A robust and efficient convolutional deep learning framework for age-invariant face recognition

Extensive research has been carried out in the past on face recognition, face detection, and age estimation. However, age-invariant face recognition (AIFR) has not been explored that thoroughly. The facial appearance of a person changes considerably over time that results in introducing significant intraclass variations, which makes AIFR a very challenging task. Most of the face recognition studies that have addressed the ageing problem in the past have employed complex models and handcrafted features with strong parametric assumptions. In this work, we propose a novel deep learning framework that extracts age-invariant and generalized features from facial images of the subjects. The proposed model trained on facial images from a minor part (20–30%) of lifespan of subjects correctly identifies them throughout their lifespan. A variety of pretrained 2D convolutional neural networks are compared in terms of accuracy, time, and computational complexity to select the most suitable network for AIFR. Extensive experimental results are carried out on the popular and challenging face and gesture recognition network ageing dataset. The proposed method achieves promising results and outperforms the state-of-the-art AIFR models by achieving an accuracy of 99%, which proves the effectiveness of deep learning in facial ageing research.     

Medical image semantic segmentation based on deep learning

The image semantic segmentation has been extensively studying. The modern methods rely on the deep convolutional neural networks, which can be trained to address this problem. A few years ago networks require the huge dataset to be trained. However, the recent advances in deep learning allow training networks on the small datasets, which is a critical issue for medical images, since the hospitals and research organizations usually do not provide the huge amount of data. In this paper, we address medical image semantic segmentation problem by applying the modern CNN model. Moreover, the recent achievements in deep learning allow processing the whole image per time by applying concepts of the fully convolutional neural network. Our qualitative and quantitate experiment results demonstrated that modern CNN can successfully tackle the medical image semantic segmentation problem.

     

Correction to: Automatic COVID-19 detection mechanisms and approaches from medical images: a systematic review

Multimedia Tools and Applications -     

Alanine containing porous beads for mercury removal from artificial solutions

N‐methacryloyl‐(L )‐alanine (MALA) was synthesized by using methacryloyl chloride and alanine as a metal‐complexing ligand or comonomer. Spherical beads with an average diameter of 150–200 μm were obtained by suspension polymerization of MALA and 2‐hydroxyethyl methacrylate (HEMA) conducted in an aqueous dispersion medium. Poly(HEMA–MALA) beads were characterized by SEM, swelling studies, surface area measurement, and elemental analysis. Poly(HEMA–MALA) beads have a specific surface area of 68.5 m²/g. Poly(HEMA–MALA) beads with a swelling ratio of 63%, and containing 247 μmol MALA/g were used in the removal of Hg²⁺ from aqueous solutions. Adsorption equilibrium was achieved in about 60 min. The adsorption of Hg²⁺ ions onto PHEMA beads was negligible (0.3 mg/g). The MALA incorporation into the polymer structure significantly increased the mercury adsorption capacity (168 mg/g). Adsorption capacity of MALA containing beads increased significantly with pH. The adsorption of Hg²⁺ ions increased with increasing pH and reached a plateau value at around pH 5.0. Competitive heavy metal adsorption from aqueous solutions containing Cd²⁺, Cu²⁺, Pb²⁺, and Hg²⁺ was also investigated. The adsorption capacities are 44.5 mg/g for Hg²⁺, 6.4 mg/g for Cd²⁺, 2.9 mg/g for Pb²⁺, and 2.0 mg/g for Cu²⁺ ions. These results may be considered as an indication of higher specificity of the poly(HEMA–MALA) beads for the Hg²⁺ comparing to other ions. Consecutive adsorption and elution operations showed the feasibility of repeated use for poly(HEMA–MALA) chelating beads. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 1222–1228, 2006     

Thermoelectric and Magnetic Properties of Pt-Substituted $${BaFe_{4-{x}}Pt_{{x}}Sb_{12}}$$ Compounds

\({BaFe_{4-{x}}Pt_{{x}}Sb_{12}}\) (x = 0, 0.1, 0.2) compounds were prepared by melting and annealing, followed by a spark plasma sintering method. Low-temperature thermoelectric and magnetic properties were investigated based on Seebeck coefficient, electrical and thermal conductivity and magnetization measurements. The structural properties of \({BaFe_{4-{x}}Pt_{{x}}Sb_{12}}\) (x = 0, 0.1, 0.2) compounds were ascertained by powder x-ray diffraction analysis, confirming that all samples have a main phase of a skutterudite structure with the space group Im\({\mathrm {\bar{3}}}\). The lattice parameters obtained, 9.202(5), 9.199(5) and 9.202(1) Å for x = 0, 0.1 and 0.2, respectively, were found consistent with literature. The Seebeck coefficient sign shows that holes are dominant carriers in all compounds. The local maximum Seebeck coefficient was observed around 50 K which may be a trace of paramagnon-drag effect of charge carriers. Thermal conductivity and electrical resistivity measurements were carried out between 4.2 and 300 K. Temperature dependence of electrical resistivity reflects that all samples show semi-metallic behavior in our temperature range of 4.2–300 K. Samples for x = 0.1 and x = 0.2 show Kondo-like behavior. In magnetization measurement, we observe that there are two successive magnetic transitions in Pt-substituted compounds; however, there is only one (transition from a paramagnetic state to long-range magnetic ordering) in Pt-free compounds. In Pt-substituted compounds, the first transition appears at \( T _{ {\rm c}}\) = 48 K. In addition, the second transition is observed at \( T _{ {\rm irr}}\) = 30 K where an intermediate state is observed before the magnetic ordering transforms to an irreversible ferromagnetic state. We concluded that Pt substitution on the Fe side effectual on the thermoelectric and magnetic properties of \({BaFe_{4-{x}}Pt_{{x}}Sb_{12}}\) (x = 0, 0.1, 0.2) compounds.     

Effects of urban coarse particles inhalation on oxidative and inflammatory parameters in the mouse lung and colon

Background

Air pollution is a recognized aggravating factor for pulmonary diseases and has notably deleterious effects on asthma, bronchitis and pneumonia. Recent studies suggest that air pollution may also cause adverse effects in the gastrointestinal tract. Accumulating experimental evidence shows that immune responses in the pulmonary and intestinal mucosae are closely interrelated, and that gut-lung crosstalk controls pathophysiological processes such as responses to cigarette smoke and influenza virus infection. Our first aim was to collect urban coarse particulate matter (PM) and to characterize them for elemental content, gastric bioaccessibility, and oxidative potential; our second aim was to determine the short-term effects of urban coarse PM inhalation on pulmonary and colonic mucosae in mice, and to test the hypothesis that the well-known antioxidant N-acetyl-L-cysteine (NAC) reverses the effects of PM inhalation.

Results

The collected PM had classical features of urban particles and possessed oxidative potential partly attributable to their metal fraction. Bioaccessibility study confirmed the high solubility of some metals at the gastric level. Male mice were exposed to urban coarse PM in a ventilated inhalation chamber for 15 days at a concentration relevant to episodic elevation peak of air pollution. Coarse PM inhalation induced systemic oxidative stress, recruited immune cells to the lung, and increased cytokine levels in the lung and colon. Concomitant oral administration of NAC reversed all the observed effects relative to the inhalation of coarse PM.

Conclusions

Coarse PM-induced low-grade inflammation in the lung and colon is mediated by oxidative stress and deserves more investigation as potentiating factor for inflammatory diseases.

     

Effects of Neutron Flux on the Temperature Dependency of Permittivity of 3C-SiC Nanoparticles

In the present work, the real and imaginary parts of permittivity of cubic modification silicon carbide (3C-SiC) nanoparticles are investigated before and after neutron irradiation. The real and imaginary parts of permittivity for the samples were studied in 0.1 Hz–2.5 MHz frequency and 100 K–400 K temperature ranges. The samples were continuously irradiated by neutron flux (2x10 ¹³ n ?cm ^?2 s ^?1) up to 20 hours. The real and imaginary parts of permittivity were comparatively studied before and after irradiation. Neutron irradiation effects were studied with comparative analysis of non-irradiated samples. The increase in polarization was observed as a result of the increase in the impact period of neutron flux. All the mechanisms of the observed effects are given in the work.     

A multivariate study: variation in uptake of trace and toxic elements by various varieties of Sorghum bicolor L

The aim of present study was to evaluate the variation in uptake of elements (As, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb and Zn) by different varieties of Sorghum bicolor L., plants grown in soil amended with untreated industrial waste water sewage sludge (SUIS), on same experimental plots. The power of chemometrics was also used in exploring the potential natural and/or anthropogenic sources responsible for elemental contents in different varieties of sorghum. Hierarchical cluster analysis was used to explore the different variety of sorghum grouping according to corresponding their SUIS samples as additional information to the output obtained by principal component analysis. Significant genotypic variation was detected in the fourteen elements concentrations in sorghum grains, indicating the possibility to reduce the concentration of toxic elements in grains through breeding approach. It was observed that high tolerance limit of toxic elements was observed in sorghum variety PARC-SV-1.     

Hazardous impact of toxic metals on tobacco leaves grown in contaminated soil by ultrasonic assisted pseudo-digestion: multivariate study

Tobacco leaves (Nicotiana tabacum L.), agricultural soil and pollute irrigated lake water samples were collected during 2005–2006 and analyzed for Cd and Ni by electrothermal atomic absorption spectrometry (ETAAS). A simple and efficient procedure was investigated for the complete decomposition of tobacco leaves using ultrasonic assisted acid pseudo-digestion method (UPDM). A Plackett–Burman experimental design was used as a multivariate strategy for the evaluation of seven factors/variables at once, while central composite were used to found optimum values of significant variables. The accuracy of the proposed methods was assessed by analyzing certified reference (CRM); Virginia tobacco leaves (CTA-VTL-2). The results being compared with those obtained by conventional wet acid digestion method. The result obtained by optimized method showed good agreement with the certified values and sufficiently high recovery 97.8 and 98.7% for Cd and Ni, respectively. Under optimal conditions, the detection limits (3σ) were evaluated to be 0.019 μg g⁻¹ for Cd and 0.37 μg g⁻¹ for Ni. The proposed method was successfully applied to the determination of Cd and Ni in raw, processed tobacco and different branded cigarettes samples.     

An Effective Power-Aware At-Speed Test Methodology for IP Qualification and Characterization

Advanced nanometer technologies have led to a drastic increase in operational frequencies resulting in the performance of circuits becoming increasingly vulnerable to timing variations. The increasing process spread in advanced nanometer nodes poses considerable challenges in predicting post-fabrication silicon performance from timing models. Thus, there is a great need to qualify basic building structures on silicon in terms of critical parameters before they could be integrated within a complex System-on-Chip (SoC). The work of this paper presents a configurable circuit and an associated power-aware at-speed test methodology for the purpose of qualifying basic standard cells and complex IP structures to detect the presence of timing faults. Our design has been embedded within test-chips used for the development of the 28 nm Fully Depleted Silicon On Insulator (FD-SOI) technology node. The relevant silicon results and analysis validate the proposed power-aware test methodology for qualification and characterization of IPs and provide deeper insights for process improvements.