Studies on comb-like polymers: 5 A d.s.c. investigation of samples of poly(octadecylethylene) with different history

The crude product of the stereospecific polymerization of octadecylethylene shows, on d.s.c. analysis, two enthalpy changes associated with the melting or the crystallization of two immiscible crystalline phases. It is shown that the crystallization of the crude polymer from dilute heptane solutions leads to a satisfactory separation of supposedly isotactic from atactic material. Contrary to previous statements, it is demonstrated that both these materials display single melting and crystallization phenomena. It is also shown that appropriate annealing treatments lead to a narrow distribution of the crystallite sizes for all the crystalline structured formed by poly(octadecylethylene).     

Evaluation of outage probability of microwave radio relay systems carrying both analogue (FM) and digital (FSK) RF channels

In the letter, a new formula is derived for the (multipath) outage probability of (both analogue and digital) signals present in an existing analogue radio relay link operating below 11 GHz when some analogue channels are replaced by digital ones.     

An integrated architecture for future car generations

The DECOS architecture is an integrated architecture that builds upon the validated services of a time-triggered network, which serves as a shared resource for the communication activities of more than one application subsystem. In addition, encapsulated partitions are used to share the computational resources of Electronic Control Units (ECUs) among software modules of multiple application subsystems. This paper investigates the benefits of the DECOS architecture as an electronic infrastructure for future car generations. The shift to an integrated architecture will result in quantifiable cost reductions in the areas of system hardware cost and system development. In the paper we present a current federated Fiat car E/E architecture and discuss a possible mapping to an integrated solution based on the DECOS architecture. The proposed architecture provides a foundation for mixed criticality integration with both safety-critical and non safety-critical subsystems. In particular, this architecture supports applications up to the highest criticality classes (10^?9 failures per hour), thereby taking into account the emerging dependability requirements of by-wire functionality in the automotive industry.     

An improvement of the state-of-the-art covariance-based methods for statistical anomaly detection algorithms

This paper presents a possible improvement to one of the main statistical anomaly detection algorithms for cyber security applications, i.e., the covariance-based method. This algorithm employs covariance matrices to build a norm profile of the normal network traffic and to detect anomalous activities in the data flow. In order to improve the detection capabilities of this algorithm, we propose a modified version of the statistical decision rule based on a generalized version of the Chebyshev inequality for random vectors. The performance of the proposed algorithm is evaluated and compared, in terms of ROC (receiver operating characteristic) curves with the ones of the state-of-the-art covariance-based algorithm.     

DoMAIns: Domain-based modeling for Ambient Intelligence

Ambient Intelligence and Smart Home Automation systems are currently emerging as feasible and ready to exploit solutions to support more intelligent features inside future and current homes. Thanks to increased availability of off-the-shelf components and to relatively easy to implement solutions we are experiencing a steady evolution of households, causing an ever-increasing users’ awareness of the capabilities of such innovative environments. To foster effective adoption of Smart Home Automation technologies in our home environments, traditional architectural and plant design must be complemented by sound design methodologies and tools, supporting the whole environment design cycle, including for example modeling, simulation and emulation, as well as, when feasible, formal model-checking and verification. Several research efforts have already addressed the design of expressive modeling tools, mostly based on Semantic Web technologies, as well as of suitable platforms for adding interoperation and rule-based intelligence to home environments. This paper proposes a new modeling methodology designed to fit the different phases of Intelligent Environments design, with a particular focus on validation and verification of the whole system. Carefully designed separation of modeled entities permits to exploit the DoMAIns framework during all phases of the environment design, from early abstract conception to the final in-field deployment. The DoMAIns design methodology is applied to a sample use case that involves comprehensive modeling and simulation of a Bank Security Booth, including the environment, the control algorithms, the automation devices and the user. Results show that the approach is feasible and that can easily handle different types of environment modeling, required in the different design phases, and for each of them it may support simulation, emulation, or other verification techniques.     

Optimizing Deep Packet Inspection for High-Speed Traffic Analysis

Deep Packet Inspection (DPI) techniques are considered extremely expensive in terms of processing costs and therefore are usually deployed in edge networks, where the amount of data to be processed is limited. This paper demonstrates that, in case the application can tolerate some compromises in terms of accuracy (such as many measurement-based tasks) and in presence of normal traffic, the processing cost can be greatly reduced while even improving the classification precision, making DPI suitable also for high-speed networks.     

Exploring the molecular basis of the enantioselective binding of penicillin G acylase towards a series of 2-aryloxyalkanoic acids: a docking and molecular dynamics study

In the present paper, molecular modeling studies were undertaken in order to shed light on the molecular basis of the observed enantioselectivity of penicillin G acylase (PGA), a well known enzyme for its industrial applications, towards 16 racemic 2-aryloxyalkanoic acids, which have been reported to affect several biological systems. With this intention docking calculations and MD simulations were performed. Docking results indicated that the (S)-enantiomers establish several electrostatic interactions with SerB1, SerB386 and ArgB263 of PGA. Conversely, the absence of specific polar interactions between the (R)-enantiomers and ArgB263 seems to be the main reason for the different binding affinities observed between the two enantiomers. Results of molecular dynamics simulations demonstrated that polar interactions are responsible for both the ligand affinity and PGA enantiospecificity. Modeling calculations provided possible explanations for the observed enantioselectivity of the enzyme that rationalize available experimental data and could be the basis for future protein engineering efforts.     

Human urine biomarkers of renal cell carcinoma evaluated by ClinProt

Renal cell carcinoma (RCC) is one of the major causes of cancer death and is radio- and chemoresistant. Urine of 29 healthy subjects and 39 clear cell RCC patients were analyzed using the ClinProt technique to search for possible biomarkers for early RCC diagnosis. A cluster of three signals (marker A= at m/z 1827?±?8?Da, marker B = 1914?±?8?Da and marker C = 1968?±?8?Da) was able to discriminate patients from controls. A receiver operating characteristic curve analysis showed values of area under the curve (AUC) higher than 0.9 for marker A and B, corresponding to a sensitivity of 85-90% and a specificity of 90%, while marker C gave a lower AUC (0.84) corresponding to sensitivity of 70% and specificity of 100%. The combination of three markers lead to an improvement in diagnostic efficacy, with specificity and sensitivity of 100% and 95%, respectively, in the training test and of 100% and of 85% in the test experiment. The efficacy of this cluster of signals to distinguish RCC patients grouped by tumor stage showed a sensibility of 100% for patients at the primary tumor 1 stage. One of the signals present in the cluster was identified as a fragment of Tamm-Horsfall protein.