A Study of the Advances in IoT Security

The Internet-of-things (IoT) holds a lot of benefits to our lives by removing menial tasks and improving efficiency of everyday objects. You are trusting your personal data and device control to the manufactures and you may not be aware of how much risk your putting your privacy at by sending your data over the internet. The internet-of-things may not be as secure as you think when the devices used are constrained by a lot of variables which attackers can exploit to gain access to your data / device and anything they connected to and as the internet-of-things is all about connecting devices together one weak point can be all it takes to gain full access. In this paper we have a look at the current advances in IoT security and the most efficient methods to protect IoT devices

Spinodal Decomposition in a Binary Polymer Mixture: Dynamic Self Consistent Field Theory and Monte Carlo Simulations

We investigate how the dynamics of a single chain influences the kinetics of early stage phase separation in a symmetric binary polymer mixture. We consider quenches from the disordered phase into the region of spinodal instability. On a mean field level we approach this problem with two methods: a dynamical extension of the self consistent field theory for Gaussian chains, with the density variables evolving in time, and the method of the external potential dynamics where the effective external fields are propagated in time. Different wave vector dependencies of the kinetic coefficient are taken into account. These early stages of spinodal decomposition are also studied through Monte Carlo simulations employing the bond fluctuation model that maps the chains -- in our case with 64 effective segments -- on a coarse grained lattice. The results obtained through self consistent field calculations and Monte Carlo simulations can be compared because the time, length, and temperature scales are mapped onto each other through the diffusion constant, the chain extension, and the energy of mixing. The quantitative comparison of the relaxation rate of the global structure factor shows that a kinetic coefficient according to the Rouse model gives a much better agreement than a local, i.e. wave vector independent, kinetic factor. Including fluctuations in the self consistent field calculations leads to a shorter time span of spinodal behaviour and a reduction of the relaxation rate for smaller wave vectors and prevents the relaxation rate from becoming negative for larger values of the wave vector. This is also in agreement with the simulation results.Comment: Phys.Rev.E in prin

Three-Dimensional Visualization and Characterization of Polymeric Self-Assemblies by Transmission Electron Microtomography

Self-assembling structures and their dynamical processes in polymeric systems have been investigated using three-dimensional transmission electron microscopy (3D-TEM). Block copolymers (BCPs) self-assemble into nanoscale periodic structures called microphase-separated structures, a deep understanding of which is important for creating nanomaterials with superior physical properties, such as high-performance membranes with well-defined pore size and high-density data storage media. Because microphase-separated structures have become increasingly complicated with advances in precision polymerization, characterizing these complex morphologies is becoming increasingly difficult. Thus, microscopes capable of obtaining 3D images are required. In this article, we demonstrate that 3D-TEM is an essential tool for studying BCP nanostructures, especially those self-assembled during dynamical processes and under confined conditions.The first example is a dynamical process called order-order transitions (OOTs). Upon changing temperature or pressure or applying an external field, such as a shear flow or electric field, BCP nanostructures transform from one type of structure to another. The OOTs are examined by freezing the specimens in the middle of the OOT and then observing the boundary structures between the preexisting and newly formed nanostructures in three-dimensions. In an OOT between the bicontinuous double gyroid and hexagonally packed cylindrical structures, two different types of epitaxial phase transition paths are found. Interestingly, the paths depend on the direction of the OOT. The second example is BCP self-assemblies under confinement that have been examined by 3D-TEM. A variety of intriguing and very complicated 3D morphologies can be formed even from the BCPs that self-assemble into simple nanostructures, such as lamellar and cylindrical structures in the bulk (in free space).Although 3D-TEM is becoming more frequently used for detailed morphological investigations, it is generally used to study static nanostructures. Although OOTs are dynamical processes, the actual experiment is done in the static state, through a detailed morphological study of a snapshot taken during the OOT. Developing time-dependent nanoscale 3D imaging has become a hot topic. Here, the two main problems preventing the development of in situ electron tomography for polymer materials are addressed. First, the staining protocol often used to enhance contrast for electrons is replaced by a new contrast enhancement based on chemical differences between polymers. In this case, no staining is necessary. Second, a new 3D reconstruction algorithm allows us to obtain a high-contrast, quantitative 3D image from fewer projections than is required for the conventional algorithm to achieve similar contrast, reducing the number of projections and thus the electron beam dose. Combining these two new developments is expected to open new doors to 3D in situ real-time structural observation of polymer materials

Nanoparticle Network Formation in Nanostructured and Disordered Block Copolymer Matrices

Incorporation of nanoparticles composed of surface-functionalized fumed silica (FS) or native colloidal silica (CS) into a nanostructured block copolymer yields hybrid nanocomposites whose mechanical properties can be tuned by nanoparticle concentration and surface chemistry. In this work, dynamic rheology is used to probe the frequency and thermal responses of nanocomposites composed of a symmetric poly(styrene-b-methyl methacrylate) (SM) diblock copolymer and varying in nanoparticle concentration and surface functionality. At sufficiently high loading levels, FS nanoparticle aggregates establish a load-bearing colloidal network within the copolymer matrix. Transmission electron microscopy images reveal the morphological characteristics of the nanocomposites under these conditions

Muscleblind-Like 1 Knockout Mice Reveal Novel Splicing Defects in the Myotonic Dystrophy Brain

Myotonic dystrophy type 1 (DM1) is a multi-systemic disorder caused by a CTG trinucleotide repeat expansion (CTGexp) in the DMPK gene. In skeletal muscle, nuclear sequestration of the alternative splicing factor muscleblind-like 1 (MBNL1) explains the majority of the alternative splicing defects observed in the HSALR transgenic mouse model which expresses a pathogenic range CTGexp. In the present study, we addressed the possibility that MBNL1 sequestration by CUGexp RNA also contributes to splicing defects in the mammalian brain. We examined RNA from the brains of homozygous Mbnl1ΔE3/ΔE3 knockout mice using splicing-sensitive microarrays. We used RT-PCR to validate a subset of alternative cassette exons identified by microarray analysis with brain tissues from Mbnl1ΔE3/ΔE3 knockout mice and post-mortem DM1 patients. Surprisingly, splicing-sensitive microarray analysis of Mbnl1ΔE3/ΔE3 brains yielded only 14 candidates for mis-spliced exons. While we confirmed that several of these splicing events are perturbed in both Mbnl1 knockout and DM1 brains, the extent of splicing mis-regulation in the mouse model was significantly less than observed in DM1. Additionally, several alternative exons, including Grin1 exon 4, App exon 7 and Mapt exons 3 and 9, which have previously been reported to be aberrantly spliced in human DM1 brain, were spliced normally in the Mbnl1 knockout brain. The sequestration of MBNL1 by CUGexp RNA results in some of the aberrant splicing events in the DM1 brain. However, we conclude that other factors, possibly other MBNL proteins, likely contribute to splicing mis-regulation in the DM1 brain

Modelling Human Regulatory Variation in Mouse: Finding the Function in Genome-Wide Association Studies and Whole-Genome Sequencing

An increasing body of literature from genome-wide association studies and human whole-genome sequencing highlights the identification of large numbers of candidate regulatory variants of potential therapeutic interest in numerous diseases. Our relatively poor understanding of the functions of non-coding genomic sequence, and the slow and laborious process of experimental validation of the functional significance of human regulatory variants, limits our ability to fully benefit from this information in our efforts to comprehend human disease. Humanized mouse models (HuMMs), in which human genes are introduced into the mouse, suggest an approach to this problem. In the past, HuMMs have been used successfully to study human disease variants; e.g., the complex genetic condition arising from Down syndrome, common monogenic disorders such as Huntington disease and β-thalassemia, and cancer susceptibility genes such as BRCA1. In this commentary, we highlight a novel method for high-throughput single-copy site-specific generation of HuMMs entitled High-throughput Human Genes on the X Chromosome (HuGX). This method can be applied to most human genes for which a bacterial artificial chromosome (BAC) construct can be derived and a mouse-null allele exists. This strategy comprises (1) the use of recombineering technology to create a human variant–harbouring BAC, (2) knock-in of this BAC into the mouse genome using Hprt docking technology, and (3) allele comparison by interspecies complementation. We demonstrate the throughput of the HuGX method by generating a series of seven different alleles for the human NR2E1 gene at Hprt. In future challenges, we consider the current limitations of experimental approaches and call for a concerted effort by the genetics community, for both human and mouse, to solve the challenge of the functional analysis of human regulatory variation