163 research outputs found

    Resilience

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    ABSTRACT My objective for creating this body of work is to explore the complexity and beauty of the human brain. What inspired these works is my research on cognitive psychology and neuroscience. Cognitive psychology involves the study of internal mental processes, while neuroscience deals with nerves and nervous tissue that relate to behavior and learning. Neuroscience is where psychology meets biology. The series of paintings in Resilience, were created with the intent to connect these two fields of study, while charting my exploration and discoveries found linked with science and psychology. The brain and its components are portrayed in an abstract way to show human emotions, while experiencing complex behaviors. These works illustrate the emotions experienced while personally undergoing a variety of physical, emotional, social and financial transformations. Through these experiences, some traumatic and some exhilarating, my resilience surpassed. My art transcends to others because it is relevant on an emotional level. The ability to over setbacks is a part of life that everyone can relate to. Through these labor intensive works I express not only the resilience of the human mind, but the vulnerabilities and beauty of it as well. It is my desire to create dialogue about the emotional and psychological issues many humans face today. I feel the more we discover about the brain and how it works the better we will understand these various concerns

    PDB24 Budget Impact Analysis of the Use of Aspart Insulin During Hospitalization of Patients with Hyperglycaemia in Italy

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    Using a distributed Shapley-value based approach to ensure navigability in a social network of smart objects

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    The huge number of nodes that is expected to join the Internet of Things in the short term will add major scalability issues to several procedures. A recent promising approach to these issues is based on social networking solutions to allow objects to autonomously establish social relationships. Every object in the resulting Social IoT (SIoT) exchanges data with its friend objects in a distributed manner to avoid the need for centralized solutions to implement major functionalities, such as: node discovery, information search and trustworthiness management. However, the number and types of established friendship affects network navigability. This paper addresses this issue proposing an efficient, distributed and dynamic strategy for the objects to select the right friends for the benefit of the overall network connectivity. The proposed friendship selection model relies on a Shapley-value based algorithm mapping the friendship selection process in the SIoT onto the coalition formation problem in a corresponding cooperative game. The obtained results show that the proposed solution is able to ensure global navigability, measured in terms of average path length among two nodes in the network, by means of a distributed and wise selection of the number of friend objects a node has to handle

    Enhancing the navigability in a social network of smart objects: a Shapley-value based approach

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    The Internet of Things (IoT) holds the promise to interconnect any possible object capable of providing useful information about the physical world for the benefit of humans' quality of life. The increasing number of heterogeneous objects that the IoT has to manage introduces crucial scalability issues that still need appropriate solutions. In this respect, one promising proposal is the Social IoT (SIoT) paradigm, whose main principle is to enable objects to autonomously establish social links with each other (adhering to rules set by their owners). "Friend" objects exchange data in a distributed manner and this avoids centralized solutions to implement major functions, such as: node discovery, information search, and trustworthiness management. However, the number and types of established friendships affect network navigability. This issue is the focus of this paper, which proposes an efficient, distributed and dynamic solution for the objects to select the right friends for the benefit of the overall network connectivity. The proposed friendship selection mechanism relies on a game theoretic model and a Shapley-value based algorithm. Two different utility functions are defined and evaluated based on either a group degree centrality and an average local clustering parameter. The comparison in terms of global navigability is measured in terms of average path length for the interconnection of any couple of nodes in the network. Results show that the group degree centrality brings to an enhanced degree of navigability thanks to the ability to create a suitable core of hubs

    Hera Object Storage : a seamless, automated multi-tiering solution on top of OpenStack Swift

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    Over the last couple of decades, the demand for storage in the Cloud has grown exponentially. Distributed Cloud storage and object storage for the increasing share of unstructured data, are in high focus in both academic and industrial research activities. At the same time, efficient storage and the corresponding costs are often contrasting parameters raising a trade-off problem for any proposed solution. To this aim, classifying the data in terms of access probability became a hot topic. This paper introduces Hera Object Storage, a storage system built on top of OpenStack Swift that aims at selecting the most appropriate storage tier for any object to be stored. The goal of the multi-tiering storage we propose is to be automated and seamless, guaranteeing the required storage performance at the lowest possible cost. The paper discusses the design challenges, the proposed algorithmic solutions to the scope and, based on a prototype implementation it presents a basic proof-of-concept validation

    Monitoring resilience in a rook-managed containerized cloud storage system

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    Distributed cloud storage solutions are currently gaining high momentum in industry and academia. The enterprise data volume growth and the recent tendency to move as much as possible data to the cloud is strongly stimulating the storage market growth. In this context, and as a main requirement for cloud native applications, it is of utmost importance to guarantee resilience of the deployed applications and the infrastructure. Indeed, with failures frequently occurring, a storage system should quickly recover to guarantee service availability. In this paper, we focus on containerized cloud storage, proposing a resilience monitoring solution for the recently developed Rook storage operator. While, Rook brings storage systems into a cloud-native container platform, in this paper we design an additional module to monitor and evaluate the resilience of the Rook-based system. Our proposed module is validated in a production environment, with software components generating a constant load and a controlled removal of system elements to evaluate the self-healing capability of the storage system. Failure recovery time revealed to be 41 and 142 seconds on average for a 32GB and a 215GB object storage device respectively

    Incidental detection of Os acromiale mimicking a fracture on 18F-Fluoride PET-CT

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    Os acromiale represents an unfused accessory centre of ossification of the acromion of scapula. It may cause shoulder impingement, rotator cuff tear or degenerative acromio-clavicular joint disease. A 38-year-old male with history of degenerative disc disease presented with persistent backache. MRI of the lumbar spine had earlier showed left paracentral disc protrusion of L5/S1 vertebrae impinging the left S1 nerve root for which the patient underwent fluoroscopic guided nerve root block. Due to persistent bilateral sciatica and worsening leg pain a decompression surgery was planned. A bone scan was requested to exclude other causes of pain prior to surgery for which the patient underwent 18F- Fluoride PET-CT examination. We report a case of incidental detection of Os acromiale mimicking fracture. As the management strategy for both is quite different this case highlights the importance of correct recognition of this identity for appropriate management

    PET imaging in glioma: techniques and current evidence

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    PET holds potential to provide additional information about tumour metabolic processes, which could aid brain tumour differential diagnosis, grading, molecular subtyping and/or the distinction of therapy effects from disease recurrence. This review discusses PET techniques currently in use for untreated and treated glioma characterization and aims to critically assess the evidence for different tracers ([F]Fluorodeoxyglucose, choline and amino acid tracers) in this context

    MIFaaS: A Mobile-IoT-Federation-as-a-Service Model for dynamic cooperation of IoT Cloud Providers

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    In the Internet of Things (IoT) arena, a constant evolution is observed towards the deployment of integrated environments, wherein heterogeneous devices pool their capacities to match wide-ranging user requirements. Solutions for efficient and synergistic cooperation among objects are, therefore, required. This paper suggests a novel paradigm to support dynamic cooperation among private/public local clouds of IoT devices. Differently from . device-oriented approaches typical of Mobile Cloud Computing, the proposed paradigm envisages an . IoT Cloud Provider (ICP)-oriented cooperation, which allows all devices belonging to the same private/public owner to participate in the federation process. Expected result from dynamic federations among ICPs is a remarkable increase in the amount of service requests being satisfied. Different from the Fog Computing vision, the network edge provides only management support and supervision to the proposed Mobile-IoT-Federation-as-a-Service (MIFaaS), thus reducing the deployment cost of peripheral micro data centers. The paper proposes a coalition formation game to account for the interest of rational cooperative ICPs in their own payoff. A proof-of-concept performance evaluation confirms that obtained coalition structures not only guarantee the satisfaction of the players' requirements according to their utility function, but also these introduce significant benefits for the cooperating ICPs in terms of number of tasks being successfully assigned
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