Evaluation of Mechanical and Wear Properties of Ceramic and Inorganic compounds based Composite via PM route and Optimization through Robust design technique

The present research study investigates the Mechanical, Physical, and Tribological properties of powder metallurgy (PM) produced AA6063 alloy reinforced with silicon nitride (Si3N4) and copper nitrate (CuN2O6). Incorporation of Si3N4 & CuN2O6 reinforcement in matrix material ranged from 6 to 12 % Si3N4 in a 6-step interval and 2 to 6 %CuN2O6 in a two-step interval. The characterizations were made on the PM-produced specimens using OM, EDS, XRD, and Hardness. The reinforcement particles were uniformly distributed, which was attributed to a homogeneous mixer of matrix and reinforcements. The test findings show that as the reinforcing percentage of the ceramic and inorganic compound increases, properties such as hardness and density rise considerably and monolithically. The existence of phases such as Si3N4 and CuN2O6 reinforcement in the AA6063 matrix was ensured by X-ray diffraction. The hardness of AA6063/12%Si3N4/6%CuN2O6 increased by 88% over the base alloy due to a mismatch in thermal expansion between the Al matrix and reinforcement, which causes massive internal stress, causing the aluminium matrix to plastically deform to accommodate the reduced volume expansion of Si3N4 and CuN2O6 particles. The dry sliding wear test was determined using the Pin-on-Disc method, and the results show that the composite is more wear-resistant. An orthogonal array and analysis of variance were utilized to evaluate the solution, including parameters using the Taguchi robust design technique. The weight percentage of the Si3N4/CuN2O6 compound and the relationship between weight % of reinforcement and applied load had the most significant impact on composite wear resistance. The produced composite's wear morphology was studied using images from a scanning electron microscope and energy dispersive spectroscopy.

Gait Stability Measurement by Using Average Entropy

Gait stability has been measured by using many entropy-based methods. However, the relation between the entropy values and gait stability is worth further investigation. A research reported that average entropy (AE), a measure of disorder, could measure the static standing postural stability better than multiscale entropy and entropy of entropy (EoE), two measures of complexity. This study tested the validity of AE in gait stability measurement from the viewpoint of the disorder. For comparison, another five disorders, the EoE, and two traditional metrics methods were, respectively, used to measure the degrees of disorder and complexity of 10 step interval (SPI) and 79 stride interval (SI) time series, individually. As a result, every one of the 10 participants exhibited a relatively high AE value of the SPI when walking with eyes closed and a relatively low AE value when walking with eyes open. Most of the AE values of the SI of the 53 diseased subjects were greater than those of the 26 healthy subjects. A maximal overall accuracy of AE in differentiating the healthy from the diseased was 91.1%. Similar features also exists on those 5 disorder measurements but do not exist on the EoE values. Nevertheless, the EoE versus AE plot of the SI also exhibits an inverted U relation, consistent with the hypothesis for physiologic signals.

Key factors explaining critical swimming speed in freshwater fish: a review and statistical analysis for Iberian species

Swimming performance is a key feature that mediates fitness and survival in aquatic animals. Dispersal, habitat selection, predator–prey interactions and reproduction are processes that depend on swimming capabilities. Testing the critical swimming speed (Ucrit) of fish is the most straightforward method to assess their prolonged swimming performance. We analysed the contribution of several predictor variables (total body length, experimental water temperature, time step interval between velocity increments, species identity, taxonomic affiliation, native status, body shape and form factor) in explaining the variation of Ucrit, using linear models and random forests. We compiled in total 204 studies testing Ucrit of 35 inland fishes of the Iberian Peninsula, including 17 alien species that are non-native to that region. We found that body length is largely the most important predictor of Ucrit out of the eight tested variables, followed by family, time step interval and species identity. By contrast, form factor, temperature, body shape and native status were less important. Results showed a generally positive relationship between Ucrit and total body length, but regression slopes varied markedly among families and species. By contrast, linear models did not show significant differences between native and alien species. In conclusion, the present study provides a first comprehensive database of Ucrit in Iberian freshwater fish, which can be thus of considerable interest for habitat management and restoration plans. The resulting data represents a sound foundation to assess fish responses to hydrological alteration (e.g. water flow tolerance and dispersal capacities), or to categorize their habitat preferences.

Investigating Optimal Time Step Intervals of Imaging for Data Quality through a Novel Fully-Automated Cell Tracking Approach

Computer-based fully-automated cell tracking is becoming increasingly important in cell biology, since it provides unrivalled capacity and efficiency for the analysis of large datasets. However, automatic cell tracking’s lack of superior pattern recognition and error-handling capability compared to its human manual tracking counterpart inspired decades-long research. Enormous efforts have been made in developing advanced cell tracking packages and software algorithms. Typical research in this field focuses on dealing with existing data and finding a best solution. Here, we investigate a novel approach where the quality of data acquisition could help improve the accuracy of cell tracking algorithms and vice-versa. Generally speaking, when tracking cell movement, the more frequent the images are taken, the more accurate cells are tracked and, yet, issues such as damage to cells due to light intensity, overheating in equipment, as well as the size of the data prevent a constant data streaming. Hence, a trade-off between the frequency at which data images are collected and the accuracy of the cell tracking algorithms needs to be studied. In this paper, we look at the effects of different choices of the time step interval (i.e., the frequency of data acquisition) within the microscope to our existing cell tracking algorithms. We generate several experimental data sets where the true outcomes are known (i.e., the direction of cell migration) by either using an effective chemoattractant or employing no-chemoattractant. We specify a relatively short time step interval (i.e., 30 s) between pictures that are taken at the data generational stage, so that, later on, we may choose some portion of the images to produce datasets with different time step intervals, such as 1 min, 2 min, and so on. We evaluate the accuracy of our cell tracking algorithms to illustrate the effects of these different time step intervals. We establish that there exist certain relationships between the tracking accuracy and the time step interval associated with experimental microscope data acquisition. We perform fully-automatic adaptive cell tracking on multiple datasets, to identify optimal time step intervals for data acquisition, while at the same time demonstrating the performance of the computer cell tracking algorithms.

An Efficient Seven-Step Block Method for Numerical Solution of SIR and Growth Model

In this article, a new implicit continuous block method is developed using the interpolation and collocation techniques via Power series as the basis function. A constant step length within a seven-step interval of integration was adopted. The selected grid points were evaluated to get a continuous linear multistep method. The evaluation of the continuous method at the non-interpolation points produces the discrete schemes which form the block. The basic properties of the block method were investigated and found to be consistent, zero stable and hence convergent. The new method was tested on real life problems namely: SIR and Growth model. The results were found to compare favourably with the existing methods in terms of accuracy and efficiency. Keywords: Block method, Growth Model, implicit, power series and SIR model.

The Ability of Ultrasonic Backscatter Parametric Imaging to Characterize Bovine Trabecular Bone

The ultrasonic backscatter technique holds the promise of characterizing bone density and microstructure. This paper conducts ultrasonic backscatter parametric imaging based on measurements of apparent integrated backscatter (AIB), spectral centroid shift (SCS), frequency slope of apparent backscatter (FSAB), and frequency intercept of apparent backscatter (FIAB) for representing trabecular bone mass and microstructure. We scanned 33 bovine trabecular bone samples using a 7.5 MHz focused transducer in a 20 mm × 20 mm region of interest (ROI) with a step interval of 0.05 mm. Images based on the ultrasonic backscatter parameters (i.e., AIB, SCS, FSAB, and FIAB) were constructed to compare with photographic images of the specimens as well as two-dimensional (2D) μ-CT images from approximately the same depth and location of the specimen. Similar structures and trabecular alignments can be observed among these images. Statistical analyses demonstrated that the means and standard deviations of the ultrasonic backscatter parameters exhibited significant correlations with bone density (|R| = 0.45-0.78, p < 0.01) and bone microstructure (|R| = 0.44-0.87, p < 0.001). Some bovine trabecular bone microstructure parameters were independently associated with the ultrasonic backscatter parameters (Δ R2 = 4.18%-44.45%, p < 0.05) after adjustment for bone apparent density (BAD). The results show that ultrasonic backscatter parametric imaging can provide a direct view of the trabecular microstructure and can reflect information about the density and microstructure of trabecular bone.

Sensitivity of the Vertical Response of Footbridges to the Frequency Variability of Crossing Pedestrians

Contemporary design codes and guides for vibration serviceability assessment include some simplifications in load modelling. The same statistical distribution of the inter-pedestrian variability of the step interval (frequency) is proposed for all applications. Moreover, walking loads are considered to be periodic. The intra-pedestrian variability of the step interval is neglected. A more realistic load modelling trying to overcome the limitations of the codes is intended in this paper. Instead of a single mean value of the inter-pedestrian distribution of walking speed, a range of possible variation, which account for the real variations that occur in practice depending on the footbridge location and usage, is considered. An enhanced model is proposed in this paper to reproduce statistically both the intra- and inter-pedestrian variability of the step interval as a function of the walking speed distribution. This innovative model is then applied to study the sensitivity of the vertical response of footbridges to the variability of the step interval and to evaluate the influence of the aforementioned simplifications on the predicted characteristic responses. For this purpose, low-frequency footbridges excited by single-pedestrian crossings are chosen. The response is statistically characterized through Monte Carlo numerical simulations including 720 different configurations and 10,000 load cases in each configuration. Results of the study provide an overview of the influence of the footbridge and load parameters on the responses, which can be useful in practical applications where human–structure interactions are negligible. As for the simplifications of the codes, it is found that either using a single distribution to model the inter-pedestrian variability of the spatiotemporal parameters or neglecting the intra-pedestrian variability can lead to a significant underestimation of the characteristic response of footbridges.