Authenticated public key elliptic curve based on deep convolutional neural network for cybersecurity image encryption application

The demand for cybersecurity is growing to safeguard information flow and enhance data privacy. This essay suggests a novel authenticated public key elliptic curve based on a deep convolutional neural network (APK-EC-DCNN) for cybersecurity image encryption application. The public key elliptic curve discrete logarithmic problem (EC-DLP) is used for elliptic curve Diffie–Hellman key exchange (EC-DHKE) in order to generate a shared session key, which is used as the chaotic system’s beginning conditions and control parameters. In addition, the authenticity and confidentiality can be archived based on ECC to share the (Formula presented.) parameters between two parties by using the EC-DHKE algorithm. Moreover, the 3D Quantum Chaotic Logistic Map (3D QCLM) has an extremely chaotic behavior of the bifurcation diagram and high Lyapunov exponent, which can be used in high-level security. In addition, in order to achieve the authentication property, the secure hash function uses the output sequence of the DCNN and the output sequence of the 3D QCLM in the proposed authenticated expansion diffusion matrix (AEDM). Finally, partial frequency domain encryption (PFDE) technique is achieved by using the discrete wavelet transform in order to satisfy the robustness and fast encryption process. Simulation results and security analysis demonstrate that the proposed encryption algorithm achieved the performance of the state-of-the-art techniques in terms of quality, security, and robustness against noise- and signal-processing attacks

Role of lipids in phosphine resistant stored-grain insect pests Tribolium castaneum and Rhyzopertha dominica

Insects rely on lipids as an energy source to perform various activities, such as growth, flight, diapause, and metamorphosis. This study evaluated the role of lipids in phosphine resistance by stored-grain insects. Phosphine resistant and susceptible strains of the two main stored-grain insects, Tribolium castaneum and Rhyzopertha dominica, were analyzed using liquid chromatography-mass spectroscopy (LC-MS) to determine their lipid contents. Phosphine resistant strains of both species had a higher amount of lipids than susceptible stains. Significant variance ratios between the resistant and susceptible strains of T. castaneum were observed for glycerolipids (1.13- to 53.10-fold) and phospholipids (1.05- to 20.00-fold). Significant variance ratios between the resistant and susceptible strains of R. dominica for glycerolipids were 1.04- to 31.50-fold and for phospholipids were 1.04- to 10.10-fold. Glycerolipids are reservoirs to face the long-term energy shortage. Phospholipids act as a barrier to isolate the cells from the surrounding environment and allow each cell to perform its specific function. Thus, lipids offer a consistent energy source for the resistant insect to survive under the stress of phosphine fumigation and provide a suitable environment to protect the mitochondria from phosphine. Hence, it was proposed through this study that the lipid content of phosphine-resistant and phosphine-susceptible strains of T. castaneum and R. dominica could play an important role in the resistance of phosphine

Current flux imaging of a micromagnetic electrofoil

Like air flowing over a wing, optimizing the flow of electronic charge is essential to the operation of nanoscale devices. Unfortunately, the delicate interplay of charge, spin, and heat in complex devices has precluded detailed imaging of charge flow. Here, we report on the visualization of intrinsic charge current streamlines through yttrium iron garnet micromagnetic heterostructures. Scanning photovoltage microscopy of precisely designed devices leads to striking spatial patterns, with prominent photovoltage features emerging in corners and narrow constrictions. These patterns, which evolve continuously with rotation of an external magnetic field, enable rich spatial mapping of fluid-like flow. Taking inspiration from aerodynamic Clark Y airfoils, we engineer micromagnetic wing shaped devices, called electrofoils, which allow us to precisely contort, compress and decompress flowlines of electronic charge.Comment: 7 Pages, 4 figures, supplemental materials attached after reference

Loss of UGP2 in brain leads to a severe epileptic encephalopathy, emphasizing that bi-allelic isoform-specific start-loss mutations of essential genes can cause genetic diseases.

Developmental and/or epileptic encephalopathies (DEEs) are a group of devastating genetic disorders, resulting in early-onset, therapy-resistant seizures and developmental delay. Here we report on 22 individuals from 15 families presenting with a severe form of intractable epilepsy, severe developmental delay, progressive microcephaly, visual disturbance and similar minor dysmorphisms. Whole exome sequencing identified a recurrent, homozygous variant (chr2:64083454A > G) in the essential UDP-glucose pyrophosphorylase (UGP2) gene in all probands. This rare variant results in a tolerable Met12Val missense change of the longer UGP2 protein isoform but causes a disruption of the start codon of the shorter isoform, which is predominant in brain. We show that the absence of the shorter isoform leads to a reduction of functional UGP2 enzyme in neural stem cells, leading to altered glycogen metabolism, upregulated unfolded protein response and premature neuronal differentiation, as modeled during pluripotent stem cell differentiation in vitro. In contrast, the complete lack of all UGP2 isoforms leads to differentiation defects in multiple lineages in human cells. Reduced expression of Ugp2a/Ugp2b in vivo in zebrafish mimics visual disturbance and mutant animals show a behavioral phenotype. Our study identifies a recurrent start codon mutation in UGP2 as a cause of a novel autosomal recessive DEE syndrome. Importantly, it also shows that isoform-specific start-loss mutations causing expression loss of a tissue-relevant isoform of an essential protein can cause a genetic disease, even when an organism-wide protein absence is incompatible with life. We provide additional examples where a similar disease mechanism applies

Bi-allelic variants in HOPS complex subunit VPS41 cause cerebellar ataxia and abnormal membrane trafficking.

Membrane trafficking is a complex, essential process in eukaryotic cells responsible for protein transport and processing. Deficiencies in vacuolar protein sorting (VPS) proteins, key regulators of trafficking, cause abnormal intracellular segregation of macromolecules and organelles and are linked to human disease. VPS proteins function as part of complexes such as the homotypic fusion and vacuole protein sorting (HOPS) tethering complex, composed of VPS11, VPS16, VPS18, VPS33A, VPS39 and VPS41. The HOPS-specific subunit VPS41 has been reported to promote viability of dopaminergic neurons in Parkinson's disease but to date has not been linked to human disease. Here, we describe five unrelated families with nine affected individuals, all carrying homozygous variants in VPS41 that we show impact protein function. All affected individuals presented with a progressive neurodevelopmental disorder consisting of cognitive impairment, cerebellar atrophy/hypoplasia, motor dysfunction with ataxia and dystonia, and nystagmus. Zebrafish disease modelling supports the involvement of VPS41 dysfunction in the disorder, indicating lysosomal dysregulation throughout the brain and providing support for cerebellar and microglial abnormalities when vps41 was mutated. This provides the first example of human disease linked to the HOPS-specific subunit VPS41 and suggests the importance of HOPS complex activity for cerebellar function

The Impact of Personality and Demographic Variables in Collaborative Filtering of User Interest on Social Media

The advent of social networks and micro-blogging sites online has led to an abundance of user-generated content. Hence, the enormous amount of content is viewed as inappropriate and unimportant information by many users on social media. Therefore, there is a need to use personalization to select information related to users’ interests or searchers on social media platforms. Therefore, in recent years, user interest mining has been a prominent research area. However, almost all of the emerging research suffers from significant gaps and drawbacks. Firstly, it suffers from focusing on the explicit content of the users to determine the interests of the users while neglecting the multiple facts as the personality of the users; demographic data may be a valuable source of influence on the interests of the users. Secondly, existing work represents users with their interesting topics without considering the semantic similarity between the topics based on clusters to extract the users’ implicit interests. This paper is aims to propose a novel user interest mining approach and model based on demographic data, big five personality traits and similarity between the topics based on clusters. To demonstrate the leverage of combining user personality traits and demographic data into interest investigation, various experiments were conducted on the collected data. The experimental results showed that looking at personality and demographic data gives more accurate results in mining systems, increases utility, and can help address cold start problems for new users. Moreover, the results also showed that interesting topics were the dominant factor. On the other hand, the results showed that the current users’ implicit interests can be predicted through the cluster based on similar topics. Moreover, the hybrid model based on graphs facilitates the study of the patterns of interaction between users and topics. This model can be beneficial for researchers, people on social media, and for certain research in related fields

Molecular typing and antimicrobial resistance of group B Streptococcus clinical isolates in Saudi Arabia

ABSTRACT: Objectives: Group B Streptococcus (GBS) has emerged as an important cause of severe infections in adults. However, limited data are available regarding the epidemiology of GBS in Saudi Arabia. Methods: Isolates were collected over a period of eight months from colonized (n = 104) and infected adults (n = 95). Serotypes and virulence determinants were detected by polymerase chain reactions (PCRs). Genetic relatedness was assessed using Multiple Locus Variable Number Tandem Repeat Analysis (MLVA). Antimicrobial susceptibilities were determined by disk diffusion. Results: Serotypes III and V (25% each) were the most prevalent, followed by serotypes II (16.18%), Ia (13.24%), VI (9.31%), and Ib (8.82%), while five isolates remained non-typeable (2.45%). Hypervirulent serotype III/CC17 clone (n = 21) accounted for 41.18% of the serotype III isolates. Most isolates (53.92%) harboured pilus island (PI) 1 and 2a types, while PI-2b was predominantly detected in the hypervirulent clone. Isolates were variably resistant to tetracycline (76.47%), erythromycin (36.76%), clindamycin (25.49%), and levofloxacin (6.37%), but remained susceptible to penicillin. Macrolide resistant isolates exhibited constitutive (55.42%) and inducible macrolide-lincosamide-streptogramin B resistance phenotypes (33.74%), while a few had L (9.64%) or M (1.2%) phenotypes. MLVA patterns of dominant serotypes III and V revealed 40 different types divided into 12 clusters and 28 singletons. Interestingly, macrolide resistance was significantly associated with two major MLVA types. Conclusions: GBS isolates belonged predominantly to serotypes III and V, but there were no clear associations between serotypes and patient groups. The studied isolates exhibited high levels of resistance to erythromycin and clindamycin that need further surveillance