607 research outputs found

    Size Matters: Microservices Research and Applications

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    In this chapter we offer an overview of microservices providing the introductory information that a reader should know before continuing reading this book. We introduce the idea of microservices and we discuss some of the current research challenges and real-life software applications where the microservice paradigm play a key role. We have identified a set of areas where both researcher and developer can propose new ideas and technical solutions.Comment: arXiv admin note: text overlap with arXiv:1706.0735

    Joint Channel-and-Network Coding Using EXIT Chart Aided Relay Activation

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    This paper presents a relay activation scheme designed for joint channel-and-network (JCN) coded systems relying on an iterative decoding. A primary focus is on proposing criteria of the relay activation to find the best user combination for cooperative relaying, which exploits extrinsic information transfer (EXIT) chart analysis. We will demonstrate that the EXIT chart aided relay activation scheme is capable of reducing the probability of outages, despite increasing the effective throughput of network

    Xrcc4 and mre11 Roles and Transcriptional Response to Repair of Talen-Induced Double-Strand Dna Breaks

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    Double-strand breaks (DSB) are one of the most lethal forms of DNA damage that, if left unrepaired, can lead to genomic instability, cellular transformation, and cell death. In this work, we examined how repair of transcription activator-like effector nuclease (TALEN)-induced DNA damage was altered when knocking out, or inhibiting a function of, two DNA repair proteins, XRCC4 and MRE11, respectively. We developed a fluorescent reporter assay that uses TALENs to introduce DSB and detected repair by the presence of GFP fluorescence. We observed repair of TALEN-induced breaks in the XRCC4 knockout cells treated with mirin (a pharmacological inhibitor of MRE11 exonuclease activity), albeit with ~40% reduced efficiency compared to normal cells. Editing in the absence of XRCC4 or MRE11 exonuclease was robust, with little difference between the indel profiles amongst any of the groups. Reviewing the transcriptional profiles of the mirin-treated XRCC4 knockout cells showed 307 uniquely differentially expressed genes, a number far greater than for either of the other cell lines (the HeLa XRCC4 knockout sample had 83 genes, and the mirin-treated HeLa cells had 30 genes uniquely differentially expressed). Pathways unique to the XRCC4 knockout+mirin group included differential expression of p53 downstream pathways, and metabolic pathways indicating cell adaptation for energy regulation and stress response. In conclusion, our study showed that TALEN-induced DSBs are repaired, even when a key DSB repair protein or protein function is not operational, without a change in indel profiles. However, transcriptional profiles indicate the induction of unique cellular responses dependent upon the DNA repair protein(s) hampered

    On the Impact of Partial Shading on PV Output Power

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    It is a well-documented fact that partial shading of a photovoltaic array reduces it output power capability. However, the relative amount of such degradation in energy production cannot be determined in a straight forward manner, as it is often not proportional to the shaded area. This paper clarifies the mechanism of partial PV shading on a number of PV cells connected in series and/or parallel with and without bypass diodes. The analysis is presented in simple terms and can be useful to someone who wishes to determine the impact of some shading geometry on a PV system. The analysis is illustrated by measurements on a commercial 70 W panel, and a 14.4 kW PV array

    Requirements and operational guidelines for secure and sustainable digital phenotyping:Design and development study

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    Background: Digital phenotyping, the measurement of human behavioral phenotypes using personal devices, is rapidly gaining popularity. Novel initiatives, ranging from software prototypes to user-ready research platforms, are innovating the field of biomedical research and health care apps. One example is the BEHAPP project, which offers a fully managed digital phenotyping platform as a service. The innovative potential of digital phenotyping strategies resides among others in their capacity to objectively capture measurable and quantitative components of human behavior, such as diurnal rhythm, movement patterns, and communication, in a real-world setting. The rapid development of this field underscores the importance of reliability and safety of the platforms on which these novel tools are operated. Large-scale studies and regulated research spaces (eg, the pharmaceutical industry) have strict requirements for the software-based solutions they use. Security and sustainability are key to ensuring continuity and trust. However, the majority of behavioral monitoring initiatives have not originated primarily in these regulated research spaces, which may be why these components have been somewhat overlooked, impeding the further development and implementation of such platforms in a secure and sustainable way.Objective: This study aims to provide a primer on the requirements and operational guidelines for the development and operation of a secure behavioral monitoring platform.Methods: We draw from disciplines such as privacy law, information, and computer science to identify a set of requirements and operational guidelines focused on security and sustainability. Taken together, the requirements and guidelines form the foundation of the design and implementation of the BEHAPP behavioral monitoring platform.Results: We present the base BEHAPP data collection and analysis flow and explain how the various concepts from security and sustainability are addressed in the design.Conclusions: Digital phenotyping initiatives are steadily maturing. This study helps the field and surrounding stakeholders to reflect upon and progress toward secure and sustainable operation of digital phenotyping–driven research

    Sapphire Award Program: Grants and Awards Given

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    An informational document about grants and awards given through the Sapphire Award Program

    Exploring ChatGPT's Empathic Abilities

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    Empathy is often understood as the ability to share and understand another individual's state of mind or emotion. With the increasing use of chatbots in various domains, e.g., children seeking help with homework, individuals looking for medical advice, and people using the chatbot as a daily source of everyday companionship, the importance of empathy in human-computer interaction has become more apparent. Therefore, our study investigates the extent to which ChatGPT based on GPT-3.5 can exhibit empathetic responses and emotional expressions. We analyzed the following three aspects: (1) understanding and expressing emotions, (2) parallel emotional response, and (3) empathic personality. Thus, we not only evaluate ChatGPT on various empathy aspects and compare it with human behavior but also show a possible way to analyze the empathy of chatbots in general. Our results show, that in 91.7% of the cases, ChatGPT was able to correctly identify emotions and produces appropriate answers. In conversations, ChatGPT reacted with a parallel emotion in 70.7% of cases. The empathic capabilities of ChatGPT were evaluated using a set of five questionnaires covering different aspects of empathy. Even though the results show, that the scores of ChatGPT are still worse than the average of healthy humans, it scores better than people who have been diagnosed with Asperger syndrome / high-functioning autism

    Active SLAM for autonomous underwater exploration

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    Exploration of a complex underwater environment without an a priori map is beyond the state of the art for autonomous underwater vehicles (AUVs). Despite several efforts regarding simultaneous localization and mapping (SLAM) and view planning, there is no exploration framework, tailored to underwater vehicles, that faces exploration combining mapping, active localization, and view planning in a unified way. We propose an exploration framework, based on an active SLAM strategy, that combines three main elements: a view planner, an iterative closest point algorithm (ICP)-based pose-graph SLAM algorithm, and an action selection mechanism that makes use of the joint map and state entropy reduction. To demonstrate the benefits of the active SLAM strategy, several tests were conducted with the Girona 500 AUV, both in simulation and in the real world. The article shows how the proposed framework makes it possible to plan exploratory trajectories that keep the vehicle’s uncertainty bounded; thus, creating more consistent maps.Peer ReviewedPostprint (published version

    EAGLE—A Scalable Query Processing Engine for Linked Sensor Data

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    Recently, many approaches have been proposed to manage sensor data using semantic web technologies for effective heterogeneous data integration. However, our empirical observations revealed that these solutions primarily focused on semantic relationships and unfortunately paid less attention to spatio–temporal correlations. Most semantic approaches do not have spatio–temporal support. Some of them have attempted to provide full spatio–temporal support, but have poor performance for complex spatio–temporal aggregate queries. In addition, while the volume of sensor data is rapidly growing, the challenge of querying and managing the massive volumes of data generated by sensing devices still remains unsolved. In this article, we introduce EAGLE, a spatio–temporal query engine for querying sensor data based on the linked data model. The ultimate goal of EAGLE is to provide an elastic and scalable system which allows fast searching and analysis with respect to the relationships of space, time and semantics in sensor data. We also extend SPARQL with a set of new query operators in order to support spatio–temporal computing in the linked sensor data context.EC/H2020/732679/EU/ACTivating InnoVative IoT smart living environments for AGEing well/ACTIVAGEEC/H2020/661180/EU/A Scalable and Elastic Platform for Near-Realtime Analytics for The Graph of Everything/SMARTE
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