In vivo administration of a lentiviral vaccine targets DCs and induces efficient CD8(+) T cell responses.

The present study evaluates the potential of third-generation lentivirus vectors with respect to their use as in vivo-administered T cell vaccines. We demonstrate that lentivector injection into the footpad of mice transduces DCs that appear in the draining lymph node and in the spleen. In addition, a lentivector vaccine bearing a T cell antigen induced very strong systemic antigen-specific cytotoxic T lymphocyte (CTL) responses in mice. Comparative vaccination performed in two different antigen models demonstrated that in vivo administration of lentivector was superior to transfer of transduced DCs or peptide/adjuvant vaccination in terms of both amplitude and longevity of the CTL response. Our data suggest that a decisive factor for efficient T cell priming by lentivector might be the targeting of DCs in situ and their subsequent migration to secondary lymphoid organs. The combination of performance, ease of application, and absence of pre-existing immunity in humans make lentivector-based vaccines an attractive candidate for cancer immunotherapy.

Implementation Manual — 3D Engineered Models for Highway Construction: The Iowa Experience; RB33-014, 2015

3D engineered modeling is a relatively new and developing technology that can provide numerous benefits to owners, engineers, contractors, and the general public. This manual is for highway agencies that are considering or are in the process of switching from 2D plan sets to 3D engineered models in their highway construction projects. It will discuss some of the benefits, applications, limitations, and implementation considerations for 3D engineered models used for survey, design, and construction. Note that is not intended to cover all eventualities in all states regarding the deployment of 3D engineered models for highway construction. Rather, it describes how one state—Iowa—uses 3D engineered models for construction of highway projects, from planning and surveying through design and construction.

Recombinant human tumor necrosis factor: an efficient agent for cancer treatment.

Recombinant human TNF (rhTNF) has a selective effect on endothelial cells in tumour angiogenic vessels. Its clinical use has been limited because of its property to induce vascular collapsus. TNF administration through isolated limb perfusion (ILP) for regionally advanced melanomas and soft tissue sarcomas of the limbs was shown to be safe and efficient. When combined to the alkylating agent melphalan, a single ILP produces a very high objective response rate. ILP with TNF and melphalan provided the proof of concept that a vasculotoxic strategy combined to chemotherapy may produce a strong anti-tumour effect. The registered indication of TNF-based ILP is a regional therapy for regionally spread tumours. In soft tissue sarcomas, it is a limb sparing neoadjuvant treatment and, in melanoma in-transit metastases, a curative treatment. Despite its demonstrated regional efficiency TNF-based ILP is unlikely to have any impact on survival. High TNF dosages induce endothelial cells apoptosis, leading to vascular destruction. However, lower TNF dosage produces a very strong effect that is to increase the drug penetration into the tumour, presumably by decreasing the intratumoural hypertension resulting in better tumour uptake. TNF-ILP allowed the identification of the role of alphaVbeta3 integrin deactivation as an important mechanism of antiangiogenesis. Several recent studies have shown that TNF targeting is possible, paving the way to a new opportunity to administer TNF systemically for improving cancer drug penetration. TNF was the first agent registered for the treatment of cancer that improves drug penetration in tumours and selectively destroys angiogenic vessels.

Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Efficient targeted transcript discovery via array-based normalization of RACE libraries.

Rapid amplification of cDNA ends (RACE) is a widely used approach for transcript identification. Random clone selection from the RACE mixture, however, is an ineffective sampling strategy if the dynamic range of transcript abundances is large. To improve sampling efficiency of human transcripts, we hybridized the products of the RACE reaction onto tiling arrays and used the detected exons to delineate a series of reverse-transcriptase (RT)-PCRs, through which the original RACE transcript population was segregated into simpler transcript populations. We independently cloned the products and sequenced randomly selected clones. This approach, RACEarray, is superior to direct cloning and sequencing of RACE products because it specifically targets new transcripts and often results in overall normalization of transcript abundance. We show theoretically and experimentally that this strategy leads indeed to efficient sampling of new transcripts, and we investigated multiplexing the strategy by pooling RACE reactions from multiple interrogated loci before hybridization.

Implementation of the Federal Highway Administration Final Rule on Work Zone Safety and Mobility, 2007

The Federal Highway Administration published the final rule updating 23 CFR 630 Subpart J in September 2004. The revised rule requires agencies using federal funding to address both safety and mobility in planning and construction of roadway improvements. The Iowa Department of Transportation (Iowa DOT) requested the assistance of the Center for Transportation and Research in developing guidance for a policy and procedures to comply with the final rule. This report describes an in-depth examination of current Iowa DOT project development processes for all types of improvements, including maintenance, as well as a detailed characterization of work zone impact considerations throughout project completion. To comply with both the letter and perceived intent of the final rule on safety and mobility, the report features a suggested work zone policy statement and suggested revisions in the Iowa DOT project development processes, including a definition of the key element: significant projects.

An assurance-based model to holistically assess the information security posture

EXECUTIVE SUMMARY : Evaluating Information Security Posture within an organization is becoming a very complex task. Currently, the evaluation and assessment of Information Security are commonly performed using frameworks, methodologies and standards which often consider the various aspects of security independently. Unfortunately this is ineffective because it does not take into consideration the necessity of having a global and systemic multidimensional approach to Information Security evaluation. At the same time the overall security level is globally considered to be only as strong as its weakest link. This thesis proposes a model aiming to holistically assess all dimensions of security in order to minimize the likelihood that a given threat will exploit the weakest link. A formalized structure taking into account all security elements is presented; this is based on a methodological evaluation framework in which Information Security is evaluated from a global perspective. This dissertation is divided into three parts. Part One: Information Security Evaluation issues consists of four chapters. Chapter 1 is an introduction to the purpose of this research purpose and the Model that will be proposed. In this chapter we raise some questions with respect to "traditional evaluation methods" as well as identifying the principal elements to be addressed in this direction. Then we introduce the baseline attributes of our model and set out the expected result of evaluations according to our model. Chapter 2 is focused on the definition of Information Security to be used as a reference point for our evaluation model. The inherent concepts of the contents of a holistic and baseline Information Security Program are defined. Based on this, the most common roots-of-trust in Information Security are identified. Chapter 3 focuses on an analysis of the difference and the relationship between the concepts of Information Risk and Security Management. Comparing these two concepts allows us to identify the most relevant elements to be included within our evaluation model, while clearing situating these two notions within a defined framework is of the utmost importance for the results that will be obtained from the evaluation process. Chapter 4 sets out our evaluation model and the way it addresses issues relating to the evaluation of Information Security. Within this Chapter the underlying concepts of assurance and trust are discussed. Based on these two concepts, the structure of the model is developed in order to provide an assurance related platform as well as three evaluation attributes: "assurance structure", "quality issues", and "requirements achievement". Issues relating to each of these evaluation attributes are analysed with reference to sources such as methodologies, standards and published research papers. Then the operation of the model is discussed. Assurance levels, quality levels and maturity levels are defined in order to perform the evaluation according to the model. Part Two: Implementation of the Information Security Assurance Assessment Model (ISAAM) according to the Information Security Domains consists of four chapters. This is the section where our evaluation model is put into a welldefined context with respect to the four pre-defined Information Security dimensions: the Organizational dimension, Functional dimension, Human dimension, and Legal dimension. Each Information Security dimension is discussed in a separate chapter. For each dimension, the following two-phase evaluation path is followed. The first phase concerns the identification of the elements which will constitute the basis of the evaluation: ? Identification of the key elements within the dimension; ? Identification of the Focus Areas for each dimension, consisting of the security issues identified for each dimension; ? Identification of the Specific Factors for each dimension, consisting of the security measures or control addressing the security issues identified for each dimension. The second phase concerns the evaluation of each Information Security dimension by: ? The implementation of the evaluation model, based on the elements identified for each dimension within the first phase, by identifying the security tasks, processes, procedures, and actions that should have been performed by the organization to reach the desired level of protection; ? The maturity model for each dimension as a basis for reliance on security. For each dimension we propose a generic maturity model that could be used by every organization in order to define its own security requirements. Part three of this dissertation contains the Final Remarks, Supporting Resources and Annexes. With reference to the objectives of our thesis, the Final Remarks briefly analyse whether these objectives were achieved and suggest directions for future related research. Supporting resources comprise the bibliographic resources that were used to elaborate and justify our approach. Annexes include all the relevant topics identified within the literature to illustrate certain aspects of our approach. Our Information Security evaluation model is based on and integrates different Information Security best practices, standards, methodologies and research expertise which can be combined in order to define an reliable categorization of Information Security. After the definition of terms and requirements, an evaluation process should be performed in order to obtain evidence that the Information Security within the organization in question is adequately managed. We have specifically integrated into our model the most useful elements of these sources of information in order to provide a generic model able to be implemented in all kinds of organizations. The value added by our evaluation model is that it is easy to implement and operate and answers concrete needs in terms of reliance upon an efficient and dynamic evaluation tool through a coherent evaluation system. On that basis, our model could be implemented internally within organizations, allowing them to govern better their Information Security. RÉSUMÉ : Contexte général de la thèse L'évaluation de la sécurité en général, et plus particulièrement, celle de la sécurité de l'information, est devenue pour les organisations non seulement une mission cruciale à réaliser, mais aussi de plus en plus complexe. A l'heure actuelle, cette évaluation se base principalement sur des méthodologies, des bonnes pratiques, des normes ou des standards qui appréhendent séparément les différents aspects qui composent la sécurité de l'information. Nous pensons que cette manière d'évaluer la sécurité est inefficiente, car elle ne tient pas compte de l'interaction des différentes dimensions et composantes de la sécurité entre elles, bien qu'il soit admis depuis longtemps que le niveau de sécurité globale d'une organisation est toujours celui du maillon le plus faible de la chaîne sécuritaire. Nous avons identifié le besoin d'une approche globale, intégrée, systémique et multidimensionnelle de l'évaluation de la sécurité de l'information. En effet, et c'est le point de départ de notre thèse, nous démontrons que seule une prise en compte globale de la sécurité permettra de répondre aux exigences de sécurité optimale ainsi qu'aux besoins de protection spécifiques d'une organisation. Ainsi, notre thèse propose un nouveau paradigme d'évaluation de la sécurité afin de satisfaire aux besoins d'efficacité et d'efficience d'une organisation donnée. Nous proposons alors un modèle qui vise à évaluer d'une manière holistique toutes les dimensions de la sécurité, afin de minimiser la probabilité qu'une menace potentielle puisse exploiter des vulnérabilités et engendrer des dommages directs ou indirects. Ce modèle se base sur une structure formalisée qui prend en compte tous les éléments d'un système ou programme de sécurité. Ainsi, nous proposons un cadre méthodologique d'évaluation qui considère la sécurité de l'information à partir d'une perspective globale. Structure de la thèse et thèmes abordés Notre document est structuré en trois parties. La première intitulée : « La problématique de l'évaluation de la sécurité de l'information » est composée de quatre chapitres. Le chapitre 1 introduit l'objet de la recherche ainsi que les concepts de base du modèle d'évaluation proposé. La maniéré traditionnelle de l'évaluation de la sécurité fait l'objet d'une analyse critique pour identifier les éléments principaux et invariants à prendre en compte dans notre approche holistique. Les éléments de base de notre modèle d'évaluation ainsi que son fonctionnement attendu sont ensuite présentés pour pouvoir tracer les résultats attendus de ce modèle. Le chapitre 2 se focalise sur la définition de la notion de Sécurité de l'Information. Il ne s'agit pas d'une redéfinition de la notion de la sécurité, mais d'une mise en perspectives des dimensions, critères, indicateurs à utiliser comme base de référence, afin de déterminer l'objet de l'évaluation qui sera utilisé tout au long de notre travail. Les concepts inhérents de ce qui constitue le caractère holistique de la sécurité ainsi que les éléments constitutifs d'un niveau de référence de sécurité sont définis en conséquence. Ceci permet d'identifier ceux que nous avons dénommés « les racines de confiance ». Le chapitre 3 présente et analyse la différence et les relations qui existent entre les processus de la Gestion des Risques et de la Gestion de la Sécurité, afin d'identifier les éléments constitutifs du cadre de protection à inclure dans notre modèle d'évaluation. Le chapitre 4 est consacré à la présentation de notre modèle d'évaluation Information Security Assurance Assessment Model (ISAAM) et la manière dont il répond aux exigences de l'évaluation telle que nous les avons préalablement présentées. Dans ce chapitre les concepts sous-jacents relatifs aux notions d'assurance et de confiance sont analysés. En se basant sur ces deux concepts, la structure du modèle d'évaluation est développée pour obtenir une plateforme qui offre un certain niveau de garantie en s'appuyant sur trois attributs d'évaluation, à savoir : « la structure de confiance », « la qualité du processus », et « la réalisation des exigences et des objectifs ». Les problématiques liées à chacun de ces attributs d'évaluation sont analysées en se basant sur l'état de l'art de la recherche et de la littérature, sur les différentes méthodes existantes ainsi que sur les normes et les standards les plus courants dans le domaine de la sécurité. Sur cette base, trois différents niveaux d'évaluation sont construits, à savoir : le niveau d'assurance, le niveau de qualité et le niveau de maturité qui constituent la base de l'évaluation de l'état global de la sécurité d'une organisation. La deuxième partie: « L'application du Modèle d'évaluation de l'assurance de la sécurité de l'information par domaine de sécurité » est elle aussi composée de quatre chapitres. Le modèle d'évaluation déjà construit et analysé est, dans cette partie, mis dans un contexte spécifique selon les quatre dimensions prédéfinies de sécurité qui sont: la dimension Organisationnelle, la dimension Fonctionnelle, la dimension Humaine, et la dimension Légale. Chacune de ces dimensions et son évaluation spécifique fait l'objet d'un chapitre distinct. Pour chacune des dimensions, une évaluation en deux phases est construite comme suit. La première phase concerne l'identification des éléments qui constituent la base de l'évaluation: ? Identification des éléments clés de l'évaluation ; ? Identification des « Focus Area » pour chaque dimension qui représentent les problématiques se trouvant dans la dimension ; ? Identification des « Specific Factors » pour chaque Focus Area qui représentent les mesures de sécurité et de contrôle qui contribuent à résoudre ou à diminuer les impacts des risques. La deuxième phase concerne l'évaluation de chaque dimension précédemment présentées. Elle est constituée d'une part, de l'implémentation du modèle général d'évaluation à la dimension concernée en : ? Se basant sur les éléments spécifiés lors de la première phase ; ? Identifiant les taches sécuritaires spécifiques, les processus, les procédures qui auraient dû être effectués pour atteindre le niveau de protection souhaité. D'autre part, l'évaluation de chaque dimension est complétée par la proposition d'un modèle de maturité spécifique à chaque dimension, qui est à considérer comme une base de référence pour le niveau global de sécurité. Pour chaque dimension nous proposons un modèle de maturité générique qui peut être utilisé par chaque organisation, afin de spécifier ses propres exigences en matière de sécurité. Cela constitue une innovation dans le domaine de l'évaluation, que nous justifions pour chaque dimension et dont nous mettons systématiquement en avant la plus value apportée. La troisième partie de notre document est relative à la validation globale de notre proposition et contient en guise de conclusion, une mise en perspective critique de notre travail et des remarques finales. Cette dernière partie est complétée par une bibliographie et des annexes. Notre modèle d'évaluation de la sécurité intègre et se base sur de nombreuses sources d'expertise, telles que les bonnes pratiques, les normes, les standards, les méthodes et l'expertise de la recherche scientifique du domaine. Notre proposition constructive répond à un véritable problème non encore résolu, auquel doivent faire face toutes les organisations, indépendamment de la taille et du profil. Cela permettrait à ces dernières de spécifier leurs exigences particulières en matière du niveau de sécurité à satisfaire, d'instancier un processus d'évaluation spécifique à leurs besoins afin qu'elles puissent s'assurer que leur sécurité de l'information soit gérée d'une manière appropriée, offrant ainsi un certain niveau de confiance dans le degré de protection fourni. Nous avons intégré dans notre modèle le meilleur du savoir faire, de l'expérience et de l'expertise disponible actuellement au niveau international, dans le but de fournir un modèle d'évaluation simple, générique et applicable à un grand nombre d'organisations publiques ou privées. La valeur ajoutée de notre modèle d'évaluation réside précisément dans le fait qu'il est suffisamment générique et facile à implémenter tout en apportant des réponses sur les besoins concrets des organisations. Ainsi notre proposition constitue un outil d'évaluation fiable, efficient et dynamique découlant d'une approche d'évaluation cohérente. De ce fait, notre système d'évaluation peut être implémenté à l'interne par l'entreprise elle-même, sans recourir à des ressources supplémentaires et lui donne également ainsi la possibilité de mieux gouverner sa sécurité de l'information.

Oscillations, phase-of-firing coding, and spike timing-dependent plasticity: an efficient learning scheme

Recent experiments have established that information can be encoded in the spike times of neurons relative to the phase of a background oscillation in the local field potential—a phenomenon referred to as “phase-of-firing coding” (PoFC). These firing phase preferences could result from combining an oscillation in the input current with a stimulus-dependent static component that would produce the variations in preferred phase, but it remains unclear whether these phases are an epiphenomenon or really affect neuronal interactions—only then could they have a functional role. Here we show that PoFC has a major impact on downstream learning and decoding with the now well established spike timing-dependent plasticity (STDP). To be precise, we demonstrate with simulations how a single neuron equipped with STDP robustly detects a pattern of input currents automatically encoded in the phases of a subset of its afferents, and repeating at random intervals. Remarkably, learning is possible even when only a small fraction of the afferents (~10%) exhibits PoFC. The ability of STDP to detect repeating patterns had been noted before in continuous activity, but it turns out that oscillations greatly facilitate learning. A benchmark with more conventional rate-based codes demonstrates the superiority of oscillations and PoFC for both STDP-based learning and the speed of decoding: the oscillation partially formats the input spike times, so that they mainly depend on the current input currents, and can be efficiently learned by STDP and then recognized in just one oscillation cycle. This suggests a major functional role for oscillatory brain activity that has been widely reported experimentally.

Effective squark/chargino/neutralino couplings: MadGraph implementation

We have included the effective description of squark interactions with charginos/neutralinos in the MadGraph MSSM model. This effective description includes the effective Yukawa couplings, and another logarithmic term which encodes the supersymmetry-breaking. We have performed an extensive test of our implementation analyzing the results of the partial decay widths of squarks into charginos and neutralinos obtained by using FeynArts/FormCalc programs and the new model file in MadGraph. We present results for the cross-section of top-squark production decaying into charginos and neutralinos.

Review of Automated Vehicle Technology: Policy and Implementation Implications; Version 1.0; RB28-015, 2016

This report provides recommendations for the state of Iowa over the next five years in regards to automated vehicle policy development. These administrative, planning, legal, and community strategy recommendations for government agencies include: • Encouraging automation by preparing government agencies, infrastructure, leveraging procurement, and advocating for safety mandates • Adjusting long range planning processes by identifying and incorporating a wide range of new automation scenarios • Beginning to analyze and, as necessary, clarify existing law as it apples to automated driving • Auditing existing law • Enforcing existing laws • Ensuring vehicle owners and operators bear the true cost of driving • Embracing flexibility by giving agencies the statutory authority to achieve regulatory goals through different means, allowing them to make small-scale exemptions to statutory regimes and clarifying their enforcement discretion • Thinking locally and preparing publicly • Sharing the steps being taken to promote (as well as to anticipate and regulate) automated driving • Instituting public education about automated vehicle technologies.

Embankment Quality and Assessment of Moisture Control Implementation, TR-677, 2016

A specification for contractor moisture quality control (QC) in roadway embankment construction has been in use for approximately 10 years in Iowa on about 190 projects. The use of this QC specification and the development of the soils certification program for the Iowa Department of Transportation (DOT) originated from Iowa Highway Research Board (IHRB) embankment quality research projects. Since this research, the Iowa DOT has applied compaction with moisture control on most embankment work under pavements. This study set out to independently evaluate the actual quality of compaction using the current specifications. Results show that Proctor tests conducted by Iowa State University (ISU) using representative material obtained from each test section where field testing was conducted had optimum moisture contents and maximum dry densities that are different from what was selected by the Iowa DOT for QC/quality assurance (QA) testing. Comparisons between the measured and selected values showed a standard error of 2.9 lb/ft3 for maximum dry density and 2.1% for optimum moisture content. The difference in optimum moisture content was as high as 4% and the difference in maximum dry density was as high as 6.5 lb/ft3 . The difference at most test locations, however, were within the allowable variation suggested in AASHTO T 99 for test results between different laboratories. The ISU testing results showed higher rates of data outside of the target limits specified based on the available contractor QC data for cohesive materials. Also, during construction observations, wet fill materials were often observed. Several test points indicated that materials were placed and accepted at wet of the target moisture contents. The statistical analysis results indicate that the results obtained from this study showed improvements over results from previous embankment quality research projects (TR-401 Phases I through III and TR-492) in terms of the percentage of data that fell within the specification limits. Although there was evidence of improvement, QC/QA results are not consistently meeting the target limits/values. Recommendations are provided in this report for Iowa DOT consideration with three proposed options for improvements to the current specifications. Option 1 provides enhancements to current specifications in terms of material-dependent control limits, training, sampling, and process control. Option 2 addresses development of alternative specifications that incorporate dynamic cone penetrometer or light weight deflectometer testing into QC/QA. Option 3 addresses incorporating calibrated intelligent compaction measurements into QC/QA.

Optimization strategies for fast detection of positive selection on phylogenetic trees.

MOTIVATION: The detection of positive selection is widely used to study gene and genome evolution, but its application remains limited by the high computational cost of existing implementations. We present a series of computational optimizations for more efficient estimation of the likelihood function on large-scale phylogenetic problems. We illustrate our approach using the branch-site model of codon evolution. RESULTS: We introduce novel optimization techniques that substantially outperform both CodeML from the PAML package and our previously optimized sequential version SlimCodeML. These techniques can also be applied to other likelihood-based phylogeny software. Our implementation scales well for large numbers of codons and/or species. It can therefore analyse substantially larger datasets than CodeML. We evaluated FastCodeML on different platforms and measured average sequential speedups of FastCodeML (single-threaded) versus CodeML of up to 5.8, average speedups of FastCodeML (multi-threaded) versus CodeML on a single node (shared memory) of up to 36.9 for 12 CPU cores, and average speedups of the distributed FastCodeML versus CodeML of up to 170.9 on eight nodes (96 CPU cores in total).Availability and implementation: ftp://ftp.vital-it.ch/tools/FastCodeML/. CONTACT: selectome@unil.ch or nicolas.salamin@unil.ch.