Mass Culture in Egypt

Mass Culture and Modernism in Egypt began as my dissertation research. My plan was to write about concepts of the person in Egypt, and one of my sources was to be media, though this was not necessarily to be the primary focus of the research. At the outset, my plans were quite flexible. I was interested in the relation of local identity to practices associated with both foreign and ‘classical’ Islamic ideals

The Case for Learned Index Structures

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not. In this exploratory research paper, we start from this premise and posit that all existing index structures can be replaced with other types of models, including deep-learning models, which we term learned indexes. The key idea is that a model can learn the sort order or structure of lookup keys and use this signal to effectively predict the position or existence of records. We theoretically analyze under which conditions learned indexes outperform traditional index structures and describe the main challenges in designing learned index structures. Our initial results show, that by using neural nets we are able to outperform cache-optimized B-Trees by up to 70% in speed while saving an order-of-magnitude in memory over several real-world data sets. More importantly though, we believe that the idea of replacing core components of a data management system through learned models has far reaching implications for future systems designs and that this work just provides a glimpse of what might be possible

3.4 Physical activity in adolescents with juvenile idiopathic arthritis

OBJECTIVE: To explore physical activity (PA) in adolescents with juvenile idiopathic arthritis (JIA) compared with a healthy population and to examine associations between PA and disease-related factors. METHODS: Total energy expenditure (TEE), activity-related energy expenditure (AEE), PA level, and PA pattern were assessed with a 3-day activity diary. Aerobic capacity was assessed using a Symptom Limited Bicycle Ergometry test. Functional ability was assessed with the Childhood Health Assessment Questionnaire. Disease activity was assessed using Paediatric Rheumatology International Trials Organisation core set criteria. Overall well-being was measured using a visual analog scale, and time since diagnosis was assessed by retrospective study from patients' charts. We used a cross-sectional study design. Reference data were collected from healthy Dutch secondary school children. RESULTS: Thirty patients and 106 controls were included (mean +/- SD age 17.0 +/- 0.6 and 16.7 +/- 0.9 years, respectively). TEE, AEE, and PA level were significantly lower in the JIA group. The JIA group spent more time in bed and less time on moderate to vigorous PA. Only 23% of the JIA patients met public health recommendations to perform >/=1 hour daily moderate to vigorous PA compared with 66% in the reference group. Higher PA was associated with higher levels of well-being and maximal oxygen consumption. CONCLUSION: Adolescents with JIA have low PA levels and are at risk of losing the benefits of PA. Low PA is not related to disease activity, and control over the disease does not restore previous PA levels. Interventions by pediatric rheumatologists are needed to increase PA levels in patients with JIA

Continuous-action reinforcement learning for memory allocation in virtualized servers

In a virtualized computing server (node) with multiple Virtual Machines (VMs), it is necessary to dynamically allocate memory among the VMs. In many cases, this is done only considering the memory demand of each VM without having a node-wide view. There are many solutions for the dynamic memory allocation problem, some of which use machine learning in some form. This paper introduces CAVMem (Continuous-Action Algorithm for Virtualized Memory Management), a proof-of-concept mechanism for a decentralized dynamic memory allocation solution in virtualized nodes that applies a continuous-action reinforcement learning (RL) algorithm called Deep Deterministic Policy Gradient (DDPG). CAVMem with DDPG is compared with other RL algorithms such as Q-Learning (QL) and Deep Q-Learning (DQL) in an environment that models a virtualized node. In order to obtain linear scaling and be able to dynamically add and remove VMs, CAVMem has one agent per VM connected via a lightweight coordination mechanism. The agents learn how much memory to bid for or return, in a given state, so that each VM obtains a fair level of performance subject to the available memory resources. Our results show that CAVMem with DDPG performs better than QL and a static allocation case, but it is competitive with DQL. However, CAVMem incurs significant less training overheads than DQL, making the continuous-action approach a more cost-effective solution.This research is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 754337 (EuroEXA) and the European Union’s 7th Framework Programme under grant agreement number 610456 (Euroserver). It also received funding from the Spanish Ministry of Science and Technology (project TIN2015-65316-P), Generalitat de Catalunya (contract 2014-SGR-1272), and the Severo Ochoa Programme (SEV-2015-0493) of the Spanish Government.Peer ReviewedPostprint (author's final draft

Pharmacological conditioning for juvenile idiopathic arthritis: a potential solution to reduce methotrexate intolerance

Background Methotrexate (MTX) therapy has proven to be a successful and safe treatment for Juvenile Idiopathic Arthritis (JIA). Despite the high efficacy rates of MTX, treatment outcomes are often complicated by burdensome gastro-intestinal side effects. Intolerance rates for MTX in children are high (approximately 50%) and thus far no conclusive effective treatment strategies to control for side effects have been found. To address this need, this article proposes an innovative research approach based on pharmacological conditioning, to reduce MTX intolerance. Presentation of the hypothesis A collaboration between medical psychologists, pediatric rheumatologists, pharmacologists and patient groups was set up to develop an innovative research design that may be implemented to study potential improved control of side effects in JIA, by making use of the psychobiological principles of pharmacological conditioning. In pharmacological conditioning designs, learned positive associations from drug therapies (conditioning effects) are integrated in regular treatment regimens to maximize treatment outcomes. Medication regimens with immunosuppressant drugs that made use of pharmacological conditioning principles have been shown to lead to optimized therapeutic effects with reduced drug dosing, which might ultimately cause a reduction in side effects. Testing the hypothesis This research design is tailored to serve the needs of the JIA patient group. We developed a research design in collaboration with an interdisciplinary research group consisting of patient representatives, pediatric rheumatologists, pharmacologists, and medical psychologists

Pharmacological conditioning for juvenile idiopathic arthritis: a potential solution to reduce methotrexate intolerance

Background Methotrexate (MTX) therapy has proven to be a successful and safe treatment for Juvenile Idiopathic Arthritis (JIA). Despite the high efficacy rates of MTX, treatment outcomes are often complicated by burdensome gastro-intestinal side effects. Intolerance rates for MTX in children are high (approximately 50%) and thus far no conclusive effective treatment strategies to control for side effects have been found. To address this need, this article proposes an innovative research approach based on pharmacological conditioning, to reduce MTX intolerance. Presentation of the hypothesis A collaboration between medical psychologists, pediatric rheumatologists, pharmacologists and patient groups was set up to develop an innovative research design that may be implemented to study potential improved control of side effects in JIA, by making use of the psychobiological principles of pharmacological conditioning. In pharmacological conditioning designs, learned positive associations from drug therapies (conditioning effects) are integrated in regular treatment regimens to maximize treatment outcomes. Medication regimens with immunosuppressant drugs that made use of pharmacological conditioning principles have been shown to lead to optimized therapeutic effects with reduced drug dosing, which might ultimately cause a reduction in side effects. Testing the hypothesis This research design is tailored to serve the needs of the JIA patient group. We developed a research design in collaboration with an interdisciplinary research group consisting of patient representatives, pediatric rheumatologists, pharmacologists, and medical psychologists