Source-specific Data Research Articles

Modelling the interplay of future changes and wastewater management measures on the microbiological river water quality considering safe drinking water production

Rivers are important for drinking water supply worldwide. However, they are often impacted by pathogen discharges via wastewater treatment plants (WWTP) and combined sewer overflows (CSO). To date, accurate predictions of the effects of future changes and pollution control measures on the microbiological water quality of rivers considering safe drinking water production are hindered due to the uncertainty of the pathogen source and transport variables. The aim of this study was to test an integrative approach for an improved understanding of these effects, i.e. climate change and population growth as well as enhanced treatment at WWTPs and/or prevention of CSOs. We applied a significantly extended version of QMRAcatch (v1.0 Python), a probabilistic-deterministic model that combines fate and transport modelling with quantitative microbial infection risk assessment. The impact of climatic changes until the period 2035–2049 was investigated by a conceptual semi-distributed hydrological model, based on regional climate model outputs. QMRAcatch was calibrated and validated using site- and source-specific data (human-associated genetic microbial source tracking marker and enterovirus). The study showed that the degree to which future changes affect drinking water safety strongly depends on the type and magnitude of faecal pollution sources and are thus highly site- and scenario-specific. For example, if the load of pathogens from WWTPs is reduced through enhanced treatment, climate-change driven increases in CSOs had a considerable impact. Preventing CSOs and installing enhanced treatment at the WWTPs together had the most significant positive effect. The simultaneous consideration of source apportionment and concentrations of reference pathogens, focusing on human-specific viruses (enterovirus, norovirus) and cross-comparison with bacterial and protozoan pathogens (Campylobacter, Cryptosporidium), was found crucial to quantify these effects. While demonstrated here for a large, wastewater-impacted river, the approach is applicable at other catchments and pollution sources. It allows assessing future changes and selecting suitable pollution control measures for long-term water safety planning.

Technological and methodological aspects of using reference and search tools in maintaining the database of Dubna University faculty’s publications

The author discusses the experience of building, maintaining and using the bibliographical database of science publications by the faculty of the state Dubna University. She analyzes in detail MegaPro ALIS retrieval functionality and describes different types of the system’s dictionaries and guides, their advantages and drawbacks in terms of entering data into bibliographic entry. The algorithm of using outer tables for reference when entering repeated subfields in one-click or entering data into several subfields of the bibliographic records. The example is given how hierarchical data of organization structure is used as an outer dictionary.Feasibility of using the directories of faculty authors and journals/other sources of information in publication databases is substantiated; example is given how to use them when entering several subfields of MARC21 fields 100, 700 and 773. The methodological solutions for maintaining directories of faculty authors and journals (and other information sources) are discussed.User and program interface for retrieving publications by author’s affliation, academic degree or title, institution, information source specific data are discussed as a result of building database of publications. The author emphasizes that the dictionaries may be used as supplementary information resources to support faculty publication activities and to integrate them into other university systems.

Consideration of sample source for establishing reliable genetic microsatellite data from mammalian carnivore specimens held in natural history collections

AbstractSpecimens from natural history collections (NHCs) are increasingly being used for genetic studies and can provide information on extinct populations, facilitate comparisons of historical and contemporary populations, produce baseline data before environmental changes, and elucidate patterns of change. Destructive sampling for DNA may be in disagreement with NHC goals of long-term care and maintenance. Differentiating quality among sample sources can direct destructive sampling to the source predicted to yield the highest quality DNA and most reliable data, potentially reducing damage to specimens, laboratory costs, and genotyping errors. We used the kit fox (Vulpes macrotis) as a model species and evaluated the quality and reliability of genetic data obtained from carnivoran specimens via three different sample sources: cranial bones, nasal bones, and toepads. We quantified variation in microsatellite amplification success and genotyping error rates and assessed the reliability of source-specific genic data. Toepads had the highest amplification success rates and lowest genotyping error rates. Shorter loci had higher amplification success and lower allelic dropout rates than longer loci. There were substantial differences in the reliability of resulting multilocus genotypes. Toepads produced the most reliable data, required the fewest replicates, and therefore, had the lowest costs to achieve reliable data. Our results demonstrate that the quality of DNA obtained from specimens varies by sample source and can inform NHCs when evaluating requests for destructive sampling. Our results suggest that prior to large-scale specimen sampling, researchers should conduct pilot studies to differentiate among source-specific data reliability, identify high performing loci, reduce costs of analyses, and minimize destructive sampling.

Investigating fine particulate matter sources in Salt Lake City during persistent cold air pool events

During wintertime, Salt Lake City experiences periods of high-pressure atmospheric stagnation that leads to prolonged periods with stable atmospheric boundary layers (ABL) due to the unique orography of the region. These atmospheric conditions typically lead to persistent cold air pool (PCAP) events, where the stable ABL remains over several days, degrading air quality in the Salt Lake Valley. In this work, we applied novel source apportionment methods to identify sources that were the greatest contributors to elevated secondary PM2.5 concentrations during PCAP events in winter 2007. A source-oriented modeling approach that relies on emissions inventory data (i.e., source-specific data) was utilized for source characterization. A correction was applied to chemical transport model (CTM) outputs to improve the estimates of source contributions to secondary PM2.5 components (organic carbon, nitrate, sulfate, and ammonium). As a result, gasoline vehicles (25%), natural gas combustion (21%), and other sources (29%) were identified as the largest sources of nitrate, which was the dominant aerosol component during the PCAP periods ([NO3−]max = 37.5 μg m−3). Further, receptor-oriented source apportionment modeling was conducted using the chemical mass balance method with gas constraints (CMB-GC) with location-specific, mathematically optimized PM2.5 source profiles to examine the multi-year trend in PCAP pollution. These optimized profiles were enhanced by integrating the initial guess profiles with CTM results and observations. CMB-GC was applied for the period 2007–2015 at an urban monitor, and the use of seasonally varying optimized source profiles improved results by resolving more mass than when using static source profiles, increasing the predicted-observed PM2.5 mass ratio from 0.91 to 1.03. The averaged biomass burning impacts exhibited the most significant change, increasing from an average of 0.85 to 1.87 μg m−3 when using the static profiles and the optimized profiles, respectively. The static and optimized CMB-GC results were similar for secondary components but differed slightly for mobile impacts. Stratification of PCAP vs. non-PCAP CMB-GC source impacts revealed that the dominant sources of PM2.5 varied under the two meteorological conditions.

Urban link travel time estimation using traffic states‐based data fusion

Estimated travel time is a key input for many intelligent transport systems (ITS) applications and traffic management functions. There are numerous studies that show that fusing data from different sources such as global positioning system (GPS), Bluetooth, mobile phone network (MPN), and inductive loop detector (ILD) can result in more accurate travel time estimation. However, to date, there has been little research investigating the contribution of individual data sources to the quality of the final estimate or how this varies according to source-specific data quality under different traffic states. Here, three different data sources, namely bus-based GPS (bGPS) data, ILD data, and MPN data, of varying quality are combined using three different data fusion techniques of varying complexity. In order to quantify the accuracy of travel time estimation, travel time calculated using automatic number plate recognition (ANPR) data are used as the `ground truth'. The final results indicate that fusing multiple data together does not necessarily enhance the accuracy of travel time estimation. The results also show that even in dense urban areas, bGPS data, when combined with ILD data, can provide reasonable travel time estimates of general traffic stream under different traffic states.

Odor Control Scrubber System Planning and Design with Limited Source Specific Data

Odor Control Scrubber System Planning and Design with Limited Source Specific Data

A Bayesian approach to the global estimation of maternal mortality

The maternal mortality ratio (MMR) is defined as the number of maternal deaths in a population per 100,000 live births. Country-specific MMR estimates are published on a regular basis by the United Nations Maternal Mortality Estimation Inter-agency Group (UN MMEIG) to track progress in reducing maternal deaths and were used to evaluate regional and national performance related to Millennium Development Goal (MDG) 5, which called for a 75% reduction in the MMR between 1990 and 2015. Until 2014, the UN MMEIG used a multilevel regression model for producing estimates for countries without sufficient data from vital registration systems. While this model worked well in the past to assess MMR levels for countries with limited data, it was deemed unsatisfactory for final MDG 5 reporting for countries where longer time series of observations had become available because, by construction, estimated trends in the MMR were covariate-driven only and did not necessarily track data-driven trends. We developed a Bayesian maternal mortality estimation model, which extends upon the UN MMEIG multilevel regression model. The new model assesses data-driven trends through the inclusion of an ARIMA time series model that captures accelerations and decelerations in the rate of change in the MMR. Varying reporting and data quality issues are accounted for in source-specific data models. The revised model provides data-driven estimates of MMR levels and trends and was used for MDG 5 reporting for all countries.

KaBOB: ontology-based semantic integration of biomedical databases.

BackgroundThe ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources.ResultsWe present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license.ConclusionsKaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0559-3) contains supplementary material, which is available to authorized users.

Model-Based Multiple Pitch Tracking Using Factorial HMMs: Model Adaptation and Inference

Robustness against noise and interfering audio signals is one of the challenges in speech recognition and audio analysis technology. One avenue to approach this challenge is single-channel multiple-source modeling. Factorial hidden Markov models (FHMMs) are capable of modeling acoustic scenes with multiple sources interacting over time. While these models reach good performance on specific tasks, there are still serious limitations restricting the applicability in many domains. In this paper, we generalize these models and enhance their applicability. In particular, we develop an EM-like iterative adaptation framework which is capable to adapt the model parameters to the specific situation (e.g. actual speakers, gain, acoustic channel, etc.) using only speech mixture data. Currently, source-specific data is required to learn the model. Inference in FHMMs is an essential ingredient for adaptation. We develop efficient approaches based on observation likelihood pruning. Both adaptation and efficient inference are empirically evaluated for the task of multipitch tracking using the GRID corpus.

High performance multi-track recording system for automotive applications

This paper describes a framework used to develop and run automotive applications both on board of vehicles and in laboratory. It includes the recording system designed and implemented in the GOLD framework. The system can record data from different sensors, such as cameras, laserscanners, radars, GPS, IMU, IO boards. The system can easily be expanded adding new device drivers. An in-RAM prerecording functionality is available to let the user record events started in the past. An index file collects essential information on each recorded event, such as timestamp, source identifier, and other sourcespecific data. Different file formats can be used to store data on disks; standard file formats are available for images and audio, small data such as CAN messages or GPS data are recorded directly into the index file. In order to have a faster lookup of a particular scene, the system is also equipped with a user interface that allows to insert tags during the recording. This system has been under development and successfully employed in the last 15 years to acquiring data for several VisLab projects. The description of two case studies is included in this paper. BRAiVE is an advanced prototype used as mobile laboratory to acquire data for different purposes. VIAC is a trip from Parma, Italy, to Shanghai, China, performed to test the robustness of VisLab driving assistance systems; the autonomous driving sessions have been recorded generating a unique database suitable to study and possibly improve the algorithm performance.

Using ‘new’ data sources for ‘old’ newspaper research: Developing guidelines for data collection

Abstract This article discusses the benefits and limitations of collecting electronic data for large-scale thematic content analysis. We will discuss a number of methodological and technical issues. The first one is the construction of a list of relevant keywords that serves as the primary data collecting device. This is not only a technical necessity, but also secures a theoretically and empirically valid collection of data. The second concern is the quality of electronic archive information. Finally, source-specific data characteristics and coding difficulties are dealt with. In conclusion, seven guidelines for electronic data collecting are proposed.

Thyroid Function and Perchlorate in Drinking Water: An Evaluation among California Newborns, 1998

Perchlorate (ClO4−) has been detected in groundwater sources in numerous communities in California and other parts of the United States, raising concerns about potential impacts on health. For California communities where ClO4− was tested in 1997 and 1998, we evaluated the prevalence of primary congenital hypothyroidism (PCH) and high thyroid-stimulating hormone (TSH) levels among the 342,257 California newborns screened in 1998. We compared thyroid function results among newborns from 24 communities with average ClO4− concentrations in drinking water > 5 μg/L (n = 50,326) to newborns from 287 communities with average concentrations ≤5 μg/L (n = 291,931). ClO4− concentrations obtained from the California Drinking Water Program provided source-specific data for estimating weighted average concentrations in community water. Fifteen cases of PCH from communities with average concentration > 5 μg/L were observed, with 20.4 expected [adjusted prevalence odds ratio (POR) = 0.71; 95% confidence interval (CI), 0.40–1.19]. Although only 36% of all California newborns were screened before 24 hr of age in 1998, nearly 80% of newborns with high TSH were screened before 24 hr of age. Because of the physiologic postnatal surge of TSH, the results for newborns screened before 24 hr were uninformative for assessing an environmental impact. For newborns screened ≥24 hr, the adjusted POR for high TSH was 0.73 (95% CI, 0.40–1.23). All adjusted odds ratios (ORs) were controlled for sex, ethnicity, birth weight, and multiple birth status. Using an assessment of ClO4− in drinking water based on available data, we did not observe an association between estimated average ClO4− concentrations > 5 μg/L in drinking water supplies and the prevalence of clinically diagnosed PCH or high TSH concentrations.

SELECTIVE OIL SPILL COMBAT PLANNING FOR OFFSHORE EXPLORATION AND PRODUCTION OPERATIONS IN THE NORTH SEA

ABSTRACT Experience shows that during emergencies (Ekofisk, Amoco Cadiz) considerable differences of opinion can arise concerning the best combat-action to be taken, in spite of existing approved contingency plans. In this paper, a case is made for an improvement of the decision-making during emergencies through selective contingency planning for offshore operations. In such selective contingency planning, a spill from a specific (potential) source and its impact on a stretch of coastline are being interconnected and analysed. This will involve consideration of source-specific data (such as location, oil-composition, flow-rates, and temperatures), together with such items as estimates of the fate and movement of that oil across the intermediate stretch of sea, seasonal conditions, pollution risks in terms of oil arrival times and amounts, and coastal vulnerability In consultation between government and industry, a scenario for action tailored to that situation then can be decided in advance, both for combat at the spill location and for coastal protection. The paper is illustrated with evidence from the Ekofisk blow-out case, and with the estimated pollution hazard for the Dutch Wad-denzee from an oil blow-out in the central North Sea area.