Genetic learning based texture surface inspection

This paper presents a novel approach of visual inspection for texture surface defects. It is based on the measure of texture energy acquired by a kind if high performance 2D detection mask, which is learned by genetic algorithms. Experimental results of texture defect inspection on textile images are presented to illustrate the merit and feasibility of the proposed method.<br /

Genetic image enhancement based on saturation feedback

In this paper an adaptive approach for color image enhancement is proposed. In this approach, the saturation feedback technique is used as a means of supplementing color image shmpness and contrast. This technique of the saturation feedback can serve to bring out image details that have low luminance contrast. In the technique, the feedback parameters are the key component and are usually determined manually. In order to realize the adaptive color image enhancement, the genetic algorithm is employed to search global optimal parameters for saturation feedback automatically. The detailed procedures are described in the paper. Experimental results on color images show the feasibility of the proposed method.<br /

Effect of bilayer coupling on tunneling conductance of double-layer high T_c cuprates

Physical effects of bilayer coupling on the tunneling spectroscopy of high T$_{c}$ cuprates are investigated. The bilayer coupling separates the bonding and antibonding bands and leads to a splitting of the coherence peaks in the tunneling differential conductance. However, the coherence peak of the bonding band is strongly suppressed and broadened by the particle-hole asymmetry in the density of states and finite quasiparticle life-time, and is difficult to resolve by experiments. This gives a qualitative account why the bilayer splitting of the coherence peaks was not clearly observed in tunneling measurements of double-layer high-T$_c$ oxides.Comment: 4 pages, 3 figures, to be published in PR

A Novel IoT Intrusion Detection Model Using 2dCNN-BiLSTM

With the continuous advancement of Internet of Things (IoT) intelligence, IoT security issues have become more and more prominent in recent years. The research on IoT security has become a hot spot. A lightweight IoT intrusion detection model fusing a convolutional neural network, bidirectional long short-term memory network is proposed. It aims to improve processed data security and attack detection accuracy. First, sampling is performed by a hybrid sampling algorithm fusing SMOTE and ENN. Its aim is to minimize the impact of imbalanced-data and ensure data quantity in the process. Then, the data features are extracted by 2-dimensional convolutional neural network (2dCNN), and the effect of useless information is reduced by mean pooling and maximum pooling, so it can be adapted to the demanding resource environment of the IoT. On this basis, long-range dependent temporal features are extracted using bidirectional long short-term memory (BiLSTM), which aims to fully extract data features to improve detection accuracy in the limited resource environment. Finally, the algorithm is validated on the UNSW_NB15 dataset, and the results of the experiments reaches 93.5% at Accuracy, 86.4% at Precision, 85.3% at Recall and 85.8% at F1-Score. According to the results, the proposed algorithm can generate higher-quality samples, achieve higher detection rate with faster inference time and spend lower memory costs. This paper is part of special issue AI-DRIVEN SECURE COMMUNICATION IN MASSIVE IOT FOR 5G AND BEYOND

Variation in both host defense and prior herbivory can alter plant-vector-virus interactions

Background: While virus-vector-host interactions have been a major focus of both basic and applied ecological research, little is known about how different levels of plant defense interact with prior herbivory to affect these relationships. We used genetically-modified strains of tomato (Solanum lycopersicum) varying in the jasmonic acid (JA) plant defense pathways to explore how plant defense and prior herbivory affects a plant virus (tomato yellow leaf curl virus, ‘TYLCV’), its vector (the whitefly Bemisia tabaci MED), and the host. Results: Virus-free MED preferred low-JA over high-JA plants and had lower fitness on high-JA plants. Viruliferous MED preferred low-JA plants but their survival was unaffected by JA levels. While virus-free MED did not lower plant JA levels, viruliferous MED decreased both JA levels and the expression of JA-related genes. Infestation by viruliferous MED reduced plant JA levels. In preference tests, neither virus-free nor viruliferous MED discriminated among JA-varying plants previously exposed to virus-free MED. However, both virus-free and viruliferous MED preferred low-JA plant genotypes when choosing between plants that had both been previously exposed to viruliferous MED. The enhanced preference for low-JA genotypes appears linked to the volatile compound neophytadiene, which was found only in whitefly-infested plants and at concentrations inversely related to plant JA levels. Conclusions: Our findings illustrate how plant defense can interact with prior herbivory to affect both a plant virus and its whitefly vector, and confirm the induction of neophytadiene by MED. The apparent attraction of MED to neophytadiene may prove useful in pest detection and management

A density matrix renormalisation group algorithm for quantum lattice systems with a large number of states per site

A variant of White's density matrix renormalisation group scheme which is designed to compute low-lying energies of one-dimensional quantum lattice models with a large number of degrees of freedom per site is described. The method is tested on two exactly solvable models---the spin-1/2 antiferromagnetic Heisenberg chain and a dimerised XY spin chain. To illustrate the potential of the method, it is applied to a model of spins interacting with quantum phonons. It is shown that the method accurately resolves a number of energy gaps on periodic rings which are sufficiently large to afford an accurate investigation of critical properties via the use of finite-size scaling theory.Comment: RevTeX, 8 pages, 2 figure

Low mass fraction impregnation with graphene oxide (GO) enhances thermo-physical properties of paraffin for heat storage applications

Whereas previous researchers analyzed the thermal behavior of paraffin waxes impregnated with graphene oxide nanoparticles (P-GONP) at high mass fraction ( > 1%), this paper analyzes behavior and stability at only 0.3% mass fraction. GONP was prepared by Hummer’s method. The morphology was studied using scanning electron microscope (SEM), transmission electron microscope (TEM), X-Ray diffraction (XRD) and Fourier Transformation-Infrared (FT-IR) Spectrometer and the thermal properties were measured using laser flash analyser (LFA), differential scanning calorimetry (DSC), thermo-gravimetric analysis (TGA) and thermal cycling. LFA showed a 101.2% and 94.5% increase in the thermal conductivity of P-GONP compared to pure paraffin (P) in solid and liquid state respectively. Melting and solidifying temperatures and latent heat were found to be 63.5, 59 °C & 102 kJ/kg and 57.5, 56 °C & 64.7 kJ/kg for P and P-GONP respectively. Thermal cycling over 4000 cycles showed that P-GONP was 27% more stable than P. The latent heat was 64.7 kJ/kg, a 36.5% deterioration compared to virgin paraffin. Compared against higher mass fraction impregnation, lower mass fraction P-GONP was found to have almost equivalent thermo-physical properties (namely thermal conductivity, melting and solidifying characteristics, thermo-chemical stability and reliability) while providing considerable cost saving

Characterization of a Peptide Domain within the GB Virus C NS5A Phosphoprotein that Inhibits HIV Replication

BACKGROUND:GBV-C infection is associated with prolonged survival in HIV-infected people and GBV-C inhibits HIV replication in co-infection models. Expression of the GBV-C nonstructural phosphoprotein 5A (NS5A) decreases surface levels of the HIV co-receptor CXCR4, induces the release of SDF-1 and inhibits HIV replication in Jurkat CD4+ T cell lines. METHODOLOGY/PRINCIPAL FINDINGS:Jurkat cell lines stably expressing NS5A protein and peptides were generated and HIV replication in these cell lines assessed. HIV replication was significantly inhibited in all cell lines expressing NS5A amino acids 152-165. Substitution of an either alanine or glycine for the serine at position 158 (S158A or S158G) resulted in a significant decrease in the HIV inhibitory effect. In contrast, substituting a phosphomimetic amino acid (glutamic acid; S158E) inhibited HIV as well as the parent peptide. HIV inhibition was associated with lower levels of surface expression of the HIV co-receptor CXCR4 and increased release of the CXCR4 ligand, SDF-1 compared to control cells. Incubation of CD4+ T cell lines with synthetic peptides containing amino acids 152-167 or the S158E mutant peptide prior to HIV infection resulted in HIV replication inhibition compared to control peptides. CONCLUSIONS/SIGNIFICANCE:Expression of GBV-C NS5A amino acids 152-165 are sufficient to inhibit HIV replication in vitro, and the serine at position 158 appears important for this effect through either phosphorylation or structural changes in this peptide. The addition of synthetic peptides containing 152-167 or the S158E substitution to Jurkat cells resulted in HIV replication inhibition in vitro. These data suggest that GBV-C peptides or a peptide mimetic may offer a novel, cellular-based approach to antiretroviral therapy

Giant Hall Switching by Surface-State-Mediated Spin-Orbit Torque in a Hard Ferromagnetic Topological Insulator

Topological insulators (TI) can apply highly efficient spin-orbit torque (SOT) and manipulate the magnetization with their unique topological surface states, and their magnetic counterparts, magnetic topological insulators (MTI) offer magnetization without shunting and are one of the highest in SOT efficiency. Here, we demonstrate efficient SOT switching of a hard MTI, V-doped (Bi,Sb)2Te3 (VBST) with a large coercive field that can prevent the influence of an external magnetic field and a small magnetization to minimize stray field. A giant switched anomalous Hall resistance of 9.2 $k\Omega$ is realized, among the largest of all SOT systems. The SOT switching current density can be reduced to $2.8\times10^5 A/cm^2$, and the switching ratio can be enhanced to 60%. Moreover, as the Fermi level is moved away from the Dirac point by both gate and composition tuning, VBST exhibits a transition from edge-state-mediated to surface-state-mediated transport, thus enhancing the SOT effective field to $1.56\pm 0.12 T/ (10^6 A/cm^2)$ and the spin Hall angle to $23.2\pm 1.8$ at 5 K. The findings establish VBST as an extraordinary candidate for energy-efficient magnetic memory devices

Glutamic acid decarboxylase autoantibodies are dominant but insufficient to identify most Chinese with adult-onset non-insulin requiring autoimmune diabetes: LADA China study 5.

AIMS: Adult-onset autoimmune diabetes is prevalent in China, in contrast to childhood-onset type 1 diabetes mellitus. Islet autoantibodies are the most important immune biomarkers to diagnose autoimmune diabetes. We assayed four different islet autoantibodies in recently diagnosed adult non-insulin-requiring diabetes Chinese subjects to investigate the best antibody assay strategy for the correct diagnosis of these subjects. METHODS: LADA China study is a nation-wide multicenter study conducted in diabetes patients from 46 university-affiliated hospitals in China. Non-insulin-treated newly diagnosed adult diabetes patients (n = 2388) were centrally assayed for glutamic acid decarboxylase autoantibody (GADA), protein tyrosine phosphatase-2 autoantibody (IA-2A), and zinc transporter 8 autoantibody (ZnT8A) by radioligand assay and insulin autoantibody (IAA) by microtiter plate radioimmunoassay. Clinical data were determined locally. RESULTS: Two hundred and six (8.63 %) subjects were autoantibody positive, of which GADA identified 5.78 % (138/2388) of the total, but only 67 % (138/206) of the autoimmune cases. IA-2A, ZnT8A, and IAA were found in 1.51, 1.84, and 1.26 % of the total study subjects, respectively. When assaying three islet autoantibodies, the most effective strategy was the combination of GADA, ZnT8A, and IAA, which could identify 92.2 % (190/206) autoimmune diabetes patients. The clinical data showed that those subjects with positive GADA had lower random C-peptide than autoantibody negative subjects (P < 0.05). CONCLUSIONS: As with Europeans, GADA is the dominant autoantibody in this form of autoimmune diabetes in China, but in contrast to Europeans, screening should include other diabetes-associated autoantibodies