EPSRC Data Management Plan Assessment Rubric v2.0

This rubric is intended to assist in the assessment of EPSRC data management plans, against the criteria required by the funder. It is not intended to be used as a template for researchers to follow when writing a data management plan. The rubric has been divided into 'performance criteria' (on the left hand side) which cover the information the funder expects to be covered by the data management plan. Each performance criteria is followed by three descriptions of how it might be addressed, each indicating a different level of response. The descriptions are intended as examples of how the performance criteria might be addressed and are not considered to be exhaustive. The rubric also lists the documents and resources on which it was based

The Android Smartphone as an Inexpensive Sentry Ground Sensor

Proc. SPIE Conf. on Unattended Ground, Sea, and Air Sensor Technologies and Applications XIV, Baltimore, MD, April 2012A key challenge of sentry and monitoring duties is detection of approaching people in areas of little human traffic. We are exploring smartphones as easily available, easily portable, and less expensive alternatives to traditional military sensors for this task, where the sensors are already integrated into the package. We developed an application program for the Android smartphone that uses its sensors to detect people passing nearby; it takes their pictures for subsequent transmission to a central monitoring station. We experimented with the microphone, light sensor, vibration sensor, proximity sensor, orientation sensor, and magnetic sensor of the Android. We got best results with the microphone (looking for footsteps) and light sensor (looking for abrupt changes in light), and sometimes good results with the vibration sensor. We ran a variety of tests with subjects walking at various distances from the phone under different environmental conditions to measure limits on acceptable detection. We got best results by combining average loudness over a 200 millisecond period with a brightness threshold adjusted to the background brightness, and we set our phones to trigger pictures no more than twice a second. Subjects needed to be within ten feet of the phone for reliable triggering, and some surfaces gave poorer results. We primarily tested using the Motorola Atrix 4G (Android 2.3.4) and HTC Evo 4G (Android 2.3.3) and found only a few differences in performance running the same program, which we attribute to differences in the hardware. We also tested two older Android phones that had problems with crashing when running our program. Our results provide good guidance for when and where to use this approach to inexpensive sensing

Making Sense of Email Addresses on Drives

Drives found during investigations often have useful information in the form of email addresses, which can be acquired by search in the raw drive data independent of the file system. Using these data, we can build a picture of the social networks in which a drive owner participated, even perhaps better than investigating their online profiles maintained by social-networking services, because drives contain much data that users have not approved for public display. However, many addresses found on drives are not forensically interesting, such as sales and support links. We developed a program to filter these out using a Naïve Bayes classifier and eliminated 73.3% of the addresses from a representative corpus. We show that the byte-offset proximity of the remaining addresses found on a drive, their word similarity, and their number of co-occurrences over a corpus are good measures of association of addresses, and we built graphs using this data of the interconnections both between addresses and between drives. Results provided several new insights into our test data

Patient-reported financial barriers to adherence to treatment in neurology

OBJECTIVE: Many effective medical therapies are available for treating neurological diseases, but these therapies tend to be expensive and adherence is critical to their effectiveness. We used patient-reported data to examine the frequency and determinants of financial barriers to medication adherence among individuals treated for neurological disorders. PATIENTS AND METHODS: Patients completed cross-sectional surveys on iPads as part of routine outpatient care in a neurology clinic. Survey responses from a 3-month period were collected and merged with administrative sources of demographic and clinical information (eg, insurance type). We explored the association between patient characteristics and patient-reported failure to refill prescription medication due to cost in the previous 12 months, termed here as "nonadherence". RESULTS: The population studied comprised 6075 adults who were presented between July and September 2015 for outpatient neurology appointments. The mean age of participants was 56 (standard deviation: 18) years, and 1613 (54%) were females. The patients who participated in the surveys (2992, 49%) were comparable to nonparticipants with respect to gender and ethnicity but more often identified English as their preferred language (94% vs 6%, p<0.01). Among respondents, 9.8% (n=265) reported nonadherence that varied by condition. These patients were more frequently Hispanic (16.7% vs 9.8% white, p=0.01), living alone (13.9% vs 8.9% cohabitating, p<0.01), and preferred a language other than English (15.3% vs 9.4%, p=0.02). CONCLUSION: Overall, the magnitude of financial barriers to medication adherence appears to vary across neurological conditions and demographic characteristics

Comparison of performance achievement award recognition with primary stroke center certification for acute ischemic stroke care.

BackgroundHospital certification and recognition programs represent 2 independent but commonly used systems to distinguish hospitals, yet they have not been directly compared. This study assessed acute ischemic stroke quality of care measure conformity by hospitals receiving Primary Stroke Center (PSC) certification and those receiving the American Heart Association's Get With The Guidelines-Stroke (GWTG-Stroke) Performance Achievement Award (PAA) recognition.Methods and resultsThe patient and hospital characteristics as well as performance/quality measures for acute ischemic stroke from 1356 hospitals participating in the GWTG-Stroke Program 2010-2012 were compared. Hospitals were classified as PAA+/PSC+ (hospitals n = 410, patients n = 169,302), PAA+/PSC- (n = 415, n = 129,454), PAA-/PSC+ (n = 88, n = 26,386), and PAA-/PSC- (n = 443, n = 75,565). A comprehensive set of stroke measures were compared with adjustment for patient and hospital characteristics. Patient characteristics were similar by PAA and PSC status but PAA-/PSC- hospitals were more likely to be smaller and nonteaching. Measure conformity was highest for PAA+/PSC+ and PAA+/PSC- hospitals, intermediate for PAA-/PSC+ hospitals, and lowest for PAA-/PSC- hospitals (all-or-none care measure 91.2%, 91.2%, 84.3%, and 76.9%, respectively). After adjustment for patient and hospital characteristics, PAA+/PSC+, PAA+/PSC-, and PAA-/PSC+ hospitals had 3.15 (95% CIs 2.86 to 3.47); 3.23 (2.93 to 3.56) and 1.72 (1.47 to 2.00), higher odds for providing all indicated stroke performance measures to patients compared with PAA-/PSC- hospitals.ConclusionsWhile both PSC certification and GWTG-Stroke PAA recognition identified hospitals providing higher conformity with care measures for patients hospitalized with acute ischemic stroke, PAA recognition was a more robust identifier of hospitals with better performance

Detecting explosive-device emplacement at multiple granularities

This paper appeared in the Proceedings of the Military Sensing Society (MSS) National Symposium, Las Vegas, Nevada, U.S., July 2010.We report on experiments with a nonimaging sensor network for detection of suspicious behavior related to pedestrian emplacement of IEDs. Emplacement is the time when detection is the most feasible for IEDs since it almost necessarily must involve some unusual behaviors. Sensors at particularly dangerous locations such as bridges, culverts, road narrowings, and road intersections could provide early warning of such activity. Imaging for surveillance has weaknesses in its susceptibility to occlusion, problems operating at night, sensitivity to angle of view, high processing requirements, and need to invade privacy. Our approach is to use a variety of nonimaging sensors with different modalities to track people. We particularly look for clues as to accelerations since these are often associated with suspicious behavior. Our approach involves preanalyzing terrain for the probability of emplacement of an IED, then combining this with real-time assessment of suspicious behavior obtained from probabilities of location derived from sensor data. We describe some experiments with a prototype sensor network and the promising results obtained.supported by the U.S. National Science Foundation under grant 0729696 of the EXP ProgramApproved for public release; distribution is unlimited

Sequoyah v. TVA, USDC Northern District of TN, Docket No. 3-79-418: TVA’s Brief in Support of Its Motion to Dismiss, or, for Summary Judgment, and in Opposition to Plaintiffs’’ Motion for restraining Order or Preliminary Injunction

Brief prepared by the Tennessee Valley Authority (TVA) in the suit brought by Native American groups seeking an injunction on the Tellico Project. The brief is followed by extensive appendices, including sections of TVA annual reports, and affidavits by John E. Linn, Title Attorney, Tennessee Valley Authority, Ross O. Swimmer, Principal Chief of the Cherokee Nation, and Edward H. Lessne, Director of the Division of Water Resources in the Office of Natural Resources of the Tennessee Valley Authority

Hospital Acquired Pneumonia Is Linked to Right Hemispheric Peri-Insular Stroke

Purpose Hospital acquired pneumonia (HAP) is a major complication of stroke. We sought to determine associations between infarction of specific brain regions and HAP. Methods: 215 consecutive acute stroke patients with HAP (2003–2009) were carefully matched with 215 non-pneumonia controls by gender, then NIHSS, then age. Admission imaging and binary masks of infarction were registered to MNI-152 space. Regional atlas and voxel-based log-odds were calculated to assess the relationship between infarct location and the likelihood of HAP. An independently validated penalized conditional logistic regression model was used to identify HAP associated imaging regions. Results: The HAP and control patients were well matched by gender (100%), age (95% within 5-years), NIHSS (98% within 1-point), infarct size, dysphagia, and six other clinical variables. Right hemispheric infarcts were more frequent in patients with HAP versus controls (43.3% vs. 34.0%, p = 0.054), whereas left hemispheric infarcts were more frequent in controls (56.7% vs. 44.7%, p = 0.012); there was no significant difference between groups in the rate of brainstem strokes (p = 1.0). Of the 10 most infarcted regions, only right insular cortex volume was different in HAP versus controls (20 vs. 12 ml, p = 0.02). In univariate analyses, the highest log-odds regions for pneumonia were right hemisphere, cerebellum, and brainstem. The best performing multivariate model selected 7 brain regions of infarction and 2 infarct volume-based variables independently associated with HAP. Conclusions: HAP is associated with right hemispheric peri-insular stroke. These associations may be related to autonomic modulation of immune mechanisms, supporting recent hypotheses of stroke mediated immune suppression

Relationship of national institutes of health stroke scale to 30-day mortality in medicare beneficiaries with acute ischemic stroke.

BackgroundThe National Institutes of Health Stroke Scale (NIHSS), a well-validated tool for assessing initial stroke severity, has previously been shown to be associated with mortality in acute ischemic stroke. However, the relationship, optimal categorization, and risk discrimination with the NIHSS for predicting 30-day mortality among Medicare beneficiaries with acute ischemic stroke has not been well studied.Methods and resultsWe analyzed data from 33102 fee-for-service Medicare beneficiaries treated at 404 Get With The Guidelines-Stroke hospitals between April 2003 and December 2006 with NIHSS documented. The 30-day mortality rate by NIHSS as a continuous variable and by risk-tree determined or prespecified categories were analyzed, with discrimination of risk quantified by the c-statistic. In this cohort, mean age was 79.0 years and 58% were female. The median NIHSS score was 5 (25th to 75th percentile 2 to 12). There were 4496 deaths in the first 30 days (13.6%). There was a strong graded relation between increasing NIHSS score and higher 30-day mortality. The 30-day mortality rates for acute ischemic stroke by NIHSS categories were as follows: 0 to 7, 4.2%; 8 to 13, 13.9%; 14 to 21, 31.6%; 22 to 42, 53.5%. A model with NIHSS alone provided excellent discrimination whether included as a continuous variable (c-statistic 0.82 [0.81 to 0.83]), 4 categories (c-statistic 0.80 [0.79 to 0.80]), or 3 categories (c-statistic 0.79 [0.78 to 0.79]).ConclusionsThe NIHSS provides substantial prognostic information regarding 30-day mortality risk in Medicare beneficiaries with acute ischemic stroke. This index of stroke severity is a very strong discriminator of mortality risk, even in the absence of other clinical information, whether used as a continuous or categorical risk determinant. (J Am Heart Assoc. 2012;1:42-50.)