Long-range dependence in a changing Internet traffic mix

This paper provides a deep analysis of long-range dependence in a continually evolving Internet traffic mix by employing a number of recently developed statistical methods. Our study considers time-of-day, day-of-week, and cross-year variations in the traffic on an Internet link. Surprisingly large and consistent differences in the packet-count time series were observed between data from 2002 and 2003. A careful examination, based on stratifying the data according to protocol, revealed that the large difference was driven by a single UDP application that was not present in 2002. Another result was that the observed large differences between the two years showed up only in packet-count time series, and not in byte counts (while conventional wisdom suggests that these should be similar). We also found and analyzed several of the time series that exhibited more “bursty” characteristics than could be modeled as Fractional Gaussian Noise. The paper also shows how modern statistical tools can be used to study long-range dependence and non-stationarity in Internet traffic data

Efficient Reconstruction of Metabolic Pathways by Bidirectional Chemical Search

One of the main challenges in systems biology is the establishment of the metabolome: a catalogue of the metabolites and biochemical reactions present in a specific organism. Current knowledge of biochemical pathways as stored in public databases such as KEGG, is based on carefully curated genomic evidence for the presence of specific metabolites and enzymes that activate particular biochemical reactions. In this paper, we present an efficient method to build a substantial portion of the artificial chemistry defined by the metabolites and biochemical reactions in a given metabolic pathway, which is based on bidirectional chemical search. Computational results on the pathways stored in KEGG reveal novel biochemical pathways

Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time, and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space. While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes, vast areas of the tropics remain understudied. In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity, but it remains among the least known forests in America and is often underrepresented in biodiversity databases. To worsen this situation, human-induced modifications may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge, it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

International nosocomial infection control consortium (INICC) report, data summary of 36 countries, for 2004-2009

The results of a surveillance study conducted by the International Nosocomial Infection Control Consortium (INICC) from January 2004 through December 2009 in 422 intensive care units (ICUs) of 36 countries in Latin America, Asia, Africa, and Europe are reported. During the 6-year study period, using Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN; formerly the National Nosocomial Infection Surveillance system [NNIS]) definitions for device-associated health care-associated infections, we gathered prospective data from 313,008 patients hospitalized in the consortium's ICUs for an aggregate of 2,194,897 ICU bed-days. Despite the fact that the use of devices in the developing countries' ICUs was remarkably similar to that reported in US ICUs in the CDC's NHSN, rates of device-associated nosocomial infection were significantly higher in the ICUs of the INICC hospitals; the pooled rate of central line-associated bloodstream infection in the INICC ICUs of 6.8 per 1,000 central line-days was more than 3-fold higher than the 2.0 per 1,000 central line-days reported in comparable US ICUs. The overall rate of ventilator-associated pneumonia also was far higher (15.8 vs 3.3 per 1,000 ventilator-days), as was the rate of catheter-associated urinary tract infection (6.3 vs. 3.3 per 1,000 catheter-days). Notably, the frequencies of resistance of Pseudomonas aeruginosa isolates to imipenem (47.2% vs 23.0%), Klebsiella pneumoniae isolates to ceftazidime (76.3% vs 27.1%), Escherichia coli isolates to ceftazidime (66.7% vs 8.1%), Staphylococcus aureus isolates to methicillin (84.4% vs 56.8%), were also higher in the consortium's ICUs, and the crude unadjusted excess mortalities of device-related infections ranged from 7.3% (for catheter-associated urinary tract infection) to 15.2% (for ventilator-associated pneumonia). Copyright © 2012 by the Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved

Using the shape of sgitta otoliths in the discrimination of phenotypic stocks in Scomberomorus sierra (Jordan and Starks, 1895)

Geometric morphometric analysis was used to evaluate the shape of complete and broken otoliths in stock discrimination of Scomberomorus sierra. Data come from three different fishing locations in the mouth of the Gulf of California. Of the 70 otoliths pairs from location, 35 were broken. On the Complete Otoliths (CO) image 41 marks were located and 31 on Broken Otoliths (BO), the latter lacking rostrum. To evaluate the potential loss of BO resolution, the last 10 marks were eliminated from the CO and a third set of information was integrated as Virtually Broken Otoliths (VBO). The effect of the size, position and orientation of the spatial configurations of the otoliths were eliminated through the procedure of Procrustes superimposition. A canonical variable analysis detected significant differences (p&lt;0.05) in the three data sets and the distribution of the scores indicated a clear separation of the three groups, suggesting a morphologic difference of the otoliths from the three fishing locations. Also, the pairwise differences based on the Procrustes distances were statistically significant in all cases (p&lt;0.05). In agreement with Mahalanobis distances, the average percentage of correct assignation varied from 89% in CO and VBO to 80% in BO. It is ruled out that the morphologic differences are attributed to an allometric effect, since, in none of the cases the size of the centroid showed a significant correlation with the canonical axes. The present study constitutes an important referent to maximize the use of the information about otoliths, which due to their fragility break during extraction and manipulation