Impact of data quality in real-time big data systems

Data Quality is one of the main challenges in any type of Big Data System. Timeliness is one of the main factors in real-time Big Data. Limiting data quality evaluations to data sources may be insufficient in Big Data Systems with high Velocity and Variability. On the other hand, real-time Data Quality evaluations throughout the Big Data Pipeline can be costly (i.e., latency introduced by Data Quality Evaluations). This paper identifies four categories – embedded, parallel, in-line, and independent– of approaches for Big Data Quality Evaluation available in the literature. A real-time Big Data System based on the SmartCambridge Real-Time Data Platform is deployed and used as basis to implement a representative case for each one of the four categories identified. An application for bus catching dynamic prediction is used as case study to quantify the impact of these Data Quality Evaluations in the Real-Time Data Platform in terms of latency introduced in the system. Results suggests that the impact of Data Quality Evaluations differ depending on the type of method used, and that the main factors are the data transfers between Data Quality modules and the data processing algorithms, the synchronisation of messages, and the complexity of the Data Quality algorithms

Molecular Diversity of Trypanosoma cruzi Detected in the Vector Triatoma protracta from California, USA.

BACKGROUND: Trypanosoma cruzi, causative agent of Chagas disease in humans and dogs, is a vector-borne zoonotic protozoan parasite that can cause fatal cardiac disease. While recognized as the most economically important parasitic infection in Latin America, the incidence of Chagas disease in the United States of America (US) may be underreported and even increasing. The extensive genetic diversity of T. cruzi in Latin America is well-documented and likely influences disease progression, severity and treatment efficacy; however, little is known regarding T. cruzi strains endemic to the US. It is therefore important to expand our knowledge on US T. cruzi strains, to improve upon the recognition of and response to locally acquired infections. METHODOLOGY/PRINCIPLE FINDINGS: We conducted a study of T. cruzi molecular diversity in California, augmenting sparse genetic data from southern California and for the first time investigating genetic sequences from northern California. The vector Triatoma protracta was collected from southern (Escondido and Los Angeles) and northern (Vallecito) California regions. Samples were initially screened via sensitive nuclear repetitive DNA and kinetoplast minicircle DNA PCR assays, yielding an overall prevalence of approximately 28% and 55% for southern and northern California regions, respectively. Positive samples were further processed to identify discrete typing units (DTUs), revealing both TcI and TcIV lineages in southern California, but only TcI in northern California. Phylogenetic analyses (targeting COII-ND1, TR and RB19 genes) were performed on a subset of positive samples to compare Californian T. cruzi samples to strains from other US regions and Latin America. Results indicated that within the TcI DTU, California sequences were similar to those from the southeastern US, as well as to several isolates from Latin America responsible for causing Chagas disease in humans. CONCLUSIONS/SIGNIFICANCE: Triatoma protracta populations in California are frequently infected with T. cruzi. Our data extend the northern limits of the range of TcI and identify a novel genetic exchange event between TcI and TcIV. High similarity between sequences from California and specific Latin American strains indicates US strains may be equally capable of causing human disease. Additional genetic characterization of Californian and other US T. cruzi strains is recommended

Exercise training in obese rats does not induce browning at thermoneutrality and induces a muscle-like signature in brown adipose tissue

Aim: Exercise training elicits diverse effects on brown (BAT) and white adipose tissue (WAT) physiology in rodents housed below their thermoneutral zone (i.e., 28–32°C). In these conditions, BAT is chronically hyperactive and, unlike human residence, closer to thermoneutrality. Therefore, we set out to determine the effects of exercise training in obese animals at 28°C (i.e., thermoneutrality) on BAT and WAT in its basal (i.e., inactive) state. Methods: Sprague-Dawley rats (n = 12) were housed at thermoneutrality from 3 weeks of age and fed a high-fat diet. At 12 weeks of age half these animals were randomized to 4-weeks of swim-training (1 h/day, 5 days per week). Following a metabolic assessment interscapular and perivascular BAT and inguinal (I)WAT were taken for analysis of thermogenic genes and the proteome. Results: Exercise attenuated weight gain but did not affect total fat mass or thermogenic gene expression. Proteomics revealed an impact of exercise training on 2-oxoglutarate metabolic process, mitochondrial respiratory chain complex IV, carbon metabolism, and oxidative phosphorylation. This was accompanied by an upregulation of multiple proteins involved in skeletal muscle physiology in BAT and an upregulation of muscle specific markers (i.e., Myod1, CkM, Mb, and MyoG). UCP1 mRNA was undetectable in IWAT with proteomics highlighting changes to DNA binding, the positive regulation of apoptosis, HIF-1 signaling and cytokine-cytokine receptor interaction. Conclusion: Exercise training reduced weight gain in obese animals at thermoneutrality and is accompanied by an oxidative signature in BAT which is accompanied by a muscle-like signature rather than induction of thermogenic genes. This may represent a new, UCP1-independent pathway through which BAT physiology is regulated by exercise training

A Multi-Faceted Strategy for Evidence Translation Reduces Healthcare Waiting Time: A Mixed Methods Study Using the RE-AIM Framework

Background: Waiting lists are often thought to be inevitable in healthcare, but strategies that address patient flow by reducing complexity, combining triage with initial management, and/or actively managing the relationship between supply and demand can work. One such model, Specific Timely Appointments for Triage (STAT), brings these elements together and has been found in multiple trials to reduce waiting times by 30–40%. The next challenge is to translate this knowledge into practice.Method: A multi-faceted knowledge translation strategy, including workshops, resources, dissemination of research findings and a community of practice (CoP) was implemented. A mixed methods evaluation of the strategy was conducted based on the RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework, drawing on an internal database and a survey of workshop and CoP participants.Results: Demonstrating reach, at July 2020 an internal database held details of 342 clinicians and managers from 64 health services who had participated in the workshop program (n = 308) and/or elected to join an online CoP (n = 227). 40 of 69 (58%) respondents to a survey of this population reported they had adopted the model, with some providing data demonstrating that the STAT model had been efficacious in reducing waiting time. Perceived barriers to implementation included an overwhelming existing waiting list, an imbalance between supply and demand and lack of resources.Conclusion: There is high quality evidence from trials that STAT reduces waiting time. Using the RE-AIM framework, this evaluation of a translation strategy demonstrates uptake of evidence to reduce waiting time in health services.</jats:p

Ecological correlates of chimpanzee (Pan troglodytes schweinfurthii) density in Mahale Mountains National Park, Tanzania

Understanding the ecological factors that drive animal density patterns in time and space is key to devising effective conservation strategies. In Tanzania, most chimpanzees (~75%) live outside national parks where human activities threaten their habitat’s integrity and connectivity. Mahale Mountains National Park (MMNP), therefore, is a critical area for chimpanzees (Pan troglodytes schweinfurthii) in the region due to its location and protective status. Yet, despite its importance and long history of chimpanzee research (>50 years), a park-wide census of the species has never been conducted. The park is categorized as a savanna-woodland mosaic, interspersed with riparian forest, wooded grassland, and bamboo thicket. This heterogeneous landscape offers an excellent opportunity to assess the ecological characteristics associated with chimpanzee density, a topic still disputed, which could improve conservation plans that protect crucial chimpanzee habitat outside the park. We examined the influence of fine-scale vegetative characteristics and topographical features on chimpanzee nest density, modeling nest counts using hierarchical distance sampling. We counted 335 nests in forest and woodland habitats across 102 transects in 13 survey sites. Nests were disproportionately found more in or near evergreen forests, on steep slopes, and in feeding tree species. We calculated chimpanzee density in MMNP to be 0.23 ind/km2 , although density varied substantially among sites (0.09 - 3.43 ind/km2 29 ). Density was associated with factors related to the availability of food and nesting trees, with topographic heterogeneity and the total basal area of feeding tree species identified as significant positive predictors. Species-rich habitats and floristic diversity likely play a principal role in shaping chimpanzee density within a predominately open landscape with low food abundance. Our results provide valuable baseline data for future monitoring efforts in MMNP and enhance our understanding of this endangered species’ density and distribution across Tanzania

The use of happiness research for public policy

Research on happiness tends to follow a "benevolent dictator" approach where politicians pursue people's happiness. This paper takes an antithetic approach based on the insights of public choice theory. First, we inquire how the results of happiness research may be used to improve the choice of institutions. Second, we show that the policy approach matters for the choice of research questions and the kind of knowledge happiness research aims to provide. Third, we emphasize that there is no shortcut to an optimal policy maximizing some happiness indicator or social welfare function since governments have an incentive to manipulate this indicator

Spatiotemporal correlations of handset-based service usages

We study spatiotemporal correlations and temporal diversities of handset-based service usages by analyzing a dataset that includes detailed information about locations and service usages of 124 users over 16 months. By constructing the spatiotemporal trajectories of the users we detect several meaningful places or contexts for each one of them and show how the context affects the service usage patterns. We find that temporal patterns of service usages are bound to the typical weekly cycles of humans, yet they show maximal activities at different times. We first discuss their temporal correlations and then investigate the time-ordering behavior of communication services like calls being followed by the non-communication services like applications. We also find that the behavioral overlap network based on the clustering of temporal patterns is comparable to the communication network of users. Our approach provides a useful framework for handset-based data analysis and helps us to understand the complexities of information and communications technology enabled human behavior.Comment: 11 pages, 15 figure

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review

Background: Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. Methods: We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. Results: For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Conclusions: Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses