Using Business Intelligence to Improve DBA Productivity

The amount of data collected and used by companies has grown rapidly in size over the last decade. Business leaders are now using Business Intelligence (BI) systems to make effective business decisions against large amounts of data. The growth in the size of data has been a major challenge for Database Administrators (DBAs). The increase in the number and size of databases at the speed they have grown has made it difficult for DBA teams to provide the same level of service that the business requires they provide. The methods that DBAs have used in the last several decades can no longer be performed with the efficiency needed over all of the databases they administer. This paper presents the first BI system to improve DBA productivity and providing important data metrics for Information Technology (IT) managers. The BI system has been well received by Sherwin Williams Database Administrators. It has i) enabled the DBA team to quickly determine which databases needed work by a DBA without manually logging into the system; ii) helped the DBA team and its management to easily answer other business users' questions without using DBAs' time to research the issue; and iii) helped the DBA team to provide the business data for unanticipated audit request

Integrated modelling of Atlantic mackerel distribution patterns and movements : a template for dynamic impact assessments

The study was funded by Equinor (formerly Statoil).Modelling is important for impact assessments of anthropogenic pressures on wildlife. Models are particularly useful when dealing with complex dynamic systems (as pelagic ecosystems) where data are limited and if various ‘what if’ scenarios should be tested. The aim of this study was to produce and implement an integrated modelling approach, linking high resolution hydrodynamic models (HDM) of the marine environment with correlative species distribution models (SDM) and agent-based models (ABM), for describing the spatio-temporal distribution and movements of Atlantic mackerel (Scomber scombrus) in the Norwegian Sea. The SDM was fitted with scientific mackerel trawl data as response variables (collected in July and August 2006–2014) and temperature (from the HDM), water depth and time period as predictors of spatial distributions. The SDM was able to produce dynamic predictions of a similar order of magnitude as observed catch per unit effort (CPUE) as well as realistic large-scale distribution patterns, when tested on independent data (not included in the modelling). The ABM was calibrated, with normalized SDM predictions (habitat suitability as a proxy for food availability) and hydrodynamics as input and simulated on a single year (2013) for the period May–October, when the migratory mackerel is present in the study area. A pattern-oriented modelling (POM) approach was used to verify if the model reproduced multiple observed real-world patterns. The ABM produced similar patterns as observed regarding migration timing, growth and large scale geographic distribution. Fine scaled information on mackerel movement and behaviour is limited, which is also reflected in the results. More data and knowledge are therefore required to improve the patterns emerging from fine scaled processes. The potential of the model for assessing an impact of a single seismic survey (mimicking a real survey) was finally evaluated. The exercise allowed estimating the number of affected fish (within 50 km from the sound source) and potential changes in local migrations, with the specific assumed minimum sound pressure thresholds (resulting in a fleeing reaction by the mackerel) set to 165 dB re 1 μPa. The model framework was shown to be useful by allowing simulations of impact scenarios in a realistic and dynamic environment. The model can be further updated when data on fine scale movements of mackerel and most importantly when improved data on response behaviour to impacts of sound become available.PostprintPeer reviewe

Suicides among Danish cancer patients 1971–1999

Compared to the general population, the suicide risk among Danish cancer patients diagnosed in 1971–1986 was increased by 50% for men and 30% for women. We updated the earlier study to evaluate both long-term and recent trends in the suicide risk. Cancer patients with a first cancer diagnosed between 1971 and 1999 in Denmark were followed-up for completed suicide through 1999. Excluding nonmelanoma skin cancer, 564 508 cancer patients were included and 1241 suicides observed. Both the standardised mortality ratio (SMR) of suicide relative to the general population and the suicide rates were analysed with Poisson regression methods. The overall SMR was increased to 1.7 (95% CI. 1.6–1.9) for men and 1.4 (95% CI: 1.3–1.5) for women. Following the cancer diagnosis, the suicide risk was highest in the first 3 months for men and between months 3 and 12 for women. The risk was higher for nonlocalised cancer and for cancers with perceived poor prognosis. Breast cancer patients had a higher risk than other cancer patients with similar good prognosis. The suicide rates among cancer patients decreased with calendar time, but less so than the rates in the general population. The suicide risk among cancer patients has not decreased as much as in the Danish population and reasons for this should be explored. Breast cancer might be believed by patients to be more life threatening than it is. Assessment and treatment of depression could improve the quality of life for cancer patients who suffer from unrecognised depressions and in turn reduce the risk of suicide in cancer patients

Skeletal Adaptation to Intramedullary Pressure-Induced Interstitial Fluid Flow Is Enhanced in Mice Subjected to Targeted Osteocyte Ablation

Interstitial fluid flow (IFF) is a potent regulatory signal in bone. During mechanical loading, IFF is generated through two distinct mechanisms that result in spatially distinct flow profiles: poroelastic interactions within the lacunar-canalicular system, and intramedullary pressurization. While the former generates IFF primarily within the lacunar-canalicular network, the latter generates significant flow at the endosteal surface as well as within the tissue. This gives rise to the intriguing possibility that loading-induced IFF may differentially activate osteocytes or surface-residing cells depending on the generating mechanism, and that sensation of IFF generated via intramedullary pressurization may be mediated by a non-osteocytic bone cell population. To begin to explore this possibility, we used the Dmp1-HBEGF inducible osteocyte ablation mouse model and a microfluidic system for modulating intramedullary pressure (ImP) to assess whether structural adaptation to ImP-driven IFF is altered by partial osteocyte depletion. Canalicular convective velocities during pressurization were estimated through the use of fluorescence recovery after photobleaching and computational modeling. Following osteocyte ablation, transgenic mice exhibited severe losses in bone structure and altered responses to hindlimb suspension in a compartment-specific manner. In pressure-loaded limbs, transgenic mice displayed similar or significantly enhanced structural adaptation to Imp-driven IFF, particularly in the trabecular compartment, despite up to ∼50% of trabecular lacunae being uninhabited following ablation. Interestingly, regression analysis revealed relative gains in bone structure in pressure-loaded limbs were correlated with reductions in bone structure in unpressurized control limbs, suggesting that adaptation to ImP-driven IFF was potentiated by increases in osteoclastic activity and/or reductions in osteoblastic activity incurred independently of pressure loading. Collectively, these studies indicate that structural adaptation to ImP-driven IFF can proceed unimpeded following a significant depletion in osteocytes, consistent with the potential existence of a non-osteocytic bone cell population that senses ImP-driven IFF independently and potentially parallel to osteocytic sensation of poroelasticity-derived IFF

Accelerating root system phenotyping of seedlings through a computer-assisted processing pipeline

Background: There are numerous systems and techniques to measure the growth of plant roots. However, phenotyping large numbers of plant roots for breeding and genetic analyses remains challenging. One major difficulty is to achieve high throughput and resolution at a reasonable cost per plant sample. Here we describe a cost-effective root phenotyping pipeline, on which we perform time and accuracy benchmarking to identify bottlenecks in such pipelines and strategies for their acceleration. Results: Our root phenotyping pipeline was assembled with custom software and low cost material and equipment. Results show that sample preparation and handling of samples during screening are the most time consuming task in root phenotyping. Algorithms can be used to speed up the extraction of root traits from image data, but when applied to large numbers of images, there is a trade-off between time of processing the data and errors contained in the database. Conclusions: Scaling-up root phenotyping to large numbers of genotypes will require not only automation of sample preparation and sample handling, but also efficient algorithms for error detection for more reliable replacement of manual interventions

Efficient 3D Medical Image Segmentation Algorithm over a Secured Multimedia Network

Image segmentation has proved its importance and plays an important role in various domains such as health systems and satellite-oriented military applications. In this context, accuracy, image quality, and execution time deem to be the major issues to always consider. Although many techniques have been applied, and their experimental results have shown appealing achievements for 2D images in real-time environments, however, there is a lack of works about 3D image segmentation despite its importance in improving segmentation accuracy. Specifically, HMM was used in this domain. However, it suffers from the time complexity, which was updated using different accelerators. As it is important to have efficient 3D image segmentation, we propose in this paper a novel system for partitioning the 3D segmentation process across several distributed machines. The concepts behind distributed multimedia network segmentation were employed to accelerate the segmentation computational time of training Hidden Markov Model (HMMs). Furthermore, a secure transmission has been considered in this distributed environment and various bidirectional multimedia security algorithms have been applied. The contribution of this work lies in providing an efficient and secure algorithm for 3D image segmentation. Through a number of extensive experiments, it was proved that our proposed system is of comparable efficiency to the state of art methods in terms of segmentation accuracy, security and execution time

Rad51 Inhibits Translocation Formation by Non-Conservative Homologous Recombination in Saccharomyces cerevisiae

Chromosomal translocations are a primary biological response to ionizing radiation (IR) exposure, and are likely to result from the inappropriate repair of the DNA double-strand breaks (DSBs) that are created. An abundance of repetitive sequences in eukaryotic genomes provides ample opportunity for such breaks to be repaired by homologous recombination (HR) between non-allelic repeats. Interestingly, in the budding yeast, Saccharomyces cerevisiae the central strand exchange protein, Rad51 that is required for DSB repair by gene conversion between unlinked repeats that conserves genomic structure also suppresses translocation formation by several HR mechanisms. In particular, Rad51 suppresses translocation formation by single-strand annealing (SSA), perhaps the most efficient mechanism for translocation formation by HR in both yeast and mammalian cells. Further, the enhanced translocation formation that emerges in the absence of Rad51 displays a distinct pattern of genetic control, suggesting that this occurs by a separate mechanism. Since hypomorphic mutations in RAD51 in mammalian cells also reduce DSB repair by conservative gene conversion and stimulate non-conservative repair by SSA, this mechanism may also operate in humans and, perhaps contribute to the genome instability that propels the development of cancer

Repurposing NGO data for better research outcomes: A scoping review of the use and secondary analysis of NGO data in health policy and systems research

Background Non-government organisations (NGOs) collect and generate vast amounts of potentially rich data, most of which are not used for research purposes. Secondary analysis of NGO data (their use and analysis in a study for which they were not originally collected) presents an important but largely unrealised opportunity to provide new research insights in critical areas including the evaluation of health policy and programmes. Methods A scoping review of the published literature was performed to identify the extent to which secondary analysis of NGO data has been used in health policy and systems research (HPSR). A tiered analytic approach provided a comprehensive overview and descriptive analyses of the studies which: 1) used data produced or collected by or about NGOs; 2) performed secondary analysis of the NGO data (beyond use of an NGO report as a supporting reference); 3) used NGO-collected clinical data. Results Of the 156 studies which performed secondary analysis of NGO-produced or collected data, 64% (n=100) used NGO-produced reports (e.g. to critique NGO activities and as a contextual reference) and 8% (n=13) analysed NGO-collected clinical data.. Of the studies, 55% investigated service delivery research topics, with 48% undertaken in developing countries and 17% in both developing and developed. NGO-collected clinical data enabled HPSR within marginalised groups (e.g. migrants, people in conflict-affected areas), with some limitations such as inconsistencies and missing data. Conclusion We found evidence that NGO-collected and produced data are most commonly perceived as a source of supporting evidence for HPSR and not as primary source data. However, these data can facilitate research in under-researched marginalised groups and in contexts that are hard to reach by academics, such as conflict-affected areas. NGO–academic collaboration could help address issues of NGO data quality to facilitate their more widespread use in research. Their use could enable relevant and timely research in the areas of health policy, programme evaluation and advocacy to improve health and reduce health inequalities, especially in marginalised groups and developing countries

Measurement of the W±Z boson pair-production cross section in pp collisions at √s=13TeV with the ATLAS detector

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