938 resultados para Domain-specific programming languages
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Teniendo en cuenta el drástico aumento en Colombia y el mundo de la población adulta mayor la pirámide poblacional se ha invertido. Lo que ha generado que cada vez haya más adultos mayores y la esperanza de vida sea mayor. Motivo por el cual surge la importancia de conocer diversos aspectos del envejecimiento, entre ellos los estereotipos. Adicionalmente hay muy poca investigación relacionada con los estereotipos sobre el envejecimiento según el género y el periodo de desarrollo. Levy (2009) encontró que son los jóvenes quienes tienen más estereotipos negativos sobre el envejecimiento pues estos sienten que la vejez está muy lejos de su realidad actual y no es en una amenaza personal. Por otro lado Bodner, Bergman y Cohen (2012), encontraron que son los hombres quienes tienen más estereotipos negativos sobre el envejecimiento. La presente investigación tuvo como objetivo describir el efecto del periodo del desarrollo y el género en los estereotipos sobre el envejecimiento en 860 adultos colombianos. Se midió la variable de estereotipos sobre el envejecimiento a través del cuestionario de Ramírez y Palacios (2015) y el periodo del desarrollo y el género a través de un cuestionario de datos sociodemograficos. Contrario a lo esperado, los resultados mostraron que no existe relación entre los estereotipos negativos con el género, el periodo del desarrollo, ni en la interacción de estos. En cambio, se encontraron diferencias entre los estereotipos positivos el género y el periodo de desarrollo. Se considera importante continuar realizando investigaciones relacionadas con esta temática pues cada vez son más los adultos mayores y la manera en que nos relacionemos con ellos, va a determinar un mejor proceso de envejecimiento para ellos.
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Neste documento foi feita a apresentação do conceito de Programação Visual, estudados alguns exemplos de Linguagens de Programação Visual e investigado vantagens e desvantagens sobre o seu uso comparativamente à programação tradicional (por texto) e, adicionalmente, foram estudados três jogos para aprender a programar com fortes características visuais. A partir desta investigação, foi criada uma nova Linguagem de Programação Visual(LPV) sendo a base de um prototipo de um jogo para aprender a programar. Este jogo é representado pela deslocação e execução de tarefas feitas por um robô dentro de uma casa, sendo o objetivo do programador colocar objetos nesta casa que manipulam a deslocação do robô dentro desta de forma a resolver um problema; Abstract: A game to learn programming Aplication of concepts of visual programming to create a game to learn how to program In this document we will explain the concept of Visual Programming, study some examples of Visual Programming Languages, analyze some arguments in favor and against its use in comparison to traditional programming (by text) and, additionally, study three games to learn programming with strong visual features. Using this research, a new Visual Programming Language(VPL) was created, being the basis of a prototype of a game to learn programming. This game is represented by the movement and execution of tasks done by a robot inside a house, being the goal of the programmer to place objects in this house that manipulate the movement of the robot inside of it in order to solve a problem.
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This dissertation explores the link between hate crimes that occurred in the United Kingdom in June 2017, June 2018 and June 2019 through the posts of a robust sample of Conservative and radical right users on Twitter. In order to avoid the traditional challenges of this kind of research, I adopted a four staged research protocol that enabled me to merge content produced by a group of randomly selected users to observe the phenomenon from different angles. I collected tweets from thirty Conservative/right wing accounts for each month of June over the three years with the help of programming languages such as Python and CygWin tools. I then examined the language of my data focussing on humorous content in order to reveal whether, and if so how, radical users online often use humour as a tool to spread their views in conditions of heightened disgust and wide-spread political instability. A reflection on humour as a moral occurrence, expanding on the works of Christie Davies as well as applying recent findings on the behavioural immune system on online data, offers new insights on the overlooked humorous nature of radical political discourse. An unorthodox take on the moral foundations pioneered by Jonathan Haidt enriched my understanding of the analysed material through the addition of a moral-based layer of enquiry to my more traditional content-based one. This convergence of theoretical, data driven and real life events constitutes a viable “collection of strategies” for academia, data scientists; NGO’s fighting hate crimes and the wider public alike. Bringing together the ideas of Davies, Haidt and others to my data, helps us to perceive humorous online content in terms of complex radical narratives that are all too often compressed into a single tweet.
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The availability of a huge amount of source code from code archives and open-source projects opens up the possibility to merge machine learning, programming languages, and software engineering research fields. This area is often referred to as Big Code where programming languages are treated instead of natural languages while different features and patterns of code can be exploited to perform many useful tasks and build supportive tools. Among all the possible applications which can be developed within the area of Big Code, the work presented in this research thesis mainly focuses on two particular tasks: the Programming Language Identification (PLI) and the Software Defect Prediction (SDP) for source codes. Programming language identification is commonly needed in program comprehension and it is usually performed directly by developers. However, when it comes at big scales, such as in widely used archives (GitHub, Software Heritage), automation of this task is desirable. To accomplish this aim, the problem is analyzed from different points of view (text and image-based learning approaches) and different models are created paying particular attention to their scalability. Software defect prediction is a fundamental step in software development for improving quality and assuring the reliability of software products. In the past, defects were searched by manual inspection or using automatic static and dynamic analyzers. Now, the automation of this task can be tackled using learning approaches that can speed up and improve related procedures. Here, two models have been built and analyzed to detect some of the commonest bugs and errors at different code granularity levels (file and method levels). Exploited data and models’ architectures are analyzed and described in detail. Quantitative and qualitative results are reported for both PLI and SDP tasks while differences and similarities concerning other related works are discussed.
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Slot and van Emde Boas Invariance Thesis states that a time (respectively, space) cost model is reasonable for a computational model C if there are mutual simulations between Turing machines and C such that the overhead is polynomial in time (respectively, linear in space). The rationale is that under the Invariance Thesis, complexity classes such as LOGSPACE, P, PSPACE, become robust, i.e. machine independent. In this dissertation, we want to find out if it possible to define a reasonable space cost model for the lambda-calculus, the paradigmatic model for functional programming languages. We start by considering an unusual evaluation mechanism for the lambda-calculus, based on Girard's Geometry of Interaction, that was conjectured to be the key ingredient to obtain a space reasonable cost model. By a fine complexity analysis of this schema, based on new variants of non-idempotent intersection types, we disprove this conjecture. Then, we change the target of our analysis. We consider a variant over Krivine's abstract machine, a standard evaluation mechanism for the call-by-name lambda-calculus, optimized for space complexity, and implemented without any pointer. A fine analysis of the execution of (a refined version of) the encoding of Turing machines into the lambda-calculus allows us to conclude that the space consumed by this machine is indeed a reasonable space cost model. In particular, for the first time we are able to measure also sub-linear space complexities. Moreover, we transfer this result to the call-by-value case. Finally, we provide also an intersection type system that characterizes compositionally this new reasonable space measure. This is done through a minimal, yet non trivial, modification of the original de Carvalho type system.
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Embedding intelligence in extreme edge devices allows distilling raw data acquired from sensors into actionable information, directly on IoT end-nodes. This computing paradigm, in which end-nodes no longer depend entirely on the Cloud, offers undeniable benefits, driving a large research area (TinyML) to deploy leading Machine Learning (ML) algorithms on micro-controller class of devices. To fit the limited memory storage capability of these tiny platforms, full-precision Deep Neural Networks (DNNs) are compressed by representing their data down to byte and sub-byte formats, in the integer domain. However, the current generation of micro-controller systems can barely cope with the computing requirements of QNNs. This thesis tackles the challenge from many perspectives, presenting solutions both at software and hardware levels, exploiting parallelism, heterogeneity and software programmability to guarantee high flexibility and high energy-performance proportionality. The first contribution, PULP-NN, is an optimized software computing library for QNN inference on parallel ultra-low-power (PULP) clusters of RISC-V processors, showing one order of magnitude improvements in performance and energy efficiency, compared to current State-of-the-Art (SoA) STM32 micro-controller systems (MCUs) based on ARM Cortex-M cores. The second contribution is XpulpNN, a set of RISC-V domain specific instruction set architecture (ISA) extensions to deal with sub-byte integer arithmetic computation. The solution, including the ISA extensions and the micro-architecture to support them, achieves energy efficiency comparable with dedicated DNN accelerators and surpasses the efficiency of SoA ARM Cortex-M based MCUs, such as the low-end STM32M4 and the high-end STM32H7 devices, by up to three orders of magnitude. To overcome the Von Neumann bottleneck while guaranteeing the highest flexibility, the final contribution integrates an Analog In-Memory Computing accelerator into the PULP cluster, creating a fully programmable heterogeneous fabric that demonstrates end-to-end inference capabilities of SoA MobileNetV2 models, showing two orders of magnitude performance improvements over current SoA analog/digital solutions.
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This thesis investigates how individuals can develop, exercise, and maintain autonomy and freedom in the presence of information technology. It is particularly interested in how information technology can impose autonomy constraints. The first part identifies a problem with current autonomy discourse: There is no agreed upon object of reference when bemoaning loss of or risk to an individual’s autonomy. Here, thesis introduces a pragmatic conceptual framework to classify autonomy constraints. In essence, the proposed framework divides autonomy in three categories: intrinsic autonomy, relational autonomy and informational autonomy. The second part of the thesis investigates the role of information technology in enabling and facilitating autonomy constraints. The analysis identifies eleven characteristics of information technology, as it is embedded in society, so-called vectors of influence, that constitute risk to an individual’s autonomy in a substantial way. These vectors are assigned to three sets that correspond to the general sphere of the information transfer process to which they can be attributed to, namely domain-specific vectors, agent-specific vectors and information recipient-specific vectors. The third part of the thesis investigates selected ethical and legal implications of autonomy constraints imposed by information technology. It shows the utility of the theoretical frameworks introduced earlier in the thesis when conducting an ethical analysis of autonomy-constraining technology. It also traces the concept of autonomy in the European Data Lawsand investigates the impact of cultural embeddings of individuals on efforts to safeguard autonomy, showing intercultural flashpoints of autonomy differences. In view of this, the thesis approaches the exercise and constraint of autonomy in presence of information technology systems holistically. It contributes to establish a common understanding of (intuitive) terminology and concepts, connects this to current phenomena arising out of ever-increasing interconnectivity and computational power and helps operationalize the protection of autonomy through application of the proposed frameworks.
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Blazor è un innovativo framework di Microsoft per lo sviluppo di applicazioni web in C#, HTML e CSS. Questo framework non possiede un designer visuale, ovvero un supporto grafico "drag-and-drop" alla creazione delle web applications. Questa tesi affronta la progettazione e la prototipazione di "Blazor Designer", un DSL (Domain-Specific Language) grafico a supporto dello sviluppo applicazioni web a pagina singola (SPA) sviluppato in collaborazione con IPREL Progetti srl, società del gruppo SACMI. Nella tesi si fa una analisi delle tecnologie messe a disposizione da Blazor, compreso WebAssembly, si discutono le caratteristiche e i vantaggi dei DSL, si descrive la progettazione e l'implementazione di "Blazor Designer" come estensione di Visual Studio. La conclusione riassume i risultati raggiunti, i limiti e le opportunità future: un DSL è effettivamente in grado di rendere più user-friendly e semplice lo sviluppo, ma lo strumento deve essere integrato per essere sfruttato pienamente.
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A global italian pharmaceutical company has to provide two work environments that favor different needs. The environments will allow to develop solutions in a controlled, secure and at the same time in an independent manner on a state-of-the-art enterprise cloud platform. The need of developing two different environments is dictated by the needs of the working units. Indeed, the first environment is designed to facilitate the creation of application related to genomics, therefore, designed more for data-scientists. This environment is capable of consuming, producing, retrieving and incorporating data, furthermore, will support the most used programming languages for genomic applications (e.g., Python, R). The proposal was to obtain a pool of ready-togo Virtual Machines with different architectures to provide best performance based on the job that needs to be carried out. The second environment has more of a traditional trait, to obtain, via ETL (Extract-Transform-Load) process, a global datamodel, resembling a classical relational structure. It will provide major BI operations (e.g., analytics, performance measure, reports, etc.) that can be leveraged both for application analysis or for internal usage. Since, both architectures will maintain large amounts of data regarding not only pharmaceutical informations but also internal company informations, it would be possible to digest the data by reporting/ analytics tools and also apply data-mining, machine learning technologies to exploit intrinsic informations. The thesis work will introduce, proposals, implementations, descriptions of used technologies/platforms and future works of the above discussed environments.
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Nowadays the idea of injecting world or domain-specific structured knowledge into pre-trained language models (PLMs) is becoming an increasingly popular approach for solving problems such as biases, hallucinations, huge architectural sizes, and explainability lack—critical for real-world natural language processing applications in sensitive fields like bioinformatics. One recent work that has garnered much attention in Neuro-symbolic AI is QA-GNN, an end-to-end model for multiple-choice open-domain question answering (MCOQA) tasks via interpretable text-graph reasoning. Unlike previous publications, QA-GNN mutually informs PLMs and graph neural networks (GNNs) on top of relevant facts retrieved from knowledge graphs (KGs). However, taking a more holistic view, existing PLM+KG contributions mainly consider commonsense benchmarks and ignore or shallowly analyze performances on biomedical datasets. This thesis start from a propose of a deep investigation of QA-GNN for biomedicine, comparing existing or brand-new PLMs, KGs, edge-aware GNNs, preprocessing techniques, and initialization strategies. By combining the insights emerged in DISI's research, we introduce Bio-QA-GNN that include a KG. Working with this part has led to an improvement in state-of-the-art of MCOQA model on biomedical/clinical text, largely outperforming the original one (+3.63\% accuracy on MedQA). Our findings also contribute to a better understanding of the explanation degree allowed by joint text-graph reasoning architectures and their effectiveness on different medical subjects and reasoning types. Codes, models, datasets, and demos to reproduce the results are freely available at: \url{https://github.com/disi-unibo-nlp/bio-qagnn}.
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"Names of books referred to": p. [vii]-xiii.
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In this study, we have compared the effector functions and fate of a number of human CTL clones in vitro or ex vivo following contact with variant peptides presented either on the cell surface or in a soluble multimeric format. In the presence of CD8 coreceptor binding, there is a good correlation between TCR signaling, killing of the targets, and Fast-mediated CTL apoptosis. Blocking CD8 binding using (alpha3 domain mutants of MHC class I results in much reduced signaling and reduced killing of the targets. Surprisingly, however, Fast expression is induced to a similar degree on these CTLs, and apoptosis of CTL is unaffected. The ability to divorce these events may allow the deletion of antigen-specific and pathological CTL populations without the deleterious effects induced by full CTL activation.
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Vesicular carriers for intracellular transport associate with unique sets of accessory molecules that dictate budding and docking on specific membrane domains. Although many of these accessory molecules are peripheral membrane proteins, in most cases the targeting sequences responsible for their membrane recruitment have yet to be identified. We have previously defined a novel Golgi targeting domain (GRIP) shared by a family of coiled-coil peripheral membrane Golgi proteins implicated in membrane trafficking. We show here that the docking site for the GRIP motif of p230 is a specific domain of Golgi. membranes. By immunoelectron microscopy of HeLa cells stably expressing a green fluorescent protein (GFP)-p230(GRIP) fusion protein, we show binding specifically to a subset of membranes of the trans-Golgi network (TGN). Real-time imaging of live HeLa cells revealed that the GFP-p230(GRIP) was associated with highly dynamic tubular extensions of the TGN, which have the appearance and behaviour of transport carriers. To further define the nature of the GRIP membrane binding site, in vitro budding assays were performed using purified rat liver Golgi membranes and cytosol from GFP-p230(GRIP) transfected cells. Analysis of Golgi-derived vesicles by sucrose gradient fractionation demonstrated that GFP-p230(GRIP) binds to a specific population of vesicles distinct from those labelled for beta -COP or gamma -adaptin. The GFP-p230(GRIP) fusion protein is recruited to the same vesicle population as full-length p230, demonstrating that the GRIP domain is solely proficient as a targeting signal for membrane binding of the native molecule. Therefore, p230 GRIP is a targeting signal for recruitment to a highly selective membrane attachment site on a specific population of trans-Golgi network tubulovesicular carriers.
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This work is a contribution to the e-Framework, arguably the most prominent e-learning framework today, and consists of the definition of a service for the automatic evaluation of programming exercises. This evaluation domain differs from trivial evaluations modelled by languages such as the IMS Question & Test Interoperability (QTI) specification. Complex evaluation domains justify the development of specialized evaluators that participate in several business processes. These business processes can combine other type of systems such as Programming Contest Management Systems, Learning Management Systems, Integrated Development Environments and Learning Object Repositories where programming exercises are stored as Learning Objects. This contribution describes the implementation approaches used, more precisely, behaviours & requests, use & interactions, applicable standards, interface definition and usage scenarios.
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BACKGROUND: Sodium channel NaV1.5 underlies cardiac excitability and conduction. The last 3 residues of NaV1.5 (Ser-Ile-Val) constitute a PDZ domain-binding motif that interacts with PDZ proteins such as syntrophins and SAP97 at different locations within the cardiomyocyte, thus defining distinct pools of NaV1.5 multiprotein complexes. Here, we explored the in vivo and clinical impact of this motif through characterization of mutant mice and genetic screening of patients. METHODS AND RESULTS: To investigate in vivo the regulatory role of this motif, we generated knock-in mice lacking the SIV domain (ΔSIV). ΔSIV mice displayed reduced NaV1.5 expression and sodium current (INa), specifically at the lateral myocyte membrane, whereas NaV1.5 expression and INa at the intercalated disks were unaffected. Optical mapping of ΔSIV hearts revealed that ventricular conduction velocity was preferentially decreased in the transversal direction to myocardial fiber orientation, leading to increased anisotropy of ventricular conduction. Internalization of wild-type and ΔSIV channels was unchanged in HEK293 cells. However, the proteasome inhibitor MG132 rescued ΔSIV INa, suggesting that the SIV motif is important for regulation of NaV1.5 degradation. A missense mutation within the SIV motif (p.V2016M) was identified in a patient with Brugada syndrome. The mutation decreased NaV1.5 cell surface expression and INa when expressed in HEK293 cells. CONCLUSIONS: Our results demonstrate the in vivo significance of the PDZ domain-binding motif in the correct expression of NaV1.5 at the lateral cardiomyocyte membrane and underline the functional role of lateral NaV1.5 in ventricular conduction. Furthermore, we reveal a clinical relevance of the SIV motif in cardiac disease.