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.     

Structure‐Based Design of Microsomal Prostaglandin E2 Synthase‐1 (mPGES‐1) Inhibitors using a Virtual Fragment Growing Optimization Scheme

A small library of 2,3‐dihydroxybenzamide‐ and N‐(2,3‐dihydroxyphenyl)‐4‐sulfonamide‐based microsomal prostaglandin E₂ synthase‐1 (mPGES‐1) inhibitors was identified following a step‐by‐step optimization of small aromatic fragments selected to interact in focused regions in the active site of mPGES‐1. During the virtual optimization process, the 2,3‐dihydroxybenzamide moiety was first selected as a backbone of the proposed new chemical entities; the identified compounds were then synthesized and biologically evaluated, identifying derivatives with very promising inhibitory activities in the micromolar range. Subsequent structure‐guided replacement of the 2,3‐dihydroxybenzamide by the N‐(2,3‐dihydroxyphenyl)sulfonamide moiety led to the identification of N‐(2,3‐dihydroxyphenyl)‐4‐biphenylsulfonamide ( 6 ), the most potent small molecule of the series (IC₅₀=0.53±0.04 μm ). The simple synthetic procedure and the possibility of enhancing the potency of this class of inhibitors through additional structural modifications pave the way for further development of new molecules with mPGES‐1‐inhibitory activity, with potential application as anti‐inflammatory and anticancer agents.     

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.     

A Robust Design for Cellular Vehicles of Gold Nanorods for Multimodal Imaging

The pursuit of more selectivity in the delivery of plasmonic particles to tumors is critical before their penetration into clinical applications as the photoacoustic imaging and the photothermal ablation of cancer. As their direct infusion into the bloodstream remains problematic, due to a multitude of biological barriers, the development of alternative approaches is emerging as a new challenge. In this context, the recruitment of homologous tumor‐tropic cells that may serve as Trojan horses stands out as a fascinating possibility. Here, a novel model of gold nanorods is presented that feature a composite shell and undergo efficient and reproducible endocytic uptake from murine macrophages, which is fine‐tunable over a broad range of conditions. These cells preserve their viability and more than 90% of their innate chemotactic behavior in vitro, even with a cargo exceeding 200 000 particles per cell. In addition, we show that these vehicles are detectible by photoacoustic imaging down to concentrations in the order of 1% in whole blood and by clinical X‐ray computed tomography below 10%, which is within the typical fraction of a leukocytic infiltrate in a tumor microenvironment, and may even work as contrast agents for the photothermal ablation of cancer.     

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.     

Event-triggered transmission for linear control over communication channels

We consider an exponentially stable closed loop interconnection between a continuous-time linear plant and a continuous-time linear controller, and we study the problem of interconnecting the plant output to the controller input through a digital channel. We propose an event-triggered transmission policy whose goal is to transmit the measured plant output information as little as possible while preserving closed-loop stability. Global asymptotic stability is guaranteed when the plant state is available or when an estimate of the state is available (provided by a classical continuous-time linear observer). Under further assumptions, the transmission policy guarantees global exponential stability of the origin.