On dual-phase-lag thermoelasticity theory with memory-dependent derivative

A new mathematical model of generalized thermoelasticity with memory-dependent derivatives for the dual-phase-lag heat conduction law is constructed. The governing equations of the new model are applied to a half-space subjected to ramp-type heating. Laplace transforms technique is used. The solution is obtained for different types of functions representing the thermal shock and for different values of the parameter of the time fraction derivative of the model. The effects of time-delay and arbitrary kernel function on elastic material are studied and represented graphically. The predictions of the theory are discussed and compared with dynamic classical coupled theory.     

Sub‐Micron Polymeric Stomatocytes as Promising Templates for Confined Crystallization and Diffraction Experiments

The possibility of using sub‐micrometer polymeric stomatocytes is investigated to effectuate confined crystallization of inorganic compounds. These bowl‐shaped polymeric compartments facilitate confined crystallization while their glassy surfaces provide their crystalline cargos with convenient shielding from the electron beam's harsh effects during transmission electron microscopy experiments. Stomatocytes host the growth of a single nanocrystal per nanocavity, and the electron diffraction experiments reveal that their glassy membranes do not interfere with the diffraction patterns obtained from their crystalline cargos. Therefore, it is expected that the encapsulation and crystallization within these compartments can be considered as a promising template (nanovials) that hold and protect nanocrystals and protein clusters from the direct radiation damage before data acquisition, while they are examined by modern crystallography methodologies such as serial femtosecond crystallography.     

Thermal blooming and photoluminescence characterizations of sol–gel CdO–SiO<Subscript>2</Subscript> with different nanocomposite

The CdO NPs was synthesized using the sol–gel method and the nanoparticles were characterized using an UV–Vis spectrophotometer, with shape and size were examined by SEM and XRD. The XRD analysis respects the Bragg’s law and confirmed the crystalline nature of CdO nanoparticles. From the XRD, the average size of CdO NPs was found to be around 41 nm. The photoluminescence spectra of the CdO NPs, as recorded at room temperature, were excited at 300 nm wavelength. The broad emission peaks were between 600 and 650 nm (orange emission). The optical limiting performance of the nanocomposite was described in the sol–gel state. Also, this study has observed and studied the diffraction rings generated in CdO NPs using the same CW laser. The number of rings increases almost exponentially with an increasing volume fraction of SiO₂ in the nanocomposites. The refractive index change, Δn, and effective nonlinear refractive index, n ₂, were found to be 10^?4 and 10^?8 cm²/W, respectively. The effective nonlinear refractive index, n ₂, was determined based on the observed number of rings. The threshold values of the CdO, CdO–2SiO₂ and CdO–5SiO₂ nanocomposites are 7.1, 6.55 and 6.34 mW, respectively. This large nonlinearity is attributed to the thermal effect. The present studies suggest that the nanocomposite is a potential candidate for optical device applications such as the optical limiters. The thermal blooming technique was applied to evaluate the thermo-optic coefficient and thermal diffusivity of the CdO NPs. In the thermal blooming experimental setup a transistor–transistor logic modulated CW laser of wavelength 532 nm was used as the excitation source.     

The reference temperature dependence of Young’s modulus of two-temperature thermoelastic damping of gold nano-beam

This work is concerning with the study of the thermoelastic damping of a nanobeam resonator in the context of the two-temperature generalized thermoelasticity theory. An explicit formula of thermoelastic damping has been derived when Young’s modulus is a function of the reference temperature. Influences of the beam height and Young’s modulus have been studied with some comparisons between the Biot model and the Lord–Shulman model (L–S) for one- and two-temperature types. Numerical results show that the values of the thermal relaxation parameter and the two-temperature parameter have a strong influence on thermoelastic damping at nanoscales.     

Silver nanoparticles reduce the apoptosis induced by tumor necrosis factor-α

Silver nanoparticles (AgNPs) are widely known to have anti-inflammatory properties, but the exact mechanism underlying this anti-inflammatory effect is not clearly understood. Tumor necrosis factor-α (TNFα) is a major pro-inflammatory cytokine that is expressed in the early stage of cell inflammation and induces apoptosis by several known pathways. Our study aimed to investigate the effect of AgNPs on the response of lung epithelial cells to TNFα and the molecular mechanism of this response. Lung epithelial cell line NCI-H292 cells were exposed to AgNPs (5 µg/mL) and/or TNFα (20 ng/mL) for 24 h, then cellular uptake was analyzed using flow cytometry. Our results showed that AgNPs were taken up by cells in a dose-dependent manner and that the cellular uptake ratio of AgNPs was significantly increased in the presence of TNFα. Apoptosis assays indicated that exposure to AgNPs significantly decreased the apoptotic effect of TNFα. Confocal microscopy was used to localize the tumor necrosis factor receptor 1 (TNFR1) and revealed that TNFR1 localized on the surface of cells exposed to TNFα. In contrast, TNFR1 localized inside cells exposed to both AgNPs and TNFα, with very few receptors scattered on the cell membrane. The results indicated that AgNPs reduced the cell surface TNFR1 expression level. The results suggested that the reduction of surface TNFR1 reduced cellular response to TNFα, resulting in an anti-apoptotic effect.     

A review of wave-net identical learning &; filling-in in a decomposition space of (JPG-JPEG) sampled images

Continuous flow to send images via encrypted wireless channels may reduce the efficiency of transmission. This is due to the damage or loss of the numerous macro-blocks from these images. Therefore, it is difficult to rebuild these patches from the point of reception. Many algorithms have been proposed in the past decade, particularly error concealment (EC) algorithms. In this paper, we focus on the algorithms that have high efficiency to fill-in the corrupted patches. On the other hand, we also present a new way of detecting the horizontal and vertical gradients especially, in the un-smooth patches. This improves the edge detector filter. Ultimately, a novel scheme for vertical and horizontal interpolation between the corrupted pixels and the non-corrupted adjacent pixels is achieved by improving the efficiency of filling-in. We used a new technique known as the wave-net model. This model combines the wavelet with the neural network classifier (NNC). The neural network was trained in advance to reduce the error extent for the pixels that may occur in the error. The experimental results were convincing and close to the desired. The proposed method is able to enhance image quality in term of both visual perception and the blurriness effects (BE).     

An effort prediction framework for software defect correction

This article tackles the problem of predicting effort (in person–hours) required to fix a software defect posted on an Issue Tracking System. The proposed method is inspired by the Nearest Neighbour Approach presented by the pioneering work of Weiss et al. (2007) [1]. We propose four enhancements to Weiss et al. (2007) [1]: Data Enrichment, Majority Voting, Adaptive Threshold and Binary Clustering. Data Enrichment infuses additional issue information into the similarity-scoring procedure, aiming to increase the accuracy of similarity scores. Majority Voting exploits the fact that many of the similar historical issues have repeating effort values, which are close to the actual. Adaptive Threshold automatically adjusts the similarity threshold to ensure that we obtain only the most similar matches. We use Binary Clustering if the similarity scores are very low, which might result in misleading predictions. This uses common properties of issues to form clusters (independent of the similarity scores) which are then used to produce the predictions. Numerical results are presented showing a noticeable improvement over the method proposed in Weiss et al. (2007) [1].     

Trading Off Cache Capacity for Low-Voltage Operation

Two proposed techniques let microprocessors operate at low voltages despite high memory-cell failure rates. They identify and disable defective portions of the cache at two granularities: individual words or pairs of bits. Both techniques use the entire cache during high-voltage operation while sacrificing cache capacity during low-voltage operation to reduce the minimum voltage below 500 mV.     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

Utility of solid phase spectrophotometry for the modified determination of trace amounts of cadmium in food samples

A modified selective, highly sensitive and accurate procedure for the determination of trace amounts of cadmium which reacts with 1-(2-benzothiazolylazo)-2-hydroxy-3-naphthoic acid (BTAHNA) to give a deep violet complex with high molar absorptivity (7.05 × 10⁶ L mol⁻¹ cm⁻¹, 3.92 × 10⁷ L mol⁻¹ cm⁻¹, 1.78 × 10⁸ L mol⁻¹ cm⁻¹, and 4.10 × 10⁸ L mol⁻¹ cm⁻¹), fixed on a Dowex 1-X8 type anion-exchange resin for 10 mL, 100 mL, 500 mL, and 1000 mL, respectively. Calibration is linear over the range 0.2-3.5 μg L⁻¹ with RSD of ?1.14% (n = 10). The detection and quantification limits were calculated. Increasing the sample volume can enhance the sensitivity. The method has been successfully applied for the determination of Cd(II) in food samples, water samples and some salts samples without interfering effect of various cations and anions.