Science.gov

Sample records for predicting nursing times

  1. Nurse Staffing and Hospital Characteristics Predictive of Time to Diagnostic Evaluation for Patients in the Emergency Department.

    PubMed

    Shindul-Rothschild, Judith; Read, Catherine Y; Stamp, Kelly D; Flanagan, Jane

    2016-10-20

    In the 2014 Emergency Department Benchmarking Alliance Summit, for the first time, participants recommended tracking nursing and advanced practice nurse hours. Performance data from the Centers for Medicare and Medicaid Services provides an opportunity to analyze factors associated with delays in emergency care. The purpose of this study was to investigate hospital characteristics associated with time to a diagnostic evaluation in 67 Massachusetts emergency departments from 2013 to 2014.

  2. A comparison of two nursing program exit exams that predict first-time NCLEX-RN outcome.

    PubMed

    Brodersen, Lisa D; Mills, Andrew C

    2014-08-01

    This retrospective descriptive correlational study compared the predictive accuracy of the Health Education Systems, Inc, Exit Exam (Elsevier) and Assessment Technologies Institute's RN Comprehensive Predictor, both of which were administered to nursing students in an upper-division baccalaureate nursing program during their final semester of study. Using logistic regression analyses, it was determined that the two examinations were statistically significant but weak predictors of success on the RN licensure examination. The RN Comprehensive Predictor had a slightly better odds ratio; however, both examinations had similar sensitivity, specificity, and overall accuracy. Because the RN Comprehensive Predictor was included in the Assessment Technologies Institute's Comprehensive Assessment and Review Program already being used by the BSN program, based on the results of this study, the nursing faculty decided to use only the RN Comprehensive Predictor during its NCLEX-RN preparation course.

  3. Changing how nurses spend their time.

    PubMed

    Prescott, P A; Phillips, C Y; Ryan, J W; Thompson, K O

    1991-01-01

    The results of work sampling studies are used to examine how nurses spend their time and to relate nurses' time to the shortage of nursing practice in hospitals. Four types of proposals for improving the delivery of nursing care in hospitals are discussed. The likely impact of these proposals on how nurses spend their time and the consequences of increasing the effectiveness of professional nursing practice are explored.

  4. 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%…

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

    PubMed

    Jones, Terry L; Yoder, Linda H

    2015-09-01

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

  6. 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…

  7. Mentoring new nurses in stressful times.

    PubMed

    Young, Lisa E

    2009-06-01

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

  8. 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

  9. 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.

  10. Time Spent in Indirect Nursing Care

    DTIC Science & Technology

    1983-09-01

    Part of the FY 83 Army Study Program and intended to augment the FY 81 completed study titled ’ Nursing Care Hours Standards’ by providing valid and...reliable percentages for hospital patient nursing care unit requirements (i.e., direct care, indirect care, and non-productive time). These data

  11. Nurses who do not nurse: factors that predict non-nursing work in the U.S. registered nursing labor market.

    PubMed

    Black, Lisa; Spetz, Joanne; Harrington, Charlene

    2010-01-01

    Registered nurses (RNs) who work outside of nursing have seldom been examined. This aim of this study was to compare the 122,178 (4%) of RNs who are employed outside of nursing to those who work in nursing jobs in terms of sociodemographic, market, and political variables to determine if these groups are substantively different from one another. Using a logit regression model, wages were a significant predictor of working outside of nursing for unmarried nurses but not for married nurses. Married and unmarried male nurses were more likely to work outside of nursing. Baccalaureate education, children under age 6, higher family income, and years since graduation increased the odds of working outside of nursing for married nurses. Ultimately, identifying characteristics on which these groups differ may inform future policy directions that could target nurses who may leave nursing at a time when retention efforts might be effective to alter their trajectory away from the profession.

  12. Prediction of Successful Nursing Performance. Part I and Part II.

    ERIC Educational Resources Information Center

    Schwirian, Patricia M.

    Two of three phases of a study were conducted to (1) assess the state of the art on the prediction of nursing clinical performance and (2) obtain current information from nursing education programs about prediction criteria in use by them. Phase one involved a review of the 1965 through 1975 literature pertaining to studies that focused on the…

  13. [Time, education and nursing training].

    PubMed

    Héron, Myriam

    2012-10-01

    Time is a complex reality. In education, time is a concept, a transversal aid and an omnipresent element. Using the past, practising in the present and anticipating the future are the objectives; but learning is often anchored in the "here and now".

  14. Predicting Nonlinear Time Series

    DTIC Science & Technology

    1993-12-01

    response becomes R,(k) = f (Y FV,(k)) (2.4) where Wy specifies the weight associated with the output of node i to the input of nodej in the next layer and...interconnections for each of these previous nodes. 18 prr~~~o• wfe :t iam i -- ---- --- --- --- Figure 5: Delay block for ATNN [9] Thus, nodej receives the...computed values, aj(tn), and dj(tn) denotes the desired output of nodej at time in. In this thesis, the weights and time delays update after each input

  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. Non-value-added time: the million dollar nursing opportunity.

    PubMed

    Storfjell, Judith Lloyd; Ohlson, Susan; Omoike, Osei; Fitzpatrick, Therese; Wetasin, Kanokwan

    2009-01-01

    The dual crises of high healthcare costs and the nursing shortage require a better understanding of inpatient nursing unit activities and, more specifically, their costs and the drivers of inefficiencies. This includes knowing not only how staff spend their time but also how much of this time is non-value-added (NVA) because wasted time leads to both high costs and nurse dissatisfaction. The authors discuss a study that determined the NVA time and costs of acute care nursing unit staff, identified drivers of high-cost NVA time, and compared activities and costs by type of nursing unit. These data have considerable implications for developing efficient and effective nursing care delivery models and for implementing process improvement and staff satisfaction initiatives.

  17. 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.

  18. 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.

  19. 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…

  20. Pre-Implementation Study of a Nursing e-Chart: How Nurses Use Their Time.

    PubMed

    Schachner, Maria B; Recondo, Francisco J; Sommer, Janine A; González, Zulma A; García, Gabriela M; Luna, Daniel R; Benítez, Sonia E

    2015-01-01

    In clinical practice, nurses perform different activities that exceed direct care of patients, and influence workload and time administration among different tasks. When implementing changes in an electronic nursing record, it is important to measure how it affects the time committed to documentation. The objective of this study was to determine the time dedicated to different activities, including those related to electronic documentation prior to implementing a redesigned nurse chart in an Electronic Health Record at the Hospital Italiano de Buenos Aires. An observational work sampling study was performed. Nursing activities observed were categorized as direct care, indirect care, support, non-patient related, and personal activities. During the study, 74 nurses were observed and 2,418 observations were made in the Intensive Care Unit (32.22%), the Intermediate Care Unit (29.57%), and the General Care Unit (38.21%). Nurses' activities included 37.40% of direct care, 41.18% of indirect care, 0.43% support tasks, 11.14% non-related to patient tasks, and 9.77% personal activities. The results allow for the estimation of the impact of a nursing e-chart on nurses' activities, workflow and patient care.

  1. The lived experience of part-time baccalaureate nursing faculty.

    PubMed

    Gazza, Elizabeth A; Shellenbarger, Teresa

    2010-01-01

    Hiring part-time nursing faculty may impact students, faculty careers, and the institution. Yet, little has been studied, particularly in nursing, regarding the experiences of these faculty. This hermeneutic phenomenological study seeks to understand the lived experience of being a part-time faculty member in a baccalaureate nursing program. Through purposive and snowball sampling, nine nursing faculty in part-time positions in northeastern baccalaureate nursing programs participated in in-depth personal interviews. Four themes were uncovered during data analysis, including achieving the dream, a group divided, for the love of the students, and jump in and figure it out. Results of the study seem to indicate that the experience of being a part-time faculty differs in several ways from being a full-time faculty. Understanding part-time faculty experiences provides insight into faculty needs, issues, and concerns while facilitating the development of research-based recruitment and retention strategies. Recommendations for those involved in nursing education, including nursing faculty and administrators, are provided.

  2. 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.

  3. Predicting academic progression for student registered nurse anesthetists.

    PubMed

    Burns, Sharon M

    2011-06-01

    In order to foster academic progression and improve retention in nurse anesthesia programs, admission selection criteria require attention. With the escalating cost of graduate education coupled with the current economic crisis, efforts by educational leaders to minimize attrition remain pivotal. Selecting potential candidates who are most likely to succeed, aligned with data-driven evidence, offers the greatest potential for academic success for student registered nurse anesthetists. The purpose of this quantitative correlational study was to determine if a relationship existed between admission criteria (grade point average [GPA], science grade point average [SGPA], Graduate Record Examination scores, and critical care experience) and academic progression (current academic status and GPA). Key findings revealed that statistically significant relationships exist between the admission selection criteria and academic progression. Findings also indicated that a combination of the independent variables, specifically the GPA and SGPA, predict academic progression. Further research that includes examination of cognitive and noncognitive admission criteria may offer greater evidence predicting academic performance by student registered nurse anesthetists.

  4. Japanese professional nurses spend unnecessarily long time doing nursing assistants' tasks.

    PubMed

    Kudo, Yasushi; Yoshimura, Emiko; Shahzad, Machiko Taruzuka; Shibuya, Akitaka; Aizawa, Yoshiharu

    2012-01-01

    In environments in which professional nurses do simple tasks, e.g., laundry, cleaning, and waste disposal, they cannot concentrate on technical jobs by utilizing their expertise to its fullest benefit. Particularly, in Japan, the nursing shortage is a serious problem. If professional nurses take their time to do any of these simple tasks, the tasks should be preferentially allocated to nursing assistants. Because there has been no descriptive study to investigate the amount of time Japanese professional nurses spent doing such simple tasks during their working time, their actual conditions remain unclear. Professional nurses recorded their total working time and the time they spent doing such simple tasks during the week of the survey period. The time an individual respondent spent doing one or more simple tasks during that week was summed up, as was their working time. Subsequently, the percentage of the summed time he or she spent doing any of those tasks in his or her summed working time was calculated. A total of 1,086 respondents in 19 hospitals that had 87 to 376 beds were analyzed (response rate: 53.3%). The average time (SD) that respondents spent doing those simple tasks and their total working time were 2.24 (3.35) hours and 37.48 (10.88) hours, respectively. The average percentage (SD) of the time they spent doing the simple tasks in their working time was 6.00% (8.39). Hospital administrators must decrease this percentage. Proper working environments in which professional nurses can concentrate more on their technical jobs must be created.

  5. Methodological Challenges in Examining the Impact of Healthcare Predictive Analytics on Nursing-Sensitive Patient Outcomes.

    PubMed

    Jeffery, Alvin D

    2015-06-01

    The expansion of real-time analytic abilities within current electronic health records has led to innovations in predictive modeling and clinical decision support systems. However, the ability of these systems to influence patient outcomes is currently unknown. Even though nurses are the largest profession within the healthcare workforce, little research has been performed to explore the impact of clinical decision support on their decisions and the patient outcomes associated with them. A scoping literature review explored the impact clinical decision support systems containing healthcare predictive analytics have on four nursing-sensitive patient outcomes (pressure ulcers, failure to rescue, falls, and infections). While many articles discussed variable selection and predictive model development/validation, only four articles examined the impact on patient outcomes. The novelty of predictive analytics and the inherent methodological challenges in studying clinical decision support impact are likely responsible for this paucity of literature. Major methodological challenges include (1) multilevel nature of intervention, (2) treatment fidelity, and (3) adequacy of clinicians' subsequent behavior. There is currently insufficient evidence to demonstrate efficacy of healthcare predictive analytics-enhanced clinical decision support systems on nursing-sensitive patient outcomes. Innovative research methods and a greater emphasis on studying this phenomenon are needed.

  6. Accelerated second-degree nursing students: predictors of graduation and NCLEX-RN first-time pass rates.

    PubMed

    Penprase, Barbara B; Harris, Margaret A

    2013-01-01

    It is important to understand and identify factors that affect students' academic performance before entry into a nursing program and as they progress through the program. The authors discuss a study, and its outcomes, that assessed accelerated second-degree nursing students' prenursing and core nursing grades that served to predict their success at completing the nursing program and passing NCLEX-RN on first attempt. Strategies were identified to help at-risk students to be successful in the program and with first-time passage of NCLEX-RN.

  7. 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

  8. 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…

  9. The Prediction of Success in Nursing Education. Phase III, 1967-1968.

    ERIC Educational Resources Information Center

    Thurston, John R.; And Others

    Specific aims of Phase III, planned as a 4-year program, included: (1) evaluating the efficiency of three instruments--Nursing Sentence Completions (NSC), Nurse Attitudes Inventory (NAI), and Luther Hospital Sentence Completions (LHSC)--for the prediction of success early in nursing school, (2) developing attitudinal area scores for the three…

  10. 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

  11. 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.

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

    Code of Federal Regulations, 2013 CFR

    2013-10-01

    ... registered nurse. 57.313 Section 57.313 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN... in full-time employment as a registered nurse (including teaching in any of the fields of nurse... for full-time employment as a registered nurse will be made by the institution to whose fund his...

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

    Code of Federal Regulations, 2014 CFR

    2014-10-01

    ... registered nurse. 57.313 Section 57.313 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN... in full-time employment as a registered nurse (including teaching in any of the fields of nurse... for full-time employment as a registered nurse will be made by the institution to whose fund his...

  14. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... registered nurse. 57.313 Section 57.313 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN... in full-time employment as a registered nurse (including teaching in any of the fields of nurse... for full-time employment as a registered nurse will be made by the institution to whose fund his...

  15. 42 CFR 57.313 - Loan cancellation for full-time employment as a registered nurse.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... registered nurse. 57.313 Section 57.313 Public Health PUBLIC HEALTH SERVICE, DEPARTMENT OF HEALTH AND HUMAN... in full-time employment as a registered nurse (including teaching in any of the fields of nurse... for full-time employment as a registered nurse will be made by the institution to whose fund his...

  16. An evaluation of the time for nursing activity in a hospital using a full Electronic Medical Record System (EMR).

    PubMed

    Chung, Eun-Ja; Kim, Hyun-Ja; Park, Kwang-Hee; Song, Young-Ae; Lee, Boek-Nam; Lee, Mi-Jeong; Lee, Jeong-Hee; Lee, Hye-A; Lim, Yeon-Sook; Choi, Eun-Young; Hwang, Hye-Young; Lee, Hyun-Sook

    2006-01-01

    This study was designed to analyze the time for direct and indirect nursing activity to evaluate the workload of nurses using a full Electronic Medical Record (EMR) system on practice. The result is that the mean time for nursing activity per nurse was 499.56 minutes, the mean time for direct nursing activity per nurse was 251.1 minutes (50.3%), and the mean time for indirect nursing activity per nurse was 248.42 minutes(49.7%). The time for direct nursing activity was more than the time for indirect nursing activity. There was a significant difference in the time for nursing activity according to workplace (p < 0.00*), but no difference according to nursing career. Regarding 3 duty-shifts, the time for direct nursing activity was highest in the evening shift and the time for indirect nursing activity was highest in the night shift.

  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. 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"…

  19. Prediction of Sucessful Nursing Performance. Part III and Part IV. Health Manpower References.

    ERIC Educational Resources Information Center

    Schwirian, Patricia M.; And Others

    As part of the three-phase national study to provide information to form a basis for predictions about successful nursing performance, a review was conducted of the performance of nursing school graduates at their first jobs. In March, 1976, questionnaires were mailed to a cohort of 1975 graduates who were selected by school officials as having…

  20. Informal Workplace Learning among Nurses: Organisational Learning Conditions and Personal Characteristics That Predict Learning Outcomes

    ERIC Educational Resources Information Center

    Kyndt, Eva; Vermeire, Eva; Cabus, Shana

    2016-01-01

    Purpose: This paper aims to examine which organisational learning conditions and individual characteristics predict the learning outcomes nurses achieve through informal learning activities. There is specific relevance for the nursing profession because of the rapidly changing healthcare systems. Design/Methodology/Approach: In total, 203 nurses…

  1. A Model for Intervention and Predicting Success on the National Council Licensure Examination for Registered Nurses.

    ERIC Educational Resources Information Center

    Heupel, Carol

    1994-01-01

    The relationship of selected academic variables to National Council Licensure Examination for Registered Nurses (NCLEX-RN) performance was studied and a "best set" of indicators predictive of NCLEX-RN success was identified. Results indicated that selected nursing theory courses and the junior year grade point average could be used to…

  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. Predicting National Council Licensure Examination for Registered Nurses Performance

    ERIC Educational Resources Information Center

    Whitehead, Charles D.

    2016-01-01

    The Baccalaureate Nursing program in San Antonio, Texas experienced a decrease in National Council Licensure Examination for Registered Nurses (NCLEX-RN) on the first attempt for students graduating between 2009 and 2014 without a clear explanation for the decline. The purpose of this quantitative non-experimental correlational study was to…

  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. Affective and instrumental communication in primary care interactions: predicting the satisfaction of nursing staff and patients.

    PubMed

    Haskard, Kelly B; DiMatteo, M Robin; Heritage, John

    2009-01-01

    Verbal and nonverbal communication between nursing staff and patients has received scant research attention. This study examined patients' and nursing staff members' global affective and instrumental communication, mutual influence, and relationship to postvisit satisfaction. This study employed ratings of videotaped primary care visits of 81 nursing staff members with 235 patients, and assessed communication in 2 channels: nonverbal visual and speech including vocal tone. Communication channel differences and prediction of patient satisfaction were examined. The visual and vocal communication of nursing staff members and patients robustly predicted each other's satisfaction and reflected their own satisfaction with the dyadic visit. Affect was communicated more clearly through the speech with vocal tone channel, whereas instrumental communication was stronger in visual nonverbal behavior. Patients' and nursing staff members' behaviors of pleasantness and involvement frequently co-occurred.

  6. 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.

  7. Psychosocial work environment and prediction of job satisfaction among Swedish registered nurses and physicians - a follow-up study.

    PubMed

    Jönsson, Sandra

    2012-06-01

    In Sweden, the health care sector was subject to considerable changes during the 1990s: decreased costs, related staff redundancies and high rates of sick leave. The situation has now changed, and the sector is not facing the same all-embracing and turbulent changes. In addition, there is a shortage of nurses and physicians and a difficulty in retaining qualified staff. Regarding the psychosocial work environment, there is a lack of studies where both physicians and nurses are in focus. It is from a managerial perspective important to take a holistic approach towards questions regarding the work environment in general and the psychosocial work environment in particular. The aims of this study were to analyse similarities and differences in Registered Nurses and physicians' experience of quantitative and qualitative demands, control, role conflicts, role clarity, social support and job satisfaction in 2002 and 2009 and to analyse the stability in the prediction of job satisfaction over time. Questionnaires regarding psychosocial work environment aspects were distributed in 2002 and 2009, and a total of 860 nurses and 866 physicians answered the questionnaire. Independent t tests and linear stepwise regression analyses were conducted. The results indicate that the work environment has improved between 2002 and 2009 and that nurses experience their psychosocial working environment as more satisfactory than physicians. Social support, control, role conflicts, role clarity and qualitative demands were the best predictors of job satisfaction in 2002 and 2009. Quantitative demands did not contribute to predicting job satisfaction. Variables predicting job satisfaction are quite stable over time and are quite comparable for both nurses and physicians.

  8. 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.

  9. Nursing care time and quality indicators for adult intensive care: correlation analysis.

    PubMed

    Garcia, Paulo Carlos; Fugulin, Fernanda Maria Togeiro

    2012-01-01

    The objective of this quantitative, correlational and descriptive study was to analyze the time the nursing staff spends to assist patients in Adult Intensive Care Units, as well as to verify its correlation with quality care indicators. The average length of time spent on care and the quality care indicators were identified by consulting management instruments the nursing head of the Unit employs. The average hours of nursing care delivered to patients remained stable, but lower than official Brazilian agencies' indications. The correlation between time of nursing care and the incidence of accidental extubation indicator indicated that it decreases with increasing nursing care delivered by nurses. The results of this investigation showed the influence of nursing care time, provided by nurses, in the outcome of care delivery.

  10. Predicting application run times using historical information.

    SciTech Connect

    Foster, I.; Smith, W.; Taylor, V.

    1999-06-25

    The authors present a technique for deriving predictions for the run times of parallel applications from the run times of similar applications that have executed in the past. The novel aspect of the work is the use of search techniques to determine those application characteristics that yield the best definition of similarity for the purpose of making predictions. They use four workloads recorded from parallel computers at Argonne National Laboratory, the Cornell Theory Center, and the San Diego Supercomputer Center to evaluate the effectiveness of the approach.They show that on these workloads the techniques achieve predictions that are between 14 and 60% better than those achieved by other researchers; the approach achieves mean prediction errors that are between 41 and 65% of mean application run times.

  11. 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…

  12. 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.

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

    Code of Federal Regulations, 2010 CFR

    2010-10-01

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

  14. Factors Predicting the Provision of Smoking Cessation Services Among Occupational Health Nurses in Thailand.

    PubMed

    Chatdokmaiprai, Kannikar; Kalampakorn, Surintorn; McCullagh, Marjorie; Lagampan, Sunee; Keeratiwiriyaporn, Sansanee

    2017-01-01

    The purpose of this study was to identify factors predicting occupational health nurses' provision of smoking cessation services. Data were collected via a self-administered questionnaire distributed to 254 occupational health nurses in Thailand. Analysis by structural equation modeling revealed that self-efficacy directly and positively influenced smoking cessation services, and mediated the relationship between workplace factors, nurse factors, and smoking cessation services. The final model had good fit to the data, accounting for 20.4% and 38.0% of the variance in self-efficacy and smoking cessation services, respectively. The findings show that self-efficacy is a mediator that influences provision of smoking cessation services by occupational health nurses. Interventions to enhance nurses' self-efficacy in providing smoking cessation services are expected to promote provision of smoking cessation services to workers.

  15. 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.

  16. 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.

  17. 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.

  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. 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.

  20. 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

  1. Time will show: real time predictions during interpersonal action perception.

    PubMed

    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.

  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 Nursing Facility Transition Candidates Using AID: A Case Study

    ERIC Educational Resources Information Center

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

    2007-01-01

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

  4. On understanding and predicting groundwater response time.

    PubMed

    Sophocleous, Marios

    2012-01-01

    An aquifer system, when perturbed, has a tendency to evolve to a new equilibrium, a process that can take from just a few seconds to possibly millions of years. The time scale on which a system adjusts to a new equilibrium is often referred to as "response time" or "lag time." Because groundwater response time affects the physical and economic viability of various management options in a basin, natural resource managers are increasingly interested in incorporating it into policy. However, the processes of how groundwater responds to land-use change are not well understood, making it difficult to predict the timing of groundwater response to such change. The difficulty in estimating groundwater response time is further compounded because the data needed to quantify this process are not usually readily available. This article synthesizes disparate pieces of information on aquifer response times into a relatively brief but hopefully comprehensive review that the community of water professionals can use to better assess the impact of aquifer response time in future groundwater management investigations. A brief exposition on dimensional/scaling analysis is presented first, followed by an overview of aquifer response time for simplified aquifer systems. The aquifer response time is considered first from a water-quantity viewpoint and later expanded to incorporate groundwater age and water-quality aspects. Monitoring programs today, as well as water policies and regulations, should address this issue of aquifer response time so that more realistic management expectations can be reached.

  5. Participation in a national nursing outcomes database: monitoring outcomes over time.

    PubMed

    Loan, Lori A; Patrician, Patricia A; McCarthy, Mary

    2011-01-01

    The current and future climates in health care require increased accountability of health care organizations for the quality of the care they provide. Never before in the history of health care in America has this focus on quality been so critical. The imperative to measure nursing's impact without fully developed and tested monitoring systems is a critical issue for nurse executives and managers alike. This article describes a project to measure nursing structure, process, and outcomes in the military health system, the Military Nursing Outcomes Database project. Here we review the effectiveness of this project in monitoring changes over time, in satisfying expectations of nurse leaders in participating hospitals, and evaluate the potential budgetary impacts of such a system. We conclude that the Military Nursing Outcomes Database did meet the needs of a monitoring system that is sensitive to changes over time in outcomes, provides interpretable data for nurse leaders, and could result in cost benefits and patient care improvements in organizations.

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

    PubMed Central

    LIU, Qiong; ZHU, Hui

    2016-01-01

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

  7. Managing distribution changes in time series prediction

    NASA Astrophysics Data System (ADS)

    Matias, J. M.; Gonzalez-Manteiga, W.; Taboada, J.; Ordonez, C.

    2006-07-01

    When a problem is modeled statistically, a single distribution model is usually postulated that is assumed to be valid for the entire space. Nonetheless, this practice may be somewhat unrealistic in certain application areas, in which the conditions of the process that generates the data may change; as far as we are aware, however, no techniques have been developed to tackle this problem.This article proposes a technique for modeling and predicting this change in time series with a view to improving estimates and predictions. The technique is applied, among other models, to the hypernormal distribution recently proposed. When tested on real data from a range of stock market indices the technique produces better results that when a single distribution model is assumed to be valid for the entire period of time studied.Moreover, when a global model is postulated, it is highly recommended to select the hypernormal distribution parameter in the same likelihood maximization process.

  8. Predicting road accidents: Structural time series approach

    NASA Astrophysics Data System (ADS)

    Junus, Noor Wahida Md; Ismail, Mohd Tahir

    2014-07-01

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

  9. 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.

  10. Developing students' time management skills in clinical settings: practical considerations for busy nursing staff.

    PubMed

    Cleary, Michelle; Horsfall, Jan

    2011-06-01

    In clinical settings, nursing staff often find themselves responsible for students who have varying time management skills. Nurses need to respond sensitively and appropriately, and to teach nursing students how to prioritize and better allocate time. This is important not only for developing students' clinical skills but also for shaping their perceptions about the quality of the placement and their willingness to consider it as a potential work specialty. In this column, some simple, practical strategies that nurses can use to assist students with improving their time management skills are identified.

  11. Globally disruptive events show predictable timing patterns

    NASA Astrophysics Data System (ADS)

    Gillman, Michael P.; Erenler, Hilary E.

    2017-01-01

    Globally disruptive events include asteroid/comet impacts, large igneous provinces and glaciations, all of which have been considered as contributors to mass extinctions. Understanding the overall relationship between the timings of the largest extinctions and their potential proximal causes remains one of science's great unsolved mysteries. Cycles of about 60 Myr in both fossil diversity and environmental data suggest external drivers such as the passage of the Solar System through the galactic plane. While cyclic phenomena are recognized statistically, a lack of coherent mechanisms and a failure to link key events has hampered wider acceptance of multi-million year periodicity and its relevance to earth science and evolution. The generation of a robust predictive model of timings, with a clear plausible primary mechanism, would signal a paradigm shift. Here, we present a model of the timings of globally disruptive events and a possible explanation of their ultimate cause. The proposed model is a symmetrical pattern of 63 Myr sequences around a central value, interpreted as the occurrence of events along, and parallel to, the galactic midplane. The symmetry is consistent with multiple dark matter disks, aligned parallel to the midplane. One implication of the precise pattern of timings and the underlying physical model is the ability to predict future events, such as a major extinction in 1-2 Myr.

  12. A real-time prediction of UTC

    NASA Astrophysics Data System (ADS)

    Thomas, Claudine; Allan, David W.

    1994-05-01

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

  13. 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.

  14. '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.

  15. Geriatric nursing: an idea whose time has gone? A polemic.

    PubMed

    Nolan, M

    1994-12-01

    The future role of the nursing profession in providing health care for older people is considered. It is argued that, despite claims to holism, nursing has maintained a narrow focus, concentrating mainly on acute hospital care. The concepts of professional protectionism and professional reductionism are used to explain the manifest failure of nursing and other professions working with older people and their carers to place the needs of their clients at the top of their agendas. A reorientation of nursing practice is advocated in order that the profession fulfils its potential with respect to older people.

  16. The experience of being a full-time nursing faculty member in a baccalaureate nursing education program.

    PubMed

    Gazza, Elizabeth A

    2009-01-01

    The purpose of this hermeneutic phenomenological study was to understand the experience of being a full-time nursing faculty member in a baccalaureate nursing program. Eight female informants, with an average of 6.1 years of experience in a full-time faculty position, shared their experiences through in-depth personal interviews and a follow-up telephone interview. Field notes and a demographic questionnaire also served as data sources. Data were analyzed using a hermeneutic phenomenological approach based on the Urecht School of phenomenology. Five themes were uncovered through data analysis, including (a) making a difference in the student, profession, and the world; (b) being a gatekeeper to the profession; (c) trying ways to balance multiple roles; (d) support is vital: can't do it alone; and (e) workplace relationships: the good, the bad, and the ugly. Findings have implications for the development of research-based faculty recruitment and retention strategies. Implications for the practice of nursing education focus on current nursing faculty, administrators in nursing education, and those responsible for developing higher education policies. Future research is recommended for exploring the rewards of making a difference, the rationale for incivility in the workplace, and the level of faculty mentoring occurring in nursing education.

  17. Fitness and lifestyle parameters fail to predict back injuries in nurses.

    PubMed

    Ready, A E; Boreskie, S L; Law, S A; Russell, R

    1993-03-01

    Performance on fitness and back related isometric strength tests, as well as the response to a lifestyle questionnaire, were related to the subsequent occurrence of back injuries in 119 nurses. In all, 22% of subjects sustained injuries during the 18-month study. Injured nurses were more likely to be from high-risk wards and to have received worker's compensation pay for past back injuries. Fitness and lifestyle characteristics did not differ significantly between injured and not-injured groups. Using backward stepwise logistic regression, a model was developed that accounted for 41% of the variability between groups and predicted 67% of those injured. Prior compensation pay, smoking status, and job satisfaction were the most useful discriminators. It was concluded, however, that the fitness and lifestyle parameters measured did not effectively predict back injury in nurses.

  18. Time Series Prediction of Hurricane Landfall.

    DTIC Science & Technology

    1986-05-01

    8217 132 111112-2 11111111.8 MICROCOPY RESOLUTION TEST CHART NATIONAL BUR[AU OIf SIANARD lq A .5. 𔃿. SECURITY CLASSIFICATION OF THIS PAGE (When, Dta Entered...parameters to change as the storm moves to a new region of the ocean. For test cases, operational average 72 hour prediction error is at least three...comparatively accurate for forecast times of 24 hours or less. The SANBAR model (Sanders and Burpee , 1968), has been in use at NHC since 1970. It is a

  19. More time where it matters: improving work environments in home healthcare nursing.

    PubMed

    Ray, Karen; Decicco, Julie; Lefebre, Nancy; Bender, Danielle

    2011-04-01

    The nursing profession is currently experiencing a shift to community care, more complex clients and a shortage of human resources. Home healthcare organizations can increase job satisfaction and retention by better managing nurses' workloads and ensuring more time for direct client care. This project used innovative technology and dynamic methods to document nurses' work lives, identify areas for process improvements and increase time available for direct client care. This case study provides insight into ways in which organizations can streamline non-care activities and discusses implications for nursing leaders at the local and regional levels.

  20. 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…

  1. 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…

  2. Patient cues that predict nurses' triage decisions for acute coronary syndromes.

    PubMed

    Arslanian-Engoren, Cynthia

    2005-05-01

    The purpose of this study was to determine the patient cues that emergency department (ED) nurses use to triage male and female patients with complaints suggestive of acute coronary syndromes (ACSs) and to determine if cues used by ED nurses to make clinical inferences varied by patient sex or nurses' demographic characteristics. Using clinical vignette questionnaires with different patient characteristics, ED nurses' triage decisions were evaluated to determine the patient cues used to predict ACS. Men and women were equally likely to be given an ACS triage decision and this was not affected by nurses' demographic characteristics. However, nurses used different cues to triage men and women with complaints suggestive of ACS, although by receiver operating characteristic curves, the differences between sexes were small. In addition, female vignette patients were more likely than male vignette patients to be assigned a suspected cause of cholecystitis for their presentation in a small subset of 13 (11:2; odds ratio, 1.653; 95% confidence interval, 1.115-24.47; p=.036). This study provides insight into the complex phenomenon of triage decision making and warrants further exploration.

  3. 'It is Time to Prepare the Next patient' Real-Time Prediction of Procedure Duration in Laparoscopic Cholecystectomies.

    PubMed

    Guédon, Annetje C P; Paalvast, M; Meeuwsen, F C; Tax, D M J; van Dijke, A P; Wauben, L S G L; van der Elst, M; Dankelman, J; van den Dobbelsteen, J J

    2016-12-01

    Operating Room (OR) scheduling is crucial to allow efficient use of ORs. Currently, the predicted durations of surgical procedures are unreliable and the OR schedulers have to follow the progress of the procedures in order to update the daily planning accordingly. The OR schedulers often acquire the needed information through verbal communication with the OR staff, which causes undesired interruptions of the surgical process. The aim of this study was to develop a system that predicts in real-time the remaining procedure duration and to test this prediction system for reliability and usability in an OR. The prediction system was based on the activation pattern of one single piece of equipment, the electrosurgical device. The prediction system was tested during 21 laparoscopic cholecystectomies, in which the activation of the electrosurgical device was recorded and processed in real-time using pattern recognition methods. The remaining surgical procedure duration was estimated and the optimal timing to prepare the next patient for surgery was communicated to the OR staff. The mean absolute error was smaller for the prediction system (14 min) than for the OR staff (19 min). The OR staff doubted whether the prediction system could take all relevant factors into account but were positive about its potential to shorten waiting times for patients. The prediction system is a promising tool to automatically and objectively predict the remaining procedure duration, and thereby achieve optimal OR scheduling and streamline the patient flow from the nursing department to the OR.

  4. On-Admission Pressure Ulcer Prediction Using the Nursing Needs Score

    PubMed Central

    Setoguchi, Yoko; Mitani, Kazue; Abe, Yoshiro; Hashimoto, Ichiro; Moriguchi, Hiroki

    2015-01-01

    Background Pressure ulcers (PUs) are considered a serious problem in nursing care and require preventive measures. Many risk assessment methods are currently being used, but most require the collection of data not available on admission. Although nurses assess the Nursing Needs Score (NNS) on a daily basis in Japanese acute care hospitals, these data are primarily used to standardize the cost of nursing care in the public insurance system for appropriate nurse staffing, and have never been used for PU risk assessment. Objective The objective of this study was to predict the risk of PU development using only data available on admission, including the on-admission NNS score. Methods Logistic regression was used to generate a prediction model for the risk of developing PUs after admission. A random undersampling procedure was used to overcome the problem of imbalanced data. Results A combination of gender, age, surgical duration, and on-admission total NNS score (NNS group B; NNS-B) was the best predictor with an average sensitivity, specificity, and area under receiver operating characteristic curve (AUC) of 69.2% (6920/100), 82.8% (8280/100), and 84.0% (8400/100), respectively. The model with the median AUC achieved 80% (4/5) sensitivity, 81.3% (669/823) specificity, and 84.3% AUC. Conclusions We developed a model for predicting PU development using gender, age, surgical duration, and on-admission total NNS-B score. These results can be used to improve the efficiency of nurses and reduce the number of PU cases by identifying patients who require further examination. PMID:25673118

  5. 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.

  6. Fall Risk in Community Dwelling Elderly Cancer Survivors—A Predictive Model for Gerontological Nurses

    PubMed Central

    Spoelstra, Sandra; Given, Barbara; von Eye, Alexander; Given, Charles

    2015-01-01

    The aim of this predictive study was to test a structural model to establish predictors of fall risk. An aging and nursing model of care was synthesized and used to examine 6912 older adult participants who are low income, using the Minimum Data Set in a community setting in the Midwest. Data analysis established relationships among age, race, a history of a previous fall, depression, pain, and ADLs, IADLs, incontinence, vision, and cognitive status. Factors leading to fall risk can direct nursing activities that have the potential to prevent falls, improving quality of life. PMID:20128528

  7. Missed nursing care and predicting factors in the Italian medical care setting.

    PubMed

    Palese, Alvisa; Ambrosi, Elisa; Prosperi, Letizia; Guarnier, Annamaria; Barelli, Paolo; Zambiasi, Paola; Allegrini, Elisabetta; Bazoli, Letizia; Casson, Paola; Marin, Meri; Padovan, Marisa; Picogna, Michele; Taddia, Patrizia; Salmaso, Daniele; Chiari, Paolo; Marognolli, Oliva; Canzan, Federica; Gonella, Silvia; Saiani, Luisa

    2015-09-01

    Missed nursing care (MNC), such as nursing care omitted or delayed, has not been measured in the Italian context where several cost containment interventions affect the care offered in medical units. The aim of the study is to identify the amount, type, and reasons for MNC in the Italian medical care setting and to explore the factors that affect the occurrence of MNC. A 3-month longitudinal survey was carried out followed by a cross-sectional study design in 12 north eastern acute medical units. A total of 314 nursing staff members were involved. Multivariate logistic regression was performed to identify the predictors of MNC. Patient ambulation (91.4 %), turning the patient every 2 h (74.2 %), and right timing in administering medications (64.6 %) were the most perceived MNC. Among the most frequent reasons were the unexpected rise in patient volume or critical conditions (95.2 %), inadequate numbers of staff (94.9 %), and large numbers of admissions/discharges (93.3 %). The R (2) 33.2 % of the variance in MNC were explained by a full-time position (OR 4.743, 95 % CI 1.146-19.629), communication tensions between Registered Nurses and Nurses' Aides (OR 1.601, 95 % CI 1.020-2.515), the amount of experience in medical unit (OR 1.564, 95 % CI 1.021-2.397), and the amount of daily care offered by Nurses' Aides (1.039, 95 % CI 1.011-1.067). A substantial amount of basic and clinically relevant nursing interventions was perceived to be missed, and this may lead to an increase in negative outcomes for patients admitted to a medical unit. Appropriate standards of nursing care should be adopted urgently in medical units aiming to protect frail patients.

  8. 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…

  9. 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.

  10. Predicting nurse staffing needs for a labor and birth unit in a large-volume perinatal service.

    PubMed

    Simpson, Kathleen Rice

    2015-01-01

    This project was designed to test a nurse staffing model for its ability to accurately determine staffing needs for a large-volume labor and birth unit based on a staffing gap analysis using the nurse staffing guidelines from the Association of Women's Health, Obstetric and Neonatal Nurses (AWHONN). The staffing model and the AWHONN staffing guidelines were found to be reliable methods to predict staffing needs for a large-volume labor and birth unit.

  11. 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…

  12. Predicting Persistence in Practical Nursing and Success on the NCLEX-PN: Examining Demographic, Non-Academic, and Academic Variables

    ERIC Educational Resources Information Center

    Davis, Alicia Debra

    2015-01-01

    The United States is now in the midst of a major nursing shortage that is predicted to get worse over the next ten years (Kurzen, 2005). The Health Resources and Services Administration reports that all 50 states will suffer from a nursing shortage by 2020 (U.S. Department of Health and Human Services, 2004). This means that there will be a…

  13. 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…

  14. How many research nurses for how many clinical trials in an oncology setting? Definition of the Nursing Time Required by Clinical Trial-Assessment Tool (NTRCT-AT).

    PubMed

    Milani, Alessandra; Mazzocco, Ketti; Stucchi, Sara; Magon, Giorgio; Pravettoni, Gabriella; Passoni, Claudia; Ciccarelli, Chiara; Tonali, Alessandra; Profeta, Teresa; Saiani, Luisa

    2017-02-01

    Few resources are available to quantify clinical trial-associated workload, needed to guide staffing and budgetary planning. The aim of the study is to describe a tool to measure clinical trials nurses' workload expressed in time spent to complete core activities. Clinical trials nurses drew up a list of nursing core activities, integrating results from literature searches with personal experience. The final 30 core activities were timed for each research nurse by an outside observer during daily practice in May and June 2014. Average times spent by nurses for each activity were calculated. The "Nursing Time Required by Clinical Trial-Assessment Tool" was created as an electronic sheet that combines the average times per specified activities and mathematic functions to return the total estimated time required by a research nurse for each specific trial. The tool was tested retrospectively on 141 clinical trials. The increasing complexity of clinical research requires structured approaches to determine workforce requirements. This study provides a tool to describe the activities of a clinical trials nurse and to estimate the associated time required to deliver individual trials. The application of the proposed tool in clinical research practice could provide a consistent structure for clinical trials nursing workload estimation internationally.

  15. Nurses ready to right back. Ruling that full-time charge nurses can't belong to unions has labor leaders determined to work for ways around it.

    PubMed

    Evans, Melanie

    2006-10-09

    Nurse labor leaders are fighting mad over last week's ruling that full-time charge nurses aren't eligible for union membership. Labor and healthcare insiders say the decision leaves gray areas that will have to be settled at the negotiating table. Barbara Medvec, left, an executive at the system that brought the case before the NLRB, says she finds the "silence" on part-time charge nurses puzzling.

  16. Factors predicting clinical nurses' willingness to care for Ebola virus disease-infected patients: A cross-sectional, descriptive survey.

    PubMed

    Kim, Ji Soo; Choi, Jeong Sil

    2016-09-01

    The purpose of this study was to identify factors predicting clinical nurses' willingness to care for Ebola virus disease (EVD)-infected patients. Data were collected from 179 nurses employed at 10 hospitals in Korea using self-reporting questionnaires. Only 26.8% of the participants were willing to care for EVD-infected patients. Factors predicting their willingness to provide care were their belief in public service, risk perception, and age. Nurses' willingness to provide care was high when their belief in public service was high, low when their risk perception was high, and low as their age increased. In order to strengthen nurses' willingness to care for EVD-infected patients, education that targets the enhancement of belief in public service should be included in nurse training. Efforts should be directed toward lowering EVD risk perception and developing systematic responses through government-led organized support.

  17. 75 FR 80073 - Reasonable Break Time for Nursing Mothers

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-12-21

    ... gradually diminish. \\1\\ See ``The Business Case for Breastfeeding: Steps for Creating a Breastfeeding... Administration (2008), available at http://www.womenshealth.gov/breastfeeding/government-programs/business-case-for-breastfeeding/index.cfm . The Department expects that nursing mothers typically will need...

  18. 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

  19. 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.

  20. Creative alliances between nursing service and education in times of economic constraint.

    PubMed

    Patton, J G; Cook, L R

    1994-01-01

    Health care and higher education in America are both in economic crisis and undergoing reform. Forming collaborative relationships between health care providers and nursing educational institutions is a savvy, economical, and mutually beneficial strategy in these changing times. Creative alliances between service and education are addressed in terms of clinical educational preceptorships for senior nursing students and joint appointments between service and education. The educational and service perspectives are discussed, from development to implementation.

  1. 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…

  2. 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.

  3. 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.

  4. 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.

  5. Annual Released Time for Faculty: The Experience of One School of Nursing.

    ERIC Educational Resources Information Center

    Johnston, Sarah R.

    1987-01-01

    The experience of the University of Alabama School of Nursing with a plan that provides released time for faculty by reducing their teaching load is described. The availability of released time increased the involvement of the faculty in research, writing, education, clinical practice, and consultation. (MLW)

  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. PREDICTING EVAPORATION RATES AND TIMES FOR SPILLS OF CHEMICAL MIXTURES

    EPA Science Inventory


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

  8. 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.

  9. Understanding and Visualizing Multitasking and Task Switching Activities: A Time Motion Study to Capture Nursing Workflow.

    PubMed

    Yen, Po-Yin; Kelley, Marjorie; Lopetegui, Marcelo; Rosado, Amber L; Migliore, Elaina M; Chipps, Esther M; Buck, Jacalyn

    2016-01-01

    A fundamental understanding of multitasking within nursing workflow is important in today's dynamic and complex healthcare environment. We conducted a time motion study to understand nursing workflow, specifically multitasking and task switching activities. We used TimeCaT, a comprehensive electronic time capture tool, to capture observational data. We established inter-observer reliability prior to data collection. We completed 56 hours of observation of 10 registered nurses. We found, on average, nurses had 124 communications and 208 hands-on tasks per 4-hour block of time. They multitasked (having communication and hands-on tasks simultaneously) 131 times, representing 39.48% of all times; the total multitasking duration ranges from 14.6 minutes to 109 minutes, 44.98 minutes (18.63%) on average. We also reviewed workflow visualization to uncover the multitasking events. Our study design and methods provide a practical and reliable approach to conducting and analyzing time motion studies from both quantitative and qualitative perspectives.

  10. Understanding and Visualizing Multitasking and Task Switching Activities: A Time Motion Study to Capture Nursing Workflow

    PubMed Central

    Yen, Po-Yin; Kelley, Marjorie; Lopetegui, Marcelo; Rosado, Amber L.; Migliore, Elaina M.; Chipps, Esther M.; Buck, Jacalyn

    2016-01-01

    A fundamental understanding of multitasking within nursing workflow is important in today’s dynamic and complex healthcare environment. We conducted a time motion study to understand nursing workflow, specifically multitasking and task switching activities. We used TimeCaT, a comprehensive electronic time capture tool, to capture observational data. We established inter-observer reliability prior to data collection. We completed 56 hours of observation of 10 registered nurses. We found, on average, nurses had 124 communications and 208 hands-on tasks per 4-hour block of time. They multitasked (having communication and hands-on tasks simultaneously) 131 times, representing 39.48% of all times; the total multitasking duration ranges from 14.6 minutes to 109 minutes, 44.98 minutes (18.63%) on average. We also reviewed workflow visualization to uncover the multitasking events. Our study design and methods provide a practical and reliable approach to conducting and analyzing time motion studies from both quantitative and qualitative perspectives. PMID:28269924

  11. Coping with SLE: just in case vs. just in time: nurse's perspective.

    PubMed

    Brown, S

    2013-10-01

    This paper considers the experiences of people with lupus in comparison with those with diabetes, and discusses the impact of lupus specialist nurses in information-giving and education under the guise of 'just in case' vs. 'just in time'. Now recognized as a difficult condition to diagnose, lupus can lead to significant worry and distress especially during delays to diagnosis and times of high disease activity. Providing appropriate, individualized information to people with lupus is embedded in specialist nursing practice and enables individuals to use the tools of self-management approaches in gaining control over everyday symptoms.

  12. 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

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

    PubMed

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

    2013-10-11

    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.

  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.

  15. 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

  16. The contribution of nursing data to the development of a predictive model for the detection of acute pancreatitis.

    PubMed

    Cho, In Sook; Haug, Peter J

    2006-01-01

    The increasing use of information system has resulted in the accumulation of a large volume of nursing data in electronic medical records. These data have great potential for supporting the various clinical decisions made by physicians, nurses, and managers. However, how to re-use of nursing data remains largely an issue of informatics. The aim of this study was to demonstrate how these nursing data can be used and how much they could contribute to developing a predictive model for an expert system for early detection of acute pancreatitis. We employed a probability-based model consisting of a Bayesian network and trained this model with the patient data retrospectively retrieved from the enterprise data warehouse of a tertiary hospital. The performance of the predictive model was measured based on the error rate and the area under receiver operating characteristics curve, which were 13.89 % and 0.93, respectively. The sensitivity of the acute pancreatitis to the findings from each nursing data was measured using a test of sensitivity. The results showed that the role of nursing data is as important as laboratory data in formulating a model for an expert system.

  17. Relationship between time management skills and anxiety and academic motivation of nursing students in Tehran

    PubMed Central

    Ghiasvand, Arezoo Mohamadkhani; Naderi, Manijeh; Tafreshi, Mansoureh Zagheri; Ahmadi, Farzane; Hosseini, Meimanat

    2017-01-01

    Introduction Time management skills are essential for nursing students’ success, and development of clinical competence. The purpose of this study was to determine the relationship between time management skills and anxiety and academic motivation of nursing students in Tehran medical sciences universities in 2015. Methods This cross-sectional study was carried out on 441 nursing students in three medical universities in Tehran. Random stratified sampling was done to select the samples. Data were collected using demographic Questionnaire, Time Management Questionnaire (TMQ), Spielberger State-Trait Anxiety Inventory (STAI) and Academic Motivation Scale (AMS), which was completed t by self-report. Data were analyzed using SPSS 18 software with descriptive and analytical statistics such as ANOVA, independent t-test, Regression and Pearson Correlation Coefficient. Results Most participants had a moderate level of time Management skills (49%), State Anxiety (58%), Trait Anxiety (60%) and Academic Motivation (58%). The results also showed a statistically significant negative correlation between the students’ TMQ scores and the state anxiety (r= −0.282, p< 0.001) and trait anxiety scores (r= −0.325, p<0.001). Moreover, there was a statistically significant positive correlation between the students’ TMQ scores and AMS scores (r= 0.279, p< 0.001). Conclusion Regarding the findings, it seems that it is necessary to plan for improving time management skills in order to enhance academic motivation and reduce anxiety rates among nursing students. PMID:28243424

  18. Time-to-event analysis of individual variables associated with nursing students' academic failure: a longitudinal study.

    PubMed

    Dante, Angelo; Fabris, Stefano; Palese, Alvisa

    2013-12-01

    Empirical studies and conceptual frameworks presented in the extant literature offer a static imagining of academic failure. Time-to-event analysis, which captures the dynamism of individual factors, as when they determine the failure to properly tailor timely strategies, impose longitudinal studies which are still lacking within the field. The aims of this longitudinal study were to investigate the time which elapses from a nursing student's admission to a Bachelor of Nursing program to their academic failure and to estimate the predictive power of individual variables on academic failure. Enrolled students (n = 170) in two Italian nursing degree programs during academic year 2008-2009, received at the beginning of each years a questionnaire which evaluated individual variables. Academic failure rate was 37.2 %. Time-to-event analysis has shown that academic failure occurred after an average of 664.52 days of course attendance ((95 %)CI = 623.2-705.8). Kaplan-Meier analyses demonstrated a high likelihood of failure among males (χ(2) 7.790, p 0.005) and among those who had obtained a final average grade in their secondary education ≤73/100 (χ(2)11.676, p 0.001). Cox regression analysis confirmed an increased likelihood of failure over time among males as compared to females (HR 1.931, (95 %)CI = 1.017-3.670), and among students living more than a 30 min commute from their place of study (HR 1.898, (95 %)CI = 1.015-3.547). The effect of these two factors on academic failure has been seen to manifest primarily toward the end of students' second academic year; students at risk might be supported by the appropriate university staff prior to this period.

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

    PubMed

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

    2008-12-01

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

  20. 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.

  1. Changes to physician and nurse time burdens when caring for patients under contact precautions.

    PubMed

    Barker, Anna K; Codella, James; Ewers, Tola; Dundon, Adam; Alagoz, Oguzhan; Safdar, Nasia

    2017-03-13

    Contact precautions are complex behavioral interventions. To better understand barriers to compliance, we conducted a prospective study that compared the time burden for health care workers caring for contact precautions patients versus other patients. We found that nurses spent significantly more time in the rooms of contact precautions patients. There was no significant change in physician timing. Future studies need to evaluate workflow changes so that barriers to contact precaution implementation can be fully understood and addressed.

  2. 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.

  3. Chaotic time series prediction using artificial neural networks

    SciTech Connect

    Bartlett, E.B.

    1991-12-31

    This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.

  4. Chaotic time series prediction using artificial neural networks

    SciTech Connect

    Bartlett, E.B.

    1991-01-01

    This paper describes the use of artificial neural networks to model the complex oscillations defined by a chaotic Verhuist animal population dynamic. A predictive artificial neural network model is developed and tested, and results of computer simulations are given. These results show that the artificial neural network model predicts the chaotic time series with various initial conditions, growth parameters, or noise.

  5. Three Millennia of Seemingly Time-Predictable Earthquakes, Tell Ateret

    NASA Astrophysics Data System (ADS)

    Agnon, Amotz; Marco, Shmuel; Ellenblum, Ronnie

    2014-05-01

    Among various idealized recurrence models of large earthquakes, the "time-predictable" model has a straightforward mechanical interpretation, consistent with simple friction laws. On a time-predictable fault, the time interval between an earthquake and its predecessor is proportional to the slip during the predecessor. The alternative "slip-predictable" model states that the slip during earthquake rupture is proportional to the preceding time interval. Verifying these models requires extended records of high precision data for both timing and amount of slip. The precision of paleoearthquake data can rarely confirm or rule out predictability, and recent papers argue for either time- or slip-predictable behavior. The Ateret site, on the trace of the Dead Sea fault at the Jordan Gorge segment, offers unique precision for determining space-time patterns. Five consecutive slip events, each associated with deformed and offset sets of walls, are correlated with historical earthquakes. Two correlations are based on detailed archaeological, historical, and numismatic evidence. The other three are tentative. The offsets of three of the events are determined with high precision; the other two are not as certain. Accepting all five correlations, the fault exhibits a striking time-predictable behavior, with a long term slip rate of 3 mm/yr. However, the 30 October 1759 ~0.5 m rupture predicts a subsequent rupture along the Jordan Gorge toward the end of the last century. We speculate that earthquakres on secondary faults (the 25 November 1759 on the Rachaya branch and the 1 January 1837 on the Roum branch, both M≥7) have disrupted the 3 kyr time-predictable pattern.

  6. Nursing faculty shortage in 2009.

    PubMed

    Sims, Jennifer M

    2009-01-01

    As everyone is well aware, we are in the midst of a nursing shortage-one with no end in sight at the present time. But are you aware that we also have a shortage of nursing faculty? This article will briefly describe the current and predicted shortage of faculty, potential reasons for the shortage, current ways of coping, and the future for nursing faculty.

  7. 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.

  8. 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…

  9. 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

  10. Improving Predictability in Embedded Real-Time Systems

    DTIC Science & Technology

    2000-12-01

    Systems CMU/SEI-2000-SR-011 Peter H. Feiler , Software Engineering Institute Bruce Lewis, U.S. Army Aviation and Missile Command Steve Vestal...SUBTITLE Improving Predictability in Embedded Real-Time Systems 5. FUNDING NUMBERS F19628-00-C-0003 6. AUTHOR(S) Peter H. Feiler , Bruce ...Carnegie Metton Software Engineering Institute Improving Predictability in Embedded Real-Time Systems Peter H. Feiler , Software Engineering

  11. Nurses' Time Use in Forensic Psychiatry: Core Interventions Outlined in the Finnish Clinical Practice Guideline on Schizophrenia.

    PubMed

    Tenkanen, Helena; Taskinen, Helena; Kontio, Raija; Repo-Tiihonen, Eila; Tiihonen, Jari; Kinnunen, Juha

    2016-01-01

    Forensic psychiatric nurses are key in implementing the core interventions outlined in the clinical practice guideline on schizophrenia. This study endeavors to ascertain how these were implemented in routine practice in forensic psychiatry by measuring how nurses use their time. Data were collected from registered nurses and practical mental nurses in all forensic psychiatric facilities in Finland using self-report diary forms for 1 week. In total, nurses used 20% of their weekly working hours on core interventions. The differences between the nurse groups were statistically significant (p ≤ 0.05) regarding the following core interventions: (a) care planning with physicians, (b) pharmacotherapy, and (c) basic clinical care. Nurses' qualifications, types of facilities and units, working experience, gender, and staffing levels explained the time used on core interventions. In summary, forensic psychiatric inpatients received insufficient appropriate nursing services according to the relevant guideline regarding schizophrenia. Furthermore, managerial recommendations need to restructure nurses' time use to increase the proportion of productive working hours spent with patients.

  12. 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.

  13. 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

  14. Scalable Prediction of Energy Consumption using Incremental Time Series Clustering

    SciTech Connect

    Simmhan, Yogesh; Noor, Muhammad Usman

    2013-10-09

    Time series datasets are a canonical form of high velocity Big Data, and often generated by pervasive sensors, such as found in smart infrastructure. Performing predictive analytics on time series data can be computationally complex, and requires approximation techniques. In this paper, we motivate this problem using a real application from the smart grid domain. We propose an incremental clustering technique, along with a novel affinity score for determining cluster similarity, which help reduce the prediction error for cumulative time series within a cluster. We evaluate this technique, along with optimizations, using real datasets from smart meters, totaling ~700,000 data points, and show the efficacy of our techniques in improving the prediction error of time series data within polynomial time.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. Clinical time series prediction: towards a hierarchical dynamical system framework

    PubMed Central

    Liu, Zitao; Hauskrecht, Milos

    2014-01-01

    Objective Developing machine learning and data mining algorithms for building temporal models of clinical time series is important for understanding of the patient condition, the dynamics of a disease, effect of various patient management interventions and clinical decision making. In this work, we propose and develop a novel hierarchical framework for modeling clinical time series data of varied length and with irregularly sampled observations. Materials and methods Our hierarchical dynamical system framework for modeling clinical time series combines advantages of the two temporal modeling approaches: the linear dynamical system and the Gaussian process. We model the irregularly sampled clinical time series by using multiple Gaussian process sequences in the lower level of our hierarchical framework and capture the transitions between Gaussian processes by utilizing the linear dynamical system. The experiments are conducted on the complete blood count (CBC) panel data of 1000 post-surgical cardiac patients during their hospitalization. Our framework is evaluated and compared to multiple baseline approaches in terms of the mean absolute prediction error and the absolute percentage error. Results We tested our framework by first learning the time series model from data for the patient in the training set, and then applying the model in order to predict future time series values on the patients in the test set. We show that our model outperforms multiple existing models in terms of its predictive accuracy. Our method achieved a 3.13% average prediction accuracy improvement on ten CBC lab time series when it was compared against the best performing baseline. A 5.25% average accuracy improvement was observed when only short-term predictions were considered. Conclusion A new hierarchical dynamical system framework that lets us model irregularly sampled time series data is a promising new direction for modeling clinical time series and for improving their predictive

  20. 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…

  1. 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.

  2. Glass Fibre/Epoxy Resin Interface Life-Time Prediction.

    DTIC Science & Technology

    1983-04-01

    RD-Ai32 26 GLASS FIBRE /POXY RESIN INTERFACE LIFE-TIME PREDICTION 1/1 (U) BRISTOL UNIV (ENGLAND) H H WILLS PHYSICS LAB K H RSHBEE ET AL. APR 83...D 3005-MS GLASS FIBRE /EPOXY RESIN INTERFACE LIFE-TIME PREDICTION - Final Report by K H G Ashbee, Principal Investigator R Ho~l J P Sargent Elizabeth...REPORT h PERIOD COVERED. Glass Fibre /Epoxy Resin Interface Life-time F-inal Technical 11’ port PreictonApril 1981 - A:’ril 1983 6. PERFORMING ORG. REPORT

  3. 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

  4. 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.

  5. 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.

  6. Time series prediction using artificial neural network for power stabilization

    SciTech Connect

    Puranik, G.; Philip, T.; Nail, B.

    1996-12-31

    Time series prediction has been applied to many business and scientific applications. Prominent among them are stock market prediction, weather forecasting, etc. Here, this technique has been applied to forecast plasma torch voltages to stabilize power using a backpropagation, a model of artificial neural network. The Extended-Delta-Bar-Delta algorithm is used to improve the convergence rate of the network and also to avoid local minima. Results from off-line data was quite promising to use in on-line.

  7. On the Prediction of α-Stable Time Series

    NASA Astrophysics Data System (ADS)

    Mohammadi, Mohammad; Mohammadpour, Adel

    2016-07-01

    This paper addresses the point prediction of α-stable time series. Our key idea is to define a new Hilbert space that contains α-stable processes. Then, we apply the advantage of Hilbert space theory for finding the best linear prediction. We show how to use the presented predictor practically for α-stable linear processes. The implementation of the presented method is easier than the implementation of the minimum dispersion method. We reveal the appropriateness of the presented method through an empirical study on predicting the natural logarithms of the volumes of SP500 market.

  8. Impaired predictive motor timing in patients with cerebellar disorders.

    PubMed

    Bares, Martin; Lungu, Ovidiu; Liu, Tao; Waechter, Tobias; Gomez, Christopher M; Ashe, James

    2007-06-01

    The ability to precisely time events is essential for both perception and action. There is evidence that the cerebellum is important for the neural representation of time in a variety of behaviors including time perception, the tapping of specific time intervals, and eye-blink conditioning. It has been difficult to assess the contribution of the cerebellum to timing during more dynamic motor behavior because the component movements themselves may be abnormal or any motor deficit may be due to an inability to combine the component movements into a complete action rather than timing per se. Here we investigated the performance of subjects with cerebellar disease in predictive motor timing using a task that involved mediated interception of a moving target, and we tested the effect of movement type (acceleration, deceleration, constant), speed (slow, medium, fast), and angle (0 degrees , 15 degrees and 30 degrees) on performance. The subjects with cerebellar damage were significantly worse at interception than healthy controls even when we controlled for basic motor impairments such as response time. Our data suggest that subjects with damage to the cerebellum have a fundamental problem with predictive motor timing and indicate that the cerebellum plays an essential role in integrating incoming visual information with motor output when making predictions about upcoming actions. The findings demonstrate that the cerebellum may have properties that would facilitate the processing or storage of internal models of motor behavior.

  9. 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

  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. Prediction of Long-Memory Time Series: A Tutorial Review

    NASA Astrophysics Data System (ADS)

    Bhansali, R. J.; Kokoszka, P. S.

    Two different approaches, called Type-I and Type-II, to linear least-squares prediction of a long-memory time series are distinguished. In the former, no new theory is required and a long-memory time series is treated on par with a standard short-memory time series and its multistep predictions are obtained by using the existing modelling approaches to prediction of such time series. The latter, by contrast, seeks to model the long-memory stochastic characteristics of the observed time series by a fractional process such that its dth fractional difference, 0 < d < 0.5, follows a standard short-memory process. The various approaches to constructing long-memory stochastic models are reviewed, and the associated question of parameter estimation for these models is discussed. Having fitted a long-memory stochastic model to a time series, linear multi-step forecasts of its future values are constructed from the model itself. The question of how to evaluate the multistep prediction constants is considered and three different methods proposed for doing so are outlined; it is further noted that, under appropriate regularity conditions, these methods apply also to the class of linear long memory processes with infinite variance. In addition, a brief review of the class of non-linear chaotic maps implying long-memory is given.

  12. 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

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

    PubMed

    Huang, Yu-Li; Hanauer, David A

    2016-05-09

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

  14. 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.

  15. 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

  16. An Approximation of a Hierarchical Logistic Regression Model Used To Establish the Predictive Validity of Scores on a Nursing Licensure Exam.

    ERIC Educational Resources Information Center

    Schmidt, Amy Elizabeth

    2000-01-01

    Conducted a validity study to examine the degree to which scores on the newly developed Diagnostic Readiness Test (DRT) and National League for Nursing Pre-Admission Test scores could predict success or failure on the National Council Licensure Examination for Registered Nurses (NCLEX-RN). Results for 5,698 students indicate that the DRT is a…

  17. 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.

  18. 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.

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

    ERIC Educational Resources Information Center

    Shiu, Ann Tak-Ying

    1999-01-01

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

  20. 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.

  1. Predictive influence in the accelerated failure time model.

    PubMed

    Bedrick, Edward J; Exuzides, Alex; Johnson, Wesley O; Thurmond, Mark C

    2002-09-01

    We develop case deletion diagnostics for prediction of future observations in the accelerated failure time model. We view prediction to be an important inferential goal in a survival analysis and thus it is important to identify whether particular observations may be influencing the quality of predictions. We use the Kullback-Leibler divergence as a measure of the discrepancy between the estimated probability distributions for the full and the case-deleted samples. In particular, we focus on the effect of case deletion on estimated survival curves but where we regard the survival curve estimate as a vehicle for prediction. We also develop a diagnostic for assessing the effect of case deletion on inferences for the median time to failure. The estimated median can be used with both predictive and estimative purposes in mind. We also discuss the relationship between our suggested measures and the corresponding Cook distance measure, which was designed with the goal of assessing estimative influence. Several applications of the proposed diagnostics are presented.

  2. 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

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

    PubMed

    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.

  4. 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.

  5. 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…

  6. The Prediction of Success in Nursing Education: Phase I and Phase II, 1959-1967.

    ERIC Educational Resources Information Center

    Thurston, John R.; And Others

    This study concerned the development and testing of an instrument designed to provide nursing schools with meaningful information about the personalities and potential problems of their students. In Phase I, the instrument--the Luther Hospital Sentence Completions (LHSC)--was constructed along with a Nursing Education Scale (NES) which provided…

  7. 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…

  8. 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…

  9. The assessment of patients' waiting and nursing consultation times at urban clinics in the National Capital District, Papua New Guinea.

    PubMed

    Benjamin, Amos L

    2003-01-01

    This study was conducted in the National Capital District during the months of August, September and October 2000. The study sites were the 3 urban clinics situated in the suburbs of Six Mile, Hohola and Konedobu. The aim of the study was to determine the patients' waiting times and nursing consultation times in the urban clinics. A total of 1075 patients were surveyed, including 264 children under 5 years of age. 58% of patients were males. 24% of patients were able to see a nurse within 30 minutes and 70% within 2 hours. 47% had to wait 1-3 hours to see a consulting nurse and a further 9.5% had to wait 3-5 hours. 67% of nursing consultations were 5 minutes or less, which is too short to interview, examine and prescribe treatment for the patients and to use the Paediatric 10 Steps. The short consultations of 5 minutes or less did not involve children under 5 years of age. There were only one to two nurses seeing the patients when 79% of patients were seen. This explains why the patients' waiting time was long. After consultations many patients (71%) were able to get their treatment within 30 minutes but 28% had to wait from 30 minutes to 2 hours for their treatment. The small number of nurses giving treatment leads to long waiting times. From the time of entry to exit out of the clinic, only 11% of patients spent 30 minutes or less in the clinic while 51% spent between 1 and 3 hours. The patients' waiting times and the short nursing consultation times are directly related to the insufficient number of nursing officers working in the clinics.

  10. The neural substrate of predictive motor timing in spinocerebellar ataxia.

    PubMed

    Bares, Martin; Lungu, Ovidiu V; Liu, Tao; Waechter, Tobias; Gomez, Christopher M; Ashe, James

    2011-06-01

    The neural mechanisms involved in motor timing are subcortical, involving mainly cerebellum and basal ganglia. However, the role played by these structures in predictive motor timing is not well understood. Unlike motor timing, which is often tested using rhythm production tasks, predictive motor timing requires visuo-motor coordination in anticipation of a future event, and it is evident in behaviors such as catching a ball or shooting a moving target. We examined the role of the cerebellum and striatum in predictive motor timing in a target interception task in healthy (n = 12) individuals and in subjects (n = 9) with spinocerebellar ataxia types 6 and 8. The performance of the healthy subjects was better than that of the spinocerebellar ataxia. Successful performance in both groups was associated with increased activity in the cerebellum (right dentate nucleus, left uvula (lobule V), and lobule VI), thalamus, and in several cortical areas. The superior performance in the controls was related to activation in thalamus, putamen (lentiform nucleus) and cerebellum (right dentate nucleus and culmen-lobule IV), which were not activated either in the spinocerebellar subjects or within a subgroup of controls who performed poorly. Both the cerebellum and the basal ganglia are necessary for the predictive motor timing. The degeneration of the cerebellum associated with spinocerebellar types 6 and 8 appears to lead to quantitative rather than qualitative deficits in temporal processing. The lack of any areas with greater activity in the spinocerebellar group than in controls suggests that limited functional reorganization occurs in this condition.

  11. 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

  12. Model predictive control of P-time event graphs

    NASA Astrophysics Data System (ADS)

    Hamri, H.; Kara, R.; Amari, S.

    2016-12-01

    This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

  13. 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.

  14. Determining the agent factors related with time management of responsible doctors and nurses in clinics at Ankara University hospitals.

    PubMed

    Acuner, Ahmet Munir; Nilgun, Sarp; Cifteli, F Gulay

    2006-01-01

    This research has been planned and conducted as a descriptive scanning model field study in order to determine the agent factors related with time management of doctors and nurses in positions of responsibility at Ankara University hospitals. As data collection instruments; the "Personal Information Form" which has been developed to determine the socio-demographical characteristics of the research group, the questionnaire of "Determining the Time Management Attitudes and Behaviour of Managers, Time Management Opportunities of the Managers, Prodcutive Working Times of the Managers and the Factors Causing Them to Lose Time", developed by Erdem has been used. It has been determined that the time management attitudes and behaviour of doctors, nurses and nurse assistants responsible for clinics are all different. It was found that nurse assistants graduated from pre-undergraduate or high schools are the least conscious of time management. In particular, nurse assistants of 36 years old and over with 21 years of work experience and 11 years of management experience show little awareness of time management. The time losing factors of the research group were found to be unnecessary visitors, lack of materials and the excessive amount of time spent on obtaining the necessary equipment.

  15. Timing and duration of nursing from birth affect neonatal porcine uterine matrix metalloproteinase 9 and tissue inhibitor of metalloproteinase 1.

    PubMed

    Ho, T Y; Rahman, K M; Camp, M E; Wiley, A A; Bartol, F F; Bagnell, C A

    2017-04-01

    Nursing for 2 d from birth supports neonatal porcine uterine and cervical development. However, it is not clear how timing or duration of lactocrine signaling from birth (postnatal day = PND 0) affects development of neonatal female reproductive tract tissues. Therefore, studies were conducted to determine effects of age at first nursing and duration of nursing from birth on specific elements of the matrix metalloproteinase (MMP)/tissue inhibitor of metalloproteinase (TIMP) system in uterine and cervical tissues at PND 2. When nursing was initiated at 0 h or 30 min of age, targeted proteins, including proMMP9 and MMP9, were detected in uterine and cervical tissues on PND 2, as was uterine TIMP1. However, these proteins were undetectable when nursing was delayed for 12 h and when gilts were fed milk replacer for 48 h from birth. Increasing the duration of nursing from 30 min to 12 h from birth increased uterine (P < 0.05) and cervical (P < 0.001) MMP9 levels to those observed in gilts nursed for 48 h. Similarly, uterine TIMP1 levels increased with duration of nursing. Uterine MMP2 levels were detectable but unaffected by age at first nursing or duration of nursing from birth. Uterine MMP2 and MMP9 activities, monitored by zymography, reflected immunoblotting data. Results provide evidence for the utility of MMP9 and TIMP1 as markers of age- and lactocrine-sensitive porcine female reproductive tract development.

  16. 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.

  17. 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

  18. Optimal model-free prediction from multivariate time series

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

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

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

    PubMed

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

    2015-05-01

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

  20. 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.

  1. 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

  2. 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.

  3. 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.

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

    PubMed Central

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

    2014-01-01

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

  5. Predicting the level of job satisfaction based on hardiness and its components among nurses with tension headache

    PubMed Central

    Mahdavi, A; Nikmanesh, E; AghaeI, M; Kamran, F; Zahra Tavakoli, Z; Khaki Seddigh, F

    2015-01-01

    Nurses are the most significant part of human resources in a sanitary and health system. Job satisfaction results in the enhancement of organizational productivity, employee commitment to the organization and ensuring his/ her physical and mental health. The present research was conducted with the aim of predicting the level of job satisfaction based on hardiness and its components among the nurses with tension headache. The research method was correlational. The population consisted of all the nurses with tension headache who referred to the relevant specialists in Tehran. The sample size consisted of 50 individuals who were chosen by using the convenience sampling method and were measured and investigated by using the research tools of “Job Satisfaction Test” of Davis, Lofkvist and Weiss and “Personal Views Survey” of Kobasa. The data analysis was carried out by using the Pearson Correlation Coefficient and the Regression Analysis. The research findings demonstrated that the correlation coefficient obtained for “hardiness”, “job satisfaction” was 0.506, and this coefficient was significant at the 0.01 level. Moreover, it was specified that the sense of commitment and challenge were stronger predictors for job satisfaction of nurses with tension headache among the components of hardiness, and, about 16% of the variance of “job satisfaction” could be explained by the two components (sense of commitment and challenge). PMID:28316713

  6. Predicting the level of job satisfaction based on hardiness and its components among nurses with tension headache.

    PubMed

    Mahdavi, A; Nikmanesh, E; AghaeI, M; Kamran, F; Zahra Tavakoli, Z; Khaki Seddigh, F

    2015-01-01

    Nurses are the most significant part of human resources in a sanitary and health system. Job satisfaction results in the enhancement of organizational productivity, employee commitment to the organization and ensuring his/ her physical and mental health. The present research was conducted with the aim of predicting the level of job satisfaction based on hardiness and its components among the nurses with tension headache. The research method was correlational. The population consisted of all the nurses with tension headache who referred to the relevant specialists in Tehran. The sample size consisted of 50 individuals who were chosen by using the convenience sampling method and were measured and investigated by using the research tools of "Job Satisfaction Test" of Davis, Lofkvist and Weiss and "Personal Views Survey" of Kobasa. The data analysis was carried out by using the Pearson Correlation Coefficient and the Regression Analysis. The research findings demonstrated that the correlation coefficient obtained for "hardiness", "job satisfaction" was 0.506, and this coefficient was significant at the 0.01 level. Moreover, it was specified that the sense of commitment and challenge were stronger predictors for job satisfaction of nurses with tension headache among the components of hardiness, and, about 16% of the variance of "job satisfaction" could be explained by the two components (sense of commitment and challenge).

  7. A Stochastic Semiclassical Time Front Prediction for Ocean Acoustics

    NASA Astrophysics Data System (ADS)

    Hegewisch, Katherine; Tomsovic, Steven

    2008-05-01

    Low frequency sound propagates in the ocean within a wave guide formed by the confining effects of temperature, salinity and pressure on the sound speed. This wave guide enables long range propagation upwards of 3000 km. Within the wave guide, sound scatters due to range dependent sound speed oscillations from internal waves and gives rise to wave chaos, where most of the classical rays are chaotic. This chaos poses challenges to ray predictions of the range and frequency dependence of properties of the 'time fronts', the acoustic arrivals in depth and time. Though semiclassical theory works well for strongly chaotic systemss, finding the necessary eigenrays for long ranges is unrealistic here. Instead, we utilize semiclassical and perturbation theories ONLY for short ranges and extend these results to long ranges using a previously introduced diffusive theory. We verify the diffusive assumptions and demonstrate the analytic results for these theories for short ranges before arriving at a stochastic prediction.

  8. 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

  9. 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.

  10. 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.

  11. 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

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

    NASA Astrophysics Data System (ADS)

    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.

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

    SciTech Connect

    Cuntz, M. Heidelberg Universitaet )

    1990-01-01

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

  14. 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

  15. 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.

  16. Connectionist Architectures for Time Series Prediction of Dynamical Systems

    NASA Astrophysics Data System (ADS)

    Weigend, Andreas Sebastian

    We investigate the effectiveness of connectionist networks for predicting the future continuation of temporal sequences. The problem of overfitting, particularly serious for short records of noisy data, is addressed by the method of weight-elimination: a term penalizing network complexity is added to the usual cost function in back-propagation. We describe the dynamics of the procedure and clarify the meaning of the parameters involved. From a Bayesian perspective, the complexity term can be usefully interpreted as an assumption about prior distribution of the weights. We analyze three time series. On the benchmark sunspot series, the networks outperform traditional statistical approaches. We show that the network performance does not deteriorate when there are more input units than needed. In the second example, the notoriously noisy foreign exchange rates series, we pick one weekday and one currency (DM vs. US). Given exchange rate information up to and including a Monday, the task is to predict the rate for the following Tuesday. Weight-elimination manages to extract a significant part of the dynamics and makes the solution interpretable. In the third example, the networks predict the resource utilization of a chaotic computational ecosystem for hundreds of steps forward in time.

  17. Using Latent Transition Analysis in Nursing Research to Explore Change Over Time

    PubMed Central

    Roberts, Tonya J.; Ward, Sandra E.

    2011-01-01

    Background Latent transition analysis is a method of modeling change over time in categorical variables. It has been used in the social sciences for many years, but not in nursing research. Objective To illustrate the utility of latent transition analysis for nursing research by presenting a case example (a secondary analysis of data from a previously conducted randomized control trial testing the effectiveness of a tailored psychoeducational intervention to decrease patient-related attitudinal barriers to cancer pain management) and to understand for whom, and in what direction, the tailored intervention resulted in change with respect to attitudinal barriers and pain symptoms. Method The model was developed by (a) defining a class structure based on individuals’ barrier patterns, (b) adding demographic predictors and distal pain outcomes, and (c) modeling and testing transitions across classes. Results There were two classes of individuals: Low Barriers and High Barriers. Older, less educated individuals were more likely to be in the High Barriers class at time 1. Individuals in either class did not have different pain outcomes at the end of the study. Of those individuals that transitioned across classes, those who received the intervention were statistically more likely to move in a favorable direction (to the Low Barriers class). Furthermore, there is evidence that some individuals in the control group had unfavorable outcomes. Discussion The results from the example provide useful information about for whom, and in what direction, the intervention resulted in change. Latent transition analysis is a valuable procedure for nurse researchers because it collapses large arrays of categorical data into meaningful patterns. It is a flexible modeling procedure with extensions allowing further understanding of a change process. PMID:21127448

  18. Time-motion analysis of clinical nursing documentation during implementation of an electronic operating room management system for ophthalmic surgery.

    PubMed

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

    2013-01-01

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

  19. 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.

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

    NASA Astrophysics Data System (ADS)

    Pettarin, Nicola; Campolo, Marina; Soldati, Alfredo

    2015-12-01

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

  1. 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.

  2. Real-time multi-model decadal climate predictions

    NASA Astrophysics Data System (ADS)

    Smith, Doug M.; Scaife, Adam A.; Boer, George J.; Caian, Mihaela; Doblas-Reyes, Francisco J.; Guemas, Virginie; Hawkins, Ed; Hazeleger, Wilco; Hermanson, Leon; Ho, Chun Kit; Ishii, Masayoshi; Kharin, Viatcheslav; Kimoto, Masahide; Kirtman, Ben; Lean, Judith; Matei, Daniela; Merryfield, William J.; Müller, Wolfgang A.; Pohlmann, Holger; Rosati, Anthony; Wouters, Bert; Wyser, Klaus

    2013-12-01

    We present the first climate prediction of the coming decade made with multiple models, initialized with prior observations. This prediction accrues from an international activity to exchange decadal predictions in near real-time, in order to assess differences and similarities, provide a consensus view to prevent over-confidence in forecasts from any single model, and establish current collective capability. We stress that the forecast is experimental, since the skill of the multi-model system is as yet unknown. Nevertheless, the forecast systems used here are based on models that have undergone rigorous evaluation and individually have been evaluated for forecast skill. Moreover, it is important to publish forecasts to enable open evaluation, and to provide a focus on climate change in the coming decade. Initialized forecasts of the year 2011 agree well with observations, with a pattern correlation of 0.62 compared to 0.31 for uninitialized projections. In particular, the forecast correctly predicted La Niña in the Pacific, and warm conditions in the north Atlantic and USA. A similar pattern is predicted for 2012 but with a weaker La Niña. Indices of Atlantic multi-decadal variability and Pacific decadal variability show no signal beyond climatology after 2015, while temperature in the Niño3 region is predicted to warm slightly by about 0.5 °C over the coming decade. However, uncertainties are large for individual years and initialization has little impact beyond the first 4 years in most regions. Relative to uninitialized forecasts, initialized forecasts are significantly warmer in the north Atlantic sub-polar gyre and cooler in the north Pacific throughout the decade. They are also significantly cooler in the global average and over most land and ocean regions out to several years ahead. However, in the absence of volcanic eruptions, global temperature is predicted to continue to rise, with each year from 2013 onwards having a 50 % chance of exceeding the

  3. [Dialogues in psychology and nursing in a time of shifting paradigms].

    PubMed

    Corradi-Webster, Clarissa Mendonça; Carvalho, Ana Maria Pimenta

    2011-08-01

    Currently, we are experiencing a paradigm shift in relation to how we understand health and care. The biomedical model has been replaced by a vision of an integral being, and care emphasis is being placed on health promotion and disease prevention. However, the discourse of personal responsibility for health can generate in patients feelings of guilt, shame, fear and paranoia, while in professionals it can cause feelings of powerlessness and frustration. These feelings disrupt attachments and, thus, reduce the effectiveness of care. The objective of this theoretical study is to propose a dialogue between Psychology, with social constructionist sensitivity, and Nursing, to examine the possibilities of improving care from this approach. As an alternative to the discourse of personal responsibility, relational responsibility and understanding health and care in the long time, lived time and short time, is proposed.

  4. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts.

    PubMed

    Balasubramanian, A; Shamsuddin, R; Prabhakaran, B; Sawant, A

    2017-03-07

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5-91.4%); (ii) the predictive modeling yields lowest accuracies (50-60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96-0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  5. Predictive modeling of respiratory tumor motion for real-time prediction of baseline shifts

    NASA Astrophysics Data System (ADS)

    Balasubramanian, A.; Shamsuddin, R.; Prabhakaran, B.; Sawant, A.

    2017-03-01

    Baseline shifts in respiratory patterns can result in significant spatiotemporal changes in patient anatomy (compared to that captured during simulation), in turn, causing geometric and dosimetric errors in the administration of thoracic and abdominal radiotherapy. We propose predictive modeling of the tumor motion trajectories for predicting a baseline shift ahead of its occurrence. The key idea is to use the features of the tumor motion trajectory over a 1 min window, and predict the occurrence of a baseline shift in the 5 s that immediately follow (lookahead window). In this study, we explored a preliminary trend-based analysis with multi-class annotations as well as a more focused binary classification analysis. In both analyses, a number of different inter-fraction and intra-fraction training strategies were studied, both offline as well as online, along with data sufficiency and skew compensation for class imbalances. The performance of different training strategies were compared across multiple machine learning classification algorithms, including nearest neighbor, Naïve Bayes, linear discriminant and ensemble Adaboost. The prediction performance is evaluated using metrics such as accuracy, precision, recall and the area under the curve (AUC) for repeater operating characteristics curve. The key results of the trend-based analysis indicate that (i) intra-fraction training strategies achieve highest prediction accuracies (90.5–91.4%) (ii) the predictive modeling yields lowest accuracies (50–60%) when the training data does not include any information from the test patient; (iii) the prediction latencies are as low as a few hundred milliseconds, and thus conducive for real-time prediction. The binary classification performance is promising, indicated by high AUCs (0.96–0.98). It also confirms the utility of prior data from previous patients, and also the necessity of training the classifier on some initial data from the new patient for reasonable

  6. 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.

  7. 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…

  8. 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.

  9. 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.

  10. Quantitative research on critical thinking and predicting nursing students' NCLEX-RN performance.

    PubMed

    Romeo, Elizabeth M

    2010-07-01

    The concept of critical thinking has been influential in several disciplines. Both education and nursing in general have been attempting to define, teach, and measure this concept for decades. Nurse educators realize that critical thinking is the cornerstone of the objectives and goals for nursing students. The purpose of this article is to review and analyze quantitative research findings relevant to the measurement of critical thinking abilities and skills in undergraduate nursing students and the usefulness of critical thinking as a predictor of National Council Licensure Examination-Registered Nurse (NCLEX-RN) performance. The specific issues that this integrative review examined include assessment and analysis of the theoretical and operational definitions of critical thinking, theoretical frameworks used to guide the studies, instruments used to evaluate critical thinking skills and abilities, and the role of critical thinking as a predictor of NCLEX-RN outcomes. A list of key assumptions related to critical thinking was formulated. The limitations and gaps in the literature were identified, as well as the types of future research needed in this arena.

  11. 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.

  12. Time-dependent Predictive Values of Prognostic Biomarkers with Failure Time Outcome.

    PubMed

    Zheng, Yingye; Cai, Tianxi; Pepe, Margaret S; Levy, Wayne C

    2008-01-01

    In a prospective cohort study, information on clinical parameters, tests and molecular markers is often collected. Such information is useful to predict patient prognosis and to select patients for targeted therapy. We propose a new graphical approach, the positive predictive value (PPV) curve, to quantify the predictive accuracy of prognostic markers measured on a continuous scale with censored failure time outcome. The proposed method highlights the need to consider both predictive values and the marker distribution in the population when evaluating a marker, and it provides a common scale for comparing different markers. We consider both semiparametric and nonparametric based estimating procedures. In addition, we provide asymptotic distribution theory and resampling based procedures for making statistical inference. We illustrate our approach with numerical studies and datasets from the Seattle Heart Failure Study.

  13. Time-predictable recurrence model for large earthquakes

    SciTech Connect

    Shimazaki, K.; Nakata, T.

    1980-04-01

    We present historical and geomorphological evidence of a regularity in earthquake recurrence at three different sites of plate convergence around the Japan arcs. The regularity shows that the larger an earthquake is, the longer is the following quiet period. In other words, the time interval between two successive large earthquakes is approximately proportional to the amount of coseismic displacement of the preceding earthquake and not of the following earthquake. The regularity enables us, in principle, to predict the approximate occurrence time of earthquakes. The data set includes 1) a historical document describing repeated measurements of water depth at Murotsu near the focal region of Nankaido earthquakes, 2) precise levelling and /sup 14/C dating of Holocene uplifted terraces in the southern boso peninsula facing the Sagami trough, and 3) similar geomorphological data on exposed Holocene coral reefs in Kikai Island along the Ryukyu arc.

  14. Satellite attitude prediction by multiple time scales method

    NASA Technical Reports Server (NTRS)

    Tao, Y. C.; Ramnath, R.

    1975-01-01

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

  15. 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.

  16. 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.

  17. 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.

  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. 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

  20. 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.

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

    PubMed Central

    Jansson, Inger; Pilhammar, Ewa; Forsberg, Anna

    2009-01-01

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

  2. 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.

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

    PubMed Central

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

    2015-01-01

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

  4. Gut microbiota may predict host divergence time during Glires evolution.

    PubMed

    Li, Huan; Qu, Jiapeng; Li, Tongtong; Yao, Minjie; Li, Jiaying; Li, Xiangzhen

    2017-01-29

    The gut microbial communities of animals play key roles in host evolution. However, the possible relationship between gut microbiota and host divergence time remains unknown. Here, we investigated the gut microbiota of eight Glires species (four lagomorpha species and four rodent species) distributed throughout the Qinghai-Tibet plateau and Inner Mongolia grassland. Lagomorphs and rodents had distinct gut microbial compositions. Three out of four lagomorpha species were dominated by Firmicutes, while rodents were dominated by Bacteroidetes in general. The alpha diversity values (Shannon diversity and evenness) exhibited significant differences between any two species within lagomorphs, whereas there were no significant differences among rodents. The structure of the gut microbiota between lagomorphs and rodents showed significant differences. In addition, we calculated host phylogeny and divergence times, and used a phylogenetic approach to reconstruct how the animal gut microbiota has diverged from their ancestral species. Some core bacterial genera (e.g. Prevotella and Clostridium) shared by more than nine-tenths of all the Glires individuals associated with plant polysaccharide degradation showed marked changes within lagomorphs. Differences in Glires gut microbiota (based on weighted UniFrac and Bray-Curtis dissimilarity metrics) were positively correlated with host divergence time. Our results thus suggest the gut microbial composition is associated with host phylogeny, and further suggest that dissimilarity of animal gut microbiota may predict host divergence time.

  5. Strategies for retaining midcareer nurses.

    PubMed

    McGillis Hall, Linda; Lalonde, Michelle; Dales, Lorraine; Peterson, Jessica; Cripps, Lauren

    2011-12-01

    One method of reducing predicted shortages because of the aging nursing workforce is to increase retention. Few studies have examined the unique needs of midcareer nurses. A mixed-method approach including surveys and focus groups was used to identify key retention strategies and desires for midcareer nurses. Salary, benefits, positive working relationships, flexible scheduling, and the opportunity for continued education were identified as key retention strategies from this study. Registered nurses in this study reported higher perceptions of their work and work environment than licensed practical nurses did. Differences in work outcomes were evident across sectors, with community nurses reporting higher levels of job satisfaction and perceptions of work quality than nurses in acute and long-term care. Findings suggest that recruitment opportunities may exist with midcareer nurses seeking employment to return to work after time off to have a family. Proactive retention policies that focus on the needs of midcareer nurses would demonstrate a commitment and interest in keeping them in their work positions and in the profession.

  6. Predicting Student Retention and Academic Achievement in Western United States Associate Degree in Nursing Programs.

    ERIC Educational Resources Information Center

    Wilson, Margaret

    This study addresses the extreme shortage of registered nurses (RNs) in California and the changing demographics of those entering the occupation. It focuses on the issue that racially diverse RN students have shown a significantly lower completion rate than their white counterparts. Since community colleges provide 70% of the hospital-based RN…

  7. 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.

  8. Comparing response time, errors, and satisfaction between text-based and graphical user interfaces during nursing order tasks.

    PubMed

    Staggers, N; Kobus, D

    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 leam (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.

  9. 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

  10. 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

    2016-09-06

    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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-09-01

    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.

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

    NASA Astrophysics Data System (ADS)

    King, Jeffery T.; Karpenko, Mark

    2016-03-01

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

  13. Political participation of registered nurses.

    PubMed

    Vandenhouten, Christine L; Malakar, Crystalmichelle L; Kubsch, Sylvia; Block, Derryl E; Gallagher-Lepak, Susan

    2011-08-01

    Level of political participation and factors contributing to participation were measured among Midwest RNs (n = 468) via an online survey (Cronbach's α = .95). Respondents reported engaging in primarily "low cost" activities (e.g., voting, discussing politics, and contacting elected officials), with fewer reporting speaking at public gatherings, participating in demonstrations, and membership in nursing organizations. Psychological engagement was most predictive (p < .001) of political participation with the dimensions of political interest, political efficacy, and political information/knowledge highly significant (p < .001). Resources (time/money/civic skills) significantly contributed to political participation (p < .001). Less than half (40%) felt they could impact local decisions, and fewer (32%) felt they could impact state or national government decisions. Most respondents (80%) indicated their nursing courses lacked political content and did not prepare them for political participation. Findings showed that nurse educators and leaders of professional nursing organizations need to model and cultivate greater psychological engagement among students and nurses.

  14. Predicting Rocket or Jet Noise in Real Time

    NASA Technical Reports Server (NTRS)

    Frendi, Kader

    2007-01-01

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

  15. Can the care transitions measure predict rehospitalization risk or home health nursing use of home healthcare patients?

    PubMed

    Ryvicker, Miriam; McDonald, Margaret V; Trachtenberg, Melissa; Peng, Timothy R; Sridharan, Sridevi; Feldman, Penny H

    2013-01-01

    The Care Transitions Measure (CTM) was designed to assess the quality of patient transitions from the hospital. Many hospitals are using the measure to inform their efforts to improve transitional care. We sought to determine if the measure would have utility for home healthcare providers by predicting newly admitted patients at heightened risk for emergency department use, rehospitalization, or increased home health nursing visits. The CTM was administered to 495 home healthcare patients shortly after hospital discharge and home healthcare admission. Follow-up interviews were completed 30 and 60 days post hospital discharge. Interview data were supplemented with agency assessment and service use data. We did not find evidence that the CTM could predict home healthcare patients having an elevated risk for emergent care, rehospitalization, or higher home health nursing use. Because Medicare/Medicaid-certified home healthcare providers already use a comprehensive, mandated start of care assessment, the CTM may not provide them additional crucial information. Process and outcome measurement is increasingly becoming part of usual care. Selection of measures appropriate for each service setting requires thorough site-specific evaluation. In light of our findings, we cannot recommend the CTM as an additional measure in the home healthcare setting.

  16. Time Granularity Transformation of Time Series Data for Failure Prediction of Overhead Line

    NASA Astrophysics Data System (ADS)

    Ma, Yan; Zhu, Wenbing; Yao, Jinxia; Gu, Chao; Bai, Demeng; Wang, Kun

    2017-01-01

    In this paper, we give an approach of transforming time series data with different time granularities into the same plane, which is the basis of further association analysis. We focus on the application of overhead line tripping. First all the relative state variables with line tripping are collected into our big data platform. We collect line account, line fault, lightning, power load and meteorological data. Second we respectively pre-process the five kinds of data to guarantee the integrality of data and simplicity of analysis. We use a representation way combining the aggregated representation and trend extraction methods, which considers both short term variation and long term trend of time sequence. Last we use extensive experiments to demonstrate that the proposed time granularity transformation approach not only lets multiple variables analysed on the same plane, but also has a high prediction accuracy and low running time no matter for SVM or logistic regression algorithm.

  17. Prediction of shock arrival times from CME and flare data

    NASA Astrophysics Data System (ADS)

    Núñez, Marlon; Nieves-Chinchilla, Teresa; Pulkkinen, Antti

    2016-08-01

    This paper presents the Shock Arrival Model (SARM) for predicting shock arrival times for distances from 0.72 AU to 8.7 AU by using coronal mass ejections (CME) and flare data. SARM is an aerodynamic drag model described by a differential equation that has been calibrated with a data set of 120 shocks observed from 1997 to 2010 by minimizing the mean absolute error (MAE), normalized to 1 AU. SARM should be used with CME data (radial, earthward, or plane-of-sky speeds) and flare data (peak flux, duration, and location). In the case of 1 AU, the MAE and the median of absolute errors were 7.0 h and 5.0 h, respectively, using the available CME/flare data. The best results for 1 AU (an MAE of 5.8 h) were obtained using both CME data, either radial or cone model-estimated speeds, and flare data. For the prediction of shock arrivals at distances from 0.72 AU to 8.7 AU, the normalized MAE and the median were 7.1 h and 5.1 h, respectively, using the available CME/flare data. SARM was also calibrated to be used with CME data alone or flare data alone, obtaining normalized MAE errors of 8.9 h and 8.6 h, respectively, for all shock events. The model verification was carried out with an additional data set of 20 shocks observed from 2010 to 2012 with radial CME speeds to compare SARM with the empirical ESA model and the numerical MHD-based ENLIL model. The results show that the ENLIL's MAE was lower than the SARM's MAE, which was lower than the ESA's MAE. The SARM's best results were obtained when both flare and true CME speeds were used.

  18. 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.

  19. Learning in the First Professional Job: The First Year of Full Time Employment After College for Accountants, Engineers and Nurses.

    ERIC Educational Resources Information Center

    Eraut, Michael; Maillardet, Fred; Miller, Carolyn; Steadman, Stephen; Ali, Amer; Blackman, Claire; Furner, Judith

    Learning in the first professional job was examined in a study of 40 nurses, 27 engineers, and 16 accountants who were in their first full year of full-time employment after college in hospitals and firms located in the United Kingdom. Data were collected through the following activities: (1) interviews with the respondents; (2) 1- to 2-day visits…

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

    ERIC Educational Resources Information Center

    Carlson, Joanne S.

    2012-01-01

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

  1. 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…

  2. 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…

  3. 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…

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

    ERIC Educational Resources Information Center

    Hanford, Karen J.

    2010-01-01

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

  5. [Is It Time to Implement a 12-Hour Shift for Nurses in Taiwan?

    PubMed

    Lin, Yi-Fung; Chang, Shiow-Ru; Wang, Li-Ting

    2017-04-01

    The twelve-hour shift system, first introduced in the U.S. in 1967 to address a nursing shortage, is now the main system of shift rotation used in numerous countries. In recent years, several hospitals in Taiwan have implemented the 12-hour shift model as one initiative to improve the problems of overtime and high turnover rate among nursing staff. Under this model, nurses work only three to four days per week for 12-hour shifts per day. Despite the increase in numbers of days off, there is growing concern that long shift hours may harm both the safety of patients and the well being of the nurses. The aim of the present article is to explain the application of the 12-hour shift system and to review the potential impacts of this model. Benefits of the 12-hour shift system include improving quality of life for nursing staff, reducing the turnover rate, and increasing job satisfaction. Primary concerns regarding this system include patient safety, nurse fatigue, and the potential negative effects on the sleep quality of nurses. These findings may be referenced by policymakers considering the development / implementation of flexible work schedules in Taiwan. The government must set a ceiling on work hours allowed per week and impose limits on overtime in order to prevent burnout in nursing staff.

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

    PubMed Central

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

    2016-01-01

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

  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. 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

  9. Understanding and Predicting Time-Dependent Dune Erosion

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  10. Evidence toads may modulate landing preparation without predicting impact time

    PubMed Central

    Cox, S. M.; Gillis, Gary

    2017-01-01

    ABSTRACT Within anurans (frogs and toads), cane toads (Bufo marinus) perform particularly controlled landings in which the forelimbs are exclusively used to decelerate and stabilize the body after impact. Here we explore how toads achieve dynamic stability across a wide range of landing conditions. Specifically, we suggest that torques during landing could be reduced by aligning forelimbs with the body's instantaneous velocity vector at impact (impact angle). To test whether toad forelimb orientation varies with landing conditions, we used high-speed video to collect forelimb and body kinematic data from six animals hopping off platforms of different heights (0, 5 and 9 cm). We found that toads do align forelimbs with the impact angle. Further, toads align forelimbs with the instantaneous velocity vector well before landing and then track its changes until touchdown. This suggests that toads may be prepared to land well before they hit the ground rather than preparing for impact at a specific moment, and that they may use a motor control strategy that allows them to perform controlled landings without the need to predict impact time. PMID:27895052

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

    PubMed

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

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

  12. 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

  13. 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.

  14. Prediction of Universal Time using the artificial neural network

    NASA Astrophysics Data System (ADS)

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

    2014-12-01

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

  15. Real-Time Reporting of Small Operational Failures in Nursing Care

    PubMed Central

    Ferrer, Robert L.

    2016-01-01

    Addressing microsystem problems from the frontline holds promise for quality enhancement. Frontline providers are urged to apply quality improvement; yet no systematic approach to problem detection has been tested. This study investigated a self-report approach to detecting operational failures encountered during patient care. Methods. Data were collected from 5 medical-surgical units over 4 weeks. Unit staff documented operational failures on a small distinctive Pocket Card. Frequency distributions for the operational failures in each category were calculated for each hospital overall and disaggregated by shift. Rate of operational failures on each unit was also calculated. Results. A total of 160 nurses participated in this study reporting a total of 2,391 operational failures over 429 shifts. Mean number of problems per shift varied from 4.0 to 8.5 problems with equipment/supply problems being the most commonly reported category. Conclusions. Operational failures are common on medical-surgical clinical units. It is feasible for unit staff to record these failures in real time. Many types of failures were recognized by frontline staff. This study provides preliminary evidence that the Pocket Card is a feasible approach to detecting operational failures in real time. Continued research on methodologies to investigate the impact of operational failures is warranted. PMID:27895940

  16. What predicts the selection of nursing as a career choice in 5th and 6th year school students?

    PubMed

    Neilson, Gavin R; Jones, Martyn C

    2012-07-01

    Demand for nursing care, and nurses, is growing in the United Kingdom given an increasingly ageing patient population with long-term co-morbidities. An ageing nursing workforce and fewer school leavers entering nursing are key barriers to student nurse recruitment. This paper aims to identify the socio-demographic and correlates nursing as a career choice in 5th and 6th year school students. This cross-sectional descriptive study gathered self-administered questionnaires from a total cohort of 5th and 6th year school students (n=1059) in one educational authority in Scotland. A response rate of 100% was achieved, with 702 students expressing a career choice. Some 71.7% (n=503) of students providing a full data set would never consider nursing, even if they obtained poor grades. Only 28.3% (n=199) would ever consider nursing. Students cited nursing as a career choice if they were female, of average to below average academic ability/achievement, expressed a positive attitude to nursing as a degree subject which was shared by their career guidance teacher. Each additional higher reduced the likelihood of nursing as a career choice by 22%. Nursing is an unpopular career choice amongst school students. Strategies are required to improve the occupational image of nursing in secondary education.

  17. Loneliness and nursing home admission among rural older adults.

    PubMed

    Russell, D W; Cutrona, C E; de la Mora, A; Wallace, R B

    1997-12-01

    In this study, the authors tested the relation between loneliness and subsequent admission to a nursing home over a 4-year time period in a sample of approximately 3,000 rural older Iowans. Higher levels of loneliness were found to increase the likelihood of nursing home admission and to decrease the time until nursing home admission. The influence of extremely high loneliness on nursing home admission remained statistically significant after controlling for other variables, such as age, education, income, mental status, physical health, morale, and social contact, that were also predictive of nursing home admission. Several mechanisms are proposed to explain the link between extreme loneliness and nursing home admission. These include loneliness as a precipitant of declines in mental and physical health and nursing home placement as a strategy to gain social contact with others. Implications for preventative interventions are discussed.

  18. [Responsibility in health care: regarding the time we live as intensive care nurses].

    PubMed

    Vargas, Mara Ambrosina de Oliveira; Ramos, Flávia Regina Souza

    2011-08-01

    This qualitative investigation was supported by Foucault's analysis with emphasis on the notion of governability, and had the following objectives: to analyze the relationship between techno-biomedicine and bioethics as discourses of the contemporaneousness implied in the production of nurses' subjectivity within the context of the Intensive Care Unit (ICU); and approach the responsibility implied in health care as one of the unfolding strategies of technology of speech of bioethics and biotechnology, creating certain forms of the nurse understanding and intervening in the Intensive Care Unit (ICU). From the perspective of the multiple ways that can emerge when analyzing a critical reading of analyzed texts and interviews with nurses, responsibility in health care was unfolded into categories that expressed the responsibility in front of new languages and of nursing as a guardian of certain attributes in the Intensive Care Unit (ICU).

  19. 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.

  20. Climate predictability and prediction skill on seasonal time scales over South America from CHFP models

    NASA Astrophysics Data System (ADS)

    Osman, Marisol; Vera, C. S.

    2016-11-01

    This work presents an assessment of the predictability and skill of climate anomalies over South America. The study was made considering a multi-model ensemble of seasonal forecasts for surface air temperature, precipitation and regional circulation, from coupled global circulation models included in the Climate Historical Forecast Project. Predictability was evaluated through the estimation of the signal-to-total variance ratio while prediction skill was assessed computing anomaly correlation coefficients. Both indicators present over the continent higher values at the tropics than at the extratropics for both, surface air temperature and precipitation. Moreover, predictability and prediction skill for temperature are slightly higher in DJF than in JJA while for precipitation they exhibit similar levels in both seasons. The largest values of predictability and skill for both variables and seasons are found over northwestern South America while modest but still significant values for extratropical precipitation at southeastern South America and the extratropical Andes. The predictability levels in ENSO years of both variables are slightly higher, although with the same spatial distribution, than that obtained considering all years. Nevertheless, predictability at the tropics for both variables and seasons diminishes in both warm and cold ENSO years respect to that in all years. The latter can be attributed to changes in signal rather than in the noise. Predictability and prediction skill for low-level winds and upper-level zonal winds over South America was also assessed. Maximum levels of predictability for low-level winds were found were maximum mean values are observed, i.e. the regions associated with the equatorial trade winds, the midlatitudes westerlies and the South American Low-Level Jet. Predictability maxima for upper-level zonal winds locate where the subtropical jet peaks. Seasonal changes in wind predictability are observed that seem to be related to

  1. Improving practice one patient, one nurse, one day at a time: design and evaluation of a quality education workshop for oncology nurses.

    PubMed

    Lillington, Linda; Scaramuzzo, Leah; Friese, Christopher; Sein, Elaine; Harrison, Karen; Lefebvre, Kristine B; Fessele, Kristen

    2013-12-01

    High-quality nursing care is not delivered consistently to the millions of Americans treated for invasive cancer in the United States. As part of its quality initiative, the Oncology Nursing Society (ONS) developed and tested nursing-sensitive quality measures for breast cancer care. Findings from the pilot testing suggested significant knowledge and practice gaps that could be addressed through member education.

  2. The Validity of College Grade Prediction Equations Over Time.

    ERIC Educational Resources Information Center

    Sawyer, Richard L.; Maxey, James

    A sample of 260 colleges was surveyed during the years 1972-1976 to determine the validity of predicting college freshmen grades from standardized test scores and high school grades using the American College Testing (ACT) Assessment Program, an evaluative and placement service for students and educators involved in the transition from high school…

  3. 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…

  4. Generalized dualities in one-time physics as holographic predictions from two-time physics

    NASA Astrophysics Data System (ADS)

    Araya, Ignacio J.; Bars, Itzhak

    2014-03-01

    In the conventional formalism of physics, with one time, systems with different Hamiltonians or Lagrangians have different physical interpretations and are considered to be independent systems unrelated to each other. However, in this paper we construct explicitly canonical maps in one-time (1T) phase space (including timelike components, specifically the Hamiltonian) to show that it is appropriate to regard various 1T physics systems, with different Lagrangians or Hamiltonians, as being duals of each other. This concept is similar in spirit to dualities discovered in more complicated examples in field theory or string theory. Our approach makes it evident that such generalized dualities are widespread. This suggests that, as a general phenomenon, there are hidden relations and hidden symmetries that conventional 1T physics does not capture, implying the existence of a more unified formulation of physics that naturally supplies the hidden information. In fact, we show that two-time (2T) physics in (d +2) dimensions is the generator of these dualities in 1T physics in d dimensions by providing a holographic perspective that unifies all the dual 1T systems into one. The unifying ingredient is a gauge symmetry in phase space. Via such dualities it is then possible to gain new insights toward new physical predictions not suspected before, and suggest new methods of computation that yield results not obtained before. As an illustration, we will provide concrete examples of 1T systems in classical mechanics that are solved analytically for the first time via our dualities. These dualities in classical mechanics have counterparts in quantum mechanics and field theory, and in some simpler cases they have already been constructed in field theory. We comment on the impact of our approach on the meaning of space-time and on the development of new computational methods based on dualities.

  5. Association between symptom burden and time to hospitalization, nursing home placement, and death among the chronically ill urban homebound

    PubMed Central

    Yang, Nancy; Ornstein, Katherine; Reckrey, Jennifer M.

    2017-01-01

    CONTEXT Homebound adults experience significant symptom burden. OBJECTIVES (1) To examine demographic and clinical characteristics associated with high symptom burden in the homebound, and (2) to examine associations between symptom burden and time to hospitalization, nursing home placement, and death. METHODS 318 patients newly enrolled in the Mount Sinai Visiting Doctors Program, an urban home-based primary care program, were studied. Patient sociodemographic characteristics, symptom burden (measured via the Edmonton Symptom Assessment Scale, ESAS), and incidents of hospitalization, nursing home placement, and death were collected via medical chart review. Multivariate Cox proportional hazards models were used to analyze the effect of high symptom burden on time to first hospitalization, nursing home placement, and death. RESULTS 43% of the study sample had severe symptom burden (i.e. ESAS score ≥6 on at least one symptom). Patients with severe symptom burden were younger (82.0 vs 85.5 yrs, p<0.01), had more comorbid conditions (3.2 vs 2.5 Charlson score, p<0.01), higher prevalence of depression (43.4% vs 12.0%, p<0.01), lower prevalence of dementia (34.3% vs 60.6%, p<0.01), and utilized fewer hours of home health services (86.2 vs 110.4 hrs/wk, p<0.01). Severe symptom burden was associated with a shorter time to first hospitalization (hazards ratio=1.51, 95% CI 1.06–2.15) in adjusted models, but had no association with time to nursing home placement or death. CONCLUSION The homebound with severe symptom burden represent a unique patient cohort who are at increased risk of hospitalization. Tailored symptom management via home-based primary and palliative care programs may prevent unnecessary healthcare utilization in this population. PMID:27033155

  6. [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.

  7. New BSN nurses' perspectives on the transition to practice in changing economic times.

    PubMed

    Craig, Carol; Moscato, Susan; Moyce, Sally

    2012-04-01

    Helping nursing graduates transition to practice is a concern for nursing educators and employers. This article reports graduates' perceptions of transition both when jobs were plentiful and when jobs were scarce. Survey results from comparison of 2008 and 2010 graduates demonstrated few differences. Key indicators of successful transition were positive feedback at the work site, increased self-confidence on the part of the new graduate, and acceptance by the care team. Presence of good role models, ability to ask questions safely, and ongoing feedback on performance assisted successful transition.

  8. 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…

  9. 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.

  10. 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…

  11. A real-time Excel-based scheduling solution for nursing staff reallocation.

    PubMed

    Tuominen, Outi Anneli; Lundgren-Laine, Heljä; Kauppila, Wiveka; Hupli, Maija; Salanterä, Sanna

    2016-09-30

    Aim This article describes the development and testing of an Excel-based scheduling solution for the flexible allocation and reallocation of nurses to cover sudden, unplanned absences among permanent nursing staff. Method A quasi-experimental, one group, pre- and post-test study design was used ( Box 1 ) with total sampling. Participants (n=17) were selected purposefully by including all ward managers (n=8) and assistant ward managers (n=9) from one university hospital department. The number of sudden absences among the nursing staff was identified during two 4-week data collection periods (pre- and post-test). Results During the use of the paper-based scheduling system, 121 absences were identified; during the use of the Excel-based system, 106 were identified. The main reasons for the use of flexible 'floating' nurses were sick leave (n=66) and workload (n=31). Other reasons (n=29) included patient transfer to another hospital, scheduling errors and the start or end of employment. Conclusion The Excel-based scheduling solution offered better support in obtaining substitute labour inside the organisation, with smaller employment costs. It also reduced the number of tasks ward managers had to carry out during the process of reallocating staff.

  12. Nurses' personal statements about factors that influence their decisions about the time they spend with residents with long-term mental illness living in psychiatric group dwellings.

    PubMed

    Hellzén, Ove

    2004-09-01

    One seldom-discussed issue is the factors that influence nurses' decisions about the time they spend with residents in psychiatric care. This study uses a qualitative naturalistic approach and consists of an analysis of focus-group interviews with nurses, which aimed to identify factors affecting nurses' decisions about being with or being nonattendant in their relationship with their residents. Two series of focus-group interviews were conducted, interpreted and analysed through content analysis. The study included all the staff (n=32) at two municipal psychiatric group dwellings housing residents mainly with a diagnosis of long-term schizophrenia. This study revealed that the main factor that determined nurses' nurse/resident time together or nonattendance time was whether they liked or disliked the individual resident. One possible explanation is the carers' change from a perspective in which the nursing care was given on the basis of each resident's needs and rights, based on the individual nurse's professional judgement, to a consumer perspective, which leads to a change in responsibility from themselves to the individual residents.

  13. 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.

  14. Predicting sexual assault kit submission among adolescent rape cases treated in forensic nurse examiner programs.

    PubMed

    Shaw, Jessica; Campbell, Rebecca

    2013-12-01

    Following a sexual assault, victims are usually advised to have a medical forensic exam and sexual assault forensic exam kit (SAK). Once completed, the SAK is to be transported by law enforcement to the crime lab for analysis. However, many kits are never transported to the crime lab, thereby preventing forensic evidence obtained in the kit to be used during the prosecutorial process. The current study examined rates of SAK submission for 393 adolescent sexual assault cases in two Midwestern communities and explored what factors predicted law enforcement officers' submission of SAKs to the crime lab for analysis. Findings reveal that more than 40% of the adolescent cases did not have their SAK submitted, and several factors, including the age and race of the victim, the number of perpetrators in the assault, and the number of assaultive acts, predicted SAK submission. Implications for SAK community protocols are discussed.

  15. 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…

  16. SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

    SciTech Connect

    Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.; Young, Christopher J.; Encarnacao, Andre V.; Chael, Eric P.; Phillips, W. Scott

    2016-10-11

    The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source to receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.

  17. SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

    DOE PAGES

    Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.; ...

    2016-10-11

    The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

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

    ERIC Educational Resources Information Center

    Panchanadeswaran, Subadra; McCloskey, Laura A.

    2007-01-01

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

  19. Predicting survival time for metastatic castration resistant prostate cancer: An iterative imputation approach

    PubMed Central

    Deng, Detian; Du, Yu; Ji, Zhicheng; Rao, Karthik; Wu, Zhenke; Zhu, Yuxin; Coley, R. Yates

    2016-01-01

    In this paper, we present our winning method for survival time prediction in the 2015 Prostate Cancer DREAM Challenge, a recent crowdsourced competition focused on risk and survival time predictions for patients with metastatic castration-resistant prostate cancer (mCRPC). We are interested in using a patient's covariates to predict his or her time until death after initiating standard therapy. We propose an iterative algorithm to multiply impute right-censored survival times and use ensemble learning methods to characterize the dependence of these imputed survival times on possibly many covariates. We show that by iterating over imputation and ensemble learning steps, we guide imputation with patient covariates and, subsequently, optimize the accuracy of survival time prediction. This method is generally applicable to time-to-event prediction problems in the presence of right-censoring. We demonstrate the proposed method's performance with training and validation results from the DREAM Challenge and compare its accuracy with existing methods. PMID:28299176

  20. Timing Correlations in Proteins Predict Functional Modules and Dynamic Allostery.

    PubMed

    Lin, Milo M

    2016-04-20

    How protein structure encodes functionality is not fully understood. For example, long-range intraprotein communication can occur without measurable conformational change and is often not captured by existing structural correlation functions. It is shown here that important functional information is encoded in the timing of protein motions, rather than motion itself. I introduce the conditional activity function to quantify such timing correlations among the degrees of freedom within proteins. For three proteins, the conditional activities between side-chain dihedral angles were computed using the output of microseconds-long atomistic simulations. The new approach demonstrates that a sparse fraction of side-chain pairs are dynamically correlated over long distances (spanning protein lengths up to 7 nm), in sharp contrast to structural correlations, which are short-ranged (<1 nm). Regions of high self- and inter-side-chain dynamical correlations are found, corresponding to experimentally determined functional modules and allosteric connections, respectively.

  1. 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.

  2. 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.

  3. Predicting Prostate Cancer Progression at Time of Diagnosis

    DTIC Science & Technology

    2013-07-01

    Active surveillance incorporates serial PSA measurements , physical examinations, and repeat prostate biopsies to monitor for either the presence of occult...reflecting events throughout the prostate gland and suitable for repeat measurements over time. PCA3 and the TMPRSS2:ERG fusion are 2 prostate cancer... measurements of TMPRSS2:ERG transcript levels associate with cancer volume and grade at prosta- tectomy, and upgrading from biopsy histologic assess- ments (31

  4. Predicted Water Immersion Survival Times for Anti-Exposure Ensembles

    DTIC Science & Technology

    2005-10-01

    level of garment insulation and anthropometrics to provide guidelines for safe immersed exposure times. 176 Report Documentation Page Form ApprovedOMB...males only. The model can account for variations in weight, body fat (BF), and metabolic rate. For this study, three anthropometric cases were used: (1...chest, abdomen, right and left thighs, calves, feet, biceps, forearms and hands. A clo value can be specified for each area. Clo is a measure of

  5. The MDS Mortality Risk Index: The evolution of a method for predicting 6-month mortality in nursing home residents

    PubMed Central

    2010-01-01

    Background Accurate prognosis is vital to the initiation of advance care planning particularly in a vulnerable, at risk population such as care home residents. The aim of this paper is to report on the revision and simplification of the MDS Mortality Rating Index (MMRI) for use in clinical practice to predict the probability of death in six months for care home residents. Methods The design was a secondary analysis of a US Minimum Data Set (MDS) for long term care residents using regression analysis to identify predictors of mortality within six months. Results Using twelve easy to collect items, the probability of mortality within six months was accurately predicted within the MDS database. The items are: admission to the care home within three months; lost weight unintentionally in past three months; renal failure; chronic heart failure; poor appetite; male; dehydrated; short of breath; active cancer diagnosis; age; deteriorated cognitive skills in past three months; activities of daily living score. Conclusion A lack of recognition of the proximity of death is often blamed for inappropriate admission to hospital at the end of an older person's life. An accurate prognosis for older adults living in a residential or nursing home can facilitate end of life decision making and planning for preferred place of care at the end of life. The original MMRI was derived and validated from a large database of long term care residents in the USA. However, this simplification of the revised index (MMRI-R) may provide a means for facilitating prognostication and end of life discussions for application outside the USA where the MDS is not in use. Prospective testing is needed to further test the accuracy of the MMRI-R and its application in the UK and other non-MDS settings. PMID:20637076

  6. Improving predictability of time series using maximum entropy methods

    NASA Astrophysics Data System (ADS)

    Chliamovitch, G.; Dupuis, A.; Golub, A.; Chopard, B.

    2015-04-01

    We discuss how maximum entropy methods may be applied to the reconstruction of Markov processes underlying empirical time series and compare this approach to usual frequency sampling. It is shown that, in low dimension, there exists a subset of the space of stochastic matrices for which the MaxEnt method is more efficient than sampling, in the sense that shorter historical samples have to be considered to reach the same accuracy. Considering short samples is of particular interest when modelling smoothly non-stationary processes, which provides, under some conditions, a powerful forecasting tool. The method is illustrated for a discretized empirical series of exchange rates.

  7. 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.

  8. Allometric scaling and prediction of concentration-time profiles of coagulation factors in humans from animals.

    PubMed

    Mahmood, Iftekhar

    2013-09-01

    Allometric scaling is a useful tool in early drug development and can be used for the prediction of human pharmacokinetic (PK) parameters from animal PK parameters. The main objective of this work was to predict concentration-time profiles of coagulation factors in humans in a multi-compartment system using animal PK parameters. The prediction of concentration-time profiles in humans in a multi-compartment system was based on the predicted values of clearance and volumes of distribution (V(c), V(ss) and V(β)) from animals. Five coagulation factors from the literature were chosen that were described by two-compartment model in both humans and animals. Clearance and volumes of distribution from animals were allometrically scaled to humans and then were used to predict concentration-time profiles in humans. The predicted concentration-time profile for a given coagulation factor was accurate for most of the time points. Percent prediction error range varied across coagulation factors. The prediction error >50% was observed either at 1 or a maximum of two time points for a given drug. The study indicated that the allometric scaling can be useful in the prediction of concentration-time profiles of coagulation factors in humans from animals and may be helpful in designing a first-in-human study.

  9. 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.

  10. 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.

  11. 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…

  12. A Hypothetical Model to Predict Nursing Students’ Perceptions of the Usefulness of Pre-Service Integrated Management of Childhood Illness Training

    PubMed Central

    Al-Araimi, Fannah A.; Langrial, Sitwat U.

    2016-01-01

    Objectives This study aimed to test a hypothetical model to predict nursing students’ perceptions of the usefulness of pre-service Integrated Management of Childhood Illness (IMCI) training and their intention to apply this training in clinical practice. Methods This study was carried out at the Sur Nursing Institute, Sur, Oman, in May 2015. Using six predefined constructs, a hypothetical structural model was created. The constructs were used as latent variables to highlight their probable impact on intention to apply IMCI-related knowledge and skills in practice. A structured validated questionnaire was subsequently developed to assess the perceptions of nursing students. Factor loadings and calculated variances were examined to ensure convergent validity. Cronbach’s alpha was used to calculate internal consistency reliability. Results Factor loadings for each item in the model were above 0.70. All of the constructs had Cronbach’s alpha values over 0.700, except for enhanced assessment skills (Cronbach’s alpha: 0.694). The variance extracted value was 0.815 for perceived usefulness, 0.800 for enhanced assessment skills, 0.687 for enhanced knowledge, attitudes and skills, 0.697 for enhanced confidence, 0.674 for enhanced counselling skills and 0.805 for future intention to use IMCI in a clinical setting. Conclusion Overall, the results support the hypothetical model and indicate that nursing students perceive IMCI training to be beneficial and intend to apply IMCI-related knowledge and skills in clinical practice. PMID:28003894

  13. A divide-and-conquer method for space-time series prediction

    NASA Astrophysics Data System (ADS)

    Deng, Min; Yang, Wentao; Liu, Qiliang; Zhang, Yunfei

    2017-01-01

    Space-time series can be partitioned into space-time smooth and space-time rough, which represent different scale characteristics. However, most existing methods for space-time series prediction directly address space-time series as a whole and do not consider the interaction between space-time smooth and space-time rough in the process of prediction. This will possibly affect the accuracy of space-time series prediction, because the interaction between these two components (i.e., space-time smooth and space-time rough) may cause one of them as dominant component, thus weakening the behavior of the other. Therefore, a divide-and-conquer method for space-time prediction is proposed in this paper. First, the observational fine-grained data are decomposed into two components: coarse-grained data and the residual terms of fine-grained data. These two components are then modeled, respectively. Finally, the predicted values of the fine-grained data are obtained by integrating the predicted values of the coarse-grained data with the residual terms. The experimental results of two groups of different space-time series demonstrated the effectiveness of the divide-and-conquer method.

  14. 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.

  15. The relationships among work stress, resourcefulness, and depression level in psychiatric nurses.

    PubMed

    Wang, Shu Mi; Lai, Chien Yu; Chang, Yong-Yuan; Huang, Chiung-Yu; Zauszniewski, Jaclene A; Yu, Ching-Yun

    2015-02-01

    Psychiatric nurses are exposed to highly stressful work environments that can lead to depression over time. This study aimed to explore the relationships among work stress, resourcefulness, and depression levels of psychiatric nurses. A cross-sectional design with randomized sampling was used; 154 psychiatric nurses were recruited from six medical centers in Taiwan. Psychiatric nurses' work stress was found positively correlated with their depression level, and negatively related to resourcefulness. Work stress significantly predicted depression level. These results suggest that the hospital administrative units may develop training courses about resourcefulness skills to reduce psychiatric nurses' work stress, and improve their mental health.

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

    PubMed Central

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

    2005-01-01

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

  17. Nurse-Faculty Census, 1968.

    ERIC Educational Resources Information Center

    National League for Nursing, New York, NY. Research and Development.

    This is the 1968 biennial census of nurse-faculty members teaching in nursing programs and in cooperating institutions providing clinical experiences for students in nursing. It is intended as an overview of current conditions and a basis for future estimates and planning. As of January 1968, 20,077 full-time and 3,554 part-time nurse-faculty…

  18. 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.

  19. 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

  20. 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.

  1. Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

    PubMed

    Limongi, Roberto; Silva, Angélica M

    2016-11-01

    The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

  2. The shortage of nurses and nursing faculty: what critical care nurses can do.

    PubMed

    Siela, Debra; Twibell, K Renee; Keller, Vicki

    2008-01-01

    Nurses are needed more than ever to support the healthcare needs of every American. Nurses make up the greatest single component of hospital staff. In 2004, of the almost 3 million nurses in the United States, 83% were employed in nursing, and 58% of those were employed full-time. However, a severe shortage of nurses exists nationwide, putting the safe, effective healthcare of Americans in jeopardy. The concurrent shortage of nursing faculty has significant impact on the potential for admitting and graduating sufficient numbers of nursing students to address the shortage of prepared nurses. A close examination of the demographics of the 3 million nurses provides a context for an in-depth discussion of strategies that critical care nurses can employ to help alleviate the nursing and nurse faculty shortages.

  3. 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.

  4. 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

  5. Improving timeliness for acute asthma care for paediatric ED patients using a nurse driven intervention: an interrupted time series analysis

    PubMed Central

    Brown, Kathleen; Iqbal, Sabah; Sun, Su-Lin; Fritzeen, Jennifer; Chamberlain, James; C. Mullan, Paul

    2016-01-01

    Asthma is the most common chronic paediatric disease treated in the emergency department (ED). Rapid corticosteroid administration is associated with improved outcomes, but our busy ED setting has made it challenging to achieve this goal. Our primary aim was to decrease the time to corticosteroid administration in a large, academic paediatric ED. We conducted an interrupted time series analysis for moderate to severe asthma exacerbations of one to 18 year old patients. A multidisciplinary team designed the intervention of a bedside nurse initiated administration of oral dexamethasone, to replace the prior system of a physician initiated order for oral prednisone. Our baseline and intervention periods were 12 month intervals. Our primary process measure was the time to corticosteroid administration. Other process measures included ED length of stay, admission rate, and rate of emesis. The balance measures included rate of return visits to the ED or clinic within five days, as well as the proportion of discharged patients who were admitted within five days. No special cause variation occurred in the baseline period. The mean time to corticosteroid administration decreased significantly, from 98 minutes in the baseline period to 59 minutes in the intervention period (p < 0.01), and showed special cause variation improvement within two months after the intervention using statistical process control methodology. We sustained the improvement and demonstrated a stable process. The intervention period had a significantly lower admission rate (p<0.01) and emesis rate (p<0.01), with no unforeseen harm to patients found with any of our balance measures. In summary, the introduction of a nurse initiated, standardized protocol for corticosteroid therapy for asthma exacerbations in a paediatric ED was associated with decreased time to corticosteroid administration, admission rates, and post-corticosteroid emesis. PMID:28090325

  6. "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."

  7. 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.

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

    ERIC Educational Resources Information Center

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

    2012-01-01

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

  9. 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

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

    NASA Astrophysics Data System (ADS)

    Miziński, Bartłomiej; Niedzielski, Tomasz

    2014-05-01

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

  11. A data-integrated simulation model to evaluate nurse-patient assignments.

    PubMed

    Sundaramoorthi, Durai; Chen, Victoria C P; Rosenberger, Jay M; Kim, Seoung Bum; Buckley-Behan, Deborah F

    2009-09-01

    This research develops a novel data-integrated simulation to evaluate nurse-patient assignments (SIMNA) based on a real data set provided by a northeast Texas hospital. Tree-based models and kernel density estimation (KDE) were utilized to extract important knowledge from the data for the simulation. Classification and Regression Tree models, data mining tools for prediction and classification, were used to develop five tree structures: (a) four classification trees from which transition probabilities for nurse movements are determined, and (b) a regression tree from which the amount of time a nurse spends in a location is predicted based on factors such as the primary diagnosis of a patient and the type of nurse. Kernel density estimation is used to estimate the continuous distribution for the amount of time a nurse spends in a location. Results obtained from SIMNA to evaluate nurse-patient assignments in Medical/Surgical unit I of the northeast Texas hospital are discussed.

  12. 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,…

  13. Hematology and biochemistry reference intervals for Ontario commercial nursing pigs close to the time of weaning.

    PubMed

    Perri, Amanda M; O'Sullivan, Terri L; Harding, John C S; Wood, R Darren; Friendship, Robert M

    2017-04-01

    The evaluation of pig hematology and biochemistry parameters is rarely done largely due to the costs associated with laboratory testing and labor, and the limited availability of reference intervals needed for interpretation. Within-herd and between-herd biological variation of these values also make it difficult to establish reference intervals. Regardless, baseline reference intervals are important to aid veterinarians in the interpretation of blood parameters for the diagnosis and treatment of diseased swine. The objective of this research was to provide reference intervals for hematology and biochemistry parameters of 3-week-old commercial nursing piglets in Ontario. A total of 1032 pigs lacking clinical signs of disease from 20 swine farms were sampled for hematology and iron panel evaluation, with biochemistry analysis performed on a subset of 189 randomly selected pigs. The 95% reference interval, mean, median, range, and 90% confidence intervals were calculated for each parameter.

  14. Nurse staffing level and nosocomial infections: empirical evaluation of the case-crossover and case-time-control designs.

    PubMed

    Hugonnet, Stéphane; Villaveces, Andrés; Pittet, Didier

    2007-06-01

    The authors compared a case-crossover design, a case-time-control design, and a cohort design to evaluate the effect of nurse staffing level on the risk of nosocomial infections. They evaluated two strategies, conditional logistic regression and generalized estimating equation, to analyze the case-crossover study. The study was performed among critically ill patients in the medical intensive care unit of the University of Geneva Hospitals, Geneva, Switzerland. Of 366 patients who stayed more than 7 days in the intensive care unit between 1999 and 2002, 144 developed an infection. The main reasons for admission were infectious (35.3%), cardiovascular (32.5%), and pulmonary (19.7%) conditions. A comparison of the three study designs showed that lower nurse staffing was associated with an approximately 50% increased risk of nosocomial infections. All analyses yielded similar estimates, except that the point estimate obtained by the conditional logistic regression used in the case-crossover design was biased away from unity; the generalized estimating equation yielded unbiased results and is the most appropriate technique for case-crossover designs. The case-crossover methodology in hospital epidemiology is a promising alternative to traditional approaches, but selection of the referent periods is challenging.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    Xu, Chengcheng; Liu, Pan; Wang, Wei

    2016-09-01

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

  17. Estimation and prediction of noise power based on variational Bayesian and adaptive ARMA time series

    NASA Astrophysics Data System (ADS)

    Zhang, Jingyi; Li, Yonggui; Zhu, Yonggang; Li, Binwu

    2014-04-01

    Estimation and prediction of noise power are very important for communication anti-jamming and efficient allocation of spectrum resources in adaptive wireless communication and cognitive radio. In order to estimate and predict the time-varying noise power caused by natural factors and jamming in the high frequency channel, Variational Bayesian algorithm and adaptive ARMA time series are proposed. Through establishing the time-varying noise power model, which controlled by the noise variance rate, the noise power can be estimated with Variational Bayesian algorithm, and the results show that the estimation error is related to observation interval. What's more, through the analysis of the correlation characteristics of the estimation power, noise power can be predicted based on adaptive ARMA time series, and the results show that it will be available to predict the noise power in next 5 intervals with the proportional error less than 0.2.

  18. Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario

    PubMed Central

    Shu, Hua; Song, Ci; Pei, Tao; Xu, Lianming; Ou, Yang; Zhang, Libin; Li, Tao

    2016-01-01

    Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals’ average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day’s WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas. PMID:27879663

  19. Queuing Time Prediction Using WiFi Positioning Data in an Indoor Scenario.

    PubMed

    Shu, Hua; Song, Ci; Pei, Tao; Xu, Lianming; Ou, Yang; Zhang, Libin; Li, Tao

    2016-11-22

    Queuing is common in urban public places. Automatically monitoring and predicting queuing time can not only help individuals to reduce their wait time and alleviate anxiety but also help managers to allocate resources more efficiently and enhance their ability to address emergencies. This paper proposes a novel method to estimate and predict queuing time in indoor environments based on WiFi positioning data. First, we use a series of parameters to identify the trajectories that can be used as representatives of queuing time. Next, we divide the day into equal time slices and estimate individuals' average queuing time during specific time slices. Finally, we build a nonstandard autoregressive (NAR) model trained using the previous day's WiFi estimation results and actual queuing time to predict the queuing time in the upcoming time slice. A case study comparing two other time series analysis models shows that the NAR model has better precision. Random topological errors caused by the drift phenomenon of WiFi positioning technology (locations determined by a WiFi positioning system may drift accidently) and systematic topological errors caused by the positioning system are the main factors that affect the estimation precision. Therefore, we optimize the deployment strategy during the positioning system deployment phase and propose a drift ratio parameter pertaining to the trajectory screening phase to alleviate the impact of topological errors and improve estimates. The WiFi positioning data from an eight-day case study conducted at the T3-C entrance of Beijing Capital International Airport show that the mean absolute estimation error is 147 s, which is approximately 26.92% of the actual queuing time. For predictions using the NAR model, the proportion is approximately 27.49%. The theoretical predictions and the empirical case study indicate that the NAR model is an effective method to estimate and predict queuing time in indoor public areas.

  20. Predicting dose-time profiles of solar energetic particle events using Bayesian forecasting methods.

    PubMed

    Neal, J S; Townsend, L W

    2001-12-01

    Bayesian inference techniques, coupled with Markov chain Monte Carlo sampling methods, are used to predict dose-time profiles for energetic solar particle events. Inputs into the predictive methodology are dose and dose-rate measurements obtained early in the event. Surrogate dose values are grouped in hierarchical models to express relationships among similar solar particle events. Models assume nonlinear, sigmoidal growth for dose throughout an event. Markov chain Monte Carlo methods are used to sample from Bayesian posterior predictive distributions for dose and dose rate. Example predictions are provided for the November 8, 2000, and August 12, 1989, solar particle events.

  1. Trip-oriented travel time prediction (TOTTP) with historical vehicle trajectories

    NASA Astrophysics Data System (ADS)

    Xu, Tao; Li, Xiang; Claramunt, Christophe

    2017-03-01

    Accurate travel time prediction is undoubtedly of importance to both traffic managers and travelers. In highly-urbanized areas, trip-oriented travel time prediction (TOTTP) is valuable to travelers rather than traffic managers as the former usually expect to know the travel time of a trip which may cross over multiple road sections. There are two obstacles to the development of TOTTP, including traffic complexity and traffic data coverage.With large scale historical vehicle trajectory data and meteorology data, this research develops a BPNN-based approach through integrating multiple factors affecting trip travel time into a BPNN model to predict trip-oriented travel time for OD pairs in urban network. Results of experiments demonstrate that it helps discover the dominate trends of travel time changes daily and weekly, and the impact of weather conditions is non-trivial.

  2. Predicting Time-to-Relapse in Breast Cancer Using Neural Networks

    DTIC Science & Technology

    1997-12-01

    AD GRANT NUMBER DÄMD17-94-J-4137 TITLE: Predicting Time-to-Relapse in Breast Cancer Using Neural Networks PRINCIPAL INVESTIGATOR: Jonathan D...Nov 97) 4. TITLE AND SUBTITLE Predicting Time-to-Relapse in Breast Cancer Using Neural Networks 6. AUTHOR(S) Buckley, Jonathan D., Ph.D. 5...Biomedical Laboratories. Date in TABLE OF CONTENTS STANDARD FORM 298 ii FOREWORD iii TABLE OF CONTENTS iv INTRODUCTION 1 Neural networks - a

  3. Impact of meteorological predictions on real-time spring flow forecasting

    NASA Astrophysics Data System (ADS)

    Coulibaly, Paulin

    2003-12-01

    Meteorological predictions, such as precipitation and temperature, are commonly used to improve real-time hydrologic forecasting, despite their inherent uncertainty and their absence in the model calibration stage. In this study, we quantify the effect of meteorological prediction errors on the accuracy of daily spring reservoir inflow forecasts using weather predictions in both the model calibration and testing phases. Different modelling experiments are compared using an operational conceptual model and nonlinear empirical models to assess the effects of using daily numerical weather predictions as opposed to the use of historical observations. It is found that, even with large prediction errors, meteorological forecasts can provide significant improvement of spring flow forecast for up to 7 days lead time, particularly for low flows. Spring flow prediction errors associated with the type of hydrological model used are significantly larger than those related to the meteorological predictions, particularly for 1 to 4 days ahead forecasts. The experimental results also indicate that multiple model-based forecasting using an iterative prediction approach appears to be the most effective method for an adequate use of weather predictions. Copyright

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

    PubMed

    Cavanagh, James F

    2015-04-15

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

  5. 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

  6. 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.

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

    NASA Astrophysics Data System (ADS)

    Khokhar, Rashid H.; Md Sap, Mohd Noor

    2005-03-01

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

  8. Gain scheduled continuous-time model predictive controller with experimental validation on AC machine

    NASA Astrophysics Data System (ADS)

    Wang, Liuping; Gan, Lu

    2013-08-01

    Linear controllers with gain scheduling have been successfully used in the control of nonlinear systems for the past several decades. This paper proposes the design of gain scheduled continuous-time model predictive controller with constraints. Using induction machine as an illustrative example, the paper will show the four steps involved in the design of a gain scheduled predictive controller: (i) linearisation of a nonlinear plant according to operating conditions; (ii) the design of linear predictive controllers for the family of linear models; (iii) gain scheduled predictive control law that will optimise a multiple model objective function with constraints, which will also ensure smooth transitions (i.e. bumpless transfer) between the predictive controllers; (iv) experimental validation of the gain scheduled predictive control system with constraints.

  9. A Prospective, Observational Study to Assess the Use of Thermography to Predict Progression of Discolored Intact Skin to Necrosis Among Patients in Skilled Nursing Facilities.

    PubMed

    Cox, Jill; Kaes, Loretta; Martinez, Miguel; Moles, Daniel

    2016-10-01

    Skin temperature may help prospectively determine whether an area of skin discoloration will evolve into necrosis. A prospective, observational study was conducted in 7 skilled nursing facilities to determine if skin temperature measured using infrared thermography could predict the progression of discolored intact skin (blanchable erythema, Stage 1 pressure ulcer, or sus- pected deep tissue injury [sDTI]) to necrosis and to evaluate if nurses could effectively integrate thermography into the clinical setting. Patients residing in or presenting to the facility between October 2014 and August 2015 with a pressure-related area of discolored skin determined to be blanchable erythema, a Stage 1 pressure ulcer, or sDTI and anticipated length of stay >6 days were assessed at initial presentation of the discolored area and after 7 and 14 days by facility nurses trained on camera operation and study protocol. Variables included patient demographic and clinical data, data related to the discolored area (eg, size, date of initial discovery), and temperature and appearance differences between discolored and adjacent intact skin. Skin temperatures at the discolored and adjacent areas were measured during the initial assessment. All facility pressure ulcer prevention and treatment protocols derived from evidence-based clinical practice guidelines remained in use during the study time period. Participating nurses completed a 2-part, pencil/paper survey to examine the feasibility of incorporating thermography for skin assessment into practice. Data analyses were performed using descriptive statistics (frequency analyses) and bivariate analysis (t-tests and chi-squared tests); logistic regression was used to assess associations among patient and pressure ulcer variables. Of the 67 patients studied, the overall mean age was 85 years (SD 10); 52 were women; 63 were Caucasian; and the top 3 diagnoses, accounting for 60% of the study sample, included neurologic (ie, cardiovascular

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

    PubMed

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

    2015-08-01

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

  11. 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

  12. 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).

  13. An Extended Expectation-Confirmation Model for Mobile Nursing Information System Continuance.

    PubMed

    Hsieh, Pi-Jung; Lai, Hui-Min; Ma, Chen-Chung; Alexander, Judith W; Lin, Memg-Yi

    2016-11-01

    Nursing is critical in health care systems and comprises the planning, execution, and documentation of nursing care. To better manage health care information during patient care, the use of a mobile nursing information system (MNIS) provides more time to care for inpatients by reducing time-consuming and redundant paperwork. The purpose of this study was to extend the expectation-confirmation model and explore the roles of nursing professional competency (skill in use), habit (customary use), satisfaction (with use), and frequency of prior use in the context of MNIS continuance usage. We randomly chose 3 hospitals from among 14 hospitals in Taiwan that had indicated they used an MNIS. We conducted a field survey of nurses who had experience using the MNIS. We used a valid sample of 90 nurses to test the research model, using structural equation modeling with the partial least squares method. The results show that habit and frequency of prior use had a significant impact on MNIS continuance usage. Satisfaction and frequency of prior use had a significant impact on habit. Nurses' professional competence is crucial to perceived usefulness and, thus, is relevant in the context of MNIS continuance usage. When habit weakens over time, the continuance intention predicts continuance usage. This study showed that the extended expectation-confirmation model effectively predicts nurses' MNIS continuance usage and provides implications. Academics and practitioners should understand how nurses' habits form and how they affect continued MNIS use. Understanding the antecedents of habits can help nursing managers identify and manipulate habit formation.

  14. Time-Preference Tests Fail to Predict Behavior Related to Self-control

    PubMed Central

    Arfer, Kodi B.; Luhmann, Christian C.

    2017-01-01

    According to theory, choices relating to patience and self-control in domains as varied as drug use and retirement saving are driven by generalized preferences about delayed rewards. Past research has shown that measurements of these time preferences are associated with these choices. Research has also attempted to examine how well such measurements can predict choices, but only with inappropriate analytical methods. Moreover, it is not clear which of the many kinds of time-preference tests that have been proposed are most useful for prediction, and a theoretically important aspect of time preferences, nonstationarity, has been neglected in measurement. In Study 1, we examined three approaches to measuring time preferences with 181 users of Mechanical Turk. Retest reliability, for both immediate and 1-month intervals, was decent, as was convergent validity between tests, and association was similar to previous results, but predictive accuracy for 10 criterion variables (e.g., tobacco use) was approximately nil. In Study 2, we examined one other approach to measuring time preferences, and 40 criterion variables, using 7,127 participants in the National Longitudinal Survey of Youth 1979. Time preferences were significantly related to criterion variables, but predictive accuracy was again poor. Our findings imply serious problems for using time-preference tests to predict real-world decisions. The results of Study 1 further suggest there is little value in measuring nonstationarity separately from patience. PMID:28232810

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

    NASA Astrophysics Data System (ADS)

    Karthikeyan, L.; Nagesh Kumar, D.

    2013-10-01

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

  16. 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

  17. 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…

  18. DCDS: A Real-time Data Capture and Personalized Decision Support System for Heart Failure Patients in Skilled Nursing Facilities

    PubMed Central

    Zhu, Wei; Luo, Lingyun; Jain, Tarun; Boxer, Rebecca S.; Cui, Licong; Zhang, Guo-Qiang

    2016-01-01

    Heart disease is the leading cause of death in the United States. Heart failure disease management can improve health outcomes for elderly community dwelling patients with heart failure. This paper describes DCDS, a real-time data capture and personalized decision support system for a Randomized Controlled Trial Investigating the Effect of a Heart Failure Disease Management Program (HF-DMP) in Skilled Nursing Facilities (SNF). SNF is a study funded by the NIH National Heart, Lung, and Blood Institute (NHLBI). The HF-DMP involves proactive weekly monitoring, evaluation, and management, following National HF Guidelines. DCDS collects a wide variety of data including 7 elements considered standard of care for patients with heart failure: documentation of left ventricular function, tracking of weight and symptoms, medication titration, discharge instructions, 7 day follow up appointment post SNF discharge and patient education. We present the design and implementation of DCDS and describe our preliminary testing results. PMID:28269970

  19. 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

  20. 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.

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

    PubMed

    Rusconi, Marco; Valleriani, Angelo

    2016-06-20

    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.

  2. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  4. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.

    PubMed

    Li, Yi; Chen, Yuren

    2016-12-30

    To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.

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

    PubMed Central

    Rodrigues, Joel J. P. C.

    2014-01-01

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

  6. Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve

    PubMed Central

    Li, Yi; Chen, Yuren

    2016-01-01

    To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers’ perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers’ vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers’ perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers’ perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers’ perception-response time. PMID:28042851

  7. 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…

  8. Time series analysis as input for clinical predictive modeling: Modeling cardiac arrest in a pediatric ICU

    PubMed Central

    2011-01-01

    Background Thousands of children experience cardiac arrest events every year in pediatric intensive care units. Most of these children die. Cardiac arrest prediction tools are used as part of medical emergency team evaluations to identify patients in standard hospital beds that are at high risk for cardiac arrest. There are no models to predict cardiac arrest in pediatric intensive care units though, where the risk of an arrest is 10 times higher than for standard hospital beds. Current tools are based on a multivariable approach that does not characterize deterioration, which often precedes cardiac arrests. Characterizing deterioration requires a time series approach. The purpose of this study is to propose a method that will allow for time series data to be used in clinical prediction models. Successful implementation of these methods has the potential to bring arrest prediction to the pediatric intensive care environment, possibly allowing for interventions that can save lives and prevent disabilities. Methods We reviewed prediction models from nonclinical domains that employ time series data, and identified the steps that are necessary for building predictive models using time series clinical data. We illustrate the method by applying it to the specific case of building a predictive model for cardiac arrest in a pediatric intensive care unit. Results Time course analysis studies from genomic analysis provided a modeling template that was compatible with the steps required to develop a model from clinical time series data. The steps include: 1) selecting candidate variables; 2) specifying measurement parameters; 3) defining data format; 4) defining time window duration and resolution; 5) calculating latent variables for candidate variables not directly measured; 6) calculating time series features as latent variables; 7) creating data subsets to measure model performance effects attributable to various classes of candidate variables; 8) reducing the number of

  9. 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…

  10. Practical calculator programs. Part 6. Program predicts drilling time, penetration rate

    SciTech Connect

    Chenevert, M.E.; Hollo, R.

    1981-10-05

    Chenevert's program, designed for the TI-59 programmable calculator, can determine the time (hr) needed to drill a new well to a given depth and the expected penetration rate (ft/hr) at that depth. The program bases its calculations on bit records obtained from an offset well. Extrapolation of the results can predict drilling times for deeper wells.

  11. Trust in health care providers: factors predicting trust among homeless veterans over time.

    PubMed

    van den Berk-Clark, Carissa; McGuire, James

    2014-08-01

    We examined whether a combination of predisposing, enabling, need, and primary care experience variables would predict trust in medical health care providers for homeless veterans over 18 months. Linear mixed model analysis indicated that, among these variables, race, social support, service-connected disability status, and satisfaction and continuity with providers predicted trust in provider over time. Trust in providers improved during the initial stages of the relationship between patient and provider and then declined to slightly below baseline levels over time. Further research is needed to determine generalizability and effects of provider trust on patient health care status over longer periods of time.

  12. Making time for reflexive dialogue in philosophical group discussion: extending the debate on the militarization of nursing.

    PubMed

    Springer, Rusla Anne; Kent-Wilkinson, Arlene; Ewashen, Carol; Ali, Ruth

    2013-01-01

    In the 2010 July-September issue of Advances in Nursing Science, Perron et al offered a persuasive and substantive account of the troubling incursion of military speech into nursing practice and education. The article proved contentious, resulting in accusations of fallacious misrepresentation. This article extends the philosophical debate initiated by Perron et al on the militarization of nursing and the war on terror and offers the perspectives of members of a philosophical discussion group who took up the challenge to engage in critical debate and dialogue on the ways in which external organizations penetrate nursing education, practice, and knowledge.

  13. "Once upon a time": a discussion of children's picture books as a narrative educational tool for nursing students.

    PubMed

    Crawley, Josephine Mary

    2009-01-01

    Narrative pedagogy influences many areas of nursing education, with emphasis on the co-constructing of narrative between students, educators, and clinicians. Little has been written about published children's literature as a basis for narrative discussion in nursing education. This article describes how narrative pedagogy already works within nursing education and explores features of children's picture books that give them value as a narrative educational tool for nursing students, providing stories that encourage self-understanding and deconstruct the multiple realities of narratives about the human condition.

  14. Leveraging data to transform nursing care: insights from nurse leaders.

    PubMed

    Jeffs, Lianne; Nincic, Vera; White, Peggy; Hayes, Laureen; Lo, Joyce

    2015-01-01

    A study was undertaken to gain insight into how nurse leaders are influencing the use of performance data to improve nursing care in hospitals. Two themes emerged: getting relevant, reliable, and timely data into the hands of nurses, and the leaders' ability to "connect the dots" in working with different stakeholders. Study findings may inform nurse leaders in their efforts to leverage data to transform nursing care.

  15. Prediction of half-marathon race time in recreational female and male runners.

    PubMed

    Knechtle, Beat; Barandun, Ursula; Knechtle, Patrizia; Zingg, Matthias A; Rosemann, Thomas; Rüst, Christoph A

    2014-01-01

    Half-marathon running is of high popularity. Recent studies tried to find predictor variables for half-marathon race time for recreational female and male runners and to present equations to predict race time. The actual equations included running speed during training for both women and men as training variable but midaxillary skinfold for women and body mass index for men as anthropometric variable. An actual study found that percent body fat and running speed during training sessions were the best predictor variables for half-marathon race times in both women and men. The aim of the present study was to improve the existing equations to predict half-marathon race time in a larger sample of male and female half-marathoners by using percent body fat and running speed during training sessions as predictor variables. In a sample of 147 men and 83 women, multiple linear regression analysis including percent body fat and running speed during training units as independent variables and race time as dependent variable were performed and an equation was evolved to predict half-marathon race time. For men, half-marathon race time might be predicted by the equation (r(2) = 0.42, adjusted r(2) = 0.41, SE = 13.3) half-marathon race time (min) = 142.7 + 1.158 × percent body fat (%) - 5.223 × running speed during training (km/h). The predicted race time correlated highly significantly (r = 0.71, p < 0.0001) to the achieved race time. For women, half-marathon race time might be predicted by the equation (r(2) = 0.68, adjusted r(2) = 0.68, SE = 9.8) race time (min) = 168.7 + 1.077 × percent body fat (%) - 7.556 × running speed during training (km/h). The predicted race time correlated highly significantly (r = 0.89, p < 0.0001) to the achieved race time. The coefficients of determination of the models were slightly higher than for the existing equations. Future studies might include physiological

  16. Lung Cancer Stigma Predicts Timing of Medical Help–Seeking Behavior

    PubMed Central

    Carter-Harris, Lisa; Hermann, Carla P.; Schreiber, Judy; Weaver, Michael T.; Rawl, Susan M.

    2014-01-01

    Purpose/Objectives To examine relationships among demographic variables, healthcare system distrust, lung cancer stigma, smoking status, and timing of medical help–seeking behavior in individuals with symptoms suggestive of lung cancer after controlling for ethnicity, socioeconomic status, and social desirability. Design Descriptive, cross-sectional, correlational study. Setting Outpatient oncology clinics in Louisville, KY. Sample 94 patients diagnosed in the past three weeks to six years with all stages of lung cancer. Methods Self-report, written survey packets were administered in person followed by a semistructured interview to assess symptoms and timing characteristics of practice-identified patients with lung cancer. Main Research Variables Timing of medical help–seeking behavior, healthcare system distrust, lung cancer stigma, and smoking status. Findings Lung cancer stigma was independently associated with timing of medical help–seeking behavior in patients with lung cancer. Healthcare system distrust and smoking status were not independently associated with timing of medical help–seeking behavior. Conclusions Findings suggest that stigma influences medical help–seeking behavior for lung cancer symptoms, serving as a barrier to prompt medical help–seeking behavior. Implications for Nursing When designing interventions to promote early medical help–seeking behavior in individuals with symptoms suggestive of lung cancer, methods that consider lung cancer stigma as a barrier that can be addressed through public awareness and patient-targeted interventions should be included. PMID:24769603

  17. Using Time Series Analysis to Predict Cardiac Arrest in a Pediatric Intensive Care Unit

    PubMed Central

    Kennedy, Curtis E; Aoki, Noriaki; Mariscalco, Michele; Turley, James P

    2015-01-01

    Objectives To build and test cardiac arrest prediction models in a pediatric intensive care unit, using time series analysis as input, and to measure changes in prediction accuracy attributable to different classes of time series data. Methods A retrospective cohort study of pediatric intensive care patients over a 30 month study period. All subjects identified by code documentation sheets with matches in hospital physiologic and laboratory data repositories and who underwent chest compressions for two minutes were included as arrest cases. Controls were randomly selected from patients that did not experience arrest and who survived to discharge. Modeling data was based on twelve hours of data preceding the arrest (reference time for controls). Measurements and Main Results 103 cases of cardiac arrest and 109 control cases were used to prepare a baseline data set that consisted of 1025 variables in four data classes: multivariate, raw time series, clinical calculations, and time series trend analysis. We trained 20 arrest prediction models using a matrix of five feature sets (combinations of data classes) with four modeling algorithms: linear regression, decision tree, neural network and support vector machine. The reference model (multivariate data with regression algorithm) had an accuracy of 78% and 87% area under the receiver operating characteristic curve (AUROC). The best model (multivariate + trend analysis data with support vector machine algorithm) had an accuracy of 94% and 98% AUROC. Conclusions Cardiac arrest predictions based on a traditional model built with multivariate data and a regression algorithm misclassified cases 3.7 times more frequently than predictions that included time series trend analysis and built with a support vector machine algorithm. Although the final model lacks the specificity necessary for clinical application, we have demonstrated how information from time series data can be used to increase the accuracy of clinical

  18. 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 ...

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

    NASA Astrophysics Data System (ADS)

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

    1993-09-01

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

  20. A method for the time-varying nonlinear prediction of complex nonstationary biomedical signals.

    PubMed

    Faes, Luca; Chon, Ki H; Nollo, Giandomenico

    2009-02-01

    A method to perform time-varying (TV) nonlinear prediction of biomedical signals in the presence of nonstationarity is presented in this paper. The method is based on identification of TV autoregressive models through expansion of the TV coefficients onto a set of basis functions and on k-nearest neighbor local linear approximation to perform nonlinear prediction. The approach provides reasonable nonlinear prediction even for TV deterministic chaotic signals, which has been a daunting task to date. Moreover, the method is used in conjunction with a TV surrogate method to provide statistical validation that the presence of nonlinearity is not due to nonstationarity itself. The approach is tested on simulated linear and nonlinear signals reproducing both time-invariant (TIV) and TV dynamics to assess its ability to quantify TIV and TV degrees of predictability and detect nonlinearity. Applicative examples relevant to heart rate variability and EEG analyses are then illustrated.

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

    PubMed Central

    2013-01-01

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

  2. Father attendance in nurse home visitation.

    PubMed

    Holmberg, John R; Olds, David L

    2015-01-01

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

  3. 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.

  4. 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.

  5. Evaluation of Timed Up and Go Test as a tool to measure postoperative function and prediction of one year walking ability for patients with hip fracture

    PubMed Central

    Nygard, Heid; Matre, Kjell; Fevang, Jonas Meling

    2015-01-01

    Objective: To evaluate if the Timed Up and Go Test is a useful tool to measure postoperative function and to predict one-year results of rehabilitation in patients operated owing to hip fracture. Design: Prospective cohort study. Setting: The department of orthopaedic surgery at five hospitals in Norway. Patients were assessed five days postoperatively and after one year. Subjects: A total of 684 patients over 60 years with trochanteric or subtrochanteric hip fractures were included. A total of 171 (25%) patients died within a year and 373 (73% of patients still alive) attended follow-up one year after surgery. Main measures: Timed Up and Go Test and walking ability. Results: A total of 258 (38%) patients passed the postoperative Timed Up and Go Test. A total of 217 (56%) patients with a prefracture independent outdoor walking ability, passed the test. The average Timed Up and Go Test score was 71 seconds. A total of 171 (25%) patients could not rise from a chair without assistance; 8% of the patients with cognitive impairment, and 8% of those admitted from nursing homes, were able to pass the postoperative Timed Up and Go Test. The sensitivity and specificity of the Timed Up and Go Test in predicting walking ability one year after the operation were low. At one year follow-up, 38% of the patients not able to perform the postoperative Timed Up and Go Test, passed the test. A total of 81 (21%) patients did not use any walking-aid, 17 of them did not pass the postoperative Timed Up and Go Test. Conclusion: The Timed Up and Go Test performed the fifth postoperative day was not a suitable tool to assess functional mobility for the majority of the patients with hip fractures in our study. Neither was the postoperative Timed Up and Go Test a suitable tool to predict the walking ability one year after the operation. PMID:26109590

  6. 38 CFR 51.130 - Nursing services.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... service must be under the direction of a full-time registered nurse who is currently licensed by the State... nurses 24 hours per day, 7 days per week. (c) The director of nursing service must designate a registered nurse as a supervising nurse for each tour of duty. (1) Based on the application and results of the...

  7. 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.

  8. 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!

  9. 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…

  10. A Study of the Effect of the Type and Timing of Professional Development and Job Satisfaction in the Nurse Faculty Role

    ERIC Educational Resources Information Center

    Noble-Britton, Pinky A.

    2014-01-01

    The ability to adapt to one's profession and display satisfaction while in that role has been a subject of discussion for educators. This quantitative, cross-sectional survey examined how types of professional development activities and their timing affected job satisfaction among nurse faculty members in Tennessee. Results indicated that the…

  11. PSO-MISMO modeling strategy for multistep-ahead time series prediction.

    PubMed

    Bao, Yukun; Xiong, Tao; Hu, Zhongyi

    2014-05-01

    Multistep-ahead time series prediction is one of the most challenging research topics in the field of time series modeling and prediction, and is continually under research. Recently, the multiple-input several multiple-outputs (MISMO) modeling strategy has been proposed as a promising alternative for multistep-ahead time series prediction, exhibiting advantages compared with the two currently dominating strategies, the iterated and the direct strategies. Built on the established MISMO strategy, this paper proposes a particle swarm optimization (PSO)-based MISMO modeling strategy, which is capable of determining the number of sub-models in a self-adaptive mode, with varying prediction horizons. Rather than deriving crisp divides with equal-size s prediction horizons from the established MISMO, the proposed PSO-MISMO strategy, implemented with neural networks, employs a heuristic to create flexible divides with varying sizes of prediction horizons and to generate corresponding sub-models, providing considerable flexibility in model construction, which has been validated with simulated and real datasets.

  12. 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.

  13. 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

  14. 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.

  15. Long-term prediction of the Arctic ionospheric TEC based on time-varying periodograms.

    PubMed

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

    2014-01-01

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

  16. 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

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

    ERIC Educational Resources Information Center

    Gillespie, Maria

    2012-01-01

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

  18. 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.

  19. On the feasibility of real-time prediction of aircraft carrier motion at sea

    NASA Technical Reports Server (NTRS)

    Sidar, M. M.; Doolin, B. F.

    1983-01-01

    Landing aircraft on board carriers is a most delicate phase of flight operations at sea. The ability to predict the aircraft carrier's motion over an interval of several seconds within reasonable error bounds may allow an improvement in touchdown dispersion and reduce the value of the ramp clearance due to a smoother aircraft trajectory. Also, improved information to the landing signal officer should decrease the number of waveoffs substantially. This paper indicates and shows quantitatively that, based upon the power density spectrum data for pitch and heave measured for various ships and sea conditions, the motion can be predicted well, for up to 15 s. Moreover, the zero crossover times for both pitch and heave motions can be predicted with impressive accuracy. The predictor was designed on the basis of Kalman's optimum filtering theory (the discrete time case), being compatible with real-time digital computer operation.

  20. On the feasibility of real-time prediction of aircraft carrier motion at sea

    NASA Technical Reports Server (NTRS)

    Sidar, M.; Doolin, B. F.

    1975-01-01

    The ability to predict the aircraft carrier's motion over an interval of several seconds within reasonable error bounds may allow an improvement in touchdown dispersion and a more certain value for ramp clearance due to a smoother aircraft trajectory. Also, improved information to the landing signal officer should decrease the number of waveoffs substantially. It is quantitatively shown that, based on the power density spectrum data for pitch and heave measured for various ships and sea conditions, the motion can be predicted well for up to 15 seconds. The zero crossover times for both pitch and heave motions can be predicted with impressive accuracy. The predictor was designed on the basis of Kalman's optimum filtering theory for the discrete time case, adapted for real-time digital computer operation.

  1. Computational fluid dynamic prediction of the residence time of a vortex separator applied to disinfection.

    PubMed

    Egarr, D; Faram, M G; O'Doherty, T; Phipps, D; Syred, N

    2005-01-01

    A Hydrodynamic Vortex Separator (HDVS) has been modelled using Computational Fluid Dynamics (CFD) in order to predict the residence time of the fluid at the overflow and underflow outlets. A technique which was developed for use in Heating, Ventilation and Air Conditioning (HVAC) was used to determine the residence time and the results have been compared with those determined experimentally. It is shown that in using CFD, it is possible to predict the mean residence time of the fluid and to study the response to a pulse injection of tracer. It is also shown that it is possible to apply these techniques to predict the mean survival rate of bacteria in a combined separation and disinfection process.

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

    ERIC Educational Resources Information Center

    Carbanaro, Michael; Dawber, Tess; Arav, Isanna

    2006-01-01

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

  3. 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.

  4. Optimal Futility Interim Design: A Predictive Probability of Success Approach with Time-to-Event Endpoint.

    PubMed

    Tang, Zhongwen

    2015-01-01

    An analytical way to compute predictive probability of success (PPOS) together with credible interval at interim analysis (IA) is developed for big clinical trials with time-to-event endpoints. The method takes account of the fixed data up to IA, the amount of uncertainty in future data, and uncertainty about parameters. Predictive power is a special type of PPOS. The result is confirmed by simulation. An optimal design is proposed by finding optimal combination of analysis time and futility cutoff based on some PPOS criteria.

  5. Predicting retention time shifts associated with variation of the gradient slope in peptide RP-HPLC.

    PubMed

    Spicer, Vic; Grigoryan, Marine; Gotfrid, Alexander; Standing, Kenneth G; Krokhin, Oleg V

    2010-12-01

    We have developed a sequence-specific model for predicting slopes (S) in the fundamental equation of linear solvent strength theory for the reversed-phase HPLC separation of tryptic peptides detected in a typical bottom-up-proteomics experiment. These slopes control the variation in the separation selectivity observed when the physical parameters of chromatographic separation, such as gradient slope, flow rate, and column size are altered. For example, with the use of an arbitrarily chosen set of tryptic peptides with a 4-times difference in the gradient slope between two experiments, the R(2)-value of correlation between the observed retention times of identical species decreases to ~0.993-0.996 (compared to a theoretical value of ~1.00). The observed retention time shifts associated with variations of the gradient slope can be predicted a priori using the approach described here. The proposed model is based on our findings for a set of synthetic species (Vu, H.; Spicer, V.; Gotfrid, A.; Krokhin, O. V. J. Chromatogr., A, 2010, 1217, 489-497), which postulate that slopes S can be predicted taking into account simultaneously peptide length, charge, and hydrophobicity. Here we extend this approach using an extensive set of real tryptic peptides. We developed the procedure to accurately measure S-values in nano-RP HPLC MS experiments and introduced sequence-specific corrections for a more accurate prediction of the slopes S. A correlation of ~0.95 R(2)-value between the predicted and experimental S-values was demonstrated. Predicting S-values and calculating the expected retention time shifts when the physical parameters of separation like gradient slope are altered will facilitate a more accurate application of peptide retention prediction protocols, aid in the transfer of scheduled MRM (SRM) procedures between LC systems, and increase the efficiency of interlaboratory data collection and comparison.

  6. 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

  7. 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

  8. Window-Based Channel Impulse Response Prediction for Time-Varying Ultra-Wideband Channels

    PubMed Central

    Al-Samman, A. M.; Azmi, M. H.; Rahman, T. A.; Khan, I.; Hindia, M. N.; Fattouh, A.

    2016-01-01

    This work proposes channel impulse response (CIR) prediction for time-varying ultra-wideband (UWB) channels by exploiting the fast movement of channel taps within delay bins. Considering the sparsity of UWB channels, we introduce a window-based CIR (WB-CIR) to approximate the high temporal resolutions of UWB channels. A recursive least square (RLS) algorithm is adopted to predict the time evolution of the WB-CIR. For predicting the future WB-CIR tap of window wk, three RLS filter coefficients are computed from the observed WB-CIRs of the left wk−1, the current wk and the right wk+1 windows. The filter coefficient with the lowest RLS error is used to predict the future WB-CIR tap. To evaluate our proposed prediction method, UWB CIRs are collected through measurement campaigns in outdoor environments considering line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. Under similar computational complexity, our proposed method provides an improvement in prediction errors of approximately 80% for LOS and 63% for NLOS scenarios compared with a conventional method. PMID:27992445

  9. Jump neural network for real-time prediction of glucose concentration.

    PubMed

    Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; Cobelli, Claudio

    2015-01-01

    Prediction of the future value of a variable is of central importance in a wide variety of fields, including economy and finance, meteorology, informatics, and, last but not least important, medicine. For example, in the therapy of Type 1 Diabetes (T1D), in which, for patient safety, glucose concentration in the blood should be maintained in a defined normoglycemic range, the ability to forecast glucose concentration in the short-term (with a prediction horizon of around 30 min) might be sufficient to reduce the incidence of hypoglycemic and hyperglycemic events. Neural Network (NN) approaches are suitable for prediction purposes because of their ability to model nonlinear dynamics and handle in their inputs signals coming from different domains. In this chapter we illustrate the design of a jump NN glucose prediction algorithm that exploits past glucose concentration data, measured in real-time by a minimally invasive continuous glucose monitoring (CGM) sensor, and information on ingested carbohydrates, supplied by the patient himself or herself. The methodology is assessed by tuning the NN on data of ten T1D individuals and then testing it on a dataset of ten different subjects. Results with a prediction horizon of 30 min show that prediction of glucose concentration in T1D via NN is feasible and sufficiently accurate. The average time anticipation obtained is compatible with the generation of preventive hypoglycemic and hyperglycemic alerts and the improvement of artificial pancreas performance.

  10. 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).

  11. Combinatorial modeling of chromatin features quantitatively predicts DNA replication timing in Drosophila.

    PubMed

    Comoglio, Federico; Paro, Renato

    2014-01-01

    In metazoans, each cell type follows a characteristic, spatio-temporally regulated DNA replication program. Histone modifications (HMs) and chromatin binding proteins (CBPs) are fundamental for a faithful progression and completion of this process. However, no individual HM is strictly indispensable for origin function, suggesting that HMs may act combinatorially in analogy to the histone code hypothesis for transcriptional regulation. In contrast to gene expression however, the relationship between combinations of chromatin features and DNA replication timing has not yet been demonstrated. Here, by exploiting a comprehensive data collection consisting of 95 CBPs and HMs we investigated their combinatorial potential for the prediction of DNA replication timing in Drosophila using quantitative statistical models. We found that while combinations of CBPs exhibit moderate predictive power for replication timing, pairwise interactions between HMs lead to accurate predictions genome-wide that can be locally further improved by CBPs. Independent feature importance and model analyses led us to derive a simplified, biologically interpretable model of the relationship between chromatin landscape and replication timing reaching 80% of the full model accuracy using six model terms. Finally, we show that pairwise combinations of HMs are able to predict differential DNA replication timing across different cell types. All in all, our work provides support to the existence of combinatorial HM patterns for DNA replication and reveal cell-type independent key elements thereof, whose experimental investigation might contribute to elucidate the regulatory mode of this fundamental cellular process.

  12. Addressing the mental health nurse shortage: undergraduate nursing students working as assistants in nursing in inpatient mental health settings.

    PubMed

    Browne, Graeme; Cashin, Andrew; Graham, Iain; Shaw, Warren

    2013-10-01

    The population of mental health nurses is ageing and in the next few years we can expect many to retire. This paper makes an argument for the employment of undergraduate nursing students as Assistants in Nursing (AINs) in mental health settings as a strategy to encourage them to consider a career in mental health nursing. Skill mix in nursing has been debated since at least the 1980s. It appears that the use of AINs in general nursing is established and will continue. The research suggests that with the right skill mix, nursing outcomes and safety are not compromised. It seems inevitable that assistants in nursing will increasingly be part of the mental health nursing workforce; it is timely for mental health nurses to lead these changes so nursing care and the future mental health nursing workforce stay in control of nursing.

  13. 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.

  14. 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…

  15. A multi-time scale approach to remaining useful life prediction in rolling bearing

    NASA Astrophysics Data System (ADS)

    Qian, Yuning; Yan, Ruqiang; Gao, Robert X.

    2017-01-01

    This paper presents a novel multi-time scale approach to bearing defect tracking and remaining useful life (RUL) prediction, which integrates enhanced phase space warping (PSW) with a modified Paris crack growth model. As a data-driven method, PSW describes the dynamical behavior of the bearing being tested on a fast-time scale, whereas the Paris crack growth model, as a physics-based model, characterizes the bearing's defect propagation on a slow-time scale. Theoretically, PSW constructs a tracking metric by evaluating the phase space trajectory warping of the bearing vibration data, and establishes a correlation between measurement on a fast-time scale and defect growth variables on a slow-time scale. Furthermore, PSW is enhanced by a multi-dimensional auto-regression (AR) model for improved accuracy in defect tracking. Also, the Paris crack growth model is modified by a time-piecewise algorithm for real-time RUL prediction. Case studies performed on two run-to-failure experiments indicate that the developed technique is effective in tracking the evolution of bearing defects and accurately predict the bearing RUL, thus contributing to the literature of bearing prognosis .

  16. Least squares support vector machine for short-term prediction of meteorological time series

    NASA Astrophysics Data System (ADS)

    Mellit, A.; Pavan, A. Massi; Benghanem, M.

    2013-01-01

    The prediction of meteorological time series plays very important role in several fields. In this paper, an application of least squares support vector machine (LS-SVM) for short-term prediction of meteorological time series (e.g. solar irradiation, air temperature, relative humidity, wind speed, wind direction and pressure) is presented. In order to check the generalization capability of the LS-SVM approach, a K-fold cross-validation and Kolmogorov-Smirnov test have been carried out. A comparison between LS-SVM and different artificial neural network (ANN) architectures (recurrent neural network, multi-layered perceptron, radial basis function and probabilistic neural network) is presented and discussed. The comparison showed that the LS-SVM produced significantly better results than ANN architectures. It also indicates that LS-SVM provides promising results for short-term prediction of meteorological data.

  17. A real-time prediction system for solar weather based on magnetic nonpotentiality (I)

    NASA Astrophysics Data System (ADS)

    Yang, Xiao; Lin, GangHua; Deng, YuanYong

    2016-07-01

    The Sun is the source of space weather. The characteristics and evolution of the solar active-region magnetic field closely relate to violent solar eruptions such as flares and coronal mass ejections. The Solar Magnetic Field Telescope in Huairou Solar Observing Station has accumulated numerous vector magnetogram data of solar photospheric active regions (AR) covering nearly 30 years. Utilizing these precious historical data to establish statistical prediction models for solar eruptive events, not only can provide a reference for the timely adjustment of observation mode to specific active regions, but also can offer valuable reference to the monitoring and forecasting departments of solar and space weather. In this part of work, we focus on the Yes/No and occurrence time predictions for AR-related solar flares, and the predictions independently rely on the vector magnetic-filed observation of the solar surface.

  18. 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.

  19. Time Perspectives Predict Mood States and Satisfaction with Life over and above Personality.

    PubMed

    Stolarski, Maciej; Matthews, Gerald

    2016-01-01

    The present study aimed to test the incremental validity of Time Perspective (TP) scales in predicting satisfaction with life and mood, over and above the Big Five personality traits. It also investigated whether the new TP construct of Future Negative perspective contributed to prediction of these outcomes. Participants (N = 265) completed four measures: Satisfaction With Life Scale (SWLS), UWIST Mood Adjective Checklist (UMACL), a modified Zimbardo Time Perspective Inventory (ZTPI), and NEO-Five Factor Inventory (NEO-FFI). Results confirmed the incremental validity of TP, although Big Five dimensions were independently predictive of life satisfaction and certain mood scales. Past Negative TP was the strongest single predictor of life satisfaction. However, Future Negative TP was be the strongest mood predictor from the TP universe, after controlling for the Big Five and remaining TP dimensions. Findings suggest that TP is an important aspect of personality for understanding individual differences in well-being.

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

    SciTech Connect

    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.; Lemaire, S.; Mancini, R. C.; Marshall, F. J.; Masse, L.; Masson-Laborde, P. E.; Michel, D. T.; Philippe, F.; Reverdin, C.; Seka, W.; Tassin, V.

    2016-01-14

    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. In contrast, we show that the pulse shape affects the implosion stability, assessed by comparing the target performances between prediction and measurement. For the 1-ns square pulse, the 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%.

  1. AL and Dst Predictions with the Real-Time WINDMI Model

    NASA Astrophysics Data System (ADS)

    Mays, L.; Horton, W.; Spencer, E.; Weigel, R.; Vassiliadis, D.; Kozyra, J.

    2006-12-01

    First results are presented of the space weather forecasting capability of the real-time WINDMI model that has been operating since February 2006 as a physics based AL and Dst prediction tool. The well documented WINDMI model is a network of eight coupled ordinary differential equations which describe the transfer of power from the solar wind through the geomagnetic tail, the ionosphere, and ring current in the solar WIND driven Magnetosphere-Ionosphere system. WINDMI includes ring current energization physics from substrom injections and outputs a predicted westward auroral electojet index (AL) and equatorial geomagnetic disturbance storm time index (Dst). At the time of abstract submission (August 2006) real-time WINDMI has captured two storms with the first alarm being sent by email for a moderate -150 nT storm on 14-15 April 2006 and a second -100 nT storm on 19-20 August 2006. During the August 2006 storm period the WINDMI model was a more consistent Dst predictor than the Kyoto WDC Quicklook Dst data which has an incorrect offset of ~-100 nT. Real-time WINDMI uses real-time solar wind data from received from ACE every ten minutes to derive in less than one minute of computational time a predicted AL and Dst and magnetopause standoff distance. Real-time WINDMI predicts the AL index one hour earlier than the data is available from the Kyoto WDC Quicklook website and the Dst index two hours earlier. Every ten minutes real-time AL and Dst data and WINDMI predictions are shown on this website: http://orion.ph.utexas.edu/~windmi/realtime/. The 18 physical parameters of WINDMI are approximated analytically from planetary parameters and optimized within physically allowable ranges using the genetic algorithm. Real-time WINDMI parameters are optimized every hour based on 8 hours of past model/data comparison. In addition to the geomagnetic indices the model predicts the major energy components and power transfers in the solar wind-magnetosphere-ionosphere system. The

  2. Running speed during training and percent body fat predict race time in recreational male marathoners

    PubMed Central

    Barandun, Ursula; Knechtle, Beat; Knechtle, Patrizia; Klipstein, Andreas; Rüst, Christoph Alexander; Rosemann, Thomas; Lepers, Romuald

    2012-01-01

    Background Recent studies have shown that personal best marathon time is a strong predictor of race time in male ultramarathoners. We aimed to determine variables predictive of marathon race time in recreational male marathoners by using the same characteristics of anthropometry and training as used for ultramarathoners. Methods Anthropometric and training characteristics of 126 recreational male marathoners were bivariately and multivariately related to marathon race times. Results After multivariate regression, running speed of the training units (β = −0.52, P < 0.0001) and percent body fat (β = 0.27, P < 0.0001) were the two variables most strongly correlated with marathon race times. Marathon race time for recreational male runners may be estimated to some extent by using the following equation (r2 = 0.44): race time ( minutes) = 326.3 + 2.394 × (percent body fat, %) − 12.06 × (speed in training, km/hours). Running speed during training sessions correlated with prerace percent body fat (r = 0.33, P = 0.0002). The model including anthropometric and training variables explained 44% of the variance of marathon race times, whereas running speed during training sessions alone explained 40%. Thus, training speed was more predictive of marathon performance times than anthropometric characteristics. Conclusion The present results suggest that low body fat and running speed during training close to race pace (about 11 km/hour) are two key factors for a fast marathon race time in recreational male marathoner runners. PMID:24198587

  3. Measuring Complexity and Predictability of Time Series with Flexible Multiscale Entropy for Sensor Networks.

    PubMed

    Zhou, Renjie; Yang, Chen; Wan, Jian; Zhang, Wei; Guan, Bo; Xiong, Naixue

    2017-04-06

    Measurement of time series complexity and predictability is sometimes the cornerstone for proposing solutions to topology and congestion control problems in sensor networks. As a method of measuring time series complexity and predictability, multiscale entropy (MSE) has been widely applied in many fields. However, sample entropy, which is the fundamental component of MSE, measures the similarity of two subsequences of a time series with either zero or one, but without in-between values, which causes sudden changes of entropy values even if the time series embraces small changes. This problem becomes especially severe when the length of time series is getting short. For solving such the problem, we propose flexible multiscale entropy (FMSE), which introduces a novel similarity function measuring the similarity of two subsequences with full-range values from zero to one, and thus increases the reliability and stability of measuring time series complexity. The proposed method is evaluated on both synthetic and real time series, including white noise, 1/f noise and real vibration signals. The evaluation results demonstrate that FMSE has a significant improvement in reliability and stability of measuring complexity of time series, especially when the length of time series is short, compared to MSE and composite multiscale entropy (CMSE). The proposed method FMSE is capable of improving the performance of time series analysis based topology and traffic congestion control techniques.

  4. Development and implementation of a real-time 30-day readmission predictive model.

    PubMed

    Cronin, Patrick R; Greenwald, Jeffrey L; Crevensten, Gwen C; Chueh, Henry C; Zai, Adrian H

    2014-01-01

    Hospitals are under great pressure to reduce readmissions of patients. Being able to reliably predict patients at increased risk for rehospitalization would allow for tailored interventions to be offered to them. This requires the creation of a functional predictive model specifically designed to support real-time clinical operations. A predictive model for readmissions within 30 days of discharge was developed using retrospective data from 45,924 MGH admissions between 2/1/2012 and 1/31/2013 only including factors that would be available by the day after admission. It was then validated prospectively in a real-time implementation for 3,074 MGH admissions between 10/1/2013 and 10/31/2013. The model developed retrospectively had an AUC of 0.705 with good calibration. The real-time implementation had an AUC of 0.671 although the model was overestimating readmission risk. A moderately discriminative real-time 30-day readmission predictive model can be developed and implemented in a large academic hospital.

  5. Time-of-day-dependent adaptation of the HPA axis to predictable social defeat stress.

    PubMed

    Koch, C E; Bartlang, M S; Kiehn, J T; Lucke, L; Naujokat, N; Helfrich-Förster, C; Reber, S O; Oster, H

    2016-12-01

    In modern societies, the risk of developing a whole array of affective and somatic disorders is associated with the prevalence of frequent psychosocial stress. Therefore, a better understanding of adaptive stress responses and their underlying molecular mechanisms is of high clinical interest. In response to an acute stressor, each organism can either show passive freezing or active fight-or-flight behaviour, with activation of sympathetic nervous system and the hypothalamus-pituitary-adrenal (HPA) axis providing the necessary energy for the latter by releasing catecholamines and glucocorticoids (GC). Recent data suggest that stress responses are also regulated by the endogenous circadian clock. In consequence, the timing of stress may critically affect adaptive responses to and/or pathological effects of repetitive stressor exposure. In this article, we characterize the impact of predictable social defeat stress during daytime versus nighttime on bodyweight development and HPA axis activity in mice. While 19 days of social daytime stress led to a transient reduction in bodyweight without altering HPA axis activity at the predicted time of stressor exposure, more detrimental effects were seen in anticipation of nighttime stress. Repeated nighttime stressor exposure led to alterations in food metabolization and reduced HPA axis activity with lower circulating adrenocorticotropic hormone (ACTH) and GC concentrations at the time of predicted stressor exposure. Our data reveal a circadian gating of stress adaptation to predictable social defeat stress at the level of the HPA axis with impact on metabolic homeostasis underpinning the importance of timing for the body's adaptability to repetitive stress.

  6. Observations and predictions of eclipse times by astronomers in the pre-telescopic period.

    NASA Astrophysics Data System (ADS)

    Steele, J. M.

    Eclipses of the Sun and Moon are among the most impressive of celestial events. It is therefore unsurprising that they have played an important role in the astronomy and astrology of most early cultures. Many hundreds of references to eclipses are found in the writings of the chroniclers and astronomers of the pre-telescopic world. In particular, the astronomers of Babylon, Ancient Greece, the Islamic Near East. Later Medieval and Renaissance Europe, China, and Japan, recorded a large number of observations and predictions of the time of an eclipse. The present study contains an extensive compilation of all known timed reports of eclipse observations and predictions made by astronomers in the pre-telescopic period. By performing a basic analysis of the recorded times, it has been possible to trace the gradual development of the techniques used by the astronomers to observe and predict eclipses. In order to conduct this analysis, it has been necessary to investigate a number of other problems including the dating of damaged observational accounts, the units of time used by the early astronomers, and the methods by which the Babylonians predicted eclipses. Many of these questions have not previously been answered. Therefore, the results of this study provide important information regarding the astronomies of these early cultures.

  7. 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…

  8. 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…

  9. 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.

  10. Neural network incorporating meal information improves accuracy of short-time prediction of glucose concentration.

    PubMed

    Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; De Nicolao, Giuseppe; Cobelli, Claudio

    2012-06-01

    Diabetes mellitus is one of the most common chronic diseases, and a clinically important task in its management is the prevention of hypo/hyperglycemic events. This can be achieved by exploiting continuous glucose monitoring (CGM) devices and suitable short-term prediction algorithms able to infer future glycemia in real time. In the literature, several methods for short-time glucose prediction have been proposed, most of which do not exploit information on meals, and use past CGM readings only. In this paper, we propose an algorithm for short-time glucose prediction using past CGM sensor readings and information on carbohydrate intake. The predictor combines a neural network (NN) model and a first-order polynomial extrapolation algorithm, used in parallel to describe, respectively, the nonlinear and the linear components of glucose dynamics. Information on the glucose rate of appearance after a meal is described by a previously published physiological model. The method is assessed on 20 simulated datasets and on 9 real Abbott FreeStyle Navigator datasets, and its performance is successfully compared with that of a recently proposed NN glucose predictor. Results suggest that exploiting meal information improves the accuracy of short-time glucose prediction.

  11. Time Critical Targeting: Predictive Vs Reactionary Methods An Analysis For The Future

    DTIC Science & Technology

    2002-06-01

    Chapter 5 Results & Conclusions Having investigated the different methods and techniques that can be used for time critical targeting in the......Targeting: Predictive Vs Reactionary Methods An Analysis For The Future 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S

  12. 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.

  13. 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.

  14. Analysis of locality-sensitive hashing for fast critical event prediction on physiological time series.

    PubMed

    Kim, Yongwook Bryce; O'Reilly, Una-May

    2016-08-01

    We apply the sublinear time, scalable locality-sensitive hashing (LSH) and majority discrimination to the problem of predicting critical events based on physiological waveform time series. Compared to using the linear exhaustive k-nearest neighbor search, our proposed method vastly speeds up prediction time up to 25 times while sacrificing only 1% of accuracy when demonstrated on an arterial blood pressure dataset extracted from the MIMIC2 database. We compare two widely used variants of LSH, the bit sampling based (L1LSH) and the random projection based (E2LSH) methods to measure their direct impact on retrieval and prediction accuracy. We experimentally show that the more sophisticated E2LSH performs worse than L1LSH in terms of accuracy, correlation, and the ability to detect false negatives. We attribute this to E2LSH's simultaneous integration of all dimensions when hashing the data, which actually makes it more impotent against common noise sources such as data misalignment. We also demonstrate that the deterioration of accuracy due to approximation at the retrieval step of LSH has a diminishing impact on the prediction accuracy as the speed up gain accelerates.

  15. 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...

  16. 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…

  17. Factors that Predict Full-Time Community College Faculty Engagement in Online Instruction

    ERIC Educational Resources Information Center

    Akroyd, Duane; Patton, Bess; Bracken, Susan

    2013-01-01

    This study is a secondary quantitative analysis of the 2004 National Study of Postsecondary Faculty (NSOPF) data. It examines the ability of human capital, intrinsic rewards, extrinsic rewards, and gender/race demographics to predict full-time community college faculty teaching on-line courses. Findings indicate that those faculty with higher…

  18. Predicting Time to Recovery Among Depressed Adolescents Treated in Two Psychosocial Group Interventions

    ERIC Educational Resources Information Center

    Rohde, Paul; Seeley, John R.; Kaufman, Noah K.; Clarke, Gregory N.; Stice, Eric

    2006-01-01

    Aims were to identify the demographic, psychopathology, and psychosocial factors predicting time to major depressive disorder (MDD) recovery and moderators of treatment among 114 depressed adolescents recruited from a juvenile justice center and randomized to a cognitive behavioral treatment (CBT) condition or a life skills-tutoring control…

  19. Microwave emission as a proxy of CME speed in ICME arrival time predictions

    NASA Astrophysics Data System (ADS)

    Salas Matamoros, Carolina; Klein, Karl-Ludwig; Trottet, Gerard

    2016-04-01

    The propagation of a coronal mass ejection (CME) to the Earth takes between about 13 hours and several days. Observations of early radiative signatures of CMEs therefore provide a possible means to predict the arrival time of the CME near Earth. The fundamental tool to measure CME speeds in the corona is coronography, but the Earth-directed speed of a CME cannot be measured by a coronagraph located on the Sun-Earth line. Various proxies have been devised, based on the coronographic measurement. As an alternative, we explore radiative proxies. In the present contribution we investigate if microwave observations can be employed as a proxy for CME propagation speed. Caroubalos (1964) had shown that the higher the fluence of a solar radio burst near 3 GHz, the shorter is the time lapse between the solar event and the sudden commencement of a geomagnetic storm. We reconsider the relationship between CME speed and microwave fluence for limb CMEs in cycle 23 and early cycle 24. Then we use the microwave fluence as a proxy of CME speed of Earth-directed CMEs, together with the empirical interplanetary acceleration model devised by Gopalswamy et al. (2001), to predict the CME arrival time at Earth. These predictions are compared with observed arrival times and with the predictions based on other proxies, including soft X-rays and coronographic measurements.

  20. What Time Is Sunrise? Revisiting the Refraction Component of Sunrise/set Prediction Models

    NASA Astrophysics Data System (ADS)

    Wilson, Teresa; Bartlett, Jennifer L.; Hilton, James Lindsay

    2017-01-01

    Algorithms that predict sunrise and sunset times currently have an error of one to four minutes at mid-latitudes (0° - 55° N/S) due to limitations in the atmospheric models they incorporate. At higher latitudes, slight changes in refraction can cause significant discrepancies, even including difficulties determining when the Sun appears to rise or set. While different components of refraction are known, how they affect predictions of sunrise/set has not yet been quantified. A better understanding of the contributions from temperature profile, pressure, humidity, and aerosols could significantly improve the standard prediction. We present a sunrise/set calculator that interchanges the refraction component by varying the refraction model. We then compare these predictions with data sets of observed rise/set times to create a better model. Sunrise/set times and meteorological data from multiple locations will be necessary for a thorough investigation of the problem. While there are a few data sets available, we will also begin collecting this data using smartphones as part of a citizen science project. The mobile application for this project will be available in the Google Play store. Data analysis will lead to more complete models that will provide more accurate rise/set times for the benefit of astronomers, navigators, and outdoorsmen everywhere.

  1. Semiparametric models of time-dependent predictive values of prognostic biomarkers.

    PubMed

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

    2010-03-01

    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 positive predictive values 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, The Annals of Statistics 25, 1510-1540) 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.

  2. 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.

  3. 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.

  4. 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

  5. Predictive Motor Timing and the Cerebellar Vermis in Schizophrenia: An fMRI Study.

    PubMed

    Lošák, Jan; Hüttlová, Jitka; Lipová, Petra; Mareček, Radek; Bareš, Martin; Filip, Pavel; Žůbor, Jozef; Ustohal, Libor; Vaníček, Jiří; Kašpárek, Tomáš

    2016-11-01

    Abnormalities in both time processing and dopamine (DA) neurotransmission have been observed in schizophrenia. Time processing seems to be linked to DA neurotransmission. The cognitive dysmetria hypothesis postulates that psychosis might be a manifestation of the loss of coordination of mental processes due to impaired timing. The objective of the present study was to analyze timing abilities and their corresponding functional neuroanatomy in schizophrenia. We performed a functional magnetic resonance imaging (fMRI) study using a predictive motor timing paradigm in 28 schizophrenia patients and 27 matched healthy controls (HC). The schizophrenia patients showed accelerated time processing compared to HC; the amount of the acceleration positively correlated with the degree of positive psychotic symptoms and negatively correlated with antipsychotic dose. This dysfunctional predictive timing was associated with BOLD signal activity alterations in several brain networks, especially those previously described as timing networks (basal ganglia, cerebellum, SMA, and insula) and reward networks (hippocampus, amygdala, and NAcc). BOLD signal activity in the cerebellar vermis was negatively associated with accelerated time processing. Several lines of evidence suggest a direct link between DA transmission and the cerebellar vermis that could explain their relevance for the neurobiology of schizophrenia.

  6. 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

  7. 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

  8. 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.

  9. 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.

  10. Predictive motor timing performance dissociates between early diseases of the cerebellum and Parkinson's disease.

    PubMed

    Bares, Martin; Lungu, Ovidiu V; Husárová, Ivica; Gescheidt, Tomás

    2010-03-01

    There is evidence that both the basal ganglia and the cerebellum play a role in the neural representation of time in a variety of behaviours, but whether one of them is more important is not yet clear. To address this question in the context of predictive motor timing, we tested patients with various movement disorders implicating these two structures in a motor-timing task. Specifically, we investigated four different groups: (1) patients with early Parkinson's disease (PD); (2) patients with sporadic spinocerebellar ataxia (SCA); (3) patients with familial essential tremor (ET); and (4) matched healthy controls. We used a predictive motor-timing task that involved mediated interception of a moving target, and we assessed the effect of movement type (acceleration, deceleration and constant), speed (slow, medium and fast) and angle (0 degrees , 15 degrees and 30 degrees) on performance (hit, early error and late error). The main results showed that PD group and arm ET subgroup did not significantly differ from the control group. SCA and head ET subjects (severe and mild cerebellar damage, respectively) were significantly worse at interception than the other two groups. Our findings support the idea that the basal ganglia play a less significant role in predictive motor timing than the cerebellum. The fact that SCA and ET subjects seemed to have a fundamental problem with predictive motor timing suggests that the cerebellum plays an essential role in integrating incoming visual information with the motor output in a timely manner, and that ET is a heterogeneous entity that deserves increased attention from clinicians.

  11. 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.

  12. A Labor and Delivery Patient Classification System Based on Direct Nursing Care Time

    DTIC Science & Technology

    1991-08-01

    were also excluded. Overall, the infrequently selected tasks were also short in duration. The two tasks that consumed more time-- amniocentesis and nipple...1. Assists with amniocentesis 2. Assists with amnioinfusion 3. Assists with amniotomy 4. Assists with delivery a.) Vaginal delivery without...Nonstress test 2423 Amniotomy 2424 Amniocentesis 2425 Newborn identification procedure 2426 Teaching--breast feeding 2427 Pitocin induction 2428

  13. High-resolution summer rainfall prediction in the JHWC real-time WRF system

    NASA Astrophysics Data System (ADS)

    Lee, Dong-Kyou; Eom, Dae-Yong; Kim, Joo-Wan; Lee, Jae-Bok

    2010-08-01

    The WRF-based real-time forecast system (http://jhwc.snu.ac.kr/weather) of the Joint Center for High-impact Weather and Climate Research (JHWC) has been in operation since November 2006; this system has three nested model domains using GFS (Global Forecast System) data for its initial and boundary conditions. In this study, we evaluate the improvement in daily and hourly weather prediction, particularly the prediction of summer rainfall over the Korean Peninsula, in the JHWC WRF (Weather Research and Forecasting) model system by 3DVAR (three-Dimensional Variational) data assimilation using the data obtained from KEOP (Korea Enhanced Observation Program). KEOP was conducted during the period June 15 to July 15, 2007, and the data obtained included GTS (Global Telecommunication System) upper-air sounding, AWS (Automatic Weather System), wind profiler, and radar observation data. Rainfall prediction and its characteristics should be verified by using the precipitation observation and the difference field of each experiment. High-resolution (3 km in domain 3) summer rainfall prediction over the Korean peninsula is substantially influenced by improved synoptic-scale prediction in domains 1 (27 km) and 2 (9 km), in particular by data assimilation using the sounding and wind profiler data. The rainfall prediction in domain 3 was further improved by radar and AWS data assimilation in domain 3. The equitable threat score and bias score of the rainfall predicted in domain 3 indicated improvement for the threshold values of 0.1, 1, and 2.5 mm with data assimilation. For cases of occurrence of heavy rainfall (7 days), the equitable threat score and bias score improved considerably at all threshold values as compared to the entire period of KEOP. Radar and AWS data assimilation improved the temporal and spatial distributions of diurnal rainfall over southern Korea, and AWS data assimilation increased the predicted rainfall amount by approximately 0.3 mm 3hr-1.

  14. 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

    2013-06-04

    "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.

  15. 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.

  16. A novel multi-target regression framework for time-series prediction of drug efficacy

    PubMed Central

    Li, Haiqing; Zhang, Wei; Chen, Ying; Guo, Yumeng; Li, Guo-Zheng; Zhu, Xiaoxin

    2017-01-01

    Excavating from small samples is a challenging pharmacokinetic problem, where statistical methods can be applied. Pharmacokinetic data is special due to the small samples of high dimensionality, which makes it difficult to adopt conventional methods to predict the efficacy of traditional Chinese medicine (TCM) prescription. The main purpose of our study is to obtain some knowledge of the correlation in TCM prescription. Here, a novel method named Multi-target Regression Framework to deal with the problem of efficacy prediction is proposed. We employ the correlation between the values of different time sequences and add predictive targets of previous time as features to predict the value of current time. Several experiments are conducted to test the validity of our method and the results of leave-one-out cross-validation clearly manifest the competitiveness of our framework. Compared with linear regression, artificial neural networks, and partial least squares, support vector regression combined with our framework demonstrates the best performance, and appears to be more suitable for this task. PMID:28098186

  17. 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.

  18. 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.

  19. 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.

  20. Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling

    NASA Astrophysics Data System (ADS)

    Kwasniok, Frank

    2013-11-01

    A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

  1. Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

    PubMed

    Kwasniok, Frank

    2013-11-01

    A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

  2. Fast time-series prediction using high-dimensional data: evaluating confidence interval credibility.

    PubMed

    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, 2859:TROOCI>2.0.CO;2">J. Atmos. Sci. 57, 2859 (2000).

  3. Post Anesthesia Care Unit Patient Classification System: The Direct Care Nursing Time Component

    DTIC Science & Technology

    1991-07-18

    Bedpan 0306 Giving a Urinal 0307 Incontinent Care 0308 Output Weight - Diapers /Bed Linen 0401 Mobility - Ambulating First Time 0402 Mobility - Bed to...0001 .8595 Change [4.2] Incontinent Care 1 8.74 .5750 .0001 .8514 [4.3] Chg Occupied Bed 1 10.08 .9471 .0001 .7983 Note. Bracketed numbers...area. 0307 INCONTINENT CARE: Place equipment at patient’s bedside, bathe buttocks, perineum and thighs; change bedding and then remove equipment and

  4. 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.

  5. 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.

  6. 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.

  7. Effects of intensity and positional predictability of a visual stimulus on simple reaction time.

    PubMed

    Carreiro, Luiz Renato Rodrigues; Haddad, Hamilton; Baldo, Marcus Vinicius Chrysóstomo

    2011-01-10

    The influence of visual stimuli intensity on manual reaction time (RT) was investigated under two different attentional settings: high (Experiment 1) and low (Experiment 2) stimulus location predictability. These two experiments were also run under both binocular and monocular viewing conditions. We observed that RT decreased as stimulus intensity increased. It also decreased as the viewing condition was changed from monocular to binocular as well as the location predictability shifted from low to high. A significant interaction was found between stimulus intensity and viewing condition, but no interaction was observed between neither of these factors and location predictability. These findings support the idea that the stimulus intensity effect arises from purely sensory, pre-attentive mechanisms rather than deriving from more efficient attentional capture.

  8. Application of thermodynamic-based retention time prediction to ionic liquid stationary phases.

    PubMed

    Weber, Brandon M; Harynuk, James J

    2014-06-01

    First- and second-dimension retention times for a series of alkyl phosphates were predicted for multiple column combinations in GC×GC. This was accomplished through the use of a three-parameter thermodynamic model where the analytes' interactions with the stationary phases in both dimensions are known. Ionic liquid columns were employed to impart unique selectivity for alkyl phosphates, and it was determined that for alkyl phosphate compounds, ionic liquid columns are best used in the primary dimension. Retention coordinates for unknown phosphates are predicted from the thermodynamic parameters of a set standard alkyl phosphates. Additionally, we present changing retention properties of alkyl phosphates on some ionic liquid columns, due to suspected reaction between the analyte and column. This makes it difficult to accurately predict their retention properties, and in general poses a problem for ionic liquid columns with these types of analytes.

  9. 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.

  10. 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.

  11. Prediction of reverberation time and speech transmission index in long enclosures

    NASA Astrophysics Data System (ADS)

    Li, Kai Ming; Lam, Pou Man

    2005-06-01

    It is known that the sound field in a long space is not diffuse, and that the classic theory of room acoustics is not applicable. A theoretical model is developed for the prediction of reverberation time and speech transmission index in rectangular long enclosures, such as corridors and train stations, where the acoustic quality is important for speech. The model is based on an image-source method, and both acoustically hard and impedance boundaries are investigated. An approximate analytical solution is used to predict the frequency response of the sound field. The reverberation time is determined from the decay curve which is computed by a reverse-time integration of the squared impulse response. The angle-dependence of reflection coefficients of the boundaries and the change of phase upon reflection are incorporated in this model. Due to the relatively long distance of sound propagation, the effect of atmospheric absorption is also considered. Measurements of reverberation time and speech transmission index taken from a real tunnel, a corridor, and a model tunnel are presented. The theoretical predictions are found to agree well with the experimental data. An application of the proposed model has been suggested. .

  12. Prediction of time to exhaustion in competitive cyclists from a perceptually based scale.

    PubMed

    Garcin, Murielle; Coquart, Jérémy B J; Robin, Sophie; Matran, Régis

    2011-05-01

    Prediction of time to exhaustion in competitive cyclists from a perceptually based scale. We have tested the validity of the estimated time limit (ETL) scale to predict an exhaustion time (T(lim)) from values stemming from incremental and randomized constant workloads tests on a cycle ergometer. Twenty-five cyclists performed 1 continuous incremental test, 1 discontinuous test with randomized workloads, and 1 constant power output test at 90% of maximal aerobic power (MAP) to exhaustion. Estimated time limits at 90% MAP during the incremental test and the test with randomized workloads were calculated from exponential relationships between power and ETL using the same 4 workloads. Real measured T(lim) during the constant power output test was converted into ETL values (called measured ETL). The differences between the calculated and measured ETLs were examined. Estimated time limits calculated at 90% MAP during the incremental and randomized tests corresponded to 14 minutes 56 seconds and 10 minutes 14 seconds, whereas measured ETL was equal to 11 minutes 19 seconds ± 3 minutes 40 seconds. The results showed a nonsignificant difference between calculated and measured ETLs. However, the mean differences between the measured ETL values during the constant test performed at the same intensity were -1.3 ± 2.9 and 0.3 ± 3.0 for the incremental and the randomized constant workloads tests, respectively. Consequently, the use of ETL calculated at 90% MAP during the test with randomized constant workloads may be preferable to predict the accurate T(lim). Moreover, it would seem that high-level cyclists, who were more consciously attuned to their bodies and their own effort sense, were more accurate in their prediction than low-level cyclists. It is concluded that the randomized constant workloads test that is both shorter and less strenuous would be more convenient for high-level athletes.

  13. Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

    PubMed

    Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

    2017-04-06

    When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task.

  14. Bayesian prediction of earthquake network based on space-time influence domain

    NASA Astrophysics Data System (ADS)

    Zhang, Ya; Zhao, Hai; He, Xuan; Pei, Fan-Dong; Li, Guang-Guang

    2016-03-01

    Bayesian networks (BNs) are used to analyze the conditional dependencies among different events, which are expressed by conditional probability. Scientists have already investigated the seismic activities by using BNs. Recently, earthquake network is used as a novel methodology to analyze the relationships among the earthquake events. In this paper, we propose a way to predict earthquake from a new perspective. The BN is constructed after processing, which is derived from the earthquake network based on space-time influence domain. And then, the BN parameters are learnt by using the cases which are designed from the seismic data in the period between 00:00:00 on January 1, 1992 and 00:00:00 on January 1, 2012. At last, predictions are done for the data in the period between 00:00:00 on January 1, 2012 and 00:00:00 on January 1, 2015 combining the BN with the parameters. The results show that the success rate of the prediction including delayed prediction is about 65%. It is also discovered that the predictions for some nodes have high rate of accuracy under investigation.

  15. Timing predictability enhances regularity encoding in the human subcortical auditory pathway.

    PubMed

    Gorina-Careta, Natàlia; Zarnowiec, Katarzyna; Costa-Faidella, Jordi; Escera, Carles

    2016-11-17

    The encoding of temporal regularities is a critical property of the auditory system, as short-term neural representations of environmental statistics serve to auditory object formation and detection of potentially relevant novel stimuli. A putative neural mechanism underlying regularity encoding is repetition suppression, the reduction of neural activity to repeated stimulation. Although repetitive stimulation per se has shown to reduce auditory neural activity in animal cortical and subcortical levels and in the human cerebral cortex, other factors such as timing may influence the encoding of statistical regularities. This study was set out to investigate whether temporal predictability in the ongoing auditory input modulates repetition suppression in subcortical stages of the auditory processing hierarchy. Human auditory frequency-following responses (FFR) were recorded to a repeating consonant-vowel stimuli (/wa/) delivered in temporally predictable and unpredictable conditions. FFR amplitude was attenuated by repetition independently of temporal predictability, yet we observed an accentuated suppression when the incoming stimulation was temporally predictable. These findings support the view that regularity encoding spans across the auditory hierarchy and point to temporal predictability as a modulatory factor of regularity encoding in early stages of the auditory pathway.

  16. 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

  17. 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

  18. Timing predictability enhances regularity encoding in the human subcortical auditory pathway

    PubMed Central

    Gorina-Careta, Natàlia; Zarnowiec, Katarzyna; Costa-Faidella, Jordi; Escera, Carles

    2016-01-01

    The encoding of temporal regularities is a critical property of the auditory system, as short-term neural representations of environmental statistics serve to auditory object formation and detection of potentially relevant novel stimuli. A putative neural mechanism underlying regularity encoding is repetition suppression, the reduction of neural activity to repeated stimulation. Although repetitive stimulation per se has shown to reduce auditory neural activity in animal cortical and subcortical levels and in the human cerebral cortex, other factors such as timing may influence the encoding of statistical regularities. This study was set out to investigate whether temporal predictability in the ongoing auditory input modulates repetition suppression in subcortical stages of the auditory processing hierarchy. Human auditory frequency–following responses (FFR) were recorded to a repeating consonant–vowel stimuli (/wa/) delivered in temporally predictable and unpredictable conditions. FFR amplitude was attenuated by repetition independently of temporal predictability, yet we observed an accentuated suppression when the incoming stimulation was temporally predictable. These findings support the view that regularity encoding spans across the auditory hierarchy and point to temporal predictability as a modulatory factor of regularity encoding in early stages of the auditory pathway. PMID:27853313

  19. 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

  20. 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.

  1. Prediction of color changes in acetaminophen solution using the time-temperature superposition principle.

    PubMed

    Mochizuki, Koji; Takayama, Kozo

    2016-01-01

    A prediction method for color changes based on the time-temperature superposition principle (TTSP) was developed for acetaminophen solution. Color changes of acetaminophen solution are caused by the degradation of acetaminophen, such as hydrolysis and oxidation. In principle, the TTSP can be applied to only thermal aging. Therefore, the impact of oxidation on the color changes of acetaminophen solution was verified. The results of our experiment suggested that the oxidation products enhanced the color changes in acetaminophen solution. Next, the color changes of acetaminophen solution samples of the same head space volume after accelerated aging at various temperatures were investigated using the Commission Internationale de l'Eclairage (CIE) LAB color space (a*, b*, L* and ΔE*ab), following which the TTSP was adopted to kinetic analysis of the color changes. The apparent activation energies using the time-temperature shift factor of a*, b*, L* and ΔE*ab were calculated as 72.4, 69.2, 72.3 and 70.9 (kJ/mol), respectively, which are similar to the values for acetaminophen hydrolysis reported in the literature. The predicted values of a*, b*, L* and ΔE*ab at 40 °C were obtained by calculation using Arrhenius plots. A comparison between the experimental and predicted values for each color parameter revealed sufficiently high R(2) values (>0.98), suggesting the high reliability of the prediction. The kinetic analysis using TTSP was successfully applied to predicting the color changes under the controlled oxygen amount at any temperature and for any length of time.

  2. Are transit times key process-based tools for regional classification and prediction in ungauged basins?

    NASA Astrophysics Data System (ADS)

    Tetzlaff, D.; Soulsby, C.; Hrachowitz, M.; Speed, M.

    2009-04-01

    In recent years, transit times (TTs) have been increasingly explored as a process-based tools for conceptualising hydrological processes in an integrated manner at a range of scales. Traditionally the identification of the appropriate transit time distribution (TTD) for a hydrological system (e.g. hillslope or catchment), and the derivation of metrics such as the mean transit time (MTT) have required quantitative assessment of input-output relationships for conservative tracers using lumped parameter models. Such work has allowed the main landscape controls on TTs to be identified and facilitated the prediction of MTT in ungauged basins in particular geomorphic provinces. This has shown TT to be a useful diagnostic index of similarity that can be valuable in process-based catchment classification. In this contribution, we used well-constrained MTT estimates (with uncertainty) from 32 experimental catchments (1 to 250km2 in area) with contrasting geologic, topographic, pedologic and climatic characteristics in Scotland. The MTT was highly variable ranging from 30 days to ca. 1200 days for individual catchments. Moreover, MTT was also found to be closely correlated with key hydrometric design statistics such as the Q95, Q5, Mean Annual Flood (MAF) and the slope of the hydrograph recession curve. Analysis of the TT estimates, in conjunction with GIS-based quantitative assessment of key landscape controls, showed that MTT could be predicted to within 25% for ungauged basins from catchment soil cover, drainage density and topographic wetness index. For ungauged basins it was found that the hydrometric design statistics (Q95, Q5, MAF and the recession slope) could be more simply and accurately forecasted from MTT predictions than a single set of catchment characteristics. We demonstrate that TTs - predicted from mapped landscape characteristics - are useful integrating diagnostic metrics for regional classification, prediction and process assessment in ungauged montane

  3. A real-time predictive simulation of abdominal viscera positions during quiet free breathing.

    PubMed

    Hostettler, A; Nicolau, S A; Rémond, Y; Marescaux, J; Soler, L

    2010-12-01

    Prediction of abdominal viscera and tumour positions during free breathing is a major challenge from which several medical applications could benefit. For instance, in radiotherapy it would reduce the healthy tissue irradiation. In this paper, we present a new approach to predict real-time abdominal viscera positions during free breathing. Our method needs an abdo-thoracic 3D preoperative CT or MR image, a second one limited to the diaphragmatic area, and a tracking of the patient's skin position. First, a physical analysis of the breathing motion shows it is possible to predict accurately abdominal viscera positions from the skin position and a modelling of the diaphragm motion. Secondly, a quantitative analysis of the skin and organ motion allows us to define the demands our real-time simulation has to fulfill. Then, we present in detail all the necessary steps of our original method to compute a deformation field from data extracted in both 3D preoperative image and skin surface tracking. Finally, experiments carried out with two human data show that our simulation model predicts abdominal viscera positions, such as liver, kidneys or spleen, at 50 Hz with an accuracy within 2-3 mm.

  4. Methods and on-farm devices to predict calving time in cattle.

    PubMed

    Saint-Dizier, Marie; Chastant-Maillard, Sylvie

    2015-09-01

    In livestock farming, accurate prediction of calving time is a key factor for profitability and animal welfare. The most accurate and sensitive methods to date for prediction of calving within 24 h are the measurement of pelvic ligament relaxation and assays for circulating progesterone and oestradiol-17β. Conversely, the absence of calving within the next 12-24 h can be accurately predicted by the measurement of incremental daily decrease in vaginal temperature and by the combination of pelvic ligament relaxation and teat filling estimates. Continuous monitoring systems can detect behavioural changes occurring on the actual day of calving, some of them being accentuated in the last few hours before delivery; standing/lying transitions, tail raising, feeding time, and dry matter and water intakes differ between cows with dystocia and those with eutocia. Use of these behavioural changes has the potential to improve the management of calving. Currently, four types of devices for calving detection are on the market: inclinometers and accelerometers detecting tail raising and overactivity, abdominal belts monitoring uterine contractions, vaginal probes detecting a decrease in vaginal temperature and expulsion of the allantochorion, and devices placed in the vagina or on the vulvar lips that detect calf expulsion. The performance of these devices under field conditions and their capacity to predict dystocia require further investigation.

  5. 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.

  6. Can a Clinical Test of Reaction Time Predict a Functional Head-Protective Response?

    PubMed Central

    ECKNER, JAMES T.; LIPPS, DAVID B.; KIM, HOGENE; RICHARDSON, JAMES K.; ASHTON-MILLER, JAMES A.

    2015-01-01

    Purpose Reaction time is commonly prolonged after a sport-related concussion. Besides being a marker for injury, a rapid reaction time is necessary for protective maneuvers that can reduce the frequency and severity of additional head impacts. The purpose of this study was to determine whether a clinical test of simple visuomotor reaction time predicted the time taken to raise the hands to protect the head from a rapidly approaching ball. Methods Twenty-six healthy adult participants recruited from campus and community recreation and exercise facilities completed two experimental protocols during a single session: a manual visuomotor simple reaction time test (RTclin) and a sport-related head-protective response (RTsprt). RTclin measured the time required to catch a thin vertically oriented device on its release by the tester and was calculated from the distance the device fell before being arrested. RTsprt measured the time required to raise the hands from waist level to block a foam tennis ball fired toward the subject’s face from an air cannon and was determined using an optoelectronic camera system. A correlation coefficient was calculated between RTclin and RTsprt, with linear regression used to assess for effect modification by other covariates. Results A strong positive correlation was found between RTclin and RTsprt (r = 0.725, P < 0.001) independent of age, gender, height, or weight. Conclusions RTclin is predictive of a functional sport-related head-protective response. To our knowledge, this is the first demonstration of a clinical test predicting the ability to protect the head in a simulated sport environment. This correlation with a functional head-protective response is a relevant consideration for the potential use of RTclin as part of a multifaceted concussion assessment program. PMID:20689458

  7. Integrating random matrix theory predictions with short-time dynamical effects in chaotic systems.

    PubMed

    Smith, A Matthew; Kaplan, Lev

    2010-07-01

    We discuss a modification to random matrix theory eigenstate statistics that systematically takes into account the nonuniversal short-time behavior of chaotic systems. The method avoids diagonalization of the Hamiltonian; instead it requires only knowledge of short-time dynamics for a chaotic system or ensemble of similar systems. Standard random matrix theory and semiclassical predictions are recovered in the limits of zero Ehrenfest time and infinite Heisenberg time, respectively. As examples, we discuss wave-function autocorrelations and cross correlations, and show that significant improvement in accuracy is obtained for simple chaotic systems where comparison can be made with brute-force diagonalization. The accuracy of the method persists even when the short-time dynamics of the system or ensemble is known only in a classical approximation. Further improvement in the rate of convergence is obtained when the method is combined with the correlation function bootstrapping approach introduced previously.

  8. 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.

  9. School nurse perspectives of challenges and how they perceive success in their professional nursing roles.

    PubMed

    Smith, Shirley G; Firmin, Michael W

    2009-04-01

    This is a phenomenological study of 25 school nurses employed in a large, urban school district in the midwestern section of the United States. In addition to school nursing, the participants also had professional work experience in other nursing specialties. Thematic analysis of the data focused on the challenges faced by the school nurses, their views of school nursing success, and elements of job satisfaction. Overall, the school nurses reported the positive aspects of school nursing outweigh the negative aspects of their jobs. Developmental changes were reported among the school nurses in this study as they reflected on how they perceived their nursing career over time and during different seasons of their lives.

  10. 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…

  11. 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.

  12. Predictive time-series modeling using artificial neural networks for Linac beam symmetry: an empirical study.

    PubMed

    Li, Qiongge; Chan, Maria F

    2017-01-01

    Over half of cancer patients receive radiotherapy (RT) as partial or full cancer treatment. Daily quality assurance (QA) of RT in cancer treatment closely monitors the performance of the medical linear accelerator (Linac) and is critical for continuous improvement of patient safety and quality of care. Cumulative longitudinal QA measurements are valuable for understanding the behavior of the Linac and allow physicists to identify trends in the output and take preventive actions. In this study, artificial neural networks (ANNs) and autoregressive moving average (ARMA) time-series prediction modeling techniques were both applied to 5-year daily Linac QA data. Verification tests and other evaluations were then performed for all models. Preliminary results showed that ANN time-series predictive modeling has more advantages over ARMA techniques for accurate and effective applicability in the dosimetry and QA field.

  13. 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.

  14. 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

  15. 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 ...

  16. Mentoring practices benefiting pediatric nurses.

    PubMed

    Weese, Meghan M; Jakubik, Louise D; Eliades, Aris B; Huth, Jennifer J

    2015-01-01

    Previous studies examining predictors of pediatric nurse protégé mentoring benefits demonstrated that protégé perception of quality was the single best predictor of mentoring benefits. The ability to identify the mentoring practices that predict specific benefits for individual nurses provides a better understanding of how mentoring relationships can be leveraged within health care organizations promoting mutual mentoring benefits. This descriptive correlational, non-experimental study of nurses at a northeast Ohio, Magnet® recognized, free-standing pediatric hospital advances nursing science by demonstrating how mentoring practices benefit pediatric nurse protégés.

  17. A Neural Network Approach to the Prediction and Confidence Assignation of Nonlinear Time Series Classifications

    DTIC Science & Technology

    1995-12-01

    your technical expertise and insight. This research began with your suggestion and would be nowhere without your market insight. Despite some set backs...predict stock market behavior prior to this work. Chapter III will describe in detail the methodology that was developed in this research to improve the...network. In this research effort, various market indicators (e.g., net changes over time) are used to develop a backpropagation neural network to

  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. 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.

  20. Potential for long-lead prediction of the western North Pacific monsoon circulation beyond seasonal time scales

    NASA Astrophysics Data System (ADS)

    Choi, Jung; Son, Seok-Woo; Seo, Kyong-Hwan; Lee, June-Yi; Kang, Hyun-Suk

    2016-02-01

    Although the western North Pacific (WNP) monsoon circulation significantly impacts the socioeconomic communities around Asia, its prediction is only limited to a few months. By examining the Coupled Model Intercomparison Project phase 5 decadal hindcast experiments, we explore a possibility of the extended prediction skill for the WNP monsoon circulation beyond seasonal time scales. It is found that the multimodel ensemble (MME) predictions, initialized in January, successfully predict the WNP circulation in spring and early summer. Somewhat surprisingly, a reliable prediction of the WNP circulation appears even in the following spring with a maximum lead time of 14 months. This unexpected prediction skill is likely caused by the improved El Niño-Southern Oscillation (ENSO) prediction and the exaggerated dynamical link between the ENSO and premonsoon circulation in the MME prediction. Although further studies are needed, this result may open up new opportunities for the multiseasonal prediction of the WNP monsoon circulation.

  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. 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.

  3. 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

    2015-08-07

    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.

  4. Fast template matching based on grey prediction for real-time object tracking

    NASA Astrophysics Data System (ADS)

    Lv, Mingming; Hou, Yuanlong; Liu, Rongzhong; Hou, Runmin

    2017-02-01

    Template matching is a basic algorithm for image processing, and real-time is a crucial requirement of object tracking. For real-time tracking, a fast template matching algorithm based on grey prediction is presented, where computation cost can be reduced dramatically by minimizing search range. First, location of the tracked object in the current image is estimated by Grey Model (GM). GM(1,1), which is the basic model of grey prediction, can use some known information to foretell the location. Second, the precise position of the object in the frame is computed by template matching. Herein, Sequential Similarity Detection Algorithm (SSDA) with a self-adaptive threshold is employed to obtain the matching position in the neighborhood of the predicted location. The role of threshold in SSDA is important, as a proper threshold can make template matching fast and accurate. Moreover, a practical weighted strategy is utilized to handle scale and rotation changes of the object, as well as illumination changes. The experimental results show the superior performance of the proposed algorithm over the conventional full-search method, especially in terms of executive time.

  5. 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

  6. Neural Network of Predictive Motor Timing in the Context of Gender Differences.

    PubMed

    Filip, Pavel; Lošák, Jan; Kašpárek, Tomáš; Vaníček, Jiří; Bareš, Martin

    2016-01-01

    Time perception is an essential part of our everyday lives, in both the prospective and the retrospective domains. However, our knowledge of temporal processing is mainly limited to the networks responsible for comparing or maintaining specific intervals or frequencies. In the presented fMRI study, we sought to characterize the neural nodes engaged specifically in predictive temporal analysis, the estimation of the future position of an object with varying movement parameters, and the contingent neuroanatomical signature of differences in behavioral performance between genders. The established dominant cerebellar engagement offers novel evidence in favor of a pivotal role of this structure in predictive short-term timing, overshadowing the basal ganglia reported together with the frontal cortex as dominant in retrospective temporal processing in the subsecond spectrum. Furthermore, we discovered lower performance in this task and massively increased cerebellar activity in women compared to men, indicative of strategy differences between the genders. This promotes the view that predictive temporal computing utilizes comparable structures in the retrospective timing processes, but with a definite dominance of the cerebellum.

  7. 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

  8. Model-based planning and real-time predictive control for laser-induced thermal therapy

    PubMed Central

    Feng, Yusheng; Fuentes, David

    2014-01-01

    In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity. PMID:22098360

  9. 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.

  10. 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

  11. 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

  12. 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.

  13. Prediction of optimal vaccination timing for infectious bursal disease based on chick weight.

    PubMed

    Vaziry, Asaad; Venne, Daniel; Frenette, Diane; Gingras, Sylvain; Silim, Amer

    2007-12-01

    Growth rate in broiler birds has increased substantially in the last decade due to improvement in genetics, feed formulation, cleaner environment, and vaccine formulations. As a result, it has become necessary to review and revise prediction method for vaccination in chicks. This study was undertaken to determine the possible use of the rate of weight gain rather than age in predicting vaccination time. Two groups of 1-day-old broilers originating from old and young breeders, respectively, and with different levels of maternal antibodies against infectious bursal disease virus (IBDV) were used in this study. The chicks were divided into four groups and subjected to two feed regiments: groups A1 and B1 were fed broiler feed for normal growth rate, and groups A2 and B2 were fed breeder feed for slower growth rate. At 1, 4, 8, 12, 16, 22, 29, and 36 days of age, 22 chicks in each group were weighed, and blood samples were collected. Serum samples were tested for antibodies against IBDV by enzyme-linked immunosorbent assay (ELISA) and virus neutralization test. Maternal antibody decline curves for each group were plotted according to chick age and chick weight. Fast-growing birds in groups A1 and B1 showed a faster rate of antibody decline, whereas slow-growing birds in groups A2 and B2 had a slower rate of antibody decline. Based on the effect of weight gain on maternal antibody decline, a new way of predicting vaccination time for IBDV based on measuring maternal antibody titers at 4 days of age was proposed and tested. The predicted antibody decline was shown to correspond to the real ELISA titers measured in our experiments (R = 0.9889), whereas a lower correlation (R = 0.8355) was detected between real ELISA titers and the titers predicted by the current method using age-based Deventer formula.

  14. The timing and precision of action prediction in the aging brain

    PubMed Central

    Jones, Alex L.; Cross, Emily S.

    2015-01-01

    Abstract 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. Hum Brain Mapp 37:54–66, 2016. © 2015 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc. PMID:26503586

  15. T-CREST: A Time-Predictable Multi-Core Platform for Aerospace Applications

    NASA Astrophysics Data System (ADS)

    Schoeberl, Martin; Silva, Claudio; Rocha, Andre

    2014-08-01

    Space systems are hard real-time systems, where the worst-case execution time (WCET) of tasks needs to be known to prove absence of deadline misses. For simple processor and memory architectures it is possible to statically derive a safe upper bound of the WCET. However, future requirements in more autonomous missions require more processing power. This increase in processing power is approached by multi-core processors. However, current multi-core processors are not WCET analyzable.The mission of T-CREST is to develop tools and build a multi-core system that provides high performance, but be WCET analyzable. The T-CREST time-predictable system will simplify the safety argument with respect to the maximum execution time and increase the performance with multi-core technology. Thus the T-CREST system will result in lower costs for safety-relevant applications, reducing system complexity, simultaneously providing faster time-predictable execution. Most of the T-CREST technology is available in open-source.

  16. 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).

  17. Psychological resilience predicts depressive symptoms among spouses of persons with Alzheimer disease over time.

    PubMed

    O'Rourke, Norm; Kupferschmidt, Anthony L; Claxton, Amy; Smith, Julianna Z; Chappell, Neena; Beattie, B Lynn

    2010-11-01

    This study examines the three facets of psychological resilience (i.e., perceived control, commitment to living, challenge versus stability) as predictors of depressive symptoms over time among spousal caregivers of persons with Alzheimer disease; these resilience factors were considered over and above dementia-related and socio-demographic control variables. A sample of 105 cohabiting spouses of persons diagnosed with probable or possible Alzheimer disease was recruited for this study. Multilevel modeling enabled us to examine baseline resilience, and the direction and magnitude of change in resilience over time, as distinct predictors of depressive symptoms one year later, and change in depressive symptoms between points of measurement. Both Time 1 control and challenge predicted lower levels of depressive symptoms one year later; furthermore, an increase in challenge over this interval predicted lower Time 2 depressive symptoms. In contrast, commitment did not emerge as a statistically significant predictor of caregiver depression. Findings of this study provide general support for the stress process model of caregiving; in particular, the central role of intra-psychic factors as significant predictors of depressive symptoms over time.

  18. Analysis of ischemia/reperfusion injury in time-zero biopsies predicts liver allograft outcomes.

    PubMed

    Ali, Jason M; Davies, Susan E; Brais, Rebecca J; Randle, Lucy V; Klinck, John R; Allison, Michael E D; Chen, Yining; Pasea, Laura; Harper, Simon F J; Pettigrew, Gavin J

    2015-04-01

    Ischemia/reperfusion injury (IRI) that develops after liver implantation may prejudice long-term graft survival, but it remains poorly understood. Here we correlate the severity of IRIs that were determined by histological grading of time-zero biopsies sampled after graft revascularization with patient and graft outcomes. Time-zero biopsies of 476 liver transplants performed at our center between 2000 and 2010 were graded as follows: nil (10.5%), mild (58.8%), moderate (26.1%), and severe (4.6%). Severe IRI was associated with donor age, donation after circulatory death, prolonged cold ischemia time, and liver steatosis, but it was also associated with increased rates of primary nonfunction (9.1%) and retransplantation within 90 days (22.7%). Longer term outcomes in the severe IRI group were also poor, with 1-year graft and patient survival rates of only 55% and 68%, respectively (cf. 90% and 93% for the remainder). Severe IRI on the time-zero biopsy was, in a multivariate analysis, an independent determinant of 1-year graft survival and was a better predictor of 1-year graft loss than liver steatosis, early graft dysfunction syndrome, and high first-week alanine aminotransferase with a positive predictive value of 45%. Time-zero biopsies predict adverse clinical outcomes after liver transplantation, and severe IRI upon biopsy signals the likely need for early retransplantation.

  19. Communication in Nursing Practice

    PubMed Central

    Kourkouta, Lambrini; Papathanasiou, Ioanna V.

    2014-01-01

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

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

    PubMed

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

    2016-03-01

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