187 research outputs found

    GRADES: Gradient descent for similarity caching

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    International audienceA similarity cache can reply to a query for an object with similar objects stored locally. In some applications of similarity caches, queries and objects are naturally represented as points in a continuous space. Examples include 360° videos where user's head orientation-expressed in spherical coordinates determines what part of the video needs to be retrieved, and recommendation systems where the objects are embedded in a finite-dimensional space with a distance metric to capture content dissimilarity. Existing similarity caching policies are simple modifications of classic policies like LRU, LFU, and qLRU and ignore the continuous nature of the space where objects are embedded. In this paper, we propose GRADES, a new similarity caching policy that uses gradient descent to navigate the continuous space and find the optimal objects to store in the cache. We provide theoretical convergence guarantees and show GRADES increases the similarity of the objects served by the cache in both applications mentioned above

    GRADES: Gradient descent for similarity caching

    Get PDF
    A similarity cache can reply to a query for an object with similar objects stored locally. In some applications of similarity caches, queries and objects are naturally represented as points in a continuous space. Examples include 360° videos where user's head orientation - expressed in spherical coordinates - determines what part of the video needs to be retrieved, and recommendation systems where the objects are embedded in a finite-dimensional space with a distance metric to capture content dissimilarity. Existing similarity caching policies are simple modifications of classic policies like LRU, LFU, and qLRU and ignore the continuous nature of the space where objects are embedded. In this paper, we propose Grades, a new similarity caching policy that uses gradient descent to navigate the continuous space and find the optimal objects to store in the cache. We provide theoretical convergence guarantees and show Grades increases the similarity of the objects served by the cache in both applications mentioned above

    Oral Migalastat HCl Leads to Greater Systemic Exposure and Tissue Levels of Active α-Galactosidase A in Fabry Patients when Co-Administered with Infused Agalsidase.

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    UnlabelledMigalastat HCl (AT1001, 1-Deoxygalactonojirimycin) is an investigational pharmacological chaperone for the treatment of α-galactosidase A (α-Gal A) deficiency, which leads to Fabry disease, an X-linked, lysosomal storage disorder. The currently approved, biologics-based therapy for Fabry disease is enzyme replacement therapy (ERT) with either agalsidase alfa (Replagal) or agalsidase beta (Fabrazyme). Based on preclinical data, migalastat HCl in combination with agalsidase is expected to result in the pharmacokinetic (PK) enhancement of agalsidase in plasma by increasing the systemic exposure of active agalsidase, thereby leading to increased cellular levels in disease-relevant tissues. This Phase 2a study design consisted of an open-label, fixed-treatment sequence that evaluated the effects of single oral doses of 150 mg or 450 mg migalastat HCl on the PK and tissue levels of intravenously infused agalsidase (0.2, 0.5, or 1.0 mg/kg) in male Fabry patients. As expected, intravenous administration of agalsidase alone resulted in increased α-Gal A activity in plasma, skin, and peripheral blood mononuclear cells (PBMCs) compared to baseline. Following co-administration of migalastat HCl and agalsidase, α-Gal A activity in plasma was further significantly increased 1.2- to 5.1-fold compared to agalsidase administration alone, in 22 of 23 patients (95.6%). Importantly, similar increases in skin and PBMC α-Gal A activity were seen following co-administration of migalastat HCl and agalsidase. The effects were not related to the administered migalastat HCl dose, as the 150 mg dose of migalastat HCl increased α-Gal A activity to the same extent as the 450 mg dose. Conversely, agalsidase had no effect on the plasma PK of migalastat. No migalastat HCl-related adverse events or drug-related tolerability issues were identified.Trial registrationClinicalTrials.gov NCT01196871

    Low Latency Geo-distributed Data Analytics

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    Low latency analytics on geographically distributed dat-asets (across datacenters, edge clusters) is an upcoming and increasingly important challenge. The dominant approach of aggregating all the data to a single data-center significantly inflates the timeliness of analytics. At the same time, running queries over geo-distributed inputs using the current intra-DC analytics frameworks also leads to high query response times because these frameworks cannot cope with the relatively low and variable capacity of WAN links. We present Iridium, a system for low latency geo-distri-buted analytics. Iridium achieves low query response times by optimizing placement of both data and tasks of the queries. The joint data and task placement op-timization, however, is intractable. Therefore, Iridium uses an online heuristic to redistribute datasets among the sites prior to queries ’ arrivals, and places the tasks to reduce network bottlenecks during the query’s ex-ecution. Finally, it also contains a knob to budget WAN usage. Evaluation across eight worldwide EC2 re-gions using production queries show that Iridium speeds up queries by 3 × − 19 × and lowers WAN usage by 15% − 64 % compared to existing baselines

    The Radish Gene Reveals a Memory Component with Variable Temporal Properties

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    Memory phases, dependent on different neural and molecular mechanisms, strongly influence memory performance. Our understanding, however, of how memory phases interact is far from complete. In Drosophila, aversive olfactory learning is thought to progress from short-term through long-term memory phases. Another memory phase termed anesthesia resistant memory, dependent on the radish gene, influences memory hours after aversive olfactory learning. How does the radish-dependent phase influence memory performance in different tasks? It is found that the radish memory component does not scale with the stability of several memory traces, indicating a specific recruitment of this component to influence different memories, even within minutes of learning

    Income and Poverty in a Developing Economy

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    We present a stochastic agent-based model for the distribution of personal incomes in a developing economy. We start with the assumption that incomes are determined both by individual labour and by stochastic effects of trading and investment. The income from personal effort alone is distributed about a mean, while the income from trade, which may be positive or negative, is proportional to the trader's income. These assumptions lead to a Langevin model with multiplicative noise, from which we derive a Fokker-Planck (FP) equation for the income probability density function (IPDF) and its variation in time. We find that high earners have a power-law income distribution while the low income groups have a Levy IPDF. Comparing our analysis with the Indian survey data (obtained from the world bank website) taken over many years we obtain a near-perfect data collapse onto our model's equilibrium IPDF. The theory quantifies the economic notion of "given other things". Using survey data to relate the IPDF to actual food consumption we define a poverty index, which is consistent with traditional indices, but independent of an arbitrarily chosen "poverty line" and therefore less susceptible to manipulation

    The Utility of Endoscopic Ultrasound in Patients with Isolated Elevations in Serum Amylase and/or Lipase

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    Background/Aims The aim of this study was to describe the diagnostic yield of endoscopic ultrasound (EUS) in patients with isolated elevated levels of amylase and/or lipase. Methods A retrospective chart review was conducted at a large academic medical center from 2000 to 2016. Patients were selected based on having elevated amylase, lipase, or both, but without a diagnosis of pancreatitis or known pancreatobiliary disease. Patients were excluded if they had abnormal liver function tests or abnormal imaging of the pancreas. Results Of 299 EUS procedures performed, 38 met inclusion criteria. Symptoms were present in 31 patients, most frequently abdominal pain (87%). In 20 patients (53%), initial EUS most commonly found chronic pancreatitis (n=7; 18%), sludge (5; 13%), or new diagnosis of pancreas divisum (3; 8%). In the asymptomatic patients (7), 3 had a finding on EUS, most importantly sludge (2), stone (1), and pancreas divisum (1). No patients were diagnosed with a mass or pancreatic cyst. During the follow up period, 6 patients (22%) had cholecystectomy. Conclusions In our study of patients with isolated elevations in amylase and/or lipase without acute pancreatitis who underwent EUS, approximately 50% had a pancreatobiliary finding, most commonly chronic pancreatitis or biliary sludge

    Protein Microarray On-Demand: A Novel Protein Microarray System

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    We describe a novel, simple and low-cost protein microarray strategy wherein the microarrays are generated by printing expression ready plasmid DNAs onto slides that can be converted into protein arrays on-demand. The printed expression plasmids serve dual purposes as they not only direct the synthesis of the protein of interest; they also serve to capture the newly synthesized proteins through a high affinity DNA-protein interaction. To accomplish this we have exploited the high-affinity binding (∼3–7×10 −13 M) of E. coli Tus protein to Ter, a 20 bp DNA sequence involved in the regulation of E. coli DNA replication. In our system, each protein of interest is synthesized as a Tus fusion protein and each expression construct directing the protein synthesis contains embedded Ter DNA sequence. The embedded Ter sequence functions as a capture reagent for the newly synthesized Tus fusion protein. This “all DNA” microarray can be converted to a protein microarray on-demand without need for any additional capture reagent.
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