Automated legal sensemaking: the centrality of relevance and intentionality

Introduction: In a perfect world, discovery would ideally be conducted by the senior litigator who is responsible for developing and fully understanding all nuances of their client’s legal strategy. Of course today we must deal with the explosion of electronically stored information (ESI) that never is less than tens-of-thousands of documents in small cases and now increasingly involves multi-million-document populations for internal corporate investigations and litigations. Therefore scalable processes and technologies are required as a substitute for the authority’s judgment. The approaches taken have typically either substituted large teams of surrogate human reviewers using vastly simplified issue coding reference materials or employed increasingly sophisticated computational resources with little focus on quality metrics to insure retrieval consistent with the legal goal. What is required is a system (people, process, and technology) that replicates and automates the senior litigator’s human judgment. In this paper we utilize 15 years of sensemaking research to establish the minimum acceptable basis for conducting a document review that meets the needs of a legal proceeding. There is no substitute for a rigorous characterization of the explicit and tacit goals of the senior litigator. Once a process has been established for capturing the authority’s relevance criteria, we argue that literal translation of requirements into technical specifications does not properly account for the activities or states-of-affairs of interest. Having only a data warehouse of written records, it is also necessary to discover the intentions of actors involved in textual communications. We present quantitative results for a process and technology approach that automates effective legal sensemaking

Using microbiological data to improve the use of antibiotics for respiratory tract infections: a protocol for an individual patient data meta-analysis

Background Resistance to antibiotics is rising and threatens future antibiotic effectiveness. ‘Antibiotic targeting’ ensures patients who may benefit from antibiotics receive them, while being safely withheld from those who may not. Point-of-care tests may assist with antibiotic targeting by allowing primary care clinicians to establish if symptomatic patients have a viral, bacterial, combined, or no infection. However, because organisms can be harmlessly carried, it is important to know if the presence of the virus/bacteria is related to the illness for which the patient is being assessed. One way to do this is to look for associations with more severe/prolonged symptoms and test results. Previous research to answer this question for acute respiratory tract infections has given conflicting results with studies has not having enough participants to provide statistical confidence. Aim To undertake a synthesis of IPD from both randomised controlled trials (RCTs) and observational cohort studies of respiratory tract infections (RTI) in order to investigate the prognostic value of microbiological data in addition to, or instead of, clinical symptoms and signs. Methods A systematic search of Cochrane Central Register of Controlled Trials, Ovid Medline and Ovid Embase will be carried out for studies of acute respiratory infection in primary care settings. The outcomes of interest are duration of disease, severity of disease, repeated consultation with new/worsening illness and complications requiring hospitalisation. Authors of eligible studies will be contacted to provide anonymised individual participant data. The data will be harmonised and aggregated. Multilevel regression analysis will be conducted to determine key outcome measures for different potential pathogens and whether these offer any additional information on prognosis beyond clinical symptoms and signs. Trial registration PROSPERO Registration number: CRD42023376769

Numerical Simulations of Gravity Waves Imaged Over Arecibo During the 10-Day January 1993 Campaign

Recently, measurements were made of mesospheric gravity waves in the OI (5577 Å) nightglow observed from Arecibo, Puerto Rico, during January 1993 as part of a special 10-day campaign. Clear, monochromatic gravity waves were observed on several nights. By using a full-wave model that realistically includes the major physical processes in this region, we have simulated the propagation of two waves through the mesopause region and calculated the O(1 S) nightglow response to the waves. Mean winds derived from both UARS wind imaging interferometer (WINDII) and Arecibo incoherent scatter radar observations were employed in the computations as were the climatological zonal winds defined by COSPAR International Reference Atmosphere 1990 (CIRA). For both sets of measured winds the observed waves encounter critical levels within the O(1 S) emission layer, and wave amplitudes, derived from the requirement that the simulated and observed amplitudes of the O(1 S) fluctuations be equal, are too large for the waves to be gravitationally stable below the emission layer. Some of the model coefficients were adjusted in order to improve the agreement with the measurements, including the eddy diffusion coefficients and the height of the atomic oxygen layer. The effect of changing the chemical kinetic parameters was investigated but was found to be unimportant. Eddy diffusion coefficients that are 10 to 100 times larger than presently accepted values are required to explain most of the observations in the cases that include the measured background winds, whereas the observations can be modeled using the nominal eddy diffusion coefficients and the CIRA climatological winds. Lowering the height of the atomic oxygen layer improved the simulations slightly for one of the simulated waves but caused a less favorable simulation for the other wave. For one of the waves propagating through the WINDII winds the simulated amplitude was too large below 82 km for the wave to be gravitationally stable, in spite of the adjustments made to the model parameters. This study demonstrates that an accurate description of the mean winds is an essential requirement for a complete interpretation of observed wave-driven airglow fluctuations

Thinking outside the channel : modeling nitrogen cycling in networked river ecosystems

Author Posting. © Ecological Society of America, 2011. This article is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Frontiers in Ecology and the Environment 9 (2011): 229–238, doi:10.1890/080211.Agricultural and urban development alters nitrogen and other biogeochemical cycles in rivers worldwide. Because such biogeochemical processes cannot be measured empirically across whole river networks, simulation models are critical tools for understanding river-network biogeochemistry. However, limitations inherent in current models restrict our ability to simulate biogeochemical dynamics among diverse river networks. We illustrate these limitations using a river-network model to scale up in situ measures of nitrogen cycling in eight catchments spanning various geophysical and land-use conditions. Our model results provide evidence that catchment characteristics typically excluded from models may control river-network biogeochemistry. Based on our findings, we identify important components of a revised strategy for simulating biogeochemical dynamics in river networks, including approaches to modeling terrestrial–aquatic linkages, hydrologic exchanges between the channel, floodplain/riparian complex, and subsurface waters, and interactions between coupled biogeochemical cycles.This research was supported by NSF (DEB-0111410). Additional support was provided by NSF for BJP and SMT (DEB-0614301), for WMW (OCE-9726921 and DEB-0614282), for WHM and JDP (DEB-0620919), for SKH (DEB-0423627), and by the Gordon and Betty Moore Foundation for AMH, GCP, ESB, and JAS, and by an EPA Star Fellowship for AMH

Stream denitrification across biomes and its response to anthropogenic nitrate loading

Author Posting. © The Author(s), 2008. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in Nature 452 (2008): 202-205, doi:10.1038/nature06686.Worldwide, anthropogenic addition of bioavailable nitrogen (N) to the biosphere is increasing and terrestrial ecosystems are becoming increasingly N saturated, causing more bioavailable N to enter groundwater and surface waters. Large-scale N budgets show that an average of about 20-25% of the N added to the biosphere is exported from rivers to the ocean or inland basins, indicating substantial sinks for N must exist in the landscape. Streams and rivers may be important sinks for bioavailable N owing to their hydrologic connections with terrestrial systems, high rates of biological activity, and streambed sediment environments that favor microbial denitrification. Here, using data from 15N tracer experiments replicated across 72 streams and 8 regions representing several biomes, we show that total biotic uptake and denitrification of nitrate increase with stream nitrate concentration, but that the efficiency of biotic uptake and denitrification declines as concentration increases, reducing the proportion of instream nitrate that is removed from transport. Total uptake of nitrate was related to ecosystem photosynthesis and denitrification was related to ecosystem respiration. Additionally, we use a stream network model to demonstrate that excess nitrate in streams elicits a disproportionate increase in the fraction of nitrate that is exported to receiving waters and reduces the relative role of small versus large streams as nitrate sinks.Funding for this research was provided by the National Science Foundation

Using microbiological data to improve the use of antibiotics for respiratory tract infections: A protocol for an individual patient data meta-analysis

Background Resistance to antibiotics is rising and threatens future antibiotic effectiveness. ‘Antibiotic targeting’ ensures patients who may benefit from antibiotics receive them, while being safely withheld from those who may not. Point-of-care tests may assist with antibiotic targeting by allowing primary care clinicians to establish if symptomatic patients have a viral, bacterial, combined, or no infection. However, because organisms can be harmlessly carried, it is important to know if the presence of the virus/bacteria is related to the illness for which the patient is being assessed. One way to do this is to look for associations with more severe/ prolonged symptoms and test results. Previous research to answer this question for acute respiratory tract infections has given conflicting results with studies has not having enough participants to provide statistical confidence. Aim To undertake a synthesis of IPD from both randomised controlled trials (RCTs) and observational cohort studies of respiratory tract infections (RTI) in order to investigate the prognostic value of microbiological data in addition to, or instead of, clinical symptoms and signs. Methods A systematic search of Cochrane Central Register of Controlled Trials, Ovid Medline and Ovid Embase will be carried out for studies of acute respiratory infection in primary care settings. The outcomes of interest are duration of disease, severity of disease, repeated consultation with new/worsening illness and complications requiring hospitalisation. Authors of eligible studies will be contacted to provide anonymised individual participant data. The data will be harmonised and aggregated. Multilevel regression analysis will be conducted to determine key outcome measures for different potential pathogens and whether these offer any additional information on prognosis beyond clinical symptoms and signs

Using microbiological data to improve the use of antibiotics for respiratory tract infections: A protocol for an individual patient data meta-analysis

Background: Resistance to antibiotics is rising and threatens future antibiotic effectiveness. ‘Antibiotic targeting’ ensures patients who may benefit from antibiotics receive them, while being safely withheld from those who may not. Point-of-care tests may assist with antibiotic targeting by allowing primary care clinicians to establish if symptomatic patients have a viral, bacterial, combined, or no infection. However, because organisms can be harmlessly carried, it is important to know if the presence of the virus/bacteria is related to the illness for which the patient is being assessed. One way to do this is to look for associations with more severe/prolonged symptoms and test results. Previous research to answer this question for acute respiratory tract infections has given conflicting results with studies has not having enough participants to provide statistical confidence. Aim: To undertake a synthesis of IPD from both randomised controlled trials (RCTs) and observational cohort studies of respiratory tract infections (RTI) in order to investigate the prognostic value of microbiological data in addition to, or instead of, clinical symptoms and signs. Methods: A systematic search of Cochrane Central Register of Controlled Trials, Ovid Medline and Ovid Embase will be carried out for studies of acute respiratory infection in primary care settings. The outcomes of interest are duration of disease, severity of disease, repeated consultation with new/worsening illness and complications requiring hospitalisation. Authors of eligible studies will be contacted to provide anonymised individual participant data. The data will be harmonised and aggregated. Multilevel regression analysis will be conducted to determine key outcome measures for different potential pathogens and whether these offer any additional information on prognosis beyond clinical symptoms and signs. Trial registration: PROSPERO Registration number: CRD42023376769

Using microbiological data to improve the use of antibiotics for respiratory tract infections: A protocol for an individual patient data meta-analysis

Background Resistance to antibiotics is rising and threatens future antibiotic effectiveness. ‘Antibiotic targeting’ ensures patients who may benefit from antibiotics receive them, while being safely withheld from those who may not. Point-of-care tests may assist with antibiotic targeting by allowing primary care clinicians to establish if symptomatic patients have a viral, bacterial, combined, or no infection. However, because organisms can be harmlessly carried, it is important to know if the presence of the virus/bacteria is related to the illness for which the patient is being assessed. One way to do this is to look for associations with more severe/prolonged symptoms and test results. Previous research to answer this question for acute respiratory tract infections has given conflicting results with studies has not having enough participants to provide statistical confidence. Aim To undertake a synthesis of IPD from both randomised controlled trials (RCTs) and observational cohort studies of respiratory tract infections (RTI) in order to investigate the prognostic value of microbiological data in addition to, or instead of, clinical symptoms and signs. Methods A systematic search of Cochrane Central Register of Controlled Trials, Ovid Medline and Ovid Embase will be carried out for studies of acute respiratory infection in primary care settings. The outcomes of interest are duration of disease, severity of disease, repeated consultation with new/worsening illness and complications requiring hospitalisation. Authors of eligible studies will be contacted to provide anonymised individual participant data. The data will be harmonised and aggregated. Multilevel regression analysis will be conducted to determine key outcome measures for different potential pathogens and whether these offer any additional information on prognosis beyond clinical symptoms and signs. Trial registration PROSPERO Registration number: CRD42023376769

Respiratory microbiota resistance and resilience to pulmonary exacerbation and subsequent antimicrobial intervention

© 2016 International Society for Microbial Ecology All rights reserved. Pulmonary symptoms in cystic fibrosis (CF) begin in early life with chronic lung infections and concomitant airway inflammation leading to progressive loss of lung function. Gradual pulmonary function decline is interspersed with periods of acute worsening of respiratory symptoms known as CF pulmonary exacerbations (CFPEs). Cumulatively, CFPEs are associated with more rapid disease progression. In this study multiple sputum samples were collected from adult CF patients over the course of CFPEs to better understand how changes in microbiota are associated with CFPE onset and management. Data were divided into five clinical periods: pre-CFPE baseline, CFPE, antibiotic treatment, recovery, and post-CFPE baseline. Samples were treated with propidium monoazide prior to DNA extraction, to remove the impact of bacterial cell death artefacts following antibiotic treatment, and then characterised by 16S rRNA gene-targeted high-throughput sequencing. Partitioning CF microbiota into core and rare groups revealed compositional resistance to CFPE and resilience to antibiotics interventions. Mixed effects modelling of core microbiota members revealed no significant negative impact on the relative abundance of Pseudomonas aeruginosa across the exacerbation cycle. Our findings have implications for current CFPE management strategies, supporting reassessment of existing antimicrobial treatment regimens, as antimicrobial resistance by pathogens and other members of the microbiota may be significant contributing factors