (EVs). A solid electrolyte (SE) model must have an economical synthesis approach, exhibit electrochemical and chemical stability, high ionic conductivity, and low interfacial resistance. Owing to its highest conductivity of 17 mS·cm^-1, and deformability, the sulfide-based Li₇P₃S₁₁ solid electrolyte is a promising contender for the high-performance bulk type of ASSLBs. Herein, we present a current glimpse of the progress of synthetic procedures, structural aspects, and ionic conductivity improvement strategies. Structural elucidation and mechanistic approaches have been extensively discussed by using various characterization techniques. The chemical stability of Li₇P₃S₁₁ could be enhanced via oxide doping, and hard and soft acid/base (HSAB) concepts are also discussed. The issues to be undertaken for designing the ideal solid electrolytes, interfacial challenges, and high energy density have been discoursed. This review aims to provide a bird's eye view of the recent development of Li₇P₃S₁₁-based solid-state electrolyte applications and explore the strategies for designing new solid electrolytes with a target-oriented approach to enhance the efficiency of high energy density all-solid-state lithium batteries.     

Modeling and Analysis of Temperature Compensation for Multi-temperature Zone Sintering Furnace Temperature Sensing

International Journal of Control, Automation and Systems - The surface temperature of workpieces in a multi-temperature zone sintering furnace is an important parameter to characterize the...     

Brain tumor classification from multi-modality MRI using wavelets and machine learning

In this paper, we propose a brain tumor segmentation and classification method for multi-modality magnetic resonance imaging scans. The data from multi-modal brain tumor segmentation challenge (MICCAI BraTS 2013) are utilized which are co-registered and skull-stripped, and the histogram matching is performed with a reference volume of high contrast. From the preprocessed images, the following features are then extracted: intensity, intensity differences, local neighborhood and wavelet texture. The integrated features are subsequently provided to the random forest classifier to predict five classes: background, necrosis, edema, enhancing tumor and non-enhancing tumor, and then these class labels are used to hierarchically compute three different regions (complete tumor, active tumor and enhancing tumor). We performed a leave-one-out cross-validation and achieved 88% Dice overlap for the complete tumor region, 75% for the core tumor region and 95% for enhancing tumor region, which is higher than the Dice overlap reported from MICCAI BraTS challenge.     

Potential Chemical Markers for the Identification of Irradiated Sausages

Abstract: Hydrocarbons, gas compounds, and off‐odor volatiles were determined for irradiated (0 or 5 kGy) commercial sausages with different fat contents (16% and 29%) during a 60‐d storage period at 4 °C. Total of 4 hydrocarbons (C14:1, C15:0, C16:2, and C17:1) were detected only in irradiated sausages: the amount of C16:2 was the highest, followed by C17:1, C14:1, and C15:0. The concentrations of hydrocarbons decreased significantly (P < 0.05) with storage, but were still detectable at the end of 60‐d storage. Irradiated sausages produced significantly higher amounts of CO than the nonirradiated ones. CH₄ was detected only in irradiated sausages. Dimethyl disulfide was detected only in irradiated sausages and its concentration decreased significantly (P < 0.05) with storage. Fat content of sausages showed a significant effect on the production and retention of hydrocarbons, gas compounds, and sulfur volatiles in irradiated sausages during storage. Some hydrocarbons (C16:2, C17:1, C14:1, and C15:0), CH₄, and dimethyl disulfide were only found in irradiated sausages indicating that these compounds can be used as potential markers for irradiated sausages.