315 research outputs found
Near-Optimal Straggler Mitigation for Distributed Gradient Methods
Modern learning algorithms use gradient descent updates to train inferential
models that best explain data. Scaling these approaches to massive data sizes
requires proper distributed gradient descent schemes where distributed worker
nodes compute partial gradients based on their partial and local data sets, and
send the results to a master node where all the computations are aggregated
into a full gradient and the learning model is updated. However, a major
performance bottleneck that arises is that some of the worker nodes may run
slow. These nodes a.k.a. stragglers can significantly slow down computation as
the slowest node may dictate the overall computational time. We propose a
distributed computing scheme, called Batched Coupon's Collector (BCC) to
alleviate the effect of stragglers in gradient methods. We prove that our BCC
scheme is robust to a near optimal number of random stragglers. We also
empirically demonstrate that our proposed BCC scheme reduces the run-time by up
to 85.4% over Amazon EC2 clusters when compared with other straggler mitigation
strategies. We also generalize the proposed BCC scheme to minimize the
completion time when implementing gradient descent-based algorithms over
heterogeneous worker nodes
Sustainable Architecture of the Bazaar of Tabriz and its relation with the social and cultural aspects
ABSTRACT - Sustainable architecture aims to design buildings and infra-structures, such as squares and bazaars, adapted to the social, economic, cultural and environmental contexts of certain place. The practice of sustainable architecture contributes to sustainable development, therefore for the development of future generations. The concept must integrate not only bioclimatic strategies, but also economic, social and cultural facets. Sustainable architecture research is either carried while the designing process takes place (the present) but is also focused on the built environment through the historical time of a place (the past). The aim of this article is to bring to the academic discussion new perspectives on sustainable architecture and debate the relationship between the architectural elements and the social and cultural aspects by taking the Tabriz Historic Bazaar Complex as case study. Infra-structures like Bazaars are geographically placed all over the world, from Turkey to Egypt, from Tajikistan to Iran. In Iranian cities, the bazaar keeps playing an important role as economic and social engine. Thus, research the main elements that keep the Bazaar of Tabriz so actively dynamic in the present will be discussed
Higher fundamental frequency in bonobos is explained by larynx morphology
Acoustic signals, shaped by natural and sexual selection, reveal ecological and social selection pressures [1]. Examining acoustic signals together with morphology can be particularly revealing. But this approach has rarely been applied to primates, where clues to the evolutionary trajectory of human communication may be found. Across vertebrate species, there is a close relationship between body size and acoustic parameters, such as formant dispersion and fundamental frequency (f0). Deviations from this acoustic allometry usually produce calls with a lower f0 than expected for a given body size, often due to morphological adaptations in the larynx or vocal tract [2]. An unusual example of an obvious mismatch between fundamental frequency and body size is found in the two closest living relatives of humans, bonobos (Pan paniscus) and chimpanzees (Pan troglodytes). Although these two ape species overlap in body size [3], bonobo calls have a strikingly higher f0 than corresponding calls from chimpanzees [4]. Here, we compare acoustic structures of calls from bonobos and chimpanzees in relation to their larynx morphology. We found that shorter vocal fold length in bonobos compared to chimpanzees accounted for species differences in f0, showing a rare case of positive selection for signal diminution in both bonobo sexes
Lagrange Coded Computing: Optimal Design for Resiliency, Security, and Privacy
We consider a scenario involving computations over a massive dataset stored distributedly across multiple workers, which is at the core of distributed learning algorithms. We propose Lagrange Coded Computing (LCC), a new framework to simultaneously provide (1) resiliency against stragglers that may prolong computations; (2) security against Byzantine (or malicious) workers that deliberately modify the computation for their benefit; and (3) (information-theoretic) privacy of the dataset amidst possible collusion of workers. LCC, which leverages the well-known Lagrange polynomial to create computation redundancy in a novel coded form across workers, can be applied to any computation scenario in which the function of interest is an arbitrary multivariate polynomial of the input dataset, hence covering many computations of interest in machine learning. LCC significantly generalizes prior works to go beyond linear computations. It also enables secure and private computing in distributed settings, improving the computation and communication efficiency of the state-of-the-art. Furthermore, we prove the optimality of LCC by showing that it achieves the optimal tradeoff between resiliency, security, and privacy, i.e., in terms of tolerating the maximum number of stragglers and adversaries, and providing data privacy against the maximum number of colluding workers. Finally, we show via experiments on Amazon EC2 that LCC speeds up the conventional uncoded implementation of distributed least-squares linear regression by up to 13.43×, and also achieves a 2.36×-12.65× speedup over the state-of-the-art straggler mitigation strategies
Adverse effects of nasal continuous positive airway pressure therapy in sleep apnoea syndrome
Nasal continuous positive airway pressure (nCPAP) is now the treatment of choice for patients with sleep apnoea syndrome. Side-effects and adverse reactions have been described in isolated reports with this device. We have, therefore, systematically studied the side-effects of nCPAP therapy in 300 consecutive patients referred to the London Chest Hospital Ventilatory Support Unit. Ninety-six per cent of patients complained of at least one side-effect resulting from the therapy, with 45 per cent complaining of a side-effect specific to the nasal mask. There was no correlation between the side-effects and level of pressure used during nCPAP. The rate of compliance remained high in spite of the side-effects, with a daily use of 7.8 hours (SD 8.05) and with 83 per cent of the patients using the device every night. Although nCPAP treatment remains acceptable to most patients there exists a high incidence of adverse effects
Cardiac rupture after myocardial infarction treated with tissue plasminogen activator: Results fron TIMI-II
Cannabis sativa L. oil extract affects neuroinflammation, clinical score, and cannabinoid receptor-1 gene expression in C57bl/6 experimental autoimmune encephalomyelitis
Introduction: Multiple sclerosis (MS) is a degenerative central nervous system disease derived by immune mechanisms, which ultimately results in clinical debilities. Numerous nutraceuticals have been cited to be effective in treatment of central nervous system complications. Objectives: This study investigated the effect of Cannabis sativa L. seed oil on experimental autoimmune encephalomyelitis (EAE). Materials and Methods: Female C57bl/6 mice were assigned randomly into three groups (8 in each). Group-A received no myelin oligodendrocyte glycoprotein (MOG), group B was immunized by MOG and treated with oil, while in group C animals were immunized and treated with normal saline. Clinical scores were recorded every other day throughout the study and after four weeks, all mice were sacrificed and spinal cords were incised for molecular and histopathological evaluations. Results: Significant differences were observed in mean clinical scores between control and experiment groups (P<0.001). Cannabinoid receptor-1 gene expression increased significantly in treatment group (P<0.001). Histopathologic evaluations also showed a significant decrease in overall infiltrated and vacuolated area and immune cells infiltration into the central nervous system in the treatment group (P<0.01). Conclusion: Cannabis sativa L. oil extract administration alleviated inflammation and paralysis in animal model. Therefore, its oil extract might be useful in soothing inflammatory and auto-immune diseases. However, additional research might be required.</jats:p
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