Strength evaluation of granite block samples with different predictive models

Over the last decade, application of soft computing techniques has rapidly grown up in different scientific fields, especially in rock mechanics. One of these cases relates to indirect assessment of uniaxial compressive strength (UCS) of rock samples with different artificial intelligent-based methods. In fact, the main advantage of such systems is to readily remove some difficulties arising in direct assessment of UCS, such as time-consuming and costly UCS test procedure. This study puts an effort to propose four accurate and practical predictive models of UCS using artificial neural network (ANN), hybrid ANN with imperialism competitive algorithm (ICA–ANN), hybrid ANN with artificial bee colony (ABC–ANN) and genetic programming (GP) approaches. To reach the aim of the current study, an experimental database containing a total of 71 data sets was set up by performing a number of laboratory tests on the rock samples collected from a tunnel site in Malaysia. To construct the desired predictive models of UCS based on training and test patterns, a combination of several rock characteristics with the most influence on UCS has been used as input parameters, i.e. porosity (n), Schmidt hammer rebound number (R), p-wave velocity (V_p) and point load strength index (Is(50)). To evaluate and compare the prediction precision of the developed models, a series of statistical indices, such as root mean squared error (RMSE), determination coefficient (R²) and variance account for (VAF) are utilized. Based on the simulation results and the measured indices, it was observed that the proposed GP model with the training and test RMSE values 0.0726 and 0.0691, respectively, gives better performance as compared to the other proposed models with values of (0.0740 and 0.0885), (0.0785 and 0.0742), and (0.0746 and 0.0771) for ANN, ICA–ANN and ABC–ANN, respectively. Moreover, a parametric analysis is accomplished on the proposed GP model to further verify its generalization capability. Hence, this GP-based model can be considered as a new applicable equation to accurately estimate the uniaxial compressive strength of granite block samples.

     

Study of Tire Particle Mixing in a Moving and Stirred Bed Vacuum Pyrolysis Reactor

The paper studies the motion of scrap tire shreds in a moving and stirred bed vacuum pyrolysis reactor. The reactor configuration is a novel concept. The pattern and the residence time distribution (RTD) of the particle motion in the reactor were investigated using tracers, for different feed rates and blade speeds. It was shown that the particle motion in the reactor is plug flow nature with intermediate dispersion (σ² = 0.02—0.055). The mean residence time is in the range of 7—23 min, depending on the speed of the blades and the feed rate. The ratio of mean particle speed and the speed of blades v_m/v_b varied between 0.03 and 0.07.     

Theoretical Study of Interplay of Superconductivity and Ferromagnetism in Hybrid Rutheno–Cuprate Superconductors RuSr2RCu2O8

We consider the extended two-band s–f model with additional terms, describing intersite Cooper pairs’ interaction between 4f (5f) and conduction electrons. Following Green’s function technique and equation of motion method, self-consistent equations for superconducting order parameter (Δ) and magnetic order parameter (m _f ) are derived. The expressions for specific heat, density of states, and free energy are also derived. The theory has been applied to explain the coexistence of superconductivity and ferromagnetism in hybrid rutheno-cuprate superconductors RuSr₂RECu₂O₈ (RE = Gd, Eu). The theory shows that it is possible to become superconducting if the system is already ferromagnetic. A study of specific heat, density of states and free energy is also presented. The agreement between theory and experimental observations is quite satisfactory.      

The reliability of the diagnostic features in patients with narcolepsy

This study determined the test-retest reliability of the polysomnographic findings in narcolepsy. The diagnosis of narcolepsy was based on clinical symptoms and polysomnographic signs. Control subjects were screened before participation and were split based on their screening multiple sleep latency test (MSLT) into high- and low-MSLT groups. Subjects completed two polysomnographic evaluations with at least 5 days between laboratory tests. Narcoleptics had lower sleep efficiencies and high stage 1% when compared to the low MSLT control group. They had more awakenings and less stage 2% than the control groups. Narcoleptics had a shorter latency to 1 when compared to the high-MSLT group but comparable to that of the low-MSLT group. Narcoleptics had a higher number of sleep-onset rapid eye movement periods (SOREMPs) than both control groups. The MSLT scores were stable across the two evaluations and showed a statistically significant correlation. Twenty-eight of the 30 narcoleptic subjects had two or more SOREMPs on reevaluation. None of the controls had multiple SOREMPs. Thus, multiple SOREMPs were shown to be a reliable finding in patients with narcolepsy.     

Modelling the Effective Thermal Conductivity in Polydispersed Bed Systems: A Unified Approach using the Linear Packing Theory and Unit Cell Model

A comprehensive, unified approach, using the Linear Packing Theory and Unit Cell Model, is proposed for calculating of the effective thermal conductivity of polydispersed packed beds. In this new approach, the effect of packing density is incorporated by the use of (i) an initial porosity to take into account the packing of mono‐sized particles, and (ii) the packing size ratio as a measure of the particle‐particle interaction. The proposed approach was validated with the experimental measurements of binary and ternary beds. This new approach demonstrates that the effective thermal conductivity of beds composed of polydispersed particles can be simulated for any composition without the need to measure the in situ porosity.     

Effect of cholesterol removal on the granulation behaviour of low‐cholesterol ghee

Grain formation is one of the critical attributes affecting consumer acceptability of ghee. It was observed that both control ghee and low‐cholesterol ghee had grains of 0.236 ± 0.006 and 0.250 ± 0.002 mm size after incubation at 29 °C for 24 h, respectively. The maximum grain yield was 63 ± 2.60% and 68 ± 1.15% at 26 °C in control and low‐cholesterol ghee, respectively. Ghee grains in both the cases were stable over a temperature range of 25° to 36 °C. Time taken by both the samples for onset of nucleation was 50 min. The study revealed that cholesterol removal did not affect the crystallisation behaviour.     

The use of new intelligent techniques in designing retaining walls

Engineering with Computers - The stability of retaining walls against overturning is analyzed in this study using artificial intelligence methods. Five input parameters including wall height, wall...     

Affinity Versus Label‐Free Isolation of Circulating Tumor Cells: Who Wins?

The study of circulating tumor cells (CTCs) has been made possible by many technological advances in their isolation. Their isolation has seen many fronts, but each technology brings forth a new set of challenges to overcome. Microfluidics has been a key player in the capture of CTCs and their downstream analysis, with the aim of shedding light into their clinical application in cancer and metastasis. Researchers have taken diverging paths to isolate such cells from blood, ranging from affinity‐based isolation targeting surface antigens expressed on CTCs, to label‐free isolation taking advantage of the size differences between CTCs and other blood cells. For both major groups, many microfluidic technologies have reported high sensitivity and specificity for capturing CTCs. However, the question remains as to the superiority among these two isolation techniques, specifically to identify different CTC populations. This review highlights the key aspects of affinity and label‐free microfluidic CTC technologies, and discusses which of these two would be the highest benefactor for the study of CTCs.