An algorithmic and architectural study on Montgomery exponentiation in RNS

The modular exponentiation on large numbers is computationally intensive. An effective way for performing this operation consists in using Montgomery exponentiation in the Residue Number System (RNS). This paper presents an algorithmic and architectural study of such exponentiation approach. From the algorithmic point of view, new and state-of-the-art opportunities that come from the reorganization of operations and precomputations are considered. From the architectural perspective, the design opportunities offered by well-known computer arithmetic techniques are studied, with the aim of developing an efficient arithmetic cell architecture. Furthermore, since the use of efficient RNS bases with a low Hamming weight are being considered with ever more interest, four additional cell architectures specifically tailored to these bases are developed and the tradeoff between benefits and drawbacks is carefully explored. An overall comparison among all the considered algorithmic approaches and cell architectures is presented, with the aim of providing the reader with an extensive overview of the Montgomery exponentiation opportunities in RNS

Current and emerging treatments for amyotrophic lateral sclerosis

Stefano Zoccolella1, Andrea Santamato2, Paolo Lamberti31Azienda Ospedaliero-UniversitariaOspedali Riuniti, Department of Medical and Neurological Sciences, Clinic of Nervous System Diseases, University of Foggia, Italy; 2Department of Physical Medicine and Rehabilitation, University of Foggia, OORR, Italy; 3Department of Neurology and Psychiatry, University of Bari, ItalyBackground: Amyotrophic lateral sclerosis (ALS) is a relatively rare neurodegenerative disorder of both upper and lower motoneurons. Currently, the management of ALS is essentially symptoms-based, and riluzole, an antiglutamatergic agent, is the only drug for the treatment of ALS approved by the food and drug administration.Objective: We reviewed current literature concerning emerging treatments for amyotrophic lateral sclerosis.Methods: A Medline literature search was performed to identify all studies on ALS treatment published from January 1st, 1986 through August 31st, 2009. We selected papers concerning only disease-modifying therapy.Results: Forty-eight compounds were identified and reviewed in this study.Conclusions: Riluzole is the only compound that demonstrated a beneficial effect on ALS patients, but with only modest increase in survival. Although several drugs showed effective results in the animal models for ALS, none of them significantly prolonged survival or improved quality of life of ALS patients. Several factors have been implicated in explaining the predominantly negative results of numerous randomized clinical trials in ALS, including methodological problems in the use of animal-drug screening, the lack of assessment of pharmacokinetic profile of the drugs, and methodological pitfalls of clinical trials in ALS patients.Keywords: amyotrophic lateral sclerosis, therapy, drug, surviva

Mixed marker-based/marker-less visual odometry system for mobile robots

When moving in generic indoor environments, robotic platforms generally rely solely on information provided by onboard sensors to determine their position and orientation. However, the lack of absolute references often leads to the introduction of severe drifts in estimates computed, making autonomous operations really hard to accomplish. This paper proposes a solution to alleviate the impact of the above issues by combining two vision‐based pose estimation techniques working on relative and absolute coordinate systems, respectively. In particular, the unknown ground features in the images that are captured by the vertical camera of a mobile platform are processed by a vision‐based odometry algorithm, which is capable of estimating the relative frame‐to‐frame movements. Then, errors accumulated in the above step are corrected using artificial markers displaced at known positions in the environment. The markers are framed from time to time, which allows the robot to maintain the drifts bounded by additionally providing it with the navigation commands needed for autonomous flight. Accuracy and robustness of the designed technique are demonstrated using an off‐the‐shelf quadrotor via extensive experimental test

Is immersive virtual reality the ultimate interface for 3D animators?

Creating computer animations is a labor-intensive task. Existing virtual reality (VR)-based animation solutions offer only heterogeneous subsets of traditional tools' functionalities. We present an add-on for the Blender animation suite that enables users to switch between native and immersive VR-based interfaces and employ the latter to perform a representative set of tasks

Permittivity optimization for Maxwell's eigenvalues

We formulate an optimization problem for the dependence of the eigenvalues of Maxwell's equations in a cavity upon variation of the electric permittivity and we prove a corresponding Maximum Principle

Translational Control in Tumour Progression and Drug Resistance

Protein biosynthesis is a multi-step process that starts with the transcription of nuclear DNA, depository of genetic information, into messenger RNA (mRNA) that is used as template for the following polypeptide chain synthesis, also known as translation. Each step of this essential process is highly controlled in order to modulate any specific protein requirement of the cell in response to different stimuli and cellular events. This regulatory process is called translational control. Deregulation of the core signalling network in translational control, the phosphatidyl inositol trisphosphate kinase (PI3K), Protein Kinase B (PKB or Akt), mammalian target of rapamycin (mTOR) and RAS mitogen-activated protein kinase (MAPK)/MAPK-interacting Kinases (MNK) pathways, frequently occurs in human cancers and leads to aberrant modulation of mRNA translation. However, investigations on the contribution of these two pathways to translational regulation led to the interesting finding that translation factors are also substrate of signalling molecules. Post-translational modifications, including cleavage and phosphorylation, usually affect translational factors activity in protein biosynthesis; on the other hand, direct interaction of translational components with signalling mediators can either activate the pathway in which the mediator is involved or redirect translation factors to other activities, such as cytoskeletal rearrangements. These findings shed light on new functions of translation factors, different from their canonical role in protein synthesis. Taken together, these new functions are an intriguing step forward to the discovery of molecular mechanisms at the base of cellular response during “special” conditions such as cancer and drug resistance

Comparing algorithms for aggressive driving event detection based on vehicle motion data

Aggressive driving is one of the main causes of fatal crashes. Correctly identifying aggressive driving events still represents a challenge in the literature. Furthermore, datasets available for testing the proposed approaches have some limitations since they generally (a) include only a few types of events, (b) contain data collected with only one device, and (c) are generated in drives that did not fully consider the variety of road characteristics and/or driving conditions. The main objective of this work is to compare the performance of several state-of-the-art algorithms for aggressive driving event detection (belonging to anomaly detection-, threshold- and machine learning-based categories) on multiple datasets containing sensors data collected with different devices (black-boxes and smartphones), on different vehicles and in different locations. A secondary objective is to verify whether smartphones could replace black-boxes in aggressive/non-aggressive classification tasks. To this aim, we propose the AD 2 (Aggressive Driving Detection) dataset, which contains (i) data collected using multiple devices to evaluate their influence on the algorithm performance, (ii) geographical data useful to analyze the context in which the events occurred, (iii) events recorded in different situations, and (iv) events generated by traveling the same path with aggressive and non-aggressive driving styles, in order to possibly separate the effects of driving style from those of road characteristics. Our experimental results highlighted the superiority of machine learning-based approaches and underlined the ability of smartphones to ensure a level of performance similar to that of black-boxes

Comparing state-of-the-art and emerging augmented reality interfaces for autonomous vehicle-to-pedestrian communication

In the last few years, a considerable literature has grown around the theme of how to provide pedestrians and other vulnerable road users (VRUs) with a clear indication about a fully autonomous vehicle (FAV)'s status and intentions, which is crucial to make FAVs and VRUs coexist. So far, a variety of external interfaces leveraging different paradigms and technologies have been created. Proposed designs include vehicle-mounted devices (like LED panels), short-range on-road projection, and road infrastructure interfaces (e.g., special asphalts with embedded displays). These designs have been experimented in different settings, using mockups, specially prepared vehicles, or virtual environments, with heterogeneous evaluation metrics. Some promising interfaces based on Augmented Reality (AR) have been proposed too, but their usability and effectiveness have not been tested yet. This paper aims to complement such body of literature by presenting a comparison of state-of-the-art interfaces and new designs under common conditions. To this aim, an immersive Virtual Reality-based simulation was developed, recreating a well-known scenario used in previous works represented by pedestrian crossing in urban environments under non-regulated conditions. A user study was then performed to investigate the various dimensions of vehicle-to-pedestrian interaction in both objective and subjective terms. Results showed that, although an interface clearly standing out over all the considered dimensions does not exists, one of the studied AR designs was able to provide state-of-the-art results in terms of safety and trust, at the cost of a higher cognitive effort and lower intuitiveness compared to LED panels showing anthropomorphic features. Together with rankings on the various dimensions, indications about advantages and drawbacks of the various alternatives that emerged from the study could be an important information source for next developments in the field