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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. 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…

  3. 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

  4. Redefining "time" to meet nursing's evolving demands.

    PubMed

    Altman, Marian; Rosa, William

    2016-03-01

    The American Association of Critical-Care Nurses (AACN) developed the Clinical Scene Investigator (CSI) Academy for nurses at the bedside to hone leadership and innovation skills to create and sustain lasting change and improve patient outcomes. In this first part of a three-part series, we take a look at how the AACN CSI Academy helps clinical nurses cultivate skills that measurably demonstrate how "nonproductive time" is a misnomer that interferes with achieving optimal patient outcomes. PMID:26910094

  5. Predicting nurses' acceptance of radiofrequency identification technology.

    PubMed

    Norten, Adam

    2012-10-01

    The technology of radiofrequency identification allows for the scanning of radiofrequency identification-tagged objects and individuals without line-of-sight requirements. Healthcare organizations use radiofrequency identification to ensure the health and safety of patients and medical personnel and to uncover inefficiencies. Although the successful implementation of a system incorporating radiofrequency identification technologies requires acceptance and use of the technology, some nurses using radiofrequency identification in hospitals feel like "Big Brother" is watching them. This predictive study used a theoretical model assessing the effect of five independent variables: privacy concerns, attitudes, subjective norms, controllability, and self-efficacy, on a dependent variable, nurses' behavioral intention to use radiofrequency identification. A Web-based questionnaire containing previously validated questions was answered by 106 US RNs. Multiple linear regression showed that all constructs together accounted for 60% of the variance in nurses' intention to use radiofrequency identification. Of the predictors in the model, attitudes provided the largest unique contribution when the other predictors in the model were held constant; subjective norms also provided a unique contribution. Privacy concerns, controllability, and self-efficacy did not provide a significant contribution to nurses' behavioral intention to use radiofrequency identification.

  6. Predictors of Nursing Home Residents' Time to Hospitalization

    PubMed Central

    O'Malley, A James; Caudry, Daryl J; Grabowski, David C

    2011-01-01

    Objectives To model the predictors of the time to first acute hospitalization for nursing home residents, and accounting for previous hospitalizations, model the predictors of time between subsequent hospitalizations. Data Sources Merged file from New York State for the period 1998–2004 consisting of nursing home information from the minimum dataset and hospitalization information from the Statewide Planning and Research Cooperative System. Study Design Accelerated failure time models were used to estimate the model parameters and predict survival times. The models were fit to observations from 50 percent of the nursing homes and validated on the remaining observations. Principal Findings Pressure ulcers and facility-level deficiencies were associated with a decreased time to first hospitalization, while the presence of advance directives and facility staffing was associated with an increased time. These predictors of the time to first hospitalization model had effects of similar magnitude in predicting the time between subsequent hospitalizations. Conclusions This study provides novel evidence suggesting modifiable patient and nursing home characteristics are associated with the time to first hospitalization and time to subsequent hospitalizations for nursing home residents. PMID:20849556

  7. 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.

  8. Nursing handover: it's time for a change.

    PubMed

    O'Connell, Bev; Macdonald, Kate; Kelly, Cherene

    2008-08-01

    Nursing handover is a common part of nursing practice that is fundamental to safe patient care. Despite this, the literature provides little direction on the best way to conduct handover. This project aimed to examine nurses' perceptions of handover and to determine the strengths and imitations of the handover process. A staff survey was distributed to nurses in all inpatient wards at a metropolitan tertiary hospital. A total of 176 nurses responded to the staff survey. The findings revealed conflicting opinions about the effectiveness of the handover process; although a number of nurses were positive about current handover practice, indicating they were provided with sufficient information about patients and given opportunity to clarify patient care information, other nurses identified aspects of handover that could be improved. These included: the subjectivity of handover information, the time taken to conduct handover, repetition of information that could be found in the patients' care plans, and handing over of information by a nurse who has not cared for the patient. Some attention needs to be given to addressing the perceived weaknesses associated with the handover process.

  9. 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…

  10. Nursing takes time: workload associated with administering cancer protocols.

    PubMed

    de Raad, Johan; van Gool, Kees; Haas, Marion; Haywood, Philip; Faedo, Margaret; Gallego, Gisselle; Pearson, Sallie; Ward, Robyn

    2010-12-01

    New medicines and therapeutic combinations are tested and marketed every year. Healthcare decision makers have to make explicit choices about adopting new treatments and deal with the resource consequences of their choices. The aim of this article is to examine the nursing workload of administering alternative chemotherapy protocols as a driver of costs. Data collection (focus groups with chemotherapy nurses and a survey of nurse unit managers) was conducted to ascertain the time required to undertake chemotherapy-related tasks and the sources of variability in six chemotherapy centers in New South Wales, Australia. Four task types (patient education, patient assessment, administration, and patient communication) were identified as being associated with administering chemotherapy. On average, patient education required 48 minutes during the first visit and 18.5 minutes thereafter, patient assessment took 20.3 minutes, administration averaged 23 minutes, and patient communication required 24.2 minutes. Each center treated an average of 14 patients per day. Each patient received 3.3 hours of staff time (1.7 hours of direct contact time and 1.6 hours of noncontact time). The result of this research will allow healthcare decision makers and evaluators to predict the amount of nursing time required to administer chemotherapy based on the characteristics of a wide range of chemotherapy protocols.

  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. 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.

  13. Real-time assessment of nurse work environment and stress.

    PubMed

    Shively, Martha; Rutledge, Thomas; Rose, Barbara A; Graham, Patricia; Long, Rebecca; Stucky, Erin; Weinger, Matthew B; Dresselhaus, Timothy

    2011-01-01

    Ecological momentary assessment methods were used to examine real-time relationships between work environment factors and stress in a sample of 119 registered nurses (RNs) in acute and critical care settings of three hospitals. The RNs carried handheld computers for 1 week of work shifts and were randomly surveyed within 90-min intervals to self-report work activity, perceived workload, and stress. Mixed effects linear regression analyses were completed to predict the stress score in the sample. The number of patients assigned significantly predicted stress; the greater the number of assigned patients, the higher the reported stress (p<.01). Age, gender, adult versus pediatric facility type, familiarity with patients, and proportion of direct care tasks were not significant predictors of stress. Further research is needed to link work environment factors and stress with errors among nurses.

  14. Predictive coding of multisensory timing

    PubMed Central

    Shi, Zhuanghua; Burr, David

    2016-01-01

    The sense of time is foundational for perception and action, yet it frequently departs significantly from physical time. In the paper we review recent progress on temporal contextual effects, multisensory temporal integration, temporal recalibration, and related computational models. We suggest that subjective time arises from minimizing prediction errors and adaptive recalibration, which can be unified in the framework of predictive coding, a framework rooted in Helmholtz’s ‘perception as inference’.

  15. Predictive coding of multisensory timing

    PubMed Central

    Shi, Zhuanghua; Burr, David

    2016-01-01

    The sense of time is foundational for perception and action, yet it frequently departs significantly from physical time. In the paper we review recent progress on temporal contextual effects, multisensory temporal integration, temporal recalibration, and related computational models. We suggest that subjective time arises from minimizing prediction errors and adaptive recalibration, which can be unified in the framework of predictive coding, a framework rooted in Helmholtz’s ‘perception as inference’. PMID:27695705

  16. Normalized Elution Time Prediction Utility

    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.

  17. Nursing in Transition: A Time of Opportunity.

    ERIC Educational Resources Information Center

    Duxbury, Mitzi L.; Adams, Lawrence A.

    1987-01-01

    Current challenges to the nursing profession are examined, including changing health needs, health care providers and the cost and quality of their services, the recruitment, retention, and regulation of nurses, and competition. Implications for nursing and parallels with pharmacy are discussed. (MSE)

  18. 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....

  19. Nursing students' confidence in medication calculations predicts math exam performance.

    PubMed

    Andrew, Sharon; Salamonson, Yenna; Halcomb, Elizabeth J

    2009-02-01

    The aim of this study was to examine the psychometric properties, including predictive validity, of the newly-developed nursing self-efficacy for mathematics (NSE-Math). The NSE-Math is a 12 item scale that comprises items related to mathematic and arithmetic concepts underpinning medication calculations. The NSE-Math instrument was administered to second year Bachelor of Nursing students enrolled in a nursing practice subject. Students' academic results for a compulsory medication calculation examination for this subject were collected. One-hundred and twelve students (73%) completed both the NSE-Math instrument and the drug calculation assessment task. The NSE-Math demonstrated two factors 'Confidence in application of mathematic concepts to nursing practice' and 'Confidence in arithmetic concepts' with 63.5% of variance explained. Cronbach alpha for the scale was 0.90. The NSE-Math demonstrated predictive validity with the medication calculation examination results (p=0.009). Psychometric testing suggests the NSE-Math is a valid measure of mathematics self-efficacy of second year nursing students.

  20. Time well spent? Assessing nursing-supply chain activities.

    PubMed

    Ferenc, Jeff

    2010-02-01

    The amount of time nurses spend providing direct patient care seems to be continually eroding. So it's little wonder a survey conducted last year of critical care, OR nurses and nurse executives found that half of the 1600 respondents feel they spend too much time on supply chain duties. Most also said their supply chain duties impact patient safe ty and their ability to provide bedside care. Experts interviewed for this report believe it's time for supply chain leaders and nurses to develop a closer working partnership. Included are their recommendations to improve performance.

  1. 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

  2. A personal reflection: nursing in times of disaster.

    PubMed

    Mather, Mary E

    2010-01-01

    Nurses have the responsibility to provide and promote health with our patients. This can be difficult during the best of times and even harder in times of disaster. This personal reflection discusses one nurse and her team's efforts to assist in the wake of Hurricane Ike.

  3. Factors influencing job satisfaction of oncology nurses over time.

    PubMed

    Cummings, Greta; Olson, Karin; Raymond-Seniuk, Christy; Lo, Eliza; Masaoud, Elmabrok; Bakker, Debra; Fitch, Margaret; Green, Esther; Butler, Lorna; Conlon, Michael

    2013-01-01

    In this study, we tested a structural equation model to examine work environment factors related to changes in job satisfaction of oncology nurses between 2004 and 2006. Relational leadership and good physician/nurse relationships consistently influenced perceptions of enough RNs to provide quality care, and freedom to make patient care decisions, which, in turn, directly influenced nurses' job satisfaction over time. Supervisor support in resolving conflict and the ability to influence patient care outcomes were significant influences on job satisfaction in 2004, whereas, in 2006, a clear philosophy of nursing had a greater significant influence. Several factors that influence job satisfaction of oncology nurses in Canada have changed over time, which may reflect changes in work environments and work life. These findings suggest opportunities to modify work conditions that could improve nurses' job satisfaction and work life.

  4. 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…

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

    PubMed

    Carlson, Joanne S

    2015-07-10

    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.

  6. 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

  7. 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

  8. 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.

  9. 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

  10. 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…

  11. 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

  12. 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

  13. [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

  14. 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.

  15. Research methodology for real-time stress assessment of nurses.

    PubMed

    Milosevic, Mladen; Jovanov, Emil; Frith, Karen H

    2013-12-01

    This article presents a research methodology for analysis of stress effects and allostatic load of nurses during daily activities. Stress-related health issues are critical in healthcare workers, in particular nurses. Typical causes of stress include inadequate staffing of nurses for the number and acuity of patients, dealing with difficult patients and families, and lack of autonomy in care delivery decisions. This is all compounded by lack of recovery time while on shift, variable shifts with limited recovery time between days worked, and fatigue from dealing with difficult patients, families, and healthcare workers. Under unresolved stress, the heart rate and other vital parameters may fail to return to the baseline. This study examined the physiological responses of nurses during care on a high-fidelity patient simulation to develop a research methodology and identify physiological parameters suitable for real-time assessment of allostatic load during work. Our results demonstrated that heart rate and heart rate variability can be reliably measured using wearable sensors to assess allostatic load. During this study and our previous related work, we acquired valuable experience regarding selection and deployment of commercially available sensors, system integration, recruitment of subjects, and general research methodology. The research methodology developed and presented in this article can be applied to a number of other applications and experimental protocols.

  16. Time to talk, time to see: changing microeconomies of professional practice among nurses and doctors in Australian general practice.

    PubMed

    Phillips, Christine; Dwan, Kathryn; Pearce, Christopher; Hall, Sally; Porritt, Julie; Yates, Rachel; Sibbald, Bonnie

    2007-08-01

    In Australia, more nurses are entering general practice, and nurses' work is being funded in increasingly complex ways through Medicare. Little research has explored the ways doctors and nurses realign their priorities and activities when working together in general practice. We undertook rapid, intensive multimethod studies of 25 general practices to explore the ways in which the labour of nurses and doctors was structured, and the implicit decisions made by both professions about the values placed on different ways of working and on their time. Data collected included photographs, floor-plans, interviews with 37 nurses, 24 doctors and 22 practice managers, and 50 hours of structured observation. Nursing time was constructed by both nurses and doctors as being fluid and non-contingent; they were regarded as being 'available' to patients in a way that doctors were not. Compared to medical time, nursing time could be disposed more flexibly, underpinning a valorized attribute of nursing: deep clinical and personal contact with patients. The location of practice nurses' desks in areas of traffic, such as administrative stations, or in the treatment room, underpinned this valuable unstructured contact with patients. Changes to the practice nurse role through direct fee-for-service items for nurses may lead to greater congruence between the microeconomies of nursing and medicine in general practice. In a time of pressure upon a primary care workforce, this is likely to lead to more independent clinical work by nurses, but may also lead to a decrease in flexible contact with patients. PMID:18041994

  17. Interactions of timing and prediction error learning.

    PubMed

    Kirkpatrick, Kimberly

    2014-01-01

    Timing and prediction error learning have historically been treated as independent processes, but growing evidence has indicated that they are not orthogonal. Timing emerges at the earliest time point when conditioned responses are observed, and temporal variables modulate prediction error learning in both simple conditioning and cue competition paradigms. In addition, prediction errors, through changes in reward magnitude or value alter timing of behavior. Thus, there appears to be a bi-directional interaction between timing and prediction error learning. Modern theories have attempted to integrate the two processes with mixed success. A neurocomputational approach to theory development is espoused, which draws on neurobiological evidence to guide and constrain computational model development. Heuristics for future model development are presented with the goal of sparking new approaches to theory development in the timing and prediction error fields.

  18. Interactions of timing and prediction error learning.

    PubMed

    Kirkpatrick, Kimberly

    2014-01-01

    Timing and prediction error learning have historically been treated as independent processes, but growing evidence has indicated that they are not orthogonal. Timing emerges at the earliest time point when conditioned responses are observed, and temporal variables modulate prediction error learning in both simple conditioning and cue competition paradigms. In addition, prediction errors, through changes in reward magnitude or value alter timing of behavior. Thus, there appears to be a bi-directional interaction between timing and prediction error learning. Modern theories have attempted to integrate the two processes with mixed success. A neurocomputational approach to theory development is espoused, which draws on neurobiological evidence to guide and constrain computational model development. Heuristics for future model development are presented with the goal of sparking new approaches to theory development in the timing and prediction error fields. PMID:23962670

  19. 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…

  20. 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"…

  1. 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

  2. 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.

  3. Dynamic visuomotor synchronization: quantification of predictive timing.

    PubMed

    Maruta, Jun; Heaton, Kristin J; Kryskow, Elisabeth M; Maule, Alexis L; Ghajar, Jamshid

    2013-03-01

    When a moving target is tracked visually, spatial and temporal predictions are used to circumvent the neural delay required for the visuomotor processing. In particular, the internally generated predictions must be synchronized with the external stimulus during continuous tracking. We examined the utility of a circular visual-tracking paradigm for assessment of predictive timing, using normal human subjects. Disruptions of gaze-target synchronization were associated with anticipatory saccades that caused the gaze to be temporarily ahead of the target along the circular trajectory. These anticipatory saccades indicated preserved spatial prediction but suggested impaired predictive timing. We quantified gaze-target synchronization with several indices, whose distributions across subjects were such that instances of extremely poor performance were identifiable outside the margin of error determined by test-retest measures. Because predictive timing is an important element of attention functioning, the visual-tracking paradigm and dynamic synchronization indices described here may be useful for attention assessment.

  4. A Holistic Framework for Nursing Time: Implications for Theory, Practice, and Research

    PubMed Central

    Jones, Terry L.

    2010-01-01

    Topic Nursing time has relevance for those who produce it, those who receive it and those who must pay for it. Though the term nursing time may be commonly used, a common understanding of the concept within the fields of nursing and healthcare administration is lacking. Purpose The purposes of this paper are to explore the concept of nursing time and to identify implications for theory development, clinical and administrative practice, and research. Discussion Both physical and psychological forms of time are viewed as fundamental to our experience of time as social beings. Nursing time has significant intrinsic and instrumental value in nursing and healthcare. A holistic approach incorporating the physical, psychological, and sociological aspects and dimensions of nursing time is advocated. Conclusions Multiple strategies to enhance the patient experience of nursing time are warranted and should address how much time nurses spend with patients as well as how they spend that time. Patterns of overlapping and competing time structures for nurses should be identified and evaluated for their effect on physical time available for patient care and the psychological experiences of time by nurses and patients. PMID:20690994

  5. Teachers' perceptions of full- and part-time nurses at school.

    PubMed

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

    2015-06-01

    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 teachers in nine low-income, ethnically diverse urban schools. These schools were part of a multiyear project that placed full-time nurses in four schools, while five schools with part-time nurses were used as a comparison group. Findings indicate that teachers had strong appreciation for the wide range of responsibilities undertaken by the school nurse. Teachers' level of satisfaction was linked to the number of hours the nurse is on-site, where teachers reported greater satisfaction with nurses who worked on campus full time. Results point to factors that may improve working relations between teachers and nurses.

  6. 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…

  7. 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.

  8. How much time do nurses have for patients? a longitudinal study quantifying hospital nurses' patterns of task time distribution and interactions with health professionals

    PubMed Central

    2011-01-01

    Background Time nurses spend with patients is associated with improved patient outcomes, reduced errors, and patient and nurse satisfaction. Few studies have measured how nurses distribute their time across tasks. We aimed to quantify how nurses distribute their time across tasks, with patients, in individual tasks, and engagement with other health care providers; and how work patterns changed over a two year period. Methods Prospective observational study of 57 nurses for 191.3 hours (109.8 hours in 2005/2006 and 81.5 in 2008), on two wards in a teaching hospital in Australia. The validated Work Observation Method by Activity Timing (WOMBAT) method was applied. Proportions of time in 10 categories of work, average time per task, time with patients and others, information tools used, and rates of interruptions and multi-tasking were calculated. Results Nurses spent 37.0%[95%CI: 34.5, 39.3] of their time with patients, which did not change in year 3 [35.7%; 95%CI: 33.3, 38.0]. Direct care, indirect care, medication tasks and professional communication together consumed 76.4% of nurses' time in year 1 and 81.0% in year 3. Time on direct and indirect care increased significantly (respectively 20.4% to 24.8%, P < 0.01;13.0% to 16.1%, P < 0.01). Proportion of time on medication tasks (19.0%) did not change. Time in professional communication declined (24.0% to 19.2%, P < 0.05). Nurses completed an average of 72.3 tasks per hour, with a mean task length of 55 seconds. Interruptions arose at an average rate of two per hour, but medication tasks incurred 27% of all interruptions. In 25% of medication tasks nurses multi-tasked. Between years 1 and 3 nurses spent more time alone, from 27.5%[95%CI 24.5, 30.6] to 39.4%[34.9, 43.9]. Time with health professionals other than nurses was low and did not change. Conclusions Nurses spent around 37% of their time with patients which did not change. Work patterns were increasingly fragmented with rapid changes between tasks of short

  9. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... STUDENT LOANS Nursing Student Loans § 57.313 Loan cancellation for full-time employment as a registered...) Received one or more nursing student loans after November 18, 1971, and before September 29, 1979; (2) is...) is entitled to have a portion of these nursing student loans canceled as follows: 15 percent of...

  10. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... STUDENT LOANS Nursing Student Loans § 57.313 Loan cancellation for full-time employment as a registered...) Received one or more nursing student loans after November 18, 1971, and before September 29, 1979; (2) is...) is entitled to have a portion of these nursing student loans canceled as follows: 15 percent of...

  11. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... STUDENT LOANS Nursing Student Loans § 57.313 Loan cancellation for full-time employment as a registered...) Received one or more nursing student loans after November 18, 1971, and before September 29, 1979; (2) is...) is entitled to have a portion of these nursing student loans canceled as follows: 15 percent of...

  12. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... STUDENT LOANS Nursing Student Loans § 57.313 Loan cancellation for full-time employment as a registered...) Received one or more nursing student loans after November 18, 1971, and before September 29, 1979; (2) is...) is entitled to have a portion of these nursing student loans canceled as follows: 15 percent of...

  13. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... STUDENT LOANS Nursing Student Loans § 57.313 Loan cancellation for full-time employment as a registered...) Received one or more nursing student loans after November 18, 1971, and before September 29, 1979; (2) is...) is entitled to have a portion of these nursing student loans canceled as follows: 15 percent of...

  14. 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.

  15. 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

  16. 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

  17. 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

  18. 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…

  19. Do Past Experiences Predict Agitation in Nursing Home Residents?

    ERIC Educational Resources Information Center

    Cohen-Mansfield, Jiska; Marx, Marcia S.

    1989-01-01

    Examined relationships between agitated behavior and past personality in 408 nursing home residents. Agitated and nonaggressive behaviors were correlated with past stressful events, and physically aggressive behavior was correlated with the lack thereof; no relationships were found between agitated behavior and history of a mental disorder or past…

  20. Predicting Pointing Time from Hand Strength

    NASA Astrophysics Data System (ADS)

    Biswas, Pradipta; Robinson, Peter

    Pointing tasks form a significant part of human-computer interaction in graphical user interfaces. We have developed a model to predict the task completion time for pointing tasks for people with motor-impairment. As part of the model, we have also developed a new scale of characterizing the extent of disability of users by measuring their grip strength. We have validated the model by conducting two trials involving people with motor-impairment and in both trials the model has predicted pointing time with statistically significant accuracy.

  1. 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.

  2. 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

  3. 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.

  4. Time Horizon in Students' Predictions of Grades.

    ERIC Educational Resources Information Center

    Manger, Terje; Teigen, Karl Halvor

    1988-01-01

    Eight and two months before their final exam, 252 undergraduates in Norway stated their expectations and hopes for examination grades. Correlations between expected and obtained grades were low. A shift from optimism to pessimism occurred. Results confirm the time horizon's crucial role in the prediction of academic achievement. (TJH)

  5. 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

  6. Time Will Show: Real Time Predictions during Interpersonal Action Perception

    PubMed Central

    Manera, Valeria; Schouten, Ben; Verfaillie, Karl; Becchio, Cristina

    2013-01-01

    Predictive processes are crucial not only for interpreting the actions of individual agents, but also to predict how, in the context of a social interaction between two agents, the actions of one agent relate to the actions of a second agent. In the present study we investigated whether, in the context of a communicative interaction between two agents, observers can use the actions of one agent to predict when the action of a second agent will take place. Participants observed point-light displays of two agents (A and B) performing separate actions. In the communicative condition, the action performed by agent B responded to a communicative gesture performed by agent A. In the individual condition, agent A's communicative action was substituted with a non-communicative action. For each condition, we manipulated the temporal coupling of the actions of the two agents, by varying the onset of agent A's action. Using a simultaneous masking detection task, we demonstrated that the timing manipulation had a critical effect on the communicative condition, with the visual discrimination of agent B increasing linearly while approaching the original interaction timing. No effect of the timing manipulation was found for the individual condition. Our finding complements and extends previous evidence for interpersonal predictive coding, suggesting that the communicative gestures of one agent can serve not only to predict what the second agent will do, but also when his/her action will take place. PMID:23349992

  7. 'Moral distress'--time to abandon a flawed nursing construct?

    PubMed

    Johnstone, Megan-Jane; Hutchinson, Alison

    2015-02-01

    Moral distress has been characterised in the nursing literature as a major problem affecting nurses in all healthcare systems. It has been portrayed as threatening the integrity of nurses and ultimately the quality of patient care. However, nursing discourse on moral distress is not without controversy. The notion itself is conceptually flawed and suffers from both theoretical and practical difficulties. Nursing research investigating moral distress is also problematic on account of being methodologically weak and disparate. Moreover, the ultimate purpose and significance of the research is unclear. In light of these considerations, it is contended that the notion of moral distress ought to be abandoned and that concerted attention be given to advancing inquiries that are more conducive to improving the quality and safety of moral decision-making, moral conduct and moral outcomes in nursing and healthcare domains.

  8. A systematic review of time studies to assess the impact of patient transfers on nurse workload.

    PubMed

    Blay, Nicole; Duffield, Christine M; Gallagher, Robyn; Roche, Michael

    2014-12-01

    Patients in hospital are increasingly being moved between clinical units and between bedspaces; however, the impact of patient transfers and bedspace moves on nurses' workload is not known. Time studies are an established observational research method that can be used to determine the duration of time taken to perform an activity or process. This review systematically searched four databases for literature published between 2000 and 2013 for observational time study techniques and patient transfers as a nurse activity. Eleven publications from three countries were included in the review. All studies used timing techniques to explore nurse work associated with the transfer process. The review highlights the duration of time spent by nurses on certain aspects of the transfer process. However, as few studies published results from timings, the impact on nurse time is likely to be higher than indicated. Further research is recommended. PMID:24689656

  9. A systematic review of time studies to assess the impact of patient transfers on nurse workload.

    PubMed

    Blay, Nicole; Duffield, Christine M; Gallagher, Robyn; Roche, Michael

    2014-12-01

    Patients in hospital are increasingly being moved between clinical units and between bedspaces; however, the impact of patient transfers and bedspace moves on nurses' workload is not known. Time studies are an established observational research method that can be used to determine the duration of time taken to perform an activity or process. This review systematically searched four databases for literature published between 2000 and 2013 for observational time study techniques and patient transfers as a nurse activity. Eleven publications from three countries were included in the review. All studies used timing techniques to explore nurse work associated with the transfer process. The review highlights the duration of time spent by nurses on certain aspects of the transfer process. However, as few studies published results from timings, the impact on nurse time is likely to be higher than indicated. Further research is recommended.

  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. Predicting success on the National Council Licensure Examination-Registered Nurse: another piece of the puzzle.

    PubMed

    Foti, I; DeYoung, S

    1991-01-01

    A retrospective correlational study was conducted at a state-supported bachelor's degree nursing program to determine variables that predict success on the National Council Licensure Examination-Registered Nurse (NCLEX-RN). Data were collected from 1985 through 1988 on a sample of 298 students. The independent variables studied were: grade point average (GPA) overall, GPA in the major, GPA in science, Scholastic Aptitude Test (SAT) verbal and quantitative scores, National League for Nursing (NLN) Comprehensive Baccalaureate Achievement Test scores, and Mosby Assess Test scores. The outcome variable was the NCLEX-RN. Pearson correlations indicated the Mosby Assess Test, overall GPA and GPA in the major, NLN Achievement Test, and SAT verbal to be of moderate predictive value. Multiple regression analysis indicated that the most useful combination of predictors was the Mosby Assess Test, SAT verbal, and overall GPA. The results support the value of a program at this school designed to increase students' verbal abilities.

  12. 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.

  13. 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…

  14. 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…

  15. 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.

  16. A time-motion study of registered nurses' workflow in intensive care unit remote monitoring.

    PubMed

    Tang, Zhihua; Mazabob, Janine; Weavind, Liza; Thomas, Eric; Johnson, Todd R

    2006-01-01

    Utilizing advanced information technology, Intensive Care Unit (ICU) remote monitoring allows highly trained specialists to oversee a large number of patients at multiple sites on a continuous basis. In the current research, we conducted a time-motion study of registered nurses' work in an ICU remote monitoring facility. Data were collected on seven nurses through 40 hours of observation. The results showed that nurses' essential tasks were centered on three themes: monitoring patients, maintaining patients' health records, and managing technology use. In monitoring patients, nurses spent 52% of the time assimilating information embedded in a clinical information system and 15% on monitoring live vitals. System-generated alerts frequently interrupted nurses in their task performance and redirected them to manage suddenly appearing events. These findings provide insight into nurses' workflow in a new, technology-driven critical care setting and have important implications for system design, work engineering, and personnel selection and training.

  17. Interprofessional communication between surgery trainees and nurses in the inpatient wards: Why time and space matter.

    PubMed

    Fernando, Oshan; Coburn, Natalie G; Nathens, Avery B; Hallet, Julie; Ahmed, Najma; Conn, Lesley Gotlib

    2016-09-01

    Optimal interprofessional communication (IPC) is broadly viewed as a prerequisite to providing quality patient care. In this study, we explored the enablers and barriers to IPC between surgical trainees and ward nurses with a view towards improving IPC and the quality of surgical patient care. We conducted an ethnography in two academic centres in Canada totalling 126 hours of observations and 32 semi-structured interviews with trainees and nurses. Our findings revealed constraints on IPC between trainees and nurses derived from contested meanings of space and time. Trainees experienced the contested spatial boundaries of the surgical ward when they perceived nurses to project a sense of territoriality. Nurses expressed difficulty getting trainees to respond and attend to pages from the ward, and to have a poor understanding of the nurses' role. Contestations over time spent in training and patient care were found in trainee-nurse interactions, wherein trainees perceived seasoned nurses to devalue their clinical knowledge on the ward. Nurses viewed the limited time that trainees spent in clinical rotation in the ward as adversely affecting communication. This study underscores that challenges to enhancing IPC at academic health centres are rooted in team and professional cultures. Efforts to improve IPC should therefore: identify and target the social and cultural dimensions of healthcare team member relations; recognise how power is deployed and experienced in ways that negatively impact IPC; and enhance an understanding and appreciation in the temporal and spatial dimensions of IPC.

  18. 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.

  19. 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

  20. 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…

  1. 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…

  2. 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.

  3. 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

  4. In visible bodies: minority women, nurses, time, and the new economy of care.

    PubMed

    Spitzer, Denise L

    2004-12-01

    Health care reform in Canadian hospitals has resulted in increased workloads and bureaucratization of patient care contributing to the development of a new economy of care. Interviews with nurses and visible (non-white) minority women who have given birth in institutions undergoing health care reform revealed that nurses felt compelled to avoid interactions with patients deemed too costly in terms of time. Overwhelmingly, these patients were members of culturally marginalized populations whose bodies were read by nurses as potentially problematic and time consuming. As their calls for assistance go unanswered, visible minority women complained of feeling invisible. Taken in context of historical and contemporary interethnic relations, these women regarded such avoidance patterns as evidence of racism. Obstetrical nurses, too, understood that the new economy of care wrought by health care restructuring has altered nursing practice and patient care to the detriment of minority women.

  5. 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…

  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. Nursing intuition as an assessment tool in predicting severity of injury in trauma patients.

    PubMed

    Cork, Lora L

    2014-01-01

    Emergency nurses assess patients using objective and subjective data. When the charge nurse takes report from a paramedic, another form of assessment occurs. By eliciting apt data and using trauma-scoring criteria, a decision to enact a "trauma code" occurs. Considering the cost and staff utilization, it is important for the charge nurse to make sound decisions when activating a trauma code. The objective of this study is to explore the validity of nurses' use of intuition in patients to predict the severity of their injuries, and whether it impacts their choice to institute a trauma code.The study design was a descriptive, quantitative, cross-sectional record review and cohort analysis. The setting was a rural Trauma Level III emergency department (ED) located 80 miles from the nearest Level I trauma center. Phase I was a convenience cluster sample of all charge nurses in an ED. Phase II was a collection of all trauma records from June 2010 to May 2012. The inclusion criterion for Phase I subjects was that all participants were currently working as ED charge nurses. Analysis for Phase I data consisted of evaluating demographic information provided in questions 1 through 6 in a questionnaire. For Phase II data, a power analysis using Cohen's d was performed to determine the sample size to be evaluated. On the basis of the 2012 trauma data, a total of 419 records needed to be assessed (confidence interval, 0.164; P < .286). Two groups were created: (1) gut instinct only, and (2) all other criteria. Injury severity scores were categorized by ascending severity: (1) 0 to 4, (2) 5 to 9, (3) 10 to 16, (4) 17 to 24, and (5) greater than 25. The data analysis consisted of a 2-tailed t test for probability and a linear regression analysis using Pearson's r for correlation. In Phase I, 6 of the 8 charge nurses responded. Results showed an average of greater than 10 years of experience as an ED registered nurse, certification was equally yes and no, and highest level of

  8. War time experiences of triage and resuscitation: Australian Army nurses in the Vietnam War, 1967-1971.

    PubMed

    Biedermann, N E; Harvey, N R

    2001-07-01

    The experiences of nurses in war is prolifically described in the North American scholarly literature, and in the Australian nursing literature to a lesser extent. The literature describes the plights and achievements of nurses caring for soldiers and civilians often under the most undesirable of circumstances. A central focus of war time nursing is the resuscitation of critically wounded soldiers. This paper addresses the experiences of the Australian Army nurses who were involved in the triage and resuscitation of critically wounded allied and enemy soldiers in the Vietnam War between 1967 and 1971. As part of a research study to explore and analyse the nature of nursing work in the Vietnam War, seventeen Vietnam veteran nurses were interviewed about their experiences. This paper explores the progression of the triage department in the Australian military hospital in Vung Tau, and it highlights that the majority of the nurses who took part in this study were clinically unprepared, particularly as emergency nurses.

  9. 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…

  10. 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)

  11. Hardiness, stress, and use of ill-time among nurse managers: is there a connection?

    PubMed

    Judkins, Sharon; Massey, Christy; Huff, Burlean

    2006-01-01

    Intense job-related demands often result in effects on job performance and increased use of ill-time. In this study, associations between hardiness, stress, and use of ill-time among nurse managers were examined. High-hardy/low-stress managers used 27% less ill-time than those low-hardy/high-stressed. PMID:16967889

  12. Effect of Full-Time versus Part-Time School Nurses on Attendance of Elementary Students with Asthma

    ERIC Educational Resources Information Center

    Telljohann, Susan K.; Dake, Joseph A.; Price, James H.

    2004-01-01

    Asthma, the most common chronic disease in children today, is the leading cause of absenteeism among students. It accounts for nearly 20 million lost school days annually. This study examined whether full-time (5 days per week) or part-time (2 days per week) school nurses would have a differential effect on the frequency of absences among…

  13. Nurses and doctors in prime time series: the dynamics of depicting professional power.

    PubMed

    Turow, Joseph

    2012-01-01

    This essay sketches a comparison of 1960s' television portrayals with those of the present to show that a limited and incomplete portrayal of nurses has been an enduring feature of prime-time medical television programs. They have depicted physicians then and now as captains of the medical ship and nurses then and now their ancillary and ill-defined helpers. As the comparison makes clear, part of nurses' lack of clear power in TV medical scenarios has to do with the explicit and implicit clout exercised by physicians' organizations to present doctor images effectively. That clout contrasts with nursing organizations' lack of attempts or ability (it's hard to gauge which) to influence network television's most prominent representations of their roles and the environments in which they work. PMID:23036794

  14. Nurses and doctors in prime time series: the dynamics of depicting professional power.

    PubMed

    Turow, Joseph

    2012-01-01

    This essay sketches a comparison of 1960s' television portrayals with those of the present to show that a limited and incomplete portrayal of nurses has been an enduring feature of prime-time medical television programs. They have depicted physicians then and now as captains of the medical ship and nurses then and now their ancillary and ill-defined helpers. As the comparison makes clear, part of nurses' lack of clear power in TV medical scenarios has to do with the explicit and implicit clout exercised by physicians' organizations to present doctor images effectively. That clout contrasts with nursing organizations' lack of attempts or ability (it's hard to gauge which) to influence network television's most prominent representations of their roles and the environments in which they work.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. Impact of learning adaptability and time management disposition on study engagement among Chinese baccalaureate nursing students.

    PubMed

    Liu, Jing-Ying; Liu, Yan-Hui; Yang, Ji-Peng

    2014-01-01

    The aim of this study was to explore the relationships among study engagement, learning adaptability, and time management disposition in a sample of Chinese baccalaureate nursing students. A convenient sample of 467 baccalaureate nursing students was surveyed in two universities in Tianjin, China. Students completed a questionnaire that included their demographic information, Chinese Utrecht Work Engagement Scale-Student Questionnaire, Learning Adaptability Scale, and Adolescence Time Management Disposition Scale. One-way analysis of variance tests were used to assess the relationship between certain characteristics of baccalaureate nursing students. Pearson correlation was performed to test the correlation among study engagement, learning adaptability, and time management disposition. Hierarchical linear regression analyses were performed to explore the mediating role of time management disposition. The results revealed that study engagement (F = 7.20, P < .01) and learning adaptability (F = 4.41, P < .01) differed across grade groups. Learning adaptability (r = 0.382, P < .01) and time management disposition (r = 0.741, P < .01) were positively related with study engagement. Time management disposition had a partially mediating effect on the relationship between study engagement and learning adaptability. The findings implicate that educators should not only promote interventions to increase engagement of baccalaureate nursing students but also focus on development, investment in adaptability, and time management.

  20. "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.

  1. 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

  2. Time, Not Size, Matters for Striatal Reward Predictions to Dopamine.

    PubMed

    Burke, Christopher J; Tobler, Philippe N

    2016-07-01

    Midbrain dopamine neurons encode reward prediction errors. In this issue of Neuron, Takahashi et al. (2016) show that the ventral striatum provides dopamine neurons with prediction information specific to the timing, but not the quantity, of reward, suggesting a surprisingly nuanced neural implementation of reward prediction errors. PMID:27387646

  3. 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

  4. 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

  5. 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

  6. 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.

  7. Individualized Course Completion Time Predictions: Development of Instruments and Techniques.

    ERIC Educational Resources Information Center

    Wagner, Harold; And Others

    Research was undertaken to develop a system for predicting completion time in a self-paced training course. The hypotheses were developed that: 1) course content-related instruments would be better predictors of completion time than general aptitude measures; and that 2) a linear predictive function would provide the best description of the…

  8. 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.

  9. Predictability of a Professional Practice Model to Affect Nurse and Patient Outcomes.

    PubMed

    Stallings-Welden, Lois M; Shirey, Maria R

    2015-01-01

    Thousands of patients experience needless deaths and injuries as a result of errors while hospitalized for an unrelated problem. The lack of an established professional practice model (PPM) of nursing may be a contributing factor to patient care quality and safety breaches. The PPM of nursing was tested for its ability to affect nurse and patient outcomes. Using a retrospective/prospective research design, secondary data were collected from 2395 staff nurses on 15 inpatient-nursing units covering a 6-year timeframe. Data were analyzed using ANOVA and the Pearson correlation. Nurse and patient outcomes on 2 hospital campuses reached statistical significance. Positive correlations were seen between the initiation of a PPM and subsequent nurses' perception of quality of care, nurse interactions, decision making, autonomy, job enjoyment, and patient satisfaction. This study provides empirical evidence that a uniquely designed PPM in alignment with organizational context can indeed impact nurse and patient outcomes in a community health system. PMID:26049597

  10. The Art versus Science of Predicting Prognosis: Can a Prognostic Index Predict Short-Term Mortality Better than Experienced Nurses Do?

    PubMed Central

    Farrington, Sue; Craig, Teresa; Slattery, Julie; Harrold, Joan; Oldanie, Betty; Roy, Jason; Biehl, Richard; Teno, Joan

    2012-01-01

    Abstract Objective To determine whether a prognostic index could predict one-week mortality more accurately than hospice nurses can. Method An electronic health record-based retrospective cohort study of 21,074 hospice patients was conducted in three hospice programs in the Southeast, Northeast, and Midwest United States. Model development used logistic regression with bootstrapped confidence intervals and multiple imputation to account for missing data. The main outcome measure was mortality within 7 days of hospice enrollment. Results A total of 21,074 patients were admitted to hospice between October 1, 2008 and May 31, 2011, and 5562 (26.4%) died within 7 days. An optimal predictive model included the Palliative Performance Scale (PPS) score, admission from a hospital, and gender. The model had a c-statistic of 0.86 in the training sample and 0.84 in the validation sample, which was greater than that of nurses' predictions (0.72). The index's performance was best for patients with pulmonary disease (0.89) and worst for patients with cancer and dementia (both 0.80). The index's predictions of mortality rates in each index category were within 5.0% of actual rates, whereas nurses underestimated mortality by up to 18.9%. Using the optimal index threshold (<3), the index's predictions had a better c-statistic (0.78 versus 0.72) and higher sensitivity (74.4% versus 47.8%) than did nurses' predictions but a lower specificity (80.6% versus 95.1%). Conclusions Although nurses can often identify patients who will die within 7 days, a simple model based on available clinical information offers improved accuracy and could help to identify those patients who are at high risk for short-term mortality. PMID:22583382

  11. 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.

  12. 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

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. 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

  18. Characterizing Complex Time Series from the Scaling of Prediction Error.

    NASA Astrophysics Data System (ADS)

    Hinrichs, Brant Eric

    This thesis concerns characterizing complex time series from the scaling of prediction error. We use the global modeling technique of radial basis function approximation to build models from a state-space reconstruction of a time series that otherwise appears complicated or random (i.e. aperiodic, irregular). Prediction error as a function of prediction horizon is obtained from the model using the direct method. The relationship between the underlying dynamics of the time series and the logarithmic scaling of prediction error as a function of prediction horizon is investigated. We use this relationship to characterize the dynamics of both a model chaotic system and physical data from the optic tectum of an attentive pigeon exhibiting the important phenomena of nonstationary neuronal oscillations in response to visual stimuli.

  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. 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

  1. Model-free quantification of time-series predictability

    NASA Astrophysics Data System (ADS)

    Garland, Joshua; James, Ryan; Bradley, Elizabeth

    2014-11-01

    This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data, which results from the dimension, nonlinearity, and nonstationarity of the generating process, as well as from measurement issues such as noise, aggregation, and finite data length, is both empirically quantifiable and directly correlated with predictability. In particular, we argue that redundancy is an effective way to measure complexity and predictive structure in an experimental time series and that weighted permutation entropy is an effective way to estimate that redundancy. To validate these conjectures, we study 120 different time-series data sets. For each time series, we construct predictions using a wide variety of forecast models, then compare the accuracy of the predictions with the permutation entropy of that time series. We use the results to develop a model-free heuristic that can help practitioners recognize when a particular prediction method is not well matched to the task at hand: that is, when the time series has more predictive structure than that method can capture and exploit.

  2. Model-free quantification of time-series predictability.

    PubMed

    Garland, Joshua; James, Ryan; Bradley, Elizabeth

    2014-11-01

    This paper provides insight into when, why, and how forecast strategies fail when they are applied to complicated time series. We conjecture that the inherent complexity of real-world time-series data, which results from the dimension, nonlinearity, and nonstationarity of the generating process, as well as from measurement issues such as noise, aggregation, and finite data length, is both empirically quantifiable and directly correlated with predictability. In particular, we argue that redundancy is an effective way to measure complexity and predictive structure in an experimental time series and that weighted permutation entropy is an effective way to estimate that redundancy. To validate these conjectures, we study 120 different time-series data sets. For each time series, we construct predictions using a wide variety of forecast models, then compare the accuracy of the predictions with the permutation entropy of that time series. We use the results to develop a model-free heuristic that can help practitioners recognize when a particular prediction method is not well matched to the task at hand: that is, when the time series has more predictive structure than that method can capture and exploit.

  3. 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…

  4. [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

  5. 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…

  6. Decreasing Interferences and Time Spent on Transferring Information on Changing Nursing Shifts.

    PubMed

    Sans Torres, Elisenda; Albaladejo, Jessica Rubio; Benítez, Manuela

    2016-01-01

    The exchange of clinical information on patients is a common component in nursing shift changes where professionals have limited time to transfer this information. There is no standardized or structured methodology for transferring information, which requires increased time to complete. Also, during the exchange, some interruptions can disrupt the communication among professionals, which can affect the patient's safety. A descriptive study was developed for five months, the information transfer arrangement among nurses was changed in order to determine which interruption increased the time spent on shift change and, therefore, decreased the safety of pediatric patients. The results obtained on the type of interruption caused us to rethink the organization that includes pediatric patient care.

  7. 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.

  8. 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

  9. Transformation by design: nursing workforce innovation and reduction strategies in turbulent times of change.

    PubMed

    Palazzo, Mary O

    2015-01-01

    The evolution of care delivery from an acute care and inpatient standard to the outpatient setting and health promotion model is generating the need for innovative workforce and infrastructure adjustments to meet the new paradigm of population health management. Successful transformation of the nursing workforce necessitates a positive style of thinking that addresses rational concerns during times of difficult transition. Nurse leaders are called to recognize and appreciate the strengths of the nursing workforce by involving them in the course of change through collaboration, planning, and discussion. One unique way to plan and develop new care delivery models is to adopt the framework used in health facility planning and design for new services, units, or hospitals. This framework is flexible and can be adjusted easily to meet the objectives of a small nursing workforce innovation project or expanded to encompass the needs of a large-scale hospital transformation. Structured questioning further helps the team to identify barriers to care and allows for the development of new concepts that are objective and in accord with evidence-based practice and data. This article explores the advantages and disadvantages of implementing innovative workforce redesign and workforce reduction strategies.

  10. Transformation by design: nursing workforce innovation and reduction strategies in turbulent times of change.

    PubMed

    Palazzo, Mary O

    2015-01-01

    The evolution of care delivery from an acute care and inpatient standard to the outpatient setting and health promotion model is generating the need for innovative workforce and infrastructure adjustments to meet the new paradigm of population health management. Successful transformation of the nursing workforce necessitates a positive style of thinking that addresses rational concerns during times of difficult transition. Nurse leaders are called to recognize and appreciate the strengths of the nursing workforce by involving them in the course of change through collaboration, planning, and discussion. One unique way to plan and develop new care delivery models is to adopt the framework used in health facility planning and design for new services, units, or hospitals. This framework is flexible and can be adjusted easily to meet the objectives of a small nursing workforce innovation project or expanded to encompass the needs of a large-scale hospital transformation. Structured questioning further helps the team to identify barriers to care and allows for the development of new concepts that are objective and in accord with evidence-based practice and data. This article explores the advantages and disadvantages of implementing innovative workforce redesign and workforce reduction strategies. PMID:25714955

  11. 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.

  12. 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.

  13. The Prediction of Teacher Turnover Employing Time Series Analysis.

    ERIC Educational Resources Information Center

    Costa, Crist H.

    The purpose of this study was to combine knowledge of teacher demographic data with time-series forecasting methods to predict teacher turnover. Moving averages and exponential smoothing were used to forecast discrete time series. The study used data collected from the 22 largest school districts in Iowa, designated as FACT schools. Predictions…

  14. 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.

  15. 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

  16. 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

  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. 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

  19. 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

  20. The phantom robot - Predictive displays for teleoperation with time delay

    NASA Technical Reports Server (NTRS)

    Bejczy, Antal K.; Kim, Won S.; Venema, Steven C.

    1990-01-01

    An enhanced teleoperation technique for time-delayed bilateral teleoperator control is discussed. The control technique selected for time delay is based on the use of a high-fidelity graphics phantom robot that is being controlled in real time (without time delay) against the static task image. Thus, the motion of the phantom robot image on the monitor predicts the motion of the real robot. The real robot's motion will follow the phantom robot's motion on the monitor with the communication time delay implied in the task. Real-time high-fidelity graphics simulation of a PUMA arm is generated and overlaid on the actual camera view of the arm. A simple camera calibration technique is used for calibrated graphics overlay. A preliminary experiment is performed with the predictive display by using a very simple tapping task. The results with this simple task indicate that predictive display enhances the human operator's telemanipulation task performance significantly during free motion when there is a long time delay. It appears, however, that either two-view or stereoscopic predictive displays are necessary for general three-dimensional tasks.

  1. Predicting the timing of dynamic events through sound: Bouncing balls.

    PubMed

    Gygi, Brian; Giordano, Bruno L; Shafiro, Valeriy; Kharkhurin, Anatoliy; Zhang, Peter Xinya

    2015-07-01

    Dynamic information in acoustical signals produced by bouncing objects is often used by listeners to predict the objects' future behavior (e.g., hitting a ball). This study examined factors that affect the accuracy of motor responses to sounds of real-world dynamic events. In experiment 1, listeners heard 2-5 bounces from a tennis ball, ping-pong, basketball, or wiffle ball, and would tap to indicate the time of the next bounce in a series. Across ball types and number of bounces, listeners were extremely accurate in predicting the correct bounce time (CT) with a mean prediction error of only 2.58% of the CT. Prediction based on a physical model of bouncing events indicated that listeners relied primarily on temporal cues when estimating the timing of the next bounce, and to a lesser extent on the loudness and spectral cues. In experiment 2, the timing of each bounce pattern was altered to correspond to the bounce timing pattern of another ball, producing stimuli with contradictory acoustic cues. Nevertheless, listeners remained highly accurate in their estimates of bounce timing. This suggests that listeners can adopt their estimates of bouncing-object timing based on acoustic cues that provide most veridical information about dynamic aspects of object behavior.

  2. Predicting travel time to limit congestion at a highway bottleneck

    NASA Astrophysics Data System (ADS)

    Davis, L. C.

    2010-09-01

    A new method is proposed to predict the travel time on a highway route with a bottleneck caused by an on-ramp. The method takes advantage of the slow variation of the bottleneck throughput when congestion exists. The predicted travel time for a vehicle leaving the origin is given by the current number of vehicles on the route divided by the estimated throughput. The latter is an average of N/T recorded as each vehicle reaches the destination where N is the number of vehicles at the start of the trip and T is the time to complete the trip. Drivers divert to an off-ramp when the predicted travel time exceeds a target value. The target could be historical average travel times of alternative routes or chosen to limit the amount of congestion. Simulations employing three-phase traffic theory show that the travel time converges to the target value and remains close to or below it with the proposed prediction strategy. Strong oscillations in travel time obtained when other strategies are used for diversion do not develop with the new method because the inherent delay is effectively removed.

  3. Predicting the timing of dynamic events through sound: Bouncing balls.

    PubMed

    Gygi, Brian; Giordano, Bruno L; Shafiro, Valeriy; Kharkhurin, Anatoliy; Zhang, Peter Xinya

    2015-07-01

    Dynamic information in acoustical signals produced by bouncing objects is often used by listeners to predict the objects' future behavior (e.g., hitting a ball). This study examined factors that affect the accuracy of motor responses to sounds of real-world dynamic events. In experiment 1, listeners heard 2-5 bounces from a tennis ball, ping-pong, basketball, or wiffle ball, and would tap to indicate the time of the next bounce in a series. Across ball types and number of bounces, listeners were extremely accurate in predicting the correct bounce time (CT) with a mean prediction error of only 2.58% of the CT. Prediction based on a physical model of bouncing events indicated that listeners relied primarily on temporal cues when estimating the timing of the next bounce, and to a lesser extent on the loudness and spectral cues. In experiment 2, the timing of each bounce pattern was altered to correspond to the bounce timing pattern of another ball, producing stimuli with contradictory acoustic cues. Nevertheless, listeners remained highly accurate in their estimates of bounce timing. This suggests that listeners can adopt their estimates of bouncing-object timing based on acoustic cues that provide most veridical information about dynamic aspects of object behavior. PMID:26233044

  4. 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.

  5. Time Series Analysis and Prediction of AE and Dst Data

    NASA Astrophysics Data System (ADS)

    Takalo, J.; Lohikiski, R.; Timonen, J.; Lehtokangas, M.; Kaski, K.

    1996-12-01

    A new method to analyse the structure function has been constructed and used in the analysis of the AE time series for the years 1978-85 and Dst time series for 1957-84. The structure function (SF) was defined by S(l) = <|x(ti + lDt) - x(ti)|>, where Dt is the sampling time, l is an integer, and <|.|> denotes the average of absolute values. If a time series is self-affine its SF should scale for small values of l as S(l) is proportional to lH, where 0 < H < 1 is called the scaling exponent. It is known that for power-law (coloured) noise, which has P ~ f-a, a ~ 2H + 1 for 1 < a < 3. In this work the scaling exponent H was analysed by considering the local slopes dlog(S(l))/dlog(l) between two adjacent points as a function of l. For self-affine time series the local slopes should stay constant, at least for small values of l. The AE time series was found to be affine such that the scaling exponent changes at a time scale of 113 (+/-9) minutes. On the other hand, in the SF function analysis, the Dst data were dominated by the 24-hour and 27-day periods. The 27-day period was further modulated by the annual variation. These differences between the two time series arise from the difference in their periodicities in relation to their respective characteristic time scales. In the AE data the dominating periods are longer than that related to the characteristic time scale, i.e. they appear in the flatter part of the power spectrum. This is why the affinity is the dominating feature of the AE time series. In contrast with this the dominating periods of the Dst data are shorter than the characteristic time scale, and appear in the steeper part of the spectrum. Consequently periodicity is the dominating feature of the Dst data. Because of their different dynamic characteristics, prediction of Dst and AE time series appear to presuppose rather different approaches. In principle it is easier to produce the gross features of the Dst time series correctly as it is periodicity

  6. 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.

  7. 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

  8. 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

  9. 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

  10. 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).

  11. Predictable Components of ENSO Evolution in Real-time Multi-Model Predictions

    PubMed Central

    Zheng, Zhihai; Hu, Zeng-Zhen; L’Heureux, Michelle

    2016-01-01

    The most predictable components of the El Niño-Southern Oscillation (ENSO) evolution in real-time multi-model predictions are identified by applying an empirical orthogonal function analysis of the model data that maximizes the signal-to-noise ratio (MSN EOF). The normalized Niño3.4 index is analyzed for nine 3-month overlapping seasons. In this sense, the first most predictable component (MSN EOF1) is the decaying phase of ENSO during the Northern Hemisphere spring, followed by persistence through autumn and winter. The second most predictable component of ENSO evolution, with lower prediction skill and smaller explained variance than MSN EOF1, corresponds to the growth during spring and then persistence in summer and autumn. This result suggests that decay phase of ENSO is more predictable than the growth phase. Also, the most predictable components and the forecast skills in dynamical and statistical models are similar overall, with some differences arising during spring season initial conditions. Finally, the reconstructed predictions, with only the first two MSN components, show higher skill than the model raw predictions. Therefore this method can be used as a diagnostic for model comparison and development, and it can provide a new perspective for the most predictable components of ENSO. PMID:27775016

  12. 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…

  13. 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…

  14. 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…

  15. 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…

  16. Predicting Graduation Status of Nursing Students Using Entering GPA and Grades in Algebra, Biology, and Chemistry.

    ERIC Educational Resources Information Center

    Spahr, Anthony E.

    A study was undertaken at Morton College, in Illinois, to examine the relationship of entering grade point average (GPA) and grades in prerequisite support courses in algebra, biology, and chemistry to graduation in the college's nursing program. A sample was developed of 255 students admitted to the nursing program in 1990, 1991, and 1992 and…

  17. 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

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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

  6. Nursing a case of the blues: an examination of the role of depression in predicting job-related affective well-being in nurses.

    PubMed

    Morrissy, Laura; Boman, Peter; Mergler, Amanda

    2013-03-01

    The current study explored the effect of depression, optimism, and anxiety on job-related affective well-being in 70 graduate nurses. It was predicted that depression and anxiety would have a significant negative effect on job-related affective well-being, whereas optimism would have a significant positive effect on job-related affective well-being. Questionnaires were completed online or in hard-copy forms. Results revealed that depression, optimism, and anxiety were all significantly correlated to job-related affective well-being in the expected direction, however, depression was found to be the only variable that made a significant unique contribution to the prediction of job-related affective well-being. Possible explanations for these findings are explored.

  7. A study of predictability of SST at different time scales based on satellite time

    NASA Astrophysics Data System (ADS)

    Ding, Youzhuan; Fu, Dongyang; Wei, Zhihui; He, Xianqiang; Huang, Haiqing; Pan, Delu

    2008-12-01

    Sea surface temperature (SST) is both an important variable for weather and ocean forecasting, but also a key indicator of climate change. Predicting future SST at different time scales constitutes an important scientific problem. The traditional approach to prediction is achieved through numerical simulation, but it is difficult to obtain a detailed knowledge of ocean initial conditions and forcing. This paper proposes a improved prediction system based on SOFT proposed by Alvarez et al and studies the predictability of SST at different time scales, i.e., 5 day, 10 day, 15 day, 20 day and month ahead. This method is used to forecast the SST in the Yangtze River estuary and its adjacent areas. The period of time ranging from Jan 1st 2000 to Dec 31st 2005 is employed to build the prediction system and the period of time ranging from Jan 1st 2006 to Dec 31st 2007 is employed to validate the performance of this prediction system. Results indicate: The prediction errors of 5 day,10 day,15 day, 20 day and monthly ahead are 0.78°C,0.86°C,0.90°C,1.00°C and 1.45°C respectively. The longer of time scales prediction, the worse of prediction capability. Compared with the SOFT system proposed by Alvarez et al, the improved prediction system is more robust. Merging more satellite data and trying to better reflect the real state of ocean variables, we can greatly improve the predictive precision of long time scale.

  8. Regional Travel-Time Predictions, Uncertainty and Location Improvement

    SciTech Connect

    Flanagan, M; Myers, S

    2004-07-15

    We investigate our ability to improve regional travel-time prediction and seismic event location using an a priori three-dimensional (3D) velocity model of Western Eurasia and North Africa (WENA 1.0). Three principal results are presented. First, the 3D WENA 1.0 velocity model improves travel-time prediction over the IASPI91 model, as measured by variance reduction, for regional phases recorded at 22 stations throughout the modeled region, including aseismic areas. Second, a distance-dependent uncertainty model is developed and tested for the WENA 1.0 model. Third, relocation using WENA 1.0 and the associated uncertainty model provides an end-to-end validation test. Model validation is based on a comparison of approximately 10,000 Pg, Pn, and P travel-time predictions and empirical observations from ground truth (GT) events. Ray coverage for the validation dataset provides representative, regional-distances sampling across Eurasia and North Africa. The WENA 1.0 model markedly improves travel-time predictions for most stations with an average variance reduction of 14% for all ray paths. We find that improvement is station dependent, with some stations benefiting greatly from WENA predictions (25% at OBN, and 16% at BKR), some stations showing moderate improvement (12% at ARU, and 17% at NIL), and some stations benefiting only slightly (7% at AAE, and 8% at TOL). We further test WENA 1.0 by relocating five calibration events. Again, relocation of these events is dependent on ray paths that evenly sample WENA 1.0 and therefore provide an unbiased assessment of location performance. These results highlight the importance of accurate GT datasets in assessing regional travel-time models and demonstrate that an a priori 3D model can markedly improve our ability to locate small magnitude events in a regional monitoring context.

  9. 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

  10. 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

  11. Individual differences in time perspective predict autonoetic experience.

    PubMed

    Arnold, Kathleen M; McDermott, Kathleen B; Szpunar, Karl K

    2011-09-01

    Tulving (1985) posited that the capacity to remember is one facet of a more general capacity-autonoetic (self-knowing) consciousness. Autonoetic consciousness was proposed to underlie the ability for "mental time travel" both into the past (remembering) and into the future to envision potential future episodes (episodic future thinking). The current study examines whether individual differences can predict autonoetic experience. Specifically, the Zimbardo Time Perspective Inventory (ZTPI, Zimbardo & Boyd, 1999) was administered to 133 undergraduate students, who also rated phenomenological experiences accompanying autobiographical remembering and episodic future thinking. Scores on two of the five subscales of the ZTPI (Future and Present-Hedonistic) predicted the degree to which people reported feelings of mentally traveling backward (or forward) in time and the degree to which they reported re- or pre-experiencing the event, but not ten other rated properties less related to autonoetic consciousness.

  12. Insufflation using carbon dioxide versus room air during colonoscopy: comparison of patient comfort, recovery time, and nursing resources.

    PubMed

    Lynch, Isabelle; Hayes, Ann; Buffum, Martha D; Conners, Erin E

    2015-01-01

    The standard of practice for colonoscopy is room air insufflation. Recent research demonstrates safety and significant decrease in postcolonoscopy discomfort from distention when carbon dioxide (CO2) is used during insufflation. Reducing abdominal pain after colonoscopy may lead to increased acceptance of colonoscopy screening for colorectal cancer. This study aims to compare patient comfort intra- and postprocedure, length of recovery, and nursing time in patients undergoing colonoscopy using room air vs. CO2 insufflation. This study uses an experimental design with patients randomly assigned to either room air or CO2 during colonoscopy. Physician endoscopists, postprocedure nurses, and patients were blinded to assignment. Prior bowel surgery, inflammatory bowel disease, or inability to consent excluded participants. Outcome measures included discomfort assessment, nursing tasks, and recovery time.Of 191 participants, 177 were men and 14 were women; 94 received room air; 97 received CO2. Patients insufflated with room air reported higher levels of some measures of discomfort: (a) during colonoscopy (p = .02), (b) on admission to recovery (p = .001), and (c) on discharge from recovery (p = .001). Patients receiving room air required more nursing tasks in recovery (p = .001) and more total nursing time (p = .001).Compared with room air, CO2 insufflation increases patient comfort and decreases nursing tasks and time.

  13. 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

  14. Results of a national survey indicating information technology skills needed by nurses at time of entry into the work force.

    PubMed

    McCannon, Melinda; O'Neal, Pamela V

    2003-08-01

    A national survey was conducted to determine the information technology skills nurse administrators consider critical for new nurses entering the work force. The sample consisted of 2,000 randomly selected members of the American Organization of Nurse Executives. Seven hundred fifty-two usable questionnaires were returned, for a response rate of 38%. The questionnaire used a 5-point Likert scale and consisted of 17 items that assessed various technology skills and demographic information. The questionnaire was developed and pilot tested with content experts to establish content validity. Descriptive analysis of the data revealed that using e-mail effectively, operating basic Windows applications, and searching databases were critical information technology skills. The most critical information technology skill involved knowing nursing-specific software, such as bedside charting and computer-activated medication dispensers. To effectively prepare nursing students with technology skills needed at the time of entry into practice, nursing faculty need to incorporate information technology skills into undergraduate nursing curricula. PMID:12938895

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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

  20. 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.

  1. Earthquake prediction in Japan and natural time analysis of seismicity

    NASA Astrophysics Data System (ADS)

    Uyeda, S.; Varotsos, P.

    2011-12-01

    M9 super-giant earthquake with huge tsunami devastated East Japan on 11 March, causing more than 20,000 casualties and serious damage of Fukushima nuclear plant. This earthquake was predicted neither short-term nor long-term. Seismologists were shocked because it was not even considered possible to happen at the East Japan subduction zone. However, it was not the only un-predicted earthquake. In fact, throughout several decades of the National Earthquake Prediction Project, not even a single earthquake was predicted. In reality, practically no effective research has been conducted for the most important short-term prediction. This happened because the Japanese National Project was devoted for construction of elaborate seismic networks, which was not the best way for short-term prediction. After the Kobe disaster, in order to parry the mounting criticism on their no success history, they defiantly changed their policy to "stop aiming at short-term prediction because it is impossible and concentrate resources on fundamental research", that meant to obtain "more funding for no prediction research". The public were and are not informed about this change. Obviously earthquake prediction would be possible only when reliable precursory phenomena are caught and we have insisted this would be done most likely through non-seismic means such as geochemical/hydrological and electromagnetic monitoring. Admittedly, the lack of convincing precursors for the M9 super-giant earthquake has adverse effect for us, although its epicenter was far out off shore of the range of operating monitoring systems. In this presentation, we show a new possibility of finding remarkable precursory signals, ironically, from ordinary seismological catalogs. In the frame of the new time domain termed natural time, an order parameter of seismicity, κ1, has been introduced. This is the variance of natural time kai weighted by normalised energy release at χ. In the case that Seismic Electric Signals

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

    PubMed Central

    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

  3. 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.

  4. 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.

  5. Yesterday, Today, & Tomorrow: Transitioning through Time with the Cleveland Council of Black Nurses.

    ERIC Educational Resources Information Center

    George, Valerie D.; Bradford, Dorothy M.; Battle, Alice

    2000-01-01

    Presents the history of the Cleveland Council of Black Nurses, formed in 1972 after the dissolution of the National Association of Colored Graduate Nurses. Discusses struggles with discrimination in education and employment and the current challenges of recruiting and retaining African-American nurses. (Contains 51 references.) (SK)

  6. 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…

  7. 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

  8. 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.

  9. Predicting clinical image delivery time by monitoring PACS queue behavior.

    PubMed

    King, Nelson E; Documet, Jorge; Liu, Brent

    2006-01-01

    The expectation of rapid image retrieval from PACS users contributes to increased information technology (IT) infrastructure investments to increase performance as well as continuing demands upon PACS administrators to respond to "slow" system performance. The ability to provide predicted delivery times to a PACS user may curb user expectations for "fastest" response especially during peak hours. This, in turn, could result in a PACS infrastructure tailored to more realistic performance demands. A PACS with a stand-alone architecture under peak load typically holds study requests in a queue until the DICOM C-Move command can take place. We investigate the contents of a stand-alone architecture PACS RetrieveSend queue and identified parameters and behaviors that enable a more accurate prediction of delivery time. A prediction algorithm for studies delayed in a stand-alone PACS queue can be extendible to other potential bottlenecks such as long-term storage archives. Implications of a queue monitor in other PACS architectures are also discussed.

  10. Forecasts of time averages with a numerical weather prediction model

    NASA Technical Reports Server (NTRS)

    Roads, J. O.

    1986-01-01

    Forecasts of time averages of 1-10 days in duration by an operational numerical weather prediction model are documented for the global 500 mb height field in spectral space. Error growth in very idealized models is described in order to anticipate various features of these forecasts and in order to anticipate what the results might be if forecasts longer than 10 days were carried out by present day numerical weather prediction models. The data set for this study is described, and the equilibrium spectra and error spectra are documented; then, the total error is documented. It is shown how forecasts can immediately be improved by removing the systematic error, by using statistical filters, and by ignoring forecasts beyond about a week. Temporal variations in the error field are also documented.

  11. 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

  12. 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.

  13. 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

  14. 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.

  15. Real-time prediction of intense magnetic storms

    NASA Astrophysics Data System (ADS)

    Vieira, L. E.; Chen, J.; Gonzalez, W. D.

    In this paper a feature-based method for predicting geoeffective solar wind structures and intense geomagnetic storms is shown. The geoeffective structures were identified from observations of the plasma parameters and interplanetary magnetic field measurements by ACE satellite in the internal Lagrangean point (L1). The magnetospheric state was monitored by the Dst index. The proposed algorithm is based on the Chen IMF Prediction Model [Chen et al., 1996; Chen et al., 1997], which attempts to predict the occurrence of intense geomagnetic storms and how long they will last. It does this by looking for a change from positive or zero values of the Z-component of the interplanetary field, to negative values which often produce a geomagnetic storm. When it finds such a signature in ACE data, it models the strength of this component as a sinusoid and uses that to estimate the length of time the Z-component will remain negative. The longer the time, the more likely a storm will occur. Also, one can estimate the length of time that the storm will last. A detailed study of this algorithm using the ACE data for 1998-2001 period showed that this algorithm is capable to predict whether the magnetosphere will reach a certain activity level (Dst < -80nT) with a precision of approximately 80% and antecedence from some hours up to 10 hours. It was verified that the occurrence of false alarms and of periods in that the algorithm is not capable to predict the occurrence of magnetic storms are due mainly to three factors: (1) the rotation rate of the magnetic field during geoeffective events is not constant, as assumed; (2) the southward component of the interplanetary magnetic field is the most important parameter in the solar wind - magnetosphere coupling, but it is not the only one that have to be considered; and, (3) the algorithm doesn't take into account the previous magnetospheric conditions, that is, it is not capable to track the occurrence of multiple injections of energy

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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

  1. Around-the-World Atomic Clocks: Predicted Relativistic Time Gains.

    PubMed

    Hafele, J C; Keating, R E

    1972-07-14

    During October 1971, four cesium beam atomic clocks were flown on regularly scheduled commercial jet flights around the world twice, once eastward and once westward, to test Einstein's theory of relativity with macroscopic clocks. From the actual flight paths of each trip, the theory predicts that the flying clocks, compared with reference clocks at the U.S. Naval Observatory, should have lost 40 +/- 23 nanoseconds during the eastward trip, and should have gained 275 +/- 21 nanoseconds during the westward trip. The observed time differences are presented in the report that follows this one.

  2. 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.

  3. The technology acceptance model: predicting nurses' intention to use telemedicine technology (eICU).

    PubMed

    Kowitlawakul, Yanika

    2011-07-01

    The purposes of this study were to determine factors and predictors that influence nurses' intention to use the eICU technology, to examine the applicability of the Technology Acceptance Model in explaining nurses' intention to use the eICU technology in healthcare settings, and to provide psychometric evidence of the measurement scales used in the study. The study involved 117 participants from two healthcare systems. The Telemedicine Technology Acceptance Model was developed based on the original Technology Acceptance Model that was initially developed by Fred Davis in 1986. The eICU Acceptance Survey was used as an instrument for the study. Content validity was examined, and the reliability of the instrument was tested. The results show that perceived usefulness is the most influential factor that influences nurses' intention to use the eICU technology. The principal factors that influence perceived usefulness are perceived ease of use, support from physicians, and years working in the hospital. The model fit was reasonably adequate and able to explain 58% of the variance (R = 0.58) in intention to use the eICU technology with the nursing sample.

  4. 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)

  5. Predictive validity of Perceived Emotional Intelligence on nursing students' self-concept.

    PubMed

    Augusto Landa, José María; López-Zafra, Esther; Aguilar-Luzón, Maria del Carmen; de Ugarte, Maria Fe Salguero

    2009-10-01

    This study examines the role of Perceived Emotional Intelligence, in nursing students' self-concept, controlling personality dimensions. Self-image is a cognitive component of the self that contains images of who we are, what we want to be and what we express and wish to express to others. Likewise, there is also an emotional and assessable component known as self-esteem. For a profession that requires not only technical expertise but also psychologically oriented care, knowledge about the self in nursing would be crucial to further development and growth of the profession. However, the role of emotions in the formation of nursing professionals has been scarcely studied. One hundred and thirty five undergraduates from nursing studies voluntarily participated in our study. They completed a questionnaire that comprises several scales. Our results show positive correlations between the Clarity and Emotional Repair components of Perceived Emotional Intelligence and all scales of the self-concept scale. Furthermore, we found positive relationships between the Extraversion and Accountability components of personality with almost all the scales of the self-concept and negative relationships with personality and neuroticism components of the self-concept. PMID:19447529

  6. Data assimialation for real-time prediction and reanalysis

    NASA Astrophysics Data System (ADS)

    Shprits, Y.; Kellerman, A. C.; Podladchikova, T.; Kondrashov, D. A.; Ghil, M.

    2015-12-01

    We discuss the how data assimilation can be used for the analysis of individual satellite anomalies, development of long-term evolution reconstruction that can be used for the specification models, and use of data assimilation to improve the now-casting and focusing of the radiation belts. We also discuss advanced data assimilation methods such as parameter estimation and smoothing.The 3D data assimilative VERB allows us to blend together data from GOES, RBSP A and RBSP B. Real-time prediction framework operating on our web site based on GOES, RBSP A, B and ACE data and 3D VERB is presented and discussed. In this paper we present a number of application of the data assimilation with the VERB 3D code. 1) Model with data assimilation allows to propagate data to different pitch angles, energies, and L-shells and blends them together with the physics based VERB code in an optimal way. We illustrate how we use this capability for the analysis of the previous events and for obtaining a global and statistical view of the system. 2) The model predictions strongly depend on initial conditions that are set up for the model. Therefore the model is as good as the initial conditions that it uses. To produce the best possible initial condition data from different sources ( GOES, RBSP A, B, our empirical model predictions based on ACE) are all blended together in an optimal way by means of data assimilation as described above. The resulting initial condition does not have gaps. That allows us to make a more accurate predictions.

  7. The impact of unwaged domestic work on the duration and timing of sleep of female nurses working full-time on rotating 3-shift rosters.

    PubMed

    Clissold, G; Smith, P; Acutt, B

    2001-12-01

    The study examined the impact of family type on the timing and duration of sleep of 16 experienced female shiftworkers working a rotating 3-shift roster. The nurses lived in one of three domestic lifestyle arrangements: single with no child care responsibilities (N = 4), partnered with no child care responsibilities (N = 5) and partnered with child care responsibilities (N = 7). Self report sleep diaries were used to collect data over a period of 28 days, following which each nurse took part in a conversational interview. Comparisons of the roster mean sleep durations between groups show that nurses who do not have the added unwaged workload of child care, record significantly more sleep than nurses with such responsibilities. Analysis of the data by shift type shows a significant difference for afternoon shift: nurses with child care responsibilities record a significantly earlier rise time and a significantly shorter total sleep duration. The interview data further highlights how sleep patterns are related to the time constraints of both domestic and waged work. PMID:14564906

  8. 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

  9. Comparing Response Time, Errors, and Satisfaction Between Text-based and Graphical User Interfaces During Nursing Order Tasks

    PubMed Central

    Staggers, Nancy; Kobus, David

    2000-01-01

    Despite the general adoption of graphical users interfaces (GUIs) in health care, few empirical data document the impact of this move on system users. This study compares two distinctly different user interfaces, a legacy text-based interface and a prototype graphical interface, for differences in nurses' response time (RT), errors, and satisfaction when the interfaces are used in the performance of computerized nursing order tasks. In a medical center on the East Coast of the United States, 98 randomly selected male and female nurses completed 40 tasks using each interface. Nurses completed four different types of order tasks (create, activate, modify, and discontinue). Using a repeated-measures and Latin square design, the study was counterbalanced for tasks, interface types, and blocks of trials. Overall, nurses had significantly faster response times (P < 0.0001) and fewer errors (P < 0.0001) using the prototype GUI than the text-based interface. The GUI was also rated significantly higher for satisfaction than the text system, and the GUI was faster to learn (P < 0.0001). Therefore, the results indicated that the use of a prototype GUI for nursing orders significantly enhances user performance and satisfaction. Consideration should be given to redesigning older user interfaces to create more modern ones by using human factors principles and input from user-centered focus groups. Future work should examine prospective nursing interfaces for highly complex interactions in computer-based patient records, detail the severity of errors made on line, and explore designs to optimize interactions in life-critical systems. PMID:10730600

  10. 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

  11. 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.

  12. 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.

  13. 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.

  14. Patient satisfaction and time-saving implications of a nurse-led nipple and areola reconstitution service following breast reconstruction.

    PubMed

    Potter, S; Barker, J; Willoughby, L; Perrott, E; Cawthorn, S J; Sahu, A K

    2007-06-01

    Nipple tattooing is a safe and effective technique for restoration of the nipple-areola complex following breast reconstruction and has a positive impact on patient well-being and body image. This procedure is usually performed by a surgeon, but following appropriate training, a nurse-led nipple tattooing service was established in our unit in December 2005. All 14 patients who had undergone nipple tattooing over a 6 month period were contacted by telephone and questioned about their cosmetic results and satisfaction with the service. Hundred percent of patients were 'satisfied' with their tattoo and all patients rated the nurse-led service as 'excellent'. It was estimated that 20h of consultant time was saved. Our study demonstrates that a nurse-led service is associated with both excellent cosmetic outcomes and high levels of patient satisfaction. It also results in a significant saving of consultant time allowing more effective use of clinic and theatre resources. PMID:17241786

  15. 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.

  16. Multi-scale description and prediction of financial time series

    NASA Astrophysics Data System (ADS)

    Nawroth, A. P.; Friedrich, R.; Peinke, J.

    2010-08-01

    A new method is proposed that allows a reconstruction of time series based on higher order multi-scale statistics given by a hierarchical process. This method is able to model financial time series not only on a specific scale but for a range of scales. The method itself is based on the general n-scale joint probability density, which can be extracted directly from given data. It is shown how based on this n-scale statistics, general n-point probabilities can be estimated from which predictions can be achieved. Exemplary results are shown for the German DAX index. The ability to model correctly the behaviour of the original process for different scales simultaneously and in time is demonstrated. As a main result it is shown that this method is able to reproduce the known volatility cluster, although the model contains no explicit time dependence. Thus a new mechanism is shown how, in a stationary multi-scale process, volatility clustering can emerge.

  17. Do barriers to pediatric pain management as perceived by nurses change over time?

    PubMed

    Czarnecki, Michelle L; Salamon, Katherine S; Thompson, Jamie J; Hainsworth, Keri R

    2014-03-01

    For decades, nurses (RNs) have identified barriers to providing the optimal pain management that children deserve; yet no studies were found in the literature that assessed these barriers over time or across multiple pediatric hospitals. The purpose of this study was to reassess barriers that pediatric RNs perceive, and how they describe optimal pain management, 3 years after our initial assessment, collect quantitative data regarding barriers identified through comments during our initial assessment, and describe any changes over time. The Modified Barriers to Optimal Pain Management survey was used to measure barriers in both studies. RNs were invited via e-mail to complete an electronic survey. Descriptive and inferential statistics were used to compare results over time. Four hundred forty-two RNs responded, representing a 38% response rate. RNs continue to describe optimal pain management most often in terms of patient comfort and level of functioning. While small changes were seen for several of the barriers, the most significant barriers continued to involve delays in the availability of medications, insufficient physician medication orders, and insufficient orders and time allowed to pre-medicate patients before procedures. To our knowledge, this is the first study to reassess RNs' perceptions of barriers to pediatric pain management over time. While little change was seen in RNs' descriptions of optimal pain management or in RNs' perceptions of barriers, no single item was rated as more than a moderate barrier to pain management. The implications of these findings are discussed in the context of improvement strategies.

  18. 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

  19. Predicting nurses' use of healthcare technology using the technology acceptance model: an integrative review.

    PubMed

    Strudwick, Gillian

    2015-05-01

    The benefits of healthcare technologies can only be attained if nurses accept and intend to fully use them. One of the most common models utilized to understand user acceptance of technology is the Technology Acceptance Model. This model and modified versions of it have only recently been applied in the healthcare literature among nurse participants. An integrative literature review was conducted on this topic. Ovid/MEDLINE, PubMed, Google Scholar, and CINAHL were searched yielding a total of 982 references. Upon eliminating duplicates and applying the inclusion and exclusion criteria, the review included a total of four dissertations, three symposium proceedings, and 13 peer-reviewed journal articles. These documents were appraised and reviewed. The results show that a modified Technology Acceptance Model with added variables could provide a better explanation of nurses' acceptance of healthcare technology. These added variables to modified versions of the Technology Acceptance Model are discussed, and the studies' methodologies are critiqued. Limitations of the studies included in the integrative review are also examined.

  20. 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

  1. 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

  2. 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

  3. [Hygiene during leisure time among third year students from the Department of Nursing and Health Sciences].

    PubMed

    Czabak-Garbacz, Róza; Skibniewska, Agnieszka; Mazurkiewicz, Piotr; Wisowska, Anna

    2002-01-01

    The aim of the study was the assessment of hygiene of leisure time among third year students from Faculty of Nursing and Health Science of Lublin Medical Academy. It analysed passive and active ways of spending free time. The study involved 106 students (55 stationary and 51 extramural) and it was conducted by means of questionnaire. The study revealed that students prefer passive types of spending their leisure time. The most popular activity was listening to the radio, to which they devoted average 2.9 hours a day (listening to music mainly). Extramural students listened to the radio shorter than stationary ones (the difference was statistically significant). Students spent also a lot of their time watching television (average 1.5 hours a day), reading books and newspapers (average 1.85 hours a day) and doing housework, which is an active way of rest (average 2.7 hours a day), mainly preparing meals and shopping. Students devoted the least of their free time to sleep during the day in spite of the fact it is an excellent way of rest. The study found also that physical activity was not a favourite type of spending free time. Every third student did not do any sport. Stationary students did sport 4 times longer than extramural (the difference was statistically significant). Only 31% practiced taking a daily walk and only 44% of students made tourist trips. 81.9% of them went away during summer holidays, but only 31% of them during the winter break. Undoubtedly, the way of spending free time by the students under examination was not hygienic as it did not give them a sense of relaxation and rest; also the students themselves were not satisfied with it.

  4. 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…

  5. 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…

  6. 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…

  7. The effect of automated monitoring and real-time prompting on nurses' hand hygiene performance.

    PubMed

    Levchenko, Alexander I; Boscart, Veronique M; Fernie, Geoff R

    2013-10-01

    Adequate hand hygiene compliance by healthcare staff is considered an effective method to reduce hospital-acquired infections. The electronic system developed at Toronto Rehabilitation Institute automatically detects hand hygiene opportunities and records hand hygiene actions. It includes an optional visual hand hygiene status indication, generates real-time hand hygiene prompting signals, and enables automated monitoring of individual and aggregated hand hygiene performance. The system was installed on a complex continuous care unit at the entrance to 17 patient rooms and a utility room. A total of 93 alcohol gel and soap dispensers were instrumented and 14 nurses were provided with the personal wearable electronic monitors. The study included three phases with the system operating in three different modes: (1) an inactive mode during the first phase when hand hygiene opportunities and hand hygiene actions were recorded but prompting and visual indication functions were disabled, (2) only hand hygiene status indicators were enabled during the second phase, and (3) both hand hygiene status and real-time hand hygiene prompting signals were enabled during the third phase. Data collection was performed automatically during all of the three phases. The system indicated significantly higher hand hygiene activity rates and compliance during the third phase, with both hand hygiene indication and real-time prompting functions enabled. To increase the efficacy of the technology, its use was supplemented with individual performance reviews of the automatically collected data.

  8. 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

  9. Faculty Teaching Time: A Comparison of Web-Based and Face-to-Face Graduate Nursing Courses

    PubMed Central

    Andersen, Katherine M; Avery, Melissa D

    2008-01-01

    Web-based education brings a new dimension to the issue of measuring faculty workload. Current literature reflects instructor concerns related to the time required to teach web-based courses (McAlpine, Lockerbie, Ramsay & Beaman 2002; Sellani & Harrington, 2002; Smith, Ferguson & Caris, 2001). This descriptive, comparative study seeks to determine the time required to teach web-based graduate nursing courses and compare that to teaching similar courses in the face-to-face setting. Utilizing time records previously collected as part of a federally funded grant, data from 11 web-based and five face-to-face graduate level nursing courses were analyzed. Although a statistically significant difference in teaching time requirements was not demonstrated, several interesting trends did appear. Examples include differences related to preparation time and the division of teacher time while teaching web-based as opposed to face-to-face courses. Future research and continued data collection related to faculty workload and time usage will be needed as web-based courses become a growing part of graduate nursing education. PMID:18241197

  10. Faculty teaching time: a comparison of web-based and face-to-face graduate nursing courses.

    PubMed

    Andersen, Katherine M; Avery, Melissa D

    2008-01-01

    Web-based education brings a new dimension to the issue of measuring faculty workload. Current literature reflects instructor concerns related to the time required to teach web-based courses (McAlpine, Lockerbie, Ramsay & Beaman 2002; Sellani & Harrington, 2002; Smith, Ferguson & Caris, 2001). This descriptive, comparative study seeks to determine the time required to teach web-based graduate nursing courses and compare that to teaching similar courses in the face-to-face setting. Utilizing time records previously collected as part of a federally funded grant, data from 11 web-based and five face-to-face graduate level nursing courses were analyzed. Although a statistically significant difference in teaching time requirements was not demonstrated, several interesting trends did appear. Examples include differences related to preparation time and the division of teacher time while teaching web-based as opposed to face-to-face courses. Future research and continued data collection related to faculty workload and time usage will be needed as web-based courses become a growing part of graduate nursing education.

  11. Navy Global Predictions for the Dynamo Time Period

    NASA Astrophysics Data System (ADS)

    Reynolds, C. A.; Ridout, J. A.; Flatau, M. K.; Chen, J.; Richman, J. G.; Jensen, T. G.; Shriver, J. F.

    2014-12-01

    The performance of 30-day simulations of the Navy Global Environmental Model (NAVGEM) is evaluated under several metrics. The time period of interest is the DYNAMO (Dynamics of Madden Julian Oscillation) field experiment period, starting late October 2011. The NAVGEM experiments are run at an effective 37-km resolution with several different SST configurations. The in the first set of experiments, the initial SST analysis, provided by the NCODA (Navy Coupled Ocean Data Assimilation) system, is either held fixed to the initial value (fixed SST) or updated every 6 hours. These forecasts are compared with forecasts in which the SST is updated with 3-h analyses from the Hybrid Coordinate Ocean Model (HYCOM), and forecasts in which NAVGEM is interactively coupled to HYCOM. Experiments are also performed with different physical parameterization options. The extended integrations are verified using observed OLR, TRMM precipitation estimates, and global analyses. The use of fixed SSTs is clearly sub-optimal. Biases in monthly mean fields are far more pronounced in the simulations where the SST is held fixed as compared to those in simulations where updated SST analyses are used. Biases in the monthly mean fields are further reduced when NAVGEM is coupled to HYCOM. Differences in SST can "migrate" to substantial changes in the time-mean land-surface temperatures, illustrating the substantial impact of SSTs over the full domain. Concerning the simulation of the MJO, some improvement is noted when the system is fully coupled, although the simulations still exhibit deficiencies such as eastward propagation that is too slow, and difficulty propagating over the maritime continent. Simulations that are started every 5 days indicate that the NAVGEM uncoupled system has difficulty predicting MJO initiation, but simulations started when the MJO is active in the Indian Ocean are able to capture eastward propagation characteristics. The coupled NAVGEM-HYCOM system shows ability to

  12. 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.

  13. Exploring the relationship between patient call-light use rate and nurse call-light response time in acute care settings.

    PubMed

    Tzeng, Huey-Ming; Larson, Janet L

    2011-03-01

    Patient call-light usage and nurse responsiveness to call lights are two intertwined concepts that could affect patients' safety during hospital stays. Little is known about the relationship between call-light usage and call-light response time. Consequently, this exploratory study examined the relationship between the patient-initiated call-light use rate and the nursing staff's average call-light response time in a Michigan community hospital. It used hospital archived data retrieved from the call-light tracking system for the period from February 2007 through June 2008. Curve estimation regression and multiple regression analyses were conducted. The results showed that the call-light response time was not affected by the total nursing hours or RN hours. The nurse call-light response time was longer when the patient call-light use rate was higher and the average length of stay was shorter. It is likely that a shorter length of stay contributes to the nursing care activity level on the unit because it is associated with a higher frequency of patient admissions/discharges and treatment per patient-day. This suggests that the nursing care activity level on the unit and number of call-light alarms could affect nurse call-light response time, independently of the number of nurses available to respond.

  14. 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.

  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.

  16. 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

  17. [Nurse-led in Primary Health Care setting: a well-timed and promising organizational innovation].

    PubMed

    Torres-Ricarte, Marc; Crusat-Abelló, Ernest; Peñuelas-Rodríguez, Silvia; Zabaleta-del-Olmo, Edurne

    2015-01-01

    At present, the severe economic crisis along with the increasing prevalence of chronic diseases is leading to different countries to consider updating their Primary Health Care (PHC) services in order to make them more efficient and reduce health inequalities. To that end, various initiatives are being carried out, such as the provision of Nurse-led services and interventions. The purpose of this article is to present the available knowledge, controversies and opportunities for Nurse-led initiatives in the setting of PHC. Nurse- led interventions or health services in PHC have proven to be equal or more effective than usual care in disease prevention, the routine follow-up of patients with chronic conditions, and first contact care for people with minor illness. However, as there are only a few health economic evaluation studies published their efficiency is still potential. In conclusion, the Nurse-led care could be an innovative organizational initiative with the potential to provide an adequate response to the contemporary health needs of the population, as well as an opportunity for the nursing profession and for PHC and health systems in general.

  18. Evaluating the uncertainty of predicting future climate time series at the hourly time scale

    NASA Astrophysics Data System (ADS)

    Caporali, E.; Fatichi, S.; Ivanov, V. Y.

    2011-12-01

    A stochastic downscaling methodology is developed to generate hourly, point-scale time series for several meteorological variables, such as precipitation, cloud cover, shortwave radiation, air temperature, relative humidity, wind speed, and atmospheric pressure. The methodology uses multi-model General Circulation Model (GCM) realizations and an hourly weather generator, AWE-GEN. Probabilistic descriptions of factors of change (a measure of climate change with respect to historic conditions) are computed for several climate statistics and different aggregation times using a Bayesian approach that weights the individual GCM contributions. The Monte Carlo method is applied to sample the factors of change from their respective distributions thereby permitting the generation of time series in an ensemble fashion, which reflects the uncertainty of climate projections of future as well as the uncertainty of the downscaling procedure. Applications of the methodology and probabilistic expressions of certainty in reproducing future climates for the periods, 2000 - 2009, 2046 - 2065 and 2081 - 2100, using the 1962 - 1992 period as the baseline, are discussed for the location of Firenze (Italy). The climate predictions for the period of 2000 - 2009 are tested against observations permitting to assess the reliability and uncertainties of the methodology in reproducing statistics of meteorological variables at different time scales.

  19. 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…

  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. Time spent studying on a pre-registration nursing programme module: an exploratory study and implications for regulation.

    PubMed

    Snelling, Paul C; Lipscomb, Martin; Lockyer, Lesley; Yates, Sue; Young, Pat

    2010-11-01

    European Union (EU) regulations require that university programmes are of specified duration. Additional EU regulations apply specifically to university based nurse education, enacted in the UK by the Nursing and Midwifery Council (NMC). However, little is known about how much time student nurses spend on their studies. In this exploratory study, students undertaking a single module in the pre-registration diploma programme at an English university were asked to keep a log of learning activity for the duration of the module. Twenty-six students completed the log. These students achieved higher grades and attended more lectures than the average for the module. The mean study time was 128.4 h against a regulatory assumption that the module should take 200 h. More than half of the 26 students undertook paid work during the module run, though this work was not associated with poorer performance. Problems in regulation for course duration are discussed and it is suggested that undertaking a 4600 h course in 3 years is problematic. More research is required so that patterns of study can be better understood and student centred programmes meeting regulatory requirements developed.

  2. Wireless communication role in patient response time: a study of vocera integration with a nurse call system.

    PubMed

    Kuruzovich, Jason; Angst, Corey M; Faraj, Samer; Agarwal, Ritu

    2008-01-01

    This study investigated the use and impact of wireless communication technology developed by Vocera Communications and implemented at St Agnes Hospital, Baltimore, MD. The specific focus was on the impact of a newly installed component of the Vocera system, the Vocera Messaging Interface, which enables connectivity between third-party systems, such as a nurse call system. The results of the investigation of the nurse call integration confirmed that the use of the integrated communications system reduced overall mean time for completing a patient request by 51% across all observations when controlling for observation type. Furthermore, analysis of clinicians' usage of the system for different types of patient requests revealed that it enables the clinician to have more control in prioritizing and responding to requests according to the seriousness of the event. The study also exposed several "creative" and "evolving" impacts of the system that are discussed along with practical implications of the findings. PMID:18438152

  3. An Exploration of the Transition to the Full-Time Faculty Role among Associate Degree Nurse Educators

    ERIC Educational Resources Information Center

    Shapiro, Sandra A.

    2016-01-01

    In the context of the nursing and faculty shortages, recommendations have been made to increase the number of highly educated nurses who are qualified to teach. A lack of nursing faculty has been reported at all levels of education. Because the majority of nurses enter into practice with an associate degree, the professoriate at the associate…

  4. 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…

  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. Timing of food intake predicts weight loss effectiveness

    PubMed Central

    Garaulet, Marta; Gómez-Abellán, Purificación; Alburquerque-Béjar, Juan J; Lee, Yu-Chi; Ordovás, Jose M; Scheer, Frank AJL

    2013-01-01

    Background 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. Objective To evaluate the role of food-timing in weight-loss effectiveness in a sample of 420 individuals who followed a 20-week weight-loss treatment. Methods Participants (49.5% females; age [mean+/−SD]: 42±11 years; BMI: 31.4±5.4 kg/m2) were grouped in early-eaters and late-eaters, according to the timing of the main meal (lunch in this Mediterranean population). 51% of the subjects were early-eaters and 49% were late-eaters (lunch time before and after 3:00 PM, respectively), energy intake and expenditure, appetite hormones, CLOCK genotype, sleep duration and chronotype were studied. Results Late lunch eaters lost less weight and displayed a slower weight-loss rate during the 20 weeks of treatment than early-eaters (P=0.002). Surprisingly, energy intake, dietary composition, estimated energy expenditure, appetite hormones and sleep duration was similar between both groups. Nevertheless, late-eaters were more evening-types, had less energetic breakfasts, and skipped breakfast more frequently that early-eaters (P<0.05). CLOCK rs4580704 SNP associated with the timing of the main meal (P=0.015) with a higher frequency of minor allele (C) carriers among the late-eaters (P=0.041). Neither sleep duration, nor CLOCK SNPs or Morning/Evening chronotype was independently associated with weight-loss (P>0.05). Conclusions Eating late may influence the success of weight-loss therapy. Novel therapeutic strategies should incorporate not only the caloric intake and macronutrient distribution—as is classically done—but also the timing of food. PMID:23357955

  7. 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.

  8. 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.

  9. 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.

  10. 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.

  11. Good nurse, bad nurse....

    PubMed

    Alavi, C; Cattoni, J

    1995-02-01

    The construction of the nursing subject is discussed. The paper takes a historical perspective, arguing that the range of speaking positions available to the nurse is limited by gender, class and education. It evaluates the position of nursing in the university, showing how this also has propensity to limit the development of the nursing profession.

  12. Testing Theories That Predict Time Variation of Fundamental Constants

    NASA Astrophysics Data System (ADS)

    Landau, Susana J.; Vucetich, Hector

    2002-05-01

    We consider astronomical and local bounds on the time variation of fundamental constants to test some generic Kaluza-Klein-like models and some particular cases of Beckenstein theory. Bounds on the free parameters of the different theories are obtained. Furthermore, we find that none of the proposed models is able to explain recent results (as from Webb and coworkers in 1999 and 2001) claiming an observed variation of the fine-structure constant from quasar absorption systems at redshifts 0.5

  13. Airport noise predicts song timing of European birds.

    PubMed

    Dominoni, Davide M; Greif, Stefan; Nemeth, Erwin; Brumm, Henrik

    2016-09-01

    Anthropogenic noise is of increasing concern to biologists and medical scientists. Its detrimental effects on human health have been well studied, with the high noise levels from air traffic being of particular concern. However, less is known about the effects of airport noise pollution on signal masking in wild animals. Here, we report a relationship between aircraft noise and two major features of the singing behavior of birds. We found that five of ten songbird species began singing significantly earlier in the morning in the vicinity of a major European airport than their conspecifics at a quieter control site. As birds at both sites started singing before the onset of air traffic in the morning, this suggests that the birds in the vicinity of the airport advanced their activity to gain more time for unimpaired singing before the massive plane noise set in. In addition, we found that during the day, chaffinches avoided singing during airplane takeoffs, but only when the noise exceeded a certain threshold, further suggesting that the massive noise caused by the airport can impair acoustic communication in birds. Overall, our study indicates that birds may be adjusting their mating signals and time budgets in response to aircraft noise.

  14. Airport noise predicts song timing of European birds.

    PubMed

    Dominoni, Davide M; Greif, Stefan; Nemeth, Erwin; Brumm, Henrik

    2016-09-01

    Anthropogenic noise is of increasing concern to biologists and medical scientists. Its detrimental effects on human health have been well studied, with the high noise levels from air traffic being of particular concern. However, less is known about the effects of airport noise pollution on signal masking in wild animals. Here, we report a relationship between aircraft noise and two major features of the singing behavior of birds. We found that five of ten songbird species began singing significantly earlier in the morning in the vicinity of a major European airport than their conspecifics at a quieter control site. As birds at both sites started singing before the onset of air traffic in the morning, this suggests that the birds in the vicinity of the airport advanced their activity to gain more time for unimpaired singing before the massive plane noise set in. In addition, we found that during the day, chaffinches avoided singing during airplane takeoffs, but only when the noise exceeded a certain threshold, further suggesting that the massive noise caused by the airport can impair acoustic communication in birds. Overall, our study indicates that birds may be adjusting their mating signals and time budgets in response to aircraft noise. PMID:27648232

  15. 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.

  16. 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.

  17. 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.

  18. The relationship between effective nurse managers and nursing retention.

    PubMed

    Force, Mary VanOyen

    2005-01-01

    Hospital executives are challenged to recruit and retain clinical nurses in a time when the national hospital nurse turnover rates are averaging above 20%. This literature review outlines nursing research that studied characteristics of nurse managers' leadership styles that enhance hospital nurse retention. Five consistent themes provided evidence of leadership traits that lead to job satisfaction and nurse retention. These were transformational leadership style, extroverted personality traits, magnet hospital organizational structures that support nurse empowerment, autonomy and group cohesion, tenure, and graduate education. Data from these studies provide a foundation for directing strategic plans to increase nurse retention and job satisfaction. PMID:16077275

  19. The relationship between effective nurse managers and nursing retention.

    PubMed

    Force, Mary VanOyen

    2005-01-01

    Hospital executives are challenged to recruit and retain clinical nurses in a time when the national hospital nurse turnover rates are averaging above 20%. This literature review outlines nursing research that studied characteristics of nurse managers' leadership styles that enhance hospital nurse retention. Five consistent themes provided evidence of leadership traits that lead to job satisfaction and nurse retention. These were transformational leadership style, extroverted personality traits, magnet hospital organizational structures that support nurse empowerment, autonomy and group cohesion, tenure, and graduate education. Data from these studies provide a foundation for directing strategic plans to increase nurse retention and job satisfaction.

  20. 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.

  1. 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.

  2. 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…

  3. 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.

  4. Nurses at war.

    PubMed

    Dean, Erin

    The first world war opened up nursing to a wider range of women and earned new status for the profession. Nursing service records from the conflict, available online for the first time at www.national archives.gov.uk, provide a detailed insight into the lives of nurses who were the first to handle war casualties on an industrial scale.

  5. 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

  6. 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.

  7. 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.

  8. Studying the time scale dependence of environmental variables predictability using fractal analysis.

    PubMed

    Yuval; Broday, David M

    2010-06-15

    Prediction of meteorological and air quality variables motivates a lot of research in the atmospheric sciences and exposure assessment communities. An interesting related issue regards the relative predictive power that can be expected at different time scales, and whether it vanishes altogether at certain ranges. An improved understanding of our predictive powers enables better environmental management and more efficient decision making processes. Fractal analysis is commonly used to characterize the self-affinity of time series. This work introduces the Continuous Wavelet Transform (CWT) fractal analysis method as a tool for assessing environmental time series predictability. The high temporal scale resolution of the CWT enables detailed information about the Hurst parameter, a common temporal fractality measure, and thus about time scale variations in predictability. We analyzed a few years records of half-hourly air pollution and meteorological time series from which the trivial seasonal and daily cycles were removed. We encountered a general trend of decreasing Hurst values from about 1.4 (good autocorrelation and predictability), in the sub-daily time scale to 0.5 (which implies complete randomness) in the monthly to seasonal scales. The air pollutants predictability follows that of the meteorological variables in the short time scales but is better at longer scales.

  9. 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

  10. 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

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

    PubMed

    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.

  12. 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.

  13. 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

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

    PubMed Central

    Wlotko, Edward W.; Federmeier, Kara D.

    2015-01-01

    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 ms or 250 ms 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 ms SOA, implausible words related to predictable words elicited reduced N400 amplitudes compared to unrelated words (PINES vs. TULIPS), replicating past studies. At 250 ms 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 ms SOA block showed no effect of semantic similarity for this SOA, although these same participants showed the effect in the second block with 500 ms SOA. However, participants who first read sentences in the 500 ms SOA block continued to show the N400 semantic similarity effect in the 250 ms 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

  15. 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

  16. "Personal best times in an olympic distance triathlon and a marathon predict an ironman race time for recreational female triathletes".

    PubMed

    Rüst, Christoph Alexander; Knechtle, Beat; Wirth, Andrea; Knechtle, Patrizia; Ellenrieder, Birte; Rosemann, Thomas; Lepers, Romuald

    2012-06-30

    "The aim of this study was to investigate whether the characteristics of anthropometry, training or previous performance were related to an Ironman race time in recreational female Ironman triathletes. These characteristics were correlated to an Ironman race time for 53 recreational female triathletes in order to determine the predictor variables, and so be able to predict an Ironman race time for future novice triathletes. In the bi-variate analysis, no anthropometric characteristic was related to race time. The weekly cycling kilometers (r = -0.35) and hours (r = -0.32), as well as the personal best time in an Olympic distance triathlon (r = 0.49) and in a marathon (r = 0.74) were related to an Ironman race time (< 0.05). Stepwise multiple regressions showed that both the personal best time in an Olympic distance triathlon ( P = 0.0453) and in a marathon (P = 0.0030) were the best predictors for the Ironman race time (n = 28, r² = 0.53). The race time in an Ironman triathlon might be partially predicted by the following equation (r² = 0.53, n = 28): Race time (min) = 186.3 + 1.595 × (personal best time in an Olympic distance triathlon, min) + 1.318 × (personal best time in a marathon, min) for recreational female Ironman triathletes."

  17. 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.

  18. 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…

  19. 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.

  20. Testing time-predictable earthquake recurrence by direct measurement of strain accumulation and release.

    PubMed

    Murray, Jessica; Segall, Paul

    2002-09-19

    Probabilistic estimates of earthquake hazard use various models for the temporal distribution of earthquakes, including the 'time-predictable' recurrence model formulated by Shimazaki and Nakata (which incorporates the concept of elastic rebound described as early as 1910 by H. F. Reid). This model states that an earthquake occurs when the fault recovers the stress relieved in the most recent earthquake. Unlike time-independent models (for example, Poisson probability), the time-predictable model is thought to encompass some of the physics behind the earthquake cycle, in that earthquake probability increases with time. The time-predictable model is therefore often preferred when adequate data are available, and it is incorporated in hazard predictions for many earthquake-prone regions, including northern California, southern California, New Zealand and Japan. Here we show that the model fails in what should be an ideal locale for its application -- Parkfield, California. We estimate rigorous bounds on the predicted recurrence time of the magnitude approximately 6 1966 Parkfield earthquake through inversion of geodetic measurements and we show that, according to the time-predictable model, another earthquake should have occurred by 1987. The model's poor performance in a relatively simple tectonic setting does not bode well for its successful application to the many areas of the world characterized by complex fault interactions.

  1. 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

  2. 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,…

  3. 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.

  4. 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 ...

  5. 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

  6. 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…

  7. Why GPA Isn't Predictive: Student Perceptions of Success or Failure in an Associate Degree Nursing Program

    ERIC Educational Resources Information Center

    Sall, James

    2009-01-01

    The purpose of this research was to identify the factors that students attending a Midwestern community college perceived contributed to their academic success or failure in an Associate Degree nursing program. A review of student academic records revealed that many students with weak academic records were successful while students with strong…

  8. A simple accurate method to predict time of ponding under variable intensity rainfall

    NASA Astrophysics Data System (ADS)

    Assouline, S.; Selker, J. S.; Parlange, J.-Y.

    2007-03-01

    The prediction of the time to ponding following commencement of rainfall is fundamental to hydrologic prediction of flood, erosion, and infiltration. Most of the studies to date have focused on prediction of ponding resulting from simple rainfall patterns. This approach was suitable to rainfall reported as average values over intervals of up to a day but does not take advantage of knowledge of the complex patterns of actual rainfall now commonly recorded electronically. A straightforward approach to include the instantaneous rainfall record in the prediction of ponding time and excess rainfall using only the infiltration capacity curve is presented. This method is tested against a numerical solution of the Richards equation on the basis of an actual rainfall record. The predicted time to ponding showed mean error ≤7% for a broad range of soils, with and without surface sealing. In contrast, the standard predictions had average errors of 87%, and worst-case errors exceeding a factor of 10. In addition to errors intrinsic in the modeling framework itself, errors that arise from averaging actual rainfall records over reporting intervals were evaluated. Averaging actual rainfall records observed in Israel over periods of as little as 5 min significantly reduced predicted runoff (75% for the sealed sandy loam and 46% for the silty clay loam), while hourly averaging gave complete lack of prediction of ponding in some of the cases.

  9. 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

  10. 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.

  11. 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!

  12. 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

  13. A post-modern nursing model.

    PubMed

    Archibald, G

    For some time, nursing has been based on the structure of the nursing process and nursing models. However, in an age where the old order of science and medicine can no longer answer all of society's questions, can a nursing model, with its roots firmly based in the modernist structure of the nursing process, be post-modern?

  14. The Prediction of Physical Activity Intention and Behavior in Elderly Male Residents of a Nursing Home: A Comparison of Two Behavioral Theories

    PubMed Central

    Ghahremani, Leila; Niknami, Shamsaddin; Nazari, Mahin

    2012-01-01

    Background: Regular physical activity is ranked as a leading health indicator. Despite the extensive benefits of physical activity, elder people are much less active than desired. Using Theory of Planned Behavior (TPB) and the self-efficacy construct, this study examined the prediction of physical activity intention and behavior in a sample of elderly male resident of a nursing home. Methods: In a cross-sectional study of the residents of Kahrizak Nursing Home in Tehran, Iran, elderly men who were 60 years or older, capable of independent living, mobility, and verbal communication were asked to complete measures of the TPB, self-efficacy and physical activity behavior. Results: A hierarchical step-wise multiple regression analysis indicated that affective/instrumental attitude, subjective norm, and perceived behavioral control (PBC) explained 32.8% of the variance in physical activity intention, and self-efficacy provided an additional 2.7%. In a reverse step regression, the TPB variables explained an additional 12.2% of physical activity intention. In a multiple regression analysis on physical activity behavior, affective/instrumental attitude, subjective norm, perceived behavioral control (PBC) and intention explained 15.7% of the variance in physical activity behavior while self-efficacy contributed an additional 5.6%. In the reverse step regression, TPB predictors contributed an additional 3.0% in explaining the variance in physical activity behavior. Conclusion: The results indicate that in addition to the TPB, self-efficacy may also play an important role in the prediction of behavior, and should be included in the design of physical activity programs for elderly men of nursing home residents. PMID:23115427

  15. 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

  16. Healthy work revisited: do changes in time strain predict well-being?

    PubMed

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

    2013-04-01

    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

  17. Healthy work revisited: do changes in time strain predict well-being?

    PubMed

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

    2013-04-01

    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.

  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. 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).

  20. 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…

  1. 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

  2. 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.

  3. 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

  4. 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.

  5. 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.

  6. 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…

  7. 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.

  8. Testing forecasts of a new Bayesian time-predictable model of eruption occurrence

    NASA Astrophysics Data System (ADS)

    Passarelli, L.; Sansò, B.; Sandri, L.; Marzocchi, W.

    2010-12-01

    In this paper we propose a model to forecast eruptions in a real forward perspective. Specifically, the model provides a forecast of the next eruption after the end of the last one, using only the data available up to that time. We focus our attention on volcanoes with open conduit regime and high eruption frequency. We assume a generalization of the classical time predictable model to describe the eruptive behavior of open conduit volcanoes and we use a Bayesian hierarchical model to make probabilistic forecasts. We apply the model to Kilauea volcano eruptive data and Mount Etna volcano flank eruption data. The aims of the proposed model are: (1) to test whether or not the Kilauea and Mount Etna volcanoes follow a time predictable behavior; (2) to discuss the volcanological implications of the time predictable model parameters inferred; (3) to compare the forecast capabilities of this model with other models present in literature. The results obtained using the MCMC sampling algorithm show that both volcanoes follow a time predictable behavior. The numerical values inferred for the parameters of the time predictable model suggest that the amount of the erupted volume could change the dynamics of the magma chamber refilling process during the repose period. The probability gain of this model compared with other models already present in literature is appreciably greater than zero. This means that our model provides better forecast than previous models and it could be used in a probabilistic volcanic hazard assessment scheme.

  9. 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

  10. 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…

  11. 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

  12. 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.

  13. LPTA: location predictive and time adaptive data gathering scheme with mobile sink for wireless sensor networks.

    PubMed

    Zhu, Chuan; Wang, Yao; Han, Guangjie; Rodrigues, Joel J P C; Lloret, Jaime

    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

  14. 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

  15. 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…

  16. 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.

  17. Semiparametric Models of Time-dependent Predictive Values of Prognostic Biomarkers

    PubMed Central

    Zheng, Yingye; Cai, Tianxi; Stanford, Janet L.; Feng, Ziding

    2009-01-01

    Summary Rigorous statistical evaluation of the predictive values of novel biomarkers is critical prior to applying novel biomarkers into routine standard care. It is important to identify factors that influence the performance of a biomarker in order to determine the optimal conditions for test performance. We propose a covariate-specific time-dependent PPV curve to quantify the predictive accuracy of a prognostic marker measured on a continuous scale and with censored failure time outcome. The covariate effect is accommodated with a semiparametric regression model framework. In particular we adopt a smoothed survival time regression technique (Dabrowska, 1997) to account for the situation where risk for the disease occurrence and progression is likely to change over time. In addition, we provide asymptotic distribution theory and resampling-based procedures for making statistical inference on the covariate specific positive predictive values. We illustrate our approach with numerical studies and a dataset from a prostate cancer study. PMID:19397579

  18. Predicting the dengue incidence in Singapore using univariate time series models.

    PubMed

    Dayama, Pankaj; Kameshwaran, S

    2013-01-01

    Dengue is endemic in Singapore with year-around transmission. Prediction of dengue incidence is important for effective use of limited resources for vector-control and contingency measures. In the work, we develop a set of time series models based on the observed weekly dengue incidence since 2000. The dengue incidence data of Singapore from 2000 - 2011 is used to develop and fit the predictive models. For testing and validation, we use the 2012 data at two levels: A) real versus predicted incidence and B) real versus predicted outbreak severity. The statistical measures of validation show that the models predict both the dengue incidence and the outbreak severity level with acceptable level of accuracy.

  19. 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…

  20. Respiratory motion prediction for tumor following radiotherapy by using time-variant seasonal autoregressive techniques.

    PubMed

    Ichiji, Kei; Homma, Noriyasu; Sakai, Masao; Takai, Yoshihiro; Narita, Yuichiro; Abe, Mokoto; Sugita, Norihiro; Yoshizawa, Makoto

    2012-01-01

    We develop a new prediction method of respiratory motion for accurate dynamic radiotherapy, called tumor following radiotherapy. The method is based on a time-variant seasonal autoregressive (TVSAR) model and extended to further capture time-variant and complex nature of various respiratory patterns. The extended TVSAR can represent not only the conventional quasi-periodical nature, but also the residual components, which cannot be expressed by the quasi-periodical model. Then, the residuals are adaptively predicted by using another autoregressive model. The proposed method was tested on 105 clinical data sets of tumor motion. The average errors were 1.28 ± 0.87 mm and 1.75 ± 1.13 mm for 0.5 s and 1.0 s ahead prediction, respectively. The results demonstrate that the proposed method can outperform the state-of-the-art prediction methods. PMID:23367303

  1. Predicting Time Series from Short-Term High-Dimensional Data

    NASA Astrophysics Data System (ADS)

    Ma, Huanfei; Zhou, Tianshou; Aihara, Kazuyuki; Chen, Luonan

    The prediction of future values of time series is a challenging task in many fields. In particular, making prediction based on short-term data is believed to be difficult. Here, we propose a method to predict systems' low-dimensional dynamics from high-dimensional but short-term data. Intuitively, it can be considered as a transformation from the inter-variable information of the observed high-dimensional data into the corresponding low-dimensional but long-term data, thereby equivalent to prediction of time series data. Technically, this method can be viewed as an inverse implementation of delayed embedding reconstruction. Both methods and algorithms are developed. To demonstrate the effectiveness of the theoretical result, benchmark examples and real-world problems from various fields are studied.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. Reward prediction error signals associated with a modified time estimation task.

    PubMed

    Holroyd, Clay B; Krigolson, Olave E

    2007-11-01

    The feedback error-related negativity (fERN) is a component of the human event-related brain potential (ERP) elicited by feedback stimuli. A recent theory holds that the fERN indexes a reward prediction error signal associated with the adaptive modification of behavior. Here we present behavioral and ERP data recorded from participants engaged in a modified time estimation task. As predicted by the theory, our results indicate that fERN amplitude reflects a reward prediction error signal and that the size of this error signal is correlated across participants with changes in task performance.

  7. 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

  8. 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.

  9. 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

  10. 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

  11. 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

  12. Prediction intervals for a noisy nonlinear time series based on a bootstrapping reservoir computing network ensemble.

    PubMed

    Sheng, Chunyang; Zhao, Jun; Wang, Wei; Leung, Henry

    2013-07-01

    Prediction intervals that provide estimated values as well as the corresponding reliability are applied to nonlinear time series forecast. However, constructing reliable prediction intervals for noisy time series is still a challenge. In this paper, a bootstrapping reservoir computing network ensemble (BRCNE) is proposed and a simultaneous training method based on Bayesian linear regression is developed. In addition, the structural parameters of the BRCNE, that is, the number of reservoir computing networks and the reservoir dimension, are determined off-line by the 0.632 bootstrap cross-validation. To verify the effectiveness of the proposed method, two kinds of time series data, including the multisuperimposed oscillator problem with additive noises and a practical gas flow in steel industry are employed here. The experimental results indicate that the proposed approach has a satisfactory performance on prediction intervals for practical applications.

  13. 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.

  14. 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

  15. 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.

  16. Statistical Observations and Predictions of Time Changes in Electron Flux at Geosynchronous Orbit

    NASA Astrophysics Data System (ADS)

    Olson, D. K.; Larsen, B.; Friedel, R. H.; Geoffrey, R.

    2015-12-01

    A statistical survey of time changes in particle flux values (df/dt) at geosynchronous orbit reveals trends that are instructive to predictive magnetosphere models. A single spacecraft can provide short time scale df/dt measurements, while multiple spacecraft can provide values over periods comparable to the spacecraft separation. Using data from multiple LANL-GEO spacecraft provides a unique view of temporal and spatial variations that allow us to gauge time and length scales for changing particle fluxes at GEO. These scales provide a base ability to predict the plasma environment conditions for spacecraft crossing GEO. Probability distribution functions based on electron df/dt values are used to predict the electron flux at a given magnetic local time at GEO based on prior measurements. The predictions, when compared to new data taken in the same region, provide some measure of how the electron plasma environment at GEO has changed in the interim period. These predictions are compared to data from the Van Allen Probes as their orbits cross GEO to verify the validity of this technique.

  17. A model for prediction of resynchronization after time-zone flights.

    PubMed

    Wegmann, H M; Klein, K E; Conrad, B; Esser, P

    1983-06-01

    Utilizing experimental data from three flight studies, a concept was developed which allows appraising average resynchronization for any day after arrival in a new time-zone. The course of adaptation is nonlinear and can be mathematically represented by an exponential function. The model predicts higher initial resynchronization rates when more time zones are crossed, but total time for complete reentrainment is essentially the same and, thus is independent of the number of time-zones. The equation derived from experimental data is converted into an e-function and the resulting time constants are presented as they evolved for different functions and flight directions.

  18. Television news coverage of nurse strikes: a resource management perspective.

    PubMed

    Kalisch, B J; Kalisch, P A; Young, R L

    1983-01-01

    The quality of television news coverage of nurses' strikes and other labor activities plays a crucial role in expanding such conflicts to the public with either prolabor or promanagement colorations. It was found that access to the medium was influenced by the magnitude of the disruption. Nurse unions are benefited by more positive television news coverage when they (1) project an image of solidarity, (2) maintain unity over time, and (3) receive the support of other types of health-care workers. As predicted, hospital administrators were the most negative in televised comments about striking nurses. PMID:6551779

  19. 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.

  20. 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.

  1. 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

  2. An evidence-based approach to nurses week celebrations.

    PubMed

    Hensinger, Barbara; Parry, Juanita; Calarco, Margaret M; Fuhrmann, Sarah

    2008-04-01

    It is time to examine nurses week investments. With expenses increasingly scrutinized, healthcare leaders require data-driven decisions. Managing by instinct and intuition is both inadequate and reckless. This survey of 727 registered nurses identifies celebratory options for nurses week that nurses find meaningful. Knowing what registered nurses value will guide approaches to an effective nurses week activity planning. PMID:18403990

  3. 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

  4. Establishing roles in genetic nursing: interviews with Canadian nurses.

    PubMed

    Bottorff, Joan L; McCullum, Mary; Balneaves, Lynda G; Esplen, Mary Jane; Carroll, June; Kelly, Mary; Kieffer, Stephanie

    2005-12-01

    The purpose of this qualitative study was to describe nurses' roles in providing clinical genetic services related to adult onset hereditary disease and factors that influence genetic nursing practice in Canada. The study involved semi-structured telephone interviews with 22 nurses from 5 Canadian provinces with full-time or part-time roles in providing genetic services. The interviews included open-ended questions to elicit descriptions of genetic nursing roles and factors that support and limit opportunities in genetic nursing practice. Thematic analysis of the transcribed interviews revealed that, in addition to genetic counselling, the nurses reported a wide range of roles and responsibilities related to the provision of genetic services that drew directly on their nursing background (e.g., patient assessment, health promotion). Factors identified as supporting genetic nursing roles included nursing background, being part of a multidisciplinary team, and receiving mentorship. Challenges in establishing roles in genetic nursing were related to role ambiguity, lack of recognition of nursing expertise, limited availability of genetics education, isolation, and instability of nursing positions. Recommendations to support the development and expansion of genetic nursing practice were identified. A coordinated national effort among all stakeholders is needed to provide the resources necessary to support the appropriate and effective use of nursing expertise as genetics is integrated into the Canadian health-care system. PMID:16541821

  5. 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

  6. 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).

  7. 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.

  8. Strategic influence on the time course of predictive inferences in reading.

    PubMed

    Calvo, Manuel G; Castillo, M Dolores; Schmalhofer, Franz

    2006-01-01

    In the present study, we investigated how reading strategies affect the time course of online predictive inferences. Participants read sentences under instructions either to anticipate the outcomes of described events or to understand the sentences. These were followed by a target word to be named, with stimulus onset asynchronies (SOAs) of 500 or 1,000 msec (50- or 550-msec interstimulus interval, respectively). Sentences either were predictive of events or were lexically matched control sentences. There was facilitation in naming latencies for predictable target words in the strategic-anticipation condition at both SOAs, but not in the read-to-understand condition, with a significant improvement in the former condition in comparison with the latter. This suggests that predictive inferences, which are typically considered to be resource demanding, can be speeded up by specific goals in reading. Moreover, this can occur at no cost to comprehension of explicit information, as was revealed by a comprehension test.

  9. 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.

  10. Assembling genes from predicted exons in linear time with dynamic programming.

    PubMed

    Guigó, R

    1998-01-01

    In a number of programs for gene structure prediction in higher eukaryotic genomic sequences, exon prediction is decoupled from gene assembly: a large pool of candidate exons is predicted and scored from features located in the query DNA sequence, and candidate genes are assembled from such a pool as sequences of nonoverlapping frame-compatible exons. Genes are scored as a function of the scores of the assembled exons, and the highest scoring candidate gene is assumed to be the most likely gene encoded by the query DNA sequence. Considering additive gene scoring functions, currently available algorithms to determine such a highest scoring candidate gene run in time proportional to the square of the number of predicted exons. Here, we present an algorithm whose running time grows only linearly with the size of the set of predicted exons. Polynomial algorithms rely on the fact that, while scanning the set of predicted exons, the highest scoring gene ending in a given exon can be obtained by appending the exon to the highest scoring among the highest scoring genes ending at each compatible preceding exon. The algorithm here relies on the simple fact that such highest scoring gene can be stored and updated. This requires scanning the set of predicted exons simultaneously by increasing acceptor and donor position. On the other hand, the algorithm described here does not assume an underlying gene structure model. Indeed, the definition of valid gene structures is externally defined in the so-called Gene Model. The Gene Model specifies simply which gene features are allowed immediately upstream which other gene features in valid gene structures. This allows for great flexibility in formulating the gene identification problem. In particular it allows for multiple-gene two-strand predictions and for considering gene features other than coding exons (such as promoter elements) in valid gene structures.

  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.

  12. 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

  13. 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.

  14. Warning Times and Impact Predictions of Asteroids and Comets on a Collision Course with Earth

    NASA Astrophysics Data System (ADS)

    Heidt, Ahren D.

    1997-12-01

    This study investigates the amount of data and time necessary to accurately predict Earth impacts of Earth Crossing Objects (ECOs). Trajectories are simulated by numerically integrating in an N-Body system. Given final impact parameters, the trajectory is propagated backwards to an earlier time, creating initial conditions and simulated observation data at requested intervals to which Gaussian random noise is introduced. Utilizing a Bayes Filter to estimate position and velocity from the simulated observation data, the estimate is then propagated forward in time to determine whether or not an impact can be accurately predicted. State vectors and covariance matrices are then propagated to the impact time and the one sigma error ellipsoid is analyzed.

  15. Comparison of planning and using free time among students of the Faculty of Pharmacy and the Faculty of Nursing and Health Sciences.

    PubMed

    Czabak-Garbacz, Róza; Skibniewska, Agnieszka; Mazurkiewicz, Piotr; Wisowska, Anna; Gdula, Agnieszka

    2003-01-01

    The work presents a research of the group of third year students from two faculties of the Medical University in Lublin. The aim of the research was find out the correlation and differences in the ways of managing and using the so-called 'leisure time'; in relation to stable factors, as well as the system and the direction of studies and environmental factors, dependent on the influences of the psychosociological surrounding. 114 students of the Faculty of Pharmacy and also 55 daily and 51 extramural students of the Faculty of Nursing and Health Education were examined. It has been stated that students of the Faculty of Nursing and Health Education devoted most of their time to house work, reading books and magazines and watching TV, which differentiated them from pharmacy students. Daily students of both faculties in comparison with extramural students spent more time on listening to the radio, going to the cinema or taking part in social meetings. Daily students of the Faculty of Nursing and Health Education devoted more time to sport, walking, reading books and magazines, hobbies and going to the theatre, opera, museum, concerts and exhibitions, not only in comparison with the extramural students, but also with the pharmacy students. A few students showed interest in part-time work during the academic year, although their number rose during the period of holidays, especially among daily students of the Faculty of Nursing and Health Sciences. On the basis of the research it was stated that the way of managing and actual spending of leisure time was influenced by the direction of studies, family situation and sex of the examined students.

  16. Period, epoch, and prediction errors of ephemerides from continuous sets of timing measurements

    NASA Astrophysics Data System (ADS)

    Deeg, H. J.

    2015-06-01

    Space missions such as Kepler and CoRoT have led to large numbers of eclipse or transit measurements in nearly continuous time series. This paper shows how to obtain the period error in such measurements from a basic linear least-squares fit, and how to correctly derive the timing error in the prediction of future transit or eclipse events. Assuming strict periodicity, a formula for the period error of these time series is derived, σP = σT (12 / (N3-N))1 / 2, where σP is the period error, σT the timing error of a single measurement, and N the number of measurements. Compared to the iterative method for period error estimation by Mighell & Plavchan (2013), this much simpler formula leads to smaller period errors, whose correctness has been verified through simulations. For the prediction of times of future periodic events, usual linear ephemeris were epoch errors are quoted for the first time measurement, are prone to an overestimation of the error of that prediction. This may be avoided by a correction for the duration of the time series. An alternative is the derivation of ephemerides whose reference epoch and epoch error are given for the centre of the time series. For long continuous or near-continuous time series whose acquisition is completed, such central epochs should be the preferred way for the quotation of linear ephemerides. While this work was motivated from the analysis of eclipse timing measures in space-based light curves, it should be applicable to any other problem with an uninterrupted sequence of discrete timings for which the determination of a zero point, of a constant period and of the associated errors is needed.

  17. 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.

  18. 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.

  19. Probabilistic prediction of real-world time series: A local regression approach

    NASA Astrophysics Data System (ADS)

    Laio, Francesco; Ridolfi, Luca; Tamea, Stefania

    2007-02-01

    We propose a probabilistic prediction method, based on local polynomial regressions, which complements the point forecasts with robust estimates of the corresponding forecast uncertainty. The reliability, practicability and generality of the method is demonstrated by applying it to astronomical, physiological, economic, and geophysical time series.

  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. 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…

  2. 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...

  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. 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…

  5. 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.

  6. 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…

  7. 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.

  8. PREDICTION OF SOLAR FLARE SIZE AND TIME-TO-FLARE USING SUPPORT VECTOR MACHINE REGRESSION

    SciTech Connect

    Boucheron, Laura E.; Al-Ghraibah, Amani; McAteer, R. T. James

    2015-10-10

    We study the prediction of solar flare size and time-to-flare using 38 features describing magnetic complexity of the photospheric magnetic field. This work uses support vector regression to formulate a mapping from the 38-dimensional feature space to a continuous-valued label vector representing flare size or time-to-flare. When we consider flaring regions only, we find an average error in estimating flare size of approximately half a geostationary operational environmental satellite (GOES) class. When we additionally consider non-flaring regions, we find an increased average error of approximately three-fourths a GOES class. We also consider thresholding the regressed flare size for the experiment containing both flaring and non-flaring regions and find a true positive rate of 0.69 and a true negative rate of 0.86 for flare prediction. The results for both of these size regression experiments are consistent across a wide range of predictive time windows, indicating that the magnetic complexity features may be persistent in appearance long before flare activity. This is supported by our larger error rates of some 40 hr in the time-to-flare regression problem. The 38 magnetic complexity features considered here appear to have discriminative potential for flare size, but their persistence in time makes them less discriminative for the time-to-flare problem.

  9. 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

  10. 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 ...

  11. 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 ...

  12. 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

  13. 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

  14. 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.

  15. 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

  16. Data-driven prediction of thresholded time series of rainfall and self-organized criticality models

    NASA Astrophysics Data System (ADS)

    Deluca, Anna; Moloney, Nicholas R.; Corral, Álvaro

    2015-05-01

    We study the occurrence of events, subject to threshold, in a representative self-organized criticality (SOC) sandpile model and in high-resolution rainfall data. The predictability in both systems is analyzed by means of a decision variable sensitive to event clustering, and the quality of the predictions is evaluated by the receiver operating characteristic (ROC) method. In the case of the SOC sandpile model, the scaling of quiet-time distributions with increasing threshold leads to increased predictability of extreme events. A scaling theory allows us to understand all the details of the prediction procedure and to extrapolate the shape of the ROC curves for the most extreme events. For rainfall data, the quiet-time distributions do not scale for high thresholds, which means that the corresponding ROC curves cannot be straightforwardly related to those for lower thresholds. In this way, ROC curves are useful for highlighting differences in predictability of extreme events between toy models and real-world phenomena.

  17. 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.

  18. Reliability prediction of ontology-based service compositions using Petri net and time series models.

    PubMed

    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. Reliability prediction of ontology-based service compositions using Petri net and time series models.

    PubMed

    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.

  20. 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

  1. 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.

  2. Eruption forerunners from multiparameter monitoring and application for eruptions time predictability (Piton de la Fournaise)

    NASA Astrophysics Data System (ADS)

    Schmid, A.; Grasso, J. R.; Clarke, D.; Ferrazzini, V.; BachèLery, P.; Staudacher, T.

    2012-11-01

    Volcanic eruptions impact on societal risk, and volcanic hazard assessment is a necessary ingredient for decision-makers. However, the prediction of volcanic eruptions remains challenging due to the complexity and the non-linearity of volcanic processes. Identified forerunners such as increasing seismicity or deformation of the volcanic edifice prior to eruption are not deterministic. In this study, we use statistical methods to identify and discriminate precursory patterns to eruptions, on three sets of observables of Piton de la Fournaise volcano. We analyzed the short-term (i.e. the inter-eruptive period) time series of the seismicity rate, the deformation and the seismic velocity changes (deduced from seismic noise cross-correlations) over the period 1999-2006, with two main goals. First, we characterize the average pre-eruptive time patterns before 22 eruptions using superposed epoch analysis for the three observables. Using daily rate values, we resolve (1) a velocity change within 100-50 days from the eruptions onsets, then a plateau value up to eruption onset; (2) a power law increase in seismicity rate from noise level 15-10 days before eruption time; (3) an increase of displacement rate on the eruption day. These results support a three step mechanism leading to magma transfers toward the surface. Second we use pattern recognition techniques and the formalization of error diagrams to quantify the predictive power of each forerunner either as used independently or as combined to each other. We show that when seismicity rate alone performs the best prediction in the failure to predict versus alarm duration space, the combination of the displacement and seismicity data reduces the false alarm rate. We further propose a tool which explores the prediction results in order to optimize prediction strategy for decision-makers, as a function of the risk value.

  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. 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.

  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. English-language acculturation predicts academic performance in nursing students who speak English as a second language.

    PubMed

    Salamonson, Yenna; Everett, Bronwyn; Koch, Jane; Andrew, Sharon; Davidson, Patricia M

    2008-02-01

    Students who speak English as a second language (ESL) face considerable challenges in English language universities, but little is known about the relationship between English-language acculturation and academic performance. A prospective, correlational design was used to validate the English Language Acculturation Scale (ELAS), a measure of the linguistic aspect of acculturation, and to determine the relationship between English-language acculturation and academic achievement among 273 first-year nursing students. Exploratory factor analyses demonstrated that the ELAS was a valid and reliable measure (alpha = .89). When ELAS scores were examined in relation to students' grades, students with the lowest ELAS scores also had the lowest mean subject grades, highlighting the need to place greater emphasis on identifying English-language acculturation among ESL students.

  8. 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.

  9. 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.

  10. 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.

  11. Fast time-series prediction using high-dimensional data: Evaluating confidence interval credibility

    NASA Astrophysics Data System (ADS)

    Hirata, Yoshito

    2014-05-01

    I propose an index for evaluating the credibility of confidence intervals for future observables predicted from high-dimensional time-series data. The index evaluates the distance from the current state to the data manifold. I demonstrate the index with artificial datasets generated from the Lorenz'96 II model [Lorenz, in Proceedings of the Seminar on Predictability, Vol. 1 (ECMWF, Reading, UK, 1996), p. 1], the Lorenz'96 I model [Hansen and Smith, J. Atmos. Sci. 57, 2859 (2000), 10.1175/1520-0469(2000)057<2859:TROOCI>2.0.CO;2], and the coupled map lattice, and a real dataset for the solar irradiation around Japan.

  12. A 2-D Model to Predict Time Development of Scour below Pipelines with Spoiler

    NASA Astrophysics Data System (ADS)

    Alam, M. S.; Cheng, Liang

    2010-05-01

    A lattice Boltzmann 2-D scour model is developed in order to predict time development of scour around offshore pipelines with spoiler. The fluid flow is captured employing Lattice Boltzmann method and the scour model is designed with the combination of multi-particle Cellular Automata technique and threshold of sediment entrainment technique available in literature. It is revealed that the proposed hybrid model is robust enough to predict evolution of bed profiles for flow and scour underneath offshore pipelines considering various orientation and length of spoiler attached.

  13. Taking personal responsibility: Nurses' and assistant nurses' experiences of good nursing practice in psychiatric inpatient care.

    PubMed

    Gabrielsson, Sebastian; Sävenstedt, Stefan; Olsson, Malin

    2016-10-01

    Therapeutic nurse-patient relationships are considered essential for good nursing practice in psychiatric inpatient care. Previous research suggests that inpatient care fails to fulfil patients' expectations in this regard, and that nurses might experience the reality of inpatient care as an obstruction. The aim of the present study was to explore nurses' and assistant nurses' experiences of good nursing practice in the specific context of psychiatric inpatient care. Qualitative interviews were conducted with 12 skilled, relationship-oriented nurses and assistant nurses in order to explore their experiences with nursing practice related to psychiatric inpatient care. Interviews were transcribed and analysed using an interpretive descriptive approach. Findings describe good nursing practice as a matter of nurses and assistant nurses taking personal responsibility for their actions and for the individual patient as a person. Difficulties in providing dignified nursing care and taking personal responsibility cause them to experience feelings of distress and frustration. Shared values and nursing leadership supports being moral and treating patients with respect, having enough time supports being present and connecting with patients, and working as a part of a competent team with critical daily discussions and diversity supports being confident and building trust. The findings suggest that taking personal responsibility is integral to good nursing practice. If unable to improve poor circumstances, nurses might be forced to promote their own survival by refuting or redefining their responsibility. Nurses need to prioritize being with patients and gain support in shaping their own nursing practice. Nursing leadership should provide moral direction and defend humanistic values. PMID:27378375

  14. Taking personal responsibility: Nurses' and assistant nurses' experiences of good nursing practice in psychiatric inpatient care.

    PubMed

    Gabrielsson, Sebastian; Sävenstedt, Stefan; Olsson, Malin

    2016-10-01

    Therapeutic nurse-patient relationships are considered essential for good nursing practice in psychiatric inpatient care. Previous research suggests that inpatient care fails to fulfil patients' expectations in this regard, and that nurses might experience the reality of inpatient care as an obstruction. The aim of the present study was to explore nurses' and assistant nurses' experiences of good nursing practice in the specific context of psychiatric inpatient care. Qualitative interviews were conducted with 12 skilled, relationship-oriented nurses and assistant nurses in order to explore their experiences with nursing practice related to psychiatric inpatient care. Interviews were transcribed and analysed using an interpretive descriptive approach. Findings describe good nursing practice as a matter of nurses and assistant nurses taking personal responsibility for their actions and for the individual patient as a person. Difficulties in providing dignified nursing care and taking personal responsibility cause them to experience feelings of distress and frustration. Shared values and nursing leadership supports being moral and treating patients with respect, having enough time supports being present and connecting with patients, and working as a part of a competent team with critical daily discussions and diversity supports being confident and building trust. The findings suggest that taking personal responsibility is integral to good nursing practice. If unable to improve poor circumstances, nurses might be forced to promote their own survival by refuting or redefining their responsibility. Nurses need to prioritize being with patients and gain support in shaping their own nursing practice. Nursing leadership should provide moral direction and defend humanistic values.

  15. Nurse Career-Pattern Study. Part I: Practical Nursing Programs.

    ERIC Educational Resources Information Center

    Tate, Barbara L.; Knopf, Lucille

    The overall nurse career-patterns study actually consists of four concurrent longitudinal studies relating to the four kinds of nursing programs in which, if possible, each subject will be followed from the time of entrance through a 15-year period after graduation. The practical nurse study seeks to determine whether certain biographical data or…

  16. 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

  17. 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

  18. 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.

  19. Real-time prediction of ground motion using real-time correction of site amplification factors for EEW

    NASA Astrophysics Data System (ADS)

    Aoki, S.; Hoshiba, M.

    2013-12-01

    1. Introduction Hoshiba(2013a, JGR) proposed a method for prediction of ground motion based on real-time monitoring, in which hypocenter and M are not required. In this method, site amplification must be corrected in real-time manner. Hoshiba (2013b, BSSA) developed a causal recursive digital filter in the time domain for the real-time correction of frequency-dependent site factors. In this presentation we will apply this correction by using the site factors estimated by the spectral ratio method. 2. Method of site correction When the epicentral distances r to a station-pair (site 1 and 2) are much larger than the distance d between those sites, the averaged spectral ratio of S waves from many events can be regarded as the relative site factor between site 1 and 2 in the spectral ratio method. In this study, the dataset, which consists of the station-pairs and events that occurred in the area around Japan from 1996 to 2010, are selected to satisfy the conditions of 100km≦r≦350km and d≦30km, and we design the causal digital filter having similar amplitude property to relative site factor for the station-pair. The filter parameters are estimated by minimizing the residuals between the frequency-dependent site factor and modeled amplitude spectrum in the frequency range between 0.1 and 20Hz. In order to examine the effect of this method, we compare the results of following two methods for the prediction of the JMA seismic intensity. We want to focus on only site effect in this examination, so that the above-mentioned dataset is analyzed. Method A (MA): Seismic intensities at site 2 are predicted from waveforms observed at site 1 by using the correction for frequency-dependent site factors. Here, for each event the 3-componet waveforms at site 2 are first simulated from those at site 1 applying the causal filter, and then the predicted seismic intensity is calculated from the simulated waveforms by the method of Kunugi et al. (2008). Method B (MB

  20. 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

  1. Can we predict solar radiation at seasonal time-scale over Europe? A renewable energy perspective.

    NASA Astrophysics Data System (ADS)

    De Felice, Matteo; Alessandri, Andrea

    2015-04-01

    Surface solar radiation can be an important variable for the activities related to renewable energies (photovoltaic) and agriculture. Having accurate forecast may be of potential use for planning and operational tasks. This study examines the predictability of seasonal surface solar radiation comparing ECMWF System4 Seasonal operational forecasts with reanalyses (ERA-INTERIM, MERRA) and other datasets (NASA/GEWEX SRB, WFDEI). This work is focused on the period 1984-2007 and it tries to answer the following questions: 1) How similar are the chosen datasets looking at average and interannual variability? 2) What is the skill of seasonal forecasts in predicting solar radiation? 3) Is it useful for solar power operations and planning the seasonal prediction of solar radiation? It is important to assess the capability of climate datasets in describing surface solar radiation but at the same time it is critical to understand the needs of solar power industry in order to find the right problems to tackle.

  2. 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.

  3. Evaluation of a Satellite-based Near Real-time Global Flood Prediction System

    NASA Astrophysics Data System (ADS)

    Yilmaz, K. K.; Adler, R.; Pierce, H.

    2009-04-01

    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. Recently, our group has implemented an initial satellite-based near real-time global flood prediction system that is operationally available. In this system, a relatively simple hydrologic model, based on the runoff curve number (CN) and antecedent precipitation index (API) methods, transforms rainfall into runoff. Runoff is then routed grid-to-grid to estimate flow. 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, 0.25x0.25 degree). 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 focuses on the severe flooding events and will include comparison of the current product with observed runoff and inundation data at global and watershed scale as well as with other available remotely sensed products, such as those from Dartmouth Flood Observatory. Initial evaluation suggests that current global near-real time flood predictions provide valuable information related to spatial extent and onset time of extreme flooding events. However the accuracy diminishes in tracking the later stages of the flood event. This behavior suggests that one way to improve the current system is a new (possibly finer scale) routing component. Of course, flood predictions are intimately tied to the accuracy of the satellite-based rainfall estimates. Our presentation will also compare the performance of the flood prediction system when the current version of the NASA TMPA real

  4. 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

  5. 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.

  6. Neural-network predictive control for nonlinear dynamic systems with time-delay.

    PubMed

    Huang, Jin-Quan; Lewis, F L

    2003-01-01

    A new recurrent neural-network predictive feedback control structure for a class of uncertain nonlinear dynamic time-delay systems in canonical form is developed and analyzed. The dynamic system has constant input and feedback time delays due to a communications channel. The proposed control structure consists of a linearized subsystem local to the controlled plant and a remote predictive controller located at the master command station. In the local linearized subsystem, a recurrent neural network with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant. No linearity in the unknown parameters is required. No preliminary off-line weight learning is needed. The remote controller is a modified Smith predictor that provides prediction and maintains the desired tracking performance; an extra robustifying term is needed to guarantee stability. Rigorous stability proofs are given using Lyapunov analysis. The result is an adaptive neural net compensation scheme for unknown nonlinear systems with time delays. A simulation example is provided to demonstrate the effectiveness of the proposed control strategy.

  7. 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

  8. 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 ...

  9. Sickening nurses: fever nursing, nurses' illness, and the anatomy of blame, New Zealand 1903-1923.

    PubMed

    Wood, Pamela J

    2011-01-01

    In the early twentieth century, patients with infectious fevers represented a danger to the health of others including their nurses. This research describes the training New Zealand nurses received in fever nursing during the period 1903-1923, and considers how they applied hospital cross-infection principles in emergency tent fever camps in remote rural areas. It examines the reaction of nurses, hospital boards, and physicians to nurses who succumbed with their patients' fevers. It therefore reveals attitudes to nurses, prevailing ideas about responsibility for nurses' health, and elements in the emerging professional culture of nursing. Although some measures protected them against epidemic fevers, nurses were held responsible for their own health. A complex anatomy of blame is evident against those who sickened; the nature of the blame shifted, depending on the observer, disease, and practice setting. Physicians blamed nurses, especially when they sickened with typhoid fever. The country's chief nurse and other nurses blamed those who jeopardized their health through ill-spent leisure time. Sick nurses could be absolved from blame for the lax discipline evident through their failure to observe cross-infection principles if their practice setting was the fever camp. Willingness to work in difficult circumstances showed they embodied the ideal of sacrifice that, like discipline, was part of the emerging nursing culture. PMID:21329145

  10. Work-family conflict, spouse support, and nursing staff well-being during organizational restructuring.

    PubMed

    Burke, R J; Greenglass, E R

    1999-10-01

    This study examined work and family conflict, spouse support, and nursing staff well-being during a time of hospital restructuring and downsizing. Data were collected from 686 hospital-based nurses, the vast majority (97%) women. Nurses reported significantly greater work-family conflict than family-work conflict. Personal demographic but not downsizing and restructuring variables predicted family-work conflict; downsizing and restructuring variables but not personal demographics predicted work-family conflict. Spouse support had no effect on work-family conflict but reduced family-work conflict. Both work-family conflict and family-work conflict were associated with less work satisfaction and greater psychological distress.

  11. Single-trial prediction of reaction time variability from MEG brain activity.

    PubMed

    Ohata, Ryu; Ogawa, Kenji; Imamizu, Hiroshi

    2016-06-02

    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.

  12. 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

  13. 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.

  14. 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

  15. 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.

  16. 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

  17. Prediction of color changes using the time-temperature superposition principle in liquid formulations.

    PubMed

    Mochizuki, Koji; Takayama, Kozo

    2014-01-01

    This study reports the results of applying the time-temperature superposition principle (TTSP) to the prediction of color changes in liquid formulations. A sample solution consisting of L-tryptophan and glucose was used as the model liquid formulation for the Maillard reaction. After accelerated aging treatment at elevated temperatures, the Commission Internationale de l'Eclairage (CIE) LAB color parameters (a*, b*, L*, and E*ab) of the sample solution were measured using a spectrophotometer. The TTSP was then applied to a kinetic analysis of the color changes. The calculated values of the apparent activation energy of a*, b*, L*, and ΔE*ab were 105.2, 109.8, 91.6, and 103.7 kJ/mol, respectively. The predicted values of the color parameters at 40°C were calculated using Arrhenius plots for each of the color parameters. A comparison of the relationships between the experimental and predicted values of each color parameter revealed the coefficients of determination for a*, b*, L*, and ΔE*ab to be 0.961, 0.979, 0.960, and 0.979, respectively. All the R(2) values were sufficiently high, and these results suggested that the prediction was highly reliable. Kinetic analysis using the TTSP was successfully applied to calculating the apparent activation energy and to predicting the color changes at any temperature or duration. PMID:25450630

  18. 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

  19. 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

  20. 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

  1. 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

  2. Predicting the Incidence of Smear Positive Tuberculosis Cases in Iran Using Time Series Analysis

    PubMed Central

    MOOSAZADEH, Mahmood; KHANJANI, Narges; NASEHI, Mahshid; BAHRAMPOUR, Abbas

    2015-01-01

    Background: Determining the temporal variation and forecasting the incidence of smear positive tuberculosis (TB) can play an important role in promoting the TB control program. Its results may be used as a decision-supportive tool for planning and allocating resources. The present study forecasts the incidence of smear positive TB in Iran. Methods: This a longitudinal study using monthly tuberculosis incidence data recorded in the Iranian National Tuberculosis Control Program. The sum of registered cases in each month created 84 time points. Time series methods were used for analysis. Based on the residual chart of ACF, PACF, Ljung-Box tests and the lowest levels of AIC and BIC, the most suitable model was selected. Results: From April 2005 until March 2012, 34012 smear positive TB cases were recorded. The mean of TB monthly incidence was 404.9 (SD=54.7). The highest number of cases was registered in May and the difference in monthly incidence of smear positive TB was significant (P<0.001). SARIMA (0,1,1)(0,1,1)12 was selected as the most adequate model for prediction. It was predicted that the incidence of smear positive TB for 2015 will be about 9.8 per 100,000 people. Conclusion: Based on the seasonal pattern of smear positive TB recorded cases, seasonal ARIMA model was suitable for predicting its incidence. Meanwhile, prediction results show an increasing trend of smear positive TB cases in Iran. PMID:26744711

  3. Nursing in the South.

    ERIC Educational Resources Information Center

    Flitter, Hessel H.

    National needs for 1975 have been projected at 450 nurses per 100,000 population. For the South to reach a goal of 300 would require that graduations be increased by 1975 to nearly four times the number graduated in 1966. Practical nurse programs have nearly doubled since 1960; in the last six years, the number of associate degree programs has…

  4. 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.

  5. 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.

  6. PREDICTING OUTCOMES IN PATIENTS WITH CHRONIC MYELOID LEUKEMIA AT ANY TIME DURING TYROSINE KINASE INHIBITOR THERAPY

    PubMed Central

    Quintás-Cardama, Alfonso; Choi, Sangbum; Kantarjian, Hagop; Jabbour, Elias; Huang, Xuelin; Cortes, Jorge

    2014-01-01

    Current recommendations for monitoring patients with chronic myeloid leukemia (CML) provide recommendations for response assessment and treatment only at 3, 6, 12, and 18 months. These recommendations are based on clinical trial outcomes computed from treatment start. Conditional survival estimates take into account the changing hazard rates as time from treatment elapses as a continuum. We performed conditional survival analyses among patients with CML to improve prognostication at any time point during the course of therapy. We used two cohorts of patients with CML in chronic phase: one treated in the frontline DASISION phase III study (n=519) and another treated after imatinib failure in the dasatinib dose-optimization phase III CA180-034 study (n=670). Conditional survival estimates were calculated. A modified Cox proportional hazards model was used to build a prognostic nomogram. As the time alive or free from events from commencement of treatment increased, conditional survival estimates changed. No differences were observed regarding future outcomes between patients treated with imatinib or dasatinib in the frontline setting for patients with the same BCR-ABL1 transcript levels evaluated at the same time-point. Age over 60 years greatly impacted future outcomes particularly in the short-term. Conditional survival-based nomograms allowed the prediction of future outcomes at any time-point. In summary, we designed a calculator to predict future outcomes of patients with CML at any time-point during the course of therapy. PMID:24594142

  7. 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

  8. 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

  9. Variability of single trial brain activation predicts fluctuations in reaction time.

    PubMed

    Bender, Stephan; Banaschewski, Tobias; Roessner, Veit; Klein, Christoph; Rietschel, Marcella; Feige, Bernd; Brandeis, Daniel; Laucht, Manfred

    2015-03-01

    Brain activation stability is crucial to understanding attention lapses. EEG methods could provide excellent markers to assess neuronal response variability with respect to temporal (intertrial coherence) and spatial variability (topographic consistency) as well as variations in activation intensity (low frequency variability of single trial global field power). We calculated intertrial coherence, topographic consistency and low frequency amplitude variability during target P300 in a continuous performance test in 263 15-year-olds from a cohort with psychosocial and biological risk factors. Topographic consistency and low frequency amplitude variability predicted reaction time fluctuations (RTSD) in a linear model. Higher RTSD was only associated with higher psychosocial adversity in the presence of the homozygous 6R-10R dopamine transporter haplotype. We propose that topographic variability of single trial P300 reflects noise as well as variability in evoked cortical activation patterns. Dopaminergic neuromodulation interacted with environmental and biological risk factors to predict behavioural reaction time variability.

  10. 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

  11. Real-time prediction of clinical trial enrollment and event counts: A review.

    PubMed

    Heitjan, Daniel F; Ge, Zhiyun; Ying, Gui-Shuang

    2015-11-01

    Clinical trial planning involves the specification of a projected duration of enrollment and follow-up needed to achieve the targeted study power. If pre-trial estimates of enrollment and event rates are inaccurate, projections can be faulty, leading potentially to inadequate power or other mis-allocation of resources. Recent years have witnessed the development of methods that use the accumulating data from the trial itself to create improved predictions in real time. We review these methods, taking as a case study REMATCH, a trial that compared a left-ventricular assist device to optimal medical management in the treatment of end-stage heart failure. REMATCH provided the motivation and test bed for the first real-time clinical trial prediction model. Our review summarizes developments to date and points to unresolved issues and open research opportunities. PMID:26188165

  12. 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.

  13. Predicting the time-temperature dependent axial failure of B/A1 composites

    NASA Technical Reports Server (NTRS)

    Dicarlo, J. A.

    1980-01-01

    Experimental and theoretical studies were conducted in order to understand and predict the effects of time, temperature, and stress on the axial failure modes of boron fibers and B/A1 composites. Due to the anelastic nature of boron fiber deformation, it was possible to determine simple creep functions which can be employed to accurately describe creep and fracture stress of as-produced fibers. Analysis of damping and strength data for B/6061 A1 composites indicates that fiber creep effects of creep on fiber fracture are measurably reduced by the composite fabrication process. The creep function appropriate for fibers with B/Al composites was also determined. A fracture theory is presented for predicting the time-temperature dependence of the axial tensile strength for metal matrix composites in general and B/A1 composites in particular.

  14. 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.

  15. A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model

    PubMed Central

    Niu, Jian; Zhao, Jun; Xu, Zuhua; Qian, Jixin

    2009-01-01

    A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. PMID:19834542

  16. 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.

  17. 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

  18. 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.

  19. 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.

  20. Thermodynamic-based retention time predictions of endogenous steroids in comprehensive two-dimensional gas chromatography.

    PubMed

    Silva, Aline C A; Ebrahimi-Najafadabi, Heshmatollah; McGinitie, Teague M; Casilli, Alessandro; Pereira, Henrique M G; Aquino Neto, Francisco R; Harynuk, James J

    2015-05-01

    This work evaluates the application of a thermodynamic model to comprehensive two-dimensional gas chromatography (GC × GC) coupled with time-of-flight mass spectrometry for anabolic agent investigation. Doping control deals with hundreds of drugs that are prohibited in sports. Drug discovery in biological matrices is a challenging task that requires powerful tools when one is faced with the rapidly changing designer drug landscape. In this work, a thermodynamic model developed for the prediction of both primary and secondary retention times in GC × GC has been applied to trimethylsilylated hydroxyl (O-TMS)- and methoxime-trimethylsilylated carbonyl (MO-TMS)-derivatized endogenous steroids. This model was previously demonstrated on a pneumatically modulated GC × GC system, and is applied for the first time to a thermally modulated GC × GC system. Preliminary one-dimensional experiments allowed the calculation of thermodynamic parameters (ΔH, ΔS, and ΔC p ) which were successfully applied for the prediction of the analytes' interactions with the stationary phases of both the first-dimension column and the second-dimension column. The model was able to predict both first-dimension and second-dimension retention times with high accuracy compared with the GC × GC experimental measurements. Maximum differences of -8.22 s in the first dimension and 0.4 s in the second dimension were encountered for the O-TMS derivatives of 11β-hydroxyandrosterone and 11-ketoetiocholanolone, respectively. For the MO-TMS derivatives, the largest discrepancies were from testosterone (9.65 ) for the first-dimension retention times and 11-keto-etiocholanolone (0.4 s) for the second-dimension retention times.

  1. Effects of time-averaging climate parameters on predicted multicompartmental fate of pesticides and POPs.

    PubMed

    Lammel, Gerhard

    2004-01-01

    With the aim to investigate the justification of time-averaging of climate parameters in multicompartment modelling the effects of various climate parameters and different modes of entry on the predicted substances' total environmental burdens and the compartmental fractions were studied. A simple, non-steady state zero-dimensional (box) mass-balance model of intercompartmental mass exchange which comprises four compartments was used for this purpose. Each two runs were performed, one temporally unresolved (time-averaged conditions) and a time-resolved (hourly or higher) control run. In many cases significant discrepancies are predicted, depending on the substance and on the parameter. We find discrepancies exceeding 10% relative to the control run and up to an order of magnitude for prediction of the total environmental burden from neglecting seasonalities of the soil and ocean temperatures and the hydroxyl radical concentration in the atmosphere and diurnalities of atmospheric mixing depth and the hydroxyl radical concentration in the atmosphere. Under some conditions it was indicated that substance sensitivity could be explained by the magnitude of the sink terms in the compartment(s) with parameters varying. In general, however, any key for understanding substance sensitivity seems not be linked in an easy manner to the properties of the substance, to the fractions of its burden or to the sink terms in either of the compartments with parameters varying. Averaging of diurnal variability was found to cause errors of total environmental residence time of different sign for different substances. The effects of time-averaging of several parameters are in general not additive but synergistic as well as compensatory effects occur. An implication of these findings is that the ranking of substances according to persistence is sensitive to time resolution on the scale of hours to months. As a conclusion it is recommended to use high temporal resolution in multi

  2. Predicting The Time And Location For Shallow Landslide Occurrence In Northern Taiwan

    NASA Astrophysics Data System (ADS)

    Ho, J.; Lee, K.

    2007-12-01

    The topographic, geological and hydrologic conditions of Taiwan usually induce landslide and debris flow during heavy rainstorms. Poor geological conditions induce a high potential to cause hillslope disasters, and severe rainstorms often trigger slope collapses. The objective of this study is to link a slope-instability analytical procedure to a watershed runoff model for landslide prediction during heavy rainfall periods. The analytical result can provide location and time for shallow landslide occurrences to authorities for disaster warning and evacuation. In this study, hydrologic records and geological information from the Da-Tsu-Keng watershed and Chon-Ho watershed in Taipei County were collected for analysis. By using the hourly rainfall data, the varying of the water table on the hillslope was simulated using a hydrological model, and the temporal water level was then used in the slope instability analysis to predict instability grids within the study areas. The results show that more than 50% area of the study subwatershed was considered having potential for landslide occurrence during a severe typhoon in November 2000. The predicted landslide region and occurrence time matched well with the field investigation data. It is therefore considered promising to apply the proposed analytical procedure for real- time landslide warning to alleviate the loss of lives and property.

  3. 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.

  4. 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).

  5. Fast and accurate numerical method for predicting gas chromatography retention time.

    PubMed

    Claumann, Carlos Alberto; Wüst Zibetti, André; Bolzan, Ariovaldo; Machado, Ricardo A F; Pinto, Leonel Teixeira

    2015-08-01

    Predictive modeling for gas chromatography compound retention depends on the retention factor (ki) and on the flow of the mobile phase. Thus, different approaches for determining an analyte ki in column chromatography have been developed. The main one is based on the thermodynamic properties of the component and on the characteristics of the stationary phase. These models can be used to estimate the parameters and to optimize the programming of temperatures, in gas chromatography, for the separation of compounds. Different authors have proposed the use of numerical methods for solving these models, but these methods demand greater computational time. Hence, a new method for solving the predictive modeling of analyte retention time is presented. This algorithm is an alternative to traditional methods because it transforms its attainments into root determination problems within defined intervals. The proposed approach allows for tr calculation, with accuracy determined by the user of the methods, and significant reductions in computational time; it can also be used to evaluate the performance of other prediction methods.

  6. 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

  7. 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.

  8. Thermal time constant: optimising the skin temperature predictive modelling in lower limb prostheses using Gaussian processes

    PubMed Central

    Buis, Arjan

    2016-01-01

    Elevated skin temperature at the body/device interface of lower-limb prostheses is one of the major factors that affect tissue health. The heat dissipation in prosthetic sockets is greatly influenced by the thermal conductive properties of the hard socket and liner material employed. However, monitoring of the interface temperature at skin level in lower-limb prosthesis is notoriously complicated. This is due to the flexible nature of the interface liners used which requires consistent positioning of sensors during donning and doffing. Predicting the residual limb temperature by monitoring the temperature between socket and liner rather than skin and liner could be an important step in alleviating complaints on increased temperature and perspiration in prosthetic sockets. To predict the residual limb temperature, a machine learning algorithm – Gaussian processes is employed, which utilizes the thermal time constant values of commonly used socket and liner materials. This Letter highlights the relevance of thermal time constant of prosthetic materials in Gaussian processes technique which would be useful in addressing the challenge of non-invasively monitoring the residual limb skin temperature. With the introduction of thermal time constant, the model can be optimised and generalised for a given prosthetic setup, thereby making the predictions more reliable. PMID:27695626

  9. Prospective versus predictive control in timing of hitting a falling ball.

    PubMed

    Katsumata, Hiromu; Russell, Daniel M

    2012-02-01

    Debate exists as to whether humans use prospective or predictive control to intercept an object falling under gravity (Baurès et al. in Vis Res 47:2982-2991, 2007; Zago et al. in Vis Res 48:1532-1538, 2008). Prospective control involves using continuous information to regulate action. τ, the ratio of the size of the gap to the rate of gap closure, has been proposed as the information used in guiding interceptive actions prospectively (Lee in Ecol Psychol 10:221-250, 1998). This form of control is expected to generate movement modulation, where variability decreases over the course of an action based upon more accurate timing information. In contrast, predictive control assumes that a pre-programmed movement is triggered at an appropriate criterion timing variable. For a falling object it is commonly argued that an internal model of gravitational acceleration is used to predict the motion of the object and determine movement initiation. This form of control predicts fixed duration movements initiated at consistent time-to-contact (TTC), either across conditions (constant criterion operational timing) or within conditions (variable criterion operational timing). The current study sought to test predictive and prospective control hypotheses by disrupting continuous visual information of a falling ball and examining consistency in movement initiation and duration, and evidence for movement modulation. Participants (n = 12) batted a ball dropped from three different heights (1, 1.3 and 1.5 m), under both full-vision and partial occlusion conditions. In the occlusion condition, only the initial ball drop and the final 200 ms of ball flight to the interception point could be observed. The initiation of the swing did not occur at a consistent TTC, τ, or any other timing variable across drop heights, in contrast with previous research. However, movement onset was not impacted by occluding the ball flight for 280-380 ms. This finding indicates that humans did not

  10. 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.

  11. 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

  12. Anthroposophical nursing.

    PubMed

    Therkleson, Tessa

    2005-10-01

    Anthroposophical nursing evolved out of a striving to maintain the human caring and loving warmth of nursing practice whilst having cognisance of academic rigor and scientific nursing research. It is an extension of traditional nursing requiring inner personal development to accompany a modern scientific approach. PMID:19175263

  13. 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

  14. 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

  15. 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

  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.

  17. 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

  18. 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.

  19. [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

  20. 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).

  1. 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.

  2. 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

  3. Predicting Developmental Timing for Immature Canada Thistle Stem-Mining Weevils, Hadroplontus litura (Coleoptera: Curculionidae).

    PubMed

    Gramig, Greta G; Burns, Erin E; Prischmann-Voldseth, Deirdre A

    2015-08-01

    Predictions of phenological development for insect biological control agents may facilitate post-release monitoring efforts by allowing land managers to optimize the timing of monitoring activities. A logistic thermal time model was tested to predict phenology of immature stem-mining weevils, Hadroplontus litura F. (Coleoptera: Curculionidae), a biological control agent for Canada thistle, Cirsium arvense L. (Asterales: Asteraceae). Weevil eggs and larvae were collected weekly from Canada thistle stems in eastern North Dakota from May through July during 2010 and 2011. Head capsule widths of sampled larvae were measured at the widest point and plotted on a frequency histogram to establish ranges of head capsule widths associated with each instar. We found head capsule width ranges for first-, second-, and third-instar H. litura larvae were 165-324 µm, 346-490 µm, and 506-736 µm, respectively. Logistic regression models were developed to estimate the proportions of H. litura eggs, first-, and second-instar larvae in the weevil population as a function of thermal time. Model estimates of median development time for eggs, first instars, and second instars ranged from 219 ± 23 degree-days (DD) to 255 ± 27 DD, 556 ± 77 DD to 595 ± 81 DD, and 595 ± 109 DD to 653 ± 108 DD, respectively. Based on model validation statistics, model estimates for development timing were the most accurate for eggs and first instars and somewhat less accurate for second instars. These model predictions will help biological control practitioners obtain more accurate estimates of weevil population densities during post-release monitoring. PMID:26314053

  4. 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

  5. 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

  6. Gilligan: a voice for nursing?

    PubMed

    Harbison, J

    1992-12-01

    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.

  7. 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

  8. Time-Delay Neural Network for Continuous Emotional Dimension Prediction From Facial Expression Sequences.

    PubMed

    Meng, Hongying; Bianchi-Berthouze, Nadia; Deng, Yangdong; Cheng, Jinkuang; Cosmas, John P

    2016-04-01

    Automatic continuous affective state prediction from naturalistic facial expression is a very challenging research topic but very important in human-computer interaction. One of the main challenges is modeling the dynamics that characterize naturalistic expressions. In this paper, a novel two-stage automatic system is proposed to continuously predict affective dimension values from facial expression videos. In the first stage, traditional regression methods are used to classify each individual video frame, while in the second stage, a time-delay neural network (TDNN) is proposed to model the temporal relationships between consecutive predictions. The two-stage approach separates the emotional state dynamics modeling from an individual emotional state prediction step based on input features. In doing so, the temporal information used by the TDNN is not biased by the high variability between features of consecutive frames and allows the network to more easily exploit the slow changing dynamics between emotional states. The system was fully tested and evaluated on three different facial expression video datasets. Our experimental results demonstrate that the use of a two-stage approach combined with the TDNN to take into account previously classified frames significantly improves the overall performance of continuous emotional state estimation in naturalistic facial expressions. The proposed approach has won the affect recognition sub-challenge of the Third International Audio/Visual Emotion Recognition Challenge. PMID:25910269

  9. 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.

  10. DNA methylation-based measures of biological age: meta-analysis predicting time to death

    PubMed Central

    Chen, Brian H.; Marioni, Riccardo E.; Colicino, Elena; Peters, Marjolein J.; Ward-Caviness, Cavin K.; Tsai, Pei-Chien; Roetker, Nicholas S.; Just, Allan C.; Demerath, Ellen W.; Guan, Weihua; Bressler, Jan; Fornage, Myriam; Studenski, Stephanie; Vandiver, Amy R.; Moore, Ann Zenobia; Tanaka, Toshiko; Kiel, Douglas P.; Liang, Liming; Vokonas, Pantel; Schwartz, Joel; Lunetta, Kathryn L.; Murabito, Joanne M.; Bandinelli, Stefania; Hernandez, Dena G.; Melzer, David; Nalls, Michael; Pilling, Luke C.; Price, Timothy R.; Singleton, Andrew B.; Gieger, Christian; Holle, Rolf; Kretschmer, Anja; Kronenberg, Florian; Kunze, Sonja; Linseisen, Jakob; Meisinger, Christine; Rathmann, Wolfgang; Waldenberger, Melanie; Visscher, Peter M.; Shah, Sonia; Wray, Naomi R.; McRae, Allan F.; Franco, Oscar H.; Hofman, Albert; Uitterlinden, André G.; Absher, Devin; Assimes, Themistocles; Levine, Morgan E.; Lu, Ake T.; Tsao, Philip S.; Hou, Lifang; Manson, JoAnn E.; Carty, Cara L.; LaCroix, Andrea Z.; Reiner, Alexander P.; Spector, Tim D.; Feinberg, Andrew P.; Levy, Daniel; Baccarelli, Andrea; van Meurs, Joyce; Bell, Jordana T.; Peters, Annette; Deary, Ian J.; Pankow, James S.; Ferrucci, Luigi; Horvath, Steve

    2016-01-01

    Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality. PMID:27690265

  11. 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.

  12. 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

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

    DOE PAGES

    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

  14. Cumulative Time Series Representation for Code Blue prediction in the Intensive Care Unit.

    PubMed

    Salas-Boni, Rebeca; Bai, Yong; Hu, Xiao

    2015-01-01

    Patient monitors in hospitals generate a high number of false alarms that compromise patients care and burden clinicians. In our previous work, an attempt to alleviate this problem by finding combinations of monitor alarms and laboratory test that were predictive of code blue events, called SuperAlarms. Our current work consists of developing a novel time series representation that accounts for both cumulative effects and temporality was developed, and it is applied to code blue prediction in the intensive care unit (ICU). The health status of patients is represented both by a term frequency approach, TF, often used in natural language processing; and by our novel cumulative approach. We call this representation "weighted accumulated occurrence representation", or WAOR. These two representations are fed into a L1 regularized logistic regression classifier, and are used to predict code blue events. Our performance was assessed online in an independent set. We report the sensitivity of our algorithm at different time windows prior to the code blue event, as well as the work-up to detect ratio and the proportion of false code blue detections divided by the number of false monitor alarms. We obtained a better performance with our cumulative representation, retaining a sensitivity close to our previous work while improving the other metrics. PMID:26306261

  15. Predicting demographically sustainable rates of adaptation: can great tit breeding time keep pace with climate change?

    PubMed

    Gienapp, Phillip; Lof, Marjolein; Reed, Thomas E; McNamara, John; Verhulst, Simon; Visser, Marcel E

    2013-01-19

    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.

  16. 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).

  17. 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

  18. Dual-orthogonal radial basis function networks for nonlinear time series prediction.

    PubMed

    Hong, X; Billings, Steve A.

    1998-04-01

    A new structure of Radial Basis Function (RBF) neural network called the Dual-orthogonal RBF Network (DRBF) is introduced for nonlinear time series prediction. The hidden nodes of a conventional RBF network compare the Euclidean distance between the network input vector and the centres, and the node responses are radially symmetrical. But in time series prediction where the system input vectors are lagged system outputs, which are usually highly correlated, the Euclidean distance measure may not be appropriate. The DRBF network modifies the distance metric by introducing a classification function which is based on the estimation data set. Training the DRBF networks consists of two stages. Learning the classification related basis functions and the important input nodes, followed by selecting the regressors and learning the weights of the hidden nodes. In both cases, a forward Orthogonal Least Squares (OLS) selection procedure is applied, initially to select the important input nodes and then to select the important centres. Simulation results of single-step and multi-step ahead predictions over a test data set are included to demonstrate the effectiveness of the new approach.

  19. 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

  20. 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

  1. 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

  2. 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.

  3. Mortality Prediction in ICUs Using A Novel Time-Slicing Cox Regression Method.

    PubMed

    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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China.

    PubMed

    Pi, Erxu; Qu, Liqun; Tang, Xi; Peng, Tingting; Jiang, Bo; Guo, Jiangfeng; Lu, Hongfei; Du, Liqun

    2015-01-01

    Temperature is a predominant environmental factor affecting grass germination and distribution. Various thermal-germination models for prediction of grass seed germination have been reported, in which the relationship between temperature and germination were defined with kernel functions, such as quadratic or quintic function. However, their prediction accuracies warrant further improvements. The purpose of this study is to evaluate the relative prediction accuracies of genetic algorithm (GA) models, which are automatically parameterized with observed germination data. The seeds of five P. pratensis (Kentucky bluegrass, KB) cultivars were germinated under 36 day/night temperature regimes ranging from 5/5 to 40/40 °C with 5 °C increments. Results showed that optimal germination percentages of all five tested KB cultivars were observed under a fluctuating temperature regime of 20/25 °C. Meanwhile, the constant temperature regimes (e.g., 5/5, 10/10, 15/15 °C, etc.) suppressed the germination of all five cultivars. Furthermore, the back propagation artificial neural network (BP-ANN) algorithm was integrated to optimize temperature-germination response models from these observed germination data. It was found that integrations of GA-BP-ANN (back propagation aided genetic algorithm artificial neural network) significantly reduced the Root Mean Square Error (RMSE) values from 0.21~0.23 to 0.02~0.09. In an effort to provide a more reliable prediction of optimum sowing time for the tested KB cultivars in various regions in the country, the optimized GA-BP-ANN models were applied to map spatial and temporal germination percentages of blue grass cultivars in China. Our results demonstrate that the GA-BP-ANN model is a convenient and reliable option for constructing thermal-germination response models since it automates model parameterization and has excellent prediction accuracy. PMID:26154163

  9. Application of Genetic Algorithm to Predict Optimal Sowing Region and Timing for Kentucky Bluegrass in China

    PubMed Central

    Peng, Tingting; Jiang, Bo; Guo, Jiangfeng; Lu, Hongfei; Du, Liqun

    2015-01-01

    Temperature is a predominant environmental factor affecting grass germination and distribution. Various thermal-germination models for prediction of grass seed germination have been reported, in which the relationship between temperature and germination were defined with kernel functions, such as quadratic or quintic function. However, their prediction accuracies warrant further improvements. The purpose of this study is to evaluate the relative prediction accuracies of genetic algorithm (GA) models, which are automatically parameterized with observed germination data. The seeds of five P. pratensis (Kentucky bluegrass, KB) cultivars were germinated under 36 day/night temperature regimes ranging from 5/5 to 40/40°C with 5°C increments. Results showed that optimal germination percentages of all five tested KB cultivars were observed under a fluctuating temperature regime of 20/25°C. Meanwhile, the constant temperature regimes (e.g., 5/5, 10/10, 15/15°C, etc.) suppressed the germination of all five cultivars. Furthermore, the back propagation artificial neural network (BP-ANN) algorithm was integrated to optimize temperature-germination response models from these observed germination data. It was found that integrations of GA-BP-ANN (back propagation aided genetic algorithm artificial neural network) significantly reduced the Root Mean Square Error (RMSE) values from 0.21~0.23 to 0.02~0.09. In an effort to provide a more reliable prediction of optimum sowing time for the tested KB cultivars in various regions in the country, the optimized GA-BP-ANN models were applied to map spatial and temporal germination percentages of blue grass cultivars in China. Our results demonstrate that the GA-BP-ANN model is a convenient and reliable option for constructing thermal-germination response models since it automates model parameterization and has excellent prediction accuracy. PMID:26154163

  10. The effects of incidentally learned temporal and spatial predictability on response times and visual fixations during target detection and discrimination.

    PubMed

    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.

  11. Obtaining Reliable Predictions of Terrestrial Energy Coupling From Real-Time Solar Wind Measurement

    NASA Technical Reports Server (NTRS)

    Weimer, Daniel R.

    2001-01-01

    The first draft of a manuscript titled "Variable time delays in the propagation of the interplanetary magnetic field" has been completed, for submission to the Journal of Geophysical Research. In the preparation of this manuscript all data and analysis programs had been updated to the highest temporal resolution possible, at 16 seconds or better. The program which computes the "measured" IMF propagation time delays from these data has also undergone another improvement. In another significant development, a technique has been developed in order to predict IMF phase plane orientations, and the resulting time delays, using only measurements from a single satellite at L1. The "minimum variance" method is used for this computation. Further work will be done on optimizing the choice of several parameters for the minimum variance calculation.

  12. Real-Time Eddy-Resolving Ocean Prediction in the Caribbean

    NASA Astrophysics Data System (ADS)

    Hurlburt, H. E.; Smedstad, O. M.; Shriver, J. F.; Townsend, T. L.; Murphy, S. J.

    2001-12-01

    A {1/16}o eddy-resolving, nearly global ocean prediction system has been developed by the Naval Research Laboratory (NRL), Stennis Space Center, MS. It has been run in real-time by the Naval Oceanographic Office (NAVO), Stennis Space Center, MS since 18 Oct 2000 with daily updates for the nowcast and 30-day forecasts performed every Wednesday. The model has ~8 km resolution in the Caribbean region and assimilates real-time altimeter sea surface height (SSH) data from ERS-2, GFO and TOPEX/POSEIDON plus multi-channel sea surface temperature (MCSST) from satellite IR. Real-time and archived results from the system can be seen at web site: http://www7320.nrlssc.navy.mil/global\

  13. Gradient radial basis function networks for nonlinear and nonstationary time series prediction.

    PubMed

    Chng, E S; Chen, S; Mulgrew, B

    1996-01-01

    We present a method of modifying the structure of radial basis function (RBF) network to work with nonstationary series that exhibit homogeneous nonstationary behavior. In the original RBF network, the hidden node's function is to sense the trajectory of the time series and to respond when there is a strong correlation between the input pattern and the hidden node's center. This type of response, however, is highly sensitive to changes in the level and trend of the time series. To counter these effects, the hidden node's function is modified to one which detects and reacts to the gradient of the series. We call this new network the gradient RBF (GRBF) model. Single and multistep predictive performance for the Mackey-Glass chaotic time series were evaluated using the classical RBF and GRBF models. The simulation results for the series without and with a tine-varying mean confirm the superior performance of the GRBF predictor over the RBF predictor.

  14. Spontaneous Fluctuations in Sensory Processing Predict Within-Subject Reaction Time Variability.

    PubMed

    Ribeiro, Maria J; Paiva, Joana S; Castelo-Branco, Miguel

    2016-01-01

    When engaged in a repetitive task our performance fluctuates from trial-to-trial. In particular, inter-trial reaction time variability has been the subject of considerable research. It has been claimed to be a strong biomarker of attention deficits, increases with frontal dysfunction, and predicts age-related cognitive decline. Thus, rather than being just a consequence of noise in the system, it appears to be under the control of a mechanism that breaks down under certain pathological conditions. Although the underlying mechanism is still an open question, consensual hypotheses are emerging regarding the neural correlates of reaction time inter-trial intra-individual variability. Sensory processing, in particular, has been shown to covary with reaction time, yet the spatio-temporal profile of the moment-to-moment variability in sensory processing is still poorly characterized. The goal of this study was to characterize the intra-individual variability in the time course of single-trial visual evoked potentials and its relationship with inter-trial reaction time variability. For this, we chose to take advantage of the high temporal resolution of the electroencephalogram (EEG) acquired while participants were engaged in a 2-choice reaction time task. We studied the link between single trial event-related potentials (ERPs) and reaction time using two different analyses: (1) time point by time point correlation analyses thereby identifying time windows of interest; and (2) correlation analyses between single trial measures of peak latency and amplitude and reaction time. To improve extraction of single trial ERP measures related with activation of the visual cortex, we used an independent component analysis (ICA) procedure. Our ERP analysis revealed a relationship between the N1 visual evoked potential and reaction time. The earliest time point presenting a significant correlation of its respective amplitude with reaction time occurred 175 ms after stimulus onset

  15. Spontaneous Fluctuations in Sensory Processing Predict Within-Subject Reaction Time Variability

    PubMed Central

    Ribeiro, Maria J.; Paiva, Joana S.; Castelo-Branco, Miguel

    2016-01-01

    When engaged in a repetitive task our performance fluctuates from trial-to-trial. In particular, inter-trial reaction time variability has been the subject of considerable research. It has been claimed to be a strong biomarker of attention deficits, increases with frontal dysfunction, and predicts age-related cognitive decline. Thus, rather than being just a consequence of noise in the system, it appears to be under the control of a mechanism that breaks down under certain pathological conditions. Although the underlying mechanism is still an open question, consensual hypotheses are emerging regarding the neural correlates of reaction time inter-trial intra-individual variability. Sensory processing, in particular, has been shown to covary with reaction time, yet the spatio-temporal profile of the moment-to-moment variability in sensory processing is still poorly characterized. The goal of this study was to characterize the intra-individual variability in the time course of single-trial visual evoked potentials and its relationship with inter-trial reaction time variability. For this, we chose to take advantage of the high temporal resolution of the electroencephalogram (EEG) acquired while participants were engaged in a 2-choice reaction time task. We studied the link between single trial event-related potentials (ERPs) and reaction time using two different analyses: (1) time point by time point correlation analyses thereby identifying time windows of interest; and (2) correlation analyses between single trial measures of peak latency and amplitude and reaction time. To improve extraction of single trial ERP measures related with activation of the visual cortex, we used an independent component analysis (ICA) procedure. Our ERP analysis revealed a relationship between the N1 visual evoked potential and reaction time. The earliest time point presenting a significant correlation of its respective amplitude with reaction time occurred 175 ms after stimulus onset

  16. Spontaneous Fluctuations in Sensory Processing Predict Within-Subject Reaction Time Variability.

    PubMed

    Ribeiro, Maria J; Paiva, Joana S; Castelo-Branco, Miguel

    2016-01-01

    When engaged in a repetitive task our performance fluctuates from trial-to-trial. In particular, inter-trial reaction time variability has been the subject of considerable research. It has been claimed to be a strong biomarker of attention deficits, increases with frontal dysfunction, and predicts age-related cognitive decline. Thus, rather than being just a consequence of noise in the system, it appears to be under the control of a mechanism that breaks down under certain pathological conditions. Although the underlying mechanism is still an open question, consensual hypotheses are emerging regarding the neural correlates of reaction time inter-trial intra-individual variability. Sensory processing, in particular, has been shown to covary with reaction time, yet the spatio-temporal profile of the moment-to-moment variability in sensory processing is still poorly characterized. The goal of this study was to characterize the intra-individual variability in the time course of single-trial visual evoked potentials and its relationship with inter-trial reaction time variability. For this, we chose to take advantage of the high temporal resolution of the electroencephalogram (EEG) acquired while participants were engaged in a 2-choice reaction time task. We studied the link between single trial event-related potentials (ERPs) and reaction time using two different analyses: (1) time point by time point correlation analyses thereby identifying time windows of interest; and (2) correlation analyses between single trial measures of peak latency and amplitude and reaction time. To improve extraction of single trial ERP measures related with activation of the visual cortex, we used an independent component analysis (ICA) procedure. Our ERP analysis revealed a relationship between the N1 visual evoked potential and reaction time. The earliest time point presenting a significant correlation of its respective amplitude with reaction time occurred 175 ms after stimulus onset

  17. Beyond Rating Curves: Time Series Models for in-Stream Turbidity Prediction

    NASA Astrophysics Data System (ADS)

    Wang, L.; Mukundan, R.; Zion, M.; Pierson, D. C.

    2012-12-01

    The New York City Department of Environmental Protection (DEP) manages New York City's water supply, which is comprised of over 20 reservoirs and supplies over 1 billion gallons of water per day to more than 9 million customers. DEP's "West of Hudson" reservoirs located in the Catskill Mountains are unfiltered per a renewable filtration avoidance determination granted by the EPA. While water quality is usually pristine, high volume storm events occasionally cause the reservoirs to become highly turbid. A logical strategy for turbidity control is to temporarily remove the turbid reservoirs from service. While effective in limiting delivery of turbid water and reducing the need for in-reservoir alum flocculation, this strategy runs the risk of negatively impacting water supply reliability. Thus, it is advantageous for DEP to understand how long a particular turbidity event will affect their system. In order to understand the duration, intensity and total load of a turbidity event, predictions of future in-stream turbidity values are important. Traditionally, turbidity predictions have been carried out by applying streamflow observations/forecasts to a flow-turbidity rating curve. However, predictions from rating curves are often inaccurate due to inter- and intra-event variability in flow-turbidity relationships. Predictions can be improved by applying an autoregressive moving average (ARMA) time series model in combination with a traditional rating curve. Since 2003, DEP and the Upstate Freshwater Institute have compiled a relatively consistent set of 15-minute turbidity observations at various locations on Esopus Creek above Ashokan Reservoir. Using daily averages of this data and streamflow observations at nearby USGS gauges, flow-turbidity rating curves were developed via linear regression. Time series analysis revealed that the linear regression residuals may be represented using an ARMA(1,2) process. Based on this information, flow-turbidity regressions with

  18. Assessing time-integrated dissolved concentrations and predicting toxicity of metals during diel cycling in streams

    USGS Publications Warehouse

    Balistrieri, Laurie S.; Nimick, David A.; Mebane, Christopher A.

    2012-01-01

    Evaluating water quality and the health of aquatic organisms is challenging in systems with systematic diel (24 hour) or less predictable runoff-induced changes in water composition. To advance our understanding of how to evaluate environmental health in these dynamic systems, field studies of diel cycling were conducted in two streams (Silver Bow Creek and High Ore Creek) affected by historical mining activities in southwestern Montana. A combination of sampling and modeling tools were used to assess the toxicity of metals in these systems. Diffusive Gradients in Thin Films (DGT) samplers were deployed at multiple time intervals during diel sampling to confirm that DGT integrates time-varying concentrations of dissolved metals. Thermodynamic speciation calculations using site specific water compositions, including time-integrated dissolved metal concentrations determined from DGT, and a competitive, multiple-metal biotic ligand model incorporated into the Windemere Humic Aqueous Model Version 6.0 (WHAM VI) were used to determine the chemical speciation of dissolved metals and biotic ligands. The model results were combined with previously collected toxicity data on cutthroat trout to derive a relationship that predicts the relative survivability of these fish at a given site. This integrative approach may prove useful for assessing water quality and toxicity of metals to aquatic organisms in dynamic systems and evaluating whether potential changes in environmental health of aquatic systems are due to anthropogenic activities or natural variability.

  19. Assessing time-integrated dissolved concentrations and predicting toxicity of metals during diel cycling in streams

    USGS Publications Warehouse

    Balistrieri, Laurie S.; Nimick, David A.; Mebane, Christopher A.

    2012-01-01

    Evaluating water quality and the health of aquatic organisms is challenging in systems with systematic diel (24 h) or less predictable runoff-induced changes in water composition. To advance our understanding of how to evaluate environmental health in these dynamic systems, field studies of diel cycling were conducted in two streams (Silver Bow Creek and High Ore Creek) affected by historical mining activities in southwestern Montana. A combination of sampling and modeling tools was used to assess the toxicity of metals in these systems. Diffusive Gradients in Thin Films (DGT) samplers were deployed at multiple time intervals during diel sampling to confirm that DGT integrates time-varying concentrations of dissolved metals. Site specific water compositions, including time-integrated dissolved metal concentrations determined from DGT, a competitive, multiple-toxicant biotic ligand model, and the Windemere Humic Aqueous Model Version 6.0 (WHAM VI) were used to determine the equilibrium speciation of dissolved metals and biotic ligands. The model results were combined with previously collected toxicity data on cutthroat trout to derive a relationship that predicts the relative survivability of these fish at a given site. This integrative approach may prove useful for assessing water quality and toxicity of metals to aquatic organisms in dynamic systems and evaluating whether potential changes in environmental health of aquatic systems are due to anthropogenic activities or natural variability.

  20. Prediction of traffic-related nitrogen oxides concentrations using Structural Time-Series models

    NASA Astrophysics Data System (ADS)

    Lawson, Anneka Ruth; Ghosh, Bidisha; Broderick, Brian

    2011-09-01

    Ambient air quality monitoring, modeling and compliance to the standards set by European Union (EU) directives and World Health Organization (WHO) guidelines are required to ensure the protection of human and environmental health. Congested urban areas are most susceptible to traffic-related air pollution which is the most problematic source of air pollution in Ireland. Long-term continuous real-time monitoring of ambient air quality at such urban centers is essential but often not realistic due to financial and operational constraints. Hence, the development of a resource-conservative ambient air quality monitoring technique is essential to ensure compliance with the threshold values set by the standards. As an intelligent and advanced statistical methodology, a Structural Time Series (STS) based approach has been introduced in this paper to develop a parsimonious and computationally simple air quality model. In STS methodology, the different components of a time-series dataset such as the trend, seasonal, cyclical and calendar variations can be modeled separately. To test the effectiveness of the proposed modeling strategy, average hourly concentrations of nitrogen dioxide and nitrogen oxides from a congested urban arterial in Dublin city center were modeled using STS methodology. The prediction error estimates from the developed air quality model indicate that the STS model can be a useful tool in predicting nitrogen dioxide and nitrogen oxides concentrations in urban areas and will be particularly useful in situations where the information on external variables such as meteorology or traffic volume is not available.