Document replication strategies for geographically distributed web search engines

Cataloged from PDF version of article.Large-scale web search engines are composed of multiple data centers that are geographically distant to each other. Typically, a user query is processed in a data center that is geographically close to the origin of the query, over a replica of the entire web index. Compared to a centralized, single-center search engine, this architecture offers lower query response times as the network latencies between the users and data centers are reduced. However, it does not scale well with increasing index sizes and query traffic volumes because queries are evaluated on the entire web index, which has to be replicated and maintained in all data centers. As a remedy to this scalability problem, we propose a document replication framework in which documents are selectively replicated on data centers based on regional user interests. Within this framework, we propose three different document replication strategies, each optimizing a different objective: reducing the potential search quality loss, the average query response time, or the total query workload of the search system. For all three strategies, we consider two alternative types of capacity constraints on index sizes of data centers. Moreover, we investigate the performance impact of query forwarding and result caching. We evaluate our strategies via detailed simulations, using a large query log and a document collection obtained from the Yahoo! web search engine. (C) 2012 Elsevier Ltd. All rights reserved

Co-infections and superinfections complicating COVID-19 in cancer patients: A multicentre, international study

Background: We aimed to describe the epidemiology, risk factors, and clinical outcomes of co-infections and superinfections in onco-hematological patients with COVID-19. Methods: International, multicentre cohort study of cancer patients with COVID-19. All patients were included in the analysis of co-infections at diagnosis, while only patients admitted at least 48 h were included in the analysis of superinfections. Results: 684 patients were included (384 with solid tumors and 300 with hematological malignancies). Co-infections and superinfections were documented in 7.8% (54/684) and 19.1% (113/590) of patients, respectively. Lower respiratory tract infections were the most frequent infectious complications, most often caused by Streptococcus pneumoniae and Pseudomonas aeruginosa. Only seven patients developed opportunistic infections. Compared to patients without infectious complications, those with infections had worse outcomes, with high rates of acute respiratory distress syndrome, intensive care unit (ICU) admission, and case-fatality rates. Neutropenia, ICU admission and high levels of C-reactive protein (CRP) were independent risk factors for infections. Conclusions: Infectious complications in cancer patients with COVID-19 were lower than expected, affecting mainly neutropenic patients with high levels of CRP and/or ICU admission. The rate of opportunistic infections was unexpectedly low. The use of empiric antimicrobials in cancer patients with COVID-19 needs to be optimized

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

A Term-Based Inverted Index Partitioning Model for Efficient Distributed Query Processing

Cataloged from PDF version of article.In a shared-nothing, distributed text retrieval system, queries are processed over an inverted index that is partitioned among a number of index servers. In practice, the index is either document-based or term-based partitioned. This choice is made depending on the properties of the underlying hardware infrastructure, query traffic distribution, and some performance and availability constraints. In query processing on retrieval systems that adopt a term-based index partitioning strategy, the high communication overhead due to the transfer of large amounts of data from the index servers forms a major performance bottleneck, deteriorating the scalability of the entire distributed retrieval system. In this work, to alleviate this problem, we propose a novel inverted index partitioning model that relies on hypergraph partitioning. In the proposed model, concurrently accessed index entries are assigned to the same index servers, based on the inverted index access patterns extracted from the past query logs. The model aims to minimize the communication overhead that will be incurred by future queries while maintaining the computational load balance among the index servers. We evaluate the performance of the proposed model through extensive experiments using a real-life text collection and a search query sample. Our results show that considerable performance gains can be achieved relative to the term-based index partitioning strategies previously proposed in literature. In most cases, however, the performance remains inferior to that attained by document-based partitioning

Query forwarding in geographically distributed search engines

Query forwarding is an important technique for preserving the result quality in distributed search engines where the index is geographically partitioned over multiple search sites. The key component in query forwarding is the thresholding algorithm by which the forwarding decisions are given. In this paper, we propose a linear-programming-based thresholding algorithm that significantly outperforms the current state-of-the-art in terms of achieved search efficiency values. Moreover, we evaluate a greedy heuristic for partial index replication and investigate the impact of result cache freshness on query forwarding performance. Finally, we present some optimizations that improve the performance further, under certain conditions. We evaluate the proposed techniques by simulations over a real-life setting, using a large query log and a document collection obtained from Yahoo!

Energy-price-driven query processing in multi-center web search engines

Concurrently processing thousands of web queries, each with a response time under a fraction of a second, necessitates maintaining and operating massive data centers. For largescale web search engines, this translates into high energy consumption and a huge electric bill. This work takes the challenge to reduce the electric bill of commercial web search engines operating on data centers that are geographically far apart. Based on the observation that energy prices and query workloads show high spatio-temporal variation, we propose a technique that dynamically shifts the query workload of a search engine between its data centers to reduce the electric bill. Experiments on real-life query workloads obtained from a commercial search engine show that significant financial savings can be achieved by this technique

Endocardite à bacilles à Gram négatif non HACEK

Patients and methods: Retrospective analysis of clinical data using 26 diagnosed non-HACEK Gram-negative infective endocarditis cases from nine hospitals in Turkey. Results: Mean age of patients was 53 (28–84) years, with a 23% case fatality. Nineteen (73%) of the 26 patients had at least one predisposing factor. The presence of a central venous catheter was the most common predisposing factor (7/26 patients). Pseudomonas aeruginosa (7/26 patients) and Escherichia coli (7/26 patients) were the most common pathogens. The median duration of the antibiotic therapy was 42 days (range 3–84 days). Surgical procedures were performed in 10 patients. The case fatality was similar in patients who did or did not undergo surgery (20% vs. 25%). © 2019Scopu

A multi-level hypergraph partitioning algorithm using rough set clustering

The hypergraph partitioning problem has many applications in scientific computing and provides a more accurate inter-processor communication model for distributed systems than the equivalent graph problem. In this paper, we propose a sequential multi-level hypergraph partitioning algorithm. The algorithm makes novel use of the technique of rough set clustering in categorising the vertices of the hypergraph. The algorithm treats hyperedges as features of the hypergraph and tries to discard unimportant hyperedges to make better clustering decisions. It also focuses on the trade-off to be made between local vertex matching decisions (which have low cost in terms of the space required and time taken) and global decisions (which can be of better quality but have greater costs). The algorithm is evaluated and compared to state-of-the-art algorithms on a range of benchmarks. The results show that it generates better partition quality

The clinical features, diagnosis, treatment, and prognosis of neuroinvasive listeriosis: a multinational study

The aim of this study was to determine the independent risk factors, morbidity, and mortality of central nervous system (CNS) infections caused by Listeria monocytogenes. We retrospectively evaluated 100 episodes of neuroinvasive listeriosis in a multinational study in 21 tertiary care hospitals of Turkey, France, and Italy from 1990 to 2014. The mean age of the patients was 57 years (range, 19-92 years), and 64% were males. The all-cause immunosuppression rate was 54 % (54/100). Forty-nine (49 %) patients were referred to a hospital because of the classical triad of symptoms (fever, nuchal rigidity, and altered level of consciousness). Rhombencephalitis was detected radiologically in 9 (9 %) cases. Twenty-seven (64 %) of the patients who had cranial magnetic resonance imaging (MRI) performed had findings of meningeal and parenchymal involvement. The mean delay in the initiation of specific treatment was 6.8 +/- 7 days. Empiric treatment was appropriate in 52 (52 %) patients. The mortality rate was 25 %, while neurologic sequelae occurred in 13 % of the patients. In the multivariate analysis, delay in treatment [odds ratio (OR), 1.07 [95 % confidence interval (CI), 1.01-1.16]] and seizures (OR, 3.41 [95 % CI, 1.05-11.09]) were significantly associated with mortality. Independent risk factors for neurologic sequelae were delay in treatment (OR, 1.07 [95 % CI, 1.006-1.367]) and presence of bacteremia (OR, 45.2 [95 % CI, 2.73-748.1]). Delay in the initiation of treatment of neuroinvasive listeriosis was a poor risk factor for unfavorable outcomes. Bacteremia was one of the independent risk factors for morbidity, while the presence of seizures predicted worse prognosis. Moreover, the addition of aminoglycosides to ampicillin monotherapy did not improve patients' prognosis