4,681 research outputs found

    Implementing screening and brief Interventions for excessive alcohol consumption in primary health care

    Get PDF
    O consumo de bebidas alcoólicas é um dos principais fatores de risco da morbilidade e mortalidade prematura a nível mundial. As pessoas que consomem este género de bebidas têm um risco aumentado de vir a desenvolver mais de 200 problemas de saúde diferentes. A maioria do impacto do consumo de álcool na saúde humana é determinado por duas dimensões: o volume total de álcool consumido e o padrão de consumo. Existem várias medidas com comprovada eficácia que podem ser empregues para reduzir o risco associado ao consumo de álcool, entre as quais se encontra a deteção precoce e intervenção breve ao nível dos Cuidados de Saúde Primários. A maioria dos profissionais de saúde neste nível de cuidados considera o consumo de álcool como um importante problema de saúde e manifesta o seu apoio a medidas que visem reduzir o seu impacto. No entanto, poucos são os profissionais dos Cuidados de Saúde Primários que de forma sistemática identificam e aconselham os seus doentes relativamente aos seus hábitos etílicos. Como tal, o objetivo geral desta tese foi investigar como implementar a deteção precoce e intervenção breve no consumo excessivo de álcool nos Cuidados de Saúde Primários. Foi realizada uma revisão sistemática das barreiras e facilitadores à implementação da deteção precoce e intervenção breve no consumo excessivo de álcool nos Cuidados de Saúde Primários. As barreiras e facilitadores identificados nesta revisão foram analisados à luz da teoria de modificação comportamental para compreender a ligação destes fatores aos determinantes da mudança de comportamento, e para identificar as estratégias conceptualmente mais eficazes para abordar as barreiras e facilitadores à mudança de comportamento dos profissionais dos Cuidados de Saúde Primários no sentido de aumentar as taxas de deteção precoce e intervenção breve no consumo excessivo de álcool. Esta metodologia foi utilizada para desenhar um programa de implementação com base em pressupostos teóricos que foi testado num estudo experimental randomizado e controlado em clusters. Esta tese identificou diversas barreiras à implementação, ligadas a todos os domínios teóricos da mudança comportamental. As barreiras mais frequentemente mencionadas pelos profissionais foram: preocupação sobre as suas competências e eficácia para realizar a deteção precoce e intervenção breve; falta de conhecimento específico sobre o consumo de álcool; falta de tempo; falta de materiais; falta de apoio; e atitudes para com o doente com consumos excessivos de álcool. Esta tese mostrou também a existência de dois grupos distintos de médicos de família com base nas suas atitudes para com estes doentes, um com atitudes mais positivas, o outro com atitudes mais negativas. Esta tese mostrou ainda que um programa de implementação da deteção precoce e intervenção breve, desenhado com base em pressupostos teóricos de modificação comportamental, adaptado às barreiras e facilitadores da implementação, aumenta de forma significativa as taxas de identificação precoce dos consumos de álcool. Esta tese contribui para aumentar o conhecimento atual no sentido em que põe à disposição dos investigadores evidência prática sobre como abordar os fatores com influência na implementação da identificação precoce e intervenção breve para o consumo de álcool ao nível dos Cuidados de Saúde Primários. Esta tese contribui também para um melhor entendimento dos mecanismos subjacentes à resistência e à mudança de comportamento dos profissionais dos Cuidados de Saúde Primários no que respeita à implementação da deteção precoce e intervenção breve do consumo de álcool. Os resultados desta tese poderão ser usados por investigadores e decisores políticos para desenhar novos programas de implementação tendo como objetivo modificar esta prática clínica ao nível dos Cuidados de Saúde Primários.Alcohol use is among the leading risk factors for the global burden of disease and premature death. People who drink alcoholic beverages are at risk of developing more than 200 diseases and injury conditions. Most of the impact of alcohol consumption on human health and well-being is determined by two dimensions of drinking: the total volume of alcohol consumed and the pattern of drinking. Several effective strategies exist to reduce the harmful use of alcohol, which includes screening and brief interventions for excessive alcohol use in primary health care. The majority of primary health care providers agree that the excessive consumption of alcohol is an important health issue and express their support to policies for reducing the impact of alcohol on the health of their patients. Notwithstanding, implementation of screening and brief interventions is low at the primary health care level. Therefore, the overall aim of this thesis is to investigate how to implement screening and brief interventions for excessive alcohol consumption in primary health care. This thesis reviewed the barriers of, and facilitators for, the implementation of alcohol screening and brief interventions in primary health care. Behaviour change theory was used to understand how these factors linked to the determinants of behaviour change and how they could be addressed in order to change primary health care providers’ behaviour, i.e. to increase the delivery of alcohol screening and brief interventions. A comprehensive theory-based implementation programme was designed and tested in a cluster randomized controlled trial. This thesis identified several barriers to implementation which were mapped to all the theoretical domains of behaviour change. Primary health care providers concerns about their ability to deliver alcohol screening and brief interventions and to help patients to cut down, lack of alcohol-related knowledge, lack of time, lack of materials and support, and providers’ attitudes towards at-risk drinkers were among the most commonly cited barriers. This thesis found evidence that the attitudes of family physicians could be used to divide practitioners into two distinct groups, one with more positive and the other with more negative attitudes towards at-risk drinkers. This thesis also found that a behaviour change theory-based programme, tailored to the barriers for, and facilitators of, the implementation of screening and brief intervention in primary health care is effective in increasing alcohol screening rates. This thesis contributed to the evidence base by providing researchers with practical evidence on how to address the factors influencing the implementation of screening and brief interventions in primary health care. This thesis also provides researchers with insight into the behavioural mechanisms mediating primary health care providers’ decision to deliver alcohol screening and brief interventions. The results of this thesis could be used by researchers and policymakers to inform the design of novel theory-oriented interventions to support the implementation of alcohol screening and brief interventions in primary health care

    Applications of Deep Learning Models in Financial Forecasting

    Get PDF
    In financial markets, deep learning techniques sparked a revolution, reshaping conventional approaches and amplifying predictive capabilities. This thesis explored the applications of deep learning models to unravel insights and methodologies aimed at advancing financial forecasting. The crux of the research problem lies in the applications of predictive models within financial domains, characterised by high volatility and uncertainty. This thesis investigated the application of advanced deep-learning methodologies in the context of financial forecasting, addressing the challenges posed by the dynamic nature of financial markets. These challenges were tackled by exploring a range of techniques, including convolutional neural networks (CNNs), long short-term memory networks (LSTMs), autoencoders (AEs), and variational autoencoders (VAEs), along with approaches such as encoding financial time series into images. Through analysis, methodologies such as transfer learning, convolutional neural networks, long short-term memory networks, generative modelling, and image encoding of time series data were examined. These methodologies collectively offered a comprehensive toolkit for extracting meaningful insights from financial data. The present work investigated the practicality of a deep learning CNN-LSTM model within the Directional Change framework to predict significant DC events—a task crucial for timely decisionmaking in financial markets. Furthermore, the potential of autoencoders and variational autoencoders to enhance financial forecasting accuracy and remove noise from financial time series data was explored. Leveraging their capacity within financial time series, these models offered promising avenues for improved data representation and subsequent forecasting. To further contribute to financial prediction capabilities, a deep multi-model was developed that harnessed the power of pre-trained computer vision models. This innovative approach aimed to predict the VVIX, utilising the cross-disciplinary synergy between computer vision and financial forecasting. By integrating knowledge from these domains, novel insights into the prediction of market volatility were provided

    A Critical Review Of Post-Secondary Education Writing During A 21st Century Education Revolution

    Get PDF
    Educational materials are effective instruments which provide information and report new discoveries uncovered by researchers in specific areas of academia. Higher education, like other education institutions, rely on instructional materials to inform its practice of educating adult learners. In post-secondary education, developmental English programs are tasked with meeting the needs of dynamic populations, thus there is a continuous need for research in this area to support its changing landscape. However, the majority of scholarly thought in this area centers on K-12 reading and writing. This paucity presents a phenomenon to the post-secondary community. This research study uses a qualitative content analysis to examine peer-reviewed journals from 2003-2017, developmental online websites, and a government issued document directed toward reforming post-secondary developmental education programs. These highly relevant sources aid educators in discovering informational support to apply best practices for student success. Developmental education serves the purpose of addressing literacy gaps for students transitioning to college-level work. The findings here illuminate the dearth of material offered to developmental educators. This study suggests the field of literacy research is fragmented and highlights an apparent blind spot in scholarly literature with regard to English writing instruction. This poses a quandary for post-secondary literacy researchers in the 21st century and establishes the necessity for the literacy research community to commit future scholarship toward equipping college educators teaching writing instruction to underprepared adult learners

    In-memory Databases in Business Information Systems

    Get PDF
    In-memory databases are developed to keep the entire data in main memory. Compared to traditional database systems, read access is now much faster since no I/O access to a hard drive is required. In terms of write access, mechanisms are available which provide data persistence and thus secure transactions. In-memory databases have been available for a while and have proven to be suitable for particular use cases. With increasing storage density of DRAM modules, hardware systems capable of storing very large amounts of data have become affordable. In this context the question arises whether in-memory databases are suitable for business information system applications. Hasso Plattner, who developed the HANA in-memory database, is a trailblazer for this approach. He sees a lot of potential for novel concepts concerning the development of business information systems. One example is to conduct transactions and analytics in parallel and on the same database, i.e. a division into operational database systems and data warehouse systems is no longer necessary (Plattner and Zeier 2011). However, there are also voices against this approach. Larry Ellison described the idea of business information systems based on in-memory database as “wacko,” without actually making a case for his statement (cf. Bube 2010). Stonebraker (2011) sees a future for in-memory databases for business information systems but considers the division of OLTP and OLAP applications as reasonable. [From: Introduction

    Auditable and performant Byzantine consensus for permissioned ledgers

    Get PDF
    Permissioned ledgers allow users to execute transactions against a data store, and retain proof of their execution in a replicated ledger. Each replica verifies the transactions’ execution and ensures that, in perpetuity, a committed transaction cannot be removed from the ledger. Unfortunately, this is not guaranteed by today’s permissioned ledgers, which can be re-written if an arbitrary number of replicas collude. In addition, the transaction throughput of permissioned ledgers is low, hampering real-world deployments, by not taking advantage of multi-core CPUs and hardware accelerators. This thesis explores how permissioned ledgers and their consensus protocols can be made auditable in perpetuity; even when all replicas collude and re-write the ledger. It also addresses how Byzantine consensus protocols can be changed to increase the execution throughput of complex transactions. This thesis makes the following contributions: 1. Always auditable Byzantine consensus protocols. We present a permissioned ledger system that can assign blame to individual replicas regardless of how many of them misbehave. This is achieved by signing and storing consensus protocol messages in the ledger and providing clients with signed, universally-verifiable receipts. 2. Performant transaction execution with hardware accelerators. Next, we describe a cloud-based ML inference service that provides strong integrity guarantees, while staying compatible with current inference APIs. We change the Byzantine consensus protocol to execute machine learning (ML) inference computation on GPUs to optimize throughput and latency of ML inference computation. 3. Parallel transactions execution on multi-core CPUs. Finally, we introduce a permissioned ledger that executes transactions, in parallel, on multi-core CPUs. We separate the execution of transactions between the primary and secondary replicas. The primary replica executes transactions on multiple CPU cores and creates a dependency graph of the transactions that the backup replicas utilize to execute transactions in parallel.Open Acces

    Trusted Provenance with Blockchain - A Blockchain-based Provenance Tracking System for Virtual Aircraft Component Manufacturing

    Get PDF
    The importance of provenance in the digital age has led to significant interest in utilizing blockchain technology for tamper-proof storage of provenance data. This thesis proposes a blockchain-based provenance tracking system for the certification of aircraft components. The aim is to design and implement a system that can ensure the trustworthy, tamper-resistant storage of provenance documents originating from an aircraft manufacturing process. To achieve this, the thesis presents a systematic literature review, which provides a comprehensive overview of existing works in the field of provenance and blockchain technology. After obtaining strategies to utilize blockchain for the storage of provenance data on the blockchain, a system was designed to meet the requirements of stakeholders in the aviation industry. The thesis utilized a systematic approach to gather requirements by conducting interviews with stakeholders. The system was implemented using a combination of smart contracts and a graphical user interface to provide tamper-resistant, traceable storage of relevant data on a transparent blockchain. An evaluation based on the requirements identified during the requirement engineering process found that the proposed system meets all identified requirements. Overall, this thesis offers insight into a potential application of blockchain technology in the aviation industry and provides a valuable resource for researchers and industry professionals seeking to leverage blockchain technology for provenance tracking and certification purpose

    Pathway: a fast and flexible unified stream data processing framework for analytical and Machine Learning applications

    Full text link
    We present Pathway, a new unified data processing framework that can run workloads on both bounded and unbounded data streams. The framework was created with the original motivation of resolving challenges faced when analyzing and processing data from the physical economy, including streams of data generated by IoT and enterprise systems. These required rapid reaction while calling for the application of advanced computation paradigms (machinelearning-powered analytics, contextual analysis, and other elements of complex event processing). Pathway is equipped with a Table API tailored for Python and Python/SQL workflows, and is powered by a distributed incremental dataflow in Rust. We describe the system and present benchmarking results which demonstrate its capabilities in both batch and streaming contexts, where it is able to surpass state-of-the-art industry frameworks in both scenarios. We also discuss streaming use cases handled by Pathway which cannot be easily resolved with state-of-the-art industry frameworks, such as streaming iterative graph algorithms (PageRank, etc.)
    corecore