Science.gov

Sample records for predicting nursing times

  1. Predicting Success in Nursing Programs

    ERIC Educational Resources Information Center

    Herrera, Cheryl; Blair, Jennifer

    2015-01-01

    As the U.S. population ages and policy changes emerge, such as the Patient Protection and Affordable Care Act of 2010, the U.S. will experience a significant shortage of Registered Nurses (RNs). Many colleges and universities are attempting to increase the size of nursing cohorts to respond to this imminent shortage. Notwithstanding a 2.6%…

  2. Dimensions of nurse work time: Progress in instrumentation.

    PubMed

    Jones, Terry L; Yoder, Linda H

    2015-09-01

    Because the work of health care is embedded in time, understanding nursing time-allocation practices is essential for identifying nurse staffing and workflow patterns that optimize healthcare cost and quality outcomes. The interdependent nature of nursing care requires that nurses share time with other members of their work group. Shared time, also known as social or organizational time, requires careful negotiation of workflows within healthcare teams. Evaluation of negotiated workflows is contingent upon valid and reliable measures of sociological nursing time. In this study, we evaluated the psychometric properties of a newly adapted instrument for measuring sociological nursing time and describe the experience of sociological time among hospital-employed nurses. Using a cross-sectional survey design with a convenience sample of nurses (n = 359), we identified nine reliable components of sociological nursing time: insufficient time allocation; strict adherence to schedules; increased time awareness; value of quality over speed; fast and unpredictable pace changes; predictable job duties punctuated with unpredictable job demands; expectations for a fast work pace; inconsistent work-hour expectations across departments; and high expectations for punctuality. PMID:25494873

  3. Predicting Success in Nursing Programs

    ERIC Educational Resources Information Center

    Crouch, Suzanne J.

    2015-01-01

    The purpose of this study was to assess the merit of the Watson-Glaser Critical Thinking Appraisal as a pre-admission criterion in conjunction with the frequently utilized admission criteria of the college prerequisite grade point average and the National League of Nursing pre-admission test. Data were collected from 192 first-year nursing…

  4. Mentoring new nurses in stressful times.

    PubMed

    Young, Lisa E

    2009-06-01

    Meeting benchmarks of Ontario's Wait Time Strategy and the expansion of The Ottawa Hospital are key issues driving the recruitment of perioperative nurses in Ottawa and Eastern Ontario. Added pressures resulting from Canada's aging population and a nationwide nursing shortage mean perioperative nurses are overworked and understaffed. Preceptoring new members of staff raises valid concerns as many of the new recruits have little or no operating room experience. The Dreyfus Model of Skill Acquisition demonstrates the importance of time and patience in supporting the learning process. Mentoring is a valuable strategy in an effort to teach and guide new nurses, to increase nursing retention, and to promote professional growth and recognition. Building successful mentorship programs, through the creation of healthy organizational cultures, transformational leadership and staff development programs, will strengthen support for nurses in stressful times. The stress of meeting the province-wide benchmarks outlined in Ontario's Wait Time Strategy and the expansion of perioperative services at The Ottawa Hospital in Ontario are two key issues driving the need for the recruitment of nurses into the specialty of perioperative nursing. As a result of Canada's aging population and a nationwide nursing shortage, perioperative nurses are over-worked and under-staffed while being faced with the pressure to preceptor new staff members while struggling to meet the daily demands of the wait list strategy. This article discusses current trends in healthcare and the career path changes being made by many nurses in response to the demand for specialty trained nurses. It is followed by a brief explanation of the Dreyfus Model of Skill Acquisition. Mentoring is presented as an effective strategy in the guidance and teaching of new nurses with a discussion of the benefits and suggestions on how to build a successful mentorship program to support nurses in these stressful times. PMID

  5. Predicting Nursing Human Resources: An Exploratory Study

    PubMed Central

    Squires, Allison; Beltrán-Sánchez, Hiram

    2010-01-01

    The nurse-to-population ratio (NPOP) is a standard indicator used to indicate a country’s health care human resources capacity for responding to its disease burden. This study sought to explore if socioeconomic development indicators could predict the NPOP in a country. Mexico served as the case example for this exploratory study, with the final five variables selected based on findings from a qualitative study analyzing the development of nursing human resources in the country. Multiple linear regression showed that two variables proved significant predictors of the NPOP and the model itself explained 70% of the variance (r2 = .7; p = .0000). The findings have multiple implications for nursing human resources policy in Mexico and at a global level as governments attempt to build human capital to respond to population health needs. PMID:19628510

  6. Curriculum Development for Part-Time Programs for Certified Nurse Assistant to Licensed Vocational Nurse; and Licensed Vocational Nurse to Associate Degree Nurse Program (CNA-VN-RN).

    ERIC Educational Resources Information Center

    Saxe, Ellen; And Others

    This report describes the Imperial Valley College nursing program, a program developed to provide for the nursing needs of Imperial County, California. The program provides part-time education to help train nursing assistants and to allow nursing assistants to upgrade their skills to vocational nurse level and vocational nurses to become…

  7. Crunch time for US nurses.

    PubMed

    Carlisle, Daloni

    Americans are preparing to vote in the presidential election. Nurses on both sides of the political divide explain why they are supporting President Obama, and his landmark healthcare reforms, or his Republican opponent Mitt Romney, who would scrap 'Obamacare' and reduce the role of government in health care. PMID:23189597

  8. Predictive spark timing method

    SciTech Connect

    Tang, D.L.; Chang, M.F.; Sultan, M.C.

    1990-01-09

    This patent describes a method of determining spark time in a spark timing system of an internal combustion engine having a plurality of cylinders and a spark period for each cylinder in which a spark occurs. It comprises: generating at least one crankshaft position reference pulse for each spark firing event, the reference pulse nearest the next spark being set to occur within a same cylinder event as the next spark; measuring at least two reference periods between recent reference pulses; calculating the spark timing synchronously with crankshaft position by performing the calculation upon receipt of the reference pulse nearest the next spark; predicting the engine speed for the next spark period from at least two reference periods including the most recent reference period; and based on the predicted speed, calculating a spark time measured from the the reference pulse nearest the next spark.

  9. First time issue of oral hormonal contraception by nurses.

    PubMed

    Presho, M; Leadbetter, C

    1999-10-01

    This study aimed to assess whether introducing the issue of first time oral hormonal contraception by nurses could expand the role of the family planning nurse and improve the service to the client group. Nurse acceptability of, and adherence to, the protocol were examined. Results indicate that with appropriate training the first time issue of oral hormonal contraception is a valuable skill in enhancing the nurses' role, reduces waiting time for clients and is acceptable to clients. PMID:10567062

  10. Grade Point Average as a Predictor of Timely Graduation from Associate Degree Registered Nursing Programs

    ERIC Educational Resources Information Center

    Jackson, Delores J.

    2010-01-01

    The purpose of this study was to determine if admission selection strategies that utilize cumulative and/or pre-requisite GPA are predictive of timely graduation for associate degree nursing (RN-AD) students. Data were obtained from de-identified records of 437 associate degree nursing students enrolled in three Midwest community colleges from…

  11. NAQ's 40th Birthday Nursing: Predictions From the Past; Predictions for the Future, Parts I & II.

    PubMed

    McClure, Margaret L; Batcheller, Joyce

    2016-01-01

    The following two articles relate to Nursing's past and future, described through a series of predictions made by one of Nursing's great leaders Margaret L. McClure (Maggie McClure). It is reprinted from NAQ Fall 2000, Volume 25, Issue 1. The second article, by another great leader, Joyce Batcheller, DNP, RN, NEA-BC, FAAN, is a follow up on those predictions, reflecting on Nursing today and tommorow. PMID:27584886

  12. Inability of Physicians and Nurses to Predict Patient Satisfaction in the Emergency Department

    PubMed Central

    DeLaney, Matthew C.; Page, David B.; Kunstadt, Ethan B.; Ragan, Matt; Rodgers, Joel; Wang, Henry E.

    2015-01-01

    Introduction Patient satisfaction is a commonly assessed dimension of emergency department (ED) care quality. The ability of ED clinicians to estimate patient satisfaction is unknown. We sought to evaluate the ability of emergency medicine resident physicians and nurses to predict patient-reported satisfaction with physician and nursing care, pain levels, and understanding of discharge instructions. Methods We studied a convenience sample of 100 patients treated at an urban academic ED. Patients rated satisfaction with nursing care, physician care, pain level at time of disposition and understanding of discharge instructions. Resident physicians and nurses estimated responses for each patient. We compared patient, physician and nursing responses using Cohen’s kappa, weighting the estimates to account for the ordinal responses. Results Overall, patients had a high degree of satisfaction with care provided by the nurses and physicians, although this was underestimated by providers. There was poor agreement between physician estimation of patient satisfaction (weighted κ=0.23, standard error: 0.078) and nursing estimates of patient satisfaction (weighted κ=0.11, standard error: 0.043); physician estimation of patient pain (weighted κ=0.43, standard error: 0.082) and nursing estimates (weighted κ=0.39, standard error: 0.081); physician estimates of patient comprehension of discharge instruction (weighted κ=0.19, standard error: 0.082) and nursing estimates (weighted κ=0.13, standard error: 0.078). Providers underestimated pain and patient comprehension of discharge instructions. Conclusion ED providers were not able to predict patient satisfaction with nurse or physician care, pain level, or understanding of discharge instructions. PMID:26759661

  13. 75 FR 80073 - Reasonable Break Time for Nursing Mothers

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-21

    ... Hour Division RIN 1235-ZA00 Reasonable Break Time for Nursing Mothers AGENCY: Wage and Hour Division... Standards Act (FLSA) that requires employers to provide reasonable break time and a place for nursing... are the Department's preliminary interpretations of the new break time amendment to the FLSA....

  14. What Nurses Do During Time Scarcity-and Why.

    PubMed

    Jones, Terry L

    2016-09-01

    Time scarcity is a common occurrence in the nurse work environment that stimulates a decision-making process, known as clinical prioritization or implicit rationing. In implicit rationing, nurses must decide what care they will complete and what they will leave unfinished. Five mechanisms that influence this process are supported in the literature. The effects of these influential mechanisms leave patients vulnerable to unmet educational, psychological, care coordination and discharge planning needs. Potential areas for intervention by nurse leaders include redesigning care delivery models to reduce time scarcity, adding balancing measures to performance monitoring systems to promote patient-centered care, and creating work cultures that support the values of nursing. PMID:27556653

  15. Predicting Success Using HESI A2 Entrance Tests in an Associate Degree Nursing Program

    ERIC Educational Resources Information Center

    Bodman, Susan

    2012-01-01

    A challenge presented to nurse educators is retention of nursing students. This has led nursing faculty to review admission requirements and question how well entrance tests predict success in Associate Degree Nursing Programs. The purpose of this study was to investigate the relationship between the HESI Admission Assessment Exam (HESI A2) and…

  16. Continuity of nursing and the time of sickness.

    PubMed

    Elstad, Ingunn; Torjuul, Kirsti

    2009-04-01

    This paper explores the relationship between temporal continuity in nursing and temporal features of sickness. It is based on phenomenological and hermeneutical philosophy, empirical studies of sickness time, and the nursing theories of Nightingale, of Benner and of Benner and Wrubel. In the first part, temporal continuity is defined as distinct from interpersonal continuity. Tensions between temporal continuity and discontinuity are discussed in the contexts of care management, of conceptualisations of disease and of time itself. Temporal limitations to the methodological concept of situation are discussed. The main part of this paper explores nurses' possibilities to relate to their patients' time, and how temporal features of sickness may warrant temporal continuity of nursing. Three temporal characteristics of sickness are discussed: the immediacy of patients' suffering, the basic continuity of life through sickness and health care, and the indeterminism and precariousness of sickness. The timing of nursing acts is discussed. The paper explores how sickness is both part of the continuity of life, and threatens this continuity. It concludes that this tension is implicitly recognised in the temporal continuity of nursing, which allows for discontinuous and continuous aspects of sickness time. Nurses accordingly perceive the sick person's time at several levels of temporality, and distinguish highly complex temporal processes in their patients' trajectory. Temporal continuity provides the time, flexibility, and closeness for nurses to perceive and act into time dimensions of individual sickness. The paper shows that temporal continuity of nursing is grounded in temporal characteristics of severe sickness. It suggests that temporal continuity is an important theoretical concept in nursing. PMID:19291197

  17. Normalized Elution Time Prediction Utility

    Energy Science and Technology Software Center (ESTSC)

    2011-02-17

    This program is used to compute the predicted normalized elution time (NET) for a list of peptide sequences. It includes the Kangas/Petritis neural network trained model, the Krokhin hydrophobicity model, and the Mant hydrophobicity model. In addition, it can compute the predicted strong cation exchange (SCX) fraction (on a 0 to 1 scale) in which a given peptide will appear.

  18. At Least 1 Full-Time Nurse Per School, Pediatric Group Recommends

    MedlinePlus

    ... At Least 1 Full-Time Nurse Per School, Pediatric Group Recommends Children's health needs are increasingly complex, ... time registered nurse, a new American Academy of Pediatrics (AAP) policy statement says. "School nursing is one ...

  19. Orientation, Evaluation, and Integration of Part-Time Nursing Faculty.

    PubMed

    Carlson, Joanne S

    2015-01-01

    This study helps to quantify and describe orientation, evaluation, and integration practices pertaining to part-time clinical nursing faculty teaching in prelicensure nursing education programs. A researcher designed Web-based survey was used to collect information from a convenience sample of part-time clinical nursing faculty teaching in prelicensure nursing programs. Survey questions focused on the amount and type of orientation, evaluation, and integration practices. Descriptive statistics were used to analyze results. Respondents reported on average four hours of orientation, with close to half reporting no more than two hours. Evaluative feedback was received much more often from students than from full-time faculty. Most respondents reported receiving some degree of mentoring and that it was easy to get help from full-time faculty. Respondents reported being most informed about student evaluation procedures, grading, and the steps to take when students are not meeting course objectives, and less informed about changes to ongoing curriculum and policy. PMID:26151905

  20. Nursing in war-time Guernsey: a preliminary review.

    PubMed

    Birchenall, P

    The research for this article was carried out in the Channel Island of Guernsey during 1996-97 and focuses on the remarkable resilience of a small group of nurses as they strove to provide an emergency hospital service to the civilian population of Guernsey between 1940 and 1945, during which time German forces were in occupation. Insights are provided into a unique period of nursing history, giving a flavour of the harsh environment in which care was provided. Hospital records at the time described a nurse as 'someone who earns her living nursing', therefore the title 'nurse' is used collectively to describe both the qualified State Registered Nurse and the unqualified junior staff. The article is part of an ongoing oral history project representing a collaborative venture between the Department of Health Studies at the University of Lincolnshire and Humberside, and the School of Healthcare Studies at the University of Leeds. Data for this study were obtained from a series of semi-structured audio-taped interviews with 13 former nurses who worked at the States of Guernsey Emergency Hospital during the occupation. Supporting data were derived from official archives, news reports and other published literature. The article is based on the author's inaugural lecture delivered at The University of Lincoln Campus, Friday 30 May 1997. PMID:9470659

  1. Post-Implementation Study of a Nursing e-Chart: How Nurses Use Their Time.

    PubMed

    Schachner, Bibiana; González, Zulma; Recondo, Francisco; Sommer, Janine; Luna, Daniel; García, Gabriela; Benítez, Sonia

    2016-01-01

    Nursing documentation is a significant component of electronic health records nevertheless integrating a new chart into nursing activities required multiples strategies to ensure adherence. Current literature demonstrates that nurses spend part of their time performing activities no related with patients' direct care and sometimes even does not fall under their purview. Thus it is important to quantify the effect that a new system could have in the proportion of time dedicated to documentation. The objective of this work was to determine the time dedicated to different activities including those related to electronic documentation after the implementation of a renewed nurse chart in an Electronic Health Record at Hospital Italiano de Buenos Aires. An observational, cross sectional and work sampling study was performed. During the study 2396 observations were made in 3 wards. Nurses' activities included 36.09% of direct care, 28.9% of indirect care, 0.67% support tasks, 22.99% non related to patient tasks, 11.32% personal activities and documenting on EHR 17.43%. The comparison with the previous study shows indirect care activities decreased 12.28% and non-related to patients increased 11.85%. The results demonstrate that the new nurses' e-chart did not increase documentation time. PMID:27577462

  2. Most Likely to Achieve: Predicting Early Success of the Practical Nurse Student

    ERIC Educational Resources Information Center

    Cline, April P.

    2013-01-01

    It is important that practical nurse (PN) educators be able to identify which students are likely to be successful in their programs. However, the majority of literature related to predicting success of nursing students has been done on baccalaureate nursing students in the university setting. This study sought to determine whether the same…

  3. Disaggregating Activities of Daily Living Limitations for Predicting Nursing Home Admission

    PubMed Central

    Fong, Joelle H; Mitchell, Olivia S; Koh, Benedict S K

    2015-01-01

    Objective To examine whether disaggregated activities of daily living (ADL) limitations better predict the risk of nursing home admission compared to conventionally used ADL disability counts. Data Sources We used panel data from the Health and Retirement Study (HRS) for years 1998–2010. The HRS is a nationally representative survey of adults older than 50 years (n = 18,801). Study Design We fitted Cox regressions in a continuous time survival model with age at first nursing home admission as the outcome. Time-varying ADL disability types were the key explanatory variables. Principal Findings Of the six ADL limitations, bathing difficulty emerged as the strongest predictor of subsequent nursing home placement across cohorts. Eating and dressing limitations were also influential in driving admissions among more recent cohorts. Using simple ADL counts for analysis yielded similar adjusted R2s; however, the amount of explained variance doubled when we allowed the ADL disability measures to time-vary rather than remain static. Conclusions Looking beyond simple ADL counts can provide health professionals insights into which specific disability types trigger long-term nursing home use. Functional disabilities measured closer in time carry more prognostic power than static measures. PMID:25256014

  4. Application of the Workload Indicators of Staffing Need method to predict nursing human resources at a Family Health Service.

    PubMed

    Bonfim, Daiana; Laus, Ana Maria; Leal, Ana Emilia; Fugulin, Fernanda Maria Togeiro; Gaidzinski, Raquel Rapone

    2016-01-01

    Objective verify the application of the Workload Indicators of Staffing Need method in the prediction of nursing human resources at a Family Health service. Method descriptive and quantitative study, undertaken at a Family Health service in the city of São Paulo. The set of sequential operations recommended in the Workload Indicators of Staffing Need method was used: definition of the professional category, type of health service and calculation of Available Work Time; definition of workload components; identification of mean time for workload components; dimensioning of staff needs based on the method, application and interpretation of the data. Result the workload proposed in the Workload Indicators of Staffing Need method to nursing technicians/auxiliary nurses was balanced with the number of professionals available at the Family Health service. The Workload Indicators of Staffing Need index amounted to 0.6 for nurses and 1.0 for nursing technicians/auxiliary nurses. Conclusion the application of the Workload Indicators of Staffing Need method was relevant to identify the components of the nursing professionals' workload. Therefore, it is recommendable as a nursing staffing tool at Family Health services, contributing to the access and universal health coverage. PMID:27143538

  5. Application of the Workload Indicators of Staffing Need method to predict nursing human resources at a Family Health Service

    PubMed Central

    Bonfim, Daiana; Laus, Ana Maria; Leal, Ana Emilia; Fugulin, Fernanda Maria Togeiro; Gaidzinski, Raquel Rapone

    2016-01-01

    Objective verify the application of the Workload Indicators of Staffing Need method in the prediction of nursing human resources at a Family Health service. Method descriptive and quantitative study, undertaken at a Family Health service in the city of São Paulo. The set of sequential operations recommended in the Workload Indicators of Staffing Need method was used: definition of the professional category, type of health service and calculation of Available Work Time; definition of workload components; identification of mean time for workload components; dimensioning of staff needs based on the method, application and interpretation of the data. Result the workload proposed in the Workload Indicators of Staffing Need method to nursing technicians/auxiliary nurses was balanced with the number of professionals available at the Family Health service. The Workload Indicators of Staffing Need index amounted to 0.6 for nurses and 1.0 for nursing technicians/auxiliary nurses. Conclusion the application of the Workload Indicators of Staffing Need method was relevant to identify the components of the nursing professionals' workload. Therefore, it is recommendable as a nursing staffing tool at Family Health services, contributing to the access and universal health coverage. PMID:27143538

  6. Nurse-Administered, Gut-Directed Hypnotherapy in IBS: Efficacy and Factors Predicting a Positive Response.

    PubMed

    Lövdahl, Jenny; Ringström, Gisela; Agerforz, Pia; Törnblom, Hans; Simrén, Magnus

    2015-07-01

    Hypnotherapy is an effective treatment in irritable bowel syndrome (IBS). It is often delivered by a psychotherapist and is costly and time consuming. Nurse-administered hypnotherapy could increase availability and reduce costs. In this study the authors evaluate the effectiveness of nurse-administered, gut-directed hypnotherapy and identify factors predicting treatment outcome. Eighty-five patients were included in the study. Participants received hypnotherapy by a nurse once/week for 12 weeks. Patients reported marked improvement in gastrointestinal (GI) and extra-colonic symptoms after treatment, as well as a reduction in GI-specific anxiety, general anxiety, and depression. Fifty-eight percent were responders after the 12 weeks treatment period, and of these 82% had a favorable clinical response already at week 6. Women were more likely than men to respond favorably to the treatment. Nurse-administered hypnotherapy is an effective treatment for IBS. Being female and reporting a favorable response to treatment by week 6 predicted a positive treatment response at the end of the 12 weeks treatment period. PMID:26046719

  7. [Measuring nursing care times--methodologic and documentation problems].

    PubMed

    Bartholomeyczik, S; Hunstein, D

    2001-08-01

    The time for needed nursing care is one important measurement as a basic for financing care. In Germany the Long Term Care Insurance (LTCI) reimburses nursing care depending on the time family care givers need to complete selected activities. The LTCI recommends certain time ranges for these activities, which are wholly compensatory, as a basic for assessment. The purpose is to enhance assessment justice and comparability. With the example of a German research project, which had to investigate the duration of these activities and the reasons for differences, questions are raised about some definition and interpretation problems. There are definition problems, since caring activities especially in private households are nearly never performed as clearly defined modules. Moreover, often different activities are performed simultaneously. However, the most important question is what exactly time numbers can say about the essentials of nursing care. PMID:12385262

  8. Can real time location system technology (RTLS) provide useful estimates of time use by nursing personnel?

    PubMed

    Jones, Terry L; Schlegel, Cara

    2014-02-01

    Accurate, precise, unbiased, reliable, and cost-effective estimates of nursing time use are needed to insure safe staffing levels. Direct observation of nurses is costly, and conventional surrogate measures have limitations. To test the potential of electronic capture of time and motion through real time location systems (RTLS), a pilot study was conducted to assess efficacy (method agreement) of RTLS time use; inter-rater reliability of RTLS time-use estimates; and associated costs. Method agreement was high (mean absolute difference = 28 seconds); inter-rater reliability was high (ICC = 0.81-0.95; mean absolute difference = 2 seconds); and costs for obtaining RTLS time-use estimates on a single nursing unit exceeded $25,000. Continued experimentation with RTLS to obtain time-use estimates for nursing staff is warranted. PMID:24338915

  9. The validity of ACT-PEP test scores for predicting academic performance of registered nurses in BSN programs.

    PubMed

    Yang, J C; Noble, J

    1990-01-01

    This study investigated the validity of three American College Testing-Proficiency Examination Program (ACT-PEP) tests (Maternal and Child Nursing, Psychiatric/Mental Health Nursing, Adult Nursing) for predicting the academic performance of registered nurses (RNs) enrolled in bachelor's degree BSN programs nationwide. This study also examined RN students' performance on the ACT-PEP tests by their demographic characteristics: student's age, sex, race, student status (full- or part-time), and employment status (full- or part-time). The total sample for the three tests comprised 2,600 students from eight institutions nationwide. The median correlation coefficients between the three ACT-PEP tests and the semester grade point averages ranged from .36 to .56. Median correlation coefficients increased over time, supporting the stability of ACT-PEP test scores for predicting academic performance over time. The relative importance of selected independent variables for predicting academic performance was also examined; the most important variable for predicting academic performance was typically the ACT-PEP test score. Across the institutions, student demographic characteristics did not contribute significantly to explaining academic performance, over and above ACT-PEP scores. PMID:2254527

  10. At Least 1 Full-Time Nurse Per School, Pediatric Group Recommends

    MedlinePlus

    ... gov/medlineplus/news/fullstory_158986.html At Least 1 Full-Time Nurse Per School, Pediatric Group Recommends ... HealthDay News) -- Every school should have at least one full-time registered nurse, a new American Academy ...

  11. Practice to Pedagogy: A Study of the Lived Experiences of Part-Time Nursing Faculty Transitioning from Expert Nurse to Novice Educator

    ERIC Educational Resources Information Center

    Testut, Tammy A.

    2013-01-01

    Part-time faculty in nursing programs are increasingly being hired as a supplement to the deteriorating pool of full-time nursing faculty. There is a growing need to fill the many vacant slots in nursing academe at the same time that there is substantial growth in prospective students inspiring to become nurses. While these "expert"…

  12. Predictive validity of the Nursing Severity Index in patients with musculoskeletal disease. Nurses of University Hospitals of Cleveland.

    PubMed

    Rosenthal, G E; Halloran, E J; Kiley, M; Landefeld, C S

    1995-02-01

    Prior studies have not examined the validity of severity of illness instruments in patients at low risk for mortality. We, therefore, examined the predictive validity of a newly developed instrument, the Nursing Severity Index in 5347 adult medical and surgical patients with musculoskeletal diagnoses admitted to an academic medical center in 1985-88. The Index is based on aggregating 34 clinical observations which were recorded by primary nurses during patient care; observations reflect biologic, functional, cognitive and psychosocial abnormalities. Other data, including patient demographic data and outcomes were obtained from hospital data bases. We found that, among all study patients, admission Nursing Severity Index scores were highly related (p < 0.001) to in-hospital death rates-which were 0, 0.4, 0.8, 2.6, 6.7 and 23.5% in six hierarchical strata defined by the Index-and to nursing home discharge rates. In multivariate analyses, adjusting for diagnosis and other important covariates, each strata was associated with a 2.5-fold increased risk of mortality and a 1.6-fold increased risk of nursing home discharge. In addition, the Nursing Severity Index was an independent predictor (p < 0.001) of hospital charges and length of stay. We conclude that the Nursing Severity Index assesses multiple dimensions of illness, can be easily recorded during routine patient care, and accurately predicts hospital outcomes in an important 'low risk' group of patients. The validity of the Nursing Severity Index in other clinical subgroups should be further studied. PMID:7869064

  13. Factors Predicting Nurse Educators' Acceptance and Use of Educational Technology in Classroom Instruction

    ERIC Educational Resources Information Center

    Cleveland, Sandra D.

    2014-01-01

    Nurse educators may express a willingness to use educational technology, but they may not have the belief or ability to carry out the technology use in the classroom. The following non-experimental, quantitative study examined factors that predict nurse educators' willingness to accept and use educational technology in the classroom. The sample…

  14. Enhancing Nursing Staffing Forecasting With Safety Stock Over Lead Time Modeling.

    PubMed

    McNair, Douglas S

    2015-01-01

    In balancing competing priorities, it is essential that nursing staffing provide enough nurses to safely and effectively care for the patients. Mathematical models to predict optimal "safety stocks" have been routine in supply chain management for many years but have up to now not been applied in nursing workforce management. There are various aspects that exhibit similarities between the 2 disciplines, such as an evolving demand forecast according to acuity and the fact that provisioning "stock" to meet demand in a future period has nonzero variable lead time. Under assumptions about the forecasts (eg, the demand process is well fit as an autoregressive process) and about the labor supply process (≥1 shifts' lead time), we show that safety stock over lead time for such systems is effectively equivalent to the corresponding well-studied problem for systems with stationary demand bounds and base stock policies. Hence, we can apply existing models from supply chain analytics to find the optimal safety levels of nurse staffing. We use a case study with real data to demonstrate that there are significant benefits from the inclusion of the forecast process when determining the optimal safety stocks. PMID:26340239

  15. Undergraduate Nurse Variables that Predict Academic Achievement and Clinical Competence in Nursing

    ERIC Educational Resources Information Center

    Blackman, Ian; Hall, Margaret; Darmawan, I Gusti Ngurah.

    2007-01-01

    A hypothetical model was formulated to explore factors that influenced academic and clinical achievement for undergraduate nursing students. Sixteen latent variables were considered including the students' background, gender, type of first language, age, their previous successes with their undergraduate nursing studies and status given for…

  16. Perceptions of Teaching Effectiveness of Part-Time and Full-Time Clinical Nursing Faculty of BSN Education

    ERIC Educational Resources Information Center

    DeSantis, Kimberly L.

    2012-01-01

    The United States faces a critical shortage of full-time registered nurses, which is . directly affected by the shortage of nurse educators. Many schools of nursing are already seeing the impact as qualified program applicants are being turned away due to the lack of qualified educators available to teach them. The trend has become to employ…

  17. Expansion tube test time predictions

    NASA Technical Reports Server (NTRS)

    Gourlay, Christopher M.

    1988-01-01

    The interaction of an interface between two gases and strong expansion is investigated and the effect on flow in an expansion tube is examined. Two mechanisms for the unsteady Pitot-pressure fluctuations found in the test section of an expansion tube are proposed. The first mechanism depends on the Rayleigh-Taylor instability of the driver-test gas interface in the presence of a strong expansion. The second mechanism depends on the reflection of the strong expansion from the interface. Predictions compare favorably with experimental results. The theory is expected to be independent of the absolute values of the initial expansion tube filling pressures.

  18. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... registered nurse. 57.313 Section 57.313 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN... nurse. (a) For loans made after November 18, 1971, and before September 29, 1979. A person who: (1... in full-time employment as a registered nurse (including teaching in any of the fields of...

  19. Predictive values and other quality criteria of the German version of the Nurse-Work Instability Scale (Nurse-WIS) – follow-up survey findings of a prospective study of a cohort of geriatric care workers

    PubMed Central

    2014-01-01

    Background Until now there has been a lack of effective screening instruments for health care workers at risk. To counteract the forecast shortage for health care workers, the offer of early interventions to maintain their work ability will become a central concern. The Nurse-Work Instability Scale (Nurse-WIS) seems to be suitable as a screening instrument and therefore a prospective study of a cohort of nursing staff from nursing homes was undertaken to validate the Nurse-Work Instability Scale (Nurse-WIS). Methods The follow-up data was used to test the sensitivity, specificity and the predictive values of the Nurse-WIS. The participants answered a questionnaire in the baseline investigation (T1) and in a follow-up 12 month after baseline. The hypothesis was that geriatric care workers with an increased risk according to the Nurse-WIS in T1 would be more likely to have taken long-term sick leave or drawn a pension for reduced work capacity in T2. Results 396 persons took part in T1 (21.3% response), 225 in T2 (42.3% loss-to-follow-up). In T1, 28.4% indicated an increased risk according to the Nurse-WIS. In T2, 10.2% had taken long-term sick leave or had drawn a pension for reduced work capacity. The sensitivity is 73.9% (95%-CI 55.7%–92.3%), the specificity is 76.7% (95%-CI 71.2%–82.8%). The ROC AUC indicated a moderate precision for the scale, at 0.74 (95%-CI 0.64–0.84). The PPV of the Nurse-WIS is 26.6%, and the NPV is 96.3%. For those with an increased risk according to the Nurse-WIS, the probability in T2 of long-term sick leave or a pension for reduced work capacity is around eight times higher (OR 8.3, 95%-CI 2.90–23.07). Persons who had indicated a long-term sick leave or made an application for a pension for reduced work capacity in T1 had a 17 times higher risk (OR 17.4, 95%-CI 3.34–90.55). Conclusion The German version of the Nurse-WIS appears to be a valid instrument with satisfactory predictive capabilities for recording an impending long

  20. Partnership Negotiations: Innovation for Nurse Contract Negotiations During Turbulent Times.

    PubMed

    Cullen, Maryalice; Donahue, Moreen

    2016-01-01

    Health care delivery is undergoing rapid change, with frontline nurses at the epicenter. A mind-set requiring innovative collaboration, creativity, flexibility, and openness to new care delivery models is necessary. This article describes an innovative approach to modern world contract negotiations in a 371-bed university-affiliated hospital. The nurses' contract negotiations were scheduled to begin 6 months after a layoff affected nurses and other caregivers. Concurrently, a strike was underway at a hospital in the state with the same union. Contentious negotiations were anticipated. Strategies employed to prepare for negotiations included consultation with a nurse expert, and an agreement between the chief nursing officer and chairman of the Shared Governance Committee to conduct negotiations that would allow for more dialogue between the staff nurse and nursing leadership teams. Sessions opened with a video address by a major health care nurse thought leader who provided an overview of the current health care landscape and future direction of nursing. Joint presentations by staff nurses and nurse leaders on topics of interest were conducted. "Nurses for Nurses" round table sessions took place each day, and valuable work was completed at breakout sessions. Ultimately, the partnership negotiations resulted in a successfully negotiated contract. PMID:26636232

  1. A mixed methods exploration of the team and organizational factors that may predict new graduate nurse engagement in collaborative practice.

    PubMed

    Pfaff, Kathryn A; Baxter, Pamela E; Ploeg, Jenny; Jack, Susan M

    2014-03-01

    Although engagement in collaborative practice is reported to support the role transition and retention of new graduate (NG) nurses, it is not known how to promote collaborative practice among these nurses. This mixed methods study explored the team and organizational factors that may predict NG nurse engagement in collaborative practice. A total of 514 NG nurses from Ontario, Canada completed the Collaborative Practice Assessment Tool. Sixteen NG nurses participated in follow-up interviews. The team and organizational predictors of NG engagement in collaborative practice were as follows: satisfaction with the team (β = 0.278; p = 0.000), number of team strategies (β = 0.338; p = 0.000), participation in a mentorship or preceptorship experience (β = 0.137; p = 0.000), accessibility of manager (β = 0.123; p = 0.001), and accessibility and proximity of educator or professional practice leader (β = 0.126; p = 0.001 and β = 0.121; p = 0.002, respectively). Qualitative analysis revealed the team facilitators to be respect, team support and face-to-face interprofessional interactions. Organizational facilitators included supportive leadership, participation in a preceptorship or mentorship experience and time. Interventions designed to facilitate NG engagement in collaborative practice should consider these factors. PMID:24195680

  2. Teacher time spent on student health issues and school nurse presence.

    PubMed

    Hill, Nina Jean; Hollis, Marianne

    2012-06-01

    Elementary school teacher time spent on student health issues and the relationship to school nurse services was the focus of this 2-year study. A cross-sectional design was used to survey traditional and exceptional (special needs) classroom teachers about the time they spent on health issues and their perception of school nurse presence. The school nurses were surveyed regarding the impact of their presence on early releases due to illness. Study findings related to teacher perceptions indicate with school nurse presence there are fewer early releases, increased communication, less time spent on health issues, students with chronic illnesses are safer, and there is a resource available for health information. The data provide the groundwork for discussions to improve the communication of the nurses' schedules, increase teacher confidence in consistent nurse hours at their school and aid the nurse in protecting valuable on-site school hours from other interferences or commitments. PMID:22140140

  3. The Statistical Predictability of the Academic Performance of Registered Nursing Students at Macomb. Project No. 0141-77.

    ERIC Educational Resources Information Center

    Stankovich, Mary Jo

    A study was conducted at Macomb County Community College to determine whether there was a significant relationship between grades earned in individual nursing courses and the scores earned on corresponding subsets of the state board exam for nursing graduates and also whether a nursing student's success could be predicted from admissions…

  4. Leisure-Time Activities in Selected Nursing Homes.

    ERIC Educational Resources Information Center

    Tague, Jean Ruth

    This study sought to identify leisure interests and participation patterns of residents over 65 in selected nursing homes in Los Angeles County, California, together with general and professional beliefs of nursing home administrators and authorities on aging as to leisure activities for aged nursing home patients. Interviews were held with 107…

  5. Predicting Nursing Facility Transition Candidates Using AID: A Case Study

    ERIC Educational Resources Information Center

    James, Mary L.; Wiley, Elizabeth; Fries, Brant E.

    2007-01-01

    Purpose: Although the nursing facility transition literature is growing, little research has analyzed the characteristics of individuals so assisted or compared participants to those who remain institutionalized. This article describes an analytic method that researchers can apply to address these knowledge gaps, using the Arkansas Passages…

  6. Predictive factors for the Nursing Diagnoses in people living with Acquired Immune Deficiency Syndrome 1

    PubMed Central

    da Silva, Richardson Augusto Rosendo; Costa, Romanniny Hévillyn Silva; Nelson, Ana Raquel Cortês; Duarte, Fernando Hiago da Silva; Prado, Nanete Caroline da Costa; Rodrigues, Eduardo Henrique Fagundes

    2016-01-01

    Abstract Objective: to identify the predictive factors for the nursing diagnoses in people living with Acquired Immune Deficiency Syndrome. Method: a cross-sectional study, undertaken with 113 people living with AIDS. The data were collected using an interview script and physical examination. Logistic regression was used for the data analysis, considering a level of significance of 10%. Results: the predictive factors identified were: for the nursing diagnosis of knowledge deficit-inadequate following of instructions and verbalization of the problem; for the nursing diagnosis of failure to adhere - years of study, behavior indicative of failure to adhere, participation in the treatment and forgetfulness; for the nursing diagnosis of sexual dysfunction - family income, reduced frequency of sexual practice, perceived deficit in sexual desire, perceived limitations imposed by the disease and altered body function. Conclusion: the predictive factors for these nursing diagnoses involved sociodemographic and clinical characteristics, defining characteristics, and related factors, which must be taken into consideration during the assistance provided by the nurse. PMID:27384466

  7. Nurses' Assessment of Rehabilitation Potential and Prediction of Functional Status at Discharge from Inpatient Rehabilitation

    ERIC Educational Resources Information Center

    Myers, Jamie S.; Grigsby, Jim; Teel, Cynthia S.; Kramer, Andrew M.

    2009-01-01

    The goals of this study were to evaluate the accuracy of nurses' predictions of rehabilitation potential in older adults admitted to inpatient rehabilitation facilities and to ascertain whether the addition of a measure of executive cognitive function would enhance predictive accuracy. Secondary analysis was performed on prospective data collected…

  8. Application of Predictive Nursing Reduces Psychiatric Complications in ICU Patients after Neurosurgery

    PubMed Central

    LIU, Qiong; ZHU, Hui

    2016-01-01

    Background: Our aim was to investigate the effects of clinical application of perioperative predictive nursing on reducing psychiatric complications in Intensive Care Unit (ICU) patients after neurosurgery. Methods: A total of 129 patients who underwent neurosurgery and received intensive care were enrolled in our study from February 2013 to February 2014. These patients were divided into two groups: the experimental group (n=68) receiving predictive nursing before and after operation, and the control group (n=61) with general nursing. Clinical data including length of ICU stay, duration of the patients’ psychiatric symptoms, form and incidence of adverse events, and patient satisfaction ratings were recorded, and their differences between the two groups were analyzed. Results: The duration of psychiatric symptoms and the length of ICU stay for patients in the experimental group were significantly shorter than those in the control group (P<0.05). The incidence of adverse events and psychiatric symptoms, such as sensory and intuition disturbance, thought disturbance, emotional disorder, and consciousness disorder, in the experimental group was significantly lower than that in the control group (P<0.05). Patient satisfaction ratings were significantly higher in the experimental group than those in the control group (P<0.05). Conclusion: Application of predictive nursing on ICU patients who undergo neurosurgery could effectively reduce the incidence of psychiatric symptoms as well as other adverse events. Our study provided clinical evidences to encourage predictive nursing in routine settings for patients in critical conditions. PMID:27252916

  9. Uncertainties in container failure time predictions

    SciTech Connect

    Williford, R.E.

    1990-01-01

    Stochastic variations in the local chemical environment of a geologic waste repository can cause corresponding variations in container corrosion rates and failure times, and thus in radionuclide release rates. This paper addresses how well the future variations in repository chemistries must be known in order to predict container failure times that are bounded by a finite time period within the repository lifetime. Preliminary results indicate that a 5000 year scatter in predicted container failure times requires that repository chemistries be known to within {plus minus}10% over the repository lifetime. These are small uncertainties compared to current estimates. 9 refs., 3 figs.

  10. Implicit prejudice toward injecting drug users predicts intentions to change jobs among drug and alcohol nurses.

    PubMed

    von Hippel, William; Brener, Loren; von Hippel, Courtney

    2008-01-01

    The meaning and importance of implicit prejudice is a source of considerable debate. One way to advance this debate is to assess whether implicit prejudice can predict independent variance, beyond that predicted by explicit prejudice, in meaningful and unambiguous behaviors or behavioral intentions. In the current research, drug and alcohol nurses reported their level of stress working with injecting drug users, their job satisfaction, their explicit prejudice toward injecting drug users, and their intentions to leave drug and alcohol nursing. The nurses also completed the Single Category Implicit Association Test, which measured their implicit prejudice toward injecting drug users. Analyses revealed that implicit prejudice was a significant mediator, beyond explicit prejudice and job satisfaction, of the relation between job stress and intention to change jobs. PMID:18181783

  11. Teacher Time Spent on Student Health Issues and School Nurse Presence

    ERIC Educational Resources Information Center

    Hill, Nina Jean; Hollis, Marianne

    2012-01-01

    Elementary school teacher time spent on student health issues and the relationship to school nurse services was the focus of this 2-year study. A cross-sectional design was used to survey traditional and exceptional (special needs) classroom teachers about the time they spent on health issues and their perception of school nurse presence. The…

  12. Effect of Time Management Program on Job Satisfaction for Head Nurses

    ERIC Educational Resources Information Center

    Elsabahy, Hanan ELsayed; Sleem, Wafaa Fathi; El Atroush, Hala Gaber

    2015-01-01

    Background: Time management and job satisfaction all related to each other and greatly affect success of organization. Subjects and Methods: The study aimed to evaluate the efficacy of a designed program of time management on job satisfaction for head nurses. A Quasi-experimental design was used for a total number of head nurses participated. Two…

  13. Improving predictions by cross pollination in time

    NASA Astrophysics Data System (ADS)

    Schevenhoven, Francine; Selten, Frank

    2016-04-01

    Given a set of imperfect weather models, one could ask how these models can be combined in order to improve weather predictions produced with these models. In this study we explore a technique called cross-pollination in time (CPT, Smith 2001). In the CPT approach the models exchange states during the prediction. The number of possible predictions grows quickly with time and a strategy to retain only a small number of predictions, called pruning, needs to be developed. In the learning phase a pruning strategy is proposed based on retaining those solutions that remain closest to the truth. From the learning phase probabilities are derived that determine weights to be applied to the imperfect models in the forecast phase. The CPT technique is explored using low-order dynamical systems and applied to a global atmospheric model. First results indicate that the CPT approach improves the forecast quality over the individual models.

  14. Nursing students' time management, reducing stress and gaining satisfaction: a grounded theory study.

    PubMed

    Mirzaei, Tayebeh; Oskouie, Fatemeh; Rafii, Forough

    2012-03-01

    In the course of their studies, nursing students must learn many skills and acquire the knowledge required for their future profession. This study investigates how Iranian nursing students manage their time according to the circumstances and obstacles of their academic field. Research was conducted using the grounded theory method. Twenty-one nursing students were purposefully chosen as participants. Data was collected through semi-structured interviews and analyzed using the method suggested by Corbin and Strauss. One of the three processes that the nursing students used was "unidirectional time management." This pattern consists of accepting the nursing field, overcoming uncertainty, assessing conditions, feeling stress, and trying to reduce stress and create satisfaction. It was found that students allotted most of their time to academic tasks in an attempt to overcome their stress. The findings of this study indicate the need for these students to have time for the extra-curricular activities and responsibilities that are appropriate to their age. PMID:22293018

  15. Applying Theory of Planned Behavior in Predicting of Patient Safety Behaviors of Nurses

    PubMed Central

    Javadi, Marzieh; Kadkhodaee, Maryam; Yaghoubi, Maryam; Maroufi, Maryam; Shams, Asadollah

    2013-01-01

    Background: Patient safety has become a major concern throughout the world. It is the absence of preventable harm to a patient during the process of health care, ensuring safer care is an enormous challenge, psychosocial variables influences behaviors of human. The theory of planned behavior (TPB) is a well-validated behavioral decision-making model that has been used to predict social and health behaviors. This study is aimed to investigate predictors of nurse’s patient safety intentions and behavior, using a TPB framework. Methods: Stratified sampling technique was used to choose 124 nurses who worked at the selected hospitals of Isfahan in 2011. Study tool was a questionnaire, designed by researchers team including 3 nurses a physician and a psychologist based on guideline of TPB model. Questionnaire Validity was confirmed by experts and its reliability was assessed by Cronbach’s alpha as 0.87. Binary logistic regression analysis was performed to evaluate how well each TPB variables predicted the variance in patient safety behavior. Analyzing was done by SPSS18. Results: Finding revealed that “normative beliefs” had the greatest influence on nurses intention to implement patient safety behaviors. Analyzing data by hospital types and workplace wards showed that both in public and private hospitals normative beliefs has affected safety behaviors of nurses more than other variables. Also in surgical wards, nurses behaviors have been affected by “control beliefs” and in medical wards by normative beliefs. Conclusion: Normative beliefs, and subjective norms were the most influential factor of safety behavior of nurses in this study. Considering the role of cultural context in these issues, it seemseducation of managers and top individuals about patient safety and its importance is a priority also control believes were another important predicting factor of behavior in surgical wards and intensive care units. Regarding the complexity of work in these

  16. Predicting river travel time from hydraulic characteristics

    USGS Publications Warehouse

    Jobson, H.E.

    2001-01-01

    Predicting the effect of a pollutant spill on downstream water quality is primarily dependent on the water velocity, longitudinal mixing, and chemical/physical reactions. Of these, velocity is the most important and difficult to predict. This paper provides guidance on extrapolating travel-time information from one within bank discharge to another. In many cases, a time series of discharge (such as provided by a U.S. Geological Survey stream gauge) will provide an excellent basis for this extrapolation. Otherwise, the accuracy of a travel time extrapolation based on a resistance equation can be greatly improved by assuming the total flow area is composed of two parts, an active and an inactive area. For 60 reaches of 12 rivers with slopes greater than about 0.0002, travel times could be predicted to within about 10% by computing the active flow area using the Manning equation with n = 0.035 and assuming a constant inactive area for each reach. The predicted travel times were not very sensitive to the assumed values of bed slope or channel width.

  17. Teachers' Perceptions of Full- and Part-Time Nurses at School

    ERIC Educational Resources Information Center

    Biag, Manuelito; Srivastava, Ashini; Landau, Melinda; Rodriguez, Eunice

    2015-01-01

    Teachers and school nurses partner together to help ensure students stay healthy and engaged in school. The purpose of this study is to generate a deeper understanding of teachers' perceptions on the benefits and challenges of working with full- or part-time school nurses. We conducted a qualitative analysis of open-ended survey responses from 129…

  18. Time standards of nursing in Primary Health Care: an observational study.

    PubMed

    Bonfim, Daiana; Fugulin, Fernanda Maria Togeiro; Laus, Ana Maria; Peduzzi, Marina; Gaidzinski, Raquel Rapone

    2016-02-01

    OBJECTIVE To determine time standards for interventions and activities conducted by nursing professionals in Family Health Units (FHU) in Brazil to substantiate the calculation of work force. METHOD This was an observational study carried out in 27 FHU, in 12 municipalities in 10 states, in 2013. In each unit, nursing professionals were observed every 10 minutes, for eight work hours, on five consecutive days via the work sampling technique. RESULTS A total of 32,613 observations were made, involving 47 nurses and 93 nursing technicians/assistants. Appointments were the main intervention carried out by nurses, with a mean time of 25.3 minutes, followed by record-keeping, which corresponded to 9.7%. On average, nursing technicians/assistants spent 6.3% of their time keeping records and 30.6 intervention minutes on immunization/vaccination control. CONCLUSION The study resulted in standard times of interventions carried out by the FHU nursing team, which can underpin the determination of nursing staff size and human resource policies. Furthermore, the study showed the panorama of interventions currently employed, allowing for the work process to be reviewed and optimized. PMID:27007429

  19. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... 42 Public Health 1 2012-10-01 2012-10-01 false Loan cancellation for full-time employment as a registered nurse. 57.313 Section 57.313 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN SERVICES GRANTS GRANTS FOR CONSTRUCTION OF TEACHING FACILITIES, EDUCATIONAL IMPROVEMENTS, SCHOLARSHIPS AND STUDENT LOANS Nursing Student Loans...

  20. School Nurse Practitioners: Analysis of Questionnaire and Time/Motion Data.

    ERIC Educational Resources Information Center

    Dungy, Claibourne I.; Mullins, Ruth G.

    1981-01-01

    A study was done to determine how school nurse practitioners apply skills learned in training programs to their daily activities and to provide a greater understanding of their relationship to consulting physicians. Results indicate that the nurses' perceptions provide useful data on time allocation but do not give a good estimate of patient care…

  1. Nursing and en route care: history in time of war.

    PubMed

    Davis, R Scott; Connelly, Linda K

    2011-01-01

    The mission of the en route caregiver is to provide critical care in military helicopters for wounded Warriors. This care minimizes the effects of the wounds and injuries, and improves morbidity and mortality. This article will focus on the history of Army Nursing en route care. From World War II through Vietnam, and continuing through the War on Terrorism in Iraq and Afghanistan, Army nurses served in providing en route care in military airplanes and helicopters for patients being transported to higher echelons of care. From aid stations on the battlefield to forward surgical teams which provide life, limb, and eyesight saving care, to the next higher level of care in combat support hospitals, these missions require specialized nursing skills to safely care for the high acuity patients. Before the en route care concept existed, there was not a program to train nurses in these critical skills. There was also a void of information about patient outcomes associated with the nursing assessment and care provided during helicopter medical evacuation (MEDEVAC) of such unstable patients, and the consequent impact on the patient's condition after transport. The role of critical care nurses has proven to be essential and irreplaceable in providing full-spectrum care to casualties of war, in particular, the postsurgical patients transferred from one surgical facility to another in theatre. However, we have only recently developed the concepts over the required skill set, training, equipment, functionality, evidenced-based care, and sustainability of nursing in the en route care role. Much of the work to quantify and qualify nursing care has been done by individuals and individual units whose lessons-learned have only recently been captured. PMID:22124872

  2. [Nurses in the first times of World War one].

    PubMed

    Marc, Bernard

    2002-01-01

    The First World War originated in new and huge problems for both military authorities and military health service. The modern war which begun in 1914 overflowed this Service reformed in 1912. Famous journalists and political men such as Barrès and Clémenceau took part against dramatic conditions encountered by wounded soldiers. The First World War saw the introduction of many new technologies to the art of killing one's enemy among them the machine gun and the heavy use of artillery. It resulted in massive amount of wounded and ill soldiers which overflowed the military health service and every evacuation mean to the rear front. From August 2nd, 1914 to December 31st, 1914, 798. 833 French wounded soldiers and 322.672 ill soldiers were treated by the French Army 7th direction, in charge of the military health service. In such circumstances, a voluntary, parallel and the efficient sanitary organisation took an importance unknown until yet. This organisation, the Red Cross, associated the Société française de secours aux blessés militaires (French society for help to the wounded soldiers), the Union des Femmes de France (French Women Union) and the Association des Dames françaises (French Ladies Association). These three organisations, associated to many religious ones, brought a real sanitary structure so necessary in the troubled period as the beginning of the First World War. Everywhere in France, health service structures such as the hôpital temporaire no. 103 (Temporary Hospital number 103) in Paris, model hospital from the Union des Femmes de France, associated volunteers civilian doctors and surgeons. To increase the professional value of the paramedical staffs, a very specific effort was done for the formation of nurses in number, as correctly and as quickly as possible. During the first year of the First World War, nurses will be estimated since they had been able by their action to balance the disorder of the very first time of the conflict. PMID

  3. Time prediction model of subway transfer.

    PubMed

    Zhou, Yuyang; Yao, Lin; Gong, Yi; Chen, Yanyan

    2016-01-01

    Walking time prediction aims to deduce waiting time and travel time for passengers and provide a quantitative basis for the subway schedule management. This model is founded based on transfer passenger flow and type of pedestrian facilities. Chaoyangmen station in Beijing was taken as the learning set to obtain the relationship between transfer walking speed and passenger volume. The sectional passenger volume of different facilities was calculated related to the transfer passage classification. Model parameters were computed by curve fitting with respect to various pedestrian facilities. The testing set contained four transfer stations with large passenger volume. It is validated that the established model is effective and practical. The proposed model offers a real-time prediction method with good applicability. It can provide transfer scheme reference for passengers, meanwhile, improve the scheduling and management of the subway operation. PMID:26835224

  4. HELCATS Prediction of Planetary CME arrival times

    NASA Astrophysics Data System (ADS)

    Boakes, Peter; Moestl, Christian; Davies, Jackie; Harrison, Richard; Byrne, Jason; Barnes, David; Isavnin, Alexey; Kilpua, Emilia; Rollett, Tanja

    2015-04-01

    We present the first results of CME arrival time prediction at different planetary locations and their comparison to the in situ data within the HELCATS project. The EU FP7 HELCATS (Heliospheric Cataloguing, Analysis & Techniques Service) is a European effort to consolidate the exploitation of the maturing field of heliospheric imaging. HELCATS aims to catalogue solar wind transients, observed by the NASA STEREO Heliospheric Imager (HI) instruments, and validate different methods for the determination of their kinematic properties. This validation includes comparison with arrivals at Earth, and elsewhere in the heliosphere, as well as onsets at the Sun (http://www.helcats-fp7.eu/). A preliminary catalogue of manually identified CMEs, with over 1000 separate events, has been created from observations made by the STEREO/HI instruments covering the years 2007-2013. Initial speeds and directions of each CME have been derived through fitting the time elongation profile to the state of the art Self-Similar Expansion Fitting (SSEF) geometric technique (Davies et al., 2012). The technique assumes that, in the plane corresponding to the position angle of interest, CMEs can be modelled as circles subtending a fixed angular width to Sun-center and propagating anti-sunward in a fixed direction at a constant speed (we use an angular width of 30 degrees in our initial results). The model has advantages over previous geometric models (e.g. harmonic mean or fixed phi) as it allows one to predict whether a CME will 'hit' a specific heliospheric location, as well as to what degree (e.g. direct assault or glancing blow). We use correction formulae (Möstl and Davies, 2013) to convert CME speeds, direction and launch time to speed and arrival time at any in situ location. From the preliminary CME dataset, we derive arrival times for over 400 Earth-directed CMEs, and for over 100 Mercury-, Venus-, Mars- and Saturn-directed CMEs predicted to impact each planet. We present statistics of

  5. Nursing, pharmacy, or medicine? Disgust sensitivity predicts career interest among trainee health professionals.

    PubMed

    Consedine, Nathan S; Yu, Tzu-Chieh; Windsor, John A

    2013-12-01

    Given global demand on health workforces, understanding student enrollment motivations are critical. Prior studies have concentrated on variation in career and lifestyle values; the current work evaluated the importance of disgust sensitivity in the prediction of health career interests. We argue that emotional proclivities may be important and that disgust sensitivity may help explain differential student interest in nursing, pharmacy, or medical careers. 303 first year students attending a required course in human behavior provided consent before completing questionnaires assessing: (1) demographics, (2) career intentions/interests, (3) traditional determinants of career intention/interest, and (4) dispositional disgust sensitivity. As expected, disgust sensitivity varied across the three majors, with those targeting medical careers being less sensitive than those interested in either nursing or pharmacy. As importantly, even when controlling for demographics and traditional career determinants, analyses showed that greater disgust sensitivity was associated with reduced odds of intended enrolment in pharmacy versus medicine or nursing but did not predict the distinction between nursing and medicine. The impact of disgust sensitivity on career interest was substantial and equivalent to established predictors of career intention. Disgust sensitivity may represent an important factor impacting the specific choices students make within the health professions, particular when students are choosing between careers involving greater and lesser degrees of exposure to the normative elicitors of disgust. PMID:23297059

  6. The Efficacy of ATI Predictive Testing and Remediation on National Certification and Licensure Examination-Registered Nurse Pass Rates

    ERIC Educational Resources Information Center

    Winter, Alexandra Selman

    2013-01-01

    This project study sought to evaluate the effects of implementing quarterly predictive testing and remediation on National Certification and Licensure Examination-Registered Nurse (NCLEX-RN) pass rates of an associate's degree nursing program at a small Midwestern community college. The college's pass rate on the NCLEX-RN has been below both the…

  7. Can Student Nurse Critical Thinking Be Predicted from Perceptions of Structural Empowerment within the Undergraduate, Pre-Licensure Learning Environment?

    ERIC Educational Resources Information Center

    Caswell-Moore, Shelley P.

    2013-01-01

    The purpose of this study was to test a model using Rosabeth Kanter's theory (1977; 1993) of structural empowerment to determine if this model can predict student nurses' level of critical thinking. Major goals of nursing education are to cultivate graduates who can think critically with a keen sense of clinical judgment, and who can perform…

  8. Predicting road accidents: Structural time series approach

    NASA Astrophysics Data System (ADS)

    Junus, Noor Wahida Md; Ismail, Mohd Tahir

    2014-07-01

    In this paper, the model for occurrence of road accidents in Malaysia between the years of 1970 to 2010 was developed and throughout this model the number of road accidents have been predicted by using the structural time series approach. The models are developed by using stepwise method and the residual of each step has been analyzed. The accuracy of the model is analyzed by using the mean absolute percentage error (MAPE) and the best model is chosen based on the smallest Akaike information criterion (AIC) value. A structural time series approach found that local linear trend model is the best model to represent the road accidents. This model allows level and slope component to be varied over time. In addition, this approach also provides useful information on improving the conventional time series method.

  9. Entrepreneurial nursing: the right course at the right time.

    PubMed

    Barger, S E

    1991-01-01

    As more nurses start businesses of their own, there is a need for a course to help them learn to plan, organize, finance, and operate these businesses. The author describes the course's organization, its outcomes, and reactions of the first students to participate in the course. PMID:1923003

  10. Quiet Times: Ninth Graders Teach Poetry Writing in Nursing Homes.

    ERIC Educational Resources Information Center

    Dickson, Randi

    1999-01-01

    Describes a community project (based on Kenneth Koch's book "I Never Told Anybody") in which students in a ninth-grade English class paired up with nursing home residents, making regular visits to encourage them to write poetry. Discusses finding a place, getting ready, working together, and what students learned about writing poetry and about…

  11. Predicting survival time for cold exposure

    NASA Astrophysics Data System (ADS)

    Tikuisis, Peter

    1995-06-01

    The prediction of survival time (ST) for cold exposure is speculative as reliable controlled data of deep hypothermia are unavailable. At best, guidance can be obtained from case histories of accidental exposure. This study describes the development of a mathematical model for the prediction of ST under sedentary conditions in the cold. The model is based on steady-state heat conduction in a single cylinder comprised of a core and two concentric annular shells representing the fat plus skin and the clothing plus still boundary layer, respectively. The ambient condition can be either air or water; the distinction is made by assigning different values of insulation to the still boundary layer. Metabolic heat production ( M) is comprised of resting and shivering components with the latter predicted by temperature signals from the core and skin. Where the cold exposure is too severe for M to balance heat loss, ST is largely determined by the rate of heat loss from the body. Where a balance occurs, ST is governed by the endurance time for shivering. End of survival is marked by the deep core temperature reaching a value of 30° C. The model was calibrated against survival data of cold water (0 to 20° C) immersion and then applied to cold air exposure. A sampling of ST predictions for the nude exposure of an average healthy male in relatively calm air (1 km/h wind speed) are the following: 1.8, 2.5, 4.1, 9.0, and >24 h for -30, -20, -10, 0, and 10° C, respectively. With two layers of loose clothing (average thickness of 1 mm each) in a 5 km/h wind, STs are 4.0, 5.6, 8.6, 15.4, and >24 h for -50, -40, -30, -20, and -10° C. The predicted STs must be weighted against the extrapolative nature of the model. At present, it would be prudent to use the predictions in a relative sense, that is, to compare or rank-order predicted STs for various combinations of ambient conditions and clothing protection.

  12. Community Health Nursing for Working People. A Guide for Voluntary and Official Health Agencies to Provide Part-Time Occupational Health Nursing Services.

    ERIC Educational Resources Information Center

    Public Health Service (DHEW), Cincinnati, OH.

    Developed on the assumption that part-time nursing services will eventually become part of a comprehensive health program for each industry served, this 3-part guide contains guidelines for planning, promoting, and developing a part-time nursing service. Part I provides administrative considerations for planning the service and responsibilities of…

  13. A real-time prediction of UTC

    NASA Astrophysics Data System (ADS)

    Thomas, Claudine; Allan, David W.

    1994-05-01

    The reference time scale for all scientific and technologic applications on the Earth, the Universal Coordinated Time (UTC), must be as stable, reliable, and accurate as possible. With this in view the BIPM and before it the BIH, have always calculated and then disseminated UTC with a delay of about 80 days. There are three fundamental reasons for doing this: (1) It takes some weeks for data, gathered from some 200 clocks spread world-wide, to be collected and for errors to be eliminated; (2) changes in clock rates can only be measured with high precision well after the fact; and (3) the measurement noise originating in time links, in particular using Loran-C, is smoothed out only when averaging over an extended period. Until mid-1992, the ultimate stability of UTC was reached at averaging times of about 100 days and corresponded to an Allan deviation sigma(sub y)(tau) of about 1,5x10(exp -14) then compared to the best primary clock in the world, the PTB CS2. For several years now, a predicted UTC has been computed by the USNO through an extrapolation of the values as published in deferred time by the BIPM. This is made available through the USNO Series 4, through the USNO Automated Data Service, and through GPS signals. Due to the instability of UTC, the poor predictability of the available clocks, and the intentional SA degradation of GPS signals, the real-time access to this extrapolated UTC has represented the true deferred-time UTC only to within several hundreds of nanoseconds.

  14. A real-time prediction of UTC

    NASA Technical Reports Server (NTRS)

    Thomas, Claudine; Allan, David W.

    1994-01-01

    The reference time scale for all scientific and technologic applications on the Earth, the Universal Coordinated Time (UTC), must be as stable, reliable, and accurate as possible. With this in view the BIPM and before it the BIH, have always calculated and then disseminated UTC with a delay of about 80 days. There are three fundamental reasons for doing this: (1) It takes some weeks for data, gathered from some 200 clocks spread world-wide, to be collected and for errors to be eliminated; (2) changes in clock rates can only be measured with high precision well after the fact; and (3) the measurement noise originating in time links, in particular using Loran-C, is smoothed out only when averaging over an extended period. Until mid-1992, the ultimate stability of UTC was reached at averaging times of about 100 days and corresponded to an Allan deviation sigma(sub y)(tau) of about 1,5x10(exp -14) then compared to the best primary clock in the world, the PTB CS2. For several years now, a predicted UTC has been computed by the USNO through an extrapolation of the values as published in deferred time by the BIPM. This is made available through the USNO Series 4, through the USNO Automated Data Service, and through GPS signals. Due to the instability of UTC, the poor predictability of the available clocks, and the intentional SA degradation of GPS signals, the real-time access to this extrapolated UTC has represented the true deferred-time UTC only to within several hundreds of nanoseconds.

  15. Viscoelastic behavior and life-time predictions

    NASA Technical Reports Server (NTRS)

    Dillard, D. A.; Brinson, H. F.

    1985-01-01

    Fiber reinforced plastics were considered for many structural applications in automotive, aerospace and other industries. A major concern was and remains the failure modes associated with the polymer matrix which serves to bind the fibers together and transfer the load through connections, from fiber to fiber and ply to ply. An accelerated characterization procedure for prediction of delayed failures was developed. This method utilizes time-temperature-stress-moisture superposition principles in conjunction with laminated plate theory. Because failures are inherently nonlinear, the testing and analytic modeling for both moduli and strength is based upon nonlinear viscoelastic concepts.

  16. The Minimum Data Set 2.0: a functional assessment to predict mortality in nursing home residents.

    PubMed

    Abicht-Swensen, L M; Debner, L K

    1999-01-01

    Measures of functional assessment, such as the Karnofsky Scale, the Modified ADL Scale, and the Descriptive Scale, have been used to predict appropriateness for hospice care. A tool is needed to assess functional status across all treatment settings, including acute care, long-term care, and hospice. The objective of this paper is to determine whether the Minimum Data Set, when utilized in conjunction with physical assessment tools to determine prognosis, is accurate in predicting short-term mortality in nursing home residents. The paper has been designed as a retrospective study of residents in 24 Minnesota nursing homes who were referred to a hospice program. The study included 199 patients from 30 to 107 years of age. Functional variables, as triggered by the Minimum Data Set, have a direct correlation to patient mortality within three months of the documented observation of the triggered variable, and are the main outcome measure. Of a total of 199 patients, 147 patients (74 percent) died within 15 days of a documented significant decline in the Minimum Data Set in areas of cognitive function, communication, activities of daily living, incontinence, and nutrition. Age, gender, diagnosis, and significant medical data received from the nursing home staff at the time of referral to hospice were applied to the Karnofsky Scale, the Modified ADL Scale, the Descriptive Scale, and the Minimum Data Set to determine if a resident assessment protocol (RAP) would be triggered by these data. The data were then analyzed to determine whether there existed a correlation between a significant change, as documented on the Minimum Data Set, and subsequent death of the patient. If there existed a correlation, the data were further studied to determine consistency in the categories of change that might demonstrate predictors of short-term mortality in nursing home residents. A decline in functional status, as documented on the Minimum Data Set 2.0 in the areas of cognitive

  17. Sex-Role Stereotyping of Nurses and Physicians on Prime-Time Television: A Dichotomy of Occupational Portrayals.

    ERIC Educational Resources Information Center

    Kalisch, Philip A; Kalisch, Beatrice J.

    1984-01-01

    Analysis of prime-time television portrayals of nurses and physicians (1950-80) shows extreme levels of both sexual and occupational stereotyping. TV nurses are 99 percent female; TV physicians are 95 percent male. The TV image of female professional nurses is of total dependence on and subservience to male physicians. (Author/CMG)

  18. Time-dependence in mixture toxicity prediction

    PubMed Central

    Dawson, Douglas A.; Allen, Erin M.G.; Allen, Joshua L.; Baumann, Hannah J.; Bensinger, Heather M.; Genco, Nicole; Guinn, Daphne; Hull, Michael W.; Il'Giovine, Zachary J.; Kaminski, Chelsea M.; Peyton, Jennifer R.; Schultz, T. Wayne; Pöch, Gerald

    2014-01-01

    The value of time-dependent toxicity (TDT) data in predicting mixture toxicity was examined. Single chemical (A and B) and mixture (A + B) toxicity tests using Microtox® were conducted with inhibition of bioluminescence (Vibrio fischeri) being quantified after 15, 30 and 45-min of exposure. Single chemical and mixture tests for 25 sham (A1:A2) and 125 true (A:B) combinations had a minimum of seven duplicated concentrations with a duplicated control treatment for each test. Concentration/response (x/y) data were fitted to sigmoid curves using the five-parameter logistic minus one parameter (5PL-1P) function, from which slope, EC25, EC50, EC75, asymmetry, maximum effect, and r2 values were obtained for each chemical and mixture at each exposure duration. Toxicity data were used to calculate percentage-based TDT values for each individual chemical and mixture of each combination. Predicted TDT values for each mixture were calculated by averaging the TDT values of the individual components and regressed against the observed TDT values obtained in testing, resulting in strong correlations for both sham (r2 = 0.989, n = 25) and true mixtures (r2 = 0.944, n = 125). Additionally, regression analyses confirmed that observed mixture TDT values calculated for the 50% effect level were somewhat better correlated with predicted mixture TDT values than at the 25 and 75% effect levels. Single chemical and mixture TDT values were classified into five levels in order to discern trends. The results suggested that the ability to predict mixture TDT by averaging the TDT of the single agents was modestly reduced when one agent of the combination had a positive TDT value and the other had a minimal or negative TDT value. PMID:25446331

  19. Time pressure and regulations on hospital-in-the-home (HITH) nurses: An on-the-road study.

    PubMed

    Cœugnet, Stéphanie; Forrierre, Justine; Naveteur, Janick; Dubreucq, Catherine; Anceaux, Françoise

    2016-05-01

    This study investigated both causal factors and consequences of time pressure in hospital-in-the-home (HITH) nurses. These nurses may experience additional stress from the time pressure they encounter while driving to patients' homes, which may result in greater risk taking while driving. From observation in natural settings, data related to the nurses' driving behaviours and emotions were collected and analysed statistically; semi-directed interviews with the nurses were analysed qualitatively. The results suggest that objective time constraints alone do not necessarily elicit subjective time pressure. The challenges and uncertainty associated with healthcare and the driving period contribute to the emergence of this time pressure, which has a negative impact on both the nurses' driving and their emotions. Finally, the study focuses on anticipated and in situ regulations. These findings provide guidelines for organizational and technical solutions allowing the reduction of time pressure among HITH nurses. PMID:26851470

  20. An evaluation of factors influencing the assessment time in a nurse practitioner-led anaesthetic pre-operative assessment clinic.

    PubMed

    Hawes, R H; Andrzejowski, J C; Goodhart, I M; Berthoud, M C; Wiles, M D

    2016-03-01

    Elective patients undergoing anaesthetic pre-operative assessment are usually allocated the same period of time with a nurse practitioner, leading to potential inefficiencies in patient flow through the clinic. We prospectively collected data on 8519 patients attending a pre-operative assessment clinic. The data set were split into derivation and validation cohorts. Standard multiple regressions were used to construct a model in the derivation cohort, which was then tested in the validation cohort. Due to missing data, 2457 patients were not studied, leaving 5892 for analysis (3870 in the derivation cohort and 2022 in the validation cohort). The mean (SD) pre-operative assessment time was 46 (12) min. Age, ASA physical status, nurse practitioner and surgical specialty all influenced the time spent in pre-operative assessment. The predictive equations calculated using the derivation cohort, based on age and ASA physical status, correctly estimated duration of consultation to within 20% of the maximum predicted time in 74.2% of the validation cohort. We conclude that if age and ASA physical status are known before the pre-operative assessment consultation, it could allow appointment times to be allocated more accurately. PMID:26684961

  1. Nurse practitioners changing health behaviours: one patient at a time.

    PubMed

    Sangster-Gormley, Esther; Griffith, Janessa; Schreiber, Rita; Feddema, April; Boryki, Elizabeth; Thompson, Joanne

    2015-10-01

    In 2005, legislation was enacted allowing nurse practitioners (NPs) to practise in British Columbia, Canada. Although substantial human and financial resources had been dedicated to the implementation of the role, no evaluation has been conducted to date. As part of a larger multiphase, mixed-methods study design, which evaluated the integration of NPs into the British Columbia healthcare system, this article describes findings related to changes that result for patients and the implications for the healthcare system when NPs become part of the care process. Using survey and interview data, themes that emerged were patient satisfaction, access to care, and behavioural changes. Findings suggest that patients are satisfied with the care they receive from NPs and that NPs make positive changes to health behaviour. PMID:26419574

  2. Real Time Seismic Prediction while Drilling

    NASA Astrophysics Data System (ADS)

    Schilling, F. R.; Bohlen, T.; Edelmann, T.; Kassel, A.; Heim, A.; Gehring, M.; Lüth, S.; Giese, R.; Jaksch, K.; Rechlin, A.; Kopf, M.; Stahlmann, J.; Gattermann, J.; Bruns, B.

    2009-12-01

    Efficient and safe drilling is a prerequisite to enhance the mobility of people and goods, to improve the traffic as well as utility infrastructure of growing megacities, and to ensure the growing energy demand while building geothermal and in hydroelectric power plants. Construction within the underground is often building within the unknown. An enhanced risk potential for people and the underground building may arise if drilling enters fracture zones, karsts, brittle rocks, mixed solid and soft rocks, caves, or anthropogenic obstacles. Knowing about the material behavior ahead of the drilling allows reducing the risk during drilling and construction operation. In drilling operations direct observations from boreholes can be complemented with geophysical investigations. In this presentation we focus on “real time” seismic prediction while drilling which is seen as a prerequisite while using geophysical methods in modern drilling operations. In solid rocks P- and S-wave velocity, refraction and reflection as well as seismic wave attenuation can be used for the interpretation of structures ahead of the drilling. An Integrated Seismic Imaging System (ISIS) for exploration ahead of a construction is used, where a pneumatic hammer or a magnetostrictive vibration source generate repetitive signals behind the tunneling machine. Tube waves are generated which travel along the tunnel to the working face. There the tube waves are converted to mainly S- but also P-Waves which interact with the formation ahead of the heading face. The reflected or refracted waves travel back to the working front are converted back to tube waves and recorded using three-component geophones which are fit into the tips of anchor rods. In near real time, the ISIS software allows for an integrated 3D imaging and interpretation of the observed data, geological and geotechnical parameters. Fracture zones, heterogeneities, and variations in the rock properties can be revealed during the drilling

  3. Resource Selection Using Execution and Queue Wait Time Predictions

    NASA Technical Reports Server (NTRS)

    Smith, Warren; Wong, Parkson; Biegel, Bryan (Technical Monitor)

    2001-01-01

    We developed techniques to predict application execution times for instance-based learning with an average error of 33% of average run time. We developed techniques to predict queue wait times that included a simulation of scheduling algorithms and execution time predictions. We implemented these techniques for the NAS Origin cluster.

  4. In real time: exploring nursing students' learning during an international experience.

    PubMed

    Afriyie Asenso, Barbara; Reimer-Kirkham, Sheryl; Astle, Barbara

    2013-01-01

    Abstract Nursing education has increasingly turned to international learning experiences to educate students who are globally minded and aware of social injustices in local and global communities. To date, research with international learning experiences has focused on the benefits for the students participating, after they have completed the international experience. The purpose of this qualitative study was to explore how nursing students learn during the international experience. The sample consisted of eight nursing students who enrolled in an international learning experience, and data were collected in "real time" in Zambia. The students were observed during learning activities and were interviewed three times. Three major themes emerged from the thematic analysis: expectations shaped students' learning, engagement facilitated learning, and critical reflection enhanced learning. Implications are discussed, related to disrupting media representations of Africa that shape students' expectations, and educational strategies for transformative learning and global citizenship. PMID:24150212

  5. "Time enough! Or not enough time!" An oral history investigation of some British and Australian community nurses' responses to demands for "efficiency" in health care, 1960-2000.

    PubMed

    Hallett, Christine E; Madsen, Wendy; Pateman, Brian; Bradshaw, Julie

    2012-01-01

    Oral history methodology was used to investigate the perspectives of retired British district nurses and Australian domiciliary nurses who had practiced between 1960 and 2000. Interviews yielded insights into the dramatic changes in community nursing practice during the last four decades of the 20th century. Massive changes in health care and government-led drives for greater efficiency meant moving from practice governed by "experiential time" (in which perception of time depends on the quality of experience) to practice governed by "measured time" (in which experience itself is molded by the measurement of time). Nurses recognized that the quality of their working lives and their relationships with families had been altered by the social, cultural, and political changes, including the drive for professional recognition in nursing itself, soaring economic costs of health care and push for deinstitutionalization of care. Community nurses faced several dilemmas as they grappled with the demands for efficiency created by these changes. PMID:22360001

  6. Can We Predict Burnout among Student Nurses? An Exploration of the ICWR-1 Model of Individual Psychological Resilience

    PubMed Central

    Rees, Clare S.; Heritage, Brody; Osseiran-Moisson, Rebecca; Chamberlain, Diane; Cusack, Lynette; Anderson, Judith; Terry, Victoria; Rogers, Cath; Hemsworth, David; Cross, Wendy; Hegney, Desley G.

    2016-01-01

    The nature of nursing work is demanding and can be stressful. Previous studies have shown a high rate of burnout among employed nurses. Recently, efforts have been made to understand the role of resilience in determining the psychological adjustment of employed nurses. A theoretical model of resilience was proposed recently that includes several constructs identified in the literature related to resilience and to psychological functioning. As nursing students are the future of the nursing workforce it is important to advance our understanding of the determinants of resilience in this population. Student nurses who had completed their final practicum were invited to participate in an online survey measuring the key constructs of the ICWR-1 model. 422 students from across Australia and Canada completed the survey between July 2014 and July 2015. As well as several key demographics, trait negative affect, mindfulness, self-efficacy, coping, resilience, and burnout were measured. We used structural equation modeling and found support for the major pathways of the model; namely that resilience had a significant influence on the relationship between mindfulness, self-efficacy and coping, and psychological adjustment (burnout scores). Furthermore, as predicted, Neuroticism moderated the relationship between coping and burnout. Results are discussed in terms of potential approaches to supporting nursing students who may be at risk of burnout. PMID:27486419

  7. Can We Predict Burnout among Student Nurses? An Exploration of the ICWR-1 Model of Individual Psychological Resilience.

    PubMed

    Rees, Clare S; Heritage, Brody; Osseiran-Moisson, Rebecca; Chamberlain, Diane; Cusack, Lynette; Anderson, Judith; Terry, Victoria; Rogers, Cath; Hemsworth, David; Cross, Wendy; Hegney, Desley G

    2016-01-01

    The nature of nursing work is demanding and can be stressful. Previous studies have shown a high rate of burnout among employed nurses. Recently, efforts have been made to understand the role of resilience in determining the psychological adjustment of employed nurses. A theoretical model of resilience was proposed recently that includes several constructs identified in the literature related to resilience and to psychological functioning. As nursing students are the future of the nursing workforce it is important to advance our understanding of the determinants of resilience in this population. Student nurses who had completed their final practicum were invited to participate in an online survey measuring the key constructs of the ICWR-1 model. 422 students from across Australia and Canada completed the survey between July 2014 and July 2015. As well as several key demographics, trait negative affect, mindfulness, self-efficacy, coping, resilience, and burnout were measured. We used structural equation modeling and found support for the major pathways of the model; namely that resilience had a significant influence on the relationship between mindfulness, self-efficacy and coping, and psychological adjustment (burnout scores). Furthermore, as predicted, Neuroticism moderated the relationship between coping and burnout. Results are discussed in terms of potential approaches to supporting nursing students who may be at risk of burnout. PMID:27486419

  8. Identification of cognitive and non-cognitive predictive variables related to attrition in baccalaureate nursing education programs in Mississippi

    NASA Astrophysics Data System (ADS)

    Hayes, Catherine

    2005-07-01

    This study sought to identify a variable or variables predictive of attrition among baccalaureate nursing students. The study was quantitative in design and multivariate correlational statistics and discriminant statistical analysis were used to identify a model for prediction of attrition. The analysis then weighted variables according to their predictive value to determine the most parsimonious model with the greatest predictive value. Three public university nursing education programs in Mississippi offering a Bachelors Degree in Nursing were selected for the study. The population consisted of students accepted and enrolled in these three programs for the years 2001 and 2002 and graduating in the years 2003 and 2004 (N = 195). The categorical dependent variable was attrition (includes academic failure or withdrawal) from the program of nursing education. The ten independent variables selected for the study and considered to have possible predictive value were: Grade Point Average for Pre-requisite Course Work; ACT Composite Score, ACT Reading Subscore, and ACT Mathematics Subscore; Letter Grades in the Courses: Anatomy & Physiology and Lab I, Algebra I, English I (101), Chemistry & Lab I, and Microbiology & Lab I; and Number of Institutions Attended (Universities, Colleges, Junior Colleges or Community Colleges). Descriptive analysis was performed and the means of each of the ten independent variables was compared for students who attrited and those who were retained in the population. The discriminant statistical analysis performed created a matrix using the ten variable model that was able to correctly predicted attrition in the study's population in 77.6% of the cases. Variables were then combined and recombined to produce the most efficient and parsimonious model for prediction. A six variable model resulted which weighted each variable according to predictive value: GPA for Prerequisite Coursework, ACT Composite, English I, Chemistry & Lab I, Microbiology

  9. Fast-track for fast times: catching and keeping generation Y in the nursing workforce.

    PubMed

    Walker, Kim

    2007-04-01

    There is little doubt we find ourselves in challenging times as never before has there been such generational diversity in the nursing workforce. Currently, nurses from four distinct (and now well recognised and discussed) generational groups jostle for primacy of recognition and reward. Equally significant is the acute realisation that our ageing profession must find ways to sustain itself in the wake of huge attrition as the 'baby boomer' nurses start retiring over the next ten to fifteen years. These realities impel us to become ever more strategic in our thinking about how best to manage the workforce of the future. This paper presents two exciting and original innovations currently in train at one of Australia's leading Catholic health care providers: firstly, a new fast-track bachelor of nursing program for fee-paying domestic students. This is a collaborative venture between St Vincent's and Mater Health, Sydney (SV&MHS) and the University of Tasmania (UTas); as far as we know, it is unprecedented in Australia. As well, the two private facilities of SV&MHS, St Vincent's Private (SVPH) and the Mater Hospitals, have developed and implemented a unique 'accelerated progression pathway' (APP) to enable registered nurses with talent and ambition to fast track their career through a competency and merit based system of performance management and reward. Both these initiatives are aimed squarely at the gen Y demographic and provide potential to significantly augment our capacity to recruit and retain quality people well into the future. PMID:17563323

  10. Factors Associated with Time to Identify Physical Problems of Nursing Home Residents with Dementia

    PubMed Central

    Kovach, Christine R.; Logan, Brent R.; Simpson, Michelle R.; Reynolds, Sheila

    2010-01-01

    This study describes new problems emerging over six weeks for nursing home residents with advanced dementia and factors associated with time to identify the problems. The sample of 65 developed 149 new acute problems or exacerbations of existing conditions over the six weeks of data collection. The majority of these problems involved uncontrolled pain, new infections and severe psychoses. Nurse assessment skill was associated with a shorter time to identify the new problem and more time spent on the problem. A higher ratio of new to existing interventions was also associated with a shorter time to identify the problem. Other patient characteristics associated with time to identify problems included non-specific vocalizations, physical signs, cognitive status and length of stay. While future research is warranted, findings from this study highlight the frequency of problems requiring treatment and suggest that improved assessment of residents may decrease the time to identify new problems. PMID:20237337

  11. Nurse-led risk assessment/management clinics reduce predicted cardiac morbidity and mortality in claudicants.

    PubMed

    Hatfield, Josephine; Gulati, Sumit; Abdul Rahman, Morhisham N A; Coughlin, Patrick A; Chetter, Ian C

    2008-12-01

    Nurse-led assessment/management of risk factors is effective in many chronic medical conditions. We aimed to evaluate whether this finding was true for patients with intermittent claudication and to analyze its impact on patient-reported quality of life and predicted mortality due to coronary heart disease. We prospectively studied a series of 78 patients (51 men; median age, 65 years [IQR: 56-74 years]), diagnosed with intermittent claudication and referred to a nurse-led risk assessment/management clinic (NLC) from a consultant-led vascular surgical clinic. The NLC used clinical care pathways to manage antiplatelet medication, smoking cessation, hyperlipidemia, hypertension, and diabetes and to provide exercise advice. All patients were reassessed at a 3 months. Medication compliance, smoking status, fasting lipid profiles, blood pressure, and HbA1c were recorded. Disease-specific quality of life was assessed using King's College VascuQoL and predicted cardiac morbidity and mortality were calculated using the PROCAM and Framingham risk scores. We found that NLC enrollment produced an antiplatelet and a statin compliance of 100%, a smoking cessation rate of 17% (9 patients) and significant improvements in total cholesterol (median, 5.2-4.5 mmol/l), LDL (median, 3.1-2.5 mmol/l) and triglyceride (median, 1.7-1.4 mmol/l) levels. Significant disease-specific quality of life improvements and significant reduction in both the PROCAM (14% to 10%) and Framingham (14% to 11%) coronary risk scores were observed. Providing care at NLCs for claudicants is effective in assessing and managing risk factors, improves disease-specific quality of life and reduces predicted morbidity and mortality due to coronary heart disease. PMID:19022170

  12. Meanings Over Time of Working as a Nurse in Elderly Care

    PubMed Central

    Blomberg, Karin; James, Inger; Kihlgren, Annica

    2013-01-01

    Background: Although registered nurses (RNs) play a central role in the care of older persons, their work in elderly care has historically been described as “low status” in nursing. This is especially problematic due to the global issue of RN turnover, but there is still little evidence of how to change this trend. Better understanding is needed of the reasons why RNs work in elderly care, as well as knowledge of whether these reasons have changed over time. Aim: The aim was to explore the meaning of working in elderly care, over time, from the perspective of RNs. Method: We interviewed thirteen RNs working in nursing homes, six of them in 2000 and the remaining seven in 2012, and analysed the resulting data using Interpretive Description. Results: The results show similarities and differences over time in the RNs’ reasoning about the meaning of their work with older persons, from a focus on obstacles to a view of opportunities. Conclusion: An RN’s intention to continue working in elderly care might be based on their beliefs; their view of older people, and their experiences of being able to influence the care. Managing this knowledge could be an essential factor in reversing the historical trend of RN work in elderly care being seen as low status, and the increasing turnover in such nurses. Our results could stimulate reflection on daily care and beliefs about caring for older persons. PMID:24044032

  13. A review of demographic and infrastructural factors and potential solutions to the physician and nursing shortage predicted to impact the growing US elderly population.

    PubMed

    Cohen, Steven A

    2009-01-01

    This review highlights several of the key demographic, infrastructural, and cultural factors associated with the predicted labor force shortage in the healthcare field. Population dynamics play a significant role in exacerbating the healthcare labor force shortage. These factors work to simultaneously increase the size and proportion of the population needing the most care, namely, the elderly, and also to reduce the availability of physicians and nurses to provide adequate care for the growing elderly population. Physicians and nurses have expressed consistent dissatisfaction with healthcare infrastructure and have cited decreased job satisfaction, further exacerbating the shortage. Potential solutions to the shortage, aside from dramatic changes to the healthcare system, include increased medical and nursing training in geriatrics and gerontology to increase interest, competency, and knowledge of health issues specifically pertaining to the elderly. Other solutions include monetary incentives for geriatric training for nurses and physicians. Any specific measures to remedy this growing problem should be implemented in a timely manner to reduce this critical shortage of healthcare workers that will only continue to grow in the coming decades. PMID:19525780

  14. Measuring HIV stigma for PLHAs and nurses over time in five African countries.

    PubMed

    Holzemer, William L; Makoae, Lucy N; Greeff, Minrie; Dlamini, Priscilla S; Kohi, Thecla W; Chirwa, Maureen L; Naidoo, Joanne R; Durrheim, Kevin; Cuca, Yvette; Uys, Yvette R

    2009-09-01

    The aim of this article is to document the levels of HIV stigma reported by persons living with HIV infections and nurses in Lesotho, Malawi, South Africa, Swaziland and Tanzania over a 1-year period. HIV stigma has been shown to negatively affect the quality of life for people living with HIV infection, their adherence to medication, and their access to care. Few studies have documented HIV stigma by association as experienced by nurses or other health care workers who care for people living with HIV infection. This study used standardised scales to measure the level of HIV stigma over time. A repeated measures cohort design was used to follow persons living with HIV infection and nurses involved in their care from five countries over a 1-year period in a three-wave longitudinal design. The average age of people living with HIV/AIDS (PLHAs) (N=948) was 36.15 years (SD=8.69), and 67.1% (N=617) were female. The average age of nurses (N=887) was 38.44 years (SD=9.63), and 88.6% (N=784) were females. Eighty-four per cent of all PLHAs reported one or more HIV-stigma events at baseline. This declined, but was still significant 1 year later, when 64.9% reported experiencing at least one HIV-stigma event. At baseline, 80.3% of the nurses reported experiencing one or more HIV-stigma events and this increased to 83.7% 1 year later. The study documented high levels of HIV stigma as reported by both PLHAs and nurses in all five of these African countries. These results have implications for stigma reduction interventions, particularly focused at health care providers who experience HIV stigma by association. PMID:19936409

  15. Measuring HIV Stigma for PLHAs and Nurses over Time in Five African Countries

    PubMed Central

    Holzemer, William L.; Makoae, Lucy N.; Greeff, Minrie; Dlamini, Priscilla S.; Kohi, Thecla W.; Chirwa, Maureen L.; Naidoo, Joanne R.; Durrheim, Kevin; Cuca, Yvette; Uys, Leana R.

    2013-01-01

    The aim of this article is to document the levels of HIV stigma reported by persons living with HIV infections and nurses in Lesotho, Malawi, South Africa, Swaziland and Tanzania over a one-year period. HIV stigma has been shown to affect negatively the quality of life for people living with HIV infection, their adherence to medication, and their access to care. Few studies have documented HIV stigma by association as experienced by nurses or other health care workers who care for people living with HIV infection. This study used standardized scales to measure the level of HIV stigma over time. A repeated measures cohort design was used to follow persons living with HIV infection and nurses involved in their care from five countries over a one-year period in a three-wave longitudinal design. The average age of PLHAs (n = 948) was 36.15 years (SD= 8.69), and 67.1% (n= 617) were female. The average age of nurses (n = 887) was 38.44 years (SD=9.63), and 88.6% (n=784) were females. Eighty-four percent of all PLHAs reported one or more HIV stigma event at baseline. This declined, but was still significant one year later when 64.9% reported experiencing at least one HIV stigma event. At baseline, 80.3% of the nurses reported experiencing one or more HIV stigma events and this increased to 83.7% one year later. The study documented high levels of HIV stigma as reported by both PLHAs and nurses in all five of these African countries. These results have implications for stigma reduction interventions, particularly focused at health care providers who experience HIV stigma by association. PMID:19936409

  16. Physician and nurse supply in Serbia using time-series data

    PubMed Central

    2013-01-01

    Background Unemployment among health professionals in Serbia has risen in the recent past and continues to increase. This highlights the need to understand how to change policies to meet real and projected needs. This study identified variables that were significantly related to physician and nurse employment rates in the public healthcare sector in Serbia from 1961 to 2008 and used these to develop parameters to model physician and nurse supply in the public healthcare sector through to 2015. Methods The relationships among six variables used for planning physician and nurse employment in public healthcare sector in Serbia were identified for two periods: 1961 to 1982 and 1983 to 2008. Those variables included: the annual total national population; gross domestic product adjusted to 1994 prices; inpatient care discharges; outpatient care visits; students enrolled in the first year of medical studies at public universities; and the annual number of graduated physicians. Based on historic trends, physician supply and nurse supply in the public healthcare sector by 2015 (with corresponding 95% confidence level) have been modeled using Autoregressive Integrated Moving Average (ARIMA) / Transfer function (TF) models. Results The ARIMA/TF modeling yielded stable and significant forecasts of physician supply (stationary R2 squared = 0.71) and nurse supply (stationary R2 squared = 0.92) in the public healthcare sector in Serbia through to 2015. The most significant predictors for physician employment were the population and GDP. The supply of nursing staff was, in turn, related to the number of physicians. Physician and nurse rates per 100,000 population increased by 13%. The model predicts a seven-year mismatch between the supply of graduates and vacancies in the public healthcare sector is forecasted at 8,698 physicians - a net surplus. Conclusion The ARIMA model can be used to project trends, especially those that identify significant mismatches between forecasted

  17. [Proposal of a new assessment scale of work load and nursing times (VACTE].

    PubMed

    Braña Marcos, B; Del Campo Ugidos, R M; Fernández Méndez, E; de la Villa Santoveña, M

    2007-01-01

    The scale Nine Equivalents of nursing Manpower use Score (NEMS) for the evaluation of the nursing care loads is the most well known and applied worldwide. Nevertheless, we have found a series of limitations: it does not reflect the "proper nursing activity" but only the cares related to the medical intervention. Furthermore, it is directly related to severity while integral attention to the patient implies an infinity of cares, which are not necessarily related to the severity. In addition, we understand that the planned personnel ratios may be unsuitable, with the consequent repercussions for the patient, nurses and the sanitary institution. The primary targets were: elaboration of a representative scale of all the cares and tasks made by the nurses (VACTE) in our unit, to determine if it is more precise and objective than NEMS for the measurement of the service loads and to calculate the operative ratio patient-nurse based on the new proposed scale. We made a descriptive and retrospective study on 91 patients admitted to the Intermediate Care Unit of the Fundación Hospital de Jove during the first three months of 2004. Previously we created scale VACTE, making real measurements of the time inverted in the execution of each one of the cares in 50 patients. Later, a comparison was made between the APACHE II, NEMS and VACTE scales, taking as reference the scores obtained in the same ones during the first 24 hours of the stay. The statistical analysis was made by SPSS 11.0, assuming a confidence level of 95% (p < 0.05): lineal analysis of simple regression to compare the different scales; the force of its correlation with Spearman's coefficient and we compared the independent dichotomize variables with the Mann-Whitney test. The main results determined after the study were the following: regarding the scale to evaluate seriousness applied to the patients, an average APACHE II score of 12.1 +/- 5.9 was obtained. The average value with the NEMS was 19.5 +/- 5.7 and

  18. Paid part-time employment and academic performance of undergraduate nursing students.

    PubMed

    Rochford, Céire; Connolly, Michael; Drennan, Jonathan

    2009-08-01

    Nursing students are increasingly undertaking paid term-time employment to finance their living expenses and studies. However the type and duration of this part-time work is unknown; furthermore there is a limited evidence on the extent to which this part-time employment is impacting on academic performance and the student's experience of higher education. To address this shortfall this study undertook a cross-sectional survey of undergraduate nursing students to explore the incidence of student involvement in term-time employment and to develop an understanding of the relationship of employment on student's academic and clinical achievement, and on their experience of higher education. The results found that the vast majority of the sample were working in part-time employment during term-time. The average number of hours worked per week was sixteen. The number of hours worked per week was found to be a predictor of course performance, the student's experience of college and grades achieved. Students who worked greater hours reported negative outcomes in each of these three domains. The findings also support the contention that it is not working per se that has a detrimental effect on student outcomes but the numbers of hours' students are actually working while attending college. Therefore policy makers, educationalists and health service providers need to be aware of the burden that nursing students may have to contend with in combining work with their academic studies. PMID:19246132

  19. Rumination and Loneliness Independently Predict Six-Month Later Depression Symptoms among Chinese Elderly in Nursing Homes

    PubMed Central

    Gan, Pei; Xie, Yan; Duan, Wenjie; Deng, Qing; Yu, Xiuli

    2015-01-01

    Background Previous studies conducted in Western countries independently demonstrated that loneliness and rumination are remarkable risk factors of depression among the elderly in both community and nursing homes. However, knowledge on the relationship between these three constructs among the elderly in Eastern countries is scarce. The current study aims to determine the relationship between loneliness, rumination, and depression among Chinese elderly in nursing homes. Methods A total of 71 elderly participants with an average age of 82.49 years completed this six-month longitudinal study. Physical reports indicated that none of the participants were clinically depressed before the study. At Time 1, their loneliness and rumination were measured using UCLA-8 Loneliness Scale and Ruminative Responses Scale. Six months later, the participants completed the Center for Epidemiologic Studies Depression Scale to assess depressive symptoms (Time 2). Results Multiple regression analysis revealed that both loneliness and rumination at Time 1 were the predictors of depression symptoms at Time 2 among the Chinese elderly in nursing homes. However, in the mediation analysis using PROCESS, the indirect effect between loneliness at Time 1 and depression symptoms at Time 2 was insignificant. Conclusions Results suggest that previous loneliness and rumination thinking are predictors of future depression symptoms among the Chinese elderly in nursing homes. However, the insignificant mediation further suggests that the differences between loneliness and rumination should be explored in future studies. Findings have important implications for mental health professionals in nursing homes in China. PMID:26334298

  20. Family Involvement Following Institutionalization: Modeling Nursing Home Visits over Time

    ERIC Educational Resources Information Center

    Gaugler, Joseph E.; Zarit, Steven H.; Pearlin, Leonard I.

    2003-01-01

    Gerontological research has emphasized family members' continued involvement in the lives of loved ones following institutionalization. However, many of these studies are cross-sectional in design and do not ascertain how family members' visits change over time. The present study utilized a growth curve analysis to examine preplacement and…

  1. Predicting Nurses' Turnover: The Aversive Effects of Decreased Identity, Poor Interpersonal Communication, and Learned Helplessness.

    PubMed

    Moreland, Jennifer J; Ewoldsen, David R; Albert, Nancy M; Kosicki, Gerald M; Clayton, Margaret F

    2015-01-01

    Through a social identity theoretical lens, this study examines how nurses' identification with their working small group, unit, or floor, nursing role (e.g., staff ER nurse, nurse practitioner), and nursing profession relate to nurses' interaction involvement, willingness to confront conflict, feelings of learned helplessness, and tenure (employment turnover) intentions. A cross-sectional survey (N = 466) was conducted at a large, quaternary care hospital system. Structural equation modeling uncovered direct and indirect effects between the five primary variables. Findings demonstrate direct relationships between nurse identity (as a latent variable) and interaction involvement, willingness to confront conflict, and tenure intentions. Feelings of learned helplessness are attenuated by increased nurse identity through interaction involvement and willingness to confront conflict. In addition, willingness to confront conflict and learned helplessness mediate the relationship between interaction involvement and nurses' tenure intentions. Theoretical extensions include indirect links between nurse identity and learned helplessness via interaction involvement and willingness to confront conflict. Implications for interpersonal communication theory development, health communication, and the nursing profession are discussed. PMID:26042456

  2. Resource Selection Using Execution and Queue Wait Time Predictions

    NASA Technical Reports Server (NTRS)

    Warren, Smith; Wong, Parkson; Biegel, Bryan A. (Technical Monitor)

    2002-01-01

    Computational grids provide users with many possible places to execute their applications. We wish to help users select where to run their applications by providing predictions of the execution times of applications on space shared parallel computers and predictions of when scheduling systems for such parallel computers will start applications. Our predictions are based on instance based learning techniques and simulations of scheduling algorithms. We find that our execution time prediction techniques have an average error of 37 percent of the execution times for trace data recorded from SGI Origins at NASA Ames Research Center and that this error is 67 percent lower than the error of user estimates. We also find that the error when predicting how long applications will wait in scheduling queues is 95 percent of mean queue wait times when using our execution time predictions and this is 57 percent lower than if we use user execution time estimates.

  3. Eternal inflation predicts that time will end

    SciTech Connect

    Bousso, Raphael; Freivogel, Ben; Leichenauer, Stefan; Rosenhaus, Vladimir

    2011-01-15

    Present treatments of eternal inflation regulate infinities by imposing a geometric cutoff. We point out that some matter systems reach the cutoff in finite time. This implies a nonzero probability for a novel type of catastrophe. According to the most successful measure proposals, our galaxy is likely to encounter the cutoff within the next 5x10{sup 9} years.

  4. Trends over time in prescribing by English primary care nurses: a secondary analysis of a national prescription database

    PubMed Central

    2014-01-01

    Background A growing number of countries legislate for nurses to have medication prescribing authority although it is a contested issue. The UK is one of these countries, giving authority to nurses with additional qualifications since 1992 and incrementally widened the scope of nurse prescribing, most recently in 2006. The policy intention for primary care was to improve efficiency in service delivery through flexibility between medical and nursing roles. The extent to which this has occurred is uncertain. This study investigated nurses prescribing activities, over time, in English primary care settings. Methods A secondary data analysis of a national primary care prescription database 2006-2010 and National Health Service workforce database 2010 was undertaken. Results The numbers of nurses issuing more than one prescription annually in primary care rose from 13,391 in 2006 to 15,841 in 2010. This represented forty three percent of those with prescribing qualifications and authorisation from their employers. The number of items prescribed by nurses rose from 1.1% to 1.5% of total items prescribed in primary care. The greatest volume of items prescribed by independent nurse prescribers was in the category of penicillins, followed by dressings. However, the category where independent nurse prescribers contributed the largest proportion of all primary care prescriptions was emergency contraception (9.1%). In contrast, community practitioner nurse prescribers’ greatest volume and contribution was in the category of gel and colloid dressings (27%), medicated stockings (14.5%) and incontinence appliances (4.2%). There were slightly higher rates of nurse prescribing in areas with higher levels of socio-economic deprivation and fewer physicians per capita, but the correlations were weak and warrant further investigation. Conclusions The percentage of prescriptions written by nurses in primary care in England is very small in comparison to physicians. Our findings

  5. Predicting the success of minority students in a baccalaureate nursing program.

    PubMed

    Boyle, K K

    1986-05-01

    Entering grade point average (ENTGPA), American College Test Assessment (ACT), high school rank (HSRANK), high school GPA (HSGPA), number of college credit hours prior to program admission (HRSPTA), age at admission, and an index of applicant motivation and related experience (MEP) were investigated to determine the best predictive combination of variables for success among minorities in a baccalaureate nursing program. Final GPA, program completion, and State Board Examination (SBTPE) performance were used as indicators of success. Minority students (N = 145) admitted between 1971-1981 were identified by record review. Two minority subgroups, blacks (n = 111) and nonblack minorities (n = 34) were compared using multiple regression and discriminant analysis procedures. ACT was the strongest, most consistent predictor of SBTPE performance and final GPA for all minorities. ENTGPA and ACT provided substantial predictive power for both subgroups, but explained markedly less variance for blacks. HSGPA, HRSPTA, and HSRANK explained some variance differently by subgroup. ENTGPA provided the only discrimination between graduates and dropouts. Cognitive attributes are critical to academic success among minorities, although predictors may vary in explanatory power by minority group. Variables interfering with program completion need to be explored. PMID:3012033

  6. Activity-based resource allocation: a system for predicting nursing costs.

    PubMed

    Crockett, M J; DiBlasi, M; Flaherty, P; Sampson, K

    1997-01-01

    As hospital-based managers are being confronted with changing patterns of reimbursement, ranging from revenue generating to cost management, it is imperative that hospitals know the exact nursing costs associated with the actual care delivered to specific patients. Nursing care has traditionally been bundled into the room rate for patients. This approach is extremely limiting when facilities are negotiating per diem rates and capitated rate contracts. At Braintree Hospital Rehabilitation Network, the nursing department has developed and implemented an activity-based management system to determine the actual cost of nursing care provided to each patient. This approach, which differentiates nursing costs accurately by diagnostic group and by intensity of nursing care, has contributed to the hospital's success in negotiating individual patient contracts with insurers in the managed care environment that increasingly focuses on costs and outcomes. Another result has been to enhance the accuracy of the network's cost accounting system. PMID:9416189

  7. Nursing students' attitudes toward science in the nursing curricula

    NASA Astrophysics Data System (ADS)

    Maroo, Jill Deanne

    The nursing profession combines the art of caregiving with scientific concepts. Nursing students need to learn science in order to start in a nursing program. However, previous research showed that students left the nursing program, stating it included too much science (Andrew et al., 2008). Research has shown a correlation between students' attitudes and their performance in a subject (Osborne, Simon, & Collins, 2003). However, little research exists on the overall attitude of nursing students toward science. At the time of my study there existed no large scale quantitative study on my topic. The purpose of my study was to identify potential obstacles nursing students face, specifically, attitude and motivation toward learning science. According to research the nation will soon face a nursing shortage and students cite the science content as a reason for not completing the nursing program. My study explored nursing students' attitudes toward science and reasons these students are motivated to learn science. I ran a nationwide mixed methods approach with 1,402 participants for the quantitative portion and 4 participants for the qualitative portion. I validated a questionnaire in order to explore nursing students' attitudes toward science, discovered five different attitude scales in that questionnaire and determined what demographic factors provided a statistically significant prediction of a student's score. In addition, I discovered no statistical difference in attitude exists between students who have the option of taking nursing specific courses and those who do not have that option. I discovered in the qualitative interviews that students feel science is necessary in nursing but do not feel nurses are scientists. My study gives a baseline of the current attitude of nursing students toward science and why these students feel the need to learn the science.

  8. Evaluation of Fast-Time Wake Vortex Prediction Models

    NASA Technical Reports Server (NTRS)

    Proctor, Fred H.; Hamilton, David W.

    2009-01-01

    Current fast-time wake models are reviewed and three basic types are defined. Predictions from several of the fast-time models are compared. Previous statistical evaluations of the APA-Sarpkaya and D2P fast-time models are discussed. Root Mean Square errors between fast-time model predictions and Lidar wake measurements are examined for a 24 hr period at Denver International Airport. Shortcomings in current methodology for evaluating wake errors are also discussed.

  9. The Part-Time Student Role: Implications for the Emotional Experience of Managing Multiple Roles amongst Hong Kong Public Health Nurses.

    ERIC Educational Resources Information Center

    Shiu, Ann Tak-Ying

    1999-01-01

    Nine public-health nurses studying part time and 11 other nurses sampled their mood states randomly over seven days. The part-time student role created additional strain for nurses with children. The stress of managing multiple roles was greatest when both work and nonwork role responsibilities were heavy. (SK)

  10. Work–Family Conflict, Task Interruptions, and Influence at Work Predict Musculoskeletal Pain in Operating Room Nurses

    PubMed Central

    Nützi, Marina; Koch, Patricia; Baur, Heiner; Elfering, Achim

    2015-01-01

    Background The aim of this study is to examine the prevalence of musculoskeletal complaints in Swiss operating room (OR) nurses, and to investigate how work–family conflict, work interruptions, and influence at work are related to lumbar and cervical back pain. Methods Participants in this correlational questionnaire study included 116 OR nurses from eight different hospitals in Switzerland. Results We found that 66% of the OR staff suffered from musculoskeletal problems. The most prevalent musculoskeletal complaints were lumbar (52.7%) and cervical pain (38.4%). Furthermore, 20.5% reported pain in the mid spine region, 20.5% in the knees and legs, and 9.8% in the hands and feet. Multiple linear regression analyses showed that work–family conflict (p < 0.05) and interruptions (p < 0.05) significantly predicted lumbar and cervical pain in OR nurses, while influence at work (p < 0.05) only predicted lumbar pain. Conclusion These results suggest that reducing the work–family conflict and interruptions at work, as well as offering opportunities to influence one's workplace, help to promote OR nurses' health. PMID:26929846

  11. PREDICTING EVAPORATION RATES AND TIMES FOR SPILLS OF CHEMICAL MIXTURES

    EPA Science Inventory


    Spreadsheet and short-cut methods have been developed for predicting evaporation rates and evaporation times for spills (and constrained baths) of chemical mixtures. Steady-state and time-varying predictions of evaporation rates can be made for six-component mixtures, includ...

  12. ISOL Yield Predictions from Holdup-Time Measurements

    SciTech Connect

    Spejewski, Eugene H.; Carter, H Kennon; Mervin, Brenden T.; Prettyman, Emily S.; Kronenberg, Andreas; Stracener, Daniel W

    2008-01-01

    A formalism based on a simple model is derived to predict ISOL yields for all isotopes of a given element based on a holdup-time measurement of a single isotope of that element. Model predictions, based on parameters obtained from holdup-time measurements, are compared to independently-measured experimental values.

  13. Prediction of the shock arrival time with SEP observations

    NASA Astrophysics Data System (ADS)

    Qin, G.; Zhang, M.; Rassoul, H. K.

    2009-09-01

    Real-time prediction of the arrival times at Earth of shocks is very important for space weather research. Recently, various models for shock propagation are used to forecast the shock arriving times (SATs) with information of initial coronal shock and flare from near real-time radio and X-ray data. In this paper, we add the use of solar energetic particles (SEP) observation to improve the shock arrival time (SAT) prediction. High-energy SEPs originating from flares move to the Earth much faster than the shocks related to the same flares. We develop an SAT prediction model by combining a well-known shock propagation model, STOA, and the analysis of SEPs detected at Earth. We demonstrate that the SAT predictions are improved by the new model with the help of 38-53 keV electron SEP observations. In particular, the correct prediction to false alarm ratio is improved significantly.

  14. Stressors associated with qualified nurses undertaking part-time degree programmes--some implications for nurse managers to consider.

    PubMed

    Timmins, Fiona; Nicholl, Honor

    2005-11-01

    The aim of this exploratory study was to explore and describe aspects of the programme that caused stress to students and suggested measures for reducing this stress. Perceived personal and professional benefits were also explored. A descriptive exploratory study utilizing a survey design was utilized. Stressors associated with the programme included trying to balance work commitments and the required study emerged as the number one stressor. "Balancing" was a significant feature of many of these nurses' lives. Meeting work commitments in addition to study was a reported stressor for almost every nurse. Employers and managers within the health care setting need to be responsive to the needs of nurses undertaking postregistration study, and explore flexible working options and aim to provide support and encouragement to nurses who are motivated towards study. Results indicate overall benefits for both the nurses' personal and professional practice, therefore adequate infrastructure to suitably support these nurses is required that may have potential benefits for patient/client care. PMID:16238688

  15. On-time clinical phenotype prediction based on narrative reports

    PubMed Central

    Bejan, Cosmin A.; Vanderwende, Lucy; Evans, Heather L.; Wurfel, Mark M.; Yetisgen-Yildiz, Meliha

    2013-01-01

    In this paper we describe a natural language processing system which is able to predict whether or not a patient exhibits a specific phenotype using the information extracted from the narrative reports associated with the patient. Furthermore, the phenotypic annotations from our report dataset were performed at the report level which allows us to perform the prediction of the clinical phenotype at any point in time during the patient hospitalization period. Our experiments indicate that an important factor in achieving better results for this problem is to determine how much information to extract from the patient reports in the time interval between the patient admission time and the current prediction time. PMID:24551325

  16. Time for realistic job previews in nursing as a recruitment and retention tool.

    PubMed

    Gilmartin, Mattia J; Aponte, Priscilla C; Nokes, Kathleen

    2013-01-01

    Realistic job previews are well-established, cost-effective, and evidence-based recruitment and retention tools that nurses in professional development have largely overlooked. A realistic job preview for experienced staff nurses pioneering the Clinical Nurse Leader® role is presented along with implications for nursing professional development practice. PMID:24060656

  17. Factors Predicting Lawsuits against Nursing Homes in Florida 1997-2001

    ERIC Educational Resources Information Center

    Johnson, Christopher E.; Dobalian, Aram; Burkhard, Janet; Hedgecock, Deborah K.; Harman, Jeffrey

    2004-01-01

    Purpose: We explore how nursing home characteristics affect the number of lawsuits filed against the facilities in Florida during the period from 1997 to 2001. Design and Methods: We examined data from 478 nursing homes in 30 Florida counties from 1997 to 2001. We obtained the data from Westlaw's Adverse Filings: Lawsuits database, the Online…

  18. The Effectiveness of Six Personality Variables in Predicting Success on the Nursing State Board Examination.

    ERIC Educational Resources Information Center

    Cusick, Patricia; Harckham, Laura D.

    A study was conducted to determine whether six personality variables, presently used in admissions decisions by a nursing school, were effective predictors of success on the State Board Examination (SBE), the nursing licensing examination. The personality variables were measured by subtests of the Personal Preference Schedule of the Psychological…

  19. Psychological Distress among Nursing, Physiotherapy and Occupational Therapy Students: A Longitudinal and Predictive Study

    ERIC Educational Resources Information Center

    Nerdrum, Per; Rustoen, Tone; Helge Ronnestad, Michael

    2009-01-01

    In this study, we present longitudinal data on changes in psychological distress among 232 Norwegian undergraduate students of nursing, physiotherapy, and occupational therapy. Psychological distress was assessed by applying the 12-item version of the General Health Questionnaire. Nursing students became substantially more distressed during the…

  20. Characteristics Predicting Nursing Home Admission in the Program of All-Inclusive Care for Elderly People

    ERIC Educational Resources Information Center

    Friedman, Susan M.; Steinwachs, Donald M.; Rathouz, Paul J.; Burton, Lynda C.; Mukamel, Dana B.

    2005-01-01

    Long term care in a nursing home prior to enrollment in PACE remain at high risk of readmission, despite the availability of comprehensive services. This study determined overall risk and predictors of long-term nursing home admission within the Program of All-Inclusive Care for the Elderly (PACE). Design and Methods: Data PACE records for 4,646…

  1. Method for Predicting Which Customers' Time Deposit Balances Will Increase

    NASA Astrophysics Data System (ADS)

    Ono, Toshiyuki; Yoshikawa, Hiroshi; Morita, Masahiro; Komoda, Norihisa

    This paper proposes a method of predicting which customers' account balances will increase by using data mining to effectively and efficiently promote sales. Prediction by mining all the data in a business is difficult because of much time required to collect, process, and calculate it. The selection of which features are used for prediction is a critical issue. We propose a method of selecting features to improve the accuracy of prediction within practical time limits. It consists of three parts: (1) converting collected features into financial behavior features that reflect customer actions, (2) extracting features affecting increases in account balances from these collected and financial behavior features, and (3) predicting customers whose account balances will increase based on the extracted features. We found the accuracy of prediction in an experiment with our method to be higher than with other conventional methods.

  2. Nurses' daily life: gender relations from the time spent in hospital1

    PubMed Central

    Pereira, Audrey Vidal

    2015-01-01

    Objective: to analyze the everyday life of nurses through the sexual work division as well as through interdependence relations and the time in hospital. Method: quanti-qualitative study, based on the Time Use Survey and in Norbert Elias's Configuration Theory of Interdependencies. Daily shifts distribution record, directed by 42 participants - with self-confrontation - by interviews which drew dialogues on subjective aspects of the everyday experiences related to use of time, based on a job at a university hospital. The theoretical intake that founded data analysis was based on concepts of conflicts of interest, power struggles, sexual work division and polychronic-monochronic concepts - whether the work environment demands multitasking nurses or not. Results: time records allowed to observe differences between the groups studied, useful to identify conflicts, tensions, power struggles and gender inequalities in interviewees' everyday affairs that do not only affect physical and mental health, but also their way of life. Conclusion: the analytical path pointed out the need for public policies that promote equity in gender relations, keeping at sight the exercise of plural discourses and tolerant stances capable to respect differences between individual and collective time. PMID:26487146

  3. Effect of Intravenous (IV) Assistive Device (VeinViewer) on IV Access Attempts, Procedural Time, and Patient and Nurse Satisfaction.

    PubMed

    Ramer, Lois; Hunt, Pauline; Ortega, Erin; Knowlton, Jessica; Briggs, Raymond; Hirokawa, Shinichi

    2016-07-01

    This study evaluated the effectiveness of VeinViewer for peripheral vascular accessing a pediatric hematology oncology clinic. After obtaining consent, 53 patients were randomly assigned to either the VeinViewer group (n = 27) or standard methods group (n = 26). Data on number of attempts, procedural time, access complications, and patient and nurse satisfaction were collected. Patients randomized to the VeinViewer group required significantly less time to access a vein as compared with the standard methods group (P ≤ .05). Additionally, these patients rated nurses as having significantly more skill than nurses who did not use VeinViewer (P ≤ .05) and assigned significantly higher scores for "overall experience"(P ≤ .05). Responses by nurses using VeinViewer overall saw the device in a positive light. PMID:26510643

  4. Weight Suppression Predicts Time to Remission from Bulimia Nervosa

    ERIC Educational Resources Information Center

    Lowe, Michael R.; Berner, Laura A.; Swanson, Sonja A.; Clark, Vicki L.; Eddy, Kamryn T.; Franko, Debra L.; Shaw, Jena A.; Ross, Stephanie; Herzog, David B.

    2011-01-01

    Objective: To investigate whether, at study entry, (a) weight suppression (WS), the difference between highest past adult weight and current weight, prospectively predicts time to first full remission from bulimia nervosa (BN) over a follow-up period of 8 years, and (b) weight change over time mediates the relationship between WS and time to first…

  5. Nonstationary time series prediction combined with slow feature analysis

    NASA Astrophysics Data System (ADS)

    Wang, G.; Chen, X.

    2015-07-01

    Almost all climate time series have some degree of nonstationarity due to external driving forces perturbing the observed system. Therefore, these external driving forces should be taken into account when constructing the climate dynamics. This paper presents a new technique of obtaining the driving forces of a time series from the slow feature analysis (SFA) approach, and then introduces them into a predictive model to predict nonstationary time series. The basic theory of the technique is to consider the driving forces as state variables and to incorporate them into the predictive model. Experiments using a modified logistic time series and winter ozone data in Arosa, Switzerland, were conducted to test the model. The results showed improved prediction skills.

  6. Changing images of professionalism: the case of public health nurses.

    PubMed

    Bloom, J R; O'Reilly, C A; Parlette, G N

    1979-01-01

    A survey of 89 public health nurses in a California county explored factors that might account for the growing support of unions and subsequent militancy among nurses. As predicted, changes in the backgrounds of public health nurses have occurred over time: 1) older nurses are more likely to have graduated from a diploma program and to have parents of lower educational and occupational attainment than younger nurses; 2) older nurses are more likely to view nursing as a calling and less likely to desire representation in collective bargaining by the union or to believe striking professional; 3) older nurses and those from lower social class backgrounds were less likely to belong to the union and less likely to participate in a county-wide strike. Because age and parental background factors are independently related to our indicators of militancy--union membership and participation in a strike--the results are interpreted as a change in nurses' images of professionalism. PMID:420355

  7. Nurses' and Nursing Students' Knowledge and Attitudes regarding Pediatric Pain

    PubMed Central

    Ortiz, Mario I.; Ponce-Monter, Héctor A.; Rangel-Flores, Eduardo; Castro-Gamez, Blanca; Romero-Quezada, Luis C.; O'Brien, Jessica P.; Romo-Hernández, Georgina; Escamilla-Acosta, Marco A.

    2015-01-01

    Nursing staff spend more time with patients with pain than any other health staff member. For this reason, the nurse must possess the basic knowledge to identify the presence of pain in patients, to measure its intensity and make the steps necessary for treatment. Therefore, a prospective, descriptive, analytical, and cross-sectional study was conducted to investigate the knowledge and attitudes regarding pediatric pain in two different populations. The questionnaire, Pediatric Nurses Knowledge and Attitudes Survey Regarding Pain (PKNAS), was applied to 111 hospital pediatric nurses and 300 university nursing students. The final scores for pediatric nurses and nursing students were 40.1 ± 7.9 and 40.3 ± 7.5, respectively. None of the sociodemographic variables predicted the scores obtained by the participants (P > 0.05). There was a high correlation between the PKNAS scores of pediatric nurses and nursing students (r = 0.86, P < 0.001). It was observed that the degree of knowledge about pain and its treatment was very low in both groups. Due to this deficiency, pain in children remains inadequately managed, which leads to suffering in this population. It is necessary to increase the continued training in this subject in both areas. PMID:26543643

  8. Nurses' and Nursing Students' Knowledge and Attitudes regarding Pediatric Pain.

    PubMed

    Ortiz, Mario I; Ponce-Monter, Héctor A; Rangel-Flores, Eduardo; Castro-Gamez, Blanca; Romero-Quezada, Luis C; O'Brien, Jessica P; Romo-Hernández, Georgina; Escamilla-Acosta, Marco A

    2015-01-01

    Nursing staff spend more time with patients with pain than any other health staff member. For this reason, the nurse must possess the basic knowledge to identify the presence of pain in patients, to measure its intensity and make the steps necessary for treatment. Therefore, a prospective, descriptive, analytical, and cross-sectional study was conducted to investigate the knowledge and attitudes regarding pediatric pain in two different populations. The questionnaire, Pediatric Nurses Knowledge and Attitudes Survey Regarding Pain (PKNAS), was applied to 111 hospital pediatric nurses and 300 university nursing students. The final scores for pediatric nurses and nursing students were 40.1 ± 7.9 and 40.3 ± 7.5, respectively. None of the sociodemographic variables predicted the scores obtained by the participants (P > 0.05). There was a high correlation between the PKNAS scores of pediatric nurses and nursing students (r = 0.86, P < 0.001). It was observed that the degree of knowledge about pain and its treatment was very low in both groups. Due to this deficiency, pain in children remains inadequately managed, which leads to suffering in this population. It is necessary to increase the continued training in this subject in both areas. PMID:26543643

  9. Time evolution of predictability of epidemics on networks

    NASA Astrophysics Data System (ADS)

    Holme, Petter; Takaguchi, Taro

    2015-04-01

    Epidemic outbreaks of new pathogens, or known pathogens in new populations, cause a great deal of fear because they are hard to predict. For theoretical models of disease spreading, on the other hand, quantities characterizing the outbreak converge to deterministic functions of time. Our goal in this paper is to shed some light on this apparent discrepancy. We measure the diversity of (and, thus, the predictability of) outbreak sizes and extinction times as functions of time given different scenarios of the amount of information available. Under the assumption of perfect information—i.e., knowing the state of each individual with respect to the disease—the predictability decreases exponentially, or faster, with time. The decay is slowest for intermediate values of the per-contact transmission probability. With a weaker assumption on the information available, assuming that we know only the fraction of currently infectious, recovered, or susceptible individuals, the predictability also decreases exponentially most of the time. There are, however, some peculiar regions in this scenario where the predictability decreases. In other words, to predict its final size with a given accuracy, we would need increasingly more information about the outbreak.

  10. Kalman Filtering USNO's GPS Observations for Improved Time Transfer Predictions

    NASA Technical Reports Server (NTRS)

    Hutsell, Steven T.

    1996-01-01

    The Global Positioning System (GPS) Master Control Station (MCS) performs the Coordinated Universal Time (UTC) time transfer mission by uploading and broadcasting predictions of the GPS-UTC offset in subframe 4 of the GS navigation message. These predictions are based on only two successive daily data points obtained from the US Naval Observatory (USNO). USNO produces these daily smoothed data points by performing a least-squares fit on roughly 38 hours worth of data from roughly 160 successive 13-minute tracks of GPS satellites. Though sufficient for helping to maintain a time transfer error specification of 28 ns (1 Sigma), the MCS's prediction algorithm does not make the best use of the available data from from USNO, and produces data that can degrade quickly over extended prediction spans. This paper investigates how, by applying Kalman filtering to the same available tracking data, the MCS could improve its estimate of GPS-UTC, and in particular, the GPS-UTC A(sub 1) term. By refining the A(sub 1) (frequency) estimate for GPS-UTC predictions, error in GPS time transfer could drop significantly. Additional, the risk of future spikes in GPS's time transfer error could similarly be minimized, by employing robust Kalman filtering for GPS-UTC predictions.

  11. Time-Motion Analysis of Clinical Nursing Documentation During Implementation of an Electronic Operating Room Management System for Ophthalmic Surgery

    PubMed Central

    Read-Brown, Sarah; Sanders, David S.; Brown, Anna S.; Yackel, Thomas R.; Choi, Dongseok; Tu, Daniel C.; Chiang, Michael F.

    2013-01-01

    Efficiency and quality of documentation are critical in surgical settings because operating rooms are a major source of revenue, and because adverse events may have enormous consequences. Electronic health records (EHRs) have potential to impact surgical volume, quality, and documentation time. Ophthalmology is an ideal domain to examine these issues because procedures are high-throughput and demand efficient documentation. This time-motion study examines nursing documentation during implementation of an EHR operating room management system in an ophthalmology department. Key findings are: (1) EHR nursing documentation time was significantly worse during early implementation, but improved to a level near but slightly worse than paper baseline, (2) Mean documentation time varied significantly among nurses during early implementation, and (3) There was no decrease in operating room turnover time or surgical volume after implementation. These findings have important implications for ambulatory surgery departments planning EHR implementation, and for research in system design. PMID:24551402

  12. Predicting the time derivative of local magnetic perturbations

    NASA Astrophysics Data System (ADS)

    Tóth, Gábor; Meng, Xing; Gombosi, Tamas I.; Rastätter, Lutz

    2014-01-01

    Some of the potentially most destructive effects of severe space weather storms are caused by the geomagnetically induced currents. Geomagnetically induced currents (GICs) can cause failures of electric transformers and result in widespread blackouts. GICs are induced by the time variability of the magnetic field and are closely related to the time derivative of the local magnetic field perturbation. Predicting dB/dt is rather challenging, since the local magnetic perturbations and their time derivatives are both highly fluctuating quantities, especially during geomagnetic storms. The currently available first principles-based and empirical models cannot predict the detailed minute-scale or even faster time variation of the local magnetic field. On the other hand, Pulkkinen et al. (2013) demonstrated recently that several models can predict with positive skill scores whether the horizontal component of dB/dt at a given magnetometer station will exceed some threshold value in a 20 min time interval. In this paper we investigate if one can improve the efficiency of the prediction further. We find that the Space Weather Modeling Framework, the best performing among the five models compared by Pulkkinen et al. (2013), shows significantly better skill scores in predicting the magnetic perturbation than predicting its time derivative, especially for large deviations. We also find that there is a strong correlation between the magnitude of dB/dt and the magnitude of the horizontal magnetic perturbation itself. Combining these two results one can devise an algorithm that gives better skill scores for predicting dB/dt exceeding various thresholds in 20 min time intervals than the direct approach.

  13. Changing Times: A Survey of Registered Nurses in 1998. IES Report 351.

    ERIC Educational Resources Information Center

    Smith, G.; Seccombe, I.

    A national survey of registered nurses and analysis of official statistics provided an overview of the dimensions and dynamics of the labor market for nurses in the United Kingdom. Findings indicated the following: enrollment in preregistration nurse training courses decreased by 27 percent over the 1990s; initial entries to the UK Central Council…

  14. Predicting Lawsuits against Nursing Homes in the United States, 1997–2001

    PubMed Central

    Johnson, Christopher E; Dobalian, Aram; Burkhard, Janet; Hedgecock, Deborah K; Harman, Jeffrey

    2004-01-01

    Objectives To examine how nursing home characteristics impacted the number of lawsuits filed against the facilities in the United States during 1997–2001. Data Sources/Study Setting A stratified random sample of 2,378 nursing home in 45 states from 1997–2001. Data were obtained from Westlaw's Adverse Filings: Lawsuits database, the Centers for Medicare and Medicaid Services' (CMS) Online Survey, Certification, and Reporting (OSCAR) database, state complaint surveys, and through primary data. Study Design Negative binomial regression was used to explain total lawsuit variance by year. Explanatory variables included (a) facility characteristics—including staffing, number of beds, multistate system membership, for-profit ownership, (b) quality indicators—including total number and type of quality survey deficiencies, pressure sore development, and (c) market area—state has resident rights statutes, state complaint information. Resident acuity levels and year effects were controlled for. Data Collection/Extraction Methods Nursing homes were identified and linked to Westlaw data that was searched for the number of lawsuits filed against the home, and then linked to OSCAR data and a primary data analysis of multistate chain membership. Principal Findings Staffing levels for certified nursing assistants (CNAs) and registered nurses (RNs) and multistate chain membership were negatively related with higher numbers of lawsuits. More deficiencies on the licensing survey, larger, for-profit nursing homes, and being located in resident rights states were positively related with higher numbers of lawsuits. Conclusion This study suggests that nursing homes that meet long-stay staffing standards and minimum quality indicators, are nonprofit, smaller, and not located in resident rights states will experience fewer lawsuits. PMID:15533183

  15. Advanced propeller noise prediction in the time domain

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Dunn, M. H.; Spence, P. L.

    1992-01-01

    The time domain code ASSPIN gives acousticians a powerful technique of advanced propeller noise prediction. Except for nonlinear effects, the code uses exact solutions of the Ffowcs Williams-Hawkings equation with exact blade geometry and kinematics. By including nonaxial inflow, periodic loading noise, and adaptive time steps to accelerate computer execution, the development of this code becomes complete.

  16. Real-time Tsunami Inundation Prediction Using High Performance Computers

    NASA Astrophysics Data System (ADS)

    Oishi, Y.; Imamura, F.; Sugawara, D.

    2014-12-01

    Recently off-shore tsunami observation stations based on cabled ocean bottom pressure gauges are actively being deployed especially in Japan. These cabled systems are designed to provide real-time tsunami data before tsunamis reach coastlines for disaster mitigation purposes. To receive real benefits of these observations, real-time analysis techniques to make an effective use of these data are necessary. A representative study was made by Tsushima et al. (2009) that proposed a method to provide instant tsunami source prediction based on achieving tsunami waveform data. As time passes, the prediction is improved by using updated waveform data. After a tsunami source is predicted, tsunami waveforms are synthesized from pre-computed tsunami Green functions of linear long wave equations. Tsushima et al. (2014) updated the method by combining the tsunami waveform inversion with an instant inversion of coseismic crustal deformation and improved the prediction accuracy and speed in the early stages. For disaster mitigation purposes, real-time predictions of tsunami inundation are also important. In this study, we discuss the possibility of real-time tsunami inundation predictions, which require faster-than-real-time tsunami inundation simulation in addition to instant tsunami source analysis. Although the computational amount is large to solve non-linear shallow water equations for inundation predictions, it has become executable through the recent developments of high performance computing technologies. We conducted parallel computations of tsunami inundation and achieved 6.0 TFLOPS by using 19,000 CPU cores. We employed a leap-frog finite difference method with nested staggered grids of which resolution range from 405 m to 5 m. The resolution ratio of each nested domain was 1/3. Total number of grid points were 13 million, and the time step was 0.1 seconds. Tsunami sources of 2011 Tohoku-oki earthquake were tested. The inundation prediction up to 2 hours after the

  17. Prospects for eruption prediction in near real-time

    USGS Publications Warehouse

    Voight, B.; Cornelius, R.R.

    1991-01-01

    THE 'materials science' method for eruption prediction1-3 arises from the application of a general law governing the failure of materials: ??-?? ??-A=0, where A and ?? are empirical constants, and ?? is an observable quantity such as ground deformation, seismicity or gas emission. This law leads to the idea of the 'inverse-rate' plot, in which the time of failure can be estimated by extrapolation of the curve of ??-1 versus time to a pre-deter-mined intercept. Here we suggest that this method can be combined with real-time seismic amplitude monitoring to provide a tool for near-real-time eruption prediction, and we demonstrate how it might have been used to predict two dome-growth episodes at Mount St Helens volcano in 1985 and 1986, and two explosive eruptions at Redoubt volcano in 1989-90.

  18. The effect of word predictability on reading time is logarithmic.

    PubMed

    Smith, Nathaniel J; Levy, Roger

    2013-09-01

    It is well known that real-time human language processing is highly incremental and context-driven, and that the strength of a comprehender's expectation for each word encountered is a key determinant of the difficulty of integrating that word into the preceding context. In reading, this differential difficulty is largely manifested in the amount of time taken to read each word. While numerous studies over the past thirty years have shown expectation-based effects on reading times driven by lexical, syntactic, semantic, pragmatic, and other information sources, there has been little progress in establishing the quantitative relationship between expectation (or prediction) and reading times. Here, by combining a state-of-the-art computational language model, two large behavioral data-sets, and non-parametric statistical techniques, we establish for the first time the quantitative form of this relationship, finding that it is logarithmic over six orders of magnitude in estimated predictability. This result is problematic for a number of established models of eye movement control in reading, but lends partial support to an optimal perceptual discrimination account of word recognition. We also present a novel model in which language processing is highly incremental well below the level of the individual word, and show that it predicts both the shape and time-course of this effect. At a more general level, this result provides challenges for both anticipatory processing and semantic integration accounts of lexical predictability effects. And finally, this result provides evidence that comprehenders are highly sensitive to relative differences in predictability - even for differences between highly unpredictable words - and thus helps bring theoretical unity to our understanding of the role of prediction at multiple levels of linguistic structure in real-time language comprehension. PMID:23747651

  19. Obtaining a Foundation for Nursing Care at the Time of Patient Admission: A Grounded Theory Study

    PubMed Central

    Jansson, Inger; Pilhammar, Ewa; Forsberg, Anna

    2009-01-01

    The nursing process can be viewed as a problem-solving model, but we do not know whether use of the whole process including care plans with interventions based on nursing diagnoses improves nurses’ ability to carry out assessments. Therefore, the aim of this study was to illuminate and describe the assessment and decision-making process performed by nurses who formulated individual care plans including nursing diagnosis, goals and interventions or who used standardized care plans when a patient was admitted to their ward for care, and those who did not. Data collection and analysis were carried out by means of Grounded theory. Nurses were observed while assessing patients, after which they were interviewed. The main concern of all nurses was to obtain a foundation for nursing care based on four strategies; building pre-understanding, creating a caring environment, collecting information on symptoms and signs and performing an analysis from different perspectives. It appeared that the most important aspect for nurses who did not employ care plans was the medical reason for the patient’s admission. The nurses who employed care plans discussed their decisions in terms of nursing problems, needs and risks. The results indicate that nurses who formulated care plans were more aware of their professional role. PMID:19746207

  20. Attrition of full-time faculty from schools of nursing with baccalaureate and graduate programs, 2010 to 2011.

    PubMed

    Fang, Di; Bednash, Geraldine D

    2014-01-01

    The shortage of qualified faculty has been consistently reported as a major barrier impeding acceptance of all qualified applicants into nursing programs. In addition to faculty recruitment, the attrition of faculty is also a concern for schools of nursing. In this study, we found that nationally 11.8% of full-time faculty who worked in 2010 left their full-time jobs by 2011. Nearly half of total attrition, or 5.7% of full-time faculty members, were related to leaving for nonacademic nursing positions, whereas another 20% of attrition, or 2.4% of full-time faculty, resulted from retirement. Nearly 20% of faculty egressions, or 2.2% of full-time faculty, was due to leaving for nursing administrative positions or full-time faculty positions in an academic setting. Leaving for part-time faculty positions made up slightly more than 10% of faculty attrition or 1.3% of full-time faculty. Our bivariate analysis identifies distinctive academic and demographic profiles of faculty who left full-time positions for different reasons, and our multivariate analysis further shows that different individual and institutional attributes are significantly associated with different types of attrition. PMID:24564921

  1. Financial Time Series Prediction Using Elman Recurrent Random Neural Networks

    PubMed Central

    Wang, Jie; Wang, Jun; Fang, Wen; Niu, Hongli

    2016-01-01

    In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices. PMID:27293423

  2. Symplectic geometry spectrum regression for prediction of noisy time series

    NASA Astrophysics Data System (ADS)

    Xie, Hong-Bo; Dokos, Socrates; Sivakumar, Bellie; Mengersen, Kerrie

    2016-05-01

    We present the symplectic geometry spectrum regression (SGSR) technique as well as a regularized method based on SGSR for prediction of nonlinear time series. The main tool of analysis is the symplectic geometry spectrum analysis, which decomposes a time series into the sum of a small number of independent and interpretable components. The key to successful regularization is to damp higher order symplectic geometry spectrum components. The effectiveness of SGSR and its superiority over local approximation using ordinary least squares are demonstrated through prediction of two noisy synthetic chaotic time series (Lorenz and Rössler series), and then tested for prediction of three real-world data sets (Mississippi River flow data and electromyographic and mechanomyographic signal recorded from human body).

  3. Symplectic geometry spectrum regression for prediction of noisy time series.

    PubMed

    Xie, Hong-Bo; Dokos, Socrates; Sivakumar, Bellie; Mengersen, Kerrie

    2016-05-01

    We present the symplectic geometry spectrum regression (SGSR) technique as well as a regularized method based on SGSR for prediction of nonlinear time series. The main tool of analysis is the symplectic geometry spectrum analysis, which decomposes a time series into the sum of a small number of independent and interpretable components. The key to successful regularization is to damp higher order symplectic geometry spectrum components. The effectiveness of SGSR and its superiority over local approximation using ordinary least squares are demonstrated through prediction of two noisy synthetic chaotic time series (Lorenz and Rössler series), and then tested for prediction of three real-world data sets (Mississippi River flow data and electromyographic and mechanomyographic signal recorded from human body). PMID:27300890

  4. Financial Time Series Prediction Using Elman Recurrent Random Neural Networks.

    PubMed

    Wang, Jie; Wang, Jun; Fang, Wen; Niu, Hongli

    2016-01-01

    In recent years, financial market dynamics forecasting has been a focus of economic research. To predict the price indices of stock markets, we developed an architecture which combined Elman recurrent neural networks with stochastic time effective function. By analyzing the proposed model with the linear regression, complexity invariant distance (CID), and multiscale CID (MCID) analysis methods and taking the model compared with different models such as the backpropagation neural network (BPNN), the stochastic time effective neural network (STNN), and the Elman recurrent neural network (ERNN), the empirical results show that the proposed neural network displays the best performance among these neural networks in financial time series forecasting. Further, the empirical research is performed in testing the predictive effects of SSE, TWSE, KOSPI, and Nikkei225 with the established model, and the corresponding statistical comparisons of the above market indices are also exhibited. The experimental results show that this approach gives good performance in predicting the values from the stock market indices. PMID:27293423

  5. A real time monitoring system of ringer's solution residual amount for automatic nursing in hopsitals

    NASA Astrophysics Data System (ADS)

    Kwon, Jong-Won; Ha, Kwan-Yong; Nam, Chul; Ayurzana, Odgelral; Kim, Hie-Sik

    2005-12-01

    A real-time embedded system was developed for remote monitoring and checking the residual quantity and changing of Ringer's solution. It is monitored nurses' room. A Load Cell was applied as a sensor to check the residual quantity of Ringer's solution. This Load Cell detects the physical changes of Ringer's solution and transfers electronic signal to the amplifier. Amplified analog signal is converted into digital signal by A/D converter. Developed Embedded system, which computes these data with microprocess (8052) then makes it possible to monitor the residual quantity of Ringer's solution real-time on a server computer. A Checking system on Residual Quantity of Ringer's Solution Using Load cell cut costs using a simple design for a circuit.

  6. Time dependent patient no-show predictive modelling development.

    PubMed

    Huang, Yu-Li; Hanauer, David A

    2016-05-01

    Purpose - The purpose of this paper is to develop evident-based predictive no-show models considering patients' each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach - A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings - The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications - The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value - This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients' show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows. PMID:27142954

  7. Evaluation of Time Management Behaviors and Its Related Factors in the Senior Nurse Managers, Kermanshah-Iran

    PubMed Central

    Ziapour, Arash; Khatony, Alireza; Jafari, Faranak; Kianipour, Neda

    2015-01-01

    Background and Objective: Time management is an extensive concept that is associated with promoting the performance of managers. The present study was carried out to investigate the time management behaviors along with its related factors among senior nurse mangers. Materials and Methods: In this descriptive-analytical study, 180 senior nurse managers were selected using census method. The instrument for data collection was a standard time behavior questionnaire. Data were analyzed by descriptive and analytical statistics. Results: The findings showed that among the dimensions of time management behaviors, setting objectives and prioritization, and mechanics of time management dimensions obtained the highest and lowest frequency, respectively. Comparison of the mean scores of time management behaviors indicated a significant difference in the gender (p<0.05), age (p<0.001), education (p=0.015), job experience (p<0.001), managerial experience (p<0.001) and management rank management (p<0.029). Conclusion: On the whole, senior nurse managers enjoyed a favorable time management skill. Given the importance of time management behaviors, it seems that teaching these behaviors more seriously through regular educational programs can effectively promote the performance of senior nurse managers. PMID:25716413

  8. Echoed time series predictions, neural networks and genetic algorithms

    NASA Astrophysics Data System (ADS)

    Conway, A.

    This work aims to illustrate a potentially serious and previously unrecognised problem in using Neural Networks (NNs), and possibly other techniques, to predict Time Series (TS). It also demonstrates how a new training scheme using a genetic algorithm can alleviate this problem. Although it is already established that NNs can predict TS such as Sunspot Number (SSN) with reasonable success, the accuracy of these predictions is often judged solely by an RMS or related error. The use of this type of error overlooks the presence of what we have termed echoing, where the NN outputs its most recent input as its prediction. Therefore, a method of detecting echoed predictions is introduced, called time-shifting. Reasons for the presence of echo are discussed and then related to the choice of TS sampling. Finally, a new specially designed training scheme is described, which is a hybrid of a genetic algorithm search and back propagation. With this method we have successfully trained NNs to predict without any echo.

  9. Taxi Time Prediction at Charlotte Airport Using Fast-Time Simulation and Machine Learning Techniques

    NASA Technical Reports Server (NTRS)

    Lee, Hanbong

    2016-01-01

    Accurate taxi time prediction is required for enabling efficient runway scheduling that can increase runway throughput and reduce taxi times and fuel consumptions on the airport surface. Currently NASA and American Airlines are jointly developing a decision-support tool called Spot and Runway Departure Advisor (SARDA) that assists airport ramp controllers to make gate pushback decisions and improve the overall efficiency of airport surface traffic. In this presentation, we propose to use Linear Optimized Sequencing (LINOS), a discrete-event fast-time simulation tool, to predict taxi times and provide the estimates to the runway scheduler in real-time airport operations. To assess its prediction accuracy, we also introduce a data-driven analytical method using machine learning techniques. These two taxi time prediction methods are evaluated with actual taxi time data obtained from the SARDA human-in-the-loop (HITL) simulation for Charlotte Douglas International Airport (CLT) using various performance measurement metrics. Based on the taxi time prediction results, we also discuss how the prediction accuracy can be affected by the operational complexity at this airport and how we can improve the fast time simulation model before implementing it with an airport scheduling algorithm in a real-time environment.

  10. Predicting Student Nurse Academic Failures: An Analysis of Four Baccalaureate Classes.

    ERIC Educational Resources Information Center

    Wold, Jean E.; Worth, Charles

    A study was done of pre-admission or early performance predictors of persistence versus academic failure among baccalaureate program nursing students. As part of a larger longitudinal research project, 155 students from four successive classes of students admitted to the program were studied, using multiple predictor and criterion variables. The…

  11. Predicting Nursing Home Admissions among Incontinent Older Adults: A Comparison of Residential Differences across Six Years.

    ERIC Educational Resources Information Center

    Coward, Raymond T.

    1995-01-01

    Uses data from the Longitudinal Studies on Aging (1984-90) to examine a sample who at baseline lived in community settings and reported problems with urinary incontinence (n=719). Analyses indicate that residents of less urbanized and more thinly populated nonmetropolitan counties were more likely to have a nursing home admission than others. (JPS)

  12. Predicting Operator Execution Times Using CogTool

    NASA Technical Reports Server (NTRS)

    Santiago-Espada, Yamira; Latorella, Kara A.

    2013-01-01

    Researchers and developers of NextGen systems can use predictive human performance modeling tools as an initial approach to obtain skilled user performance times analytically, before system testing with users. This paper describes the CogTool models for a two pilot crew executing two different types of a datalink clearance acceptance tasks, and on two different simulation platforms. The CogTool time estimates for accepting and executing Required Time of Arrival and Interval Management clearances were compared to empirical data observed in video tapes and registered in simulation files. Results indicate no statistically significant difference between empirical data and the CogTool predictions. A population comparison test found no significant differences between the CogTool estimates and the empirical execution times for any of the four test conditions. We discuss modeling caveats and considerations for applying CogTool to crew performance modeling in advanced cockpit environments.

  13. Broadband Trailing Edge Noise Predictions in the Time Domain. Revised

    NASA Technical Reports Server (NTRS)

    Casper, Jay; Farassat, Fereidoun

    2003-01-01

    A recently developed analytic result in acoustics, "Formulation 1B," is used to compute broadband trailing edge noise from an unsteady surface pressure distribution on a thin airfoil in the time domain. This formulation is a new solution of the Ffowcs Willliams-Hawkings equation with the loading source term, and has been shown in previous research to provide time domain predictions of broadband noise that are in excellent agreement with experimental results. Furthermore, this formulation lends itself readily to rotating reference frames and statistical analysis of broadband trailing edge noise. Formulation 1B is used to calculate the far field noise radiated from the trailing edge of a NACA 0012 airfoil in low Mach number flows, by using both analytical and experimental data on the airfoil surface. The acoustic predictions are compared with analytical results and experimental measurements that are available in the literature. Good agreement between predictions and measurements is obtained.

  14. Broadband trailing edge noise predictions in the time domain

    NASA Astrophysics Data System (ADS)

    Casper, J.; Farassat, F.

    2004-03-01

    A recently developed analytic result in acoustics, "Formulation 1B," is used to compute broadband trailing edge noise from an unsteady surface pressure distribution on a thin airfoil in the time domain. This formulation is a new solution of the Ffowcs Williams-Hawkings equation with the loading source term, and has been shown in previous research to provide time domain predictions of broadband noise that are in excellent agreement with experimental results. Furthermore, this formulation lends itself readily to rotating reference frames and statistical analysis of broadband trailing edge noise. In the present work, Formulation 1B is used to calculate the farfield noise radiated from the trailing edge of a NACA 0012 airfoil in a low Mach number flow, using both analytical and experimental data on the airfoil surface. The acoustic predictions are compared with analytical results and experimental measurements that are available in the literature. Good agreement between predictions and measurements is obtained.

  15. A Comparison of CTAS and Airline Time of Arrival Predictions

    NASA Technical Reports Server (NTRS)

    Heere, Karen R.; Zelenka, Richard E.; Hsu, Rose Y.

    1999-01-01

    A statistically-based comparison of aircraft times of arrival between Center/TRACON Automation System (CTAS) air traffic control scheduling and airline predictions is presented. CTAS is found to provide much improved values, forming the foundation for airline operational improvements, as observed during an airline field trial of a CTAS display.

  16. Long-term time series prediction using OP-ELM.

    PubMed

    Grigorievskiy, Alexander; Miche, Yoan; Ventelä, Anne-Mari; Séverin, Eric; Lendasse, Amaury

    2014-03-01

    In this paper, an Optimally Pruned Extreme Learning Machine (OP-ELM) is applied to the problem of long-term time series prediction. Three known strategies for the long-term time series prediction i.e. Recursive, Direct and DirRec are considered in combination with OP-ELM and compared with a baseline linear least squares model and Least-Squares Support Vector Machines (LS-SVM). Among these three strategies DirRec is the most time consuming and its usage with nonlinear models like LS-SVM, where several hyperparameters need to be adjusted, leads to relatively heavy computations. It is shown that OP-ELM, being also a nonlinear model, allows reasonable computational time for the DirRec strategy. In all our experiments, except one, OP-ELM with DirRec strategy outperforms the linear model with any strategy. In contrast to the proposed algorithm, LS-SVM behaves unstably without variable selection. It is also shown that there is no superior strategy for OP-ELM: any of three can be the best. In addition, the prediction accuracy of an ensemble of OP-ELM is studied and it is shown that averaging predictions of the ensemble can improve the accuracy (Mean Square Error) dramatically. PMID:24365536

  17. Predicting mortality in patients treated differently: updating and external validation of a prediction model for nursing home residents with dementia and lower respiratory infections

    PubMed Central

    Heymans, Martijn W; Mehr, David R; Kruse, Robin L; Lane, Patricia; Kowall, Neil W; Volicer, Ladislav; van der Steen, Jenny T

    2016-01-01

    Objective To evaluate whether a model that was previously developed to predict 14-day mortality for nursing home residents with dementia and lower respiratory tract infection who received antibiotics could be applied to residents who were not treated with antibiotics. Specifically, in this same data set, to update the model using recalibration methods; and subsequently examine the historical, geographical, methodological and spectrum transportability through external validation of the updated model. Design 1 cohort study was used to develop the prediction model, and 4 cohort studies from 2 countries were used for the external validation of the model. Setting Nursing homes in the Netherlands and the USA. Participants 157 untreated residents were included in the development of the model; 239 untreated residents were included in the external validation cohorts. Outcome Model performance was evaluated by assessing discrimination: area under the receiver operating characteristic curves; and calibration: Hosmer and Lemeshow goodness-of-fit statistics and calibration graphs. Further, reclassification tables allowed for a comparison of patient classifications between models. Results The original prediction model applied to the untreated residents, who were sicker, showed excellent discrimination but poor calibration, underestimating mortality. Adjusting the intercept improved calibration. Recalibrating the slope did not substantially improve the performance of the model. Applying the updated model to the other 4 data sets resulted in acceptable discrimination. Calibration was inadequate only in one data set that differed substantially from the other data sets in case-mix. Adjusting the intercept for this population again improved calibration. Conclusions The discriminative performance of the model seems robust for differences between settings. To improve calibration, we recommend adjusting the intercept when applying the model in settings where different mortality rates

  18. The use of content and timing to predict turn transitions

    PubMed Central

    Garrod, Simon; Pickering, Martin J.

    2015-01-01

    For addressees to respond in a timely fashion, they cannot simply process the speaker's utterance as it occurs and wait till it finishes. Instead, they predict both when the speaker will conclude and what linguistic forms will be used. While doing this, they must also prepare their own response. To explain this, we draw on the account proposed by Pickering and Garrod (2013a), in which addressees covertly imitate the speaker's utterance and use this to determine the intention that underlies their upcoming utterance. They use this intention to predict when and how the utterance will end, and also to drive their own production mechanisms for preparing their response. Following Arnal and Giraud (2012), we distinguish between mechanisms that predict timing and content. In particular, we propose that the timing mechanism relies on entrainment of low-frequency oscillations between speech envelope and brain. This constrains the context that feeds into the determination of the speaker's intention and hence the timing and form of the upcoming utterance. This approach typically leads to well-timed contributions, but also provides a mechanism for resolving conflicts, for example when there is unintended speaker overlap. PMID:26124728

  19. Occupational factors associated with obesity and leisure-time physical activity among nurses: A cross sectional study

    PubMed Central

    Chin, Dal Lae; Nam, Soohyun; Lee, Soo-Jeong

    2016-01-01

    Background and objective Adverse working conditions contribute to obesity and physical inactivity. The purpose of this study was to examine the associations of occupational factors with obesity and leisure-time physical activity among nurses. Methods This study used cross-sectional data of 394 nurses (mean age 48 years, 91% females, 61% white) randomly selected from the California Board of Registered Nursing list. Data on demographic and employment characteristics, musculoskeletal symptom comorbidity, physical and psychosocial occupational factors, body mass index (BMI), and physical activity were collected using postal and on-line surveys from January to July in 2013. Results Of the participants, 31% were overweight and 18% were obese; 41% engaged in regular aerobic physical activity (≥150 min/week) and 57% performed regular muscle-strengthening activity (≥2 days/week). In multivariable logistic regression models, overweight/obesity (BMI ≥ 25 kg/m2) was significantly more common among nurse managers/supervisors (OR = 2.54, 95% CI: 1.16–5.59) and nurses who worked full-time (OR = 2.18, 95% CI: 1.29–3.70) or worked ≥40 h per week (OR = 2.53, 95% CI: 1.58–4.05). Regular aerobic physical activity was significantly associated with high job demand (OR = 1.63, 95% CI: 1.06–2.51). Nurses with passive jobs (low job demand combined with low job control) were significantly less likely to perform aerobic physical activity (OR = 0.49, 95% CI: 0.26–0.93). Regular muscle-strengthening physical activity was significantly less common among nurses working on non-day shifts (OR = 0.55, 95% CI: 0.34–0.89). Physical workload was not associated with obesity and physical activity. Conclusions Our study findings suggest that occupational factors significantly contribute to obesity and physical inactivity among nurses. Occupational characteristics in the work environment should be considered in designing effective workplace health promotion programs targeting physical

  20. Real-time Neural Network predictions of geomagnetic activity indices

    NASA Astrophysics Data System (ADS)

    Bala, R.; Reiff, P. H.

    2009-12-01

    The Boyle potential or the Boyle Index (BI), Φ (kV)=10-4 (V/(km/s))2 + 11.7 (B/nT) sin3(θ/2), is an empirically-derived formula that can characterize the Earth's polar cap potential, which is readily derivable in real time using the solar wind data from ACE (Advanced Composition Explorer). The BI has a simplistic form that utilizes a non-magnetic "viscous" and a magnetic "merging" component to characterize the magnetospheric behavior in response to the solar wind. We have investigated its correlation with two of conventional geomagnetic activity indices in Kp and the AE index. We have shown that the logarithms of both 3-hr and 1-hr averages of the BI correlate well with the subsequent Kp: Kp = 8.93 log10(BI) - 12.55 along with 1-hr BI correlating with the subsequent log10(AE): log10(AE) = 1.78 log10(BI) - 3.6. We have developed a new set of algorithms based on Artificial Neural Networks (ANNs) suitable for short term space weather forecasts with an enhanced lead-time and better accuracy in predicting Kp and AE over some leading models; the algorithms omit the time history of its targets to utilize only the solar wind data. Inputs to our ANN models benefit from the BI and its proven record as a forecasting parameter since its initiation in October, 2003. We have also performed time-sensitivity tests using cross-correlation analysis to demonstrate that our models are as efficient as those that incorporates the time history of the target indices in their inputs. Our algorithms can predict the upcoming full 3-hr Kp, purely from the solar wind data and achieve a linear correlation coefficient of 0.840, which means that it predicts the upcoming Kp value on average to within 1.3 step, which is approximately the resolution of the real-time Kp estimate. Our success in predicting Kp during a recent unexpected event (22 July ’09) is shown in the figure. Also, when predicting an equivalent "one hour Kp'', the correlation coefficient is 0.86, meaning on average a prediction

  1. Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

    NASA Technical Reports Server (NTRS)

    He, Yuning

    2015-01-01

    Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

  2. Patient-care time allocation by nurse practitioners and physician assistants in the intensive care unit

    PubMed Central

    2012-01-01

    Introduction Use of nurse practitioners and physician assistants ("affiliates") is increasing significantly in the intensive care unit (ICU). Despite this, few data exist on how affiliates allocate their time in the ICU. The purpose of this study was to understand the allocation of affiliate time into patient-care and non-patient-care activity, further dividing the time devoted to patient care into billable service and equally important but nonbillable care. Methods We conducted a quasi experimental study in seven ICUs in an academic hospital and a hybrid academic/community hospital. After a period of self-reporting, a one-time monetary incentive of $2,500 was offered to 39 affiliates in each ICU in which every affiliate documented greater than 75% of their time devoted to patient care over a 6-month period in an effort to understand how affiliates allocated their time throughout a shift. Documentation included billable time (critical care, evaluation and management, procedures) and a new category ("zero charge time"), which facilitated record keeping of other patient-care activities. Results At baseline, no ICUs had documentation of 75% patient-care time by all of its affiliates. In the 6 months in which reporting was tied to a group incentive, six of seven ICUs had every affiliate document greater than 75% of their time. Individual time documentation increased from 53% to 84%. Zero-charge time accounted for an average of 21% of each shift. The most common reason was rounding, which accounted for nearly half of all zero-charge time. Sign out, chart review, and teaching were the next most common zero-charge activities. Documentation of time spent on billable activities also increased from 53% of an affiliate's shift to 63%. Time documentation was similar regardless of during which shift an affiliate worked. Conclusions Approximately two thirds of an affiliate's shift is spent providing billable services to patients. Greater than 20% of each shift is spent providing

  3. Referral and Timing of Referral to Hospice Care in Nursing Homes: The Significant Role of Staff Members

    ERIC Educational Resources Information Center

    Welch, Lisa C.; Miller, Susan C.; Martin, Edward W.; Nanda, Aman

    2008-01-01

    Purpose: Given concerns about end-of-life care for many nursing home (NH) residents, this study sought to understand factors influencing hospice referral or nonreferral as well as timing of referral. Design and Methods: We conducted semistructured interviews with personnel from seven participating NHs and two hospices. We interviewed NH directors…

  4. Instructional Design Process for a Course on Time Management for Head Nurses and Supervisors at a Veterans Administration Medical Center.

    ERIC Educational Resources Information Center

    Geering, Adrian D.

    This paper develops an instructional design process for teaching a time management course to head nurses and supervisors. (The course was conducted at the Veterans' Administration Medical Center, Lincoln, Nebraska, and was based on "A New Instructional Design Development Process for Instructors of Adults," by Mary Jane Even.) The paper covers…

  5. The Influence of Orientation, Integration, and Evaluation on Intent to Stay in Part-Time Clinical Nursing Faculty

    ERIC Educational Resources Information Center

    Carlson, Joanne S.

    2012-01-01

    The primary purpose of this study was to determine the extent to which orientation, evaluation, and integration practices, along with other select job aspects and demographic characteristics, were correlated with and explained intent to stay among part-time clinical nursing faculty. A conceptual model was developed and tested. A researcher…

  6. Politeness Strategies in Healthcare Communication at "Difficult Times": A Pragmatic Analysis of the "Manga" Discourse in "Nurse Aoi"

    ERIC Educational Resources Information Center

    Matsuoka, Rieko; Poole, Gregory

    2015-01-01

    This paper examines the ways in which healthcare professionals interact with patients' family members, and/or colleagues. The data are from healthcare discourses at difficult times found in the manga series entitled Nurse AOI. As the first step, we selected several communication scenes for analysis in terms of politeness strategies. From these…

  7. Optimal model-free prediction from multivariate time series.

    PubMed

    Runge, Jakob; Donner, Reik V; Kurths, Jürgen

    2015-05-01

    Forecasting a time series from multivariate predictors constitutes a challenging problem, especially using model-free approaches. Most techniques, such as nearest-neighbor prediction, quickly suffer from the curse of dimensionality and overfitting for more than a few predictors which has limited their application mostly to the univariate case. Therefore, selection strategies are needed that harness the available information as efficiently as possible. Since often the right combination of predictors matters, ideally all subsets of possible predictors should be tested for their predictive power, but the exponentially growing number of combinations makes such an approach computationally prohibitive. Here a prediction scheme that overcomes this strong limitation is introduced utilizing a causal preselection step which drastically reduces the number of possible predictors to the most predictive set of causal drivers making a globally optimal search scheme tractable. The information-theoretic optimality is derived and practical selection criteria are discussed. As demonstrated for multivariate nonlinear stochastic delay processes, the optimal scheme can even be less computationally expensive than commonly used suboptimal schemes like forward selection. The method suggests a general framework to apply the optimal model-free approach to select variables and subsequently fit a model to further improve a prediction or learn statistical dependencies. The performance of this framework is illustrated on a climatological index of El Niño Southern Oscillation. PMID:26066231

  8. Financial Time Series Prediction Using Spiking Neural Networks

    PubMed Central

    Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

    2014-01-01

    In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two “traditional”, rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments. PMID:25170618

  9. Predicting physical time series using dynamic ridge polynomial neural networks.

    PubMed

    Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

    2014-01-01

    Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950

  10. Program Predicts Time Courses of Human/Computer Interactions

    NASA Technical Reports Server (NTRS)

    Vera, Alonso; Howes, Andrew

    2005-01-01

    CPM X is a computer program that predicts sequences of, and amounts of time taken by, routine actions performed by a skilled person performing a task. Unlike programs that simulate the interaction of the person with the task environment, CPM X predicts the time course of events as consequences of encoded constraints on human behavior. The constraints determine which cognitive and environmental processes can occur simultaneously and which have sequential dependencies. The input to CPM X comprises (1) a description of a task and strategy in a hierarchical description language and (2) a description of architectural constraints in the form of rules governing interactions of fundamental cognitive, perceptual, and motor operations. The output of CPM X is a Program Evaluation Review Technique (PERT) chart that presents a schedule of predicted cognitive, motor, and perceptual operators interacting with a task environment. The CPM X program allows direct, a priori prediction of skilled user performance on complex human-machine systems, providing a way to assess critical interfaces before they are deployed in mission contexts.

  11. Financial time series prediction using spiking neural networks.

    PubMed

    Reid, David; Hussain, Abir Jaafar; Tawfik, Hissam

    2014-01-01

    In this paper a novel application of a particular type of spiking neural network, a Polychronous Spiking Network, was used for financial time series prediction. It is argued that the inherent temporal capabilities of this type of network are suited to non-stationary data such as this. The performance of the spiking neural network was benchmarked against three systems: two "traditional", rate-encoded, neural networks; a Multi-Layer Perceptron neural network and a Dynamic Ridge Polynomial neural network, and a standard Linear Predictor Coefficients model. For this comparison three non-stationary and noisy time series were used: IBM stock data; US/Euro exchange rate data, and the price of Brent crude oil. The experiments demonstrated favourable prediction results for the Spiking Neural Network in terms of Annualised Return and prediction error for 5-Step ahead predictions. These results were also supported by other relevant metrics such as Maximum Drawdown and Signal-To-Noise ratio. This work demonstrated the applicability of the Polychronous Spiking Network to financial data forecasting and this in turn indicates the potential of using such networks over traditional systems in difficult to manage non-stationary environments. PMID:25170618

  12. Predicting Physical Time Series Using Dynamic Ridge Polynomial Neural Networks

    PubMed Central

    Al-Jumeily, Dhiya; Ghazali, Rozaida; Hussain, Abir

    2014-01-01

    Forecasting naturally occurring phenomena is a common problem in many domains of science, and this has been addressed and investigated by many scientists. The importance of time series prediction stems from the fact that it has wide range of applications, including control systems, engineering processes, environmental systems and economics. From the knowledge of some aspects of the previous behaviour of the system, the aim of the prediction process is to determine or predict its future behaviour. In this paper, we consider a novel application of a higher order polynomial neural network architecture called Dynamic Ridge Polynomial Neural Network that combines the properties of higher order and recurrent neural networks for the prediction of physical time series. In this study, four types of signals have been used, which are; The Lorenz attractor, mean value of the AE index, sunspot number, and heat wave temperature. The simulation results showed good improvements in terms of the signal to noise ratio in comparison to a number of higher order and feedforward neural networks in comparison to the benchmarked techniques. PMID:25157950

  13. Predicting travel time and dispersion in rivers and streams

    USGS Publications Warehouse

    Jobson, H.E.

    1997-01-01

    The possibility of a contaminant being accidentally or intentionally spilled in a river is a constant concern to those using the water. Methods are developed to estimate: (1) the velocity of a contaminant in a river; (2) the rate of attenuation of the peak concentration of a conservative contaminant; and (3) the time required for a contaminant plume to pass a point. The methods are based on data collected by the U.S. Geological Survey in almost a hundred different rivers representing a wide range of sizes, slopes, and geomorphic types. Although the accuracy of the predictions can be greatly increased by performing time-of-travel studies, the emphasis of this paper is on providing methods for making estimates where few data are available. It is shown that the unit-peak concentration is well correlated with travel time and that the travel time of the leading edge averages 89% of the travel time of the peak concentration.

  14. Organizational and Individual Conditions Associated with Depressive Symptoms among Nursing Home Residents over Time

    ERIC Educational Resources Information Center

    Cassie, Kimberly M.; Cassie, William E.

    2012-01-01

    Purpose: To examine the effect of organizational culture and climate on depressive symptoms among nursing home residents. Design and Methods: Using a pooled cross-sectional design, this study examines a sample of 23 nursing homes, 1,114 employees, and 5,497 residents. Depressive symptoms were measured using the Minimum Data Set, Depression Rating…

  15. Survey of Current Academic Practices for Full-Time Postlicensure Nursing Faculty Who Teach Online

    ERIC Educational Resources Information Center

    Hanford, Karen J.

    2010-01-01

    Purpose: The purpose of this study was to determine current academic practices of compensation, workload, rewards, and tenure and promotion for nursing faculty who teach graduate and postlicensure programs that are delivered 50% to 100% online. Deans and directors who are members of the American Association of Colleges of Nursing (AACN) were the…

  16. Effectiveness of a nurse educational oral feeding programme on feeding outcomes in neonates: protocol for an interrupted time series design

    PubMed Central

    Touzet, Sandrine; Beissel, Anne; Denis, Angélique; Pillet, Fabienne; Gauthier-Moulinier, Hélène; Hommey, Sophie; Claris, Olivier

    2016-01-01

    Introduction Oral feeding is a complex physiological process. Several scales have been developed to assess the ability of the neonate to begin suck feedings and assist caregivers in determining feeding advancement. However, feeding premature neonates remains an ongoing challenge and depends above all on caregivers' feeding expertise. We will evaluate the effect of a nurse training programme on the achievement of full oral feeding with premature neonates. Methods and analysis The study design will be an interrupted time series design with 3 phases: (1) A 6-month baseline period; (2) a 22-month intervention period and (3) a 6-month postintervention period. The intervention will consist of an educational programme, for nurses and assistant nurses, on feeding patterns in neonates. The training modules will be composed of a 2-day conference, 2 interactive multidisciplinary workshops, and routine practice nurse coaching. A total of 120 nurses and 12 assistant nurses, who work at the neonatal unit during the study period, will participate in the study. All premature neonates of <34 weeks postmenstrual age (PMA) will be included. The primary outcome will be the age of tube withdrawal PMA and chronological age are taken into account. The secondary outcomes will be the transition time, length of hospital stay, competent suckle feeding without cardiorespiratory compromise, rate of neonates presenting with feeding issues or feeding rejection signs, and current neonatal pathologies or deaths during hospital stay. A segmented regression analysis will be performed to assess the impact of the programme. Ethics and dissemination Approval for the study was obtained from the Hospital Ethics Committee, and the Institutional Review Board, as well as the French Data Protection Agency. The findings from the study will be disseminated through peer-reviewed journals, national and international conference presentations and public events. Trial registration number NCT02404272 (https

  17. Time series prediction using a rational fraction neural networks

    SciTech Connect

    Lee, K.; Lee, Y.C.; Barnes, C.; Aldrich, C.H.; Kindel, J.

    1988-01-01

    An efficient neural network based on a rational fraction representation has been trained to perform time series prediction. The network is a generalization of the Volterra-Wiener network while still retaining the computational efficiency of the latter. Because of the second order convergent nature of the learning algorithm, the rational net is computationally far more efficient than multilayer networks. The rational fractional representation is, however, more restrictive than the multilayer networks.

  18. Nursing informatics: the future now.

    PubMed

    Mamta

    2014-01-01

    Technological advancements in the health care field have always impacted the health care practices. Nursing practice has also been greatly influenced by the technology. In the recent years, use of information technology including computers, handheld digital devices, internet has advanced the nursing by bridging the gap from nursing as an art to nursing as science. In every sphere of nursing practice, nursing research, nursing education and nursing informatics play a very important role. If used properly it is a way to save time, helping to provide quality nursing care and increases the proficiency of nursing personnel. PMID:25924417

  19. On time delay estimation from a sparse linear prediction perspective.

    PubMed

    He, Hongsen; Yang, Tao; Chen, Jingdong

    2015-02-01

    This paper proposes a sparse linear prediction based algorithm to estimate time difference of arrival. This algorithm unifies the cross correlation method without prewhitening and that with prewhitening via an ℓ2/ℓ1 optimization process, which is solved by an augmented Lagrangian alternating direction method. It also forms a set of time delay estimators that make a tradeoff between prewhitening and non-prewhitening through adjusting a regularization parameter. The effectiveness of the proposed algorithm is demonstrated in noisy and reverberant environments. PMID:25698037

  20. Real-time linear predictive analysis of speech using multimicroprocessors

    SciTech Connect

    Seethardman, S.; Radhakrishnan, T.; Suen, C.Y.

    1982-01-01

    Many applications of linear predictive coding (often known as LPC) of speech signals require a system capable of performing the complete LPC analysis in real time. This paper describes a pipeline network consisting of several general purpose microprocessors, primarily suitable for complete LPC analysis of a 10-pole model with a sampling frequency of 10 khz and a frame rate of 100 hz in real time. The proposed system is different from the previous systems, which either employed special purpose hardware or produced an analysis at a lower frame rate. 27 references.

  1. Real-time Adaptive Control Using Neural Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  2. Chromospheric extents predicted by time-dependent acoustic wave models

    SciTech Connect

    Cuntz, M. Heidelberg Universitaet )

    1990-01-01

    Theoretical models for chromospheric structures of late-type giant stars are computed, including the time-dependent propagation of acoustic waves. Models with short-period monochromatic shock waves as well as a spectrum of acoustic waves are discussed, and the method is applied to the stars Arcturus, Aldebaran, and Betelgeuse. Chromospheric extent, defined as the monotonic decrease with height of the time-averaged electron densities, are found to be 1.12, 1.13, and 1.22 stellar radii for the three stars, respectively; this corresponds to a time-averaged electron density of 10 to the 7th/cu cm. Predictions of the extended chromospheric obtained using a simple scaling law agree well with those obtained by the time-dependent wave models; thus, the chromospheres of all stars for which the scaling law is valid consist of the same number of pressure scale heights. 74 refs.

  3. Chromospheric extents predicted by time-dependent acoustic wave models

    NASA Technical Reports Server (NTRS)

    Cuntz, Manfred

    1990-01-01

    Theoretical models for chromospheric structures of late-type giant stars are computed, including the time-dependent propagation of acoustic waves. Models with short-period monochromatic shock waves as well as a spectrum of acoustic waves are discussed, and the method is applied to the stars Arcturus, Aldebaran, and Betelgeuse. Chromospheric extent, defined as the monotonic decrease with height of the time-averaged electron densities, are found to be 1.12, 1.13, and 1.22 stellar radii for the three stars, respectively; this corresponds to a time-averaged electron density of 10 to the 7th/cu cm. Predictions of the extended chromospheric obtained using a simple scaling law agree well with those obtained by the time-dependent wave models; thus, the chromospheres of all stars for which the scaling law is valid consist of the same number of pressure scale heights.

  4. Obesity as a Possible Risk Factor for Lost-time Injury in Registered Nurses: A Literature Review

    PubMed Central

    Jordan, Gillian; Nowrouzi-Kia, Behnam; Gohar, Basem; Nowrouzi, Behdin

    2015-01-01

    Time-loss injuries are still a major occurrence in Canada, injuring thousands of Canadian workers each year. With obesity rates on the rise across the country, as well as around the world, it is important that the possible effects of obesity in the workplace be fully understood, especially those effects linked to lost-time injuries. The aim of this paper was to evaluate predictors of workplace lost-time injuries and how they may be related to obesity or high body mass index by examining factors associated with lost-time injuries in the health care sector, a well-studied industry with the highest number of reported time loss injuries in Canada. A literature review focusing on lost-time injuries in Registered Nurses (RNs) was conducted using the keywords and terms: lost time injury, workers' compensation, occupational injury, workplace injury, injury, injuries, work, workplace, occupational, nurse, registered nurse, RN, health care, predictors, risk factors, risk, risks, cause, causes, obese, obesity, and body mass index. Data on predictors or factors associated with lost-time injuries in RNs were gathered and organized using Loisel's Work Disability Prevention Management Model and extrapolated upon using existing literature surrounding obesity in the Canadian workplace. PMID:25830063

  5. Chaos Time Series Prediction Based on Membrane Optimization Algorithms

    PubMed Central

    Li, Meng; Yi, Liangzhong; Pei, Zheng; Gao, Zhisheng

    2015-01-01

    This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ, m) and least squares support vector machine (LS-SVM) (γ, σ) by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM) broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). PMID:25874249

  6. Chaos time series prediction based on membrane optimization algorithms.

    PubMed

    Li, Meng; Yi, Liangzhong; Pei, Zheng; Gao, Zhisheng; Peng, Hong

    2015-01-01

    This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ, m) and least squares support vector machine (LS-SVM) (γ, σ) by using membrane computing optimization algorithm. It is an important basis for spectrum management to predict accurately the change trend of parameters in the electromagnetic environment, which can help decision makers to adopt an optimal action. Then, the model presented in this paper is used to forecast band occupancy rate of frequency modulation (FM) broadcasting band and interphone band. To show the applicability and superiority of the proposed model, this paper will compare the forecast model presented in it with conventional similar models. The experimental results show that whether single-step prediction or multistep prediction, the proposed model performs best based on three error measures, namely, normalized mean square error (NMSE), root mean square error (RMSE), and mean absolute percentage error (MAPE). PMID:25874249

  7. Real-time prediction of seismic ground motion (I) : real-time estimation of seismic wavefield using data assimilation technique and time evolutional prediction using Kirchhoff integral

    NASA Astrophysics Data System (ADS)

    Hoshiba, M.

    2013-05-01

    In this presentation, I propose a new approach for real-time prediction of seismic ground motion which is applicable to Earthquake Early Waning (EEW), in which hypocentral location and magnitude are not required. . Many methods of EEW are based on a network method in which hypocenter and magnitude (source parameters) are quickly determined, and then the ground motions are predicted, and warnings are issued depending on the strength of the predicted ground motion. In this method, it is necessary to determine the hypocenter and magnitude at first, and error of the source parameters leads directly to the error of the prediction. It is not easy to take the effects of rupture directivity and source extent into account, and it is impossible to fully reproduce the current wavefield from the interpreted source parameters. Time evolutional prediction is a method in which future wavefield is iteratively predicted from the wavefield at the certain time, that is u(x, t+Δt)=P(u(x, t)), where u is the wave motion at location x at lapse time t, and P is the prediction operator. Future wave motion, u(x, t+Δt), is predicted from the distribution of the current wave motion u(x, t) using P. For P, finite difference technique or boundary integral equation method, such as Kirchhoff integral, is used. Kirchhoff integral is qualitatively approximated by Huygens principle. The real time monitoring of wavefield are important for this method, but it is possible to predict ground motion without a hypocentral location and magnitude. In the time evolutional prediction, determination of detailed distribution of current wavefield is an important key, so that dense seismic observation network is required. Data assimilation is a technique to produce artificially denser network, which is widely used for numerical weather forecast and oceanography. Distribution of current wave motion is estimated from not only the current real observation of u(xi, t) where xi is the location of the i-th site, but

  8. Predicting aquifer response time for application in catchment modeling.

    PubMed

    Walker, Glen R; Gilfedder, Mat; Dawes, Warrick R; Rassam, David W

    2015-01-01

    It is well established that changes in catchment land use can lead to significant impacts on water resources. Where land-use changes increase evapotranspiration there is a resultant decrease in groundwater recharge, which in turn decreases groundwater discharge to streams. The response time of changes in groundwater discharge to a change in recharge is a key aspect of predicting impacts of land-use change on catchment water yield. Predicting these impacts across the large catchments relevant to water resource planning can require the estimation of groundwater response times from hundreds of aquifers. At this scale, detailed site-specific measured data are often absent, and available spatial data are limited. While numerical models can be applied, there is little advantage if there are no detailed data to parameterize them. Simple analytical methods are useful in this situation, as they allow the variability in groundwater response to be incorporated into catchment hydrological models, with minimal modeling overhead. This paper describes an analytical model which has been developed to capture some of the features of real, sloping aquifer systems. The derived groundwater response timescale can be used to parameterize a groundwater discharge function, allowing groundwater response to be predicted in relation to different broad catchment characteristics at a level of complexity which matches the available data. The results from the analytical model are compared to published field data and numerical model results, and provide an approach with broad application to inform water resource planning in other large, data-scarce catchments. PMID:24842053

  9. Long Term Mean Local Time of the Ascending Node Prediction

    NASA Technical Reports Server (NTRS)

    McKinley, David P.

    2007-01-01

    Significant error has been observed in the long term prediction of the Mean Local Time of the Ascending Node on the Aqua spacecraft. This error of approximately 90 seconds over a two year prediction is a complication in planning and timing of maneuvers for all members of the Earth Observing System Afternoon Constellation, which use Aqua's MLTAN as the reference for their inclination maneuvers. It was determined that the source of the prediction error was the lack of a solid Earth tide model in the operational force models. The Love Model of the solid Earth tide potential was used to derive analytic corrections to the inclination and right ascension of the ascending node of Aqua's Sun-synchronous orbit. Additionally, it was determined that the resonance between the Sun and orbit plane of the Sun-synchronous orbit is the primary driver of this error. The analytic corrections have been added to the operational force models for the Aqua spacecraft reducing the two-year 90-second error to less than 7 seconds.

  10. Predicting chaotic time series with a partial model

    NASA Astrophysics Data System (ADS)

    Hamilton, Franz; Berry, Tyrus; Sauer, Timothy

    2015-07-01

    Methods for forecasting time series are a critical aspect of the understanding and control of complex networks. When the model of the network is unknown, nonparametric methods for prediction have been developed, based on concepts of attractor reconstruction pioneered by Takens and others. In this Rapid Communication we consider how to make use of a subset of the system equations, if they are known, to improve the predictive capability of forecasting methods. A counterintuitive implication of the results is that knowledge of the evolution equation of even one variable, if known, can improve forecasting of all variables. The method is illustrated on data from the Lorenz attractor and from a small network with chaotic dynamics.

  11. Urban air pollution by odor sources: Short time prediction

    NASA Astrophysics Data System (ADS)

    Pettarin, Nicola; Campolo, Marina; Soldati, Alfredo

    2015-12-01

    A numerical approach is proposed to predict the short time dispersion of odors in the urban environment. The model is based on (i) a three dimensional computational domain describing the urban topography at fine spatial scale (1 m) and on (ii) highly time resolved (1 min frequency) meteorological data used as inflow conditions. The time dependent, three dimensional wind velocity field is reconstructed in the Eulerian framework using a fast response finite volume solver of Navier-Stokes equations. Odor dispersion is calculated using a Lagrangian approach. An application of the model to the historic city of Verona (Italy) is presented. Results confirm that this type of odor dispersion simulations can be used (i) to assess the impact of odor emissions in urban areas and (ii) to evaluate the potential mitigation produced by odor abatement systems.

  12. NASA AVOSS Fast-Time Wake Prediction Models: User's Guide

    NASA Technical Reports Server (NTRS)

    Ahmad, Nash'at N.; VanValkenburg, Randal L.; Pruis, Matthew

    2014-01-01

    The National Aeronautics and Space Administration (NASA) is developing and testing fast-time wake transport and decay models to safely enhance the capacity of the National Airspace System (NAS). The fast-time wake models are empirical algorithms used for real-time predictions of wake transport and decay based on aircraft parameters and ambient weather conditions. The aircraft dependent parameters include the initial vortex descent velocity and the vortex pair separation distance. The atmospheric initial conditions include vertical profiles of temperature or potential temperature, eddy dissipation rate, and crosswind. The current distribution includes the latest versions of the APA (3.4) and the TDP (2.1) models. This User's Guide provides detailed information on the model inputs, file formats, and the model output. An example of a model run and a brief description of the Memphis 1995 Wake Vortex Dataset is also provided.

  13. Real-time prediction of earthquake ground motion: time evolutional prediction using data assimilation and real-time correction of site amplification factors

    NASA Astrophysics Data System (ADS)

    Hoshiba, M.

    2012-12-01

    In this presentation, I propose a new approach for real-time prediction of seismic ground motion which is applicable to Earthquake Early Waning (EEW). Many methods of EEW are based on a network method in which hypocenter and magnitude (source parameters) are quickly determined (that is, interpretation of current wavefield), and then the ground motions are predicted, and warnings are issued depending on the strength of the predicted ground motion. In this method, though we can predict ground motions using a few parameters (location of hypocenter, magnitude, site factors) at any points, it is necessary to determine the hypocenter and magnitude at first, and error of the source parameters leads directly to the error of the prediction. It is not easy to take the effects of rupture directivity and source extent into account, and it is impossible to fully reproduce the current wavefield from the interpreted source parameters. In general, wave motion is predictable when boundary condition and initial condition are given. Time evolutional prediction is a method based on this approach using the current wavefield as an initial condition, that is u(x, t+Δt)=H(u(x, t)), where u is the wave motion at location x at lapse time t, and H is the prediction operator. Future wave motion, u(x, t+Δt), is predicted from the distribution of the current wave motion u(x, t) using H. For H, finite difference technique or boundary integral equation method, such as Kirchhoff integral, is used. In the time evolutional prediction, determination of detailed distribution of current wave motion is a key, so that dense seismic observation network is required. Data assimilation is a technique to produce artificially denser network, which is widely used for numerical weather prediction and oceanography. Distribution of current wave motion is estimated from not only the current real observation of u(x, t), but also the prediction of one step before, H(u(x, t-Δt)). Combination of them produces denser

  14. Two-parameter Failure Model Improves Time-independent and Time-dependent Failure Predictions

    SciTech Connect

    Huddleston, R L

    2004-01-27

    A new analytical model for predicting failure under a generalized, triaxial stress state was developed by the author and initially reported in 1984. The model was validated for predicting failure under elevated-temperature creep-rupture conditions. Biaxial data for three alloy steels, Types 304 and 316 stainless steels and Inconel 600, demonstrated two to three orders of magnitude reduction in the scatter of predicted versus observed creep-rupture times as compared to the classical failure models of Mises, Tresca, and Rankine. In 1990, the new model was incorporated into American Society of Mechanical Engineers (ASME) Code Case N47-29 for design of components operating under creep-rupture conditions. The current report provides additional validation of the model for predicting failure under time-independent conditions and also outlines a methodology for predicting failure under cyclic, time-dependent, creep-fatigue conditions. The later extension of the methodology may have the potential to improve failure predictions there as well. These results are relevant to most design applications, but they have special relevance to high-performance design applications such as components for high-pressure equipment, nuclear reactors, and jet engines.

  15. Validity and reliability of the scientific review process in nursing journals - time for a rethink?

    PubMed

    Jasper, Melanie; Vaismoradi, Mojtaba; Bondas, Terese; Turunen, Hannele

    2014-06-01

    As pressure to publish increases in the academic nursing world, journal submission numbers and rejection rates are soaring. The review process is crucial to journals in publishing high quality, cutting-edge knowledge development, and to authors in preparing their papers to a high quality to enable the nursing world to benefit from developments in knowledge that affect nursing practice and patient outcomes and the development of the discipline. This paper does not intend to contribute to the debate regarding the ethics of reviewing, but rather seeks to explore notions of how the quality of the reviewing process can be enhanced to benefit authors, the reviewers, and the state of nursing knowledge. Furthermore, a call is made to editors to devise strategies for aiding reviewers to attain higher validity and reliability within the reviewing process by establishing clear standards and expectations and to ensure published work is judged against industry norms for quality. PMID:23600446

  16. Most nurses I know don't have time to spend money in the pub.

    PubMed

    Harding-Price, David

    2016-02-10

    I am not sure including a pint of lager in your comparisons to illustrate the inflationary pressures nurses endure while they face yet more pay restraint is justified (news analysis, January 27). PMID:26860171

  17. Predicting the decay time of solid body electric guitar tones.

    PubMed

    Paté, Arthur; Le Carrou, Jean-Loïc; Fabre, Benoît

    2014-05-01

    Although it can be transformed by various electronic devices, the sound of the solid body electric guitar originates from, and is strongly linked with, the string vibration. The coupling of the string with the guitar alters its vibration and can lead to decay time inhomogeneities. This paper implements and justifies a framework for the study of decay times of electric guitar tones. Two damping mechanisms are theoretically and experimentally identified: the string intrinsic damping and the damping due to mechanical coupling with the neck of the guitar. The electromagnetic pickup is shown to not provide any additional damping to the string. The pickup is also shown to be far more sensitive to the out-of-plane polarization of the string. Finally, an accurate prediction of the decay time of electric guitar tones is made possible, whose only requirements are the knowledge of the isolated string dampings and the out-of-plane conductance at the neck of the guitar. This prediction can be of great help for instrument makers and manufacturers. PMID:24815284

  18. A time for self-care: role of the home healthcare nurse.

    PubMed

    Bohny, B J

    1997-04-01

    The concepts of self-efficacy and self-responsibility in personal health provide the framework for developing cost-effective nursing strategies that have positive outcomes for the consumer and the provider Promoting self-care requires that nurses be knowledgeable about outcome planning, the teaching-learning process, and supportive techniques for ongoing care. The concepts outlined in this article can be used to provide care for those who require health promotion, health maintenance, and illness management. PMID:9146165

  19. Racial and Ethnic Disparities in Time to Cure of Incontinence Present at Nursing Home Admission

    PubMed Central

    Bliss, Donna Z.; Gurvich, Olga; Savik, Kay; Eberly, Lynn E.; Harms, Susan; Wyman, Jean F.

    2015-01-01

    As many as half of older people that are admitted to nursing homes (NHs) are incontinent of urine and/or feces. Not much is known about the rate of cure of incontinence present at NH admission, but available reports suggest the rate is low. There have been racial and ethnic disparities in incontinence treatment, but the role of disparities in the cure of incontinence is understudied. Using the Peters-Belson method and multilevel predictors, our findings showed that there were disparities in the time to cure of incontinence for Hispanic NH admissions. A significantly smaller proportion of older Hispanic admissions were observed to have their incontinence cured and cured later than expected had they been White. Reducing disparities in incontinence cure will improve health outcomes of Hispanic NH admissions. Significant predictors in our model suggest strategies to reduce the disparity including attention to managing fecal incontinence and incontinence in those with cognitive impairment, improving residents’ functional status, and increasing resources to NHs admitting older Hispanics with incontinence to develop innovative and cost effective ways to provide equitable quality care. PMID:26295010

  20. Discriminability of Prediction Artifacts in a Time Delayed Virtual Environment

    NASA Technical Reports Server (NTRS)

    Adelstein, Bernard D.; Jung, Jae Y.; Ellis, Stephen R.

    2001-01-01

    Overall latency remains an impediment to perceived image stability and consequently to human performance in virtual environment (VE) systems. Predictive compensators have been proposed as a means to mitigate these shortcomings, but they introduce rendering errors because of induced motion overshoot and heightened noise. Discriminability of these compensator artifacts was investigated by a protocol in which head tracked image stability for 35 ms baseline VE system latency was compared against artificially added (16.7 to 100 ms) latency compensated by a previously studied Kalman Filter (K-F) predictor. A control study in which uncompensated 16.7 to 100 ms latencies were compared against the baseline was also performed. Results from 10 subjects in the main study and 8 in the control group indicate that predictive compensation artifacts are less discernible than the disruptions of uncompensated time delay for the shorter but not the longer added latencies. We propose that noise magnification and overshoot are contributory cues to the presence of predictive compensation.

  1. Real-Time Prediction of Neurally Mediated Syncope.

    PubMed

    Couceiro, R; Carvalho, P; Paiva, R P; Muehlsteff, J; Henriques, J; Eickholt, C; Brinkmeyer, C; Kelm, M; Meyer, C

    2016-03-01

    Neurally mediated syncope (NMS) patients suffer from sudden loss of consciousness, which is associated with a high rate of falls and hospitalization. NMS negatively impacts a subject's quality of life and is a growing cost issue in our aging society, as its incidence increases with age. In this paper, we present a solution for prediction of NMS, which is based on the analysis of the electrocardiogram (ECG) and photoplethysmogram (PPG) alone. Several parameters extracted from ECG and PPG, associated with reflectory mechanisms underlying NMS in previous publications, were combined in a single algorithm to detect impending syncope. The proposed algorithm was evaluated in a population of 43 subjects. The feature selection, distance metric selection, and optimal threshold were performed in a subset of 30 patients, while the remaining data from 13 patients were used to test the final solution. Additionally, a leave-one-out cross-validation scheme was also used to evaluate the performance of the proposed algorithm yielding the following results: sensitivity (SE)--95.2%; specificity (SP)--95.4%; positive predictive value (PPV)--90.9%; false-positive rate per hour (FPRh)-0.14 h(-1), and prediction time (aPTime)--116.4 s. PMID:25769176

  2. Maternal Jail Time, Conviction, and Arrest as Predictors of Children’s 15-year Antisocial Outcomes in the Context of a Nurse Home Visiting Program

    PubMed Central

    Shlafer, Rebecca J.; Poehlmann, Julie; Donelan-McCall, Nancy

    2012-01-01

    Data from the Nurse-Family Partnership intervention program were analyzed to compare the “selection” versus “unique” effects of maternal jail time on adolescent antisocial and health risk outcomes. Data from 320 women and their first-born children were available from the prenatal, birth, and 15-year assessments. Consistent with a selection perspective, prenatal and demographic risks directly and indirectly related to many adolescent antisocial outcomes. Maternal conviction and arrest were also associated with adolescent contact with the criminal justice system and health risk behaviors. Maternal jail time predicted whether or not children had ever been stopped by police, sent to youth corrections, or run away from home. However, these associations were not significant after controlling for prenatal risk factors and maternal conviction and arrest. The results highlight the importance of maternal criminality and other risk factors in children’s environments, including prenatal variables. PMID:22233244

  3. Satellite attitude prediction by multiple time scales method

    NASA Technical Reports Server (NTRS)

    Tao, Y. C.; Ramnath, R.

    1975-01-01

    An investigation is made of the problem of predicting the attitude of satellites under the influence of external disturbing torques. The attitude dynamics are first expressed in a perturbation formulation which is then solved by the multiple scales approach. The independent variable, time, is extended into new scales, fast, slow, etc., and the integration is carried out separately in the new variables. The theory is applied to two different satellite configurations, rigid body and dual spin, each of which may have an asymmetric mass distribution. The disturbing torques considered are gravity gradient and geomagnetic. Finally, as multiple time scales approach separates slow and fast behaviors of satellite attitude motion, this property is used for the design of an attitude control device. A nutation damping control loop, using the geomagnetic torque for an earth pointing dual spin satellite, is designed in terms of the slow equation.

  4. Dynamical recurrent neural networks--towards environmental time series prediction.

    PubMed

    Aussem, A; Murtagh, F; Sarazin, M

    1995-06-01

    Dynamical Recurrent Neural Networks (DRNN) (Aussem 1995a) are a class of fully recurrent networks obtained by modeling synapses as autoregressive filters. By virtue of their internal dynamic, these networks approximate the underlying law governing the time series by a system of nonlinear difference equations of internal variables. They therefore provide history-sensitive forecasts without having to be explicitly fed with external memory. The model is trained by a local and recursive error propagation algorithm called temporal-recurrent-backpropagation. The efficiency of the procedure benefits from the exponential decay of the gradient terms backpropagated through the adjoint network. We assess the predictive ability of the DRNN model with meterological and astronomical time series recorded around the candidate observation sites for the future VLT telescope. The hope is that reliable environmental forecasts provided with the model will allow the modern telescopes to be preset, a few hours in advance, in the most suited instrumental mode. In this perspective, the model is first appraised on precipitation measurements with traditional nonlinear AR and ARMA techniques using feedforward networks. Then we tackle a complex problem, namely the prediction of astronomical seeing, known to be a very erratic time series. A fuzzy coding approach is used to reduce the complexity of the underlying laws governing the seeing. Then, a fuzzy correspondence analysis is carried out to explore the internal relationships in the data. Based on a carefully selected set of meteorological variables at the same time-point, a nonlinear multiple regression, termed nowcasting (Murtagh et al. 1993, 1995), is carried out on the fuzzily coded seeing records. The DRNN is shown to outperform the fuzzy k-nearest neighbors method. PMID:7496587

  5. A New Time Domain Formulation for Broadband Noise Predictions

    NASA Technical Reports Server (NTRS)

    Casper, J.; Farassat, F.

    2002-01-01

    A new analytic result in acoustics called "Formulation 1B," proposed by Farassat, is used to compute the loading noise from an unsteady surface pressure distribution on a thin airfoil in the time domain. This formulation is a new solution of the Ffowcs Williams-Hawkings equation with the loading source term. The formulation contains a far field surface integral that depends on the time derivative and the surface gradient of the pressure on the airfoil, as well as a contour integral on the boundary of the airfoil surface. As a first test case, the new formulation is used to compute the noise radiated from a flat plate, moving through a sinusoidal gust of constant frequency. The unsteady surface pressure for this test case is analytically specified from a result based on linear airfoil theory. This test case is used to examine the velocity scaling properties of Formulation 1B and to demonstrate its equivalence to Formulation 1A of Farassat. The new acoustic formulation, again with an analytic surface pressure, is then used to predict broadband noise radiated from an airfoil immersed in homogeneous, isotropic turbulence. The results are compared with experimental data previously reported by Paterson and Amiet. Good agreement between predictions and measurements is obtained. Finally, an alternative form of Formulation 1B is described for statistical analysis of broadband noise.

  6. A New Time Domain Formulation for Broadband Noise Predictions

    NASA Technical Reports Server (NTRS)

    Casper, Jay H.; Farassat, Fereidoun

    2002-01-01

    A new analytic result in acoustics called "Formulation 1B," proposed by Farassat, is used to compute the loading noise from an unsteady surface pressure distribution on a thin airfoil in the time domain. This formulation is a new solution of the Ffowcs Williams-Hawkings equation with the loading source term. The formulation contains a far field surface integral that depends on the time derivative and the surface gradient of the pressure on the airfoil, as well as a contour integral on the boundary of the airfoil surface. As a first test case, the new formulation is used to compute the noise radiated from a flat plate, moving through a sinusoidal gust of constant frequency. The unsteady surface pressure for this test case is analytically specied from a result based on linear airfoil theory. This test case is used to examine the velocity scaling properties of Formulation 1B and to demonstrate its equivalence to Formulation 1A of Farassat. The new acoustic formulation, again with an analytic surface pressure, is then used to predict broadband noise radiated from an airfoil immersed in homogeneous, isotropic turbulence. The results are compared with experimental data previously reported by Paterson and Amiet. Good agreement between predictions and measurements is obtained. Finally, an alternative form of Formulation 1B is described for statistical analysis of broadband noise.

  7. Toward the Real-Time Tsunami Parameters Prediction

    NASA Astrophysics Data System (ADS)

    Lavrentyev, Mikhail; Romanenko, Alexey; Marchuk, Andrey

    2013-04-01

    Today, a wide well-developed system of deep ocean tsunami detectors operates over the Pacific. Direct measurements of tsunami-wave time series are available. However, tsunami-warning systems fail to predict basic parameters of tsunami waves on time. Dozens examples could be provided. In our view, the lack of computational power is the main reason of these failures. At the same time, modern computer technologies such as, GPU (graphic processing unit) and FPGA (field programmable gates array), can dramatically improve data processing performance, which may enhance timely tsunami-warning prediction. Thus, it is possible to address the challenge of real-time tsunami forecasting for selected geo regions. We propose to use three new techniques in the existing tsunami warning systems to achieve real-time calculation of tsunami wave parameters. First of all, measurement system (DART buoys location, e.g.) should be optimized (both in terms of wave arriving time and amplitude parameter). The corresponding software application exists today and is ready for use [1]. We consider the example of the coastal line of Japan. Numerical tests show that optimal installation of only 4 DART buoys (accounting the existing sea bed cable) will reduce the tsunami wave detection time to only 10 min after an underwater earthquake. Secondly, as was shown by this paper authors, the use of GPU/FPGA technologies accelerates the execution of the MOST (method of splitting tsunami) code by 100 times [2]. Therefore, tsunami wave propagation over the ocean area 2000*2000 km (wave propagation simulation: time step 10 sec, recording each 4th spatial point and 4th time step) could be calculated at: 3 sec with 4' mesh 50 sec with 1' mesh 5 min with 0.5' mesh The algorithm to switch from coarse mesh to the fine grain one is also available. Finally, we propose the new algorithm for tsunami source parameters determination by real-time processing the time series, obtained at DART. It is possible to approximate

  8. Thrombin time and anti-IIa dabigatran's activity: hypothesis of thrombin time's predictive value.

    PubMed

    Le Guyader, Maïlys; Kaabar, Mohammed; Lemaire, Pierre; Pineau Vincent, Fabienne

    2015-01-01

    Dabigatran etexilate (Pradaxa®) is a new oral anticoagulant, competitive inhibitor, selective, fast, direct and reversible of thrombin. Dabigatran has an impact on a large panel of used coagulation tests. There is no relationship between thrombin time's lengthening and anti-IIa activity. This study defines thrombin time's predictive value, when its time is normal. The result of negative value is 97,6%. 255 patients were studied between January 2013 and July 2014. Thrombin time and anti-IIa activity were dosed for each patient. This study can be an assistant for therapeutic decision for laboratories without specialized test. PMID:26489812

  9. Nursing 302: An Introduction to Psychiatric Nursing.

    ERIC Educational Resources Information Center

    Blaustein, Jenna Rose

    A description is provided of "Introduction to Psychiatric Nursing," a 7-week course offered to juniors and seniors in a bachelor of science nursing program. The first sections present information on curricular placement, time assignments, and the targeted student population, and define psychiatric/mental health nursing. Next, the course…

  10. Impact of a nurse navigator on genomic testing and timely treatment decision making in patients with breast cancer.

    PubMed

    McAllister, Kelly A; Schmitt, Mary L

    2015-10-01

    The purpose of this quality improvement project was to define best practices for identifying appropriate patients for genomic testing and improve timeliness for ordering tests and reporting results. An interdisciplinary team of surgeons, radiologists, medical oncologists, and nurses agreed that the RN navigator would be the key person to facilitate timely access to genomic profiling. AT A GLANCE: Genomic profiling has become the standard of care for patients with early-stage breast cancer to assist in developing individualized treatment plans. Nurse navigators can play a key role in improving timeliness of care. The APN-RN model led to improvements in turnaround time and complicance with the National Comprehensive Cancer Network's recommendations for genomic testing. PMID:26414569

  11. Using timing of ice retreat to predict timing of fall freeze-up in the Arctic

    NASA Astrophysics Data System (ADS)

    Stroeve, Julienne C.; Crawford, Alex D.; Stammerjohn, Sharon

    2016-06-01

    Reliable forecasts of the timing of sea ice advance are needed in order to reduce risks associated with operating in the Arctic as well as planning of human and environmental emergencies. This study investigates the use of a simple statistical model relating the timing of ice retreat to the timing of ice advance, taking advantage of the inherent predictive power supplied by the seasonal ice-albedo feedback and ocean heat uptake. Results show that using the last retreat date to predict the first advance date is applicable in some regions, such as Baffin Bay and the Laptev and East Siberian seas, where a predictive skill is found even after accounting for the long-term trend in both variables. Elsewhere, in the Arctic, there is some predictive skills depending on the year (e.g., Kara and Beaufort seas), but none in regions such as the Barents and Bering seas or the Sea of Okhotsk. While there is some suggestion that the relationship is strengthening over time, this may reflect that higher correlations are expected during periods when the underlying trend is strong.

  12. Predicting the Time Course of Individual Objects with MEG.

    PubMed

    Clarke, Alex; Devereux, Barry J; Randall, Billi; Tyler, Lorraine K

    2015-10-01

    To respond appropriately to objects, we must process visual inputs rapidly and assign them meaning. This involves highly dynamic, interactive neural processes through which information accumulates and cognitive operations are resolved across multiple time scales. However, there is currently no model of object recognition which provides an integrated account of how visual and semantic information emerge over time; therefore, it remains unknown how and when semantic representations are evoked from visual inputs. Here, we test whether a model of individual objects--based on combining the HMax computational model of vision with semantic-feature information--can account for and predict time-varying neural activity recorded with magnetoencephalography. We show that combining HMax and semantic properties provides a better account of neural object representations compared with the HMax alone, both through model fit and classification performance. Our results show that modeling and classifying individual objects is significantly improved by adding semantic-feature information beyond ∼200 ms. These results provide important insights into the functional properties of visual processing across time. PMID:25209607

  13. Real-Time WINDMI Predictions of Geomagnetic Storm and Substorms

    NASA Astrophysics Data System (ADS)

    Mays, M. L.; Horton, W.; Spencer, E.; Kozyra, J. U.

    2008-12-01

    Real-Time WINMDI is plasma physics-based, nonlinear dynamical model of the coupled solar WIND Magentosphere-Ionosphere system. Using upstream solar wind particle and field data, a system of nonlinear ordinary differential equations is solved numerically to describe the energy transfer from the solar wind to the magnetosphere-ionosphere system. The physics model WINMDI divides the incoming power into energy stored in multiple regions of M-I system and has been verified on GEM storm data in Spencer et al. (2007). The system of nonlinear ordinary differential equations, which describes energy transfer into, and between dominant components of the nightside magnetosphere and ionosphere, is solved numerically to determine the state of each component. The low-dimensional model characterizes the energy stored in the ring current and the region 1 field-aligned current which are use to compute model Dst and AL values. Real-time solar wind plasma parameters, available from ACE, are downloaded every 10 minutes to compute the input solar wind driving voltage for the model. Real-Time WINDMI computes model Dst and AL values about 1-2 hours before index data is available at the Kyoto WDC Quicklook website. Results are shown on the Real-Time WINDMI website. We present statistics for Real-Time WINDMI performance from 2006 to present and also compare the results for different input driving voltages. We plan to compare the database of Real-Time WINDMI Dst predictions with other ring current models which contain different loss and energization processes. The work is supported by NSF grant ATM-0638480.

  14. Predictability and prediction of tropical cyclones on daily to interannual time scales

    NASA Astrophysics Data System (ADS)

    Belanger, James Ian

    The spatial and temporal complexity of tropical cyclones (TCs) raises a number of scientific questions regarding their genesis, movement, intensification, and variability. In this dissertation, the principal goal is to determine the current state of predictability for each of these processes using global numerical prediction systems. The predictability findings are then used in conjunction with several new statistical calibration techniques to develop a proof-of-concept, operational forecast system for North Atlantic TCs on daily to intraseasonal time scales. To quantify the current extent of tropical cyclone predictability, we assess probabilistic forecasts from the most advanced global numerical weather prediction system to date, the ECMWF Variable Resolution Ensemble Prediction System (VarEPS; Hamill et al. 2008, Hagedorn et al. 2012). Using a new false alarm clustering technique to maximize the utility of the VarEPS, the ensemble system is shown to provide well-calibrated probabilistic forecasts for TC genesis through a lead-time of one week and pregenesis track forecasts with similar skill compared to the VarEPS's postgenesis track forecasts. These findings provide evidence that skillful real-time TC genesis predictions may be made in the North Indian Ocean—a region that even today has limited forecast warning windows for TCs relative to other ocean basins. To quantify the predictability of TCs on intraseasonal time scales, forecasts from the ECMWF Monthly Forecast System (ECMFS) are examined for the North Atlantic Ocean. From this assessment, dynamically based forecasts from the ECMFS provide forecast skill exceeding climatology out to weeks three and four for portions of the southern Gulf of Mexico, western Caribbean and the Main Development Region. Forecast skill in these regions is traced to the model's ability to capture correctly the variability in deep-layer vertical wind shear as well as the relative frequency of easterly waves moving through these

  15. Automatic measurement of voice onset time using discriminative structured prediction.

    PubMed

    Sonderegger, Morgan; Keshet, Joseph

    2012-12-01

    A discriminative large-margin algorithm for automatic measurement of voice onset time (VOT) is described, considered as a case of predicting structured output from speech. Manually labeled data are used to train a function that takes as input a speech segment of an arbitrary length containing a voiceless stop, and outputs its VOT. The function is explicitly trained to minimize the difference between predicted and manually measured VOT; it operates on a set of acoustic feature functions designed based on spectral and temporal cues used by human VOT annotators. The algorithm is applied to initial voiceless stops from four corpora, representing different types of speech. Using several evaluation methods, the algorithm's performance is near human intertranscriber reliability, and compares favorably with previous work. Furthermore, the algorithm's performance is minimally affected by training and testing on different corpora, and remains essentially constant as the amount of training data is reduced to 50-250 manually labeled examples, demonstrating the method's practical applicability to new datasets. PMID:23231126

  16. Real-time prediction of cell division timing in developing zebrafish embryo.

    PubMed

    Kozawa, Satoshi; Akanuma, Takashi; Sato, Tetsuo; Sato, Yasuomi D; Ikeda, Kazushi; Sato, Thomas N

    2016-01-01

    Combination of live-imaging and live-manipulation of developing embryos in vivo provides a useful tool to study developmental processes. Identification and selection of target cells for an in vivo live-manipulation are generally performed by experience- and knowledge-based decision-making of the observer. Computer-assisted live-prediction method would be an additional approach to facilitate the identification and selection of the appropriate target cells. Herein we report such a method using developing zebrafish embryos. We choose V2 neural progenitor cells in developing zebrafish embryo as their successive shape changes can be visualized in real-time in vivo. We developed a relatively simple mathematical method of describing cellular geometry of V2 cells to predict cell division-timing based on their successively changing shapes in vivo. Using quantitatively measured 4D live-imaging data, features of V2 cell-shape at each time point prior to division were extracted and a statistical model capturing the successive changes of the V2 cell-shape was developed. By applying sequential Bayesian inference method to the model, we successfully predicted division-timing of randomly selected individual V2 cells while the cell behavior was being live-imaged. This system could assist pre-selecting target cells desirable for real-time manipulation-thus, presenting a new opportunity for in vivo experimental systems. PMID:27597656

  17. Real-time prediction of cell division timing in developing zebrafish embryo

    PubMed Central

    Kozawa, Satoshi; Akanuma, Takashi; Sato, Tetsuo; Sato, Yasuomi D.; Ikeda, Kazushi; Sato, Thomas N.

    2016-01-01

    Combination of live-imaging and live-manipulation of developing embryos in vivo provides a useful tool to study developmental processes. Identification and selection of target cells for an in vivo live-manipulation are generally performed by experience- and knowledge-based decision-making of the observer. Computer-assisted live-prediction method would be an additional approach to facilitate the identification and selection of the appropriate target cells. Herein we report such a method using developing zebrafish embryos. We choose V2 neural progenitor cells in developing zebrafish embryo as their successive shape changes can be visualized in real-time in vivo. We developed a relatively simple mathematical method of describing cellular geometry of V2 cells to predict cell division-timing based on their successively changing shapes in vivo. Using quantitatively measured 4D live-imaging data, features of V2 cell-shape at each time point prior to division were extracted and a statistical model capturing the successive changes of the V2 cell-shape was developed. By applying sequential Bayesian inference method to the model, we successfully predicted division-timing of randomly selected individual V2 cells while the cell behavior was being live-imaged. This system could assist pre-selecting target cells desirable for real-time manipulation–thus, presenting a new opportunity for in vivo experimental systems. PMID:27597656

  18. A simple approach for predicting time-optimal slew capability

    NASA Astrophysics Data System (ADS)

    King, Jeffery T.; Karpenko, Mark

    2016-03-01

    The productivity of space-based imaging satellite sensors to collect images is directly related to the agility of the spacecraft. Increasing the satellite agility, without changing the attitude control hardware, can be accomplished by using optimal control to design shortest-time maneuvers. The performance improvement that can be obtained using optimal control is tied to the specific configuration of the satellite, e.g. mass properties and reaction wheel array geometry. Therefore, it is generally difficult to predict performance without an extensive simulation study. This paper presents a simple idea for estimating the agility enhancement that can be obtained using optimal control without the need to solve any optimal control problems. The approach is based on the concept of the agility envelope, which expresses the capability of a spacecraft in terms of a three-dimensional agility volume. Validation of this new approach is conducted using both simulation and on-orbit data.

  19. Predicting Rocket or Jet Noise in Real Time

    NASA Technical Reports Server (NTRS)

    Frendi, Kader

    2007-01-01

    A semi-empirical theoretical model and a C++ computer program that implements the model have been developed for use in predicting the noise generated by a rocket or jet engine. The computer program, entitled the Realtime Rocket and Jet Engine Noise Analysis and Prediction Software, is one of two main subsystems of the Acoustic Prediction/Measurement Tool, which comprises software, acoustic instrumentation, and electronic hardware combined to afford integrated capabilities for real-time prediction and measurement of noise emitted by rocket and jet engines. [The other main subsystem, consisting largely of acoustic instrumentation and electronic hardware, is described in Wireless Acoustic Measurement System, which appears elsewhere in this section.] The theoretical model was derived from the fundamental laws of fluid mechanics, as first was done by M. J. Lighthill in his now famous theory of aerodynamically generated sound. The far-field approximation of the Lighthill theory is incorporated into this model. Many other contributions from various researchers have also been introduced into the model. The model accounts for two noise components: shear noise and self noise. The final result of the model is expressed in terms of a volume integral of the acoustic intensities attributable to these two components, subject to various directivity coefficients. The computer program was written to solve the volume integral. The inputs required by the program are two data files from a computational fluid dynamics (CFD) simulation of the flow of interest: the computational-grid file and the solution file. The CFD solution should be one that has been obtained for conditions that closely approximate those of an experimental test that is yet to be performed. In the current state of development of the model and software, it is recommended that the observation points lie along a radius at an angle >60 from the jet axis. The software provides, and is driven via, a graphical user interface

  20. Nursing, Pharmacy, or Medicine? Disgust Sensitivity Predicts Career Interest among Trainee Health Professionals

    ERIC Educational Resources Information Center

    Consedine, Nathan S.; Yu, Tzu-Chieh; Windsor, John A.

    2013-01-01

    Given global demand on health workforces, understanding student enrollment motivations are critical. Prior studies have concentrated on variation in career and lifestyle values; the current work evaluated the importance of disgust sensitivity in the prediction of health career interests. We argue that emotional proclivities may be important and…

  1. Nursing leaders can deliver a new model of care.

    PubMed

    Shalala, Donna E

    2014-01-01

    Millions more insured Americans. Increasing numbers of older patients. Higher rates of chronic illness. Fewer providers. How can our healthcare system not only manage these challenges but also improve performance and access to care while containing costs? The answer lies with our nurses. In some parts of the United States, nurses provide the full spectrum of primary and preventive care. They have successfully improved access and quality in rural areas. In other parts, nurses' hands are tied by antiquated laws and regulations that limit their ability to expand access to care. Our system cannot increase access when we have providers who are not allowed to perform to the top of their education, training, and capability. It is time to rethink how we deliver primary and preventive care and redefine the roles of doctors and nurses. This article examines the history of the Institute of Medicine's (IOM) Future of Nursing report (chaired by the author) and the resulting Future of Nursing Campaign for Action, which is working to institute the report's recommendations in all 50 states. The IOM report's recommendations are simple: 1. Remove outdated restrictions on nursing practice. 2. Promote nurse leadership on hospital boards and in all healthcare sectors. 3. Strengthen nurse education and training, and increase the number of nurses with advanced degrees. 4. Increase diversity in the nursing workforce to better reflect the patient population. 5. Improve data reporting and compilation to predict workforce needs. New York, Kentucky, and Minnesota are three recent states to remove barriers pre venting advanced practice registered nurses from practicing at the top of their license. Similar efforts in California, Florida, and Indiana failed initially but are expected to make progress in the near future. The article makes clear how and why the Center to Champion Nursing in America (an initiative of AARP, the AARP Foundation, and the Robert Wood Johnson Foundation) is working to

  2. Understanding and Predicting Time-Dependent Dune Erosion

    NASA Astrophysics Data System (ADS)

    Long, J.; Stockdon, H. F.; Smith, J. R.

    2014-12-01

    The vulnerability of coastal ecosystems, habitats, and infrastructure is largely dictated by how protective sand dunes respond to extreme waves and water levels during storms. Predicting the type of dune response (e.g., scarping, overwashing, breaching) is often done with conditional storm-impact scale models (e.g. Sallenger 2000) however, these models do not describe the magnitude of expected changes or account for the continuum of dune responses throughout the duration of a storm event. Alternatively, process-based dune erosion models like XBeach explicitly compute interactions between waves, water levels, and sediment transport but are limited in regional applications due to computational requirements and inadequate knowledge of required boundary conditions. Using historical observations of storm-induced coastal change, we are developing and testing a variety of new static, probabilistic, and time-dependent models for dune erosion. Model development is informed by the observed dune response from four events that impacted geomorphically diverse regions along the U.S. Atlantic and Gulf of Mexico coastlines. Results from the static models indicate that alongshore differences in the magnitude of dune elevation change can be related to the depth of water over of the dune crest (e.g. freeboard) but that increasing freeboard does not always correspond to an increased lowering of the dune crest. Applying the concept of dune freeboard in a time-dependent approach that incorporates rising water levels that cause a dune to sequentially experience collision, overwash and then inundation shows that reasonable estimates of dune erosion are obtained. The accuracy of each of the models is now being evaluated along the large and diverse regions of coast that were impacted by Hurricane Sandy in 2012 where dune response was highly variable.

  3. Predictive active disturbance rejection control for processes with time delay.

    PubMed

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

    Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems. PMID:24182516

  4. Heat transfer model for predicting squib ignition times

    NASA Technical Reports Server (NTRS)

    Sernas, V.

    1974-01-01

    A squib ignition model based on transient heat condition from the hot bridgewire to the pyrotechnic is described. No Arrhenius-type chemical reaction is included. Instead, a thermal contact resistance is postulated to exist between the hot bridgewire and the pyrotechnic. Ignition is assumed to occur when a 2.5 micron layer of pyrotechnic next to the bridgewire reaches a characteristic ignition temperature for that pyrotechnic. This model was applied to the JPL squib, which uses a 50 micron (0.002-in.) diameter Tophet A bridgewire to ignite a boron, potassium perchlorate mix. A computer program was utilized that solves the transient heat condition problem with the boundary conditions stipulated by the model. The thermal contact conductance at the interface was determined by trial and error so that the experimentally determined ignition time for one firing condition would be properly predicted by the model. The agreement was quite good for tests run between -129 C and +93.3 C at current levels of 3.5 and 5 A. Axial heat conduction along the bridgewire is shown to be negligible.

  5. Fixed recurrence and slip models better predict earthquake behavior than the time- and slip-predictable models 1: repeating earthquakes

    USGS Publications Warehouse

    Rubinstein, Justin L.; Ellsworth, William L.; Chen, Kate Huihsuan; Uchida, Naoki

    2012-01-01

    The behavior of individual events in repeating earthquake sequences in California, Taiwan and Japan is better predicted by a model with fixed inter-event time or fixed slip than it is by the time- and slip-predictable models for earthquake occurrence. Given that repeating earthquakes are highly regular in both inter-event time and seismic moment, the time- and slip-predictable models seem ideally suited to explain their behavior. Taken together with evidence from the companion manuscript that shows similar results for laboratory experiments we conclude that the short-term predictions of the time- and slip-predictable models should be rejected in favor of earthquake models that assume either fixed slip or fixed recurrence interval. This implies that the elastic rebound model underlying the time- and slip-predictable models offers no additional value in describing earthquake behavior in an event-to-event sense, but its value in a long-term sense cannot be determined. These models likely fail because they rely on assumptions that oversimplify the earthquake cycle. We note that the time and slip of these events is predicted quite well by fixed slip and fixed recurrence models, so in some sense they are time- and slip-predictable. While fixed recurrence and slip models better predict repeating earthquake behavior than the time- and slip-predictable models, we observe a correlation between slip and the preceding recurrence time for many repeating earthquake sequences in Parkfield, California. This correlation is not found in other regions, and the sequences with the correlative slip-predictable behavior are not distinguishable from nearby earthquake sequences that do not exhibit this behavior.

  6. Creative fund-raising for nursing homes. An additional revenue source in tough economic times.

    PubMed

    March, C; Kleckner, R; Schumer, M F

    1991-12-01

    Nursing home administrators and sponsors should look to fund-raising as a way to increase their facilities' revenues. The board should first appoint a development coordinator and a special board to be responsible for the fund-raising program. The nursing home can reach potential contributors by regularly sending printed material to specially selected persons from its mailing list. The staff must know the procedures to follow when someone wants to make a donation (e.g., to whom the check should be made payable). To generate interest and to motivate contributors, the fund-raising board should identify specific needs for which the contributions will be solicited. A computer program can help keep track of to whom acknowledgements must be sent. Options for a fund-raising program include memorial and honor gifts, gifts in kind, grants and special gifts, special events, deferred gifts, educational programs, and membership clubs. PMID:10115217

  7. Prediction of Universal Time using the artificial neural network

    NASA Astrophysics Data System (ADS)

    Richard, J. Y.; Lopes, P.; Barache, C.; Bizouard, C.; Gambis, D.

    2014-12-01

    The monitoring of the Earth Orientation Parameters (EOP) variations is the main task of the Earth orientation Center of the IERS. In addition, for various applications linked in particular to navigation, precise orbit determination or leap seconds announcements, short and long term predictions are required. The method which is currently applied for predictions is based on deterministic processes, Least Square fitting, autoregressive filtering (Gambis and Luzum 2011). We present an alternative method, the Artificial Neural Networks (ANN) which has have already been successfully applied for pattern recognition. It has been tested as well by various authors for EOP predictions but with so far no real improvement compared to the current methods (Schuh et. al. 2002). New formalisms recently developed allow reconsidering the use of neural networks for EOP predictions. Series of simulations were performed for both short and long term predictions. Statistics and comparisons with the current methods are presented.

  8. Value of intensified nursing

    PubMed Central

    Frank, Wilhelm; Konta, Brigitte; Prusa, Nina; Raymann, Cornelia

    2006-01-01

    The concept "intensified nursing" is mentioned in differentiation to concepts of "nursing care" or "nursing" which intensifies resources or patient contact. Especially psychic and social needs of patients are very appreciated in nursing. A similar type of nursing is known under the concept "advanced nursing practice" (ANP) which means, that a specialised, academically trained nurse offers an extended nursing care in which a focus on the published knowledge of evidence based research is made. From the thin literature to this topic a selection of predetermined topics was analysed where at least two articles with a sufficient high methodical quality were available. The selected topic groups were: „Infant and paediatric nursing", "gerontology" and "oncology". Generally the five publications concerning infant and paediatric nursing could conclusive show a benefit of intensified nursing. Further research is still needed to prove intensified nursing care. Two publications could be found to the gerontological intensified nursing; both used an extended nursing model and an enlarged use of resources. Both studies demonstrated a measurable success in the applied parameters. Two studies also could be analysed in the oncological field in which successes were also provable by the applied parameters. The success was given especially in a higher patient satisfaction, one study showed an improved scheduling (time planning) of nurses. There was not one article concerning economic questions of intensified nursing care. It has to be taken into account that the financial resources have to be used effectively also in nursing nowadays. It has to be assumed that the costs are driven by increased use of resources. Savings can be achieved, however, in the form of avoided therapies and days in hospital by intensified nursing. The intensified nursing can be considered as similar cost-effective as conventional models of nursing. Ethically it is necessary to consider that the possibilities of

  9. Just-in-Time Evidence-Based E-mail “Reminders” in Home Health Care: Impact on Nurse Practices

    PubMed Central

    Murtaugh, Christopher M; Pezzin, Liliana E; McDonald, Margaret V; Feldman, Penny H; Peng, Timothy R

    2005-01-01

    Objective To test the effectiveness of two interventions designed to improve the adoption of evidence-based practices by home health nurses caring for heart failure (HF) patients. Data Sources/Study Setting Information on nurse practices was abstracted from the clinical records of patients admitted between June 2000 and November 2001 to the care of 354 study nurses at a large, urban, nonprofit home care agency. Study Design The study employed a randomized design with nurses assigned to usual care or one of two intervention groups upon identification of an eligible patient. The basic intervention was a one-time e-mail reminder highlighting six HF-specific clinical recommendations. The augmented intervention consisted of the initial e-mail reminder supplemented by provider prompts, patient education material, and clinical nurse specialist outreach. Data Collection At each home health visit provided by a study nurse to an eligible HF patient during the 45-day follow-up period, a structured chart abstraction tool was used to collect information on whether the nurse provided the care practices highlighted in the e-mail reminder. Principal Findings Both the basic and the augmented interventions greatly increased the practice of evidence-based care, according to patient records, in the areas of patient assessment and instructions about HF disease management. While not all results were statistically significant at conventional levels, intervention effects were positive in virtually all cases and effect magnitudes frequently were large. Conclusions The results of this randomized trial strongly support the efficacy of just-in-time evidence-based reminders as a means of changing clinical practice among home health nurses who are geographically dispersed and spend much of their time in the field. PMID:15960694

  10. Age-related differences in predictive response timing in children: evidence from regularly relative to irregularly paced reaction time performance.

    PubMed

    Debrabant, Julie; Gheysen, Freja; Vingerhoets, Guy; Van Waelvelde, Hilde

    2012-08-01

    Predictive timing refers to the anticipation and precise timing of planned motor responses. This study was performed to investigate children's predictive response timing abilities while accounting for confounding age-related effects of motor speed. Indices of predictive timing were evaluated for their contributions in motor skill proficiency as well. Eighty typically developing children in 4 age groups (5-6, 7-8, 9-10 and 11-12 years) performed a visuomotor reaction time (RT) test. Differences in speed and anticipatory responding at regularly relative to irregularly paced stimuli were evaluated as indices of predictive timing. Also, explicit timing and motor tests (M-ABC-2, VMI tracing, and KTK jumping) were administered. Significant faster responding for regularly versus irregularly paced stimuli was found from the ages of 9-10 years on. Better anticipatory responding behavior for regular in contrast with irregular stimuli was found to be present already at 7-8 years. Overall, predictive timing abilities increased across the 4 age groups. Also, inter-individual differences in the speed indices of predictive timing contributed to predicting VMI tracing and KTK jumping outcomes when controlling for age and overall motor response speed. In conclusion, predictive motor timing abilities increase during age 5 to 12 and correlate with motor skill performance. PMID:22494922

  11. Predicting the Timing and Location of the next Hawaiian Volcano

    ERIC Educational Resources Information Center

    Russo, Joseph; Mattox, Stephen; Kildau, Nicole

    2010-01-01

    The wealth of geologic data on Hawaiian volcanoes makes them ideal for study by middle school students. In this paper the authors use existing data on the age and location of Hawaiian volcanoes to predict the location of the next Hawaiian volcano and when it will begin to grow on the floor of the Pacific Ocean. An inquiry-based lesson is also…

  12. A Heat Unit Model for Predicting Blackberry Flowering Time

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Spring temperature fluctuations are often the cause of crop loss in blackberry. The maximum sensitivity to cold temperatures occurs at or near bloom, when temperatures only a few degrees below freezing will damage the pistils. The ability to predict bloom date and identify genotypes that are consi...

  13. Nursing Supplies

    MedlinePlus

    ... Stages Listen Español Text Size Email Print Share Nursing Supplies Page Content Article Body Throughout most of ... budget. (Nursing equipment also makes wonderful baby gifts.) Nursing Bras A well-made nursing bra that comfortably ...

  14. Job satisfaction among multiple sclerosis certified nurses.

    PubMed

    Gulick, Elsie E; Halper, June; Costello, Kathleen

    2007-08-01

    Several studies document high levels of job satisfaction among certified nurses, but no study has examined job satisfaction and factors influencing job satisfaction of certified multiple sclerosis (MS) nurses. This study tested a theoretical model proposing that two organizational factors, colleague relationships and benefits, will predict job satisfaction. Job satisfaction was represented by four factors: autonomy, professional status, professional growth, and time efficiency. Participants included MS nurses certified for 6 months or more practicing mostly in three countries (Canada, Great Britain, and the United States) who anonymously completed the Misener Nurse Practitioner Job Satisfaction Scale, an overall job satisfaction rating, and demographic information. Findings indicate that colleague relationships and benefits significantly estimated organization structure and that autonomy, professional status, professional growth, and time efficiency significantly estimated job satisfaction; furthermore, organization factors such as colleague relationships and benefits significantly predict job satisfaction. Among the countries, several statistically significant differences were observed between job satisfaction factors as well as items in both organization and job satisfaction subscales. Average factor scores among the countries were mostly rated satisfactory. The International Organization of Multiple Sclerosis Nurses Executive Board plans to use the study findings to see how it needs to focus efforts as an organization toward enhancing and standardizing MS care and develop MS nurse professionalism worldwide. PMID:17847673

  15. Timing of food intake predicts weight loss effectiveness

    Technology Transfer Automated Retrieval System (TEKTRAN)

    There is emerging literature demonstrating a relationship between the timing of feeding and weight regulation in animals. However, whether the timing of food intake influences the success of a weight-loss diet in humans is unknown. To evaluate the role of food timing in weight-loss effectiveness in ...

  16. Issues and challenges in nursing and nursing education in Japan.

    PubMed

    Turale, Sue; Ito, Misae; Nakao, Fujiko

    2008-01-01

    In this editorial we discuss the challenges and issues in nursing and nurse education in Japan. These include a rapid growth in the number of universities offering nursing programs without sufficient time for preparation of faculty; issues in the traditional ways of teaching in classrooms; the appearance of nursing shortages in a country with the highest rate of longevity in the world; and the position of nursing faculty in a society that is largely male dominated. PMID:17719851

  17. Nursing Leadership.

    PubMed

    Crisp, Carol

    2016-01-01

    Nurse transformational leaders can serve in academic settings and at local, national, international professional nursing organizations and community-based groups. As a transformational leader, nurses can lead in any workplace. According to a study by Stanley (2012), clinical leaders are not sought for their capacity to outline a vision, but for their values and beliefs on display that are easily recognized in their actions. This encompasses the moral component of transformational leadership. It is the APRNs duty to continue to strive towards a better vision for the well-being of all nurses, patients, and colleagues. Autonomous APRNs are happier, healthier, and better prepared to provide the best patient care to their patients. We should not be happy to sit back and let others fight this fight. APRNs need to be on the frontline, leading the way. This is only an insight that I have gained after many frustrating years of cheering our profession and then being made to feel inferior at the same time. Only nurses, who have that nurturing spirit, would hold back if they felt it might hurt others. Don't back off or hold back! It might hurt those that follow! PMID:27089563

  18. Nursing: What's a Nurse Practitioner?

    MedlinePlus

    ... nurses, or APNs) have a master's degree in nursing (MS or MSN) and board certification in their ... Nurse Practitioners (NAPNAP) and through local hospitals or nursing schools. In addition, many doctors share office space ...

  19. Caregiver Person-Centeredness and Behavioral Symptoms in Nursing Home Residents With Dementia: A Timed-Event Sequential Analysis

    PubMed Central

    Gilmore-Bykovskyi, Andrea L.; Roberts, Tonya J.; Bowers, Barbara J.; Brown, Roger L.

    2015-01-01

    Purpose: Evidence suggests that person-centered caregiving approaches may reduce dementia-related behavioral symptoms; however, little is known about the sequential and temporal associations between specific caregiver actions and behavioral symptoms. The aim of this study was to identify sequential associations between caregiver person-centered actions, task-centered actions, and resident behavioral symptoms and the temporal variation within these associations. Design and Methods: Videorecorded observations of naturally occurring interactions (N = 33; 724min) between 12 nursing home (NH) residents with dementia and eight certified nursing assistants were coded for caregiver person-centered actions, task-centered actions, and resident behavioral symptoms and analyzed using timed-event sequential analysis. Results: Although caregiver actions were predominantly person-centered, we found that resident behavioral symptoms were significantly more likely to occur following task-centered caregiver actions than person-centered actions. Implications: Findings suggest that the person-centeredness of caregivers is sequentially and temporally related to behavioral symptoms in individuals with dementia. Additional research examining the temporal structure of these relationships may offer valuable insights into the utility of caregiver person-centeredness as a low-cost strategy for improving behavioral symptom management in the NH setting. PMID:26055782

  20. [Nurse/midwife responsibility].

    PubMed

    Lagneaux, M-C

    2008-11-01

    Blood transfusion is a medical act which a nurse or midwife can do with a medical consent and only if a doctor can intercede when he is called. The following presentation reminds us of the nurse's and midwife's responsability when doing a blood transfusion. All the guidelines are laid down in the Public Health Code for nurses and midwifes as well as in the circular of the 15 December 2003. The nurse or midwife doing the transfusion must at all times respect the security guidelines, doing so along with close collaboration between nurse, midwife and doctor enables all transfusions to be conducted safely. PMID:18951056

  1. Using Time-Series Regression to Predict Academic Library Circulations.

    ERIC Educational Resources Information Center

    Brooks, Terrence A.

    1984-01-01

    Four methods were used to forecast monthly circulation totals in 15 midwestern academic libraries: dummy time-series regression, lagged time-series regression, simple average (straight-line forecasting), monthly average (naive forecasting). In tests of forecasting accuracy, dummy regression method and monthly mean method exhibited smallest average…

  2. Nursing Applicant Interview Manual.

    ERIC Educational Resources Information Center

    Kohn, Suzanne

    This manual is a tool for use in an interview for nursing student selection that will assist in sizing up the fitness or suitability of the candidate for nursing. It also includes tools and methods that could be used in the initial interview to assess what factors will predict those students most likely to stay in an Associate Degree nursing…

  3. Army nurses' knowledge base for determining triage categories in a mass casualty.

    PubMed

    Robison, Jennifer L

    2002-10-01

    The timing, location, and participants in a mass casualty scenario cannot be predicted. Nurses may be involved in performing triage, yet there is no published documentation of military nurses' ability to triage. A prospective design was used to describe 82 Army nurses' knowledge base related to designating triage categories for patients during a mass causality, examining the relationships among their education and experience as evaluated by The Darnall Mass Casualty Triage Test and Demographic Data Form. The most significant areas associated with higher scores on the Triage Test were: completion of Advanced Cardiac Life Support, advanced certification as a Certified Registered Nurse Anesthetists, Certified Emergency Nurse, or Critical Care Registered Nurse, and attendance to the Medical Management of Nuclear Weapons Course. An improved average score for nurses overall was also noted when compared with previous work with the Darnall MASCAL Triage Test. PMID:12392246

  4. PREDICTION OF AGRICULTURAL WORKER SAFETY REENTRY TIMES FOR ORGANOPHOSPHATE INSECTICIDES

    EPA Science Inventory

    Concepts and current methods of determining worker safety reentry times are reviewed. Comparison of human monitoring studies, factors in a worker reentry episode and exposure estimation methods illustrate the advantages of estimation methods. Research needs for worker reentry tim...

  5. An evaluation of rise time characterization and prediction methods

    NASA Technical Reports Server (NTRS)

    Robinson, Leick D.

    1994-01-01

    One common method of extrapolating sonic boom waveforms from aircraft to ground is to calculate the nonlinear distortion, and then add a rise time to each shock by a simple empirical rule. One common rule is the '3 over P' rule which calculates the rise time in milliseconds as three divided by the shock amplitude in psf. This rule was compared with the results of ZEPHYRUS, a comprehensive algorithm which calculates sonic boom propagation and extrapolation with the combined effects of nonlinearity, attenuation, dispersion, geometric spreading, and refraction in a stratified atmosphere. It is shown there that the simple empirical rule considerably overestimates the rise time estimate. In addition, the empirical rule does not account for variations in the rise time due to humidity variation or propagation history. It is also demonstrated that the rise time is only an approximate indicator of perceived loudness. Three waveforms with identical characteristics (shock placement, amplitude, and rise time), but with different shock shapes, are shown to give different calculated loudness. This paper is based in part on work performed at the Applied Research Laboratories, the University of Texas at Austin, and supported by NASA Langley.

  6. Father Attendance in Nurse Home Visitation

    PubMed Central

    Holmberg, John R.; Olds, David L.

    2015-01-01

    Our aim was to examine the rates and predictors of father attendance at nurse home visits in replication sites of the Nurse-Family Partnership (NFP). Early childhood programs can facilitate father involvement in the lives of their children, but program improvements require an understanding of factors that predict father involvement. The sample consisted of 29,109 low-income, first-time mothers who received services from 694 nurses from 80 sites. We conducted mixed-model multiple regression analyses to identify population, implementation, site, and nurse influences on father attendance. Predictors of father attendance included a count of maternal visits (B = 0.12, SE = 0.01, F = 3101.77), frequent contact between parents (B = 0.61, SE = 0.02, F = 708.02), cohabitation (B = 1.41, SE = 0.07, F = 631.51), White maternal race (B = 0.77, SE = 0.06, F = 190.12), and marriage (B = 0.42, SE = 0.08, F = 30.08). Random effects for sites and nurses predicted father-visit participation (2.7 & 6.7% of the variance, respectively), even after controlling for population sociodemographic characteristics. These findings suggest that factors operating at the levels of sites and nurses influence father attendance at home visits, even after controlling for differences in populations served. Further inquiry about these influences on father visit attendance is likely to inform program-improvement efforts. PMID:25521707

  7. Father attendance in nurse home visitation.

    PubMed

    Holmberg, John R; Olds, David L

    2015-01-01

    Our aim was to examine the rates and predictors of father attendance at nurse home visits in replication sites of the Nurse-Family Partnership (NFP). Early childhood programs can facilitate father involvement in the lives of their children, but program improvements require an understanding of factors that predict father involvement. The sample consisted of 29,109 low-income, first-time mothers who received services from 694 nurses from 80 sites. We conducted mixed-model multiple regression analyses to identify population, implementation, site, and nurse influences on father attendance. Predictors of father attendance included a count of maternal visits (B = 0.12, SE = 0.01, F = 3101.77), frequent contact between parents (B = 0.61, SE = 0.02, F = 708.02), cohabitation (B = 1.41, SE = 0.07, F = 631.51), White maternal race (B = 0.77, SE = 0.06, F = 190.12), and marriage (B = 0.42, SE = 0.08, F = 30.08). Random effects for sites and nurses predicted father-visit participation (2.7 & 6.7% of the variance, respectively), even after controlling for population sociodemographic characteristics. These findings suggest that factors operating at the levels of sites and nurses influence father attendance at home visits, even after controlling for differences in populations served. Further inquiry about these influences on father visit attendance is likely to inform program-improvement efforts. PMID:25521707

  8. Oncology nurse navigator.

    PubMed

    Case, Mary Ann B

    2011-02-01

    The purpose of this integrative review is to explore the presence of the oncology nurse as navigator on measurable patient outcomes. Eighteen primary nursing research studies were found using combinations of the following key words: advocate, cancer, case manager, coach, certification, guide, navigator, nurse, oncology, patient navigator, pivot nurse, and continuity of care. Nurse researchers identified nursing-sensitive patient outcomes related to the time to diagnosis and appropriate treatment, effect on mood states, satisfaction, support, continuity of care, and cost outcomes. Navigator roles are expanding globally, and nurses should continue to embrace opportunities to ensure the safe passage of patients with cancer along the entire trajectory of illness and to evaluate the implications for educational preparation, research, and practice of navigators of all kinds. PMID:21278039

  9. Strainrange partitioning life predictions of the long time metal properties council creep-fatigue tests

    NASA Technical Reports Server (NTRS)

    Saltsman, J. F.; Halford, G. R.

    1979-01-01

    The method of strainrange partitioning is used to predict the cyclic lives of the Metal Properties Council's long time creep-fatigue interspersion tests of several steel alloys. Comparisons are made with predictions based upon the time- and cycle-fraction approach. The method of strainrange partitioning is shown to give consistently more accurate predictions of cyclic life than is given by the time- and cycle-fraction approach.

  10. Nursing 436A: Pediatric Oncology for Nurses.

    ERIC Educational Resources Information Center

    Jackman, Cynthia L.

    A description is provided of "Pediatric Oncology for Nurses," the first in a series of three courses offered to fourth-year nursing students in pediatric oncology. The first section provides a course overview, discusses time assignments, and describes the target student population. Next, a glossary of terms, and lists of course goals, long-range…

  11. Predicting the Timing of Women's Departure from Abusive Relationships

    ERIC Educational Resources Information Center

    Panchanadeswaran, Subadra; McCloskey, Laura A.

    2007-01-01

    The aim of this study was to investigate forces that affect the timing of women's exit from violent relationships with men. Abused women were recruited from posters in the community and battered women's shelters, interviewed, and followed up for 10 years. Data for this study are based on 100 women and were analyzed using event history analysis.…

  12. Predicting Success for Nontraditional Students in an Afternoon and Evening/Weekend Associate Degree in Nursing Program

    ERIC Educational Resources Information Center

    Ledesma, Hernani Luison, Jr.

    2012-01-01

    Mount St. Mary's College has offered a nontraditional Associate Degree in Nursing (ADN) Program since 1992. The program has an afternoon and evening/weekend format. There has been one previous research study published in 2005 that described the student population that Mount St. Mary's College serves. This present study will examine the…

  13. Real time prediction of sea level anomaly data with the Prognocean system - comparison of results obtained using different prediction techniques

    NASA Astrophysics Data System (ADS)

    Mizinski, Bartlomiej; Niedzielski, Tomasz; Kosek, Wieslaw

    2013-04-01

    Prognocean is a near-real time modeling and prediction system elaborated and based at University of Wroclaw, Poland. It operates on gridded Sea Level Anomaly (SLA) data obtained from the Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO), France. The data acquisition flow from AVISO to Prognocean is entirely automatic and is implemented in Python. The core of the system - including data pre-processing, modeling, prediction, validation and visualization procedures - is composed of a series of R scripts that are interrelated and work at three levels of generalization. The objective of the work presented here is to show the results of our numerical experiment that have been carried out since early 2012. Four prediction models have been implemented to date: (1) extrapolation of polynomial-harmonic model and the extrapolation of polynomial-harmonic model with (2) autoregressive model, (3) threshold autoregressive model and (4) autocovariance procedure. Although the presentation is limited to four models and their predictive skills, Prognocean consists of modules and hence new techniques may be plugged in at any time. In this paper, the comparison of the results into forecasting sea level anomaly maps is presented. Along with sample predictions, with various lead times up to two weeks, we present and discuss a set of root mean square prediction error maps computed in real time after the observations have been available. We identified areas where linear prediction models reveal considerable errors, which may indicate a non-linear mode of sea level change. In addition, we have identified an agreement between the spatial pattern of large prediction errors and the spatial occurrence of key mesoscale ocean eddies.

  14. Prediction of time to go of IR imaging GIF

    NASA Astrophysics Data System (ADS)

    Fan, Min-ge; Peng, Zhi-yong; Luo, Xiao-Liang; Lu, Jin

    2011-08-01

    During the infrared imaging guided missile-target terminal impact, the remaining time estimating accuracy plays a very important role to missile burst control. The precision of anti-aircraft missile is sensitive to the angle-measured error by using infrared imaging GIF technology. But in theory, the distance information can be introduced to lower the negative effect of the angle-measured error. So, how to get missile-target distance is a key. The use of laser fuze is common solution, which but makes the system more complexity and cost higher. The paper proposes a distance-measured method, which the missile-target distance is obtained by using the grey value of target tracking point in successive infrared image frame. Then the distance and angle information is integrated together to estimate the missile-target impact time.

  15. Meditation-induced states predict attentional control over time.

    PubMed

    Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Baas, Matthijs; Hommel, Bernhard

    2015-12-01

    Meditation is becoming an increasingly popular topic for scientific research and various effects of extensive meditation practice (ranging from weeks to several years) on cognitive processes have been demonstrated. Here we show that extensive practice may not be necessary to achieve those effects. Healthy adult non-meditators underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing an Attentional Blink (AB) task - which assesses the efficiency of allocating attention over time. The size of the AB was considerably smaller after OMM than after FAM, which suggests that engaging in meditation immediately creates a cognitive-control state that has a specific impact on how people allocate their attention over time. PMID:26320866

  16. Relative Unisensory Strength and Timing Predict Their Multisensory Product

    PubMed Central

    Pluta, Scott R.; Stein, Barry E.; Rowland, Benjamin A.

    2015-01-01

    Understanding the principles by which the brain combines information from different senses provides us with insight into the computational strategies used to maximize their utility. Prior studies of the superior colliculus (SC) neuron as a model suggest that the relative timing with which sensory cues appear is an important factor in this context. Cross-modal cues that are near-simultaneous are likely to be derived from the same event, and the neural inputs they generate are integrated more strongly than those from cues that are temporally displaced from one another. However, the present results from studies of cat SC neurons show that this “temporal principle” of multisensory integration is more nuanced than previously thought and reveal that the integration of temporally displaced sensory responses is also highly dependent on the relative efficacies with which they drive their common target neuron. Larger multisensory responses were achieved when stronger responses were advanced in time relative to weaker responses. This new temporal principle of integration suggests an inhibitory mechanism that better accounts for the sensitivity of the multisensory product to differences in the timing of cross-modal cues than do earlier mechanistic hypotheses based on response onset alignment or response overlap. PMID:25834047

  17. Relationships between Self-Regulating Behaviors and Predictor Exam Scores for Senior Nursing Students

    ERIC Educational Resources Information Center

    Gillespie, Maria

    2012-01-01

    Low pass rates on the National Council Licensure Exam for Registered Nurses have directed nursing faculty to examine how to predict the readiness of the nursing student. Exit exam testing that predicts readiness has become one way to assess the nursing student's readiness. Nursing students at the research site's school of nursing are…

  18. When univariate model-free time series prediction is better than multivariate

    NASA Astrophysics Data System (ADS)

    Chayama, Masayoshi; Hirata, Yoshito

    2016-07-01

    The delay coordinate method is known to be a practically useful technique for reconstructing the states of an observed system. While this method is theoretically supported by Takens' embedding theorem concerning observations of a scalar time series, we can extend the method to include a multivariate time series. It is often assumed that a better prediction can be obtained using a multivariate time series than by using a scalar time series. However, multivariate time series contains various types of information, and it may be difficult to extract information that is useful for predicting the states. Thus, univariate prediction may sometimes be superior to multivariate prediction. Here, we compare univariate model-free time series predictions with multivariate ones, and demonstrate that univariate model-free prediction is better than multivariate one when the prediction steps are small, while multivariate prediction performs better when the prediction steps become larger. We show the validity of the former finding by using artificial datasets generated from the Lorenz 96 models and a real solar irradiance dataset. The results indicate that it is possible to determine which method is the best choice by considering how far into the future we want to predict.

  19. Real Time Volcanic Cloud Products and Predictions for Aviation Alerts

    NASA Technical Reports Server (NTRS)

    Krotkov, Nickolay A.; Habib, Shahid; da Silva, Arlindo; Hughes, Eric; Yang, Kai; Brentzel, Kelvin; Seftor, Colin; Li, Jason Y.; Schneider, David; Guffanti, Marianne; Hoffman, Robert L.; Myers, Tim; Tamminen, Johanna; Hassinen, Seppo

    2014-01-01

    Volcanic eruptions can inject significant amounts of sulfur dioxide (SO2) and volcanic ash into the atmosphere, posing a substantial risk to aviation safety. Ingesting near-real time and Direct Readout satellite volcanic cloud data is vital for improving reliability of volcanic ash forecasts and mitigating the effects of volcanic eruptions on aviation and the economy. NASA volcanic products from the Ozone Monitoring Insrument (OMI) aboard the Aura satellite have been incorporated into Decision Support Systems of many operational agencies. With the Aura mission approaching its 10th anniversary, there is an urgent need to replace OMI data with those from the next generation operational NASA/NOAA Suomi National Polar Partnership (SNPP) satellite. The data provided from these instruments are being incorporated into forecasting models to provide quantitative ash forecasts for air traffic management. This study demonstrates the feasibility of the volcanic near-real time and Direct Readout data products from the new Ozone Monitoring and Profiling Suite (OMPS) ultraviolet sensor onboard SNPP for monitoring and forecasting volcanic clouds. The transition of NASA data production to our operational partners is outlined. Satellite observations are used to constrain volcanic cloud simulations and improve estimates of eruption parameters, resulting in more accurate forecasts. This is demonstrated for the 2012 eruption of Copahue. Volcanic eruptions are modeled using the Goddard Earth Observing System, Version 5 (GEOS-5) and the Goddard Chemistry Aerosol and Radiation Transport (GOCART) model. A hindcast of the disruptive eruption from Iceland's Eyjafjallajokull is used to estimate aviation re-routing costs using Metron Aviation's ATM Tools.

  20. Near Real Time MISR Wind Observations for Numerical Weather Prediction

    NASA Astrophysics Data System (ADS)

    Mueller, K. J.; Protack, S.; Rheingans, B. E.; Hansen, E. G.; Jovanovic, V. M.; Baker, N.; Liu, J.; Val, S.

    2014-12-01

    The Multi-angle Imaging SpectroRadiometer (MISR) project, in association with the NASA Langley Atmospheric Science Data Center (ASDC), has this year adapted its original production software to generate near-real time (NRT) cloud-motion winds as well as radiance imagery from all nine MISR cameras. These products are made publicly available at the ASDC with a latency of less than 3 hours. Launched aboard the sun-synchronous Terra platform in 1999, the MISR instrument continues to acquire near-global, 275 m resolution, multi-angle imagery. During a single 7 minute overpass of any given area, MISR retrieves the stereoscopic height and horizontal motion of clouds from the multi-angle data, yielding meso-scale near-instantaneous wind vectors. The ongoing 15-year record of MISR height-resolved winds at 17.6 km resolution has been validated against independent data sources. Low-level winds dominate the sampling, and agree to within ±3 ms-1 of collocated GOES and other observations. Low-level wind observations are of particular interest to weather forecasting, where there is a dearth of observations suitable for assimilation, in part due to reliability concerns associated with winds whose heights are assigned by the infrared brightness temperature technique. MISR cloud heights, on the other hand, are generated from stereophotogrammetric pattern matching of visible radiances. MISR winds also address data gaps in the latitude bands between geostationary satellite coverage and polar orbiting instruments that obtain winds from multiple overpasses (e.g. MODIS). Observational impact studies conducted by the Naval Research Laboratory (NRL) and by the German Weather Service (Deutscher Wetterdienst) have both demonstrated forecast improvements when assimilating MISR winds. An impact assessment using the GEOS-5 system is currently in progress. To benefit air quality forecasts, the MISR project is currently investigating the feasibility of generating near-real time aerosol products.

  1. Maternal Jail Time, Conviction, and Arrest as Predictors of Children's 15-Year Antisocial Outcomes in the Context of a Nurse Home Visiting Program

    ERIC Educational Resources Information Center

    Shlafer, Rebecca J.; Poehlmann, Julie; Donelan-McCall, Nancy

    2012-01-01

    Data from the Nurse-Family Partnership intervention program were analyzed to compare the "selection" versus "unique" effects of maternal jail time on adolescent antisocial and health risk outcomes. Data from 320 women and their firstborn children were available from the prenatal, birth, and 15-year assessments. Consistent with a selection…

  2. Mackey-Glass noisy chaotic time series prediction by a swarm-optimized neural network

    NASA Astrophysics Data System (ADS)

    López-Caraballo, C. H.; Salfate, I.; Lazzús, J. A.; Rojas, P.; Rivera, M.; Palma-Chilla, L.

    2016-05-01

    In this study, an artificial neural network (ANN) based on particle swarm optimization (PSO) was developed for the time series prediction. The hybrid ANN+PSO algorithm was applied on Mackey-Glass noiseless chaotic time series in the short-term and long-term prediction. The performance prediction is evaluated and compared with similar work in the literature, particularly for the long-term forecast. Also, we present properties of the dynamical system via the study of chaotic behaviour obtained from the time series prediction. Then, this standard hybrid ANN+PSO algorithm was complemented with a Gaussian stochastic procedure (called stochastic hybrid ANN+PSO) in order to obtain a new estimator of the predictions that also allowed us compute uncertainties of predictions for noisy Mackey-Glass chaotic time series. We study the impact of noise for three cases with a white noise level (σ N ) contribution of 0.01, 0.05 and 0.1.

  3. Effective phonocardiogram segmentation using time statistics and nonlinear prediction

    NASA Astrophysics Data System (ADS)

    Sridharan, Rajeswari; Janet, J.

    2010-02-01

    In the fields of image processing, signal processing and recognition, image Segmentation is an efficient method for segmenting the phonocardiograph signals (PCG) is offered. Primarily, inter-beat segmentation is approved and carried out by means of DII lead of the ECG recording for identifying the happenings of the very first heart sound (S1). Then, the intra-beat segmentation is attained by the use of recurrence time statistics (RTS), and that is very sensitive to variations of the renovated attractor in a state space derived from nonlinear dynamic analysis. Apart from this if the segmentation with RTS is unsuccessful, a special segmentation is proposed using threshold that is extracted from the high frequency rate decomposition and the feature extraction of the disorder is classified based on the murmur sounds. In the Inter-beat segmentation process the accuracy was 100% of the over all PCG recording. Taking into account a different level of PCG beats were strongly concerned by different types of cardiac murmurs and intra-beat segmentation are give up for an accurate result.

  4. Neural Underpinnings of Impaired Predictive Motor Timing in Children with Developmental Coordination Disorder

    ERIC Educational Resources Information Center

    Debrabant, Julie; Gheysen, Freja; Caeyenberghs, Karen; Van Waelvelde, Hilde; Vingerhoets, Guy

    2013-01-01

    A dysfunction in predictive motor timing is put forward to underlie DCD-related motor problems. Predictive timing allows for the pre-selection of motor programmes (except "program" in computers) in order to decrease processing load and facilitate reactions. Using functional magnetic resonance imaging (fMRI), this study investigated the neural…

  5. Time to First Cigarette Predicts Cessation Outcomes in Adolescent Smokers

    PubMed Central

    Branstetter, Steven A.; Muscat, Joshua E.; Horn, Kimberly A.

    2013-01-01

    Introduction: This study examined the relationship between the time to the first cigarette (TTFC) of the morning with quit status among adolescent smokers at the completion of a school-based smoking cessation program. Among those who did not quit, the relationship of TTFC with changes in cigarettes/day (CPD) was also examined. Methods: A total of 1,167 adolescent smokers (1,024 nonquitters and 143 quitters) from 4 states participating in efficacy and effectiveness studies of the Not-On-Tobacco (N-O-T) cessation program were assessed prior to entry into the program and again 3 months later at the end of treatment. Linear and logistic regression analyses determined the influence of treatment condition, age, gender, motivation to quit, confidence in quitting ability, baseline CPD, and TTFC on quit status and end-of-treatment CPD. Results: Adolescents with a TTFC of >30min of waking were twice as likely to quit at end of treatment. Additionally, among those who did not quit at end of treatment (n = 700 for TTFC ≤30min and n = 324 for TTFC for >30min), those with a TTFC within 30min of waking smoked a greater number of CPD. The relationships of TTFC with both of these outcomes remained when controlling for all other predictor variables. Conclusions: Identifying adolescent smokers who smoke their first cigarette of the day within the first 30min of waking prior to a quit attempt may help to classify those individuals as having a greater risk for cessation failure. Thus, TTFC may be a behavioral indicator of nicotine dependence in adolescents. PMID:23811009

  6. Operational Precipitation prediction in Support of Real-Time Flash Flood Prediction and Reservoir Management

    NASA Astrophysics Data System (ADS)

    Georgakakos, K. P.

    2006-05-01

    The presentation will outline the implementation and performance evaluation of a number of national and international projects pertaining to operational precipitation estimation and prediction in the context of hydrologic warning systems and reservoir management support. In all cases, uncertainty measures of the estimates and predictions are an integral part of the precipitation models. Outstanding research issues whose resolution is likely to lead to improvements in the operational environment are presented. The presentation draws from the experience of the Hydrologic Research Center (http://www.hrc-lab.org) prototype implementation projects at the Panama Canal, Central America, Northern California, and South-Central US. References: Carpenter, T.M, and K.P. Georgakakos, "Discretization Scale Dependencies of the Ensemble Flow Range versus Catchment Area Relationship in Distributed Hydrologic Modeling," Journal of Hydrology, 2006, in press. Carpenter, T.M., and K.P. Georgakakos, "Impacts of Parametric and Radar Rainfall Uncertainty on the Ensemble Streamflow Simulations of a Distributed Hydrologic Model," Journal of Hydrology, 298, 202-221, 2004. Georgakakos, K.P., Graham, N.E., Carpenter, T.M., Georgakakos, A.P., and H. Yao, "Integrating Climate- Hydrology Forecasts and Multi-Objective Reservoir Management in Northern California," EOS, 86(12), 122,127, 2005. Georgakakos, K.P., and J.A. Sperfslage, "Operational Rainfall and Flow Forecasting for the Panama Canal Watershed," in The Rio Chagres: A Multidisciplinary Profile of a Tropical Watershed, R.S. Harmon, ed., Kluwer Academic Publishers, The Netherlands, Chapter 16, 323-334, 2005. Georgakakos, K. P., "Analytical results for operational flash flood guidance," Journal of Hydrology, doi:10.1016/j.jhydrol.2005.05.009, 2005.

  7. Nursing, Nursing Education, and Anxiety.

    ERIC Educational Resources Information Center

    Biggers, Thompson; And Others

    In response to the current crisis in the field of nursing, a study examined nursing students' perceived work-related stress and differences among associate degree, diploma, and baccalaureate nursing programs in their preparation of nursing students. The 171 subjects, representing the three different nursing programs, completed a questionnaire…

  8. A nursing diagnosis based model: guiding nursing practice.

    PubMed

    Krenz, M; Karlik, B; Kiniry, S

    1989-05-01

    Fiscal uncertainty, anxiety about nursing retention, and public scrutiny characterize the hospital milieu. During times such as these, introducing a conceptual model may appear inpractical and untimely. However, the conceptual model at Robert Wood Johnson University Hospital has demonstrated many practical applications. It guides nursing practice and provides a framework for quality assurance, documentation of nursing care, and education of nurses in the hospital. Future plans include using the model as a basis for developing a computerized care planning system and a method for cost accounting for nursing. The authors describe how the model serves to unify, give direction, simplify, and improve nursing practice. PMID:2723785

  9. Nursing Homes

    MedlinePlus

    ... our e-newsletter! Aging & Health A to Z Nursing Homes Basic Facts & Information Nursing homes have changed ... physical health and/or mental disabilities. Is a Nursing Home Right for You? Almost half of all ...

  10. Nursing Positions

    MedlinePlus

    ... Story" 5 Things to Know About Zika & Pregnancy Nursing Positions KidsHealth > For Parents > Nursing Positions Print A ... and actually needs to feed. Getting Comfortable With Breastfeeding Nursing can be one of the most challenging ...

  11. Applying talent management to nursing.

    PubMed

    Haines, Sue

    To deliver the chief nursing officer for England's vision for compassionate care and embed the 6Cs effectively, the NHS must attract, develop and retain talented nurses with a diverse range of skills. This is particularly important given the predicted shortage of nurses and evidence that NHS providers need to increase skill mix ratios to deliver safe patient care. "Talent management" is increasingly discussed within the health service; we recently asked nurses and student nurses to identify their priorities for talent development. They highlighted the importance of strong ward leadership, effective personal appraisal, clearer career pathways, increased staff engagement and involvement in decision making, as well as a need for greater emphasis on the recognition and reward of nursing achievements. We concluded that these factors are crucial to attracting, retaining and developing talent in nursing. Nurse leaders can learn approaches to developing talent from business and wider healthcare settings. PMID:24380172

  12. A Comparison of Students' Performance under Full-Time, Part-Time, and Online Conditions in an Undergraduate Nursing Microbiology Course

    ERIC Educational Resources Information Center

    Carbanaro, Michael; Dawber, Tess; Arav, Isanna

    2006-01-01

    The purpose of this study was to compare undergraduate nursing students' achievement on examinations for three groups in a mandatory microbiology course. The study represents one aspect of a larger research project designed to gain insight into factors that may influence online learning for distance education nursing students at a Canadian…

  13. Visual Analysis of time-dependent 2D Uncertainties in Decadal Climate Predictions

    NASA Astrophysics Data System (ADS)

    Böttinger, Michael; Röber, Niklas; Meier-Fleischer, Karin; Pohlmann, Holger

    2016-04-01

    Climate prediction systems used today for investigating the climate predictability on a decadal time scale are based on coupled global climate models. First, ensembles of hindcast experiments are carried out in order to derive the predictive skill of the prediction system. Then, in a second step, the prediction system is initialized with observations and actual future predictions are computed. The ensemble simulation techniques applied enable issuing of probabilistic information along with the quantities predicted. Different aspects of the uncertainty can be derived: The ensemble standard deviation (or ensemble spread) is a measure for the internal variability of the simulation, while the predictive skill is an inverse measure for the uncertainty in the prediction. In this work, we focus on the concurrent visualization of three related time-dependent 2D fields: the forecast variable itself, here the 2m temperature anomaly, along with the corresponding predictive skill and the ensemble spread which is given through the ensemble standard deviation. On the basis of temporally filtered data, animations are used to visualize the mean spatio-temporal development of the three quantities. Furthermore, seasonal analyses are similarly visualized in order to identify seasonal patterns. We show exemplary solutions produced with three different visualization systems: NCL, Avizo Green and ParaView. As example data set, we have used a decadal climate prediction carried out within the German research project "MiKlip - Decadal Predictions" using the MPI-M Earth System Model (MPI-ESM) from the Max Planck Institute for Meteorology in Hamburg.

  14. Two States Mapping Based Time Series Neural Network Model for Compensation Prediction Residual Error

    NASA Astrophysics Data System (ADS)

    Jung, Insung; Koo, Lockjo; Wang, Gi-Nam

    2008-11-01

    The objective of this paper was to design a model of human bio signal data prediction system for decreasing of prediction error using two states mapping based time series neural network BP (back-propagation) model. Normally, a lot of the industry has been applied neural network model by training them in a supervised manner with the error back-propagation algorithm for time series prediction systems. However, it still has got a residual error between real value and prediction result. Therefore, we designed two states of neural network model for compensation residual error which is possible to use in the prevention of sudden death and metabolic syndrome disease such as hypertension disease and obesity. We determined that most of the simulation cases were satisfied by the two states mapping based time series prediction model. In particular, small sample size of times series were more accurate than the standard MLP model.

  15. Impact of the stage of dementia on the time required for bathing-related care: a pilot study in a Japanese nursing home.

    PubMed

    Kobayashi, Nami; Yamamoto, Mariko

    2004-09-01

    Time required for bathing-related care for nursing home residents with various stages of severe dementia were observed. Time required for each resident, including guiding to the bathroom, undressing, and dressing were plotted in graphs in order to make comparisons. The situations and conversations observed for the instances when additional time was needed were analyzed. Stage of dementia affected the amount of time required for the task of guiding to the bathroom, but did not appear to affect time required for dressing or undressing. For dressing and undressing, additional time was required when caregivers failed to keep to a specific routine. PMID:15288799

  16. Time series prediction of lung cancer patients' breathing pattern based on nonlinear dynamics.

    PubMed

    Tolakanahalli, R P; Tewatia, D K; Tomé, W A

    2015-05-01

    This study focuses on predicting breathing pattern, which is crucial to deal with system latency in the treatments of moving lung tumors. Predicting respiratory motion in real-time is challenging, due to the inherent chaotic nature of breathing patterns, i.e. sensitive dependence on initial conditions. In this work, nonlinear prediction methods are used to predict the short-term evolution of the respiratory system for 62 patients, whose breathing time series was acquired using respiratory position management (RPM) system. Single step and N-point multi step prediction are performed for sampling rates of 5 Hz and 10 Hz. We compare the employed non-linear prediction methods with respect to prediction accuracy to Adaptive Infinite Impulse Response (IIR) prediction filters. A Local Average Model (LAM) and local linear models (LLMs) combined with a set of linear regularization techniques to solve ill-posed regression problems are implemented. For all sampling frequencies both single step and N-point multi step prediction results obtained using LAM and LLM with regularization methods perform better than IIR prediction filters for the selected sample patients. Moreover, since the simple LAM model performs as well as the more complicated LLM models in our patient sample, its use for non-linear prediction is recommended. PMID:25726478

  17. Impaired Spatio-Temporal Predictive Motor Timing Associated with Spinocerebellar Ataxia Type 6.

    PubMed

    Broersen, Robin; Onuki, Yoshiyuki; Abdelgabar, Abdel R; Owens, Cullen B; Picard, Samuel; Willems, Jessica; Boele, Henk-Jan; Gazzola, Valeria; Van der Werf, Ysbrand D; De Zeeuw, Chris I

    2016-01-01

    Many daily life activities demand precise integration of spatial and temporal information of sensory inputs followed by appropriate motor actions. This type of integration is carried out in part by the cerebellum, which has been postulated to play a central role in learning and timing of movements. Cerebellar damage due to atrophy or lesions may compromise forward-model processing, in which both spatial and temporal cues are used to achieve prediction for future motor states. In the present study we sought to further investigate the cerebellar contribution to predictive and reactive motor timing, as well as to learning of sequential order and temporal intervals in these tasks. We tested patients with spinocerebellar ataxia type 6 (SCA6) and healthy controls for two related motor tasks; one requiring spatio-temporal prediction of dynamic visual stimuli and another one requiring reactive timing only. We found that healthy controls established spatio-temporal prediction in their responses with high temporal precision, which was absent in the cerebellar patients. SCA6 patients showed lower predictive motor timing, coinciding with a reduced number of correct responses during the 'anticipatory' period on the task. Moreover, on the task utilizing reactive motor timing functions, control participants showed both sequence order and temporal interval learning, whereas patients only showed sequence order learning. These results suggest that SCA6 affects predictive motor timing and temporal interval learning. Our results support and highlight cerebellar contribution to timing and argue for cerebellar engagement during spatio-temporal prediction of upcoming events. PMID:27571363

  18. Impaired Spatio-Temporal Predictive Motor Timing Associated with Spinocerebellar Ataxia Type 6

    PubMed Central

    Onuki, Yoshiyuki; Abdelgabar, Abdel R.; Owens, Cullen B.; Picard, Samuel; Willems, Jessica; Boele, Henk-Jan; Gazzola, Valeria; Van der Werf, Ysbrand D.; De Zeeuw, Chris I.

    2016-01-01

    Many daily life activities demand precise integration of spatial and temporal information of sensory inputs followed by appropriate motor actions. This type of integration is carried out in part by the cerebellum, which has been postulated to play a central role in learning and timing of movements. Cerebellar damage due to atrophy or lesions may compromise forward-model processing, in which both spatial and temporal cues are used to achieve prediction for future motor states. In the present study we sought to further investigate the cerebellar contribution to predictive and reactive motor timing, as well as to learning of sequential order and temporal intervals in these tasks. We tested patients with spinocerebellar ataxia type 6 (SCA6) and healthy controls for two related motor tasks; one requiring spatio-temporal prediction of dynamic visual stimuli and another one requiring reactive timing only. We found that healthy controls established spatio-temporal prediction in their responses with high temporal precision, which was absent in the cerebellar patients. SCA6 patients showed lower predictive motor timing, coinciding with a reduced number of correct responses during the ‘anticipatory’ period on the task. Moreover, on the task utilizing reactive motor timing functions, control participants showed both sequence order and temporal interval learning, whereas patients only showed sequence order learning. These results suggest that SCA6 affects predictive motor timing and temporal interval learning. Our results support and highlight cerebellar contribution to timing and argue for cerebellar engagement during spatio-temporal prediction of upcoming events. PMID:27571363

  19. Communication in Nursing Practice

    PubMed Central

    Kourkouta, Lambrini; Papathanasiou, Ioanna V.

    2014-01-01

    Good communication between nurses and patients is essential for the successful outcome of individualized nursing care of each patient. To achieve this, however, nurses must understand and help their patients, demonstrating courtesy, kindness and sincerity. Also they should devote time to the patient to communicate with the necessary confidentiality, and must not forget that this communication includes persons who surround the sick person, which is why the language of communication should be understood by all those involved in it. Good communication also is not only based on the physical abilities of nurses, but also on education and experience. PMID:24757408

  20. Nursing: Registered Nurses

    MedlinePlus

    ... nurses for jobs in health planning and development, marketing, consulting, policy development, and quality assurance. Some RNs ... workers was $36,200. Recommend this page using: Facebook Twitter LinkedIn tools Areas at a Glance Industries ...

  1. Error criteria for cross validation in the context of chaotic time series prediction

    NASA Astrophysics Data System (ADS)

    Lim, Teck Por; Puthusserypady, Sadasivan

    2006-03-01

    The prediction of a chaotic time series over a long horizon is commonly done by iterating one-step-ahead prediction. Prediction can be implemented using machine learning methods, such as radial basis function networks. Typically, cross validation is used to select prediction models based on mean squared error. The bias-variance dilemma dictates that there is an inevitable tradeoff between bias and variance. However, invariants of chaotic systems are unchanged by linear transformations; thus, the bias component may be irrelevant to model selection in the context of chaotic time series prediction. Hence, the use of error variance for model selection, instead of mean squared error, is examined. Clipping is introduced, as a simple way to stabilize iterated predictions. It is shown that using the error variance for model selection, in combination with clipping, may result in better models.

  2. Time for prediction? The effect of presentation rate on predictive sentence comprehension during word-by-word reading.

    PubMed

    Wlotko, Edward W; Federmeier, Kara D

    2015-07-01

    Predictive processing is a core component of normal language comprehension, but the brain may not engage in prediction to the same extent in all circumstances. This study investigates the effects of timing on anticipatory comprehension mechanisms. Event-related brain potentials (ERPs) were recorded while participants read two-sentence mini-scenarios previously shown to elicit prediction-related effects for implausible items that are categorically related to expected items ('They wanted to make the hotel look more like a tropical resort. So along the driveway they planted rows of PALMS/PINES/TULIPS.'). The first sentence of every pair was presented in its entirety and was self-paced. The second sentence was presented word-by-word with a fixed stimulus onset asynchrony (SOA) of either 500 msec or 250 msec that was manipulated in a within-subjects blocked design. Amplitudes of the N400 ERP component are taken as a neural index of demands on semantic processing. At 500 msec SOA, implausible words related to predictable words elicited reduced N400 amplitudes compared to unrelated words (PINES vs TULIPS), replicating past studies. At 250 msec SOA this prediction-related semantic facilitation was diminished. Thus, timing is a factor in determining the extent to which anticipatory mechanisms are engaged. However, we found evidence that prediction can sometimes be engaged even under speeded presentation rates. Participants who first read sentences in the 250 msec SOA block showed no effect of semantic similarity for this SOA, although these same participants showed the effect in the second block with 500 msec SOA. However, participants who first read sentences in the 500 msec SOA block continued to show the N400 semantic similarity effect in the 250 msec SOA block. These findings add to results showing that the brain flexibly allocates resources to most effectively achieve comprehension goals given the current processing environment. PMID:25987437

  3. The remittances of migrant Tongan and Samoan nurses from Australia

    PubMed Central

    Connell, John; Brown, Richard PC

    2004-01-01

    Background Migration and remittances are of considerable importance in the small Pacific island states. There has been a significant migration of skilled health workers in recent decades to metropolitan fringe states, including Australia and New Zealand. This paper reports the findings of a re-analysis of survey of Samoan and Tongan migrants in Australia where the sample is split between nurse households and others. Methods The study analyzes the survey data with a view to comparing the remittance behaviour and determinants of remittances for nurses and other migrant households, using both descriptive, cross-tabulations and appropriate econometric methods. Results It is found that a significantly higher proportion of nurse households sent remittances home, and, on average remitted more. Remittances of nurse households did not decline significantly over time contrary to what has generally been predicted. This was in contrast to other migrant households in the sample, for whom remittances showed a sharp decline after 15 years absence. Remittances contribute much more to the income of migrant sending countries, than the cost of the additional human capital in nurse training. Conclusions Given the shortage of nurses in Australia and New Zealand, and therefore the high demand for immigrant nurses, investment by Pacific island governments and families in nurse training constitutes a rational use of economic resources. Policies encouraging investment in home countries may be more effective than policies directly discouraging brain drain in contributing to national development. PMID:15078577

  4. The remittances of migrant Tongan and Samoan nurses from Australia.

    PubMed

    Connell, John; Brown, Richard PC

    2004-04-13

    BACKGROUND: Migration and remittances are of considerable importance in the small Pacific island states. There has been a significant migration of skilled health workers in recent decades to metropolitan fringe states, including Australia and New Zealand. This paper reports the findings of a re-analysis of survey of Samoan and Tongan migrants in Australia where the sample is split between nurse households and others. METHODS: The study analyzes the survey data with a view to comparing the remittance behaviour and determinants of remittances for nurses and other migrant households, using both descriptive, cross-tabulations and appropriate econometric methods. RESULTS: It is found that a significantly higher proportion of nurse households sent remittances home, and, on average remitted more. Remittances of nurse households did not decline significantly over time contrary to what has generally been predicted. This was in contrast to other migrant households in the sample, for whom remittances showed a sharp decline after 15 years absence. Remittances contribute much more to the income of migrant sending countries, than the cost of the additional human capital in nurse training. CONCLUSIONS: Given the shortage of nurses in Australia and New Zealand, and therefore the high demand for immigrant nurses, investment by Pacific island governments and families in nurse training constitutes a rational use of economic resources. Policies encouraging investment in home countries may be more effective than policies directly discouraging brain drain in contributing to national development. PMID:15078577

  5. Comparison of time series models for predicting campylobacteriosis risk in New Zealand.

    PubMed

    Al-Sakkaf, A; Jones, G

    2014-05-01

    Predicting campylobacteriosis cases is a matter of considerable concern in New Zealand, after the number of the notified cases was the highest among the developed countries in 2006. Thus, there is a need to develop a model or a tool to predict accurately the number of campylobacteriosis cases as the Microbial Risk Assessment Model used to predict the number of campylobacteriosis cases failed to predict accurately the number of actual cases. We explore the appropriateness of classical time series modelling approaches for predicting campylobacteriosis. Finding the most appropriate time series model for New Zealand data has additional practical considerations given a possible structural change, that is, a specific and sudden change in response to the implemented interventions. A univariate methodological approach was used to predict monthly disease cases using New Zealand surveillance data of campylobacteriosis incidence from 1998 to 2009. The data from the years 1998 to 2008 were used to model the time series with the year 2009 held out of the data set for model validation. The best two models were then fitted to the full 1998-2009 data and used to predict for each month of 2010. The Holt-Winters (multiplicative) and ARIMA (additive) intervention models were considered the best models for predicting campylobacteriosis in New Zealand. It was noticed that the prediction by an additive ARIMA with intervention was slightly better than the prediction by a Holt-Winter multiplicative method for the annual total in year 2010, the former predicting only 23 cases less than the actual reported cases. It is confirmed that classical time series techniques such as ARIMA with intervention and Holt-Winters can provide a good prediction performance for campylobacteriosis risk in New Zealand. The results reported by this study are useful to the New Zealand Health and Safety Authority's efforts in addressing the problem of the campylobacteriosis epidemic. PMID:23551848

  6. Essays on the predictability of oil shocks and yield curves for real-time output growth

    NASA Astrophysics Data System (ADS)

    Carlton, Amelie B.

    This dissertation is a collection of three essays that revisits the long-standing puzzle of the apparently disproportionate effect of oil prices in the economy by examining output growth predictability with real-time data. Each study of the predictive content of oil shocks is from a different perspective by using newly developed real-time datasets, which allows for replicating the economic environment faced by policymakers in real time. The first study extends the conventional set of models of output growth determination by investigating predictability of models that incorporate various functional forms of oil prices and real-time data. The results are supportive of the relationship of GDP and oil in the context of Granger causality with real-time data. In the second essay, I use oil shocks to predict the economy is changing direction earlier than would be predicted by solely using initial GDP releases. The model provides compelling evidence of negative GDP growth predictability in response to oil price shocks, which could shorten the "recognition lag" for successful implementation of discretionary counter-cyclical policies. In the third essay, I evaluate short-horizon output growth predictability using real-time data for different sample periods. I find strong evidence of predictability at the one-quarter and four-quarter horizon for the United States. The major result of the paper is that we reject the null hypothesis of no predictability against an alternative hypothesis of predictability with oil shocks that include yield curves in the forecasting regression. This relationship suggests the combination of monetary policy and oil shocks are important for subsequent GDP growth.

  7. ScaleNet--multiscale neural-network architecture for time series prediction.

    PubMed

    Geva, A B

    1998-01-01

    The effectiveness of a multiscale neural-network (NN) architecture for the time series prediction of nonlinear dynamic systems has been investigated. The prediction task is simplified by decomposing different scales of past windows into different scales of wavelets (local frequencies), and predicting the coefficients of each scale of wavelets by means of a separate multilayer perceptron NN. The short-term history (short past windows) is decomposed into the lower scales of wavelet coefficients (high frequencies) which are utilized for "detailed" analysis and prediction, while the long-term history (long past window) is decomposed into higher scales of wavelet coefficients (low frequencies) that are used for the analysis and prediction of slow trends in the time series. These coordinated scales of time and frequency provides an interpretation of the series structures, and more information about the history of the series, using fewer coefficients than other methods. The prediction's results concerning all the different scales of time and frequencies are combined by another "expert" perceptron NN which learns the weight of each scale in the goal-prediction of the original time series. Each network is trained by the backpropagation algorithm using the Levenberg-Marquadt method. The weights and biases are initialized by a new clustering algorithm of the temporal patterns of the time series, which improves the prediction results as compared to random initialization. Three main sets of data were analyzed: the sunspots' benchmark, fluctuations in a farinfrared laser and a nonlinear numerically generated series. Taking the ultimate goal to be the accuracy of the prediction, we found that the suggested multiscale architecture outperforms the corresponding single-scale architectures. The employment of improved learning methods for each of the ScaleNet networks can further improve the prediction results. PMID:18255824

  8. Differences in Motor Imagery Time when Predicting Task Duration in Alpine Skiers and Equestrian Riders

    ERIC Educational Resources Information Center

    Louis, Magali; Collet, Christian; Champely, Stephane; Guillot, Aymeric

    2012-01-01

    Athletes' ability to use motor imagery (MI) to predict the speed at which they could perform a motor sequence has received little attention. In this study, 21 alpine skiers and 16 equestrian riders performed MI based on a prediction of actual performance time (a) after the course inspection, (b) before the start, and (c) after the actual…

  9. Distance education in nursing.

    PubMed

    Billings, D M

    1996-01-01

    Although not for everyone, distance education is a "connecting point" for faculty and students who are separated by time and space. As technology becomes increasingly available to nurse educators, the instructional and public relations advantages become significant benefits to nurse educators. PMID:8718839

  10. Prediction of altimetric sea level anomalies using time series models based on spatial correlation

    NASA Astrophysics Data System (ADS)

    Miziński, Bartłomiej; Niedzielski, Tomasz

    2014-05-01

    Sea level anomaly (SLA) times series, which are time-varying gridded data, can be modelled and predicted using time series methods. This approach has been shown to provide accurate forecasts within the Prognocean system, the novel infrastructure for anticipating sea level change designed and built at the University of Wrocław (Poland) which utilizes the real-time SLA data from Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO). The system runs a few models concurrently, and our ocean prediction experiment includes both uni- and multivariate time series methods. The univariate ones are: extrapolation of polynomial-harmonic model (PH), extrapolation of polynomial-harmonic model and autoregressive prediction (PH+AR), extrapolation of polynomial-harmonic model and self-exciting threshold autoregressive prediction (PH+SETAR). The following multivariate methods are used: extrapolation of polynomial-harmonic model and vector autoregressive prediction (PH+VAR), extrapolation of polynomial-harmonic model and generalized space-time autoregressive prediction (PH+GSTAR). As the aforementioned models and the corresponding forecasts are computed in real time, hence independently and in the same computational setting, we are allowed to compare the accuracies offered by the models. The objective of this work is to verify the hypothesis that the multivariate prediction techniques, which make use of cross-correlation and spatial correlation, perform better than the univariate ones. The analysis is based on the daily-fitted and updated time series models predicting the SLA data (lead time of two weeks) over several months when El Niño/Southern Oscillation (ENSO) was in its neutral state.

  11. Advanced practice registered nurse certification.

    PubMed

    Alleman, Kim; Houle, Katherine

    2013-01-01

    Advanced practice registered nurses (APRNs) in nephrology began to be certified through the Nephrology Nursing Certification Commission (NNCC) in 2006. Since that time, the APRN Consensus Model has been developed, which addresses licensure, accreditation, certification, and education and which strongly recommends specialty certification for advanced practice nurses. This article discusses NNCC certification for advanced practice in nephrology nursing and describes the major components of the APRN Consensus Model. PMID:23923801

  12. Predicting analysis time in events-driven clinical trials using accumulating time-to-event surrogate information.

    PubMed

    Wang, Jianming; Ke, Chunlei; Yu, Zhinuan; Fu, Lei; Dornseif, Bruce

    2016-05-01

    For clinical trials with time-to-event endpoints, predicting the accrual of the events of interest with precision is critical in determining the timing of interim and final analyses. For example, overall survival (OS) is often chosen as the primary efficacy endpoint in oncology studies, with planned interim and final analyses at a pre-specified number of deaths. Often, correlated surrogate information, such as time-to-progression (TTP) and progression-free survival, are also collected as secondary efficacy endpoints. It would be appealing to borrow strength from the surrogate information to improve the precision of the analysis time prediction. Currently available methods in the literature for predicting analysis timings do not consider utilizing the surrogate information. In this article, using OS and TTP as an example, a general parametric model for OS and TTP is proposed, with the assumption that disease progression could change the course of the overall survival. Progression-free survival, related both to OS and TTP, will be handled separately, as it can be derived from OS and TTP. The authors seek to develop a prediction procedure using a Bayesian method and provide detailed implementation strategies under certain assumptions. Simulations are performed to evaluate the performance of the proposed method. An application to a real study is also provided. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26689725

  13. Predicting Homework Time Management at the Secondary School Level: A Multilevel Analysis

    ERIC Educational Resources Information Center

    Xu, Jianzhong

    2010-01-01

    The purpose of this study is to test empirical models of variables posited to predict homework time management at the secondary school level. Student- and class-level predictors of homework time management were analyzed in a survey of 1895 students from 111 classes. Most of the variance in homework time management occurred at the student level,…

  14. Development and Validation of a New Air Carrier Block Time Prediction Model and Methodology

    NASA Astrophysics Data System (ADS)

    Litvay, Robyn Olson

    Commercial airline operations rely on predicted block times as the foundation for critical, successive decisions that include fuel purchasing, crew scheduling, and airport facility usage planning. Small inaccuracies in the predicted block times have the potential to result in huge financial losses, and, with profit margins for airline operations currently almost nonexistent, potentially negate any possible profit. Although optimization techniques have resulted in many models targeting airline operations, the challenge of accurately predicting and quantifying variables months in advance remains elusive. The objective of this work is the development of an airline block time prediction model and methodology that is practical, easily implemented, and easily updated. Research was accomplished, and actual U.S., domestic, flight data from a major airline was utilized, to develop a model to predict airline block times with increased accuracy and smaller variance in the actual times from the predicted times. This reduction in variance represents tens of millions of dollars (U.S.) per year in operational cost savings for an individual airline. A new methodology for block time prediction is constructed using a regression model as the base, as it has both deterministic and probabilistic components, and historic block time distributions. The estimation of the block times for commercial, domestic, airline operations requires a probabilistic, general model that can be easily customized for a specific airline’s network. As individual block times vary by season, by day, and by time of day, the challenge is to make general, long-term estimations representing the average, actual block times while minimizing the variation. Predictions of block times for the third quarter months of July and August of 2011 were calculated using this new model. The resulting, actual block times were obtained from the Research and Innovative Technology Administration, Bureau of Transportation Statistics

  15. Predicting Hyper-Chaotic Time Series Using Adaptive Higher-Order Nonlinear Filter

    NASA Astrophysics Data System (ADS)

    Zhang, Jia-Shu; Xiao, Xian-Ci

    2001-03-01

    A newly proposed method, i.e. the adaptive higher-order nonlinear finite impulse response (HONFIR) filter based on higher-order sparse Volterra series expansions, is introduced to predict hyper-chaotic time series. The effectiveness of using the adaptive HONFIR filter for making one-step and multi-step predictions is tested based on very few data points by computer-generated hyper-chaotic time series including the Mackey-Glass equation and four-dimensional nonlinear dynamical system. A comparison is made with some neural networks for predicting the Mackey-Glass hyper-chaotic time series. Numerical simulation results show that the adaptive HONFIR filter proposed here is a very powerful tool for making prediction of hyper-chaotic time series.

  16. Evaluation of the predictability of real-time crash risk models.

    PubMed

    Xu, Chengcheng; Liu, Pan; Wang, Wei

    2016-09-01

    The primary objective of the present study was to investigate the predictability of crash risk models that were developed using high-resolution real-time traffic data. More specifically the present study sought answers to the following questions: (a) how to evaluate the predictability of a real-time crash risk model; and (b) how to improve the predictability of a real-time crash risk model. The predictability is defined as the crash probability given the crash precursor identified by the crash risk model. An equation was derived based on the Bayes' theorem for estimating approximately the predictability of crash risk models. The estimated predictability was then used to quantitatively evaluate the effects of the threshold of crash precursors, the matched and unmatched case-control design, and the control-to-case ratio on the predictability of crash risk models. It was found that: (a) the predictability of a crash risk model can be measured as the product of prior crash probability and the ratio between sensitivity and false alarm rate; (b) there is a trade-off between the predictability and sensitivity of a real-time crash risk model; (c) for a given level of sensitivity, the predictability of the crash risk model that is developed using the unmatched case-controlled sample is always better than that of the model developed using the matched case-controlled sample; and (d) when the control-to-case ratio is beyond 4:1, the increase in control-to-case ratio does not lead to clear improvements in predictability. PMID:27332063

  17. Nurses' perceptions of patients' requirements for nursing resources.

    PubMed

    Dunn, Sandra V; Schmitz, Karl

    2005-01-01

    The study used semi-structured interviews in an interpretive research design to explore nurses' perceptions of patients requiring disproportionate amounts of nursing resources, and factors influencing those perceptions. A total of 50 senior nurses from a variety of medical and surgical settings, including a high dependency unit, were interviewed and the data analysed to determine common themes and differences between participants. The four major themes of patient characteristics, family needs, staffing and organisational context defined the factors nurses perceived as influencing their perceptions of patients' dependency. Patient requirements for nursing resources were seen as a continuum rather than a specific point, and were balanced on the combined influences of the four themes. At times, demands imposed on nursing resources lead to nurses' perceptions of delivering less than ideal care, stress and frustration. The latter applied particularly to factors that were outside of the control of nurses such as staffing levels and skill mix. PMID:16499239

  18. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

    PubMed Central

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

  19. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

    PubMed

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

  20. Cortical delta activity reflects reward prediction error and related behavioral adjustments, but at different times.

    PubMed

    Cavanagh, James F

    2015-04-15

    Recent work has suggested that reward prediction errors elicit a positive voltage deflection in the scalp-recorded electroencephalogram (EEG); an event sometimes termed a reward positivity. However, a strong test of this proposed relationship remains to be defined. Other important questions remain unaddressed: such as the role of the reward positivity in predicting future behavioral adjustments that maximize reward. To answer these questions, a three-armed bandit task was used to investigate the role of positive prediction errors during trial-by-trial exploration and task-set based exploitation. The feedback-locked reward positivity was characterized by delta band activities, and these related EEG features scaled with the degree of a computationally derived positive prediction error. However, these phenomena were also dissociated: the computational model predicted exploitative action selection and related response time speeding whereas the feedback-locked EEG features did not. Compellingly, delta band dynamics time-locked to the subsequent bandit (the P3) successfully predicted these behaviors. These bandit-locked findings included an enhanced parietal to motor cortex delta phase lag that correlated with the degree of response time speeding, suggesting a mechanistic role for delta band activities in motivating action selection. This dissociation in feedback vs. bandit locked EEG signals is interpreted as a differentiation in hierarchically distinct types of prediction error, yielding novel predictions about these dissociable delta band phenomena during reinforcement learning and decision making. PMID:25676913

  1. Predictive fuzzy reasoning method for time series stock market data mining

    NASA Astrophysics Data System (ADS)

    Khokhar, Rashid H.; Md Sap, Mohd Noor

    2005-03-01

    Data mining is able to uncover hidden patterns and predict future trends and behaviors in financial markets. In this research we approach quantitative time series stock selection as a data mining problem. We present another modification of extraction of weighted fuzzy production rules (WFPRs) from fuzzy decision tree by using proposed similarity-based fuzzy reasoning method called predictive reasoning (PR) method. In proposed predictive reasoning method weight parameter can be assigned to each proposition in the antecedent of a fuzzy production rule (FPR) and certainty factor (CF) to each rule. Certainty factors are calculated by using some important variables like effect of other companies, effect of other local stock market, effect of overall world situation, and effect of political situation from stock market. The predictive FDT has been tested using three data sets including KLSE, NYSE and LSE. The experimental results show that WFPRs rules have high learning accuracy and also better predictive accuracy of stock market time series data.

  2. Nurses' perceptions of administrative social support.

    PubMed

    Ihlenfeld, J T

    1996-01-01

    A meta-analysis of 125 nurses in three types of nursing roles investigated whether these nurses received social support from their administrators, the types of social support received, and whether more or less social support from these managers was desired. The Arizona Social Support Interview Schedule (ASSIS) was used to assess these questions. Results showed that home health nurses received social participation and physical assistance, whereas staff nurses received positive feedback and physical assistance. Nursing faculty received little support from their managers. Social exchange theory predicts that intangibles such as social support should exist in equitable relationships. It is possible that the difference in the nurses' and administrators' statuses and power levels affected staff nurses' results. Mental health clinical nurse specialists can use these results to help nurses understand their work relationships. PMID:8920344

  3. [Discourses on the nursing and psychiatric nurse models, published in the Annals of Nursing (1933-1951)].

    PubMed

    Pereira, Michelle de Macedo; Padilha, Maria Itayra; de Oliveira, Alexandre Barbosa; Santos, Tânia Cristina Franco; Filho, Antonio José de Almeida; Peres, Maria Angélica de Almeida

    2014-06-01

    Social-historical study aimed at discussing the nursing and psychiatric nurse models, from the discourses published in the Annals of Nursing.The historical sources were articles published in the Annals of Nursing journal, from 1933 to 1951. An analysis of the discourse was subsidized by the genealogy of power by Michel Foucault.The analysis showed that the discourse on nursing and the psychiatric nurse, in the first half of the 20th century, is set, on one side, by the propositions used by psychiatrists, who sought to reiterate stereotypes and vocations to practice nursing, and, on the other side, by the active participation of nurses seeking to legitimize expertise for psychiatric nursing. It was concluded that the discourses analyzed defined a psychiatric care focused on the nurse and not the rest of the nursing staff, at that time. PMID:25158460

  4. Using Kalman Filtering to Predict Time-Varying Parameters in a Model Predicting Baroreflex Regulation During Head-Up Tilt.

    PubMed

    Matzuka, Brett; Mehlsen, Jesper; Tran, Hien; Olufsen, Mette Sofie

    2015-08-01

    The cardiovascular control system is continuously engaged to maintain homeostasis, but it is known to fail in a large cohort of patients suffering from orthostatic intolerance. Numerous clinical studies have been put forward to understand how the system fails, yet noninvasive clinical data are sparse, typical studies only include measurements of heart rate and blood pressure, as a result it is difficult to determine what mechanisms that are impaired. It is known, that blood pressure regulation is mediated by changes in heart rate, vascular resistance, cardiac contractility, and a number of other factors. Given that numerous factors contribute to changing these quantities, it is difficult to devise a physiological model describing how they change in time. One way is to build a model that allows these controlled quantities to change and to compare dynamics between subject groups. To do so, it requires more knowledge of how these quantities change for healthy subjects. This study compares two methods predicting time-varying changes in cardiac contractility and vascular resistance during head-up tilt. Similar to the study by Williams et al. [51], the first method uses piecewise linear splines, while the second uses the ensemble transform Kalman filter (ETKF) [1], [11], [12], [33]. In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained with the ETKF. While the spline method is easier to set up, this study shows that the ETKF has a significantly shorter computational time. Moreover, while uncertainty of predictions can be augmented to spline predictions using DRAM, these are readily available with the ETKF. PMID:25769142

  5. Differences in motor imagery time when predicting task duration in alpine skiers and equestrian riders.

    PubMed

    Louis, Magali; Collet, Christian; Champely, Stéphane; Guillot, Aymeric

    2012-03-01

    Athletes' ability to use motor imagery (MI) to predict the speed at which they could perform a motor sequence has received little attention. In this study, 21 alpine skiers and 16 equestrian riders performed MI based on a prediction of actual performance time (a) after the course inspection, (b) before the start, and (c) after the actual performance. MI and physical times were similar in expert skiers during each imagery session, while novice skiers and novice and expert riders underestimated the actual course duration. These findings provide evidence that the temporal accuracy of an imagery task prediction depends on the performer's expertise level and characteristics of the motor skill. PMID:22428415

  6. A Learning Needs Assessment of Parish Nurses

    ERIC Educational Resources Information Center

    Tormoehlen, Lucy

    2009-01-01

    Parish Nursing is relatively new, having its original Scope and Standards from the American Nurses Association published in 1998. At the same time the Basic Preparation Curriculum for Parish Nursing, which had been developed through the International Parish Nurse Resource Center, was distributed to Educational Partners of the Center and used for…

  7. Gilligan: a voice for nursing?

    PubMed Central

    Harbison, J

    1992-01-01

    The current reform of nursing education is resulting in major changes in the curricula of colleges of nursing. For the first time, ethical and moral issues are being seen as an important theme underpinning the entire course. The moral theorist with whose work most nurse teachers are acquainted is Kohlberg. In this paper, it is suggested that his work, and the conventions of morality which he exemplifies, may not be the most appropriate from which to address the moral issues facing the nurse. The author suggests that the work of Carol Gilligan of Harvard university is of great significance, not only for nurses involved in the teaching of ethics, but for all nurses. Gilligan's emphasis on caring and relationships accords with the common experience of the nurse, and echoes the current revival of interest within nursing in examining, and valuing, the phenomenon of caring. PMID:1460649

  8. Healthy Work Revisited: Do Changes in Time Strain Predict Well-Being?

    PubMed Central

    Moen, Phyllis; Kelly, Erin L.; Lam, Jack

    2013-01-01

    Building on Karasek and Theorell (R. Karasek & T. Theorell, 1990, Healthy work: Stress, productivity, and the reconstruction of working life, New York, NY: Basic Books), we theorized and tested the relationship between time strain (work-time demands and control) and seven self-reported health outcomes. We drew on survey data from 550 employees fielded before and 6 months after the implementation of an organizational intervention, the Results Only Work Environment (ROWE) in a white-collar organization. Cross-sectional (Wave 1) models showed psychological time demands and time control measures were related to health outcomes in expected directions. The ROWE intervention did not predict changes in psychological time demands by Wave 2, but did predict increased time control (a sense of time adequacy and schedule control). Statistical models revealed increases in psychological time demands and time adequacy predicted changes in positive (energy, mastery, psychological well-being, self-assessed health) and negative (emotional exhaustion, somatic symptoms, psychological distress) outcomes in expected directions, net of job and home demands and covariates. This study demonstrates the value of including time strain in investigations of the health effects of job conditions. Results encourage longitudinal models of change in psychological time demands as well as time control, along with the development and testing of interventions aimed at reducing time strain in different populations of workers. PMID:23506547

  9. Real-time prediction of magnetospheric activity using the Boyle Index

    NASA Astrophysics Data System (ADS)

    Bala, Ramkumar; Reiff, P. H.; Landivar, J. E.

    2009-04-01

    We present a new algorithm with an improvement in the accuracy and lead time in short-term space weather predictions by coupling the Boyle Index, Φ = 10-4ν2 + 11.7Bsin3(?/2) kV, to artificial neural networks. The algorithm takes inputs from ACE and a handful of ground-based magnetometers to predict the next upcoming Kp in real time. The model yields a correlation coefficient of over 86% when predicting Kp with a lead time of 1 hour and over 85% for a 2 hour ahead prediction, significantly larger than the Kp persistence of 0.80. The Boyle Index, available in near-real time from http://space.rice.edu/ISTP/wind.html, has been in use for over 5 years now to predict geomagnetic activity. The logarithm of both 3-hour and 1-hour averages of the Boyle Index correlates well with the following Kp: Kp = 8.93 log10 < Boyle Index> -12.55. Using the Boyle Index alone, the algorithm yields a correlation coefficient of 85% when predicting Kp with a lead time of 1 hour and over 84% for a 3 hour ahead prediction, nearly as good as when using Kp in the history but without any possibility of "persistence contamination." Although the Boyle Index generally overestimates the polar cap potential for severe events, it does predict that severe activity will occur. Also, 1-hour value less than 100 kV is a good indicator that the magnetosphere will be quiet. However, some storm events with Kp > 6 occur when the Boyle Index is relatively low; the new algorithm is successful in predicting those events by capturing the influence of preconditioning.

  10. Predicting Regional Drought on Sub-Seasonal to Decadal Time Scales

    NASA Technical Reports Server (NTRS)

    Schubert, Siegfried; Wang, Hailan; Suarez, Max; Koster, Randal

    2011-01-01

    Drought occurs on a wide range of time scales, and within a variety of different types of regional climates. It is driven foremost by an extended period of reduced precipitation, but it is the impacts on such quantities as soil moisture, streamflow and crop yields that are often most important from a users perspective. While recognizing that different users have different needs for drought information, it is nevertheless important to understand that progress in predicting drought and satisfying such user needs, largely hinges on our ability to improve predictions of precipitation. This talk reviews our current understanding of the physical mechanisms that drive precipitation variations on subseasonal to decadal time scales, and the implications for predictability and prediction skill. Examples are given highlighting the phenomena and mechanisms controlling precipitation on monthly (e.g., stationary Rossby waves, soil moisture), seasonal (ENSO) and decadal time scales (PD and AMO).

  11. Predictability of nonstationary time series using wavelet and EMD based ARMA models

    NASA Astrophysics Data System (ADS)

    Karthikeyan, L.; Nagesh Kumar, D.

    2013-10-01

    Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology.

  12. Challenges in Real-Time Prediction of Infectious Disease: A Case Study of Dengue in Thailand.

    PubMed

    Reich, Nicholas G; Lauer, Stephen A; Sakrejda, Krzysztof; Iamsirithaworn, Sopon; Hinjoy, Soawapak; Suangtho, Paphanij; Suthachana, Suthanun; Clapham, Hannah E; Salje, Henrik; Cummings, Derek A T; Lessler, Justin

    2016-06-01

    Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidence at short and long time scales will improve public health response to outbreaks. However, scientists and public health officials face many obstacles in trying to create such real-time forecasts of infectious disease incidence. Dengue is a mosquito-borne virus that annually infects over 400 million people worldwide. We developed a real-time forecasting model for dengue hemorrhagic fever in the 77 provinces of Thailand. We created a practical computational infrastructure that generated multi-step predictions of dengue incidence in Thai provinces every two weeks throughout 2014. These predictions show mixed performance across provinces, out-performing seasonal baseline models in over half of provinces at a 1.5 month horizon. Additionally, to assess the degree to which delays in case reporting make long-range prediction a challenging task, we compared the performance of our real-time predictions with predictions made with fully reported data. This paper provides valuable lessons for the implementation of real-time predictions in the context of public health decision making. PMID:27304062

  13. Challenges in Real-Time Prediction of Infectious Disease: A Case Study of Dengue in Thailand

    PubMed Central

    Lauer, Stephen A.; Sakrejda, Krzysztof; Iamsirithaworn, Sopon; Hinjoy, Soawapak; Suangtho, Paphanij; Suthachana, Suthanun; Clapham, Hannah E.; Salje, Henrik; Cummings, Derek A. T.; Lessler, Justin

    2016-01-01

    Epidemics of communicable diseases place a huge burden on public health infrastructures across the world. Producing accurate and actionable forecasts of infectious disease incidence at short and long time scales will improve public health response to outbreaks. However, scientists and public health officials face many obstacles in trying to create such real-time forecasts of infectious disease incidence. Dengue is a mosquito-borne virus that annually infects over 400 million people worldwide. We developed a real-time forecasting model for dengue hemorrhagic fever in the 77 provinces of Thailand. We created a practical computational infrastructure that generated multi-step predictions of dengue incidence in Thai provinces every two weeks throughout 2014. These predictions show mixed performance across provinces, out-performing seasonal baseline models in over half of provinces at a 1.5 month horizon. Additionally, to assess the degree to which delays in case reporting make long-range prediction a challenging task, we compared the performance of our real-time predictions with predictions made with fully reported data. This paper provides valuable lessons for the implementation of real-time predictions in the context of public health decision making. PMID:27304062

  14. Off-Time Pubertal Timing Predicts Physiological Reactivity to Postpuberty Interpersonal Stress

    ERIC Educational Resources Information Center

    Smith, Anne Emilie; Powers, Sally I.

    2009-01-01

    We investigated associations between retrospectively assessed timing of pubertal development, interpersonal interactions, and hypothalamic-pituitary-adrenal axis reactivity to an interpersonal stress task in 110 young adult women. Participants provided salivary cortisol samples at points prior and subsequent to a video-taped conflict discussion…

  15. Predict or classify: The deceptive role of time-locking in brain signal classification

    PubMed Central

    Rusconi, Marco; Valleriani, Angelo

    2016-01-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal. PMID:27320688

  16. Predict or classify: The deceptive role of time-locking in brain signal classification.

    PubMed

    Rusconi, Marco; Valleriani, Angelo

    2016-01-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal. PMID:27320688

  17. Predict or classify: The deceptive role of time-locking in brain signal classification

    NASA Astrophysics Data System (ADS)

    Rusconi, Marco; Valleriani, Angelo

    2016-06-01

    Several experimental studies claim to be able to predict the outcome of simple decisions from brain signals measured before subjects are aware of their decision. Often, these studies use multivariate pattern recognition methods with the underlying assumption that the ability to classify the brain signal is equivalent to predict the decision itself. Here we show instead that it is possible to correctly classify a signal even if it does not contain any predictive information about the decision. We first define a simple stochastic model that mimics the random decision process between two equivalent alternatives, and generate a large number of independent trials that contain no choice-predictive information. The trials are first time-locked to the time point of the final event and then classified using standard machine-learning techniques. The resulting classification accuracy is above chance level long before the time point of time-locking. We then analyze the same trials using information theory. We demonstrate that the high classification accuracy is a consequence of time-locking and that its time behavior is simply related to the large relaxation time of the process. We conclude that when time-locking is a crucial step in the analysis of neural activity patterns, both the emergence and the timing of the classification accuracy are affected by structural properties of the network that generates the signal.

  18. Time Score: A New Feature for Link Prediction in Social Networks

    NASA Astrophysics Data System (ADS)

    Munasinghe, Lankeshwara; Ichise, Ryutaro

    Link prediction in social networks, such as friendship networks and coauthorship networks, has recently attracted a great deal of attention. There have been numerous attempts to address the problem of link prediction through diverse approaches. In the present paper, we focus on the temporal behavior of the link strength, particularly the relationship between the time stamps of interactions or links and the temporal behavior of link strength and how link strength affects future link evolution. Most previous studies have not sufficiently discussed either the impact of time stamps of the interactions or time stamps of the links on link evolution. The gap between the current time and the time stamps of the interactions or links is also important to link evolution. In the present paper, we introduce a new time-aware feature, referred to as time score, that captures the important aspects of time stamps of interactions and the temporality of the link strengths. We also analyze the effectiveness of time score with different parameter settings for different network data sets. The results of the analysis revealed that the time score was sensitive to different networks and different time measures. We applied time score to two social network data sets, namely, Facebook friendship network data set and a coauthorship network data set. The results revealed a significant improvement in predicting future links.

  19. Long-term polar motion prediction using normal time-frequency transform

    NASA Astrophysics Data System (ADS)

    Su, Xiaoqing; Liu, Lintao; Houtse, Hsu; Wang, Guocheng

    2014-02-01

    This paper presents normal time-frequency transform (NTFT) application in harmonic/quasi-harmonic signal prediction. Particularly, we use the normal wavelet transform (a special NTFT) to make long-term polar motion prediction. Instantaneous frequency, phase and amplitude of Chandler wobble, prograde and retrograde annual wobbles of Earth's polar motion are analyzed via the NTFT. Results show that the three main wobbles can be treated as quasi-harmonic processes. Current instantaneous harmonic information of the three wobbles can be acquired by the NTFT that has a kernel function constructed with a normal half-window function. Based on this information, we make the polar motion predictions with lead times of 1 year and 5 years. Results show that our prediction skills are very good with long lead time. An abnormality in the predictions occurs during the second half of 2005 and first half of 2006. Finally, we provide the future (starting from 2013) polar motion predictions with 1- and 5-year leads. These predictions will be used to verify the effectiveness of the method proposed in this paper.

  20. Real-Time Solar Wind Prediction Based on SDO/AIA Coronal Hole Data

    NASA Astrophysics Data System (ADS)

    Rotter, T.; Veronig, A. M.; Temmer, M.; Vršnak, B.

    2015-05-01

    We present an empirical model based on the visible area covered by coronal holes close to the central meridian with the aim to predict the solar wind speed at 1 AU with a lead time of up to four days in advance with a time resolution of one hour. Linear prediction functions are used to relate coronal hole areas to solar wind speed. The function parameters are automatically adapted by using the information from the previous three Carrington Rotations. Thus the algorithm automatically reacts to the changes of the solar wind speed during different phases of the solar cycle. The adaptive algorithm was applied to and tested on SDO/AIA-193 Å observations and ACE measurements during the years 2011 - 2013, covering 41 Carrington Rotations. The solar wind needs on average 4.02±0.5 days to reach Earth. The algorithm produces good predictions for the 156 solar wind high-speed streams peak amplitudes with correlation coefficients of cc≈0.60. For 80 % of the peaks, the predicted arrival matches the ACE in situ measurements within a time window of 0.5 days. The same algorithm, using linear predictions, was also applied to predict the magnetic field strength in wind streams originating from coronal hole areas, but it did not give reliable predictions ( cc≈0.15).

  1. Real-time seismic intensity prediction using frequency-dependent site amplification factors

    NASA Astrophysics Data System (ADS)

    Ogiso, Masashi; Aoki, Shigeki; Hoshiba, Mitsuyuki

    2016-05-01

    A promising approach for the next generation of earthquake early warning system is based on predicting ground motion directly from observed ground motion, without any information of hypocenter. In this study, we predicted seismic intensity at the target stations from the observed ground motion at adjacent stations, employing two different methods of correction for site amplification factors. The first method was frequency-dependent correction prediction, in which we used a digital causal filter to correct the site amplification for the observed waveform in the time domain. The second method was scalar correction, in which we used average differences in seismic intensity between two stations for the site amplification correction. Results from thousands of station pairs that covered almost all of Japan showed that seismic intensity prediction with frequency-dependent correction prediction was more accurate than prediction with scalar correction. Frequency-dependent correction for site amplification in the time domain may lead to more accurate prediction of ground motion in real time.

  2. Healing times and prediction of wound healing in neuropathic diabetic foot ulcers: a prospective study.

    PubMed

    Zimny, S; Pfohl, M

    2005-02-01

    Time line of wound healing and prediction of healing times in diabetic foot ulcers is an important issue. Usually, the percentage of wounds healed within a defined period is used for characterization of wound healing. R=sqrtA/pi (R, radius; A, planimetric wound area; pi, constant 3.14), and the wound radius reduction was 0.39 mm/week which was previously established. The initial average wound area was 96.9+/-13.1 mm2 (mean+/-SEM), and 3.61+/-1.6 mm 2 after ten weeks with an average healing time of 75.9 (95 %-CI 71-81) days. Using the equation mentioned above and the calculated weekly wound radius reduction, the predicted healing time in the test group was 86.9 (95 %-CI 73-101) days. The predicted and the observed healing times were significantly correlated with each other (r=0.55, p=0.0002). Providing standard care, the time needed for wound healing can reliably be predicted in neuropathic diabetic foot ulcers. This may be a useful tool in daily clinical practice to predict wound healing and recognize ulcers who do not respond adequately to the treatment. PMID:15772900

  3. LPTA: Location Predictive and Time Adaptive Data Gathering Scheme with Mobile Sink for Wireless Sensor Networks

    PubMed Central

    Rodrigues, Joel J. P. C.

    2014-01-01

    This paper exploits sink mobility to prolong the lifetime of sensor networks while maintaining the data transmission delay relatively low. A location predictive and time adaptive data gathering scheme is proposed. In this paper, we introduce a sink location prediction principle based on loose time synchronization and deduce the time-location formulas of the mobile sink. According to local clocks and the time-location formulas of the mobile sink, nodes in the network are able to calculate the current location of the mobile sink accurately and route data packets timely toward the mobile sink by multihop relay. Considering that data packets generating from different areas may be different greatly, an adaptive dwelling time adjustment method is also proposed to balance energy consumption among nodes in the network. Simulation results show that our data gathering scheme enables data routing with less data transmission time delay and balance energy consumption among nodes. PMID:25302327

  4. A maintenance time prediction method considering ergonomics through virtual reality simulation.

    PubMed

    Zhou, Dong; Zhou, Xin-Xin; Guo, Zi-Yue; Lv, Chuan

    2016-01-01

    Maintenance time is a critical quantitative index in maintainability prediction. An efficient maintenance time measurement methodology plays an important role in early stage of the maintainability design. While traditional way to measure the maintenance time ignores the differences between line production and maintenance action. This paper proposes a corrective MOD method considering several important ergonomics factors to predict the maintenance time. With the help of the DELMIA analysis tools, the influence coefficient of several factors are discussed to correct the MOD value and the designers can measure maintenance time by calculating the sum of the corrective MOD time of each maintenance therbligs. Finally a case study is introduced, by maintaining the virtual prototype of APU motor starter in DELMIA, designer obtains the actual maintenance time by the proposed method, and the result verifies the effectiveness and accuracy of the proposed method. PMID:27536522

  5. Decreasing the Hours That Anesthesiologists and Nurse Anesthetists Work Late by Making Decisions to Reduce the Hours of Over-Utilized Operating Room Time.

    PubMed

    Dexter, Franklin; Wachtel, Ruth E; Epstein, Richard H

    2016-03-01

    In this special article, we evaluate how to reduce the number of hours that anesthesiologists and nurse anesthetists work beyond the end of their scheduled shifts. We limit consideration to surgical suites where the hours of cases in each operating room (OR) average 8 hours or more per day. Let "allocated hours" refer to the hours into which cases are scheduled, calculated months in advance for each combination of service and day of the week. Over-Utilized time is the OR workload exceeding allocated time. Reducing Over-Utilized time is the key to reducing the hours that anesthesia providers work late. Certain decisions that reduce Over-Utilized time and reduce the hours that anesthesiologists and nurse anesthetists work late are made by the surgical committee or perioperative medical director months in advance. Such decisions include increasing the number of first case starts and planning staffing for turnovers and lunch breaks during the busiest times of the day. However, most decisions substantively influencing Over-Utilized OR time are made within 1 workday before the day of surgery and on the day of surgery, because only then are ORs sufficiently full that changes can be made to minimize Over-Utilized time. Decisions to reduce Over-Utilized time on the day of surgery include targeting ORs with expected Over-Utilized time and taking steps to reduce it, including making effective staff assignments and appropriately scheduling add-on cases. PMID:26891395

  6. Posterior Predictive Checks for Conditional Independence between Response Time and Accuracy

    ERIC Educational Resources Information Center

    Bolsinova, Maria; Tijmstra, Jesper

    2016-01-01

    Conditional independence (CI) between response time and response accuracy is a fundamental assumption of many joint models for time and accuracy used in educational measurement. In this study, posterior predictive checks (PPCs) are proposed for testing this assumption. These PPCs are based on three discrepancy measures reflecting different…

  7. Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

    PubMed

    Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

    2016-08-11

    Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times. PMID:27391254

  8. A novel trajectory prediction control for proximate time-optimal digital control DC—DC converters

    NASA Astrophysics Data System (ADS)

    Qing, Wang; Ning, Chen; Shen, Xu; Weifeng, Sun; Longxing, Shi

    2014-09-01

    The purpose of this paper is to present a novel trajectory prediction method for proximate time-optimal digital control DC—DC converters. The control method provides pre-estimations of the duty ratio in the next several switching cycles, so as to compensate the computational time delay of the control loop and increase the control loop bandwidth, thereby improving the response speed. The experiment results show that the fastest transient response time of the digital DC—DC with the proposed prediction is about 8 μs when the load current changes from 0.6 to 0.1 A.

  9. Penalised logistic regression and dynamic prediction for discrete-time recurrent event data.

    PubMed

    Elgmati, Entisar; Fiaccone, Rosemeire L; Henderson, R; Matthews, John N S

    2015-10-01

    We consider methods for the analysis of discrete-time recurrent event data, when interest is mainly in prediction. The Aalen additive model provides an extremely simple and effective method for the determination of covariate effects for this type of data, especially in the presence of time-varying effects and time varying covariates, including dynamic summaries of prior event history. The method is weakened for predictive purposes by the presence of negative estimates. The obvious alternative of a standard logistic regression analysis at each time point can have problems of stability when event frequency is low and maximum likelihood estimation is used. The Firth penalised likelihood approach is stable but in removing bias in regression coefficients it introduces bias into predicted event probabilities. We propose an alterative modified penalised likelihood, intermediate between Firth and no penalty, as a pragmatic compromise between stability and bias. Illustration on two data sets is provided. PMID:25626559

  10. [German hospital nurses' attitudes concerning evidence-based nursing practice].

    PubMed

    Köpke, Sascha; Koch, Frauke; Behncke, Anja; Balzer, Katrin

    2013-06-01

    The relevance of nurses' attitudes for establishing an evidence-based nursing practice (EBP) has been proven internationally. For German-speaking countries so far only few data are available. The present survey aims at assessing nurses' perceptions of relevant context factors for implementing an EBP. Therefore, 1384 nurses in 21 hospitals in Northern-Germany received a self-developed questionnaire based on established instruments in March and April 2012. 1023 (74 %) nurses responded. In principal, results show a positive attitude towards EBP. The majority of participants regards research as relevant for nursing practice. Support from superiors and colleagues is seen as important prerequisite. However, implementation remains a challenge. Nurses are not informed about recent research results. Original articles are hardly used. Only a minority is prepared to spend own money on congresses or to start academic nursing training in the near future. For the first time in German-speaking countries, the study provides meaningful data on nurses' attitudes towards EBP. Nurses confirm the value of research for their own practice. However, there is a lack of basic requirements to identify and implement relevant research findings as for example the use of recent scientific evidence. Nursing education in Germany should therefore focus more strongly on building competencies required for EBP, for example through properly designed academic nursing training. PMID:23732313

  11. Nurse Migration: A Canadian Case Study

    PubMed Central

    Little, Lisa

    2007-01-01

    Objective To synthesize information about nurse migration in and out of Canada and analyze its role as a policy lever to address the Canadian nursing shortage. Principal Findings Canada is both a source and a destination country for international nurse migration with an estimated net loss of nurses. The United States is the major beneficiary of Canadian nurse emigration resulting from the reduction of full-time jobs for nurses in Canada due to health system reforms. Canada faces a significant projected shortage of nurses that is too large to be ameliorated by ethical international nurse recruitment and immigration. Conclusions The current and projected shortage of nurses in Canada is a product of health care cost containment policies that failed to take into account long-term consequences for nurse workforce adequacy. An aging nurse workforce, exacerbated by layoffs of younger nurses with less seniority, and increasing demand for nurses contribute to a projection of nurse shortage that is too great to be solved ethically through international nurse recruitment. National policies to increase domestic nurse production and retention are recommended in addition to international collaboration among developed countries to move toward greater national nurse workforce self sufficiency. PMID:17489918

  12. A genetic programming approach for time-series analysis and prediction in space physics.

    NASA Astrophysics Data System (ADS)

    Jorgensen, A. M.; Brumby, S. P.; Henderson, M. G.

    2004-12-01

    A central theme in space weather prediction is the ability to predict time-series of relevant quantities, both empirically, and from physics-based models. Empirical models are often based on educated guesses, or intuition. The task of finding an empirical relationship relating quantities can be tedious and time-consuming, especially when a large number of parameters are involved. Genetic Programming (GP) provides a method for automating the guesswork, and can in some instances automatically find functional relationships between data streams. GP is an evolutionary computation technique which is an extension of the Genetic Algorithm framework used for function optimization. In GP an evolutionary algorithm combines elementary function operators in an attempt to build a function which is able to reproduce a training example from a set of input data. We will illustrate how a GP algorithm can be used in space physics by addressing two relevant topics: The prediction of relativistic electron fluxes, and prediction of Dst.

  13. Prediction of a time-to-event trait using genome wide SNP data

    PubMed Central

    2013-01-01

    Background A popular objective of many high-throughput genome projects is to discover various genomic markers associated with traits and develop statistical models to predict traits of future patients based on marker values. Results In this paper, we present a prediction method for time-to-event traits using genome-wide single-nucleotide polymorphisms (SNPs). We also propose a MaxTest associating between a time-to-event trait and a SNP accounting for its possible genetic models. The proposed MaxTest can help screen out nonprognostic SNPs and identify genetic models of prognostic SNPs. The performance of the proposed method is evaluated through simulations. Conclusions In conjunction with the MaxTest, the proposed method provides more parsimonious prediction models but includes more prognostic SNPs than some naive prediction methods. The proposed method is demonstrated with real GWAS data. PMID:23418752

  14. Time series predictions with neural nets: Application to airborne pollen forecasting

    NASA Astrophysics Data System (ADS)

    Arizmendi, C. M.; Sanchez, J. R.; Ramos, N. E.; Ramos, G. I.

    1993-09-01

    Pollen allergy is a common disease causing rhinoconjunctivitis (hay fever) in 5 10% of the population. Medical studies have indicated that pollen related diseases could be highly reduced if future pollen contents in the air could be predicted. In this work we have developed a new forecasting method that applies the ability of neural nets to predict the future behaviour of chaotic systems in order to make accurate predictions of the airborne pollen concentration. The method requires that the neural net be fed with non-zero values, which restricts the method predictions to the period following the start of pollen flight. The operational method outlined here constitutes a different point of view with respect to the more generally used forecasts of time series analysis, which require input of many meteorological parameters. Excellent forecasts were obtained training a neural net by using only the time series pollen concentration values.

  15. Neighbourhood selection for local modelling and prediction of hydrological time series

    NASA Astrophysics Data System (ADS)

    Jayawardena, A. W.; Li, W. K.; Xu, P.

    2002-02-01

    The prediction of a time series using the dynamical systems approach requires the knowledge of three parameters; the time delay, the embedding dimension and the number of nearest neighbours. In this paper, a new criterion, based on the generalized degrees of freedom, for the selection of the number of nearest neighbours needed for a better local model for time series prediction is presented. The validity of the proposed method is examined using time series, which are known to be chaotic under certain initial conditions (Lorenz map, Henon map and Logistic map), and real hydro meteorological time series (discharge data from Chao Phraya river in Thailand, Mekong river in Thailand and Laos, and sea surface temperature anomaly data). The predicted results are compared with observations, and with similar predictions obtained by using arbitrarily fixed numbers of neighbours. The results indicate superior predictive capability as measured by the mean square errors and coefficients of variation by the proposed approach when compared with the traditional approach of using a fixed number of neighbours.

  16. Accuracy of patient's turnover time prediction using RFID technology in an academic ambulatory surgery center.

    PubMed

    Marchand-Maillet, Florence; Debes, Claire; Garnier, Fanny; Dufeu, Nicolas; Sciard, Didier; Beaussier, Marc

    2015-02-01

    Patients flow in outpatient surgical unit is a major issue with regards to resource utilization, overall case load and patient satisfaction. An electronic Radio Frequency Identification Device (RFID) was used to document the overall time spent by the patients between their admission and discharge from the unit. The objective of this study was to evaluate how a RFID-based data collection system could provide an accurate prediction of the actual time for the patient to be discharged from the ambulatory surgical unit after surgery. This is an observational prospective evaluation carried out in an academic ambulatory surgery center (ASC). Data on length of stay at each step of the patient care, from admission to discharge, were recorded by a RFID device and analyzed according to the type of surgical procedure, the surgeon and the anesthetic technique. Based on these initial data (n = 1520), patients were scheduled in a sequential manner according to the expected duration of the previous case. The primary endpoint was the difference between actual and predicted time of discharge from the unit. A total of 414 consecutive patients were prospectively evaluated. One hundred seventy four patients (42%) were discharged at the predicted time ± 30 min. Only 24% were discharged behind predicted schedule. Using an automatic record of patient's length of stay would allow an accurate prediction of the discharge time according to the type of surgery, the surgeon and the anesthetic procedure. PMID:25637542

  17. Predictable component-based software design of real-time MPEG-4 video applications

    NASA Astrophysics Data System (ADS)

    Bondarev, Egor; Pastrnak, Milan; de With, Peter H. N.; Chaudron, Michel R. V.

    2005-07-01

    Component-based software development is very attractive, because it allows a clear decomposition of logical processing blocks into software blocks and it offers wide reuse. The strong real-time requirements of media processing systems should be validated as soon as possible to avoid costly system redesign. This can be achieved by prediction of timing and performance properties. In this paper, we propose a scenario simulation design approach featuring early performance prediction of a component-based software system. We validated this approach through a case study, for which we developed an advanced MPEG-4 coding application. The benefits of the approach are threefold: (a) high accuracy of the predicted performance data; (b) it delivers an efficient real-time software-hardware implementation, because the generic computational costs become known in advance, and (c) improved ease of use because of a high abstraction level of modelling. Experiments showed that the prediction accuracy of the system performance is about 90% or higher, while the prediction accuracy of the time-detailed processor usage (performance) does not get lower than 70%. However, the real-time performance requirements are sometimes not met, e.g. when other applications require intensive memory usage, thereby imposing delays on the retrieval from memory of the decoder data.

  18. Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

    PubMed

    Ak, Ronay; Fink, Olga; Zio, Enrico

    2016-08-01

    The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria. PMID:25910257

  19. Time and Space Efficient RNA-RNA Interaction Prediction via Sparse Folding

    NASA Astrophysics Data System (ADS)

    Salari, Raheleh; Möhl, Mathias; Will, Sebastian; Sahinalp, S. Cenk; Backofen, Rolf

    In the past years, a large set of new regulatory ncRNAs have been identified, but the number of experimentally verified targets is considerably low. Thus, computational target prediction methods are on high demand. Whereas all previous approaches for predicting a general joint structure have a complexity of O(n 6) running time and O(n 4) space, a more time and space efficient interaction prediction that is able to handle complex joint structures is necessary for genome-wide target prediction problems. In this paper we show how to reduce both the time and space complexity of the RNA-RNA interaction prediction problem as described by Alkan et al. [1] via dynamic programming sparsification - which allows to discard large portions of DP tables without loosing optimality. Applying sparsification techniques reduces the complexity of the original algorithm from O(n 6) time and O(n 4) space to O(n 4 ψ(n)) time and O(n 2 ψ(n) + n 3) space for some function ψ(n), which turns out to have small values for the range of n that we encounter in practice. Under the assumption that the polymer-zeta property holds for RNA-structures, we demonstrate that ψ(n) = O(n) on average, resulting in a linear time and space complexity improvement over the original algorithm. We evaluate our sparsified algorithm for RNA-RNA interaction prediction by total free energy minimization, based on the energy model of Chitsaz et al.[2], on a set of known interactions. Our results confirm the significant reduction of time and space requirements in practice.

  20. Real-time prediction learning for the simultaneous actuation of multiple prosthetic joints.

    PubMed

    Pilarski, Patrick M; Dick, Travis B; Sutton, Richard S

    2013-06-01

    Integrating learned predictions into a prosthetic control system promises to enhance multi-joint prosthesis use by amputees. In this article, we present a preliminary study of different cases where it may be beneficial to use a set of temporally extended predictions--learned and maintained in real time--within an engineered or learned prosthesis controller. Our study demonstrates the first successful combination of actor-critic reinforcement learning with real-time prediction learning. We evaluate this new approach to control learning during the myoelectric operation of a robot limb. Our results suggest that the integration of real-time prediction and control learning may speed control policy acquisition, allow unsupervised adaptation in myoelectric controllers, and facilitate synergies in highly actuated limbs. These experiments also show that temporally extended prediction learning enables anticipatory actuation, opening the way for coordinated motion in assistive robotic devices. Our work therefore provides initial evidence that realtime prediction learning is a practical way to support intuitive joint control in increasingly complex prosthetic systems. PMID:24187253

  1. Multivariable time series prediction for the icing process on overhead power transmission line.

    PubMed

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  2. Long-Term Prediction of the Arctic Ionospheric TEC Based on Time-Varying Periodograms

    PubMed Central

    Liu, Jingbin; Chen, Ruizhi; Wang, Zemin; An, Jiachun; Hyyppä, Juha

    2014-01-01

    Knowledge of the polar ionospheric total electron content (TEC) and its future variations is of scientific and engineering relevance. In this study, a new method is developed to predict Arctic mean TEC on the scale of a solar cycle using previous data covering 14 years. The Arctic TEC is derived from global positioning system measurements using the spherical cap harmonic analysis mapping method. The study indicates that the variability of the Arctic TEC results in highly time-varying periodograms, which are utilized for prediction in the proposed method. The TEC time series is divided into two components of periodic oscillations and the average TEC. The newly developed method of TEC prediction is based on an extrapolation method that requires no input of physical observations of the time interval of prediction, and it is performed in both temporally backward and forward directions by summing the extrapolation of the two components. The backward prediction indicates that the Arctic TEC variability includes a 9 years period for the study duration, in addition to the well-established periods. The long-term prediction has an uncertainty of 4.8–5.6 TECU for different period sets. PMID:25369066

  3. Predicting the timing and potential of the spring emergence of overwintered populations of Heliothis spp

    NASA Technical Reports Server (NTRS)

    Hartstack, A. W.; Witz, J. A.; Lopez, J. D. (Principal Investigator)

    1981-01-01

    The current state of knowledge dealing with the prediction of the overwintering population and spring emergence of Heliothis spp., a serious pest of numerous crops is surveyed. Current literature is reviewed in detail. Temperature and day length are the primary factors which program H. spp. larva for possible diapause. Although studies on the interaction of temperature and day length are reported, the complete diapause induction process is not identified sufficiently to allow accurate prediction of diapause timing. Mortality during diapause is reported as highly variable. The factors causing mortality are identified, but only a few are quantified. The spring emergence of overwintering H. spp. adults and mathematical models which predict the timing of emergence are reviewed. Timing predictions compare favorably to observed field data; however, prediction of actual numbers of emerging moths is not possible. The potential for use of spring emergence predictions in pest management applications, as an early warning of potential crop damage, are excellent. Research requirements to develop such an early warning system are discussed.

  4. Multivariable Time Series Prediction for the Icing Process on Overhead Power Transmission Line

    PubMed Central

    Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling

    2014-01-01

    The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters. PMID:25136653

  5. Investigation of Average Prediction Time for Different Meteorological Variables By Using Chaotic Approach

    NASA Astrophysics Data System (ADS)

    Özgür, Evren; Koçak, Kasım

    2016-04-01

    According to nonlinear dynamical system approach, it is possible that the time evolution of a system can be represented by its trajectories in phase space. This phase space is spanned by the state variables which are necessary to determine the time evolution of the system. Atmospheric processes can not be represented by linear approaches because of their dependency on numerous independent variables. Since a small changes in initial conditions lead to significant differences in prediction, long term prediction of meteorological variables is not possible. This situation can be explained by the term "sensitive dependence on initial conditions". In the study, it was tried to determine the average prediction time for different atmospheric variables by applying nonlinear approach. In order to apply the method, the first step is to reconstruct the phase space. Phase space has two parameters which are time delay and embedding dimension. Mutual Information Function (MIF) can be used to determine optimum time delay. MIF considers both linear and nonlinear inner-dependencies in a given time series. To define phase space, embedding dimension must be identified correctly. Embedding dimesion is the number of necessary state variables which describe the dynamics of a system. The algorithm to define embedding dimension is False Nearest Neighbors (FNN). After constructing the phase space by using time delay and embedding dimension, the maximum Lyapunov exponent was introduced. Lyapunov exponent is related to the exponential divergence or convergence of nearby orbits in the phase space. A dynamical system which has positive Lyapunov exponent is defined as chaotic system. Because meteorological variables can be controlled with large numbers of independent variables, time series of meteorological variables might be produced by a chaotic dynamical system. By using phase space and maximum Lyapunov exponent value, average prediction times of different parameters were calculated

  6. Engaging nursing home residents with dementia in activities: The effects of modeling, presentation order, time of day, and setting characteristics

    PubMed Central

    Cohen-Mansfield, Jiska; Thein, Khin; Dakheel-Ali, Maha; Marx, Marcia S.

    2011-01-01

    We examined the impact of setting characteristics and presentation effects on engagement with stimuli in a group of 193 nursing home residents with dementia (recruited from a total of seven nursing homes). Engagement was assessed through systematic observations using the Observational Measurement of Engagement (OME), and data pertaining to setting characteristics (background noise, light, and number of persons in proximity) were recorded via the environmental portion of the Agitation Behavior Mapping Inventory (ABMI; Cohen-Mansfield, Werner, & Marx, (1989). An observational study of agitation in agitated nursing home residents. International Psychogeriatrics, 1, 153–165). Results revealed that study participants were engaged more often with moderate levels of sound and in the presence of a small group of people (from four to nine people). As to the presentation effects, multiple presentations of the same stimulus were found to be appropriate for the severely impaired as well as the moderately cognitively impaired. Moreover, modeling of the appropriate behavior significantly increased engagement, with the severely cognitively impaired residents receiving the greatest benefit from modeling. These findings have direct implications for the way in which caregivers could structure the environment in the nursing home and how they could present stimuli to residents in order to optimize engagement in persons with dementia. PMID:20455123

  7. Time history prediction of direct-drive implosions on the Omega facility

    NASA Astrophysics Data System (ADS)

    Laffite, S.; Bourgade, J. L.; Caillaud, T.; Delettrez, J. A.; Frenje, J. A.; Girard, F.; Glebov, V. Yu.; Joshi, T.; Landoas, O.; Legay, G.; Lemaire, S.; Mancini, R. C.; Marshall, F. J.; Masse, L.; Masson-Laborde, P. E.; Michel, D. T.; Philippe, F.; Reverdin, C.; Seka, W.; Tassin, V.

    2016-01-01

    We present in this article direct-drive experiments that were carried out on the Omega facility [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)]. Two different pulse shapes were tested in order to vary the implosion stability of the same target whose parameters, dimensions and composition, remained the same. The direct-drive configuration on the Omega facility allows the accurate time-resolved measurement of the scattered light. We show that, provided the laser coupling is well controlled, the implosion time history, assessed by the "bang-time" and the shell trajectory measurements, can be predicted. This conclusion is independent on the pulse shape. In contrast, we show that the pulse shape affects the implosion stability, assessed by comparing the target performances between prediction and measurement. For the 1-ns square pulse, the measured neutron number is about 80% of the prediction. For the 2-step 2-ns pulse, we test here that this ratio falls to about 20%.

  8. Models to Predict Flowering Time in the Main Saffron Production Regions of Khorasan Province

    NASA Astrophysics Data System (ADS)

    Behdani, M. A.; Koocheki, A.; Nassiri, M.; Rezvani, P.

    The objective of this study was to develop a thermal model that can be used for prediction of saffron flowering time. For this purpose, existing data on saffron flower emergence time were collected in a wide range of temperature regimes over the saffron production regions of Khorasan province, Iran. Linear second-order polynomial and 5-parameter beta models were used and statistically compared for their ability in predicting saffron flowering time as a function of temperature. The results showed a significant delay in flowering date across the temperature gradient. While beta model had a better statistical performance but the simple linear model also showed a good predicting ability and therefore, can be used as a reliable model.

  9. Predicting conversion time of circuit design file by artificial neural networks

    NASA Astrophysics Data System (ADS)

    Jang, Sung-Hoon; Lee, Jee-Hyong; Ahn, Byoung-Sup; Ki, Won-Tai; Choi, Ji-Hyeon; Woo, Sang-Gyun; Cho, Han-Ku

    2008-03-01

    GDSII is a data format of the circuit design file for producing semiconductor. GDSII is also used as a transfer format for fabricating photo mask as well. As design rules are getting smaller and RET (Resolution Enhancement Technology) is getting more complicated, the time of converting GDSII to a mask data format has been increased, which influences the period of mask production. Photo mask shops all over the world are widely using computer clusters which are connected through a network, that is, called distributed computing method, to reduce the converting time. Commonly computing resource for conversion is assigned based on the input file size. However, the result of experiments showed that the input file size was improper to predict the computing resource usage. In this paper, we propose the methodology of artificial intelligence with considering the properties of GDSII file to handle circuit design files more efficiently. The conversion time will be optimized by controlling the hardware resource for data conversion as long as the conversion time is predictable through analyzing the design data. Neural networks are used to predict the conversion time for this research. In this paper, the application of neural networks for the time prediction will be discussed and experimental results will be shown with comparing to statistical model based approaches.

  10. Iterative prediction of chaotic time series using a recurrent neural network

    SciTech Connect

    Essawy, M.A.; Bodruzzaman, M.; Shamsi, A.; Noel, S.

    1996-12-31

    Chaotic systems are known for their unpredictability due to their sensitive dependence on initial conditions. When only time series measurements from such systems are available, neural network based models are preferred due to their simplicity, availability, and robustness. However, the type of neutral network used should be capable of modeling the highly non-linear behavior and the multi-attractor nature of such systems. In this paper the authors use a special type of recurrent neural network called the ``Dynamic System Imitator (DSI)``, that has been proven to be capable of modeling very complex dynamic behaviors. The DSI is a fully recurrent neural network that is specially designed to model a wide variety of dynamic systems. The prediction method presented in this paper is based upon predicting one step ahead in the time series, and using that predicted value to iteratively predict the following steps. This method was applied to chaotic time series generated from the logistic, Henon, and the cubic equations, in addition to experimental pressure drop time series measured from a Fluidized Bed Reactor (FBR), which is known to exhibit chaotic behavior. The time behavior and state space attractor of the actual and network synthetic chaotic time series were analyzed and compared. The correlation dimension and the Kolmogorov entropy for both the original and network synthetic data were computed. They were found to resemble each other, confirming the success of the DSI based chaotic system modeling.

  11. A two-stage approach for dynamic prediction of time-to-event distributions.

    PubMed

    Huang, Xuelin; Yan, Fangrong; Ning, Jing; Feng, Ziding; Choi, Sangbum; Cortes, Jorge

    2016-06-15

    Dynamic prediction uses longitudinal biomarkers for real-time prediction of an individual patient's prognosis. This is critical for patients with an incurable disease such as cancer. Biomarker trajectories are usually not linear, nor even monotone, and vary greatly across individuals. Therefore, it is difficult to fit them with parametric models. With this consideration, we propose an approach for dynamic prediction that does not need to model the biomarker trajectories. Instead, as a trade-off, we assume that the biomarker effects on the risk of disease recurrence are smooth functions over time. This approach turns out to be computationally easier. Simulation studies show that the proposed approach achieves stable estimation of biomarker effects over time, has good predictive performance, and is robust against model misspecification. It is a good compromise between two major approaches, namely, (i) joint modeling of longitudinal and survival data and (ii) landmark analysis. The proposed method is applied to patients with chronic myeloid leukemia. At any time following their treatment with tyrosine kinase inhibitors, longitudinally measured BCR-ABL gene expression levels are used to predict the risk of disease progression. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26748812

  12. Real-time prediction of unsteady aerodynamics: Application for aircraft control and manoeuvrability enhancement.

    PubMed

    Faller, W E; Schreck, S J

    1995-01-01

    The capability to control unsteady separated flow fields could dramatically enhance aircraft agility. To enable control, however, real-time prediction of these flow fields over a broad parameter range must be realized. The present work describes real-time predictions of three-dimensional unsteady separated flow fields and aerodynamic coefficients using neural networks. Unsteady surface-pressure readings were obtained from an airfoil pitched at a constant rate through the static stall angle. All data sets were comprised of 15 simultaneously acquired pressure records and one pitch angle record. Five such records and the associated pitch angle histories were used to train the neural network using a time-series algorithm. Post-training, the input to the network was the pitch angle (alpha), the angular velocity (dalpha/dt), and the initial 15 recorded surface pressures at time (t (0)). Subsequently, the time (t+Deltat) network predictions, for each of the surface pressures, were fed back as the input to the network throughout the pitch history. The results indicated that the neural network accurately predicted the unsteady separated flow fields as well as the aerodynamic coefficients to within 5% of the experimental data. Consistent results were obtained both for the training set as well as for generalization to both other constant pitch rates and to sinusoidal pitch motions. The results clearly indicated that the neural-network model could predict the unsteady surface-pressure distributions and aerodynamic coefficients based solely on angle of attack information. The capability for real-time prediction of both unsteady separated flow fields and aerodynamic coefficients across a wide range of parameters in turn provides a critical step towards the development of control systems targeted at exploiting unsteady aerodynamics for aircraft manoeuvrability enhancement. PMID:18263439

  13. Time-dependent damage in predictions of fatigue behaviour of normal and healing ligaments

    NASA Astrophysics Data System (ADS)

    Thornton, Gail M.; Bailey, Soraya J.; Schwab, Timothy D.

    2015-08-01

    Ligaments are dense fibrous tissues that connect bones across a joint and are exposed daily to creep and fatigue loading. Ligaments are tensile load-bearing tissues; therefore, fatigue loading will have a component of time-dependent damage from the non-zero mean stress and cycle-dependent damage from the oscillating stress. If time-dependent damage is not sufficient to completely predict the fatigue response, then cycle-dependent damage could be an important contributor. Using data from normal ligaments (current study and Thornton et al., Clin. Biomech. 22:932-940, 2007a) and healing ligaments (Thornton and Bailey, J. Biomech. Eng. 135:091004-1-091004-6, 2013), creep data was used to predict the fatigue response considering time-dependent damage. Relationships between creep lifetime and test stress or initial strain were modelled using exponential or power-law regression. In order to predict fatigue lifetimes, constant rates of damage were assumed and time-varying stresses were introduced into the expressions for time-dependent damage from creep. Then, the predictions of fatigue lifetime were compared with curvefits to the fatigue data where exponential or power-law regressions were used to determine the relationship between fatigue lifetime and test stress or initial strain. The fatigue prediction based on time-dependent damage alone greatly overestimated fatigue lifetime suggesting that time-dependent damage alone cannot account for all of the damage accumulated during fatigue and that cycle-dependent damage has an important role. At lower stress and strain, time-dependent damage was a greater relative contributor for normal ligaments than healing ligaments; however, cycle-dependent damage was a greater relative contributor with incremental increases in stress or strain for normal ligaments than healing ligaments.

  14. Oncology nurses' use of nondrug pain interventions in practice.

    PubMed

    Kwekkeboom, Kristine L; Bumpus, Molly; Wanta, Britt; Serlin, Ronald C

    2008-01-01

    Cancer pain management guidelines recommend nondrug interventions as adjuvants to analgesic medications. Although physicians typically are responsible for pharmacologic pain treatments, oncology staff nurses, who spend considerable time with patients, are largely responsible for identifying and implementing nondrug pain treatments. Oncology nurses' use of nondrug interventions, however, has not been well studied. The purpose of this study was to describe oncology nurses' use of four nondrug interventions (music, guided imagery, relaxation, distraction) and to identify factors that influence their use in practice. A national sample of 724 oncology staff nurses completed a mailed survey regarding use of the nondrug interventions in practice, beliefs about the interventions, and demographic characteristics. The percentages of nurses who reported administering the strategies in practice at least sometimes were 54% for music, 40% for guided imagery, 82% for relaxation, and 80% for distraction. Use of each nondrug intervention was predicted by a composite score on beliefs about effectiveness of the intervention (e.g., perceived benefit; P<0.025) and a composite score on beliefs about support for carrying out the intervention (e.g., time; P<0.025). In addition, use of guided imagery was predicted by a composite score on beliefs about characteristics of patients who may benefit from the intervention (e.g., cognitive ability; P<0.05). Some nurse demographic, professional preparation, and practice environment characteristics also predicted use of individual nondrug interventions. Efforts to improve application of nondrug interventions should focus on innovative educational strategies, problem solving to secure support, and development and testing of new delivery methods that require less time from busy staff nurses. PMID:17959348

  15. Evaluation of a nurse leadership development programme.

    PubMed

    West, Margaret; Smithgall, Lisa; Rosler, Greta; Winn, Erin

    2016-03-01

    The challenge for nursing leaders responsible for workforce planning is to predict the knowledge, skills and abilities required to lead future healthcare delivery systems effectively. Succession planning requires a constant, competitive pool of qualified nursing leader candidates, and retention of those interested in career growth. Formal nursing leadership education in the United States is available through graduate education and professional nursing organisation programmes, such as the Emerging Nurse Leader Institute of the American Organization of Nurse Executives. However, there is also a need for local development programmes tailored to the needs of individual organisations. Leaders at Geisinger Health System, one of the largest rural health systems in the US, identified the need for an internal professional development scheme for nurses. In 2013 the Nurses Emerging as Leaders programme was developed to prepare nurse leaders for effective leadership and successful role transition. This article describes the programme and an evaluation of its effectiveness. PMID:26927790

  16. Personal best times in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male triathletes

    PubMed Central

    Rüst, Christoph Alexander; Knechtle, Beat; Knechtle, Patrizia; Rosemann, Thomas; Lepers, Romuald

    2011-01-01

    Background The purpose of this study was to define predictor variables for recreational male Ironman triathletes, using age and basic measurements of anthropometry, training, and previous performance to establish an equation for the prediction of an Ironman race time for future recreational male Ironman triathletes. Methods Age and anthropometry, training, and previous experience variables were related to Ironman race time using bivariate and multivariate analysis. Results A total of 184 recreational male triathletes, of mean age 40.9 ± 8.4 years, height 1.80 ± 0.06 m, and weight 76.3 ± 8.4 kg completed the Ironman within 691 ± 83 minutes. They spent 13.9 ± 5.0 hours per week in training, covering 6.3 ± 3.1 km of swimming, 194.4 ± 76.6 km of cycling, and 45.0 ± 15.9 km of running. In total, 149 triathletes had completed at least one marathon, and 150 athletes had finished at least one Olympic distance triathlon. They had a personal best time of 130.4 ± 44.2 minutes in an Olympic distance triathlon and of 193.9 ± 31.9 minutes in marathon running. In total, 126 finishers had completed both an Olympic distance triathlon and a marathon. After multivariate analysis, both a personal best time in a marathon (P < 0.0001) and in an Olympic distance triathlon (P < 0.0001) were the best variables related to Ironman race time. Ironman race time (minutes) might be partially predicted by the following equation: (r2 = 0.65, standard error of estimate = 56.8) = 152.1 + 1.332 × (personal best time in a marathon, minutes) + 1.964 × (personal best time in an Olympic distance triathlon, minutes). Conclusion These results suggest that, in contrast with anthropometric and training characteristics, both the personal best time in an Olympic distance triathlon and in a marathon predict Ironman race time in recreational male Ironman triathletes. PMID:24198578

  17. MO-G-18C-05: Real-Time Prediction in Free-Breathing Perfusion MRI

    SciTech Connect

    Song, H; Liu, W; Ruan, D; Jung, S; Gach, M

    2014-06-15

    Purpose: The aim is to minimize frame-wise difference errors caused by respiratory motion and eliminate the need for breath-holds in magnetic resonance imaging (MRI) sequences with long acquisitions and repeat times (TRs). The technique is being applied to perfusion MRI using arterial spin labeling (ASL). Methods: Respiratory motion prediction (RMP) using navigator echoes was implemented in ASL. A least-square method was used to extract the respiratory motion information from the 1D navigator. A generalized artificial neutral network (ANN) with three layers was developed to simultaneously predict 10 time points forward in time and correct for respiratory motion during MRI acquisition. During the training phase, the parameters of the ANN were optimized to minimize the aggregated prediction error based on acquired navigator data. During realtime prediction, the trained ANN was applied to the most recent estimated displacement trajectory to determine in real-time the amount of spatial Results: The respiratory motion information extracted from the least-square method can accurately represent the navigator profiles, with a normalized chi-square value of 0.037±0.015 across the training phase. During the 60-second training phase, the ANN successfully learned the respiratory motion pattern from the navigator training data. During real-time prediction, the ANN received displacement estimates and predicted the motion in the continuum of a 1.0 s prediction window. The ANN prediction was able to provide corrections for different respiratory states (i.e., inhalation/exhalation) during real-time scanning with a mean absolute error of < 1.8 mm. Conclusion: A new technique enabling free-breathing acquisition during MRI is being developed. A generalized ANN development has demonstrated its efficacy in predicting a continuum of motion profile for volumetric imaging based on navigator inputs. Future work will enhance the robustness of ANN and verify its effectiveness with human

  18. Nursing Home Checklist

    MedlinePlus

    Nursing home checklist Name of nursing home: ____________________________________________________ Address: ________________________________________________________________ Phone number: __________________________________________________________ Date of visit: _____________________________________________________________ Basic information Yes No Notes Is the nursing home Medicare certified? Is the nursing ...

  19. The part-time student role: implications for the emotional experience of managing multiple roles amongst Hong Kong public health nurses.

    PubMed

    Shiu, A T

    1999-04-01

    The study investigated the contribution of the added part-time student role on the emotional experience of managing multiple roles of Hong Kong public health nurses (PHNs) who have children by comparing PHNs with and without the part-time student role. The research design employed the experience sampling method. Convenience sampling was used to recruit 20 subjects of which nine were undertaking part-time degree programmes. A watch was worn that gave a signal at six random times each day for 7 days to complete an experience sampling diary. PHNs on average responded to 34 signals (80%) and therefore completed 34 diaries, which collected data on work, college-work and family juggling and their effects on mood states. Results indicate that PHNs with an added part-time student role, although having fewer juggling occasions and higher emotional spouse support, had fewer family-related activities as well as a lower positive effect and a higher negative effect than PHNs without this role. These results suggest that taking up an added part-time student role creates additional role strain to nurses with children, and lend support to the argument that the stress of managing multiple roles is greatest and benefits least when work and non-work role responsibilities are both heavy. PMID:10578828

  20. Detecting determinism with improved sensitivity in time series: Rank-based nonlinear predictability score

    NASA Astrophysics Data System (ADS)

    Naro, Daniel; Rummel, Christian; Schindler, Kaspar; Andrzejak, Ralph G.

    2014-09-01

    The rank-based nonlinear predictability score was recently introduced as a test for determinism in point processes. We here adapt this measure to time series sampled from time-continuous flows. We use noisy Lorenz signals to compare this approach against a classical amplitude-based nonlinear prediction error. Both measures show an almost identical robustness against Gaussian white noise. In contrast, when the amplitude distribution of the noise has a narrower central peak and heavier tails than the normal distribution, the rank-based nonlinear predictability score outperforms the amplitude-based nonlinear prediction error. For this type of noise, the nonlinear predictability score has a higher sensitivity for deterministic structure in noisy signals. It also yields a higher statistical power in a surrogate test of the null hypothesis of linear stochastic correlated signals. We show the high relevance of this improved performance in an application to electroencephalographic (EEG) recordings from epilepsy patients. Here the nonlinear predictability score again appears of higher sensitivity to nonrandomness. Importantly, it yields an improved contrast between signals recorded from brain areas where the first ictal EEG signal changes were detected (focal EEG signals) versus signals recorded from brain areas that were not involved at seizure onset (nonfocal EEG signals).

  1. The timing and precision of action prediction in the aging brain.

    PubMed

    Diersch, Nadine; Jones, Alex L; Cross, Emily S

    2016-01-01

    Successful social interactions depend on the ability to anticipate other people's actions. Current conceptualizations of brain function propose that causes of sensory input are inferred through their integration with internal predictions generated in the observer's motor system during action observation. Less is known concerning how action prediction changes with age. Previously we showed that internal action representations are less specific in older compared with younger adults at behavioral and neural levels. Here, we characterize how neural activity varies while healthy older adults aged 56-71 years predict the time-course of an unfolding action as well as the relation to task performance. By using fMRI, brain activity was measured while participants observed partly occluded actions and judged the temporal coherence of the action continuation that was manipulated. We found that neural activity in frontoparietal and occipitotemporal regions increased the more an action continuation was shifted backwards in time. Action continuations that were shifted towards the future preferentially engaged early visual cortices. Increasing age was associated with neural activity that extended from posterior to anterior regions in frontal and superior temporal cortices. Lower sensitivity in action prediction resulted in activity increases in the caudate. These results imply that the neural implementation of predicting actions undergoes similar changes as the neural process of executing actions in older adults. The comparison between internal predictions and sensory input seems to become less precise with age leading to difficulties in anticipating observed actions accurately, possibly due to less specific internal action models. PMID:26503586

  2. Nursing Handbook.

    ERIC Educational Resources Information Center

    New York State Education Dept., Albany. Office of the Professions.

    A handbook with laws, rules, and regulations of the State Education Department of New York governing nursing practice is presented. It describes licensure requirements and includes complete application forms and instructions for obtaining license and first registration as a licensed practical nurse and professional registered nurse. Applicants are…

  3. Space Weather Prediction Error Bounding for Real-Time Ionospheric Threat Adaptation of GNSS Augmentation Systems

    NASA Astrophysics Data System (ADS)

    Lee, J.; Yoon, M.; Lee, J.

    2014-12-01

    Current Global Navigation Satellite Systems (GNSS) augmentation systems attempt to consider all possible ionospheric events in their correction computations of worst-case errors. This conservatism can be mitigated by subdividing anomalous conditions and using different values of ionospheric threat-model bounds for each class. A new concept of 'real-time ionospheric threat adaptation' that adjusts the threat model in real time instead of always using the same 'worst-case' model was introduced in my previous research. The concept utilizes predicted values of space weather indices for determining the corresponding threat model based on the pre-defined worst-case threat as a function of space weather indices. Since space weather prediction is not reliable due to prediction errors, prediction errors are needed to be bounded to the required level of integrity of the system being supported. The previous research performed prediction error bounding using disturbance, storm time (Dst) index. The distribution of Dst prediction error over the 15-year data was bounded by applying 'inflated-probability density function (pdf) Gaussian bounding'. Since the error distribution has thick and non-Gaussian tails, investigation on statistical distributions which properly describe heavy tails with less conservatism is required for the system performance. This paper suggests two potential approaches for improving space weather prediction error bounding. First, we suggest using different statistical models when fit the error distribution, such as the Laplacian distribution which has fat tails, and the folded Gaussian cumulative distribution function (cdf) distribution. Second approach is to bound the error distribution by segregating data based on the overall level of solar activity. Bounding errors using only solar minimum period data will have less uncertainty and it may allow the use of 'solar cycle prediction' provided by NASA when implementing to real-time threat adaptation. Lastly

  4. On determining the prediction limits of mathematical models for time series

    NASA Astrophysics Data System (ADS)

    Peluso, E.; Murari, A.; Gelfusa, M.; Lungaroni, M.; Talebzadeh, S.; Gaudio, P.; contributors, JET

    2016-07-01

    Prediction is one of the main objectives of scientific analysis and it refers to both modelling and forecasting. The determination of the limits of predictability is an important issue of both theoretical and practical relevance. In the case of modelling time series, reached a certain level in performance in either modelling or prediction, it is often important to assess whether all the information available in the data has been exploited or whether there are still margins for improvement of the tools being developed. In this paper, an information theoretic approach is proposed to address this issue and quantify the quality of the models and/or predictions. The excellent properties of the proposed indicator have been proved with the help of a systematic series of numerical tests and a concrete example of extreme relevance for nuclear fusion.

  5. Nurse Educators' Lived Experiences with Values Changes in Baccalaureate Nursing Education

    ERIC Educational Resources Information Center

    Wenda, Skip

    2012-01-01

    Values education in nursing can be a highly emotional topic. Values in nursing education can be linked to general societal values at any given point in time. Values are transmitted by nursing educators and institutions not only consciously in the nursing curriculum, but also unconsciously in the hidden curriculum. Each year many registered nurses…

  6. Clinical Nursing Instructor Perception of the Influence of Engagement in Bedside Nursing Practice on Clinical Teaching

    ERIC Educational Resources Information Center

    Berndt, Jodi L.

    2013-01-01

    Clinical experiences are an integral component of nursing education. Because the amount of time that a student spends in clinical experiences can be as many as twelve to sixteen hours per week, the clinical instructor plays a significant role in the nursing student's development of nursing knowledge. Many nurse educators attempt to balance dual…

  7. Evaluation of the Possibility of Using the Predicted Tropospheric Delays in Real Time Gnss Positioning

    NASA Astrophysics Data System (ADS)

    Kalita, J. Z.; Rzepecka, Z.; Krzan, G.

    2014-12-01

    Among many sources of errors that influence Global Navigation Satellite System (GNSS) observations, tropospheric delay is one of the most significant. It causes nonrefractive systematic bias in the observations on the level of several meters, depending on the atmospheric conditions. Tropospheric delay modelling plays an important role in precise positioning. The current models use numerical weather data for precise estimation of the parameters that are provided as a part of the Global Geodetic Observation System (GGOS). The purpose of this paper is to analyze the tropospheric data provided by the GGOS Atmosphere Service conducted by the Vienna University of Technology. There are predicted and final delay data available at the Service. In real time tasks, only the predicted values can be used. Thus it is very useful to study accuracy of the forecast delays. Comparison of data sets based on predicted and real weather models allows for conclusions concerning possibility of using the former for real time positioning applications. The predicted values of the dry tropospheric delay component, both zenith and mapped, can be safely used in real time PPP applications, but on the other hand, while using the wet predicted values, one should be very careful.

  8. The short-term prediction of universal time and length of day using atmospheric angular momentum

    NASA Technical Reports Server (NTRS)

    Freedman, A. P.; Steppe, J. A.; Dickey, J. O.; Eubanks, T. M.; Sung, L.-Y.

    1994-01-01

    The ability to predict short-term variations in the Earth's rotation has gained importance in recent years owing to more precise spacecraft tracking requirements. Universal time (UT1), that component of the Earth's orientation corresponding to the rotation angle, can be measured by number of high-precision space geodetic techniques. A Kalman filter developed at the Jet Propulsion Laboratory (JPL) optimally combines these different data sets and generates a smoothed times series and a set of predictions for UT1, as well as for additional Earth orientation components. These UT1 predictions utilize an empirically derived random walk stochastic model for the length of the day (LOD) and require frequent and up-to-date measurements of either UT1 or LOD to keep errors from quickly accumulating. Recent studies have shown that LOD variations are correlated with changes in the Earth's axial atmospheric angular momentum (AAM) over timescales of several years down to as little as 8 days. AAM estimates and forecasts out to 10 days are routinely available from meteorological analysis centers; these data can supplement geodetic measurements to improve the short-term prediction of LOD and have therefore been incorporated as independent data types in the JPL Kalman filter. We find that AAM and, to a lesser extent, AAM forecast data are extremely helpful in generating accurate near-real-time estimates of UT1 and LOD and in improving short-term predictions of these quantities out to about 10 days.

  9. Using a continuum model to predict closure time of gaps in intestinal epithelial cell layers

    PubMed Central

    Arciero, Julia C.; Mi, Qi; Branca, Maria; Hackam, David; Swigon, David

    2016-01-01

    A two-dimensional continuum model of collective cell migration is used to predict the closure of gaps in intestinal epithelial cell layers. The model assumes cell migration is governed by lamellipodia formation, cell-cell adhesion, and cell-substrate adhesion. Model predictions of the gap edge position and complete gap closure time are compared with experimental measures from cell layer scratch assays (also called scratch wound assays). The goal of the study is to combine experimental observations with mathematical descriptions of cell motion to identify effects of gap shape and area on closure time and to propose a method that uses a simple measure (e.g., area) to predict overall gap closure time early in the closure process. Gap closure time is shown to increase linearly with increasing gap area; however, gaps of equal areas but different aspect ratios differ greatly in healing time. Previous methods that calculate overall healing time according to the absolute or percent change in gap area assume that the gap area changes at a constant rate and typically underestimate gap closure time. In this study, data from scratch assays suggest that the rate of change of area is proportional to the first power or square root power of area. PMID:23421747

  10. Nursing in Nazi Germany.

    PubMed

    Steppe, H

    1992-12-01

    German nursing did indeed change during the Nazi period. There were external changes, in terms of the improved social status of nursing, the tightening and unification of professional nursing organizations, the laws affecting nursing, and the politicization of the profession. Articles written by nurses at the time and more recent interviews suggest that there were internal changes as well. It appears that at least a portion of German nurses accepted the National Socialism reinterpretation of professional nursing ethics and humanitarian principles in the assumption that through their obedience they were doing good. This historical research points to clear lessons for contemporary nurses. Nurses in Nazi Germany were under the illusion that they were remaining true to their professional ethics, unaffected by the social change around them. This apolitical professional consciousness made it possible for the profession to be subsumed as a part of the larger political system. I believe that we must be clear that nursing never takes place in a value-free, neutral context; it is always a socially significant force. This means that we cannot simply observe what is taking place around us but must take a stand and get involved, helping to shape sociopolitical developments. I also believe that we must deal with the history of our profession, especially its darkest hours, so that we may remain sensitive to any signs of inhumanity. We must call into question traditional principles, such as obedience, and replace them with professional competence, professionalism, and creative self-consciousness. And not least, we have a moral obligation to the millions of victims of National Socialism, even if it only means that, through historical research, we assure that they are not forgotten. By taking responsibility for this part of our history, we can become more sensitive for the future, with eyes and ears open for all social injustices. PMID:1455849

  11. Universities and nursing education.

    PubMed

    Hayward, J

    1982-07-01

    Trends reflected by Department of Health and Social Security statistics on the nursing workforce are examined and the ratios between grades discussed. Recruitment into nursing degree courses in the UK is considered in relation to overall recruitment into nursing. The somewhat ambiguous position of nursing degree courses in the UK leads into consideration of policy statements by the universities and the nursing profession. The importance of such policies is emphasized in the current financial climate, as are the potential contributions of university departments to professional debate, for example standards of care. Comparisons are drawn between the goals of courses involving full-time studentships as opposed to part-time apprenticeships and the present boundaries between these noted, especially in relation to the expanding roles of courses. On-going research into the preparation of nurse-tutors in the UK is mentioned, together with a preliminary analysis of the academic basis in the biological sciences possessed by learners and tutors. Out of this is derived a suggestion that the present-day shortage of nurse teachers could be helped by varying the existing patterns of recruitment, especially involving subject specialists in the biological, behavioural and social sciences. PMID:6922880

  12. [The nurse and patient's nudity].

    PubMed

    dos Santos, Regina Maria; Viana, Ivea Rayane M N; da Silva, Josefa Rita; Trezza, Maria Cristina Soares Figueiredo; Leite, Joséte Luzia

    2010-01-01

    This is a qualitative study about the relationship among nurses of a university hospital and their patients when they need to undress those patients to take care. The purpose was to analyze speech of seven nurses in this situation. The information was taken by transcribing the semi-structured interviews which were analyzed according Michel Foucault's thought. The results demonstrated that the relationship among nurses and patients at the time when nudity is needed to perform nursing care is full of power, to which the nurses don't feel always prepared. Also the nurses don't think that, acting as they act, they exert power over the patients. It is suggested to Nursing schools to perform seminars about the care with the naked body. PMID:21308217

  13. Time-specific ecological niche modeling predicts spatial dynamics of vector insects and human dengue cases.

    PubMed

    Peterson, A Townsend; Martínez-Campos, Carmen; Nakazawa, Yoshinori; Martínez-Meyer, Enrique

    2005-09-01

    Numerous human diseases-malaria, dengue, yellow fever and leishmaniasis, to name a few-are transmitted by insect vectors with brief life cycles and biting activity that varies in both space and time. Although the general geographic distributions of these epidemiologically important species are known, the spatiotemporal variation in their emergence and activity remains poorly understood. We used ecological niche modeling via a genetic algorithm to produce time-specific predictive models of monthly distributions of Aedes aegypti in Mexico in 1995. Significant predictions of monthly mosquito activity and distributions indicate that predicting spatiotemporal dynamics of disease vector species is feasible; significant coincidence with human cases of dengue indicate that these dynamics probably translate directly into transmission of dengue virus to humans. This approach provides new potential for optimizing use of resources for disease prevention and remediation via automated forecasting of disease transmission risk. PMID:15979656

  14. Ecological prediction with nonlinear multivariate time-frequency functional data models

    USGS Publications Warehouse

    Yang, Wen-Hsi; Wikle, Christopher K.; Holan, Scott H.; Wildhaber, Mark L.

    2013-01-01

    Time-frequency analysis has become a fundamental component of many scientific inquiries. Due to improvements in technology, the amount of high-frequency signals that are collected for ecological and other scientific processes is increasing at a dramatic rate. In order to facilitate the use of these data in ecological prediction, we introduce a class of nonlinear multivariate time-frequency functional models that can identify important features of each signal as well as the interaction of signals corresponding to the response variable of interest. Our methodology is of independent interest and utilizes stochastic search variable selection to improve model selection and performs model averaging to enhance prediction. We illustrate the effectiveness of our approach through simulation and by application to predicting spawning success of shovelnose sturgeon in the Lower Missouri River.

  15. A Simple PSA-Based Computational Approach Predicts the Timing of Cancer Relapse in Prostatectomized Patients.

    PubMed

    Stura, Ilaria; Gabriele, Domenico; Guiot, Caterina

    2016-09-01

    Recurrences of prostate cancer affect approximately one quarter of patients who have undergone radical prostatectomy. Reliable factors to predict time to relapse in specific individuals are lacking. Here, we present a mathematical model that evaluates a biologically sensible parameter (α) that can be estimated by the available follow-up data, in particular by the PSA series. This parameter is robust and highly predictive for the time to relapse, also after administration of adjuvant androgen deprivation therapies. We present a practical computational method based on the collection of only four postsurgical PSA values. This study offers a simple tool to predict prostate cancer relapse. Cancer Res; 76(17); 4941-7. ©2016 AACR. PMID:27587651

  16. AL and Dst Predictions with the Real-Time WINDMI Model

    NASA Astrophysics Data System (ADS)

    Mays, L.; Horton, W.; Spencer, E.; Weigel, R.; Vassiliadis, D.; Kozyra, J.

    2006-12-01

    First results are presented of the space weather forecasting capability of the real-time WINDMI model that has been operating since February 2006 as a physics based AL and Dst prediction tool. The well documented WINDMI model is a network of eight coupled ordinary differential equations which describe the transfer of power from the solar wind through the geomagnetic tail, the ionosphere, and ring current in the solar WIND driven Magnetosphere-Ionosphere system. WINDMI includes ring current energization physics from substrom injections and outputs a predicted westward auroral electojet index (AL) and equatorial geomagnetic disturbance storm time index (Dst). At the time of abstract submission (August 2006) real-time WINDMI has captured two storms with the first alarm being sent by email for a moderate -150 nT storm on 14-15 April 2006 and a second -100 nT storm on 19-20 August 2006. During the August 2006 storm period the WINDMI model was a more consistent Dst predictor than the Kyoto WDC Quicklook Dst data which has an incorrect offset of ~-100 nT. Real-time WINDMI uses real-time solar wind data from received from ACE every ten minutes to derive in less than one minute of computational time a predicted AL and Dst and magnetopause standoff distance. Real-time WINDMI predicts the AL index one hour earlier than the data is available from the Kyoto WDC Quicklook website and the Dst index two hours earlier. Every ten minutes real-time AL and Dst data and WINDMI predictions are shown on this website: http://orion.ph.utexas.edu/~windmi/realtime/. The 18 physical parameters of WINDMI are approximated analytically from planetary parameters and optimized within physically allowable ranges using the genetic algorithm. Real-time WINDMI parameters are optimized every hour based on 8 hours of past model/data comparison. In addition to the geomagnetic indices the model predicts the major energy components and power transfers in the solar wind-magnetosphere-ionosphere system. The

  17. Ebola outbreak in West Africa: real-time estimation and multiple-wave prediction.

    PubMed

    Wang, Xiang-Sheng; Zhong, Luoyi

    2015-10-01

    Based on the reported data until 18 March 2015 and numerical fitting via a simple formula of cumulative case number, we provide real-time estimation on basic reproduction number, inflection point, peak time and final outbreak size of ongoing Ebola outbreak in West Africa. From our simulation, we conclude that the first wave has passed its inflection point and predict that a second epidemic wave may appear in the near future. PMID:26280179

  18. Predicting Time to Recovery Among Depressed Adolescents Treated in Two Psychosocial Group Interventions

    ERIC Educational Resources Information Center

    Rohde, Paul; Seeley, John R.; Kaufman, Noah K.; Clarke, Gregory N.; Stice, Eric

    2006-01-01

    Aims were to identify the demographic, psychopathology, and psychosocial factors predicting time to major depressive disorder (MDD) recovery and moderators of treatment among 114 depressed adolescents recruited from a juvenile justice center and randomized to a cognitive behavioral treatment (CBT) condition or a life skills-tutoring control…

  19. Incorporating Retention Time to Refine Models Predicting Thermal Regimes of Stream Networks Across New England

    EPA Science Inventory

    Thermal regimes are a critical factor in models predicting effects of watershed management activities on fish habitat suitability. We have assembled a database of lotic temperature time series across New England (> 7000 station-year combinations) from state and Federal data s...

  20. Compensation for the distortion in satellite laser range predictions due to varying pulse travel times

    NASA Technical Reports Server (NTRS)

    Paunonen, Matti

    1993-01-01

    A method for compensating for the effect of the varying travel time of a transmitted laser pulse to a satellite is described. The 'observed minus predicted' range differences then appear to be linear, which makes data screening or use in range gating more effective.

  1. Development of VIS/NIR spectroscopic system for real-time prediction of fresh pork quality

    NASA Astrophysics Data System (ADS)

    Zhang, Haiyun; Peng, Yankun; Zhao, Songwei; Sasao, Akira

    2013-05-01

    Quality attributes of fresh meat will influence nutritional value and consumers' purchasing power. The aim of the research was to develop a prototype for real-time detection of quality in meat. It consisted of hardware system and software system. A VIS/NIR spectrograph in the range of 350 to 1100 nm was used to collect the spectral data. In order to acquire more potential information of the sample, optical fiber multiplexer was used. A conveyable and cylindrical device was designed and fabricated to hold optical fibers from multiplexer. High power halogen tungsten lamp was collected as the light source. The spectral data were obtained with the exposure time of 2.17ms from the surface of the sample by press down the trigger switch on the self-developed system. The system could automatically acquire, process, display and save the data. Moreover the quality could be predicted on-line. A total of 55 fresh pork samples were used to develop prediction model for real time detection. The spectral data were pretreated with standard normalized variant (SNV) and partial least squares regression (PLSR) was used to develop prediction model. The correlation coefficient and root mean square error of the validation set for water content and pH were 0.810, 0.653, and 0.803, 0.098 respectively. The research shows that the real-time non-destructive detection system based on VIS/NIR spectroscopy can be efficient to predict the quality of fresh meat.

  2. Predicting High Risk Adolescents' Substance Use over Time: The Role of Parental Monitoring

    ERIC Educational Resources Information Center

    Clark, Heddy Kovach; Shamblen, Stephen R.; Ringwalt, Chris L.; Hanley, Sean

    2012-01-01

    We examined whether parental monitoring at baseline predicted subsequent substance use in a high-risk youth population. Students in 14 alternative high schools in Washington State completed self-report surveys at three time points over the course of 2 years. Primary analyses included 1,423 students aged 14-20 who lived with at least one parent or…

  3. Temporal Characteristics of the Predictive Synchronous Firing Modeled by Spike-Timing-Dependent Plasticity

    ERIC Educational Resources Information Center

    Kitano, Katsunori; Fukai, Tomoki

    2004-01-01

    When a sensory cue was repeatedly followed by a behavioral event with fixed delays, pairs of premotor and primary motor neurons showed significant increases of coincident spikes at times a monkey was expecting the event. These results provided evidence that neuronal firing synchrony has predictive power. To elucidate the underlying mechanism, here…

  4. Prediction problem for target events based on the inter-event waiting time

    NASA Astrophysics Data System (ADS)

    Shapoval, A.

    2010-11-01

    In this paper we address the problem of forecasting the target events of a time series given the distribution ξ of time gaps between target events. Strong earthquakes and stock market crashes are the two types of such events that we are focusing on. In the series of earthquakes, as McCann et al. show [W.R. Mc Cann, S.P. Nishenko, L.R. Sykes, J. Krause, Seismic gaps and plate tectonics: seismic potential for major boundaries, Pure and Applied Geophysics 117 (1979) 1082-1147], there are well-defined gaps (called seismic gaps) between strong earthquakes. On the other hand, usually there are no regular gaps in the series of stock market crashes [M. Raberto, E. Scalas, F. Mainardi, Waiting-times and returns in high-frequency financial data: an empirical study, Physica A 314 (2002) 749-755]. For the case of seismic gaps, we analytically derive an upper bound of prediction efficiency given the coefficient of variation of the distribution ξ. For the case of stock market crashes, we develop an algorithm that predicts the next crash within a certain time interval after the previous one. We show that this algorithm outperforms random prediction. The efficiency of our algorithm sets up a lower bound of efficiency for effective prediction of stock market crashes.

  5. Development and Implementation of a Real-Time 30-Day Readmission Predictive Model

    PubMed Central

    Cronin, Patrick R.; Greenwald, Jeffrey L.; Crevensten, Gwen C.; Chueh, Henry C.; Zai, Adrian H.

    2014-01-01

    Hospitals are under great pressure to reduce readmissions of patients. Being able to reliably predict patients at increased risk for rehospitalization would allow for tailored interventions to be offered to them. This requires the creation of a functional predictive model specifically designed to support real-time clinical operations. A predictive model for readmissions within 30 days of discharge was developed using retrospective data from 45,924 MGH admissions between 2/1/2012 and 1/31/2013 only including factors that would be available by the day after admission. It was then validated prospectively in a real-time implementation for 3,074 MGH admissions between 10/1/2013 and 10/31/2013. The model developed retrospectively had an AUC of 0.705 with good calibration. The real-time implementation had an AUC of 0.671 although the model was overestimating readmission risk. A moderately discriminative real-time 30-day readmission predictive model can be developed and implemented in a large academic hospital. PMID:25954346

  6. Predicting the Risk of Attrition for Undergraduate Students with Time Based Modelling

    ERIC Educational Resources Information Center

    Chai, Kevin E. K.; Gibson, David

    2015-01-01

    Improving student retention is an important and challenging problem for universities. This paper reports on the development of a student attrition model for predicting which first year students are most at-risk of leaving at various points in time during their first semester of study. The objective of developing such a model is to assist…

  7. Prediction of energy requirements and drying times for surface drying fresh produce

    SciTech Connect

    Miller, W.M.

    1985-01-01

    For numerous fresh fruits and vegetables, drying of surface adhering water is required to facilitate materials handling and wax treatments. Using humidity ratio difference and air flow rates as manipulated variables, a computer program and a graphical approach were developed to predict required drying time. Modeling results were extended to investigate air recycling and the relationship of recycling on energy requirements.

  8. Factors that Predict Full-Time Community College Faculty Engagement in Online Instruction

    ERIC Educational Resources Information Center

    Akroyd, Duane; Patton, Bess; Bracken, Susan

    2013-01-01

    This study is a secondary quantitative analysis of the 2004 National Study of Postsecondary Faculty (NSOPF) data. It examines the ability of human capital, intrinsic rewards, extrinsic rewards, and gender/race demographics to predict full-time community college faculty teaching on-line courses. Findings indicate that those faculty with higher…

  9. Market Research: An Area in Need of Nurse Researchers.

    ERIC Educational Resources Information Center

    Froberg, Debra G.; And Others

    1986-01-01

    The application of marketing principles to nursing education and the need for research into the applicant market are discussed for nursing education programs, effective recruiting techniques, prediction of student success in nursing education, program quality, and the current and future nursing market. (Author/MSE)

  10. The impact of utilization review on nursing.

    PubMed

    Adams, R

    1987-09-01

    At first glance, nursing's role in UR appears to be of strategic significance to the profession. But there are several issues that nurse executives need to consider. First, since UR departments are seldom part of the nursing department, UR nurses are practicing outside the realm of nursing. What responsibility, if any, does the nursing department have to nurses practicing in the hospital, yet not in the nursing department? What can the nursing department do to help UR nurses maintain their identification with the profession and appreciate the strategic importance of their role, with its legal and financial ramifications? Second, UR is changing the established role of the primary care nurse. In your institution UR may already have taken the staff nurses' discharge planning function. It appears that several factors are contributing to this role change. Patient acuity has increased the time needed to administer physical care. The nursing shortage means more patients are assigned to each professional nurse and paraprofessionals are doing more patient care. There is less and less time left for the primary nurse to practice the professional attributes of nursing, primarily discharge planning. This function is shifting to the UR Department. Is discharge planning a function nurse executives wish to relinquish? Finally, we are entering another period of severe nurse shortages, where recruitment and retention of staff are paramount. Actively competing for our staff are the UR departments. Forty professional nurses work in three regional centers of the American Health Network, American Group Insurance Company (Dallas, Texas). In one hospital of 450 beds, nine nurses are employed by the UR department.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:3655930

  11. Compassion fatigue in nurses.

    PubMed

    Yoder, Elizabeth A

    2010-11-01

    Compassion fatigue, trigger situations, and coping strategies were investigated in hospital and home care nurses. The Professional Quality of Life Scale measured compassion fatigue, compassion satisfaction, and burnout. Narrative questions elicited trigger situations and coping strategies. Compassion fatigue scores were significantly different between nurses who worked 8- or 12-hour shifts. Fifteen percent of the participants had scores indicating risk of the compassion fatigue. There were significant differences in compassion satisfaction, depending on the unit worked and time as a nurse. The most common category of trigger situations was caring for the patient. Work-related and personal coping strategies were identified. PMID:21035028

  12. American Nurses Association Nursing World

    MedlinePlus

    ... Annual Conference Join » Care Coordination: Capitalizing on the Nursing Role in Population Health --Register Now ! For more ... ANA » My ANA » Shop » ANA Nursing Knowledge Center Nursing Insider News 9/15/16 Update Your MyANA ...

  13. Nutrition for Nurses: Nursing 245.

    ERIC Educational Resources Information Center

    Palermo, Karen R.

    A description is presented of "Nutrition for Nurses," a prerequisite course for students anticipating entrance into the junior level of a state university registered nursing program. Introductory material highlights the course focus (i.e., the basics of good nutrition; nutrition through the life cycle; nursing process in nutritional care; and…

  14. Predicting Marathon Time Using Exhaustive Graded Exercise Test in Marathon Runners.

    PubMed

    Till, Eloise S; Armstrong, Stuart A; Harris, Greg; Maloney, Stephen

    2016-02-01

    The study aimed to investigate the correlation between time on a treadmill test and exhaustion 2 weeks before a road marathon and the subsequent road marathon performance time (MPT). The study recruited 59 runners entered in the Melbourne 2012 marathon, Canberra 2013 marathon, and Gold Coast 2013 marathon. Forty runners completed both the graded exercise treadmill test to exhaustion and the 42.2 km marathon. Nineteen participants dropped out of the study due to illness, injury, or did not begin the treadmill test. A statistically significant correlation was found between treadmill time and MPT (adjusted R(2) = 0.447). Sex, weekly running duration (t = -1.58, p = 0.12), years of running (t = 1.10, p = 0.28), and age (t = 0.94, p = 0.36) did not statistically correlate with MPT. The relationship between the graded exercise test and MPT can be used to predict MPT using y = -3.85x + 351.57, where y is MPT and x is treadmill time. This is a simple, accessible, and cost-effective method to aid athletes in predicting their race time over 42.2 km. Prediction of marathon time in a simple and accessible manner was believed to be useful to the growing population of marathon runners around the world. PMID:26815178

  15. Accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients

    PubMed Central

    Martinez, Bruno Prata; Gomes, Isabela Barboza; de Oliveira, Carolina Santana; Ramos, Isis Resende; Rocha, Mônica Diniz Marques; Júnior, Luiz Alberto Forgiarini; Camelier, Fernanda Warken Rosa; Camelier, Aquiles Assunção

    2015-01-01

    OBJECTIVES: The ability of the Timed Up and Go test to predict sarcopenia has not been evaluated previously. The objective of this study was to evaluate the accuracy of the Timed Up and Go test for predicting sarcopenia in elderly hospitalized patients. METHODS: This cross-sectional study analyzed 68 elderly patients (≥60 years of age) in a private hospital in the city of Salvador-BA, Brazil, between the 1st and 5th day of hospitalization. The predictive variable was the Timed Up and Go test score, and the outcome of interest was the presence of sarcopenia (reduced muscle mass associated with a reduction in handgrip strength and/or weak physical performance in a 6-m gait-speed test). After the descriptive data analyses, the sensitivity, specificity and accuracy of a test using the predictive variable to predict the presence of sarcopenia were calculated. RESULTS: In total, 68 elderly individuals, with a mean age 70.4±7.7 years, were evaluated. The subjects had a Charlson Comorbidity Index score of 5.35±1.97. Most (64.7%) of the subjects had a clinical admission profile; the main reasons for hospitalization were cardiovascular disorders (22.1%), pneumonia (19.1%) and abdominal disorders (10.2%). The frequency of sarcopenia in the sample was 22.1%, and the mean length of time spent performing the Timed Up and Go test was 10.02±5.38 s. A time longer than or equal to a cutoff of 10.85 s on the Timed Up and Go test predicted sarcopenia with a sensitivity of 67% and a specificity of 88.7%. The accuracy of this cutoff for the Timed Up and Go test was good (0.80; IC=0.66-0.94; p=0.002). CONCLUSION: The Timed Up and Go test was shown to be a predictor of sarcopenia in elderly hospitalized patients. PMID:26039955

  16. Nursing and the nursing workplace in Queensland, 2001-2010: what the nurses think.

    PubMed

    Eley, Robert; Francis, Karen; Hegney, Desley

    2014-08-01

    The purpose of the study was to inform policy for reform in nursing. A survey mailed to members of the Queensland Nurses' Union four times between 2001 and 2010 elicited views on their employment and working conditions, professional development and career opportunities. Results across years and sectors of nursing consistently showed dissatisfaction in many aspects of employment, particularly by nurses working in aged care. However, views on staffing numbers, skill mix, workload, work stress, pay and staff morale all showed significant improvements over the decade. For example in 2001, 48.8% of nurses believed that their pay was poor, whereas in 2010, this had reduced to 35.2%. Furthermore, there was a significant rise throughout the decade in the opinion of the value of nursing as a good career. In light of the need to address nurse workforce shortages, the trends are encouraging; however, more improvements are required in order to support recruitment and retention. PMID:25157941

  17. Cognitive domains that predict time to diagnosis in prodromal Huntington disease

    PubMed Central

    Harrington, Deborah L.; Smith, Megan M.; Zhang, Ying; Carlozzi, Noelle E.; Paulsen, Jane S.

    2013-01-01

    Background Prodromal Huntington disease (prHD) is associated with a myriad of cognitive changes, but the domains that best predict time to clinical diagnosis have not been studied. This is a notable gap because some domains may be more sensitive to cognitive decline, which would inform clinical trials. Objectives The present study sought to characterize cognitive domains underlying a large test battery and for the first time, evaluate their ability to predict to time to diagnosis. Methods Participants included gene-negative and gene-positive prHD participants who were enrolled in the PREDICT-HD study. The CAG/Age Product (CAP) score was the measure of an individual’s genetic signature. A factor analysis of 18 tests was performed to identify sets of measures or latent factors that elucidated core constructs of tests. Factor scores were then fit to a survival model to evaluate their ability to predict time to diagnosis. Results Six factors were identified: 1) speed/inhibition, 2) verbal working memory, 3) motor planning/speed, 4) attention-information integration, 5) sensory-perceptual processing, and 6) verbal learning/memory. Factor scores were sensitive to a worsening of cognitive functioning in prHD, typically more so than performances on individual tests comprising the factors. Only the motor planning/speed and sensory-perceptual processing factors predicted time to diagnosis, after controlling for CAP scores and motor symptoms. Conclusions The results suggest that motor planning/speed and sensory-perceptual processing are important markers of disease prognosis. The findings also have implications for using composite indices of cognition in preventive HD trials where they may be more sensitive than individual tests. PMID:22451099

  18. Reliability Prediction of Ontology-Based Service Compositions Using Petri Net and Time Series Models

    PubMed Central

    Li, Jia; Xia, Yunni; Luo, Xin

    2014-01-01

    OWL-S, one of the most important Semantic Web service ontologies proposed to date, provides a core ontological framework and guidelines for describing the properties and capabilities of their web services in an unambiguous, computer interpretable form. Predicting the reliability of composite service processes specified in OWL-S allows service users to decide whether the process meets the quantitative quality requirement. In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. The framework includes the following steps: obtaining the historical response times series of individual service components; fitting these series with a autoregressive-moving-average-model (ARMA for short) and predicting the future firing rates of service components; mapping the OWL-S process into a NMSPN model; employing the predicted firing rates as the model input of NMSPN and calculating the normal completion probability as the reliability estimate. In the case study, a comparison between the static model and our approach based on experimental data is presented and it is shown that our approach achieves higher prediction accuracy. PMID:24688429

  19. Real-Time Safety Monitoring and Prediction for the National Airspace System

    NASA Technical Reports Server (NTRS)

    Roychoudhury, Indranil

    2016-01-01

    As new operational paradigms and additional aircraft are being introduced into the National Airspace System (NAS), maintaining safety in such a rapidly growing environment becomes more challenging. It is therefore desirable to have both an overview of the current safety of the airspace at different levels of granularity, as well an understanding of how the state of the safety will evolve into the future given the anticipated flight plans, weather forecasts, predicted health of assets in the airspace, and so on. To this end, we have developed a Real-Time Safety Monitoring (RTSM) that first, estimates the state of the NAS using the dynamic models. Then, given the state estimate and a probability distribution of future inputs to the NAS, the framework predicts the evolution of the NAS, i.e., the future state, and analyzes these future states to predict the occurrence of unsafe events. The entire probability distribution of airspace safety metrics is computed, not just point estimates, without significant assumptions regarding the distribution type and or parameters. We demonstrate our overall approach by predicting the occurrence of some unsafe events and show how these predictions evolve in time as flight operations progress.

  20. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks.

    PubMed

    Manikandan, Narayanan; Subha, Srinivasan

    2016-01-01

    Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used. PMID:26881271

  1. Software Design Challenges in Time Series Prediction Systems Using Parallel Implementation of Artificial Neural Networks

    PubMed Central

    Manikandan, Narayanan; Subha, Srinivasan

    2016-01-01

    Software development life cycle has been characterized by destructive disconnects between activities like planning, analysis, design, and programming. Particularly software developed with prediction based results is always a big challenge for designers. Time series data forecasting like currency exchange, stock prices, and weather report are some of the areas where an extensive research is going on for the last three decades. In the initial days, the problems with financial analysis and prediction were solved by statistical models and methods. For the last two decades, a large number of Artificial Neural Networks based learning models have been proposed to solve the problems of financial data and get accurate results in prediction of the future trends and prices. This paper addressed some architectural design related issues for performance improvement through vectorising the strengths of multivariate econometric time series models and Artificial Neural Networks. It provides an adaptive approach for predicting exchange rates and it can be called hybrid methodology for predicting exchange rates. This framework is tested for finding the accuracy and performance of parallel algorithms used. PMID:26881271

  2. Comparison of Prothrombin Time and Aspartate Aminotransferase in Predicting Hepatotoxicity After Acetaminophen Overdose.

    PubMed

    Levine, Michael; O'Connor, Ayrn D; Padilla-Jones, Angela; Gerkin, Richard D

    2016-03-01

    Despite decades of experience with acetaminophen (APAP) overdoses, it remains unclear whether elevated hepatic transaminases or coagulopathy develop first. Furthermore, comparison of the predictive value of these two variables in determining hepatic toxicity following APAP overdoses has been poorly elucidated. The primary objective of this study is to determine the test characteristics of the aspartate aminotransferase (AST) and the prothrombin time (PT) in patients with APAP toxicity. A retrospective chart review of APAP overdoses treated with IV N-acetylcysteine at a tertiary care referral center was performed. Of the 304 subjects included in the study, 246 with an initial AST less than 1000 were analyzed to determine predictors of hepatic injury, defined as an AST exceeding 1000 IU/L. The initial AST >50 was 79.5 % sensitive and 82.6 % specific for predicting hepatic injury. The corresponding negative and positive predictive values were 95.5 and 46.3 %, respectively. In contrast, an initial abnormal PT had a sensitivity of 82.1 % and a specificity of 63.6 %. The negative and positive predictive values for initial PT were 94.9 and 30.2 %, respectively. Although the two tests performed similarly for predicting a composite endpoint of death or liver transplant, neither was a useful predictor. Initial AST performed better than the initial PT for predicting hepatic injury in this series of patients with APAP overdose. PMID:26341088

  3. Application of Grey Model GM(1, 1) to Ultra Short-Term Predictions of Universal Time

    NASA Astrophysics Data System (ADS)

    Lei, Yu; Guo, Min; Zhao, Danning; Cai, Hongbing; Hu, Dandan

    2016-03-01

    A mathematical model known as one-order one-variable grey differential equation model GM(1, 1) has been herein employed successfully for the ultra short-term (<10days) predictions of universal time (UT1-UTC). The results of predictions are analyzed and compared with those obtained by other methods. It is shown that the accuracy of the predictions is comparable with that obtained by other prediction methods. The proposed method is able to yield an exact prediction even though only a few observations are provided. Hence it is very valuable in the case of a small size dataset since traditional methods, e.g., least-squares (LS) extrapolation, require longer data span to make a good forecast. In addition, these results can be obtained without making any assumption about an original dataset, and thus is of high reliability. Another advantage is that the developed method is easy to use. All these reveal a great potential of the GM(1, 1) model for UT1-UTC predictions.

  4. Insights from nurse leaders to optimize retaining late career nurses.

    PubMed

    Jeffs, Lianne; Nincic, Vera; Hayes, Laureen; Jerome, Danielle; Malecki, Victoria

    2014-09-01

    In an effort to stem the loss of Ontario's late career nurses, the Ontario Ministry of Health and Long-Term Care introduced the Late Career Nurse Initiative (LCNI) to implement a 0.20 full-time equivalent reduction of physically or psychologically demanding duties of nurses aged 55 or over and repurposing this time to enriching and less demanding activities. Fifty-nine nurse leaders were interviewed to explore their perceptions associated with implementing the LCNI in their respective organizations. Following a qualitative directed content analysis approach, three themes emerged: (1) having a strategic approach, (2) leveraging staff expertise and (3) securing organizational support. PMID:25676079

  5. Space can substitute for time in predicting climate-change effects on biodiversity

    NASA Astrophysics Data System (ADS)

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-06-01

    "Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption-that drivers of spatial gradients of species composition also drive temporal changes in diversity-rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  6. Space can substitute for time in predicting climate-change effects on biodiversity.

    PubMed

    Blois, Jessica L; Williams, John W; Fitzpatrick, Matthew C; Jackson, Stephen T; Ferrier, Simon

    2013-06-01

    "Space-for-time" substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption--that drivers of spatial gradients of species composition also drive temporal changes in diversity--rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as "time-for-time" predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change. PMID:23690569

  7. A Comparison of Center/TRACON Automation System and Airline Time of Arrival Predictions

    NASA Technical Reports Server (NTRS)

    Heere, Karen R.; Zelenka, Richard E.

    2000-01-01

    Benefits from information sharing between an air traffic service provider and a major air carrier are evaluated. Aircraft arrival time schedules generated by the NASA/FAA Center/TRACON Automation System (CTAS) were provided to the American Airlines System Operations Control Center in Fort Worth, Texas, during a field trial of a specialized CTAS display. A statistical analysis indicates that the CTAS schedules, based on aircraft trajectories predicted from real-time radar and weather data, are substantially more accurate than the traditional airline arrival time estimates, constructed from flight plans and en route crew updates. The improvement offered by CTAS is especially advantageous during periods of heavy traffic and substantial terminal area delay, allowing the airline to avoid large predictive errors with serious impact on the efficiency and profitability of flight operations.

  8. Predicting time to recovery among depressed adolescents treated in two psychosocial group interventions.

    PubMed

    Rohde, Paul; Seeley, John R; Kaufman, Noah K; Clarke, Gregory N; Stice, Eric

    2006-02-01

    Aims were to identify the demographic, psychopathology, and psychosocial factors predicting time to major depressive disorder (MDD) recovery and moderators of treatment among 114 depressed adolescents recruited from a juvenile justice center and randomized to a cognitive behavioral treatment (CBT) condition or a life skills-tutoring control condition. Nine variables predicted time to recovery over 1-year follow-up (e.g., earlier MDD onset, attention-deficit/hyperactivity disorder, functional impairment, hopelessness, negative thoughts, low family cohesion, coping skills); suicidal ideation and parental report of problem behaviors were the best predictors. CBT resulted in faster recovery time relative to control treatment, specifically among adolescents of White ethnicity, with recurrent MDD, and with good coping skills. Results suggest that psychopathology plays a more prominent role in maintaining adolescent depression than demographic or psychosocial factors. PMID:16551145

  9. A quantitative parameter-free prediction of simulated crystal nucleation times

    SciTech Connect

    Aga, Rachel S; Morris, James R; Hoyt, Jeffrey John; Mendelev, Mikhail I.

    2006-01-01

    We present direct comparisons between simulated crystal-nucleation times and theoretical predictions using a model of aluminum, and demonstrate that a quantitative prediction can be made. All relevant thermodynamic properties of the system are known, making the agreement of our simulation data with nucleation theories free of any adjustable parameters. The role of transient nucleation is included in the classical nucleation theory approach, and shown to be necessary to understand the observed nucleation times. The calculations provide an explanation on why nucleation is difficult to observe in simulations at moderate undercoolings. Even when the simulations are significantly larger than the critical nucleus, and when simulation times are sufficiently long, at moderate undercoolings the small concentration of critical nuclei makes the probability of the nucleation low in molecular dynamics simulations.

  10. Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurements

    NASA Technical Reports Server (NTRS)

    Weimer, Daniel R.

    2002-01-01

    Measurements of the interplanetary magnetic field (IMF) from the ACE (Advanced Composition Explorer), Wind, IMP-8 (Interplanetary Monitoring Platform), and Geotail spacecraft have revealed that the IMF variations are contained in phase planes that are tilted with respect to the propagation direction, resulting in continuously variable changes in propagation times between spacecraft, and therefore, to the Earth. Techniques for using 'minimum variance analysis' have been developed in order to be able to measure the phase front tilt angles, and better predict the actual propagation times from the L1 orbit to the Earth, using only the real-time IMF measurements from one spacecraft. The use of empirical models with the IMF measurements at L1 from ACE (or future satellites) for predicting 'space weather' effects has also been demonstrated.

  11. Actions Seen through Babies’ Eyes: A Dissociation between Looking Time and Predictive Gaze

    PubMed Central

    Daum, Moritz M.; Attig, Manja; Gunawan, Ronald; Prinz, Wolfgang; Gredebäck, Gustaf

    2012-01-01

    In this study, we explored the relation of two different measures used to investigate infants’ expectations about goal-directed actions. In previous studies, expectations about action outcomes have been either measured after the action has been terminated, that is post-hoc (e.g., via looking time) or during the action is being performed, that is online (e.g., via predictive gaze). Here, we directly compared both types of measures. Experiment 1 demonstrated a dissociation between looking time and predictive gaze for 9-month-olds. Looking time reflected identity-related expectations whereas predictive gaze did not. If at all, predictive gaze reflected location-related expectations. Experiment 2, including a wider age range, showed that the two measures remain dissociated over the first 3 years of life. It is only after the third birthday that the dissociation turns into an association, with both measures then reflecting identity-related expectations. We discuss these findings in terms of an early dissociation between two mechanisms for action expectation. We speculate that while post-hoc measures primarily tap ventral mechanisms for processing identity-related information (at least at a younger age), online measures primarily tap dorsal mechanisms for processing location-related information. PMID:23060838

  12. My Name is Nurse.

    PubMed

    2016-05-01

    : Editor's note: From its first issue in 1900 through to the present day, AJN has unparalleled archives detailing nurses' work and lives over more than a century. These articles not only chronicle nursing's growth as a profession within the context of the events of the day, but they also reveal prevailing societal attitudes about women, health care, and human rights. Today's nursing school curricula rarely include nursing's history, but it's a history worth knowing. To this end, From the AJN Archives offers articles selected to fit today's topics and times.This month's article, from the May 1993 issue, is a tongue-in-cheek editorial by former editor-in-chief Mary B. Mallison. In it, she introduces us to the "PerceptoPhone"-an imaginary device that allows the wearer to access the thoughts of nurses. PerceptoPhones are used to educate hospital trustees on nurses' essential but often invisible abilities: to identify early warning signs of complications; teach and encourage; and carefully assess, soothe, and heal-abilities that are "hard to quantify with usual accounting methods." More than 20 years later, we still look for better ways to teach the public about nursing. PMID:27123629

  13. Significance of time awake for predicting pilots' fatigue on short-haul flights: implications for flight duty time regulations.

    PubMed

    Vejvoda, Martin; Elmenhorst, Eva-Maria; Pennig, Sibylle; Plath, Gernot; Maass, Hartmut; Tritschler, Kristjof; Basner, Mathias; Aeschbach, Daniel

    2014-10-01

    European regulations restrict the duration of the maximum daily flight duty period for pilots as a function of the duty start time and the number of scheduled flights. However, late duty end times that may include long times awake are not specifically regulated. In this study, fatigue levels in pilots finishing their duty late at night (00:00-01:59 hour) were analysed and compared with pilots starting their duty early (05:00-06:59 hour). Fatigue levels of 40 commercial short-haul pilots were studied during a total of 188 flight duty periods, of which 87 started early and 22 finished late. Pilots used a small handheld computer to maintain a duty and sleep log, and to indicate fatigue levels immediately after each flight. Sleep logs were checked with actigraphy. Pilots on late-finishing flight duty periods were more fatigued at the end of their duty than pilots on early-starting flight duty periods, despite the fact that preceding sleep duration was longer by 1.1 h. Linear mixed-model regression identified time awake as a preeminent factor predicting fatigue. Workload had a minor effect. Pilots on late-finishing flight duty periods were awake longer by an average of 5.5 h (6.6 versus 1.1 h) before commencing their duty than pilots who started early in the morning. Late-finishing flights were associated with long times awake at a time when the circadian system stops promoting alertness, and an increased, previously underestimated fatigue risk. Based on these findings, flight duty limitations should consider not only duty start time, but also the time of the final landing. PMID:25040665

  14. Longitudinal study of stress, self-care, and professional identity among nursing students.

    PubMed

    Hensel, Desiree; Laux, Marcia

    2014-01-01

    This longitudinal study describes the factors associated with the acquisition of a professional identity over the course of prelicensure education among 45 baccalaureate nursing students. At every time point, personal spiritual growth practices and the students' perceptions of their caring abilities predicted sense of fit with the profession. Even as there is a growing emphasis of quality and safety education, caring and spirituality remain central to nurses' professional identities on entry to practice. PMID:24867076

  15. Predicting Ambulance Time of Arrival to the Emergency Department Using Global Positioning System and Google Maps

    PubMed Central

    Fleischman, Ross J.; Lundquist, Mark; Jui, Jonathan; Newgard, Craig D.; Warden, Craig

    2014-01-01

    Objective To derive and validate a model that accurately predicts ambulance arrival time that could be implemented as a Google Maps web application. Methods This was a retrospective study of all scene transports in Multnomah County, Oregon, from January 1 through December 31, 2008. Scene and destination hospital addresses were converted to coordinates. ArcGIS Network Analyst was used to estimate transport times based on street network speed limits. We then created a linear regression model to improve the accuracy of these street network estimates using weather, patient characteristics, use of lights and sirens, daylight, and rush-hour intervals. The model was derived from a 50% sample and validated on the remainder. Significance of the covariates was determined by p < 0.05 for a t-test of the model coefficients. Accuracy was quantified by the proportion of estimates that were within 5 minutes of the actual transport times recorded by computer-aided dispatch. We then built a Google Maps-based web application to demonstrate application in real-world EMS operations. Results There were 48,308 included transports. Street network estimates of transport time were accurate within 5 minutes of actual transport time less than 16% of the time. Actual transport times were longer during daylight and rush-hour intervals and shorter with use of lights and sirens. Age under 18 years, gender, wet weather, and trauma system entry were not significant predictors of transport time. Our model predicted arrival time within 5 minutes 73% of the time. For lights and sirens transports, accuracy was within 5 minutes 77% of the time. Accuracy was identical in the validation dataset. Lights and sirens saved an average of 3.1 minutes for transports under 8.8 minutes, and 5.3 minutes for longer transports. Conclusions An estimate of transport time based only on a street network significantly underestimated transport times. A simple model incorporating few variables can predict ambulance time of

  16. Real time prediction of marine vessel motions using Kalman filtering techniques

    NASA Technical Reports Server (NTRS)

    Triantafyllou, M. S.; Bodson, M.

    1982-01-01

    The present investigation is concerned with the prediction of the future behavior of a vessel within some confidence bounds at a specific instant of time, taking into account an interval of a few seconds. The ability to predict accurately the motions of a vessel can reduce significantly the probability of failure of operations in rough seas. The investigation was started as part of an effort to ensure safe landing of aircraft on relatively small vessels. However, the basic principles involved in the study are the same for any offshore operation, such as carbo transfer in the open sea, structure installation, and floating crane operation. The Kalman filter is a powerful tool for achieving the goals of the prediction procedure. Attention is given to a linear optimal predictor, the equations of motion of the vessel, the wave spectrum, rational approximation, the use of Kalman filter and predictor in an application for a ship, and the motions of a semisubmersible.

  17. Machine learning based prediction for peptide drift times in ion mobility spectrometry

    PubMed Central

    Shah, Anuj R.; Agarwal, Khushbu; Baker, Erin S.; Singhal, Mudita; Mayampurath, Anoop M.; Ibrahim, Yehia M.; Kangas, Lars J.; Monroe, Matthew E.; Zhao, Rui; Belov, Mikhail E.; Anderson, Gordon A.; Smith, Richard D.

    2010-01-01

    Motivation: Ion mobility spectrometry (IMS) has gained significant traction over the past few years for rapid, high-resolution separations of analytes based upon gas-phase ion structure, with significant potential impacts in the field of proteomic analysis. IMS coupled with mass spectrometry (MS) affords multiple improvements over traditional proteomics techniques, such as in the elucidation of secondary structure information, identification of post-translational modifications, as well as higher identification rates with reduced experiment times. The high throughput nature of this technique benefits from accurate calculation of cross sections, mobilities and associated drift times of peptides, thereby enhancing downstream data analysis. Here, we present a model that uses physicochemical properties of peptides to accurately predict a peptide's drift time directly from its amino acid sequence. This model is used in conjunction with two mathematical techniques, a partial least squares regression and a support vector regression setting. Results: When tested on an experimentally created high confidence database of 8675 peptide sequences with measured drift times, both techniques statistically significantly outperform the intrinsic size parameters-based calculations, the currently held practice in the field, on all charge states (+2, +3 and +4). Availability: The software executable, imPredict, is available for download from http:/omics.pnl.gov/software/imPredict.php Contact: rds@pnl.gov Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20495001

  18. Incorporating system latency associated with real-time target tracking radiotherapy in the dose prediction step

    NASA Astrophysics Data System (ADS)

    Roland, Teboh; Mavroidis, Panayiotis; Shi, Chengyu; Papanikolaou, Nikos

    2010-05-01

    System latency introduces geometric errors in the course of real-time target tracking radiotherapy. This effect can be minimized, for example by the use of predictive filters, but cannot be completely avoided. In this work, we present a convolution technique that can incorporate the effect as part of the treatment planning process. The method can be applied independently or in conjunction with the predictive filters to compensate for residual latency effects. The implementation was performed on TrackBeam (Initia Ltd, Israel), a prototype real-time target tracking system assembled and evaluated at our Cancer Institute. For the experimental system settings examined, a Gaussian distribution attributable to the TrackBeam latency was derived with σ = 3.7 mm. The TrackBeam latency, expressed as an average response time, was deduced to be 172 ms. Phantom investigations were further performed to verify the convolution technique. In addition, patient studies involving 4DCT volumes of previously treated lung cancer patients were performed to incorporate the latency effect in the dose prediction step. This also enabled us to effectively quantify the dosimetric and radiobiological impact of the TrackBeam and other higher latency effects on the clinical outcome of a real-time target tracking delivery.

  19. Real-time emissions from construction equipment compared with model predictions.

    PubMed

    Heidari, Bardia; Marr, Linsey C

    2015-02-01

    The construction industry is a large source of greenhouse gases and other air pollutants. Measuring and monitoring real-time emissions will provide practitioners with information to assess environmental impacts and improve the sustainability of construction. We employed a portable emission measurement system (PEMS) for real-time measurement of carbon dioxide (CO), nitrogen oxides (NOx), hydrocarbon, and carbon monoxide (CO) emissions from construction equipment to derive emission rates (mass of pollutant emitted per unit time) and emission factors (mass of pollutant emitted per unit volume of fuel consumed) under real-world operating conditions. Measurements were compared with emissions predicted by methodologies used in three models: NONROAD2008, OFFROAD2011, and a modal statistical model. Measured emission rates agreed with model predictions for some pieces of equipment but were up to 100 times lower for others. Much of the difference was driven by lower fuel consumption rates than predicted. Emission factors during idling and hauling were significantly different from each other and from those of other moving activities, such as digging and dumping. It appears that operating conditions introduce considerable variability in emission factors. Results of this research will aid researchers and practitioners in improving current emission estimation techniques, frameworks, and databases. PMID:25947047

  20. Predicting the start week of respiratory syncytial virus outbreaks using real time weather variables

    PubMed Central

    2010-01-01

    Background Respiratory Syncytial Virus (RSV), a major cause of bronchiolitis, has a large impact on the census of pediatric hospitals during outbreak seasons. Reliable prediction of the week these outbreaks will start, based on readily available data, could help pediatric hospitals better prepare for large outbreaks. Methods Naïve Bayes (NB) classifier models were constructed using weather data from 1985-2008 considering only variables that are available in real time and that could be used to forecast the week in which an RSV outbreak will occur in Salt Lake County, Utah. Outbreak start dates were determined by a panel of experts using 32,509 records with ICD-9 coded RSV and bronchiolitis diagnoses from Intermountain Healthcare hospitals and clinics for the RSV seasons from 1985 to 2008. Results NB models predicted RSV outbreaks up to 3 weeks in advance with an estimated sensitivity of up to 67% and estimated specificities as high as 94% to 100%. Temperature and wind speed were the best overall predictors, but other weather variables also showed relevance depending on how far in advance the predictions were made. The weather conditions predictive of an RSV outbreak in our study were similar to those that lead to temperature inversions in the Salt Lake Valley. Conclusions We demonstrate that Naïve Bayes (NB) classifier models based on weather data available in real time have the potential to be used as effective predictive models. These models may be able to predict the week that an RSV outbreak will occur with clinical relevance. Their clinical usefulness will be field tested during the next five years. PMID:21044325

  1. Prediction of color changes in acetaminophen solution using the time-temperature superposition principle.

    PubMed

    Mochizuki, Koji; Takayama, Kozo

    2016-07-01

    A prediction method for color changes based on the time-temperature superposition principle (TTSP) was developed for acetaminophen solution. Color changes of acetaminophen solution are caused by the degradation of acetaminophen, such as hydrolysis and oxidation. In principle, the TTSP can be applied to only thermal aging. Therefore, the impact of oxidation on the color changes of acetaminophen solution was verified. The results of our experiment suggested that the oxidation products enhanced the color changes in acetaminophen solution. Next, the color changes of acetaminophen solution samples of the same head space volume after accelerated aging at various temperatures were investigated using the Commission Internationale de l'Eclairage (CIE) LAB color space (a*, b*, L* and ΔE*ab), following which the TTSP was adopted to kinetic analysis of the color changes. The apparent activation energies using the time-temperature shift factor of a*, b*, L* and ΔE*ab were calculated as 72.4, 69.2, 72.3 and 70.9 (kJ/mol), respectively, which are similar to the values for acetaminophen hydrolysis reported in the literature. The predicted values of a*, b*, L* and ΔE*ab at 40 °C were obtained by calculation using Arrhenius plots. A comparison between the experimental and predicted values for each color parameter revealed sufficiently high R(2) values (>0.98), suggesting the high reliability of the prediction. The kinetic analysis using TTSP was successfully applied to predicting the color changes under the controlled oxygen amount at any temperature and for any length of time. PMID:26559666

  2. Single-trial prediction of reaction time variability from MEG brain activity.

    PubMed

    Ohata, Ryu; Ogawa, Kenji; Imamizu, Hiroshi

    2016-01-01

    Neural activity prior to movement onset contains essential information for predictive assistance for humans using brain-machine-interfaces (BMIs). Even though previous studies successfully predicted different goals for upcoming movements, it is unclear whether non-invasive recording signals contain the information to predict trial-by-trial behavioral variability under the same movement. In this paper, we examined the predictability of subsequent short or long reaction times (RTs) from magnetoencephalography (MEG) signals in a delayed-reach task. The difference in RTs was classified significantly above chance from 550 ms before the go-signal onset using the cortical currents in the premotor cortex. Significantly above-chance classification was performed in the lateral prefrontal and the right inferior parietal cortices at the late stage of the delay period. Thus, inter-trial variability in RTs is predictable information. Our study provides a proof-of-concept of the future development of non-invasive BMIs to prevent delayed movements. PMID:27250872

  3. Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex

    PubMed Central

    Wittmann, Marco K.; Kolling, Nils; Akaishi, Rei; Chau, Bolton K. H.; Brown, Joshua W.; Nelissen, Natalie; Rushworth, Matthew F. S.

    2016-01-01

    In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. PMID:27477632

  4. Bayesian prediction of earthquake network based on space-time influence domain

    NASA Astrophysics Data System (ADS)

    Zhang, Ya; Zhao, Hai; He, Xuan; Pei, Fan-Dong; Li, Guang-Guang

    2016-03-01

    Bayesian networks (BNs) are used to analyze the conditional dependencies among different events, which are expressed by conditional probability. Scientists have already investigated the seismic activities by using BNs. Recently, earthquake network is used as a novel methodology to analyze the relationships among the earthquake events. In this paper, we propose a way to predict earthquake from a new perspective. The BN is constructed after processing, which is derived from the earthquake network based on space-time influence domain. And then, the BN parameters are learnt by using the cases which are designed from the seismic data in the period between 00:00:00 on January 1, 1992 and 00:00:00 on January 1, 2012. At last, predictions are done for the data in the period between 00:00:00 on January 1, 2012 and 00:00:00 on January 1, 2015 combining the BN with the parameters. The results show that the success rate of the prediction including delayed prediction is about 65%. It is also discovered that the predictions for some nodes have high rate of accuracy under investigation.

  5. A Long-Term Prediction Model of Beijing Haze Episodes Using Time Series Analysis.

    PubMed

    Yang, Xiaoping; Zhang, Zhongxia; Zhang, Zhongqiu; Sun, Liren; Xu, Cui; Yu, Li

    2016-01-01

    The rapid industrial development has led to the intermittent outbreak of pm2.5 or haze in developing countries, which has brought about great environmental issues, especially in big cities such as Beijing and New Delhi. We investigated the factors and mechanisms of haze change and present a long-term prediction model of Beijing haze episodes using time series analysis. We construct a dynamic structural measurement model of daily haze increment and reduce the model to a vector autoregressive model. Typical case studies on 886 continuous days indicate that our model performs very well on next day's Air Quality Index (AQI) prediction, and in severely polluted cases (AQI ≥ 300) the accuracy rate of AQI prediction even reaches up to 87.8%. The experiment of one-week prediction shows that our model has excellent sensitivity when a sudden haze burst or dissipation happens, which results in good long-term stability on the accuracy of the next 3-7 days' AQI prediction. PMID:27597861

  6. Single-trial prediction of reaction time variability from MEG brain activity

    PubMed Central

    Ohata, Ryu; Ogawa, Kenji; Imamizu, Hiroshi

    2016-01-01

    Neural activity prior to movement onset contains essential information for predictive assistance for humans using brain-machine-interfaces (BMIs). Even though previous studies successfully predicted different goals for upcoming movements, it is unclear whether non-invasive recording signals contain the information to predict trial-by-trial behavioral variability under the same movement. In this paper, we examined the predictability of subsequent short or long reaction times (RTs) from magnetoencephalography (MEG) signals in a delayed-reach task. The difference in RTs was classified significantly above chance from 550 ms before the go-signal onset using the cortical currents in the premotor cortex. Significantly above-chance classification was performed in the lateral prefrontal and the right inferior parietal cortices at the late stage of the delay period. Thus, inter-trial variability in RTs is predictable information. Our study provides a proof-of-concept of the future development of non-invasive BMIs to prevent delayed movements. PMID:27250872

  7. A Long-Term Prediction Model of Beijing Haze Episodes Using Time Series Analysis

    PubMed Central

    Zhang, Zhongqiu; Sun, Liren; Xu, Cui

    2016-01-01

    The rapid industrial development has led to the intermittent outbreak of pm2.5 or haze in developing countries, which has brought about great environmental issues, especially in big cities such as Beijing and New Delhi. We investigated the factors and mechanisms of haze change and present a long-term prediction model of Beijing haze episodes using time series analysis. We construct a dynamic structural measurement model of daily haze increment and reduce the model to a vector autoregressive model. Typical case studies on 886 continuous days indicate that our model performs very well on next day's Air Quality Index (AQI) prediction, and in severely polluted cases (AQI ≥ 300) the accuracy rate of AQI prediction even reaches up to 87.8%. The experiment of one-week prediction shows that our model has excellent sensitivity when a sudden haze burst or dissipation happens, which results in good long-term stability on the accuracy of the next 3–7 days' AQI prediction. PMID:27597861

  8. Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex.

    PubMed

    Wittmann, Marco K; Kolling, Nils; Akaishi, Rei; Chau, Bolton K H; Brown, Joshua W; Nelissen, Natalie; Rushworth, Matthew F S

    2016-01-01

    In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex. PMID:27477632

  9. How Predictable Is the Operative Time of Laparoscopic Surgery for Ovarian Endometrioma?

    PubMed Central

    Gambadauro, Pietro; Campo, Vincenzo; Campo, Sebastiano

    2015-01-01

    Endometriosis is a tricky albeit common disease whose management largely relies on laparoscopy. We have studied the operative times of laparoscopic endometrioma surgery in order to assess their predictability and possible predictors. One hundred forty-eight laparoscopies were included, with a median operative time of 70 minutes (mean 75.14; 95% CI: 70.03–80.24). Half of the cases had a duration within 15–20 minutes above or below the median (IQR: 55–93.75), but the whole dataset ranged from 20 to 180 minutes, and the standard deviation was relatively large (31.4). Surgical times were significantly related to technical (number and size of the cysts) and nontechnical factors (age, parity, dysmenorrhea, and family history). At multiple logistic regression, after adjusting for number and size of the cysts, surgical times below the first quartile were associated with older age (>30 years old: aOR: 3.590; 95% CI: 1.417–9.091) and parity (≥1 delivery: aOR: 3.409; 95% CI: 1.343–8.651). Longer times, above the third quartile, were instead predicted by a familial anamnesis of endometriosis (aOR: 3.639; 95% CI: 1.246–10.627). Our findings indicate highly variable surgical times, which are predicted by unexpected nontechnical factors. This is consistent with the complexity of endometriosis and its treatment. Productivity and efficiency in endometriosis surgery should focus on the quality of healthcare outcomes rather than on the time spent in the operating theatres. PMID:26417455

  10. Pulse-echo ultrasound transit time spectroscopy: A comparison of experimental measurement and simulation prediction.

    PubMed

    Wille, Marie-Luise; Almualimi, Majdi A; Langton, Christian M

    2016-01-01

    Considering ultrasound propagation through complex composite media as an array of parallel sonic rays, a comparison of computer-simulated prediction with experimental data has previously been reported for transmission mode (where one transducer serves as transmitter, the other as receiver) in a series of 10 acrylic step-wedge samples, immersed in water, exhibiting varying degrees of transit time inhomogeneity. In this study, the same samples were used but in pulse-echo mode, where the same ultrasound transducer served as both transmitter and receiver, detecting both 'primary' (internal sample interface) and 'secondary' (external sample interface) echoes. A transit time spectrum was derived, describing the proportion of sonic rays with a particular transit time. A computer simulation was performed to predict the transit time and amplitude of various echoes created, and compared with experimental data. Applying an amplitude-tolerance analysis, 91.7% ± 3.7% of the simulated data were within ±1 standard deviation of the experimentally measured amplitude-time data. Correlation of predicted and experimental transit time spectra provided coefficients of determination (R(2)%) ranging from 100.0% to 96.8% for the various samples tested. The results acquired from this study provide good evidence for the concept of parallel sonic rays. Furthermore, deconvolution of experimental input and output signals has been shown to provide an effective method to identify echoes otherwise lost due to phase cancellation. Potential applications of pulse-echo ultrasound transit time spectroscopy include improvement of ultrasound image fidelity by improving spatial resolution and reducing phase interference artefacts. PMID:26586528

  11. Can a Clinical Test of Reaction Time Predict a Functional Head-Protective Response?

    PubMed Central

    ECKNER, JAMES T.; LIPPS, DAVID B.; KIM, HOGENE; RICHARDSON, JAMES K.; ASHTON-MILLER, JAMES A.

    2015-01-01

    Purpose Reaction time is commonly prolonged after a sport-related concussion. Besides being a marker for injury, a rapid reaction time is necessary for protective maneuvers that can reduce the frequency and severity of additional head impacts. The purpose of this study was to determine whether a clinical test of simple visuomotor reaction time predicted the time taken to raise the hands to protect the head from a rapidly approaching ball. Methods Twenty-six healthy adult participants recruited from campus and community recreation and exercise facilities completed two experimental protocols during a single session: a manual visuomotor simple reaction time test (RTclin) and a sport-related head-protective response (RTsprt). RTclin measured the time required to catch a thin vertically oriented device on its release by the tester and was calculated from the distance the device fell before being arrested. RTsprt measured the time required to raise the hands from waist level to block a foam tennis ball fired toward the subject’s face from an air cannon and was determined using an optoelectronic camera system. A correlation coefficient was calculated between RTclin and RTsprt, with linear regression used to assess for effect modification by other covariates. Results A strong positive correlation was found between RTclin and RTsprt (r = 0.725, P < 0.001) independent of age, gender, height, or weight. Conclusions RTclin is predictive of a functional sport-related head-protective response. To our knowledge, this is the first demonstration of a clinical test predicting the ability to protect the head in a simulated sport environment. This correlation with a functional head-protective response is a relevant consideration for the potential use of RTclin as part of a multifaceted concussion assessment program. PMID:20689458

  12. Methods and on-farm devices to predict calving time in cattle.

    PubMed

    Saint-Dizier, Marie; Chastant-Maillard, Sylvie

    2015-09-01

    In livestock farming, accurate prediction of calving time is a key factor for profitability and animal welfare. The most accurate and sensitive methods to date for prediction of calving within 24 h are the measurement of pelvic ligament relaxation and assays for circulating progesterone and oestradiol-17β. Conversely, the absence of calving within the next 12-24 h can be accurately predicted by the measurement of incremental daily decrease in vaginal temperature and by the combination of pelvic ligament relaxation and teat filling estimates. Continuous monitoring systems can detect behavioural changes occurring on the actual day of calving, some of them being accentuated in the last few hours before delivery; standing/lying transitions, tail raising, feeding time, and dry matter and water intakes differ between cows with dystocia and those with eutocia. Use of these behavioural changes has the potential to improve the management of calving. Currently, four types of devices for calving detection are on the market: inclinometers and accelerometers detecting tail raising and overactivity, abdominal belts monitoring uterine contractions, vaginal probes detecting a decrease in vaginal temperature and expulsion of the allantochorion, and devices placed in the vagina or on the vulvar lips that detect calf expulsion. The performance of these devices under field conditions and their capacity to predict dystocia require further investigation. PMID:26164528

  13. Biomarkers in Coronary Artery Bypass Surgery: Ready for Prime Time and Outcome Prediction?

    PubMed Central

    Parolari, Alessandro; Poggio, Paolo; Myasoedova, Veronika; Songia, Paola; Bonalumi, Giorgia; Pilozzi, Alberto; Pacini, Davide; Alamanni, Francesco; Tremoli, Elena

    2016-01-01

    Coronary artery bypass surgery (CABG) is still one of the most frequently performed surgical procedures all over the world. The results of this procedure have been constantly improved over the years with low perioperative mortality rates, with relatively low complication rates. To further improve these outstanding results, the clinicians focused their attention at biomarkers as outcome predictors. Although biological testing for disease prediction has already been discussed many times, the role of biomarkers in outcome prediction after CABG is still controversial. In this article, we reviewed the current knowledge regarding the role of genetic and dynamic biomarkers and their possible association with the occurrence of adverse clinical outcomes after CABG. We also took into consideration that the molecular pathway activation and the possible imbalance may affect hard outcomes and graft patency. We analyzed biomarkers classified in two different categories depending on their possibility to change over time: genetic markers and dynamic markers. Moreover, we evaluated these markers by dividing them, into sub-categories, such as inflammation, hemostasis, renin–angiotensin, endothelial function, and other pathways. We showed that biomarkers might be associated with unfavorable outcomes after surgery, and in some cases improved outcome prediction. However, the identification of a specific panel of biomarkers or of some algorithms including biomarkers is still in an early developmental phase. Finally, larger studies are needed to analyze broad panel of biomarkers with the specific aim to evaluate the prediction of hard outcomes and graft patency. PMID:26779491

  14. Focused attention vs. crossmodal signals paradigm: deriving predictions from the time-window-of-integration model.

    PubMed

    Colonius, Hans; Diederich, Adele

    2012-01-01

    In the crossmodal signals paradigm (CSP) participants are instructed to respond to a set of stimuli from different modalities, presented more or less simultaneously, as soon as a stimulus from any modality has been detected. In the focused attention paradigm (FAP), on the other hand, responses should only be made to a stimulus from a pre-defined target modality and stimuli from non-target modalities should be ignored. Whichever paradigm is being applied, a typical result is that responses tend to be faster to crossmodal stimuli than to unimodal stimuli, a phenomenon often referred to as "crossmodal interaction." Here, we investigate predictions of the time-window-of-integration (TWIN) modeling framework previously proposed by the authors. It is shown that TWIN makes specific qualitative and quantitative predictions on how the two paradigms differ with respect to the probability of multisensory integration and the amount of response enhancement, including the effect of stimulus intensity ("inverse effectiveness"). Introducing a decision-theoretic framework for TWIN further allows comparing the two paradigms with respect to the predicted optimal time window size and its dependence on the prior probability that the crossmodal stimulus information refers to the same event. In order to test these predictions, experimental studies that systematically compare crossmodal effects under stimulus conditions that are identical except for the CSP-FAP instruction should be performed in the future. PMID:22952460

  15. Space can substitute for time in predicting climate-change effects on biodiversity

    USGS Publications Warehouse

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-01-01

    “Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.

  16. Space can substitute for time in predicting climate-change effects on biodiversity

    PubMed Central

    Blois, Jessica L.; Williams, John W.; Fitzpatrick, Matthew C.; Jackson, Stephen T.; Ferrier, Simon

    2013-01-01

    “Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change. PMID:23690569

  17. Predicting time to prostate cancer recurrence based on joint models for non-linear longitudinal biomarkers and event time outcomes.

    PubMed

    Pauler, Donna K; Finkelstein, Dianne M

    2002-12-30

    Biological markers that are both sensitive and specific for tumour regrowth or metastasis are increasingly becoming available and routinely monitored during the regular follow-up of patients treated for cancer. Obtained by a simple blood test, these markers provide an inexpensive non-invasive means for the early detection of recurrence (or progression). Currently, the longitudinal behaviour of the marker is viewed as an indicator of early disease progression, and is applied by a physician in making clinical decisions. One marker that has been studied for use in both population screening for early disease and for detection of recurrence in prostate cancer patients is PSA. The elevation of PSA levels is known to precede clinically detectable recurrence by 2 to 5 years, and current clinical practice often relies partially on multiple recent rises in PSA to trigger a change in treatment. However, the longitudinal trajectory for individual markers is often non-linear; in many cases there is a decline immediately following radiation therapy or surgery, a plateau during remission, followed by an exponential rise following the recurrence of the cancer. The aim of this article is to determine the multiple aspects of the longitudinal PSA biomarker trajectory that can be most sensitive for predicting time to clinical recurrence. Joint Bayesian models for the longitudinal measures and event times are utilized based on non-linear hierarchical models, implied by unknown change-points, for the longitudinal trajectories, and a Cox proportional hazard model for progression times, with functionals of the longitudinal parameters as covariates in the Cox model. Using Markov chain Monte Carlo sampling schemes, the joint model is fit to longitudinal PSA measures from 676 patients treated at Massachusetts General Hospital between the years 1988 and 1995 with follow-up to 1999. Based on these data, predictive schemes for detecting cancer recurrence in new patients based on their

  18. Comparisons of Crosswind Velocity Profile Estimates Used in Fast-Time Wake Vortex Prediction Models

    NASA Technical Reports Server (NTRS)

    Pruis, Mathew J.; Delisi, Donald P.; Ahmad, Nashat N.

    2011-01-01

    Five methods for estimating crosswind profiles used in fast-time wake vortex prediction models are compared in this study. Previous investigations have shown that temporal and spatial variations in the crosswind vertical profile have a large impact on the transport and time evolution of the trailing vortex pair. The most important crosswind parameters are the magnitude of the crosswind and the gradient in the crosswind shear. It is known that pulsed and continuous wave lidar measurements can provide good estimates of the wind profile in the vicinity of airports. In this study comparisons are made between estimates of the crosswind profiles from a priori information on the trajectory of the vortex pair as well as crosswind profiles derived from different sensors and a regional numerical weather prediction model.

  19. Constructing and predicting solitary pattern solutions for nonlinear time-fractional dispersive partial differential equations

    NASA Astrophysics Data System (ADS)

    Arqub, Omar Abu; El-Ajou, Ahmad; Momani, Shaher

    2015-07-01

    Building fractional mathematical models for specific phenomena and developing numerical or analytical solutions for these fractional mathematical models are crucial issues in mathematics, physics, and engineering. In this work, a new analytical technique for constructing and predicting solitary pattern solutions of time-fractional dispersive partial differential equations is proposed based on the generalized Taylor series formula and residual error function. The new approach provides solutions in the form of a rapidly convergent series with easily computable components using symbolic computation software. For method evaluation and validation, the proposed technique was applied to three different models and compared with some of the well-known methods. The resultant simulations clearly demonstrate the superiority and potentiality of the proposed technique in terms of the quality performance and accuracy of substructure preservation in the construct, as well as the prediction of solitary pattern solutions for time-fractional dispersive partial differential equations.

  20. Predicting the learning and consultation time in a computerized primary healthcare clinic.

    PubMed

    Blignaut, P J; McDonald, T; Tolmie, C J

    2001-01-01

    Managers would like to know how long it takes healthcare service providers to achieve the same throughput of patients per day that they were used to with a pen-and-paper system. This study has been undertaken to derive a model for predicting the time it takes a service provider from a previously disadvantaged community to enter a patient's record in terms of his or her experience and the number of data units that have to be captured. A model was also derived to predict the average consultation time in terms of the number of data units that are captured by an experienced service provider. It can be inferred that healthcare service providers should be allowed at least 6 months of computerized system experience before any decisions about the success of the technology introduction can be made. PMID:11391885

  1. Reduction in predicted survival times in cold water due to wind and waves.

    PubMed

    Power, Jonathan; Simões Ré, António; Barwood, Martin; Tikuisis, Peter; Tipton, Michael

    2015-07-01

    Recent marine accidents have called into question the level of protection provided by immersion suits in real (harsh) life situations. Two immersion suit studies, one dry and the other with 500 mL of water underneath the suit, were conducted in cold water with 10-12 males in each to test body heat loss under three environmental conditions: calm, as mandated for immersion suit certification, and two combinations of wind plus waves to simulate conditions typically found offshore. In both studies mean skin heat loss was higher in wind and waves vs. calm; deep body temperature and oxygen consumption were not different. Mean survival time predictions exceeded 36 h for all conditions in the first study but were markedly less in the second in both calm and wind and waves. Immersion suit protection and consequential predicted survival times under realistic environmental conditions and with leakage are reduced relative to calm conditions. PMID:25766418

  2. Prediction of switching time between movement preparation and execution by neural activity in monkey premotor cortex.

    PubMed

    Li, Hongbao; Liao, Yuxi; Wang, Yiwen; Zhang, Qiaosheng; Zhang, Shaomin; Zheng, Xiaoxiang

    2015-01-01

    Premotor cortex is a higher level cortex than primary motor cortex in movement controlling hierarchy, which contributes to the motor preparation and execution simultaneously during the planned movement. The mediation mechanism from movement preparation to execution has attracted many scientists' attention. Gateway hypothesis is one possible explanation that some neurons act as "gating" to release the movement intention at the "on-go" cue. We propose to utilize a local-learning based feature extraction method to target the neurons in premotor cortex, which functionally contribute mostly to the discrimination between motor preparation and execution without tuning information to either target or movement trajectory. Then the support vector machine is utilized to predict the single trial switching time. With top three functional "gating" neurons, the prediction accuracy rate of the switching time is above 90%, which indicates the potential of asynchronous BMI control using premotor cortical activity. PMID:26736827

  3. Seabed Spectra Predictions Using a Time-Dependent Seafloor Boundary Layer Model

    NASA Astrophysics Data System (ADS)

    Palmsten, M. L.; Penko, A.; Olejniczak, K. O.; Calantoni, J.; Sheremet, A.; Kaihatu, J. M.; Weiss, R.

    2014-12-01

    Waves and currents on the continental shelf interact to produce time-varying complex ripple patterns on the seafloor. While high-resolution, two-phase models can provide details on the physics of sediment transport in the bottom boundary layer, time-varying ripple models can predict the seafloor topography spectrum providing estimates of ripple height, length, orientation and ultimately, seafloor roughness. Roughness is an important characteristic of the bottom boundary layer that affects waves and currents as well as acoustic scattering and penetration into the seabed. A one-dimensional spectral ripple model is used to predict the time-dependent seafloor spectra given a time series of observed or forecasted wave conditions. The model allows each wave number component of the seafloor spectra to evolve independently and treats the temporal evolution of the components as a relaxation process. The approach allows for an adjustment timescale that is dependent on the previous bed state, includes a wash out criteria for strong wave conditions, and is forced with robust equilibrium ripple predictors. We compare the spatial and temporal seafloor spectra predictions from the model to ripples observed during an experiment at the O.H. Hinsdale Wave Research Laboratory at Oregon State University. Ripple lengths were estimated from data collected by a high-frequency sector scanning sonar throughout the 6-day experiment. Wave heights and periods ranged from 0.25 m to 1 m and 2 s to 5 s, respectively. The observed data is used to validate the timescale of ripple evolution and ripple lengths predicted by the model.

  4. Real-time speech encoding based on Code-Excited Linear Prediction (CELP)

    NASA Technical Reports Server (NTRS)

    Leblanc, Wilfrid P.; Mahmoud, S. A.

    1988-01-01

    This paper reports on the work proceeding with regard to the development of a real-time voice codec for the terrestrial and satellite mobile radio environments. The codec is based on a complexity reduced version of code-excited linear prediction (CELP). The codebook search complexity was reduced to only 0.5 million floating point operations per second (MFLOPS) while maintaining excellent speech quality. Novel methods to quantize the residual and the long and short term model filters are presented.

  5. A Simple and Efficient Computational Approach to Chafed Cable Time-Domain Reflectometry Signature Prediction

    NASA Technical Reports Server (NTRS)

    Kowalski, Marc Edward

    2009-01-01

    A method for the prediction of time-domain signatures of chafed coaxial cables is presented. The method is quasi-static in nature, and is thus efficient enough to be included in inference and inversion routines. Unlike previous models proposed, no restriction on the geometry or size of the chafe is required in the present approach. The model is validated and its speed is illustrated via comparison to simulations from a commercial, three-dimensional electromagnetic simulator.

  6. The future of nursing.

    PubMed

    Moores, Y

    1999-01-01

    The White paper, "The New NHS, Modern-Dependable" has marked a turning point for the National Health Service and Nursing, replacing the internal market with integrated care, and sets out a vision of health service that meets the full range of patients' needs in all care settings. Assuring quality is an underpinning theme of the White paper, with nursing having a vital role in driving this agenda forward. Quality encompasses the environment of care, the professionalism, skill and compassion of staff, the effectiveness of treatments and respect and dignity of patients. This is an exciting time for nursing with many challenges, as the recognition and value for nursing grows. The profession has the ability to rise to these challenges and make a real difference to people's health and well being. PMID:10418368

  7. R. Louise Mcmanus and Mildred Montag Create the Associate Degree Model for the Education of Nurses: The Right Leaders, the Right Time, the Right Place: 1947 to 1959

    ERIC Educational Resources Information Center

    McAllister, Annemarie

    2012-01-01

    The development of the Associate Degree model for the education of nurses (ADN) in the United States is a significant milestone for the nursing profession. The purpose of this historical study was to examine how nurse leaders developed the model in the 1950s and to explore the contextual factors that fueled the growth of the model. Emphasis was…

  8. Prediction of leisure-time walking: an integration of social cognitive, perceived environmental, and personality factors

    PubMed Central

    Rhodes, Ryan E; Courneya, Kerry S; Blanchard, Chris M; Plotnikoff, Ronald C

    2007-01-01

    Background Walking is the primary focus of population-based physical activity initiatives but a theoretical understanding of this behaviour is still elusive. The purpose of this study was to integrate personality, the perceived environment, and planning into a theory of planned behaviour (TPB) framework to predict leisure-time walking. Methods Participants were a random sample (N = 358) of Canadian adults who completed measures of the TPB, planning, perceived neighbourhood environment, and personality at Time 1 and self-reported walking behaviour two months later. Results Analyses using structural equation modelling provided evidence that leisure-time walking is largely predicted by intention (standardized effect = .42) with an additional independent contribution from proximity to neighbourhood retail shops (standardized effect = .18). Intention, in turn, was predicted by attitudes toward walking and perceived behavioural control. Effects of perceived neighbourhood aesthetics and walking infrastructure on walking were mediated through attitudes and intention. Moderated regression analysis showed that the intention-walking relationship was moderated by conscientiousness and proximity to neighbourhood recreation facilities but not planning. Conclusion Overall, walking behaviour is theoretically complex but may best be addressed at a population level by facilitating strong intentions in a receptive environment even though individual differences may persist. PMID:17974022

  9. Neural Network of Predictive Motor Timing in the Context of Gender Differences

    PubMed Central

    Lošák, Jan; Kašpárek, Tomáš; Vaníček, Jiří; Bareš, Martin

    2016-01-01

    Time perception is an essential part of our everyday lives, in both the prospective and the retrospective domains. However, our knowledge of temporal processing is mainly limited to the networks responsible for comparing or maintaining specific intervals or frequencies. In the presented fMRI study, we sought to characterize the neural nodes engaged specifically in predictive temporal analysis, the estimation of the future position of an object with varying movement parameters, and the contingent neuroanatomical signature of differences in behavioral performance between genders. The established dominant cerebellar engagement offers novel evidence in favor of a pivotal role of this structure in predictive short-term timing, overshadowing the basal ganglia reported together with the frontal cortex as dominant in retrospective temporal processing in the subsecond spectrum. Furthermore, we discovered lower performance in this task and massively increased cerebellar activity in women compared to men, indicative of strategy differences between the genders. This promotes the view that predictive temporal computing utilizes comparable structures in the retrospective timing processes, but with a definite dominance of the cerebellum. PMID:27019753

  10. Evaluation of a Satellite-based Near Real-time Global Flood Prediction System

    NASA Astrophysics Data System (ADS)

    Yilmaz, K. K.; Adler, R. F.; Hong, Y.; Pierce, H. F.

    2008-12-01

    Satellite-based rainfall and geospatial datasets are potentially useful for cost effective detection and early warning of natural hazards, such as floods, specifically for regions of the world where local data are sparse or non-existent. An initial satellite-based near real-time global flood prediction system is operationally available on our website (http://trmm.gsfc.nasa.gov/publications_dir/potential_flood_hydro.html). The key input to the current system is the near real-time rainfall estimates from the NASA-based Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA; 3 hourly, 0.258 x 0.258 degree). A relatively simple hydrologic model, based on the runoff curve number (CN) and antecedent precipitation index (API) methods, transforms rainfall into runoff. In this study we will present an in-depth testing/evaluation of this current flood prediction system, discuss its strengths and limitations and point toward potential improvements necessary for increasing its near real-time global flood prediction reliability and accuracy. This evaluation study will focus on the severe flooding events and will include comparison of the current product with observed runoff/inundation data at global and watershed scale as well as with other available remotely sensed products (e.g., MODIS-based inundation maps from Dartmouth Flood Observatory).

  11. Model-based planning and real-time predictive control for laser-induced thermal therapy

    PubMed Central

    Feng, Yusheng; Fuentes, David

    2014-01-01

    In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity. PMID:22098360

  12. Toward an Accurate Prediction of the Arrival Time of Geomagnetic-Effective Coronal Mass Ejections

    NASA Astrophysics Data System (ADS)

    Shi, T.; Wang, Y.; Wan, L.; Cheng, X.; Ding, M.; Zhang, J.

    2015-12-01

    Accurately predicting the arrival of coronal mass ejections (CMEs) to the Earth based on remote images is of critical significance for the study of space weather. Here we make a statistical study of 21 Earth-directed CMEs, specifically exploring the relationship between CME initial speeds and transit times. The initial speed of a CME is obtained by fitting the CME with the Graduated Cylindrical Shell model and is thus free of projection effects. We then use the drag force model to fit results of the transit time versus the initial speed. By adopting different drag regimes, i.e., the viscous, aerodynamics, and hybrid regimes, we get similar results, with a least mean estimation error of the hybrid model of 12.9 hr. CMEs with a propagation angle (the angle between the propagation direction and the Sun-Earth line) larger than their half-angular widths arrive at the Earth with an angular deviation caused by factors other than the radial solar wind drag. The drag force model cannot be reliably applied to such events. If we exclude these events in the sample, the prediction accuracy can be improved, i.e., the estimation error reduces to 6.8 hr. This work suggests that it is viable to predict the arrival time of CMEs to the Earth based on the initial parameters with fairly good accuracy. Thus, it provides a method of forecasting space weather 1-5 days following the occurrence of CMEs.

  13. Neural Network of Predictive Motor Timing in the Context of Gender Differences.

    PubMed

    Filip, Pavel; Lošák, Jan; Kašpárek, Tomáš; Vaníček, Jiří; Bareš, Martin

    2016-01-01

    Time perception is an essential part of our everyday lives, in both the prospective and the retrospective domains. However, our knowledge of temporal processing is mainly limited to the networks responsible for comparing or maintaining specific intervals or frequencies. In the presented fMRI study, we sought to characterize the neural nodes engaged specifically in predictive temporal analysis, the estimation of the future position of an object with varying movement parameters, and the contingent neuroanatomical signature of differences in behavioral performance between genders. The established dominant cerebellar engagement offers novel evidence in favor of a pivotal role of this structure in predictive short-term timing, overshadowing the basal ganglia reported together with the frontal cortex as dominant in retrospective temporal processing in the subsecond spectrum. Furthermore, we discovered lower performance in this task and massively increased cerebellar activity in women compared to men, indicative of strategy differences between the genders. This promotes the view that predictive temporal computing utilizes comparable structures in the retrospective timing processes, but with a definite dominance of the cerebellum. PMID:27019753

  14. A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

    NASA Astrophysics Data System (ADS)

    Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

    2016-09-01

    This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

  15. Health habits of nursing versus non-nursing students: a longitudinal study.

    PubMed

    Shriver, C B; Scott-Stiles, A

    2000-10-01

    As our culture shifts from a sickness repair system to a health promotion and disease prevention system, nurses need to take more responsibility for practicing positive health behaviors. The problem addressed in this study was "Does exposure to nursing theory content and client interactions make any difference in the regular practice of positive health behaviors in nursing students when compared to non-nursing students?" The purpose of this study was to determine if nursing students practice healthy life styles that would help prepare them to be effective advocates for health promotion and disease prevention. The Health Habits Inventory (HHI) was used in this two-year longitudinal study to compare health habits between 71 nursing and 83 non-nursing students. There was a statistically significant difference between nursing and non-nursing students in time 1 (t = 4.91, p < .001) and time 2 (t = 3.59, p < .001) with nursing students scoring higher in health habits. Nursing students improved significantly from time 1 to time 2 (t = 2.05, p = .021) whereas nonnursing students did not improve (t = .94, p = .175). In specific behaviors, nursing students improved in eating breakfast regularly, performing monthly self breast and testicular exams, reading food labels, wearing seatbelts, and exercising at least three times a week. Implications include the importance of emphasizing self health care in nursing curricula to promote healthy life styles of nursing students who can subsequently become role models in their professional practice. PMID:11052653

  16. Recent Shift in Climate Relationship Enables Prediction of the Timing of Bird Breeding.

    PubMed

    Hinsley, Shelley A; Bellamy, Paul E; Hill, Ross A; Ferns, Peter N

    2016-01-01

    Large-scale climate processes influence many aspects of ecology including breeding phenology, reproductive success and survival across a wide range of taxa. Some effects are direct, for example, in temperate-zone birds, ambient temperature is an important cue enabling breeding effort to coincide with maximum food availability, and earlier breeding in response to warmer springs has been documented in many species. In other cases, time-lags of up to several years in ecological responses have been reported, with effects mediated through biotic mechanisms such as growth rates or abundance of food supplies. Here we use 23 years of data for a temperate woodland bird species, the great tit (Parus major), breeding in deciduous woodland in eastern England to demonstrate a time-lagged linear relationship between the on-set of egg laying and the winter index of the North Atlantic Oscillation such that timing can be predicted from the winter index for the previous year. Thus the timing of bird breeding (and, by inference, the timing of spring events in general) can be predicted one year in advance. We also show that the relationship with the winter index appears to arise through an abiotic time-lag with local spring warmth in our study area. Examining this link between local conditions and larger-scale processes in the longer-term showed that, in the past, significant relationships with the immediately preceding winter index were more common than those with the time-lagged index, and especially so from the late 1930s to the early 1970s. However, from the mid 1970s onwards, the time-lagged relationship has become the most significant, suggesting a recent change in climate patterns. The strength of the current time-lagged relationship suggests that it might have relevance for other temperature-dependent ecological relationships. PMID:27182711

  17. Prediction of Probabilistic Sleep Distributions Following Travel Across Multiple Time Zones

    PubMed Central

    Darwent, David; Dawson, Drew; Roach, Greg D.

    2010-01-01

    Study Objectives: To parameterize and validate a model to estimate average sleep times for long-haul aviation pilots during layovers following travel across multiple time zones. The model equations were based on a weighted distribution of domicile- and local-time sleepers, and included algorithms to account for sleep loss and circadian re-synchronization. Design: Sleep times were collected from participants under normal commercial operating conditions using diaries and wrist activity monitors. Participants: Participants included a total of 306 long-haul pilots (113 captains, 120 first officers, and 73 second officers). Measurement and Results: The model was parameterized based on the average sleep/wake times observed during international flight patterns from Australia to London and Los Angeles (global R2 = 0.72). The parameterized model was validated against the average sleep/wake times observed during flight patterns from Australia to London (r2 = 0.85), Los Angeles (r2 = 0.79), New York (r2 = 0.80), and Johannesburg (r2 = 0.73). Goodness-of-fit was poorer when the parameterized model equations were used to predict the variance across the sleep/wake cycles of individual pilots (R2 = 0.42, 0.35, 0.31, and 0.28 for the validation flight patterns, respectively), in part because of substantial inter-individual variability in sleep timing and duration. Conclusions: It is possible to estimate average sleep times during layovers in international patterns with a reasonable degree of accuracy. Models of this type could form the basis of a stand-alone application to estimate the likelihood that a given duty schedule provides pilots, on average, with an adequate opportunity to sleep. Citation: Darwent D; Dawson D; Roach GD. Prediction of probabilistic sleep distributions following travel across multiple time zones. SLEEP 2010;33(2):185-195. PMID:20175402

  18. Recent Shift in Climate Relationship Enables Prediction of the Timing of Bird Breeding

    PubMed Central

    Bellamy, Paul E.; Hill, Ross A.; Ferns, Peter N.

    2016-01-01

    Large-scale climate processes influence many aspects of ecology including breeding phenology, reproductive success and survival across a wide range of taxa. Some effects are direct, for example, in temperate-zone birds, ambient temperature is an important cue enabling breeding effort to coincide with maximum food availability, and earlier breeding in response to warmer springs has been documented in many species. In other cases, time-lags of up to several years in ecological responses have been reported, with effects mediated through biotic mechanisms such as growth rates or abundance of food supplies. Here we use 23 years of data for a temperate woodland bird species, the great tit (Parus major), breeding in deciduous woodland in eastern England to demonstrate a time-lagged linear relationship between the on-set of egg laying and the winter index of the North Atlantic Oscillation such that timing can be predicted from the winter index for the previous year. Thus the timing of bird breeding (and, by inference, the timing of spring events in general) can be predicted one year in advance. We also show that the relationship with the winter index appears to arise through an abiotic time-lag with local spring warmth in our study area. Examining this link between local conditions and larger-scale processes in the longer-term showed that, in the past, significant relationships with the immediately preceding winter index were more common than those with the time-lagged index, and especially so from the late 1930s to the early 1970s. However, from the mid 1970s onwards, the time-lagged relationship has become the most significant, suggesting a recent change in climate patterns. The strength of the current time-lagged relationship suggests that it might have relevance for other temperature-dependent ecological relationships. PMID:27182711

  19. Potential for long-lead prediction of the western North Pacific monsoon circulation beyond seasonal time scales

    NASA Astrophysics Data System (ADS)

    Choi, Jung; Son, Seok-Woo; Seo, Kyong-Hwan; Lee, June-Yi; Kang, Hyun-Suk

    2016-02-01

    Although the western North Pacific (WNP) monsoon circulation significantly impacts the socioeconomic communities around Asia, its prediction is only limited to a few months. By examining the Coupled Model Intercomparison Project phase 5 decadal hindcast experiments, we explore a possibility of the extended prediction skill for the WNP monsoon circulation beyond seasonal time scales. It is found that the multimodel ensemble (MME) predictions, initialized in January, successfully predict the WNP circulation in spring and early summer. Somewhat surprisingly, a reliable prediction of the WNP circulation appears even in the following spring with a maximum lead time of 14 months. This unexpected prediction skill is likely caused by the improved El Niño-Southern Oscillation (ENSO) prediction and the exaggerated dynamical link between the ENSO and premonsoon circulation in the MME prediction. Although further studies are needed, this result may open up new opportunities for the multiseasonal prediction of the WNP monsoon circulation.

  20. A nonlinear time-lag differential equation model for predicting monthly precipitation

    NASA Astrophysics Data System (ADS)

    Peng, Yongqing; Yan, Shaojin; Wang, Tongmei

    1995-08-01

    This paper investigates the nonlinear prediction of monthly rainfall time series which consists of phase space continuation of one-dimensional sequence, followed by least-square determination of the coefficients for the terms of the time-lag differential equation model and then fitting of the prognostic expression is made to 1951 1980 monthly rainfall datasets from Changsha station. Results show that the model is likely to describe the nonlinearity of the annual cycle of precipitation on a monthly basis and to provide a basis for flood prevention and drought combating for the wet season.

  1. Hydrocarbon Reservoir Prediction Using Bi-Gaussian S Transform Based Time-Frequency Analysis Approach

    NASA Astrophysics Data System (ADS)

    Cheng, Z.; Chen, Y.; Liu, Y.; Liu, W.; Zhang, G.

    2015-12-01

    Among those hydrocarbon reservoir detection techniques, the time-frequency analysis based approach is one of the most widely used approaches because of its straightforward indication of low-frequency anomalies from the time-frequency maps, that is to say, the low-frequency bright spots usually indicate the potential hydrocarbon reservoirs. The time-frequency analysis based approach is easy to implement, and more importantly, is usually of high fidelity in reservoir prediction, compared with the state-of-the-art approaches, and thus is of great interest to petroleum geologists, geophysicists, and reservoir engineers. The S transform has been frequently used in obtaining the time-frequency maps because of its better performance in controlling the compromise between the time and frequency resolutions than the alternatives, such as the short-time Fourier transform, Gabor transform, and continuous wavelet transform. The window function used in the majority of previous S transform applications is the symmetric Gaussian window. However, one problem with the symmetric Gaussian window is the degradation of time resolution in the time-frequency map due to the long front taper. In our study, a bi-Gaussian S transform that substitutes the symmetric Gaussian window with an asymmetry bi-Gaussian window is proposed to analyze the multi-channel seismic data in order to predict hydrocarbon reservoirs. The bi-Gaussian window introduces asymmetry in the resultant time-frequency spectrum, with time resolution better in the front direction, as compared with the back direction. It is the first time that the bi-Gaussian S transform is used for analyzing multi-channel post-stack seismic data in order to predict hydrocarbon reservoirs since its invention in 2003. The superiority of the bi-Gaussian S transform over traditional S transform is tested on a real land seismic data example. The performance shows that the enhanced temporal resolution can help us depict more clearly the edge of the

  2. Educating nurses for leadership roles.

    PubMed

    Heller, Barbara R; Drenkard, Karen; Esposito-Herr, Mary Beth; Romano, Carol; Tom, Sally; Valentine, Nancy

    2004-01-01

    As a result of the growing shortage of nurses and the dramatically changing role of the front-line nurse manager, leadership education for nurses is of critical importance. The purpose of the project described in this article was to design, implement, and evaluate an innovative model of nursing leadership development for students enrolled in registered nurse to bachelor of science in nursing or registered nurse to master of science in nursing programs. A guided "action-learning" course was designed that focused on both core knowledge and experiential learning. The course was developed with the assistance of an advisory panel of prominent nurse leaders with expertise in administration, health policy, informatics, and nursing education. The prototype course was offered for the first time as an elective in Spring 2003. Evaluation data indicated that the course was considered valuable by students and with modifications suggested by students, faculty, and advisory panel members, the course would be offered regularly as part of the curriculum. Recommendations also included adapting course content to a continuing education format. PMID:15481400

  3. The Power of Influence: School Nurse Stories.

    PubMed

    Mazyck, Donna; Cellucci, Margaret; Largent, Piper

    2015-07-01

    School nurses have influence, and this influence is ignited with school nurse stories. School nurses must tell school staff, leaders, families, and students what they do to help students access their education. School boards, city councils, and legislators need to know the knowledge, skills, and judgment school nurses use daily. NASN understands that school nurses benefit from a "how to" kit and has developed tools to empower school nurses in advocating for their important role in supporting the health and learning of students. This article provides an overview this newly developed electronic toolkit while at the same time reinforcing the power of influence when sharing your stories. PMID:26018906

  4. Sharable and Comparable Data for Nursing Management.

    PubMed

    Garcia, Amy; Caspers, Barbara; Westra, Bonnie; Pruinelli, Lisianne; Delaney, Connie

    2015-01-01

    Nurse leaders and researchers are challenged by the need for sharable and comparable data on the nursing workforce and the processes of patient care. This is significant, as nursing is the largest health care workforce, with significant operational costs. The Nursing Management Minimum Data Set provides a core set of data elements to compare nursing practice across time, diverse health care settings, and geographical areas. Nursing leaders from practice, association, academic, consulting, and industry settings were interviewed to provide perspectives on how the use of standardized data sets can be useful for the profession. PMID:26340240

  5. Financial Distress Prediction Using Discrete-time Hazard Model and Rating Transition Matrix Approach

    NASA Astrophysics Data System (ADS)

    Tsai, Bi-Huei; Chang, Chih-Huei

    2009-08-01

    Previous studies used constant cut-off indicator to distinguish distressed firms from non-distressed ones in the one-stage prediction models. However, distressed cut-off indicator must shift according to economic prosperity, rather than remains fixed all the time. This study focuses on Taiwanese listed firms and develops financial distress prediction models based upon the two-stage method. First, this study employs the firm-specific financial ratio and market factors to measure the probability of financial distress based on the discrete-time hazard models. Second, this paper further focuses on macroeconomic factors and applies rating transition matrix approach to determine the distressed cut-off indicator. The prediction models are developed by using the training sample from 1987 to 2004, and their levels of accuracy are compared with the test sample from 2005 to 2007. As for the one-stage prediction model, the model in incorporation with macroeconomic factors does not perform better than that without macroeconomic factors. This suggests that the accuracy is not improved for one-stage models which pool the firm-specific and macroeconomic factors together. In regards to the two stage models, the negative credit cycle index implies the worse economic status during the test period, so the distressed cut-off point is adjusted to increase based on such negative credit cycle index. After the two-stage models employ such adjusted cut-off point to discriminate the distressed firms from non-distressed ones, their error of misclassification becomes lower than that of one-stage ones. The two-stage models presented in this paper have incremental usefulness in predicting financial distress.

  6. Time-series prediction using Ensemble Kalman Filter without dynamic model

    NASA Astrophysics Data System (ADS)

    Ide, Kayo

    2016-04-01

    Ensemble data assimilation techniques have been successfully used to improve predictive skill in cases where a numerical model for forecasting has been developed. It is desirable to extend this utility to systems for which no model exists and observations of the complete state of the system may not be possible. For many natural systems, equations governing the evolution are unknown and only a partial observation of the high dimensional state vector is possible. For dissipative systems in which variables are coupled nonlinearly, the dimensionality of the phase space can be greatly reduced as the dynamics contracts onto a strange attractor. In these cases, it is possible to reconstruct the details of the phase space from a single scalar time series of observations using time-embedding. The Ensemble Transform Kalman (ETKF) can be applied to ensemble forecast and analyze the observations in the time-embedded space constructed from long time series of the data and the future evolution. We apply the method to a long historical time series of measurements of the Earth's magnetic field is recorded by ground based magnetometers The prediction skill improves with respect to persistence by incorporating information from observations and the behavior of nearby trajectories.

  7. Timing and prediction of CO2 eruptions from Crystal Geyser, UT

    SciTech Connect

    Gouveia, F J; Friedmann, S J

    2006-05-30

    Special instruments were deployed at Crystal Geyser, Utah, in August 2005 creating a contiguous 76-day record of eruptions from this cold geyser. Sensors measured temperature and fluid movement at the base of the geyser. Analysis of the time series that contains the start time and duration of 140 eruptions reveals a striking bimodal distribution in eruption duration. About two thirds of the eruptions were short (7-32 min), and about one third were long (98-113 min). No eruption lasted between 32 and 98 min. There is a strong correlation between the duration of an eruption and the subsequent time until the next eruption. A linear least-squares fit of these data can be used to predict the time of the next eruption. The predictions were within one hour of actual eruption time for 90% of the very short eruptions (7-19 min), and about 45% of the long eruptions. Combined with emission estimates from a previous study, we estimate the annual CO{sub 2} emission from Crystal Geyser to be about 11 gigagrams (11,000 tons).

  8. RELIGION & CARE INTERTWINED; NURSING IN CATHOLIC HOSPITALS 1950-1965.

    PubMed

    Anthony, Maureen

    2016-01-01

    This qualitative study explores how Catholicism influenced nursing in Catholic hospitals and how nurses met the religious needs of Catholic patients in the 1950s and early 1960s. Six nurses were interviewed who graduated from Catholic schools of nursing between 1952 and 1965 and worked in Catholic hospitals. Results indicate that nursing care was inexorably entwined with meeting the religious needs of Catholic patients. Religious practices were predictable and largely linked to the Holy Sacraments. PMID:26817370

  9. Chronic Health Conditions Managed by School Nurses. Position Statement. Revised

    ERIC Educational Resources Information Center

    Morgitan, Judith; Bushmiaer, Margo; DeSisto, Marie C.; Duff, Carolyn; Lambert, C. Patrice; Murphy, M. Kathleen; Roland, Sharon; Selser, Kendra; Wyckoff, Leah; White, Kelly

    2012-01-01

    It is the position of the National Association of School Nurses that students with chronic health conditions have access to a full-time registered professional school nurse (hereinafter referred to as school nurse). School districts should include school nurse positions in their full-time instructional support personnel to provide health services…

  10. Prediction of acoustic scattering in the time domain and its applications to rotorcraft noise

    NASA Astrophysics Data System (ADS)

    Lee, Seongkyu

    This work aims at the development of a numerical method for the analysis of acoustic scattering in the time domain and its applications to rotorcraft noise. This purpose is achieved by developing two independent methods: (1) an analytical formulation of the pressure gradient for an arbitrary moving source and (2) a time-domain moving equivalent source method. First, the analytical formulation for the pressure gradient is developed to fulfill the boundary condition on a scattering surface to account for arbitrary moving incident sources. A semi-analytical formulation was derived from the gradient of the Ffowcs Williams-Hawkings (FW-H) equation. This formulation needs to calculate the observer time differentiation outside the integrals numerically. A numerical algorithm is developed to implement this formulation in an aeroacoustic prediction code. A new analytical formulation is presented in the thesis. In this formulation, the time differentiation is taken inside the integrals analytically. This formulation avoids the numerical time differentiation with respect to the observer time, which is computationally more efficient. The acoustic pressure gradient predicted by these two formulations is validated through comparison with available exact solutions for a stationary and moving monopole sources. The agreement between the predictions and exact solutions is excellent. One of the advantages of this analytic formulation is that it efficiently provides the boundary condition for the acoustic scattering of sound generated from an arbitrary moving source, such as rotating blades, which undergoes rotation, flapping and lead-lag motions. The formulation is applied to the rotor noise problems for two model rotors (UH-1H and HART-I). For HART-I rotor, CFD/CSD coupling was used to provide unsteady aerodynamics and trim solutions of the blade motion. A purely numerical approach is compared with the analytical formulations. The agreement between the analytical formulations and

  11. Predicting permeability from the characteristic relaxation time and intrinsic formation factor of complex conductivity spectra

    NASA Astrophysics Data System (ADS)

    Revil, A.; Binley, A.; Mejus, L.; Kessouri, P.

    2015-08-01

    Low-frequency quadrature conductivity spectra of siliclastic materials exhibit typically a characteristic relaxation time, which either corresponds to the peak frequency of the phase or the quadrature conductivity or a typical corner frequency, at which the quadrature conductivity starts to decrease rapidly toward lower frequencies. This characteristic relaxation time can be combined with the (intrinsic) formation factor and a diffusion coefficient to predict the permeability to flow of porous materials at saturation. The intrinsic formation factor can either be determined at several salinities using an electrical conductivity model or at a single salinity using a relationship between the surface and quadrature conductivities. The diffusion coefficient entering into the relationship between the permeability, the characteristic relaxation time, and the formation factor takes only two distinct values for isothermal conditions. For pure silica, the diffusion coefficient of cations, like sodium or potassium, in the Stern layer is equal to the diffusion coefficient of these ions in the bulk pore water, indicating weak sorption of these couterions. For clayey materials and clean sands and sandstones whose surface have been exposed to alumina (possibly iron), the diffusion coefficient of the cations in the Stern layer appears to be 350 times smaller than the diffusion coefficient of the same cations in the pore water. These values are consistent with the values of the ionic mobilities used to determine the amplitude of the low and high-frequency quadrature conductivities and surface conductivity. The database used to test the model comprises a total of 202 samples. Our analysis reveals that permeability prediction with the proposed model is usually within an order of magnitude from the measured value above 0.1 mD. We also discuss the relationship between the different time constants that have been considered in previous works as characteristic relaxation time, including

  12. Timing of beta oscillatory synchronization and temporal prediction of upcoming stimuli.

    PubMed

    Meijer, David; Te Woerd, Erik; Praamstra, Peter

    2016-09-01

    Modulations of beta oscillatory power serve a predictive role, in preparation of future actions. It is well known that beta amplitude decreases prior to voluntary movements and expected tactile stimuli. Paradoxically, recent studies have reported a beta amplitude increase prior to expected visual and auditory stimuli. Moreover, it has been suggested that, in isochronic stimulus series, the rising beta slope is adjusted to the duration of the interstimulus interval. We investigated the characteristics of such timing related pre-stimulus beta power increases using visual stimulus sequences that were presented at three regular rates (0.61, 0.74 and 0.95Hz). EEG was recorded from twenty participants while they attended the sequences by performing a clock reading task. Time-frequency analyses showed a consistent pattern of beta modulation: the post-stimulus beta power decrease was followed by a steep increase. Contrary to recent views, we found that the peaks of beta power, for the three presentation rates, were reached at a similar latency post-stimulus, instead of a fixed interval preceding the next stimulus. This demonstrates that, at interstimulus intervals between 1-2s, beta synchronization slopes are not modulated by timing mechanisms related to prediction of upcoming stimuli. We reconcile the discrepant results by proposing that when shorter interval durations are used, as in previous studies, beta resynchronization is interrupted by the presentation of a new stimulus, making it seem as if beta power peaks prior to upcoming stimuli. We emphasize caution with respect to the notion that the timing of beta synchronization is an expression of predictive timing. PMID:27255465

  13. Less-structured time in children's daily lives predicts self-directed executive functioning

    PubMed Central

    Barker, Jane E.; Semenov, Andrei D.; Michaelson, Laura; Provan, Lindsay S.; Snyder, Hannah R.; Munakata, Yuko

    2014-01-01

    Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6–7 year-old children's daily, annual, and typical schedules. We categorized children's activities as “structured” or “less-structured” based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up

  14. Empirical prediction of climate dynamics: optimal models, derived from time series

    NASA Astrophysics Data System (ADS)

    Mukhin, D.; Loskutov, E. M.; Gavrilov, A.; Feigin, A. M.

    2013-12-01

    The new empirical method for prediction of climate indices by the analysis of climatic fields' time series is suggested. The method is based on construction of prognostic models of evolution operator (EO) in low-dimensional subspaces of system's phase space. One of the main points of suggested analysis is reconstruction of appropriate basis of dynamical variables (predictors) from spatially distributed data: different ways of data decomposition are discussed in the report including EOFs, MSSA and other relevant data rotations. We consider the models of different complexity for EO reconstruction, from linear statistical models of particular indices to more complex artificial neural network (ANN) models of climatic patterns dynamics, which take the form of discrete random dynamical systems [1]. Very important problem, that always arises in empirical modeling approaches, is optimal model selection criterium: appropriate regularization procedure is needed to avoid overfitted model. Particulary, it includes finding the optimal structural parameters of the model such as dimension of variables vector, i.e. number of principal components used for modeling, number of states used for prediction, and number of parameters determining quality of approximation. In this report the minimal descriptive length (MDL) approach [2] is proposed for this purpose: the model providing most data compression is chosen. Results of application of suggested method to analysis of SST and SLP fields' time series [3] covering last 30-50 years are presented: predictions of different climate indices time series including NINO 3.4, MEI, PDO, NOA are shown. References: 1. Y. I. Molkov, E. M. Loskutov, D. N. Mukhin, and A. M. Feigin, Random dynamical models from time series, Phys. Rev. E 85, 036216, 2012 2. Molkov, Ya.I., D.N. Mukhin, E.M. Loskutov, A.M. Feigin, and G.A. Fidelin, Using the minimum description length principle for global reconstruction of dynamic systems from noisy time series. Phys

  15. Cloud-Based Numerical Weather Prediction for Near Real-Time Forecasting and Disaster Response

    NASA Technical Reports Server (NTRS)

    Molthan, Andrew; Case, Jonathan; Venners, Jason; Schroeder, Richard; Checchi, Milton; Zavodsky, Bradley; Limaye, Ashutosh; O'Brien, Raymond

    2015-01-01

    The use of cloud computing resources continues to grow within the public and private sector components of the weather enterprise as users become more familiar with cloud-computing concepts, and competition among service providers continues to reduce costs and other barriers to entry. Cloud resources can also provide capabilities similar to high-performance computing environments, supporting multi-node systems required for near real-time, regional weather predictions. Referred to as "Infrastructure as a Service", or IaaS, the use of cloud-based computing hardware in an on-demand payment system allows for rapid deployment of a modeling system in environments lacking access to a large, supercomputing infrastructure. Use of IaaS capabilities to support regional weather prediction may be of particular interest to developing countries that have not yet established large supercomputing resources, but would otherwise benefit from a regional weather forecasting capability. Recently, collaborators from NASA Marshall Space Flight Center and Ames Research Center have developed a scripted, on-demand capability for launching the NOAA/NWS Science and Training Resource Center (STRC) Environmental Modeling System (EMS), which includes pre-compiled binaries of the latest version of the Weather Research and Forecasting (WRF) model. The WRF-EMS provides scripting for downloading appropriate initial and boundary conditions from global models, along with higher-resolution vegetation, land surface, and sea surface temperature data sets provided by the NASA Short-term Prediction Research and Transition (SPoRT) Center. This presentation will provide an overview of the modeling system capabilities and benchmarks performed on the Amazon Elastic Compute Cloud (EC2) environment. In addition, the presentation will discuss future opportunities to deploy the system in support of weather prediction in developing countries supported by NASA's SERVIR Project, which provides capacity building

  16. From Earthquake Prediction Research to Time-Variable Seismic Hazard Assessment Applications

    NASA Astrophysics Data System (ADS)

    Bormann, Peter

    2011-01-01

    The first part of the paper defines the terms and classifications common in earthquake prediction research and applications. This is followed by short reviews of major earthquake prediction programs initiated since World War II in several countries, for example the former USSR, China, Japan, the United States, and several European countries. It outlines the underlying expectations, concepts, and hypotheses, introduces the technologies and methodologies applied and some of the results obtained, which include both partial successes and failures. Emphasis is laid on discussing the scientific reasons why earthquake prediction research is so difficult and demanding and why the prospects are still so vague, at least as far as short-term and imminent predictions are concerned. However, classical probabilistic seismic hazard assessments, widely applied during the last few decades, have also clearly revealed their limitations. In their simple form, they are time-independent earthquake rupture forecasts based on the assumption of stable long-term recurrence of earthquakes in the seismotectonic areas under consideration. Therefore, during the last decade, earthquake prediction research and pilot applications have focused mainly on the development and rigorous testing of long and medium-term rupture forecast models in which event probabilities are conditioned by the occurrence of previous earthquakes, and on their integration into neo-deterministic approaches for improved time-variable seismic hazard assessment. The latter uses stress-renewal models that are calibrated for variations in the earthquake cycle as assessed on the basis of historical, paleoseismic, and other data, often complemented by multi-scale seismicity models, the use of pattern-recognition algorithms, and site-dependent strong-motion scenario modeling. International partnerships and a global infrastructure for comparative testing have recently been developed, for example the Collaboratory for the Study of

  17. Kernel density estimation-based real-time prediction for respiratory motion

    NASA Astrophysics Data System (ADS)

    Ruan, Dan

    2010-03-01

    Effective delivery of adaptive radiotherapy requires locating the target with high precision in real time. System latency caused by data acquisition, streaming, processing and delivery control necessitates prediction. Prediction is particularly challenging for highly mobile targets such as thoracic and abdominal tumors undergoing respiration-induced motion. The complexity of the respiratory motion makes it difficult to build and justify explicit models. In this study, we honor the intrinsic uncertainties in respiratory motion and propose a statistical treatment of the prediction problem. Instead of asking for a deterministic covariate-response map and a unique estimate value for future target position, we aim to obtain a distribution of the future target position (response variable) conditioned on the observed historical sample values (covariate variable). The key idea is to estimate the joint probability distribution (pdf) of the covariate and response variables using an efficient kernel density estimation method. Then, the problem of identifying the distribution of the future target position reduces to identifying the section in the joint pdf based on the observed covariate. Subsequently, estimators are derived based on this estimated conditional distribution. This probabilistic perspective has some distinctive advantages over existing deterministic schemes: (1) it is compatible with potentially inconsistent training samples, i.e., when close covariate variables correspond to dramatically different response values; (2) it is not restricted by any prior structural assumption on the map between the covariate and the response; (3) the two-stage setup allows much freedom in choosing statistical estimates and provides a full nonparametric description of the uncertainty for the resulting estimate. We evaluated the prediction performance on ten patient RPM traces, using the root mean squared difference between the prediction and the observed value normalized by the

  18. A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

    PubMed

    Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

    2015-09-20

    Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system. PMID:25980520

  19. Water quality management using statistical analysis and time-series prediction model

    NASA Astrophysics Data System (ADS)

    Parmar, Kulwinder Singh; Bhardwaj, Rashmi

    2014-12-01

    This paper deals with water quality management using statistical analysis and time-series prediction model. The monthly variation of water quality standards has been used to compare statistical mean, median, mode, standard deviation, kurtosis, skewness, coefficient of variation at Yamuna River. Model validated using R-squared, root mean square error, mean absolute percentage error, maximum absolute percentage error, mean absolute error, maximum absolute error, normalized Bayesian information criterion, Ljung-Box analysis, predicted value and confidence limits. Using auto regressive integrated moving average model, future water quality parameters values have been estimated. It is observed that predictive model is useful at 95 % confidence limits and curve is platykurtic for potential of hydrogen (pH), free ammonia, total Kjeldahl nitrogen, dissolved oxygen, water temperature (WT); leptokurtic for chemical oxygen demand, biochemical oxygen demand. Also, it is observed that predicted series is close to the original series which provides a perfect fit. All parameters except pH and WT cross the prescribed limits of the World Health Organization /United States Environmental Protection Agency, and thus water is not fit for drinking, agriculture and industrial use.

  20. Predicting long-term catchment nutrient export: the use of nonlinear time series models

    NASA Astrophysics Data System (ADS)

    Valent, Peter; Howden, Nicholas J. K.; Szolgay, Jan; Komornikova, Magda

    2010-05-01

    After the Second World War the nitrate concentrations in European water bodies changed significantly as the result of increased nitrogen fertilizer use and changes in land use. However, in the last decades, as a consequence of the implementation of nitrate-reducing measures in Europe, the nitrate concentrations in water bodies slowly decrease. This causes that the mean and variance of the observed time series also changes with time (nonstationarity and heteroscedascity). In order to detect changes and properly describe the behaviour of such time series by time series analysis, linear models (such as autoregressive (AR), moving average (MA) and autoregressive moving average models (ARMA)), are no more suitable. Time series with sudden changes in statistical characteristics can cause various problems in the calibration of traditional water quality models and thus give biased predictions. Proper statistical analysis of these non-stationary and heteroscedastic time series with the aim of detecting and subsequently explaining the variations in their statistical characteristics requires the use of nonlinear time series models. This information can be then used to improve the model building and calibration of conceptual water quality model or to select right calibration periods in order to produce reliable predictions. The objective of this contribution is to analyze two long time series of nitrate concentrations of the rivers Ouse and Stour with advanced nonlinear statistical modelling techniques and compare their performance with traditional linear models of the ARMA class in order to identify changes in the time series characteristics. The time series were analysed with nonlinear models with multiple regimes represented by self-exciting threshold autoregressive (SETAR) and Markov-switching models (MSW). The analysis showed that, based on the value of residual sum of squares (RSS) in both datasets, SETAR and MSW models described the time-series better than models of the

  1. Knowledge-based nursing diagnosis

    NASA Astrophysics Data System (ADS)

    Roy, Claudette; Hay, D. Robert

    1991-03-01

    Nursing diagnosis is an integral part of the nursing process and determines the interventions leading to outcomes for which the nurse is accountable. Diagnoses under the time constraints of modern nursing can benefit from a computer assist. A knowledge-based engineering approach was developed to address these problems. A number of problems were addressed during system design to make the system practical extended beyond capture of knowledge. The issues involved in implementing a professional knowledge base in a clinical setting are discussed. System functions, structure, interfaces, health care environment, and terminology and taxonomy are discussed. An integrated system concept from assessment through intervention and evaluation is outlined.

  2. Prediction of Late-Time Concentration Tailing Through Characterization of Hydrofacies Distributions

    NASA Astrophysics Data System (ADS)

    Zhang, Y.; Benson, D. A.

    2006-12-01

    Anomalous (non-Fickian) diffusion is often manifested in extra mass in the late-time tail of the breakthrough curve (BTC). Current non-local techniques, including the multi-rate mass transfer method (MRMT) and the continuous time random walk (CTRW) method, are a posteriori fitting procedures that assign an appropriate memory function or a transition time distribution function to account for the trapping of solute particles in relatively immobile domains. The MRMT and CTRW are functionally equivalent, but the MRMT method allows a straightforward, a priori construction of the memory function based on readily available information about the statistics of the immobile zone geometry. We explore the quantitative relationship between the memory function and aquitard material heterogeneity using Monte Carlo simulations of the regional-scale alluvial aquifer system at the Lawrence Livermore National Laboratory site. Particle tracking simulations show that the shape of the late-time BTC depends on the thickness and the associated volume fractions of immobile water in "blocks" of fine-grained material. The ensemble solute concentration at later time can be very accurately predicted using a small number of exponential functions with rates dictated by aquitard thicknesses. Specifically, if the volume fraction of immobile layer thicknesses has a power-law probability distribution function (pdf), then a power-law BTC late tail will be guaranteed. When the volume fraction of immobile blocks has an exponential pdf, the late-time BTC will have a transition from power-law to exponential decay. The MRMT solutions are easily generated and accurately predict the later BTC tails. Since the residence time dictated by diffusive motion in the silt and clay layers embedded in typical natural media far exceeds the residence time in a laboratory column, we anticipate that upscaling from lab studies is irrelevant in most cases. The observed relationship between the BTC late tail and the

  3. Evaluation of real-time hydrometeorological ensemble prediction on hydrologic scales in Northern California

    NASA Astrophysics Data System (ADS)

    Georgakakos, Konstantine P.; Graham, Nicholas E.; Modrick, Theresa M.; Murphy, Michael J.; Shamir, Eylon; Spencer, Cristopher R.; Sperfslage, Jason A.

    2014-11-01

    The paper presents an evaluation of real time ensemble forecasts produced during 2010-2012 by the demonstration project INFORM (Integrated Forecast and Reservoir Management) in Northern California. In addition, the innovative elements of the forecast component of the INFORM project are highlighted. The forecast component is designed to dynamically downscale operational multi-lead ensemble forecasts from the Global Ensemble Forecast System (GEFS) and the Climate Forecast system (CFS) of the National Centers of Environmental Prediction (NCEP), and to use adaptations of the operational hydrologic models of the US National Weather Service California Nevada River Forecast Center to provide ensemble reservoir inflow forecasts in real time. A full-physics 10-km resolution (10 km on the side) mesoscale model was implemented for the ensemble prediction of surface precipitation and temperature over the domain of Northern California with lead times out to 16 days with 6-hourly temporal resolution. An intermediate complexity regional model with a 10 km resolution was implemented to downscale the NCEP CFS ensemble forecasts for lead times out to 41.5 days. Methodologies for precipitation and temperature model forecast adjustment to comply with the corresponding observations were formulated and tested as regards their effectiveness for improving the ensemble predictions of these two variables and also for improving reservoir inflow forecasts. The evaluation is done using the real time databases of INFORM and concerns the snow accumulation and melt seasons. Performance is measured by metrics that range from those that use forecast means to those that use the entire forecast ensemble. The results show very good skill in forecasting precipitation and temperature over the subcatchments of the INFORM domain out to a week in advance for all basins, models and seasons. For temperature, in some cases, non-negligible skill has been obtained out to four weeks for the melt season

  4. Geomagnetic Storm and Substorm Predictions with the Real-Time WINDMI Model

    NASA Astrophysics Data System (ADS)

    Mays, Mona; Horton, Wendell; Kozyra, Janet

    The Real-Time WINDMI model is an implementation of WINDMI, a low dimensional, plasma physics-based, nonlinear dynamical model of the coupled magnetosphere-ionosphere system. The system of nonlinear ordinary differential equations, which describes energy transfer into, and between dominant components of the nightside magnetosphere and ionosphere, is solved numerically to determine the state of each component. The model characterizes the energy stored in the ring current and the region 1 field-aligned current which are compared to the Dst and AL indices. Solar wind parameter measurements from ACE are automatically downloaded every 10 minutes and used to derive the input solar wind driving voltage to the model. This allows the computation of model Dst and AL values by Real-Time WINDMI about 1-2 hours before index data is available at the Kyoto WDC Quicklook website. Model results are shown on the website (http://orion.ph.utexas.edu/ windmi/realtime/). The model has captured about 15 storm and/or substorm events in the past 2 years it has been running. Model validation for the AL and Dst predictions is being implemented. Real-Time WINDMI performance is also studied for the rectified driving voltage compared to the Siscoe et al. voltage as input. We plan to compare the database of Real-Time WINDMI Dst predictions with other ring current models which contain different loss and energization processes. The work is supported by NSF grant ATM-0638480.

  5. The discovery of slowness: Time to deconstruct Gretzky's and Messi's predictive brains.

    PubMed

    Erren, Thomas C; Kuffer, Liz; Pinger, Andreas; Groß, J Valérie

    2016-01-01

    Jafari and Smith hypothesized that time during games may pass slower for the world's best football player, Lionel Messi, from Argentina. This hypothesis leads to two questions: How can we explain such temporal paradox and how could this explain his dominant performances? Remarkably, the Argentinian's case was preceded by the equally astonishing case of Wayne Gretzky: The Canadian considered ice hockey as a rather slow game and was the best player in the sport's history. Whether Messi's and Gretzky's motor neurons fire faster, (inter)act differently or whether other mechanisms are at (inter)play warrants targeted research. A further explanation for such dominance of football and ice hockey, respectively, could be that both athletes "buy time": To this end, automized motor skills may allow their predictive brains to make better use of time than other players to read the games and plan ahead. Deconstructing predictive minds of outperforming individuals like Gretzky and Messi could provide unique options to elucidate how differential time perception may make performances in athletes, and beyond, more swift and more efficient. PMID:27159282

  6. Program and Teacher Characteristics Predicting the Implementation of Banking Time with Preschoolers Who Display Disruptive Behaviors.

    PubMed

    Williford, Amanda P; Wolcott, Catherine Sanger; Whittaker, Jessica Vick; Locasale-Crouch, Jennifer

    2015-11-01

    This study examined the relationship among baseline program and teacher characteristics and subsequent implementation of Banking Time. Banking Time is a dyadic intervention intended to improve a teacher's interaction quality with a specific child. Banking Time implementation was examined in the current study using a sample of 59 teachers and preschool children displaying disruptive behaviors in the classroom (~three children per classroom). Predictors included preschool program type, teacher demographic characteristics (personal and professional), and teacher beliefs (self-efficacy, authoritarian beliefs, and negative attributions about child disruptive behavior). Multiple measures and methods (i.e., teacher report, consultant report, independent observations) were used to assess implementation. We created three implementation composite measures (dosage, quality, and generalized practice) that had high internal consistencies within each composite but were only modestly associated with one another, suggesting unique constructs of implementation. We found that type of preschool program was associated with dosage and quality. Aspects of teacher demographics related to all three implementation composites. Teacher beliefs predicted dosage and generalized practice. Results suggest that the factors that predict the implementation of Banking Time vary as a function of the type of implementation being assessed. PMID:25627344

  7. Mortality Prediction in ICUs Using A Novel Time-Slicing Cox Regression Method

    PubMed Central

    Wang, Yuan; Chen, Wenlin; Heard, Kevin; Kollef, Marin H.; Bailey, Thomas C.; Cui, Zhicheng; He, Yujie; Lu, Chenyang; Chen, Yixin

    2015-01-01

    Over the last few decades, machine learning and data mining have been increasingly used for clinical prediction in ICUs. However, there is still a huge gap in making full use of the time-series data generated from ICUs. Aiming at filling this gap, we propose a novel approach entitled Time Slicing Cox regression (TS-Cox), which extends the classical Cox regression into a classification method on multi-dimensional time-series. Unlike traditional classifiers such as logistic regression and support vector machines, our model not only incorporates the discriminative features derived from the time-series, but also naturally exploits the temporal orders of these features based on a Cox-like function. Empirical evaluation on MIMIC-II database demonstrates the efficacy of the TS-Cox model. Our TS-Cox model outperforms all other baseline models by a good margin in terms of AUC_PR, sensitivity and PPV, which indicates that TS-Cox may be a promising tool for mortality prediction in ICUs. PMID:26958269

  8. Time history prediction of direct-drive implosions on the Omega facility

    DOE PAGESBeta

    Laffite, S.; Bourgade, J. L.; Caillaud, T.; Delettrez, J A; Frenje, J. A.; Girard, F.; Glebov, V. Yu.; Joshi, Tirtha Raj; Landoas, O.; Legay, G.; et al

    2016-01-14

    We present in this article direct-drive experiments that were carried out on the Omega facility [T. R. Boehly et al., Opt. Commun. 133, 495 (1997)]. Two different pulse shapes were tested in order to vary the implosion stability of the same target whose parameters, dimensions and composition, remained the same. The direct-drive configuration on the Omega facility allows the accurate time-resolvedmeasurement of the scattered light. We show that, provided the laser coupling is well controlled, the implosion time history, assessed by the “bang-time” and the shell trajectory measurements, can be predicted. This conclusion is independent on the pulse shape. Inmore » contrast, we show that the pulse shape affects the implosion stability, assessed by comparing the target performances between prediction and measurement. For the 1-ns square pulse, the measuredneutron number is about 80% of the prediction. Lastly, for the 2-step 2-ns pulse, we test here that this ratio falls to about 20%.« less

  9. Predicting demographically sustainable rates of adaptation: can great tit breeding time keep pace with climate change?

    PubMed Central

    Gienapp, Phillip; Lof, Marjolein; Reed, Thomas E.; McNamara, John; Verhulst, Simon; Visser, Marcel E.

    2013-01-01

    Populations need to adapt to sustained climate change, which requires micro-evolutionary change in the long term. A key question is how the rate of this micro-evolutionary change compares with the rate of environmental change, given that theoretically there is a ‘critical rate of environmental change’ beyond which increased maladaptation leads to population extinction. Here, we parametrize two closely related models to predict this critical rate using data from a long-term study of great tits (Parus major). We used stochastic dynamic programming to predict changes in optimal breeding time under three different climate scenarios. Using these results we parametrized two theoretical models to predict critical rates. Results from both models agreed qualitatively in that even ‘mild’ rates of climate change would be close to these critical rates with respect to great tit breeding time, while for scenarios close to the upper limit of IPCC climate projections the calculated critical rates would be clearly exceeded with possible consequences for population persistence. We therefore tentatively conclude that micro-evolution, together with plasticity, would rescue only the population from mild rates of climate change, although the models make many simplifying assumptions that remain to be tested. PMID:23209174

  10. PLIO: a generic tool for real-time operational predictive optimal control of water networks.

    PubMed

    Cembrano, G; Quevedo, J; Puig, V; Pérez, R; Figueras, J; Verdejo, J M; Escaler, I; Ramón, G; Barnet, G; Rodríguez, P; Casas, M

    2011-01-01

    This paper presents a generic tool, named PLIO, that allows to implement the real-time operational control of water networks. Control strategies are generated using predictive optimal control techniques. This tool allows the flow management in a large water supply and distribution system including reservoirs, open-flow channels for water transport, water treatment plants, pressurized water pipe networks, tanks, flow/pressure control elements and a telemetry/telecontrol system. Predictive optimal control is used to generate flow control strategies from the sources to the consumer areas to meet future demands with appropriate pressure levels, optimizing operational goals such as network safety volumes and flow control stability. PLIO allows to build the network model graphically and then to automatically generate the model equations used by the predictive optimal controller. Additionally, PLIO can work off-line (in simulation) and on-line (in real-time mode). The case study of Santiago-Chile is presented to exemplify the control results obtained using PLIO off-line (in simulation). PMID:22097020

  11. Perspectives From the Field: Bringing Nurse Leaders Into the Classroom.

    PubMed

    Sortedahl, Charlotte K; Imhoff, Hannah

    2016-01-01

    Leadership is a vital component of nurses' careers and baccalaureate nursing programs are required to include leadership competencies in undergraduate nursing education. To design learning experiences that emphasize professional identity formation, nurse leaders were invited as guest speakers in a senior-level didactic leadership course, but scheduling often interfered with participation. To inspire students and maximize nurse leaders' time, recorded video was investigated as a solution. Following videotaped interviews with nurse leaders, a 10-minute video was produced and shown to students in a nursing leadership course. The video project was evaluated for feasibility, cost-effectiveness, and usefulness as an instructional tool for empowering nursing students. PMID:27209873

  12. Pediatric Nurse Practitioner Program: Theories for Extended Pediatric Nursing Practice.

    ERIC Educational Resources Information Center

    Brady, Margaret A.

    A description is provided of "Theories for Extended Pediatric Nursing Practice," a required course for pediatric and family nurse practitioner students in a California state university program. The course description presents information on the curricular placement of the course, prerequisites, in-class time allotments, and the focus of the course…

  13. Nursing in the Pediatric Intensive Care Unit, Nursing 205.

    ERIC Educational Resources Information Center

    Varton, Deborah M.

    A description is provided of a course, "Nursing in the Pediatric Intensive Care Unit," offered for senior-level baccalaureate degree nursing students. The first section provides information on the place of the course within the curriculum, the allotment of class time, and target student populations. The next section looks at course content in…

  14. [Work related predictors for "satisfaction with dementia care" among nurses working in nursing homes].

    PubMed

    Schmidt, Sascha G; Palm, Rebecca; Dichter, Martin; Hasselhorn, Hans Martin

    2011-04-01

    In German nursing homes dementia care is gaining increasing relevance. Dementia care is known to bear the high risk of a substantial occupational burden among nursing staff. Within this context, the "nurses' satisfaction with the care for residents with dementia" is investigated. Secondary data of the German 3q-study is used to assess degrees of nurses' satisfaction with the care for residents with dementia and potential work related predictors. Data from 813 nurses and nursing aides working in 53 nursing homes were included. 42% of all nursing staff was dissatisfied with the care for residents with dementia in their institution, however, pronounced differences were found between the institutions. Registered nurses and nurses in leading positions were more dissatisfied. A multiple regression analysis indicates that high "quantitative demands", low "leadership quality" and "social interaction with other professions" are strong predictors for nurses' satisfaction with the care for residents with dementia. No association was found for "emotional demands" and "possibilities for development". The results indicate that the "nurses" satisfaction with the care for residents with dementia" may be a highly relevant work factor for nursing staff in nursing homes which deserves additional attention in practice and research. The high predictive power of several work organisational factors implies that preventive action should also include work organisational factors. PMID:21480173

  15. Predicting the timing properties of phosphor-coated scintillators using Monte Carlo light transport simulation.

    PubMed

    Roncali, Emilie; Schmall, Jeffrey P; Viswanath, Varsha; Berg, Eric; Cherry, Simon R

    2014-04-21

    Current developments in positron emission tomography focus on improving timing performance for scanners with time-of-flight (TOF) capability, and incorporating depth-of-interaction (DOI) information. Recent studies have shown that incorporating DOI correction in TOF detectors can improve timing resolution, and that DOI also becomes more important in long axial field-of-view scanners. We have previously reported the development of DOI-encoding detectors using phosphor-coated scintillation crystals; here we study the timing properties of those crystals to assess the feasibility of providing some level of DOI information without significantly degrading the timing performance. We used Monte Carlo simulations to provide a detailed understanding of light transport in phosphor-coated crystals which cannot be fully characterized experimentally. Our simulations used a custom reflectance model based on 3D crystal surface measurements. Lutetium oxyorthosilicate crystals were simulated with a phosphor coating in contact with the scintillator surfaces and an external diffuse reflector (teflon). Light output, energy resolution, and pulse shape showed excellent agreement with experimental data obtained on 3 × 3 × 10 mm³ crystals coupled to a photomultiplier tube. Scintillator intrinsic timing resolution was simulated with head-on and side-on configurations, confirming the trends observed experimentally. These results indicate that the model may be used to predict timing properties in phosphor-coated crystals and guide the coating for optimal DOI resolution/timing performance trade-off for a given crystal geometry. Simulation data suggested that a time stamp generated from early photoelectrons minimizes degradation of the timing resolution, thus making this method potentially more useful for TOF-DOI detectors than our initial experiments suggested. Finally, this approach could easily be extended to the study of timing properties in other scintillation crystals, with a range of

  16. Potential Utility of the Real-Time TMPA-RT Precipitation Estimates in Streamflow Prediction

    NASA Technical Reports Server (NTRS)

    Su, Fengge; Gao, Huilin; Huffman, George J.; Lettenmaier, Dennis P.

    2010-01-01

    We investigate the potential utility of the real-time Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA-RT) data for streamflow prediction, both through direct comparisons of TMPA-RT estimates with a gridded gauge product, and through evaluation of streamflow simulations over four tributaries of La Plata Basin (LPB) in South America using the two precipitation products. Our assessments indicate that the relative accuracy and the hydrologic performance of TMPA-RT-based streamflow simulations generally improved after February 2005. The improvements in TMPA-RT since 2005 are closely related to upgrades in the TMPA-RT algorithm in early February, 2005 which include use of additional microwave sensors (AMSR-E and AMSU-B) and implementation of different calibration schemes. Our work suggests considerable potential for hydrologic prediction using purely satellite-derived precipitation estimates (no adjustments by in situ gauges) in parts of the globe where in situ observations are sparse.

  17. Surrogate Modeling of High-Fidelity Fracture Simulations for Real-Time Residual Strength Predictions

    NASA Technical Reports Server (NTRS)

    Spear, Ashley D.; Priest, Amanda R.; Veilleux, Michael G.; Ingraffea, Anthony R.; Hochhalter, Jacob D.

    2011-01-01

    A surrogate model methodology is described for predicting in real time the residual strength of flight structures with discrete-source damage. Starting with design of experiment, an artificial neural network is developed that takes as input discrete-source damage parameters and outputs a prediction of the structural residual strength. Target residual strength values used to train the artificial neural network are derived from 3D finite element-based fracture simulations. A residual strength test of a metallic, integrally-stiffened panel is simulated to show that crack growth and residual strength are determined more accurately in discrete-source damage cases by using an elastic-plastic fracture framework rather than a linear-elastic fracture mechanics-based method. Improving accuracy of the residual strength training data would, in turn, improve accuracy of the surrogate model. When combined, the surrogate model methodology and high-fidelity fracture simulation framework provide useful tools for adaptive flight technology.

  18. Real time estimation and prediction of ship motions using Kalman filtering techniques

    NASA Technical Reports Server (NTRS)

    Triantafyllou, M. A.; Bodson, M.; Athans, M.

    1982-01-01

    A landing scheme for landing V/STOL aircraft on rolling ships was sought using computerized simulations. The equations of motion as derived from hydrodynamics, their form and the physical mechanisms involved and the general form of the approximation are discussed. The modeling of the sea is discussed. The derivation of the state-space equations for the DD-963 destroyer is described. Kalman filter studies are presented and the influence of the various parameters is assessed. The effect of various modeling parameters on the rms error is assessed and simplifying conclusions are drawn. An upper bound for prediction time of about five seconds is established, with the exception of roll, which can be predicted up to ten seconds ahead.

  19. Time Prediction Model for Pipeline Leakage Based on Grey Relational Analysis

    NASA Astrophysics Data System (ADS)

    Jing, Kang; Zhi-Hong, Zou

    Water leakage management is required for urban water supply industry to minimize water loss and yield good economic benefit. There are many factors that influence urban pipeline leakage. To study these pipeline leakage factors, Grey relational analysis(GRA) is proposed to analyze and evaluate all the factors and draw a order of factors influencing on pipeline leakage. According to the order, a prediction model on some important factors is set up for the leakage by means of the multiple linear regress analysis and the prediction was made for the initial leakage time after the supply networks came into use. It will contribute to the change of passive management mode in water supply industry, so that the leakage can be prevented and controlled as early as possible.

  20. The Effects of Incidentally Learned Temporal and Spatial Predictability on Response Times and Visual Fixations during Target Detection and Discrimination

    PubMed Central

    Beck, Melissa R.; Hong, S. Lee; van Lamsweerde, Amanda E.; Ericson, Justin M.

    2014-01-01

    Responses are quicker to predictable stimuli than if the time and place of appearance is uncertain. Studies that manipulate target predictability often involve overt cues to speed up response times. However, less is known about whether individuals will exhibit faster response times when target predictability is embedded within the inter-trial relationships. The current research examined the combined effects of spatial and temporal target predictability on reaction time (RT) and allocation of overt attention in a sustained attention task. Participants responded as quickly as possible to stimuli while their RT and eye movements were measured. Target temporal and spatial predictability were manipulated by altering the number of: 1) different time intervals between a response and the next target; and 2) possible spatial locations of the target. The effects of target predictability on target detection (Experiment 1) and target discrimination (Experiment 2) were tested. For both experiments, shorter RTs as target predictability increased across both space and time were found. In addition, the influences of spatial and temporal target predictability on RT and the overt allocation of attention were task dependent; suggesting that effective orienting of attention relies on both spatial and temporal predictability. These results indicate that stimulus predictability can be increased without overt cues and detected purely through inter-trial relationships over the course of repeated stimulus presentations. PMID:24732965