Secure Health Data Sharing for Medical Cyber-Physical Systems for the Healthcare 4.0.

The recent spades of cyber attacks have compromised end-users' data security and privacy in Medical Cyber-Physical Systems (MCPS) in the era of Health 4.0. Traditional standard encryption algorithms for data protection are designed based on a viewpoint of system architecture rather than a viewpoint of end-users. As such encryption algorithms are transferring the protection on the data to the protection on the keys, data safety, and privacy will be compromised once the key is exposed. In this paper, we propose a secure data storage and sharing method consisted of a selective encryption algorithm combined with fragmentation and dispersion to protect the data safety and privacy even when both transmission media (e.g. cloud servers) and keys are compromised. This method is based on a user-centric design that protects the data on a trusted device such as the end-users' smartphone and lets the end-user control the access for data sharing. We also evaluate the performance of the algorithm on a smartphone platform to prove efficiency.

Mobility-Aware Caching and Computation Offloading in 5G Ultra-Dense Cellular Networks.

Recent trends show that Internet traffic is increasingly dominated by content, which is accompanied by the exponential growth of traffic. To cope with this phenomena, network caching is introduced to utilize the storage capacity of diverse network devices. In this paper, we first summarize four basic caching placement strategies, i.e., local caching, Device-to-Device (D2D) caching, Small cell Base Station (SBS) caching and Macrocell Base Station (MBS) caching. However, studies show that so far, much of the research has ignored the impact of user mobility. Therefore, taking the effect of the user mobility into consideration, we proposes a joint mobility-aware caching and SBS density placement scheme (MS caching). In addition, differences and relationships between caching and computation offloading are discussed. We present a design of a hybrid computation offloading and support it with experimental results, which demonstrate improved performance in terms of energy cost. Finally, we discuss the design of an incentive mechanism by considering network dynamics, differentiated user's quality of experience (QoE) and the heterogeneity of mobile terminals in terms of caching and computing capabilities.

RNA nanotechnology for computer design and in vivo computation.

Molecular-scale computing has been explored since 1989 owing to the foreseeable limitation of Moore's law for silicon-based computation devices. With the potential of massive parallelism, low energy consumption and capability of working in vivo, molecular-scale computing promises a new computational paradigm. Inspired by the concepts from the electronic computer, DNA computing has realized basic Boolean functions and has progressed into multi-layered circuits. Recently, RNA nanotechnology has emerged as an alternative approach. Owing to the newly discovered thermodynamic stability of a special RNA motif (Shu et al. 2011 Nat. Nanotechnol. 6, 658-667 (doi:10.1038/nnano.2011.105)), RNA nanoparticles are emerging as another promising medium for nanodevice and nanomedicine as well as molecular-scale computing. Like DNA, RNA sequences can be designed to form desired secondary structures in a straightforward manner, but RNA is structurally more versatile and more thermodynamically stable owing to its non-canonical base-pairing, tertiary interactions and base-stacking property. A 90-nucleotide RNA can exhibit 49° nanostructures, and its loops and tertiary architecture can serve as a mounting dovetail that eliminates the need for external linking dowels. Its enzymatic and fluorogenic activity creates diversity in computational design. Varieties of small RNA can work cooperatively, synergistically or antagonistically to carry out computational logic circuits. The riboswitch and enzymatic ribozyme activities and its special in vivo attributes offer a great potential for in vivo computation. Unique features in transcription, termination, self-assembly, self-processing and acid resistance enable in vivo production of RNA nanoparticles that harbour various regulators for intracellular manipulation. With all these advantages, RNA computation is promising, but it is still in its infancy. Many challenges still exist. Collaborations between RNA nanotechnologists and computer scientists are necessary to advance this nascent technology.

Exponential H(infinity) synchronization of general discrete-time chaotic neural networks with or without time delays.

This brief studies exponential H(infinity) synchronization of a class of general discrete-time chaotic neural networks with external disturbance. On the basis of the drive-response concept and H(infinity) control theory, and using Lyapunov-Krasovskii (or Lyapunov) functional, state feedback controllers are established to not only guarantee exponential stable synchronization between two general chaotic neural networks with or without time delays, but also reduce the effect of external disturbance on the synchronization error to a minimal H(infinity) norm constraint. The proposed controllers can be obtained by solving the convex optimization problems represented by linear matrix inequalities. Most discrete-time chaotic systems with or without time delays, such as Hopfield neural networks, cellular neural networks, bidirectional associative memory networks, recurrent multilayer perceptrons, Cohen-Grossberg neural networks, Chua's circuits, etc., can be transformed into this general chaotic neural network to be H(infinity) synchronization controller designed in a unified way. Finally, some illustrated examples with their simulations have been utilized to demonstrate the effectiveness of the proposed methods.

Low-power, intelligent sensor hardware interface for medical data preprocessing.

This work proposes an interface design of a low-power programmable system on chip for intelligent wireless sensor nodes to reduce the overall power consumption of the heart disease monitoring system, by lending them the capability of processing complex functions and performing rapid computations on a large amount of data at the node. This facilitates the node to intelligently monitor a medical signal for impending events instead of transmitting the signal to the base station constantly. Lowering the transmission data rate decreases the transmission power consumption in a node, thereby lengthening the node life and in turn increasing the reliability of the network. This work also implements a thresholding technique, which controls the data transmission rate depending on the value of the monitored signal, and a cardiac monitoring system that performs computations at the node for the detection of either a skipped heart beat or a reduced heart rate variability, in which event the signal is transmitted to the base station for monitoring/recording or alerting the crew. The performance analysis of the system shows that there are reductions in the system power consumption and data transmission rate, which in turn reduces the network traffic and averts congestion.

Cluster analysis of hydration waters around the active sites of bacterial alanine racemase using a 2-ns MD simulation.

Structural data produced by a 2-ns molecular dynamics (MD) simulation on Geobacillus alanine racemase (AlaR; PDB: 1SFT) was used to study hydration around the two AlaR active sites. AlaR is a crucial enzyme for bacterial cell wall biosynthesis. It has been shown previously that the potency of an inhibitor can be increased by incorporating a functional group or atom that displaces hydration sites close to the substrate binding pocket of its target enzyme. The complete linkage algorithm was used for cluster analysis of the active site water positions from 126 solvent configurations sampled at regular intervals from the 2-ns MD simulation. Crystal waters in the 1SFT X-ray structure occupy most of the tightly bound water sites that were discovered. We show here that tightly bound water sites can be identified by cluster analysis of MD-generated coordinates starting with data supplied by a single X-ray structure, and we predict a highly conserved hydration site close to the carboxyl oxygen of L-Ala substrate. This approach holds promise for accelerating the drug design process. We also discuss an analysis of the well-known notion of residence time and introduce a new measure called retention time.