The neuroscience of cognitive enhancement : enhanced attention, working memory and visual information processing speed using 3D-MOT

Des interventions ciblant l’amélioration cognitive sont de plus en plus à l’intérêt dans nombreux domaines, y compris la neuropsychologie. Bien qu'il existe de nombreuses méthodes pour maximiser le potentiel cognitif de quelqu’un, ils sont rarement appuyé par la recherche scientifique. D’abord, ce mémoire examine brièvement l'état des interventions d'amélioration cognitives. Il décrit premièrement les faiblesses observées dans ces pratiques et par conséquent il établit un modèle standard contre lequel on pourrait et devrait évaluer les diverses techniques ciblant l'amélioration cognitive. Une étude de recherche est ensuite présenté qui considère un nouvel outil de l'amélioration cognitive, une tâche d’entrainement perceptivo-cognitive : 3-dimensional multiple object tracking (3D-MOT). Il examine les preuves actuelles pour le 3D-MOT auprès du modèle standard proposé. Les résultats de ce projet démontrent de l’augmentation dans les capacités d’attention, de mémoire de travail visuel et de vitesse de traitement d’information. Cette étude représente la première étape dans la démarche vers l’établissement du 3D-MOT comme un outil d’amélioration cognitive.

Optimal control of non-linear systems through hybrid cell-mapping/artificial-neural-networks techniques

In this paper, a real-time optimal control technique for non-linear plants is proposed. The control system makes use of the cell-mapping (CM) techniques, widely used for the global analysis of highly non-linear systems. The CM framework is employed for designing approximate optimal controllers via a control variable discretization. Furthermore, CM-based designs can be improved by the use of supervised feedforward artificial neural networks (ANNs), which have proved to be universal and efficient tools for function approximation, providing also very fast responses. The quantitative nature of the approximate CM solutions fits very well with ANNs characteristics. Here, we propose several control architectures which combine, in a different manner, supervised neural networks and CM control algorithms. On the one hand, different CM control laws computed for various target objectives can be employed for training a neural network, explicitly including the target information in the input vectors. This way, tracking problems, in addition to regulation ones, can be addressed in a fast and unified manner, obtaining smooth, averaged and global feedback control laws. On the other hand, adjoining CM and ANNs are also combined into a hybrid architecture to address problems where accuracy and real-time response are critical. Finally, some optimal control problems are solved with the proposed CM, neural and hybrid techniques, illustrating their good performance.

The neuroscience of cognitive enhancement : enhanced attention, working memory and visual information processing speed using 3D-MOT

Des interventions ciblant l’amélioration cognitive sont de plus en plus à l’intérêt dans nombreux domaines, y compris la neuropsychologie. Bien qu'il existe de nombreuses méthodes pour maximiser le potentiel cognitif de quelqu’un, ils sont rarement appuyé par la recherche scientifique. D’abord, ce mémoire examine brièvement l'état des interventions d'amélioration cognitives. Il décrit premièrement les faiblesses observées dans ces pratiques et par conséquent il établit un modèle standard contre lequel on pourrait et devrait évaluer les diverses techniques ciblant l'amélioration cognitive. Une étude de recherche est ensuite présenté qui considère un nouvel outil de l'amélioration cognitive, une tâche d’entrainement perceptivo-cognitive : 3-dimensional multiple object tracking (3D-MOT). Il examine les preuves actuelles pour le 3D-MOT auprès du modèle standard proposé. Les résultats de ce projet démontrent de l’augmentation dans les capacités d’attention, de mémoire de travail visuel et de vitesse de traitement d’information. Cette étude représente la première étape dans la démarche vers l’établissement du 3D-MOT comme un outil d’amélioration cognitive.

South Carolina alligator hunting guide for 2016

This booklet was developed to provide basic information regarding the alligator hunting season and what hunters will need in order to familiarize themselves with taking alligators. It includes common hunting techniques, safety tips, how to harvest an alligator, requirements for processing an alligator, and how to care for an alligator hide.

How to Efficiently Control the Title and Registration Mail-in Workload Backlog Processing

The Titles and Registration Mail-In Unit of the Department of Motor Vehicles only processes title and registration work that has been mailed in. During the time periods of May through June and November through January, the mail workload backlog becomes overbearing. This research will attempt to find out the cause of this increase backlog during those periods, determine what procedures or steps are currently in place and unnecessarily creating needless work that has a direct correlation with the backlog and deploy a recommendation that will totally eliminate peak time backlog work loads.

Waste Disposal Requirements for Commercial Deer-Processing Facilities

Waste from a deer-processing facility is required by law to be disposed of in any permitted municipal solid waste (Class 3) landfill or a permitted construction and demolition debris (Class 2) landfill that has specific approval to accept animal carcasses. Disposal of deer-processing waste on the property of the processing facility or at any other unpermitted site IS NOT ALLOWED. Waste from commercial deer processing facilities must be disposed of per the requirements of the S.C. Solid Waste Policy and Management Act of 1991.

Experimentation of mitigation techniques to reduce the effects of permafrost degradation on transportation infrastructures at Beaver Creek experimental road site, Alaska Highway, Yukon

Les méthodes de design et de construction des routes développés dans le sud canadien ont maintenant besoin d’être adaptés aux environnements nordiques du pays afin de prévenir le dégel dramatique du pergélisol lors de la construction d’une nouvelle route. De plus, le réchauffement climatique occasionne présentement d’importants problèmes de stabilité des sols dans le nord canadien. Ces facteurs causent des pertes importantes au niveau des capacités fonctionnelles et structurales de l’Alaska Highway au Yukon sur un segment de plus de 200 km situé entre le village de Destruction Bay et la frontière de l’Alaska. Afin de trouver des solutions rentables à long terme, le ministère du transport du Yukon (en collaboration avec le Federal Highway Administration du gouvernement américain, Transports Canada, l’Université Laval, l’Université de Montréal et l’Alaska University transportation Center) a mis en place 12 sections d’essais de 50 mètres de longueur sur l’autoroute de l’Alaska près de Beaver Creek en 2008. Ces différentes sections d’essais ont été conçues pour évaluer une ou plusieurs méthodes combinées de stabilisation thermique telles que le drain thermique, le remblai à convection d’air, le pare-neige / pare-soleil, le remblai couvert de matières organiques, les drains longitudinaux, le déblaiement de la neige sur les pentes et la surface réfléchissante. Les objectifs spécifiques de la recherche sont 1) d’établir les régimes thermiques et les flux de chaleur dans chacune des sections pour les 3 premières années de fonctionnement ; 2) de documenter les facteurs pouvant favoriser ou nuire à l’efficacité des systèmes de protection et ; 3) de déterminer le rapport coûts/bénéfices à long terme pour chacune des techniques utilisées. Pour ce faire, une nouvelle méthode d’analyse, basée sur la mesure de flux d’extraction de chaleur Hx et d’induction Hi à l’interface entre le remblai et le sol naturel, a été utilisée dans cette étude. Certaines techniques de protection du pergélisol démontrent un bon potentiel durant leurs 3 premières années de fonctionnement. C’est le cas pour le remblai à convection d’air non-couvert, le remblai à convection d’air pleine largeur, les drains longitudinaux, le pare-soleil / pare-neige et la surface réfléchissante. Malheureusement, des problèmes dans l’installation des drains thermiques ont empêché une évaluation complète de leur efficacité.

L’accompagnement des stagiaires au premier stage du programme collégial de techniques d’éducation spécialisée selon le point de vue de la triade de formation

L'éducation spécialisée est un domaine comportant plusieurs champs d'application possible puisque les clientèles sont variées. Toute personne possédant une difficulté d'adaptation ou de réadaptation peut bénéficier des interventions d'une éducatrice spécialisée ou d'un éducateur spécialisé. La relation d'aide étant appliquée par des personnes envers d'autres personnes, il ne s'agit pas d'une matière aussi logique et prévisible que d'autres sciences plus précises. Cette réalité impose la présence de stages dans la formation pour permettre aux futurs intervenants d'apprendre à se connaître dans des situations d'intervention et d'appliquer des techniques appropriées visant la réhabilitation des personnes en souffrance. La formation collégiale en techniques d'éducation spécialisée dispensée par le Collège de Valleyfield exige trois stages, dont le premier se déroule dès la première année d'études. Ce stage revêt une importance capitale puisqu'il est le premier contact réel pour l'étudiante ou l'étudiant avec son choix d'études. Cependant, les balises de l'accompagnement de ce stage sont variables et la ligne commune se résume au plan de stage qui est utilisé par l'ensemble des superviseurs, mais appliqué de façon individualiste. Les accompagnateurs, qui sont les intervenants du milieu d'intervention accueillant la ou le stagiaire, possèdent, quant à eux, un document décrivant leurs responsabilités dans le cadre de cette formation pratique ainsi que les responsabilités du stagiaire et du superviseur. L'importance de ce stage étant indéniable, il importe d'identifier les conditions favorables à mettre en place dans l'accompagnement du stage pour favoriser la réussite de ce stage. Pour ce faire, il faut dégager les étapes vécues par les stagiaires durant ce premier stage, puis identifier leurs besoins à chacune de ces étapes. Cette mise au point permettra alors de déterminer les rôles de chaque acteur de la triade, soit les accompagnateurs, les superviseurs et les étudiants, pour chacune de ces étapes. Dans le but de répondre à ces objectifs, une collecte de données s'imposait auprès des différents acteurs impliqués. La méthode privilégiée fut des entrevues, de groupe ou individuelles, selon la disponibilité des personnes concernées. Ces entrevues, réalisées à partir d'un guide d'entrevue semi-directif construit spécifiquement pour ces rencontres, ont conduit à des résultats et des recommandations spécifiques à ce premier stage. Une étape préliminaire au début du stage a été identifiée. Cette étape, constituée de questionnement et d'anxiété pour les futurs stagiaires, devrait être prise en considération par les superviseurs qui pourraient effectuer au moins deux rencontres avec ces étudiantes et ces étudiants pour les informer, les rassurer et les responsabiliser dans leur implication en les amenant à approfondir leurs connaissances du milieu d'intervention dans lequel elles ou ils feront leur premier stage. Durant le stage, une période d'observation, suivie d'une première prise de contact timide avec la clientèle puis d'interventions plus structurées, constituent le coeur de cette formation pratique. Cette phase doit être ponctuée de rétroaction de la part de l'accompagnateur et du superviseur qui peuvent alors renforcer positivement la ou le stagiaire ou la ou le rediriger dans ses interventions. Puis, la fin du stage, qui impose un détachement à l'égard de la clientèle et la ou le stagiaire, doit être préalablement préparée. L'accompagnatrice ou l'accompagnateur doit soutenir la ou le stagiaire dans cette transition de façon à ce que la clientèle ne soit pas affectée par cette coupure, alors que la ou le superviseur peut accompagner la ou le stagiaire dans son vécu affectif face à cette fin. Comme la littérature se fait très discrète dans le domaine de la formation à l'éducation spécialisée, les recommandations effectuées dans cet essai sont certainement appropriées à divulguer aux enseignantes et enseignants de ce domaine, qui pourront décider de leur pertinence et de leur utilisation.

Query routing in cooperative semi-structured peer-to-peer information retrieval networks

Conventional web search engines are centralised in that a single entity crawls and indexes the documents selected for future retrieval, and the relevance models used to determine which documents are relevant to a given user query. As a result, these search engines suffer from several technical drawbacks such as handling scale, timeliness and reliability, in addition to ethical concerns such as commercial manipulation and information censorship. Alleviating the need to rely entirely on a single entity, Peer-to-Peer (P2P) Information Retrieval (IR) has been proposed as a solution, as it distributes the functional components of a web search engine – from crawling and indexing documents, to query processing – across the network of users (or, peers) who use the search engine. This strategy for constructing an IR system poses several efficiency and effectiveness challenges which have been identified in past work. Accordingly, this thesis makes several contributions towards advancing the state of the art in P2P-IR effectiveness by improving the query processing and relevance scoring aspects of a P2P web search. Federated search systems are a form of distributed information retrieval model that route the user’s information need, formulated as a query, to distributed resources and merge the retrieved result lists into a final list. P2P-IR networks are one form of federated search in routing queries and merging result among participating peers. The query is propagated through disseminated nodes to hit the peers that are most likely to contain relevant documents, then the retrieved result lists are merged at different points along the path from the relevant peers to the query initializer (or namely, customer). However, query routing in P2P-IR networks is considered as one of the major challenges and critical part in P2P-IR networks; as the relevant peers might be lost in low-quality peer selection while executing the query routing, and inevitably lead to less effective retrieval results. This motivates this thesis to study and propose query routing techniques to improve retrieval quality in such networks. Cluster-based semi-structured P2P-IR networks exploit the cluster hypothesis to organise the peers into similar semantic clusters where each such semantic cluster is managed by super-peers. In this thesis, I construct three semi-structured P2P-IR models and examine their retrieval effectiveness. I also leverage the cluster centroids at the super-peer level as content representations gathered from cooperative peers to propose a query routing approach called Inverted PeerCluster Index (IPI) that simulates the conventional inverted index of the centralised corpus to organise the statistics of peers’ terms. The results show a competitive retrieval quality in comparison to baseline approaches. Furthermore, I study the applicability of using the conventional Information Retrieval models as peer selection approaches where each peer can be considered as a big document of documents. The experimental evaluation shows comparative and significant results and explains that document retrieval methods are very effective for peer selection that brings back the analogy between documents and peers. Additionally, Learning to Rank (LtR) algorithms are exploited to build a learned classifier for peer ranking at the super-peer level. The experiments show significant results with state-of-the-art resource selection methods and competitive results to corresponding classification-based approaches. Finally, I propose reputation-based query routing approaches that exploit the idea of providing feedback on a specific item in the social community networks and manage it for future decision-making. The system monitors users’ behaviours when they click or download documents from the final ranked list as implicit feedback and mines the given information to build a reputation-based data structure. The data structure is used to score peers and then rank them for query routing. I conduct a set of experiments to cover various scenarios including noisy feedback information (i.e, providing positive feedback on non-relevant documents) to examine the robustness of reputation-based approaches. The empirical evaluation shows significant results in almost all measurement metrics with approximate improvement more than 56% compared to baseline approaches. Thus, based on the results, if one were to choose one technique, reputation-based approaches are clearly the natural choices which also can be deployed on any P2P network.

Non-Equilibrium Atmospheric Plasma As A Novel Route To Nanomaterial Synthesis And Processing For Biomedical Applications

Since last century, the rising interest of value-added and advanced functional materials has spurred a ceaseless development in terms of industrial processes and applications. Among the emerging technologies, thanks to their unique features and versatility in terms of supported processes, non-equilibrium plasma discharges appear as a key solvent-free, high-throughput and cost-efficient technique. Nevertheless, applied research studies are needed with the aim of addressing plasma potentialities optimizing devices and processes for future industrial applications. In this framework, the aim of this dissertation is to report on the activities carried out and the results achieved concerning the development and optimization of plasma techniques for nanomaterial synthesis and processing to be applied in the biomedical field. In the first section, the design and investigation of a plasma assisted process for the production of silver (Ag) nanostructured multilayer coatings exhibiting anti-biofilm and anti-clot properties is described. With the aim on enabling in-situ and on-demand deposition of Ag nanoparticles (NPs), the optimization of a continuous in-flight aerosol process for particle synthesis is reported. The stability and promising biological performances of deposited coatings spurred further investigation through in-vitro and in-vivo tests which results are reported and discussed. With the aim of addressing the unanswered questions and tuning NPs functionalities, the second section concerns the study of silver containing droplet conversion in a flow-through plasma reactor. The presented results, obtained combining different analysis techniques, support a formation mechanism based on droplet to particle conversion driven by plasma induced precursor reduction. Finally, the third section deals with the development of a simulative and experimental approach used to investigate the in-situ droplet evaporation inside the plasma discharge addressing the main contributions to liquid evaporation in the perspective of process industrial scale up.

Abstractive Long Document Summarization: Studio e Sperimentazione di Modelli Generativi Retrieval-Augmented

In questa tesi si trattano lo studio e la sperimentazione di un modello generativo retrieval-augmented, basato su Transformers, per il task di Abstractive Summarization su lunghe sentenze legali. La sintesi automatica del testo (Automatic Text Summarization) è diventata un task di Natural Language Processing (NLP) molto importante oggigiorno, visto il grandissimo numero di dati provenienti dal web e banche dati. Inoltre, essa permette di automatizzare un processo molto oneroso per gli esperti, specialmente nel settore legale, in cui i documenti sono lunghi e complicati, per cui difficili e dispendiosi da riassumere. I modelli allo stato dell’arte dell’Automatic Text Summarization sono basati su soluzioni di Deep Learning, in particolare sui Transformers, che rappresentano l’architettura più consolidata per task di NLP. Il modello proposto in questa tesi rappresenta una soluzione per la Long Document Summarization, ossia per generare riassunti di lunghe sequenze testuali. In particolare, l’architettura si basa sul modello RAG (Retrieval-Augmented Generation), recentemente introdotto dal team di ricerca Facebook AI per il task di Question Answering. L’obiettivo consiste nel modificare l’architettura RAG al fine di renderla adatta al task di Abstractive Long Document Summarization. In dettaglio, si vuole sfruttare e testare la memoria non parametrica del modello, con lo scopo di arricchire la rappresentazione del testo di input da riassumere. A tal fine, sono state sperimentate diverse configurazioni del modello su diverse tipologie di esperimenti e sono stati valutati i riassunti generati con diverse metriche automatiche.

Computational Investigation of the Molecular Mechanisms Regulating Nucleic Acid Processing Metalloenzymes

Polymerases and nucleases are enzymes processing DNA and RNA. They are involved in crucial processes for cell life by performing the extension and the cleavage of nucleic acid chains during genome replication and maintenance. Additionally, both enzymes are often associated to several diseases, including cancer. In order to catalyze the reaction, most of them operate via the two-metal-ion mechanism. For this, despite showing relevant differences in structure, function and catalytic properties, they share common catalytic elements, which comprise the two catalytic ions and their first-shell acidic residues. Notably, recent studies of different metalloenzymes revealed the recurrent presence of additional elements surrounding the active site, thus suggesting an extended two-metal-ion-centered architecture. However, whether these elements have a catalytic function and what is their role is still unclear. In this work, using state-of-the-art computational techniques, second- and third-shell elements are showed to act in metallonucleases favoring the substrate positioning and leaving group release. In particular, in hExo1 a transient third metal ion is recruited and positioned near the two-metal-ion site by a structurally conserved acidic residue to assist the leaving group departure. Similarly, in hFEN1 second- and third-shell Arg/Lys residues operate the phosphate steering mechanism through (i) substrate recruitment, (ii) precise cleavage localization, and (iii) leaving group release. Importantly, structural comparisons of hExo1, hFEN1 and other metallonucleases suggest that similar catalytic mechanisms may be shared by other enzymes. Overall, the results obtained provide an extended vision on parallel strategies adopted by metalloenzymes, which employ divalent metal ion or positively charged residues to ensure efficient and specific catalysis. Furthermore, these outcomes may have implications for de novo enzyme engineering and/or drug design to modulate nucleic acid processing.

Impact of Geomatic Techniques on Topo-Bathymetric Surveys for Coastal Analysis

Sandy coasts represent vital areas whose preservation and maintenance also involve economic and tourist interests. Besides, these dynamic environments undergo the erosion process at different levels depending on their specific characteristics. For this reason, defence interventions are commonly realized by combining engineering solutions and management policies to evaluate their effects over time. Monitoring activities represent the fundamental instrument to obtain a deep knowledge of the investigated phenomenon. Thanks to technological development, several possibilities both in terms of geomatic surveying techniques and processing tools are available, allowing to reach high performances and accuracy. Nevertheless, when the littoral definition includes both emerged and submerged beaches, several issues have to be considered. Therefore, the geomatic surveys and all the following steps need to be calibrated according to the individual application, with the reference system, accuracy and spatial resolution as primary aspects. This study provides the evaluation of the available geomatic techniques, processing approaches, and derived products, aiming at optimising the entire workflow of coastal monitoring by adopting an accuracy-efficiency trade-off. The presented analyses highlight the balance point when the increase in performance becomes an additional value for the obtained products ensuring proper data management. This perspective can represent a helpful instrument to properly plan the monitoring activities according to the specific purposes of the analysis. Finally, the primary uses of the acquired and processed data in monitoring contexts are presented, also considering possible applications for numerical modelling as supporting tools. Moreover, the theme of coastal monitoring has been addressed throughout this thesis by considering a practical point of view, linking to the activities performed by Arpae (Regional agency for prevention, environment and energy of Emilia-Romagna). Indeed, the Adriatic coast of Emilia-Romagna, where sandy beaches particularly exposed to erosion are present, has been chosen as a case study for all the analyses and considerations.

Interference mitigation techniques for cloud-RAN deployments in 5G and beyond systems

The deployment of ultra-dense networks is one of the most promising solutions to manage the phenomenon of co-channel interference that affects the latest wireless communication systems, especially in hotspots. To meet the requirements of the use-cases and the immense amount of traffic generated in these scenarios, 5G ultra-dense networks are being deployed using various technologies, such as distributed antenna system (DAS) and cloud-radio access network (C-RAN). Through these centralized densification schemes, virtualized baseband processing units coordinate the distributed access points and manage the available network resources. In particular, link adaptation techniques are shown to be fundamental to overall system operation and performance enhancement. The core of this dissertation is the result of an analysis and a comparison of dynamic and adaptive methods for modulation and coding scheme (MCS) selection applied to the latest mobile telecommunications standards. A novel algorithm based on the proportional-integral-derivative (PID) controller principles and block error rate (BLER) target has been proposed. Tests were conducted in a 4G and 5G system level laboratory and, by means of a channel emulator, the performance was evaluated for different channel models and target BLERs. Furthermore, due to the intrinsic sectorization of the end-users distribution in the investigated scenario, a preliminary analysis on the joint application of users grouping algorithms with multi-antenna and multi-user techniques has been performed. In conclusion, the importance and impact of other fundamental physical layer operations, such as channel estimation and power control, on the overall end-to-end system behavior and performance were highlighted.

Deploying and processing neural representations of signals

Neural representations (NR) have emerged in the last few years as a powerful tool to represent signals from several domains, such as images, 3D shapes, or audio. Indeed, deep neural networks have been shown capable of approximating continuous functions that describe a given signal with theoretical infinite resolution. This finding allows obtaining representations whose memory footprint is fixed and decoupled from the resolution at which the underlying signal can be sampled, something that is not possible with traditional discrete representations, e.g., grids of pixels for images or voxels for 3D shapes. During the last two years, many techniques have been proposed to improve the capability of NR to approximate high-frequency details and to make the optimization procedures required to obtain NR less demanding both in terms of time and data requirements, motivating many researchers to deploy NR as the main form of data representation for complex pipelines. Following this line of research, we first show that NR can approximate precisely Unsigned Distance Functions, providing an effective way to represent garments that feature open 3D surfaces and unknown topology. Then, we present a pipeline to obtain in a few minutes a compact Neural Twin® for a given object, by exploiting the recent advances in modeling neural radiance fields. Furthermore, we move a step in the direction of adopting NR as a standalone representation, by considering the possibility of performing downstream tasks by processing directly the NR weights. We first show that deep neural networks can be compressed into compact latent codes. Then, we show how this technique can be exploited to perform deep learning on implicit neural representations (INR) of 3D shapes, by only looking at the weights of the networks.