Engineering of functional supramacromolecular complexes of proteins (enzymes) using reversed micelles as matrix microreactors

The size of the inner water cavity of reversed micelles formedin a triple system ‘water-surfactant-organic solvent’can be widely varied by changing the degree of surfactant hydration.This gives grounds to use reversed micelles as matrix microreactorsfor the design of supramolecular complexes of proteins. Usingultracentrifugation analysis, it has been demonstrated thatthe oligomeric composition of various enzymes (ketoglutaratedehydrogenase, alkaline phosphatase, lactic dehydrogenase, glyceraldehyde-3-phosphatedehydrogenase) solubilized in reversed micelles of Aerosol OT[sodium bis(2-ethylehexyl)sulfosuccinate] in octane changesupon variation of the degree of hydration. An oligomeric complexforms under conditions when the radius of the micelle innercavity is big enough to incorporate this complex as a whole.At lower degrees of hydration the micelles ‘uncouple’such complexes to their components. The catalytic propertiesof various oligomeric complexes have been studied. Possibilitiesof using reversed micelles for the separation of subunits ofoligomeric enzymes under non-denaturating conditions have beendemonstrated. In particular, the isolated subunits of alkalinephosphatase, lactic dehydrogenase and glyceralde-hyde-3-phosphatedehydrogenase have been found to be active in Aerosol OT reversedmicelles. The dependences of the catalytic activity of oligomericenzymes represent saw-like curves. The maxima of the catalyticactivity observed at these curves relate to the functioningof various oligomeric forms of an enzyme. The radii of the micelleinner cavity under conditions when these maxima are observedcorrelate with the linear dimensions of the enzyme oligomericforms. Correlation of the position of a maximum with the shapeof an oligomeric complex is discussed.     

Sensor Fault Diagnosis and Unknown Disturbances Estimation of High Switching Frequency Single-phase PWM Rectifier

International Journal of Control, Automation and Systems - The fault and disturbances estimation has an important role in the modern traction railway system. This paper proposes a unique method for...     

Function Approximation Technique Based Adaptive Control for Chaos Synchronization between Different Systems with Unknown Dynamics

This paper presents a function approximation technique based immersion and invariance adaptive controller for chaos synchronization between nonidentical systems with unknown dynamics. In the proposed control scheme, the control system is reconstructed as the combination of a controllable linear system and a variation term from the original system. The variation term is treated as time-varying uncertainty and approximated by a group of weighted chosen basis functions. The immersion and invariance methodology is employed to design the adaptive control law such that both the synchronization error and uncertainty estimation error converge to zero. Two typical chaos synchronization problems are used in numerical simulations to verify the effectiveness and superiority of the proposed controller.

     

Hydrogen effect on the molecular weight distribution of polymers obtained by polymerization of ethylene and α-olefins over supported titanium-magnesium catalysts

Comparative data on the molecular weight distribution of polymers obtained by polymerization of ethylene, propylene and 1-hexene, and copolymerization of ethylene with α-olefins over the titanium-magnesium catalysts (TMC) in the absence and presence of hydrogen are presented. In contrast to the ethylene polymerization, in the cases of propylene and 1-hexene polymerization and copolymerization of ethylene with α-olefins, the hydrogen addition is characterized by noticeable narrowing of the molecular weight distribution (MWD) due to lower contribution of the MWD component with high molecular weight. This result is an evidence of the increased reactivity of TMC active sites producing high molecular weight poly-α-olefins and copolymers of ethylene with α-olefins in the chain transfer reaction with hydrogen. It is suggested that the increased reactivity of these sites in the transfer reaction with hydrogen appears after the 2,1-addition of α-olefin to the growing polymer chain.     

On the energy-delay trade-off in geographic forwarding in always-on wireless sensor networks: A multi-objective optimization problem

The design and development of multi-hop wireless sensor networks are guided by the specific requirements of their corresponding sensing applications. These requirements can be associated with certain well-defined qualitative and/or quantitative performance metrics, which are application-dependent. The main function of this type of network is to monitor a field of interest using the sensing capability of the sensors, collect the corresponding sensed data, and forward it to a data gathering point, also known as sink. Thus, the longevity of wireless sensor networks requires that the load of data forwarding be balanced among all the sensor nodes so they deplete their battery power (or energy) slowly and uniformly. However, some sensing applications are time-critical in nature. Hence, they should satisfy strict delay constraints so the sink can receive the sensed data originated from the sensors within a specified time bound. Thus, to account for all of these various sensing applications, appropriate data forwarding protocols should be designed to achieve some or all of the following three major goals, namely minimum energy consumption, uniform battery power depletion, and minimum delay. To this end, it is necessary to jointly consider these three goals by formulating a multi-objective optimization problem and solving it. In this paper, we propose a data forwarding protocol that trades off these three goals via slicing the communication range of the sensors into concentric circular bands. In particular, we discuss an approach, called weighted scale-uniform-unit sum, which is used by the source sensors to solve this multi-objective optimization problem. Our proposed data forwarding protocol, called Trade-off Energy with Delay (TED), makes use of our solution to this multi-objective optimization problem in order to find a “best” trade-off of minimum energy consumption, uniform battery power depletion, and minimum delay. Then, we present and discuss several numerical results to show the effectiveness of TED. Moreover, we show how to relax several widely used assumptions in order to enhance the practicality of our TED protocol, and extend it to real-world network scenarios. Finally, we evaluate the performance of TED through extensive simulations. We find that TED is near optimal with respect to the energy × delay metric. This simulation study is an essential step to gain more insight into TED before implementing it using a sensor test-bed.     

Evolutionary forwarding games in delay tolerant networks: Equilibria,mechanism design and stochastic approximation

In this paper, we apply evolutionary games to non-cooperative forwarding control in Delay Tolerant Networks (DTNs). The main focus is on mechanisms to rule the participation of the relays to the delivery of messages in DTNs. Thus, we express the success probability as a function of the competition that takes place within a large population of mobiles, and we characterize the effect of reward-based mechanisms on the performance of such systems. Devices acting as active relays, in fact, sacrifice part of their batteries in order to support message replication and thus increase the probability to reach the destination. In our scheme, a relay can choose the strategy by which they participate to the message relaying. A mobile that participates receives a unit of reward based on the reward mechanism selected by the network. A utility function is introduced as the difference between the expected reward and the energy cost, i.e., the cost spent by the relay to sustain forwarding operations. We show how the evolution dynamics and the equilibrium behavior (called Evolutionary Stable Strategy – ESS) are influenced by the characteristics of inter contact time, energy expenditure and pricing characteristics.We extend our analysis to mechanisms that the system can introduce in order to have the message delivered to the destination with high probability within a given deadline and under energy constraints which bound the number of released copies per message. Finally, we apply our findings in order to devise decentralized forwarding algorithms that are rooted in the theory of stochastic approximations. Thus, we demonstrate that the ESS can be attained without complete knowledge of the system state and letting the source monitor number of released copies per message only. We provide extensive numerical results to validate the proposed scheme.     

Toward an efficient and scalable feature selection approach for internet traffic classification

There is significant interest in the network management and industrial security community about the need to identify the “best” and most relevant features for network traffic in order to properly characterize user behaviour and predict future traffic. The ability to eliminate redundant features is an important Machine Learning (ML) task because it helps to identify the best features in order to improve the classification accuracy as well as to reduce the computational complexity related to the construction of the classifier. In practice, feature selection (FS) techniques can be used as a preprocessing step to eliminate irrelevant features and as a knowledge discovery tool to reveal the “best” features in many soft computing applications. In this paper, we investigate the advantages and disadvantages of such FS techniques with new proposed metrics (namely goodness, stability and similarity). We continue our efforts toward developing an integrated FS technique that is built on the key strengths of existing FS techniques. A novel way is proposed to identify efficiently and accurately the “best” features by first combining the results of some well-known FS techniques to find consistent features, and then use the proposed concept of support to select a smallest set of features and cover data optimality. The empirical study over ten high-dimensional network traffic data sets demonstrates significant gain in accuracy and improved run-time performance of a classifier compared to individual results produced by some well-known FS techniques.     

A tree-covering problem arising in integrity of tree-structured data

We introduce and solve a problem motivated by integrity verification in third-party data distribution: Given an undirected tree, find a minimum-cardinality set of simple paths that cover all the tree edges and, secondarily, have smallest total path lengths. We give a linear time algorithm for this problem.