373 research outputs found

    miR824-Regulated AGAMOUS-LIKE16 Contributes to Flowering Time Repression in Arabidopsis

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    The timing of flowering is pivotal for maximizing reproductive success under fluctuating environmental conditions. Flowering time is tightly controlled by complex genetic networks that integrate endogenous and exogenous cues, such as light, temperature, photoperiod, and hormones. Here, we show that AGAMOUS-LIKE16 (AGL16) and its negative regulator microRNA824 (miR824) control flowering time in Arabidopsis thaliana. Knockout of AGL16 effectively accelerates flowering in nonvernalized Col-FRI, in which the floral inhibitor FLOWERING LOCUS C (FLC) is strongly expressed, but shows no effect if plants are vernalized or grown in short days. Alteration of AGL16 expression levels by manipulating miR824 abundance influences the timing of flowering quantitatively, depending on the expression level and number of functional FLC alleles. The effect of AGL16 is fully dependent on the presence of FLOWERING LOCUS T (FT). Further experiments show that AGL16 can interact directly with SHORT VEGETATIVE PHASE and indirectly with FLC, two proteins that form a complex to repress expression of FT. Our data reveal that miR824 and AGL16 modulate the extent of flowering time repression in a long-day photoperiod

    Towards multi-tenant cache management for ISP networks

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    The decreasing cost of storage and the advent of virtualization technology can allow Internet Service Providers (ISPs) to deploy multi-tenant caching infrastructures and lease them to content producers and Content Delivery Networks (CDNs). Serving content requests directly from the ISP network does not only reduce the delivery time, but also allows the ISP to optimize the network resources by controlling the placement and routing of content items. In this paper, we introduce a multi-tenant cache management approach that significantly reduces the bandwidth utilization of ISPs networks by pro-actively allocating caching space, leased by content producers and/or CDNs, and intelligently routing content to the end users. Using real content request traces, we show that the optimal solution to this problem can increase the cache hit ratio by 70.64% while reducing the bandwidth usage by 57.17% on average, compared to a commonly used reactive cache management scheme. These results provide a benchmark for the development of novel multi-tenant cache management strategies

    Cloud-Based Desktop Services for Thin Clients

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    Plasma fibrinogen: now also an antidepressant response marker?

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    Major depressive disorder (MDD) is one of the leading causes of global disability. It is a risk factor for noncompliance with medical treatment, with about 40% of patients not responding to currently used antidepressant drugs. The identification and clinical implementation of biomarkers that can indicate the likelihood of treatment response are needed in order to predict which patients will benefit from an antidepressant drug. While analyzing the blood plasma proteome collected from MDD patients before the initiation of antidepressant medication, we observed different fibrinogen alpha (FGA) levels between drug responders and nonresponders. These results were replicated in a second set of patients. Our findings lend further support to a recently identified association between MDD and fibrinogen levels from a large-scale study

    Advances in Networking Software

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    The six articles in this special section focus on advancements in networking software. Networking and communications systems are currently undergoing a substantive transformation on several fronts, promising substantially lower cost, simplified operations, and dramatically faster innovation cycles as traditional barriers to the deployment of innovations are removed. Where in the past networking functions were predominantly implemented using purpose-built hardware, custom protocols, and firmware images, those networking functions are increasingly instantiated through software that is abstracted from hardware, freely programmable, and relying on algorithmic invocation of generic application programming interfaces (APIs). This transformation is best summarized as “softwarization” of the network, which is, in turn, realized through advances in networking software. These articles exemplify this transformation, providing an excellent cross-section across these facets

    Improvements in data quality for decision support in intensive care

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    Nowadays, there is a plethora of technology in hospitals and, in particular, in intensive care units. The clinical data produced everyday can be integrated in a decision support system in real-time to improve quality of care of the critically ill patients. However, there are many sensitive aspects that must be taken into account, mainly the data quality and the integration of heterogeneous data sources. This paper presents INTCare, an Intelligent Decision Support System for Intensive Care in real-time and addresses the previous aspects, in particular, the development of an Electronic Nursing Record and the improvements in the quality of monitored data.Fundação para a Ciência e a Tecnologia (FCT

    Proactive Multi-tenant Cache Management for Virtualized ISP Networks

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    The content delivery market has mainly been dominated by large Content Delivery Networks (CDNs) such as Akamai and Limelight. However, CDN traffic exerts a lot of pressure on Internet Service Provider (ISP) networks. Recently, ISPs have begun deploying so-called Telco CDNs, which have many advantages, such as reduced ISP network bandwidth utilization and improved Quality of Service (QoS) by bringing content closer to the end-user. Virtualization of storage and networking resources can enable the ISP to simultaneously lease its Telco CDN infrastructure to multiple third parties, opening up new business models and revenue streams. In this paper, we propose a proactive cache management system for ISP-operated multitenant Telco CDNs. The associated algorithm optimizes content placement and server selection across tenants and users, based on predicted content popularity and the geographical distribution of requests. Based on a Video-on-Demand (VoD) request trace of a leading European telecom operator, the presented algorithm is shown to reduce bandwidth usage by 17% compared to the traditional Least Recently Used (LRU) caching strategy, both inside the network and on the ingress links, while at the same time offering enhanced load balancing capabilities. Increasing the prediction accuracy is shown to have the potential to further improve bandwidth efficiency by up to 79%
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