Online learning from input versus offline memory evolution in adult word learning: effects of neighborhood density and phonologically related practice.

PubMed

Storkel, Holly L; Bontempo, Daniel E; Pak, Natalie S

2014-10-01

In this study, the authors investigated adult word learning to determine how neighborhood density and practice across phonologically related training sets influence online learning from input during training versus offline memory evolution during no-training gaps. Sixty-one adults were randomly assigned to learn low- or high-density nonwords. Within each density condition, participants were trained on one set of words and then were trained on a second set of words, consisting of phonological neighbors of the first set. Learning was measured in a picture-naming test. Data were analyzed using multilevel modeling and spline regression. Steep learning during input was observed, with new words from dense neighborhoods and new words that were neighbors of recently learned words (i.e., second-set words) being learned better than other words. In terms of memory evolution, large and significant forgetting was observed during 1-week gaps in training. Effects of density and practice during memory evolution were opposite of those during input. Specifically, forgetting was greater for high-density and second-set words than for low-density and first-set words. High phonological similarity, regardless of source (i.e., known words or recent training), appears to facilitate online learning from input but seems to impede offline memory evolution.

Training transfer: a systematic review of the impact of inner setting factors.

PubMed

Jackson, Carrie B; Brabson, Laurel A; Quetsch, Lauren B; Herschell, Amy D

2018-06-19

Consistent with Baldwin and Ford's model (Pers Psychol 41(1):63-105, 1988), training transfer is defined as the generalization of learning from a training to everyday practice in the workplace. The purpose of this review was to examine the influence of work-environment factors, one component of the model hypothesized to influence training transfer within behavioral health. An electronic literature search guided by the Consolidated Framework for Implementation Research's inner setting domain was conducted was conducted on Medline OVID, Medline EMBASE, and PsycINFO databases. Of 9184 unique articles, 169 full-text versions of articles were screened for eligibility, yielding 26 articles meeting inclusion criteria. Results from the 26 studies revealed that overall, having more positive networks and communication, culture, implementation climate, and readiness for implementation can facilitate training transfer. Although few studies have examined the impact of inner setting factors on training transfer, these results suggest organizational context is important to consider with training efforts. These findings have important implications for individuals in the broader health professions educational field.

Dissociable effects of game elements on motivation and cognition in a task-switching training in middle childhood

PubMed Central

Dörrenbächer, Sandra; Müller, Philipp M.; Tröger, Johannes; Kray, Jutta

2014-01-01

Although motivational reinforcers are often used to enhance the attractiveness of trainings of cognitive control in children, little is known about how such motivational manipulations of the setting contribute to separate gains in motivation and cognitive-control performance. Here we provide a framework for systematically investigating the impact of a motivational video-game setting on the training motivation, the task performance, and the transfer success in a task-switching training in middle-aged children (8–11 years of age). We manipulated both the type of training (low-demanding/single-task training vs. high-demanding/task-switching training) as well as the motivational setting (low-motivational/without video-game elements vs. high-motivational/with video-game elements) separately from another. The results indicated that the addition of game elements to a training setting enhanced the intrinsic interest in task practice, independently of the cognitive demands placed by the training type. In the task-switching group, the high-motivational training setting led to an additional enhancement of task and switching performance during the training phase right from the outset. These motivation-induced benefits projected onto the switching performance in a switching situation different from the trained one (near-transfer measurement). However, in structurally dissimilar cognitive tasks (far-transfer measurement), the motivational gains only transferred to the response dynamics (speed of processing). Hence, the motivational setting clearly had a positive impact on the training motivation and on the paradigm-specific task-switching abilities; it did not, however, consistently generalize on broad cognitive processes. These findings shed new light on the conflation of motivation and cognition in childhood and may help to refine guidelines for designing adequate training interventions. PMID:25431564

Tutor Training Packet. "Ready-Set-ABE" To Ease Students' Transition into ABE Level Studies.

ERIC Educational Resources Information Center

Molek, Carol

This training packet, consisting of a workshop guide, two instructional guides, and assorted pamphlets and brochures, is intended for use by volunteer tutors who are themselves learning how to work with adults enrolled in an adult literacy program. The following topics are covered in the training workshop guide: the objectives and workings of…

Improving question asking in high-functioning adolescents with autism spectrum disorders: effectiveness of small-group training.

PubMed

Palmen, Annemiek; Didden, Robert; Arts, Marieke

2008-01-01

Small-group training consisting of feedback and self-management was effective in improving question-asking skills during tutorial conversations in nine high-functioning adolescents with autism spectrum disorder. Training was implemented in a therapy room and lasted 6 weeks. Sessions were conducted once a week and lasted about an hour. Experimenters collected data during tutorial conversations in a natural setting. Training of question-asking skills consisted of verbal feedback and role-play during short simulated conversations and a table game. A self-management strategy and common stimuli (e.g., flowchart) were included to promote generalization. Mean percentage of correct questions during tutorial conversations improved significantly after training. Response efficiency also increased. Participants and personal coaches evaluated the training as effective and acceptable.

Effects of training set selection on pain recognition via facial expressions

NASA Astrophysics Data System (ADS)

Shier, Warren A.; Yanushkevich, Svetlana N.

2016-07-01

This paper presents an approach to pain expression classification based on Gabor energy filters with Support Vector Machines (SVMs), followed by analyzing the effects of training set variations on the systems classification rate. This approach is tested on the UNBC-McMaster Shoulder Pain Archive, which consists of spontaneous pain images, hand labelled using the Prkachin and Solomon Pain Intensity scale. In this paper, the subjects pain intensity level has been quantized into three disjoint groups: no pain, weak pain and strong pain. The results of experiments show that Gabor energy filters with SVMs provide comparable or better results to previous filter- based pain recognition methods, with precision rates of 74%, 30% and 78% for no pain, weak pain and strong pain, respectively. The study of effects of intra-class skew, or changing the number of images per subject, show that both completely removing and over-representing poor quality subjects in the training set has little effect on the overall accuracy of the system. This result suggests that poor quality subjects could be removed from the training set to save offline training time and that SVM is robust not only to outliers in training data, but also to significant amounts of poor quality data mixed into the training sets.

The efficacy of a whole body sprint-interval training intervention in an office setting: A feasibility study.

PubMed

Gurd, Brendon J; Patel, Jugal; Edgett, Brittany A; Scribbans, Trisha D; Quadrilatero, Joe; Fischer, Steven L

2018-05-28

Whole body sprint-interval training (WB-SIT) represents a mode of exercise training that is both time-efficient and does not require access to an exercise facility. The current study examined the feasibility of implementing a WB-SIT intervention in a workplace setting. A total of 747 employees from a large office building were invited to participate with 31 individuals being enrolled in the study. Anthropometrics, aerobic fitness, core and upper body strength, and lower body mobility were assessed before and after a 12-week exercise intervention consisting of 2-4 training sessions per week. Each training session required participants to complete 8, 20-second intervals (separated by 10 seconds of rest) of whole body exercise. Proportion of participation was 4.2% while the response rate was 35% (11/31 participants completed post training testing). In responders, compliance to prescribed training was 83±17%, and significant (p <  0.05) improvements were observed for aerobic fitness, push-up performance and lower body mobility. These results demonstrate the efficacy of WB-FIT for improving fitness and mobility in an office setting, but highlight the difficulties in achieving high rates of participation and response in this setting.

Applying lessons from commercial aviation safety and operations to resuscitation.

PubMed

Ornato, Joseph P; Peberdy, Mary Ann

2014-02-01

Both commercial aviation and resuscitation are complex activities in which team members must respond to unexpected emergencies in a consistent, high quality manner. Lives are at stake in both activities and the two disciplines have similar leadership structures, standard setting processes, training methods, and operational tools. Commercial aviation crews operate with remarkable consistency and safety, while resuscitation team performance and outcomes are highly variable. This commentary provides the perspective of two physician-pilots showing how commercial aviation training, operations, and safety principles can be adapted to resuscitation team training and performance. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Evaluation of Athletic Training Students' Clinical Proficiencies

PubMed Central

Walker, Stacy E; Weidner, Thomas G; Armstrong, Kirk J

2008-01-01

Context: Appropriate methods for evaluating clinical proficiencies are essential in ensuring entry-level competence. Objective: To investigate the common methods athletic training education programs use to evaluate student performance of clinical proficiencies. Design: Cross-sectional design. Setting: Public and private institutions nationwide. Patients or Other Participants: All program directors of athletic training education programs accredited by the Commission on Accreditation of Allied Health Education Programs as of January 2006 (n  =  337); 201 (59.6%) program directors responded. Data Collection and Analysis: The institutional survey consisted of 11 items regarding institutional and program demographics. The 14-item Methods of Clinical Proficiency Evaluation in Athletic Training survey consisted of respondents' demographic characteristics and Likert-scale items regarding clinical proficiency evaluation methods and barriers, educational content areas, and clinical experience settings. We used analyses of variance and independent t tests to assess differences among athletic training education program characteristics and the barriers, methods, content areas, and settings regarding clinical proficiency evaluation. Results: Of the 3 methods investigated, simulations (n  =  191, 95.0%) were the most prevalent method of clinical proficiency evaluation. An independent-samples t test revealed that more opportunities existed for real-time evaluations in the college or high school athletic training room (t189  =  2.866, P  =  .037) than in other settings. Orthopaedic clinical examination and diagnosis (4.37 ± 0.826) and therapeutic modalities (4.36 ± 0.738) content areas were scored the highest in sufficient opportunities for real-time clinical proficiency evaluations. An inadequate volume of injuries or conditions (3.99 ± 1.033) and injury/condition occurrence not coinciding with the clinical proficiency assessment timetable (4.06 ± 0.995) were barriers to real-time evaluation. One-way analyses of variance revealed no difference between athletic training education program characteristics and the opportunities for and barriers to real-time evaluations among the various clinical experience settings. Conclusions: No one primary barrier hindered real-time clinical proficiency evaluation. To determine athletic training students' clinical proficiency for entry-level employment, athletic training education programs must incorporate standardized patients or take a disciplined approach to using simulation for instruction and evaluation. PMID:18668172

Effects of interset whole-body vibration on bench press resistance training in trained and untrained individuals.

PubMed

Timon, Rafael; Collado-Mateo, Daniel; Olcina, Guillermo; Gusi, Narcis

2016-03-01

Previous studies have demonstrated positive effects of acute vibration exercise on concentric strength and power, but few have observed the effects of vibration exposure on resistance training. The aim of this study was to verify the effects of whole body vibration applied to the chest via hands on bench press resistance training in trained and untrained individuals. Nineteen participants (10 recreationally trained bodybuilders and 9 untrained students) performed two randomized sessions of resistance training on separate days. Each strength session consisted of 3 bench press sets with a load of 75% 1RM to failure in each set, with 2 minutes' rest between sets. All subjects performed the same strength training with either, vibration exposure (12 Hz, 4 mm) of 30 seconds immediately before each bench press set or without vibration. Number of total repetitions, kinematic parameters, blood lactate and perceived exertion were analyzed. In the untrained group, vibration exposure caused a significant increase in the mean velocity (from 0.36±0.02 to 0.39±0.03 m/s) and acceleration (from 0.75±0.10 to 0.86±0.09 m/s2), as well as a decrease in perceived effort (from 8±0.57 to 7.35±0.47) in the first bench press set, but no change was observed in the third bench press set. In the recreationally trained bodybuilders, vibration exposure did not cause any improvement on the performance of bench press resistance training. These results suggest that vibration exposure applied just before the bench press exercise could be a good practice to be implemented by untrained individuals in resistance training.

Guidelines for Setting Up an Extended Field Trip to Florida and the Florida Keys: An Interactive Experiential Training Field Biology Program Consisting of Pretrip Instruction, Search Image Training, Field Exercises, and Observations of Tropical Habitats and Coral Reefs.

ERIC Educational Resources Information Center

Baker, Claude D.; And Others

The importance of experiential aspects of biological study is addressed using multi-dimensional classroom and field classroom approaches to student learning. This document includes a guide to setting up this style of field experience. Several teaching innovations are employed to introduce undergraduate students to the literature, techniques, and…

Effects of draught load exercise and training on calcium homeostasis in horses.

PubMed

Vervuert, I; Coenen, M; Zamhöfer, J

2005-01-01

This study was conducted to investigate the effects of draught load exercise on calcium (Ca) homeostasis in young horses. Five 2-year-old untrained Standardbred horses were studied in a 4-month training programme. All exercise workouts were performed on a treadmill at a 6% incline and with a constant draught load of 40 kg (0.44 kN). The training programme started with a standardized exercise test (SET 1; six incremental steps of 5 min duration each, first step 1.38 m/s, stepwise increase by 0.56 m/s). A training programme was then initiated which consisted of low-speed exercise sessions (LSE; constant velocity at 1.67 m/s for 60 min, 48 training sessions in total). After the 16th and 48th LSE sessions, SETs (SET 2: middle of training period, SET 3: finishing training period) were performed again under the identical test protocol of SET 1. Blood samples for blood lactate, plasma total Ca, blood ionized calcium (Ca(2+)), blood pH, plasma inorganic phosphorus (P(i)) and plasma intact parathyroid hormone (PTH) were collected before, during and after SETs, and before and after the first, 16th, 32nd and 48th LSE sessions. During SETs there was a decrease in ionized Ca(2+) and a rise in lactate, P(i) and intact PTH. The LSEs resulted in an increase in pH and P(i), whereas lactate, ionized Ca(2+), total Ca and intact PTH were not affected. No changes in Ca metabolism were detected in the course of training. Results of this study suggest that the type of exercise influences Ca homeostasis and intact PTH response, but that these effects are not influenced in the course of the training period.

O'Neal Training Manual.

ERIC Educational Resources Information Center

Alabama State Dept. of Education, Montgomery.

This training manual provides 42 lessons developed for a workplace literacy program at O'Neal Steel. Each lesson consists of a summary sheet with activities and corresponding materials and time; handout(s); pretest; instructor materials and samples; and worksheet(s). Activities in each lesson are set induction, guided practice, applied practice,…

Comprehensive simulation-enhanced training curriculum for an advanced minimally invasive procedure: a randomized controlled trial.

PubMed

Zevin, Boris; Dedy, Nicolas J; Bonrath, Esther M; Grantcharov, Teodor P

2017-05-01

There is no comprehensive simulation-enhanced training curriculum to address cognitive, psychomotor, and nontechnical skills for an advanced minimally invasive procedure. 1) To develop and provide evidence of validity for a comprehensive simulation-enhanced training (SET) curriculum for an advanced minimally invasive procedure; (2) to demonstrate transfer of acquired psychomotor skills from a simulation laboratory to live porcine model; and (3) to compare training outcomes of SET curriculum group and chief resident group. University. This prospective single-blinded, randomized, controlled trial allocated 20 intermediate-level surgery residents to receive either conventional training (control) or SET curriculum training (intervention). The SET curriculum consisted of cognitive, psychomotor, and nontechnical training modules. Psychomotor skills in a live anesthetized porcine model in the OR was the primary outcome. Knowledge of advanced minimally invasive and bariatric surgery and nontechnical skills in a simulated OR crisis scenario were the secondary outcomes. Residents in the SET curriculum group went on to perform a laparoscopic jejunojejunostomy in the OR. Cognitive, psychomotor, and nontechnical skills of SET curriculum group were also compared to a group of 12 chief surgery residents. SET curriculum group demonstrated superior psychomotor skills in a live porcine model (56 [47-62] versus 44 [38-53], P<.05) and superior nontechnical skills (41 [38-45] versus 31 [24-40], P<.01) compared with conventional training group. SET curriculum group and conventional training group demonstrated equivalent knowledge (14 [12-15] versus 13 [11-15], P = 0.47). SET curriculum group demonstrated equivalent psychomotor skills in the live porcine model and in the OR in a human patient (56 [47-62] versus 63 [61-68]; P = .21). SET curriculum group demonstrated inferior knowledge (13 [11-15] versus 16 [14-16]; P<.05), equivalent psychomotor skill (63 [61-68] versus 68 [62-74]; P = .50), and superior nontechnical skills (41 [38-45] versus 34 [27-35], P<.01) compared with chief resident group. Completion of the SET curriculum resulted in superior training outcomes, compared with conventional surgery training. Implementation of the SET curriculum can standardize training for an advanced minimally invasive procedure and can ensure that comprehensive proficiency milestones are met before exposure to patient care. Copyright © 2017 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Irisin and exercise training in humans - results from a randomized controlled training trial.

PubMed

Hecksteden, Anne; Wegmann, Melissa; Steffen, Anke; Kraushaar, Jochen; Morsch, Arne; Ruppenthal, Sandra; Kaestner, Lars; Meyer, Tim

2013-11-05

The recent discovery of a new myokine (irisin) potentially involved in health-related training effects has gained great attention, but evidence for a training-induced increase in irisin remains preliminary. Therefore, the present study aimed to determine whether irisin concentration is increased after regular exercise training in humans. In a randomized controlled design, two guideline conforming training interventions were studied. Inclusion criteria were age 30 to 60 years, <1 hour/week regular activity, non-smoker, and absence of major diseases. 102 participants could be included in the analysis. Subjects in the training groups exercised 3 times per week for 26 weeks. The minimum compliance was defined at 70%. Aerobic endurance training (AET) consisted of 45 minutes of walking/running at 60% heart rate reserve. Strength endurance training (SET) consisted of 8 machine-based exercises (2 sets of 15 repetitions with 100% of the 20 repetition maximum). Serum irisin concentrations in frozen serum samples were determined in a single blinded measurement immediately after the end of the training study. Physical performance provided positive control for the overall efficacy of training. Differences between groups were tested for significance using analysis of variance. For post hoc comparisons with the control group, Dunnett's test was used. Maximum performance increased significantly in the training groups compared with controls (controls: ±0.0 ± 0.7 km/h; AET: 1.1 ± 0.6 km/h, P < 0.01; SET: +0.5 ± 0.7 km/h, P = 0.01). Changes in irisin did not differ between groups (controls: 101 ± 81 ng/ml; AET: 44 ± 93 ng/ml; SET: 60 ± 92 ng/ml; in both cases: P = 0.99 (one-tailed testing), 1-β error probability = 0.7). The general upward trend was mainly accounted for by a negative association of irisin concentration with the storage duration of frozen serum samples (P < 0.01, β = -0.33). After arithmetically eliminating this confounder, the differences between groups remained non-significant. A training-induced increase in circulating irisin could not be confirmed, calling into question its proposed involvement in health-related training effects. Because frozen samples are prone to irisin degradation over time, positive results from uncontrolled trials might exclusively reflect the longer storage of samples from initial tests.

The Effect of Different Resistance Training Load Schemes on Strength and Body Composition in Trained Men

PubMed Central

Lopes, Charles Ricardo; Aoki, Marcelo Saldanha; Crisp, Alex Harley; de Mattos, Renê Scarpari; Lins, Miguel Alves; da Mota, Gustavo Ribeiro; Schoenfeld, Brad Jon; Marchetti, Paulo Henrique

2017-01-01

Abstract The purpose of this study was to evaluate the impact of moderate-load (10 RM) and low-load (20 RM) resistance training schemes on maximal strength and body composition. Sixteen resistance-trained men were randomly assigned to 1 of 2 groups: a moderate-load group (n = 8) or a low-load group (n = 8). The resistance training schemes consisted of 8 exercises performed 4 times per week for 6 weeks. In order to equate the number of repetitions performed by each group, the moderate load group performed 6 sets of 10 RM, while the low load group performed 3 sets of 20 RM. Between-group differences were evaluated using a 2-way ANOVA and independent t-tests. There was no difference in the weekly total load lifted (sets × reps × kg) between the 2 groups. Both groups equally improved maximal strength and measures of body composition after 6 weeks of resistance training, with no significant between-group differences detected. In conclusion, both moderate-load and low-load resistance training schemes, similar for the total load lifted, induced a similar improvement in maximal strength and body composition in resistance-trained men. PMID:28828088

Impact of relationships between test and training animals and among training animals on reliability of genomic prediction.

PubMed

Wu, X; Lund, M S; Sun, D; Zhang, Q; Su, G

2015-10-01

One of the factors affecting the reliability of genomic prediction is the relationship among the animals of interest. This study investigated the reliability of genomic prediction in various scenarios with regard to the relationship between test and training animals, and among animals within the training data set. Different training data sets were generated from EuroGenomics data and a group of Nordic Holstein bulls (born in 2005 and afterwards) as a common test data set. Genomic breeding values were predicted using a genomic best linear unbiased prediction model and a Bayesian mixture model. The results showed that a closer relationship between test and training animals led to a higher reliability of genomic predictions for the test animals, while a closer relationship among training animals resulted in a lower reliability. In addition, the Bayesian mixture model in general led to a slightly higher reliability of genomic prediction, especially for the scenario of distant relationships between training and test animals. Therefore, to prevent a decrease in reliability, constant updates of the training population with animals from more recent generations are required. Moreover, a training population consisting of less-related animals is favourable for reliability of genomic prediction. © 2015 Blackwell Verlag GmbH.

SU-E-E-05: Improving Contouring Precision and Consistency for Physicians-In-Training with Simple Lab Experiments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, L; Larson, D A

2015-06-15

Purpose: Target contouring for high-dose treatments such as radiosurgery of brain metastases is highly critical in eliminating marginal failure and reducing complications as shown by recent clinical studies. In order to improve contouring accuracy and practice consistency for the procedure, we introduced a self-assessed physics lab practice for the physicians-in-training. Methods: A set of commercially acquired high-precision PMMA plastic spheres were randomly embedded in a Styrofoam block and then scanned with the CT/MR via the clinical procedural imaging protocol. A group of first-year physicians-in-training (n=6) from either neurosurgery or radiation oncology department were asked to contour the scanned objects (diametermore » ranged from 0.4 cm to 3.8 cm). These user-defined contours were then compared with the ideal contour sets of object shape for self assessments to determine the maximum areas of the observed discrepancies and method of improvements. Results: The largest discrepancies from initial practice were consistently found to be located near the extreme longitudinal portions of the target for all the residents. Discrepancy was especially prominent when contouring small objects < 1.0 cm in diameters. For example, the mean volumes rendered from the initial contour data set differed from the ideal data set by 7.7%±6.6% for the participants (p> 0.23 suggesting agreement cannot be established). However, when incorporating a secondary imaging scan such as reconstructed coronal or sagittal images in a repeat practice, the agreement was dramatically improved yielding p<0.02 in agreement with the reference data set for all the participants. Conclusion: A simple physics lab revealed a common pitfall in contouring small metastatic brain tumors for radiosurgical procedures and provided a systematic tool for physicians-in-training in improving their clinical contouring skills. Dr Ma is current a board member of international stereotactic radiosurgical society.« less

Broadening Perspectives on Clinical Performance Assessment: Rethinking the Nature of In-Training Assessment

ERIC Educational Resources Information Center

Govaerts, Marjan J. B.; van der Vleuten, Cees P. M.; Schuwirth, Lambert W. T.; Muijtjens, Arno M. M.

2007-01-01

Context: In-training assessment (ITA), defined as multiple assessments of performance in the setting of day-to-day practice, is an invaluable tool in assessment programmes which aim to assess professional competence in a comprehensive and valid way. Research on clinical performance ratings, however, consistently shows weaknesses concerning…

Pre-Employment Laboratory Training. General Agricultural Mechanics Volume I. Instructional Materials.

ERIC Educational Resources Information Center

Texas A and M Univ., College Station. Vocational Instructional Services.

This course outline, the first volume of a two-volume set, consists of lesson plans for pre-employment laboratory training in general agricultural mechanics. Covered in the 12 lessons included in this volume are selecting tractors and engines, diagnosing engine conditions, servicing electrical systems, servicing cooling systems, servicing fuel and…

Practice Ethical Behavior. Work Maturity Skills. Competency 4.0.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. National Center for Research in Vocational Education.

Designed for use as a part of the Work Maturity Skills Training Program, this unit consists of instructional materials dealing with practicing ethical behavior. (The Work Maturity Skills Training Program is a set of individualized competency-based units that are designed to help participants develop the competencies they need to find and retain…

Pre-Employment Laboratory Training. General Agricultural Mechanics Volume II. Instructional Materials.

ERIC Educational Resources Information Center

Texas A and M Univ., College Station. Vocational Instructional Services.

This course outline, the second volume of a two-volume set, consists of lesson plans for pre-employment laboratory training in general agricultural mechanics. Covered in the eight lessons included in this volume are cold metal work, soldering, agricultural safety programs, farm shops, farm structures, farm and ranch electrification, soil and water…

Video Salient Object Detection via Fully Convolutional Networks.

PubMed

Wang, Wenguan; Shen, Jianbing; Shao, Ling

This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: 1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data and 2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further propose a novel data augmentation technique that simulates video training data from existing annotated image data sets, which enables our network to learn diverse saliency information and prevents overfitting with the limited number of training videos. Leveraging our synthetic video data (150K video sequences) and real videos, our deep video saliency model successfully learns both spatial and temporal saliency cues, thus producing accurate spatiotemporal saliency estimate. We advance the state-of-the-art on the densely annotated video segmentation data set (MAE of .06) and the Freiburg-Berkeley Motion Segmentation data set (MAE of .07), and do so with much improved speed (2 fps with all steps).This paper proposes a deep learning model to efficiently detect salient regions in videos. It addresses two important issues: 1) deep video saliency model training with the absence of sufficiently large and pixel-wise annotated video data and 2) fast video saliency training and detection. The proposed deep video saliency network consists of two modules, for capturing the spatial and temporal saliency information, respectively. The dynamic saliency model, explicitly incorporating saliency estimates from the static saliency model, directly produces spatiotemporal saliency inference without time-consuming optical flow computation. We further propose a novel data augmentation technique that simulates video training data from existing annotated image data sets, which enables our network to learn diverse saliency information and prevents overfitting with the limited number of training videos. Leveraging our synthetic video data (150K video sequences) and real videos, our deep video saliency model successfully learns both spatial and temporal saliency cues, thus producing accurate spatiotemporal saliency estimate. We advance the state-of-the-art on the densely annotated video segmentation data set (MAE of .06) and the Freiburg-Berkeley Motion Segmentation data set (MAE of .07), and do so with much improved speed (2 fps with all steps).

The 2-degree Field Lensing Survey: photometric redshifts from a large new training sample to r < 19.5

NASA Astrophysics Data System (ADS)

Wolf, C.; Johnson, A. S.; Bilicki, M.; Blake, C.; Amon, A.; Erben, T.; Glazebrook, K.; Heymans, C.; Hildebrandt, H.; Joudaki, S.; Klaes, D.; Kuijken, K.; Lidman, C.; Marin, F.; Parkinson, D.; Poole, G.

2017-04-01

We present a new training set for estimating empirical photometric redshifts of galaxies, which was created as part of the 2-degree Field Lensing Survey project. This training set is located in a ˜700 deg2 area of the Kilo-Degree-Survey South field and is randomly selected and nearly complete at r < 19.5. We investigate the photometric redshift performance obtained with ugriz photometry from VST-ATLAS and W1/W2 from WISE, based on several empirical and template methods. The best redshift errors are obtained with kernel-density estimation (KDE), as are the lowest biases, which are consistent with zero within statistical noise. The 68th percentiles of the redshift scatter for magnitude-limited samples at r < (15.5, 17.5, 19.5) are (0.014, 0.017, 0.028). In this magnitude range, there are no known ambiguities in the colour-redshift map, consistent with a small rate of redshift outliers. In the fainter regime, the KDE method produces p(z) estimates per galaxy that represent unbiased and accurate redshift frequency expectations. The p(z) sum over any subsample is consistent with the true redshift frequency plus Poisson noise. Further improvements in redshift precision at r < 20 would mostly be expected from filter sets with narrower passbands to increase the sensitivity of colours to small changes in redshift.

Manual cleaning of hospital mattresses: an observational study comparing high- and low-resource settings.

PubMed

Hopman, J; Hakizimana, B; Meintjes, W A J; Nillessen, M; de Both, E; Voss, A; Mehtar, S

2016-01-01

Hospital-associated infections (HAIs) are more frequently encountered in low- than in high-resource settings. There is a need to identify and implement feasible and sustainable approaches to strengthen HAI prevention in low-resource settings. To evaluate the biological contamination of routinely cleaned mattresses in both high- and low-resource settings. In this two-stage observational study, routine manual bed cleaning was evaluated at two university hospitals using adenosine triphosphate (ATP). Standardized training of cleaning personnel was achieved in both high- and low-resource settings. Qualitative analysis of the cleaning process was performed to identify predictors of cleaning outcome in low-resource settings. Mattresses in low-resource settings were highly contaminated prior to cleaning. Cleaning significantly reduced biological contamination of mattresses in low-resource settings (P < 0.0001). After training, the contamination observed after cleaning in both the high- and low-resource settings seemed comparable. Cleaning with appropriate type of cleaning materials reduced the contamination of mattresses adequately. Predictors for mattresses that remained contaminated in a low-resource setting included: type of product used, type of ward, training, and the level of contamination prior to cleaning. In low-resource settings mattresses were highly contaminated as noted by ATP levels. Routine manual cleaning by trained staff can be as effective in a low-resource setting as in a high-resource setting. We recommend a multi-modal cleaning strategy that consists of training of domestic services staff, availability of adequate time to clean beds between patients, and application of the correct type of cleaning products. Copyright © 2015 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

A novel classifier based on three preoperative tumor markers predicting the cancer-specific survival of gastric cancer (CEA, CA19-9 and CA72-4).

PubMed

Guo, Jing; Chen, Shangxiang; Li, Shun; Sun, Xiaowei; Li, Wei; Zhou, Zhiwei; Chen, Yingbo; Xu, Dazhi

2018-01-12

Several studies have highlighted the prognostic value of the individual and the various combinations of the tumor markers for gastric cancer (GC). Our study was designed to assess establish a new novel model incorporating carcino-embryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4). A total of 1,566 GC patients (Primary cohort) between Jan 2000 and July 2013 were analyzed. The Primary cohort was randomly divided into Training set (n=783) and Validation set (n=783). A three-tumor marker classifier was developed in the Training set and validated in the Validation set by multivariate regression and risk-score analysis. We have identified a three-tumor marker classifier (including CEA, CA19-9 and CA72-4) for the cancer specific survival (CSS) of GC (p<0.001). Consistent results were obtained in the both Training set and Validation set. Multivariate analysis showed that the classifier was an independent predictor of GC (All p value <0.001 in the Training set, Validation set and Primary cohort). Furthermore, when the leave-one-out approach was performed, the classifier showed superior predictive value to the individual or two of them (with the highest AUC (Area Under Curve); 0.618 for the Training set, and 0.625 for the Validation set), which ascertained its predictive value. Our three-tumor marker classifier is closely associated with the CSS of GC and may serve as a novel model for future decisions concerning treatments.

Cascade Back-Propagation Learning in Neural Networks

NASA Technical Reports Server (NTRS)

Duong, Tuan A.

2003-01-01

The cascade back-propagation (CBP) algorithm is the basis of a conceptual design for accelerating learning in artificial neural networks. The neural networks would be implemented as analog very-large-scale integrated (VLSI) circuits, and circuits to implement the CBP algorithm would be fabricated on the same VLSI circuit chips with the neural networks. Heretofore, artificial neural networks have learned slowly because it has been necessary to train them via software, for lack of a good on-chip learning technique. The CBP algorithm is an on-chip technique that provides for continuous learning in real time. Artificial neural networks are trained by example: A network is presented with training inputs for which the correct outputs are known, and the algorithm strives to adjust the weights of synaptic connections in the network to make the actual outputs approach the correct outputs. The input data are generally divided into three parts. Two of the parts, called the "training" and "cross-validation" sets, respectively, must be such that the corresponding input/output pairs are known. During training, the cross-validation set enables verification of the status of the input-to-output transformation learned by the network to avoid over-learning. The third part of the data, termed the "test" set, consists of the inputs that are required to be transformed into outputs; this set may or may not include the training set and/or the cross-validation set. Proposed neural-network circuitry for on-chip learning would be divided into two distinct networks; one for training and one for validation. Both networks would share the same synaptic weights.

Effect of core stability training on throwing velocity in female handball players.

PubMed

Saeterbakken, Atle H; van den Tillaar, Roland; Seiler, Stephen

2011-03-01

The purpose was to study the effect of a sling exercise training (SET)-based core stability program on maximal throwing velocity among female handball players. Twenty-four female high-school handball players (16.6 ± 0.3 years, 63 ± 6 kg, and 169 ± 7 cm) participated and were initially divided into a SET training group (n = 14) and a control group (CON, n = 10). Both groups performed their regular handball training for 6 weeks. In addition, twice a week, the SET group performed a progressive core stability-training program consisting of 6 unstable closed kinetic chain exercises. Maximal throwing velocity was measured before and after the training period using photocells. Maximal throwing velocity significantly increased 4.9% from 17.9 ± 0.5 to 18.8 ± 0.4 m·s in the SET group after the training period (p < 0.01), but was unchanged in the control group (17.1 ± 0.4 vs. 16.9 ± 0.4 m·s). These results suggest that core stability training using unstable, closed kinetic chain movements can significantly improve maximal throwing velocity. A stronger and more stable lumbopelvic-hip complex may contribute to higher rotational velocity in multisegmental movements. Strength coaches can incorporate exercises exposing the joints for destabilization force during training in closed kinetic chain exercises. This may encourage an effective neuromuscular pattern and increase force production and can improve a highly specific performance task such as throwing.

Fire Service Training. Rescue Practices. (Revised).

ERIC Educational Resources Information Center

North Carolina State Dept. of Community Colleges, Raleigh.

One of a set of fourteen instructional outlines for use in a course to train novice firemen, this guide covers the topic of rescue operations. Two types of rescue functions are recognized: the primary one consists of locating and saving trapped victims, and the secondary one of recovering bodies and making the area safe for other workers and…

Leaders and followers: quantifying consistency in spatio-temporal propagation patterns

NASA Astrophysics Data System (ADS)

Kreuz, Thomas; Satuvuori, Eero; Pofahl, Martin; Mulansky, Mario

2017-04-01

Repetitive spatio-temporal propagation patterns are encountered in fields as wide-ranging as climatology, social communication and network science. In neuroscience, perfectly consistent repetitions of the same global propagation pattern are called a synfire pattern. For any recording of sequences of discrete events (in neuroscience terminology: sets of spike trains) the questions arise how closely it resembles such a synfire pattern and which are the spike trains that lead/follow. Here we address these questions and introduce an algorithm built on two new indicators, termed SPIKE-order and spike train order, that define the synfire indicator value, which allows to sort multiple spike trains from leader to follower and to quantify the consistency of the temporal leader-follower relationships for both the original and the optimized sorting. We demonstrate our new approach using artificially generated datasets before we apply it to analyze the consistency of propagation patterns in two real datasets from neuroscience (giant depolarized potentials in mice slices) and climatology (El Niño sea surface temperature recordings). The new algorithm is distinguished by conceptual and practical simplicity, low computational cost, as well as flexibility and universality.

Detection of high-grade small bowel obstruction on conventional radiography with convolutional neural networks.

PubMed

Cheng, Phillip M; Tejura, Tapas K; Tran, Khoa N; Whang, Gilbert

2018-05-01

The purpose of this pilot study is to determine whether a deep convolutional neural network can be trained with limited image data to detect high-grade small bowel obstruction patterns on supine abdominal radiographs. Grayscale images from 3663 clinical supine abdominal radiographs were categorized into obstructive and non-obstructive categories independently by three abdominal radiologists, and the majority classification was used as ground truth; 74 images were found to be consistent with small bowel obstruction. Images were rescaled and randomized, with 2210 images constituting the training set (39 with small bowel obstruction) and 1453 images constituting the test set (35 with small bowel obstruction). Weight parameters for the final classification layer of the Inception v3 convolutional neural network, previously trained on the 2014 Large Scale Visual Recognition Challenge dataset, were retrained on the training set. After training, the neural network achieved an AUC of 0.84 on the test set (95% CI 0.78-0.89). At the maximum Youden index (sensitivity + specificity-1), the sensitivity of the system for small bowel obstruction is 83.8%, with a specificity of 68.1%. The results demonstrate that transfer learning with convolutional neural networks, even with limited training data, may be used to train a detector for high-grade small bowel obstruction gas patterns on supine radiographs.

A sustainable model for training teachers to use pivotal response training.

PubMed

Suhrheinrich, Jessica

2015-08-01

The increase in the rate of autism diagnoses has created a growing demand for teachers who are trained to use effective interventions. The train-the-trainer model, which involves training supervisors to train others, may be ideal for providing cost-effective training and ongoing support to teachers. Although research supports interventions, such as pivotal response training, as evidence-based, dissemination to school environments has been problematic. This study assessed the benefits of using the train-the-trainer model to disseminate pivotal response training to school settings. A multiple-baseline design was conducted across three training groups, each consisting of one school staff member (trainer), three special education teachers, and six students. Trainers conducted the teacher-training workshop with high adherence to training protocol and met mastery criteria in their ability to implement pivotal response training, assess implementation of pivotal response training, and provide feedback to teachers. Six of the nine teachers mastered all components of pivotal response training. The remaining three teachers implemented 89% of the pivotal response training components correctly. The majority of trainers and teachers maintained their abilities at follow-up. These results support the use of the train-the-trainer model as an effective method of disseminating evidence-based practices in school settings. © The Author(s) 2014.

Contour-based object orientation estimation

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel

2016-04-01

Real-time object orientation estimation is an actual problem of computer vision nowadays. In this paper we propose an approach to estimate an orientation of objects lacking axial symmetry. Proposed algorithm is intended to estimate orientation of a specific known 3D object, so 3D model is required for learning. The proposed orientation estimation algorithm consists of 2 stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. It minimizes the training image set. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy (mean error value less than 6°) in all case studies. The real-time performance of the algorithm was also demonstrated.

Charting a course to competency: an approach to mapping public health core competencies to existing trainings.

PubMed

Neiworth, Latrissa L; Allan, Susan; D'Ambrosio, Luann; Coplen-Abrahamson, Marlene

2014-03-01

Consistent with other professional fields, the goals of public health training have moved from a focus on knowledge transfer to the development of skills or competencies. At least six national competency sets have been developed in the past decade pertaining to public health professionals. State and local public health agencies are increasingly using competency sets as frameworks for staff development and assessment. Mapping competencies to training has potential for enhancing the value of public health training during resource-constrained times by directly linking training content to the desired skills. For existing public health trainings, the challenge is how to identify competencies addressed in those courses in a manner that is not burdensome and that produces valid results. This article describes a process for mapping competencies to the learning objectives, assignments, and assessments of existing trainings. The process presented could be used by any training center or organization that seeks to connect public health workforce competencies to previously developed instruction. Public health practice can be strengthened more effectively if trainings can be selected for the desired practice skills or competencies.

An automatic identification procedure to promote the use of FES-cycling training for hemiparetic patients.

PubMed

Ambrosini, Emilia; Ferrante, Simona; Schauer, Thomas; Ferrigno, Giancarlo; Molteni, Franco; Pedrocchi, Alessandra

2014-01-01

Cycling induced by Functional Electrical Stimulation (FES) training currently requires a manual setting of different parameters, which is a time-consuming and scarcely repeatable procedure. We proposed an automatic procedure for setting session-specific parameters optimized for hemiparetic patients. This procedure consisted of the identification of the stimulation strategy as the angular ranges during which FES drove the motion, the comparison between the identified strategy and the physiological muscular activation strategy, and the setting of the pulse amplitude and duration of each stimulated muscle. Preliminary trials on 10 healthy volunteers helped define the procedure. Feasibility tests on 8 hemiparetic patients (5 stroke, 3 traumatic brain injury) were performed. The procedure maximized the motor output within the tolerance constraint, identified a biomimetic strategy in 6 patients, and always lasted less than 5 minutes. Its reasonable duration and automatic nature make the procedure usable at the beginning of every training session, potentially enhancing the performance of FES-cycling training.

Massive-training support vector regression and Gaussian process for false-positive reduction in computer-aided detection of polyps in CT colonography

PubMed Central

Xu, Jian-Wu; Suzuki, Kenji

2011-01-01

Purpose: A massive-training artificial neural network (MTANN) has been developed for the reduction of false positives (FPs) in computer-aided detection (CADe) of polyps in CT colonography (CTC). A major limitation of the MTANN is the long training time. To address this issue, the authors investigated the feasibility of two state-of-the-art regression models, namely, support vector regression (SVR) and Gaussian process regression (GPR) models, in the massive-training framework and developed massive-training SVR (MTSVR) and massive-training GPR (MTGPR) for the reduction of FPs in CADe of polyps. Methods: The authors applied SVR and GPR as volume-processing techniques in the distinction of polyps from FP detections in a CTC CADe scheme. Unlike artificial neural networks (ANNs), both SVR and GPR are memory-based methods that store a part of or the entire training data for testing. Therefore, their training is generally fast and they are able to improve the efficiency of the massive-training methodology. Rooted in a maximum margin property, SVR offers excellent generalization ability and robustness to outliers. On the other hand, GPR approaches nonlinear regression from a Bayesian perspective, which produces both the optimal estimated function and the covariance associated with the estimation. Therefore, both SVR and GPR, as the state-of-the-art nonlinear regression models, are able to offer a performance comparable or potentially superior to that of ANN, with highly efficient training. Both MTSVR and MTGPR were trained directly with voxel values from CTC images. A 3D scoring method based on a 3D Gaussian weighting function was applied to the outputs of MTSVR and MTGPR for distinction between polyps and nonpolyps. To test the performance of the proposed models, the authors compared them to the original MTANN in the distinction between actual polyps and various types of FPs in terms of training time reduction and FP reduction performance. The authors’ CTC database consisted of 240 CTC data sets obtained from 120 patients in the supine and prone positions. The training set consisted of 27 patients, 10 of which had 10 polyps. The authors selected 10 nonpolyps (i.e., FP sources) from the training set. These ten polyps and ten nonpolyps were used for training the proposed models. The testing set consisted of 93 patients, including 19 polyps in 7 patients and 86 negative patients with 474 FPs produced by an original CADe scheme. Results: With the MTSVR, the training time was reduced by a factor of 190, while a FP reduction performance [by-polyp sensitivity of 94.7% (18∕19) with 2.5 (230∕93) FPs∕patient] comparable to that of the original MTANN [the same sensitivity with 2.6 (244∕93) FPs∕patient] was achieved. The classification performance in terms of the area under the receiver-operating-characteristic curve value of the MTGPR (0.82) was statistically significantly higher than that of the original MTANN (0.77), with a two-sided p-value of 0.03. The MTGPR yielded a 94.7% (18∕19) by-polyp sensitivity at a FP rate of 2.5 (235∕93) per patient and reduced the training time by a factor of 1.3. Conclusions: Both MTSVR and MTGPR improve the efficiency of the training in the massive-training framework while maintaining a comparable performance. PMID:21626922

Somatics in Action: How "I Feel Three-Dimensional and Real" Improves Dance Education and Training

ERIC Educational Resources Information Center

Kearns, Lauren W.

2010-01-01

The contemporary dance world, both in academic and professional settings, asks dancers to consistently engage with increasingly complex conceptual and physical dance work. Dancers in both settings must assimilate complex movement patterns, combine the technical nuances of multiple genres, reflect upon and critically assess their dancing, and…

The Influence of Art Expertise and Training on Emotion and Preference Ratings for Representational and Abstract Artworks

PubMed Central

van Paasschen, Jorien; Bacci, Francesca; Melcher, David P.

2015-01-01

Across cultures and throughout recorded history, humans have produced visual art. This raises the question of why people report such an emotional response to artworks and find some works more beautiful or compelling than others. In the current study we investigated the interplay between art expertise, and emotional and preference judgments. Sixty participants (40 novices, 20 art experts) rated a set of 150 abstract artworks and portraits during two occasions: in a laboratory setting and in a museum. Before commencing their second session, half of the art novices received a brief training on stylistic and art historical aspects of abstract art and portraiture. Results showed that art experts rated the artworks higher than novices on aesthetic facets (beauty and wanting), but no group differences were observed on affective evaluations (valence and arousal). The training session made a small effect on ratings of preference compared to the non-trained group of novices. Overall, these findings are consistent with the idea that affective components of art appreciation are less driven by expertise and largely consistent across observers, while more cognitive aspects of aesthetic viewing depend on viewer characteristics such as art expertise. PMID:26244368

The Influence of Art Expertise and Training on Emotion and Preference Ratings for Representational and Abstract Artworks.

PubMed

van Paasschen, Jorien; Bacci, Francesca; Melcher, David P

2015-01-01

Across cultures and throughout recorded history, humans have produced visual art. This raises the question of why people report such an emotional response to artworks and find some works more beautiful or compelling than others. In the current study we investigated the interplay between art expertise, and emotional and preference judgments. Sixty participants (40 novices, 20 art experts) rated a set of 150 abstract artworks and portraits during two occasions: in a laboratory setting and in a museum. Before commencing their second session, half of the art novices received a brief training on stylistic and art historical aspects of abstract art and portraiture. Results showed that art experts rated the artworks higher than novices on aesthetic facets (beauty and wanting), but no group differences were observed on affective evaluations (valence and arousal). The training session made a small effect on ratings of preference compared to the non-trained group of novices. Overall, these findings are consistent with the idea that affective components of art appreciation are less driven by expertise and largely consistent across observers, while more cognitive aspects of aesthetic viewing depend on viewer characteristics such as art expertise.

Academic requirements for Certificate of Completion of Training in surgical training: Consensus recommendations from the Association of Surgeons in Training/National Research Collaborative Consensus Group.

PubMed

Lee, Mathew J; Bhangu, A; Blencowe, Natalie S; Nepogodiev, D; Gokani, Vimal J; Harries, Rhiannon L; Akinfala, M; Ali, O; Allum, W; Bosanquet, D C; Boyce, K; Bradburn, M; Chapman, S J; Christopher, E; Coulter, I; Dean, B J F; Dickfos, M; El Boghdady, M; Elmasry, M; Fleming, S; Glasbey, J; Healy, C; Kasivisvanathan, V; Khan, K S; Kolias, A G; Lee, S M; Morton, D; O'Beirne, J; Sinclair, P; Sutton, P A

2016-11-01

Surgical trainees are expected to demonstrate academic achievement in order to obtain their certificate of completion of training (CCT). These standards are set by the Joint Committee on Surgical Training (JCST) and specialty advisory committees (SAC). The standards are not equivalent across all surgical specialties and recognise different achievements as evidence. They do not recognise changes in models of research and focus on outcomes rather than process. The Association of Surgeons in Training (ASiT) and National Research Collaborative (NRC) set out to develop progressive, consistent and flexible evidence set for academic requirements at CCT. A modified-Delphi approach was used. An expert group consisting of representatives from the ASiT and the NRC undertook iterative review of a document proposing changes to requirements. This was circulated amongst wider stakeholders. After ten iterations, an open meeting was held to discuss these proposals. Voting on statements was performed using a 5-point Likert Scale. Each statement was voted on twice, with ≥80% of votes in agreement meaning the statement was approved. The results of this vote were used to propose core and optional academic requirements for CCT. Online discussion concluded after ten rounds. At the consensus meeting, statements were voted on by 25 delegates from across surgical specialties and training-grades. The group strongly favoured acquisition of 'Good Clinical Practice' training and research methodology training as CCT requirements. The group agreed that higher degrees, publications in any author position (including collaborative authorship), recruiting patients to a study or multicentre audit and presentation at a national or international meeting could be used as evidence for the purpose of CCT. The group agreed on two essential 'core' requirements (GCP and methodology training) and two of a menu of four 'additional' requirements (publication with any authorship position, presentation, recruitment of patients to a multicentre study and completion of a higher degree), which should be completed in order to attain CCT. This approach has engaged stakeholders to produce a progressive set of academic requirements for CCT, which are applicable across surgical specialties. Flexibility in requirements whilst retaining a high standard of evidence is desirable. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

SU-F-T-450: The Investigation of Radiotherapy Quality Assurance and Automatic Treatment Planning Based On the Kernel Density Estimation Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, J; Fan, J; Hu, W

Purpose: To develop a fast automatic algorithm based on the two dimensional kernel density estimation (2D KDE) to predict the dose-volume histogram (DVH) which can be employed for the investigation of radiotherapy quality assurance and automatic treatment planning. Methods: We propose a machine learning method that uses previous treatment plans to predict the DVH. The key to the approach is the framing of DVH in a probabilistic setting. The training consists of estimating, from the patients in the training set, the joint probability distribution of the dose and the predictive features. The joint distribution provides an estimation of the conditionalmore » probability of the dose given the values of the predictive features. For the new patient, the prediction consists of estimating the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimation of the DVH. The 2D KDE is implemented to predict the joint probability distribution of the training set and the distribution of the predictive features for the new patient. Two variables, including the signed minimal distance from each OAR (organs at risk) voxel to the target boundary and its opening angle with respect to the origin of voxel coordinate, are considered as the predictive features to represent the OAR-target spatial relationship. The feasibility of our method has been demonstrated with the rectum, breast and head-and-neck cancer cases by comparing the predicted DVHs with the planned ones. Results: The consistent result has been found between these two DVHs for each cancer and the average of relative point-wise differences is about 5% within the clinical acceptable extent. Conclusion: According to the result of this study, our method can be used to predict the clinical acceptable DVH and has ability to evaluate the quality and consistency of the treatment planning.« less

Effect of strength training on regional hypertrophy of the elbow flexor muscles.

PubMed

Drummond, Marcos D M; Szmuchrowski, Leszek A; Goulart, Karine N O; Couto, Bruno P

2016-10-01

Muscle hypertrophy is the main structural adaptation to strength training. We investigated the chronic effects of strength training on muscle hypertrophy in different regions of the elbow flexor muscles. Eleven untrained men (21.8 ± 1.62 years) underwent magnetic resonance imaging to determine the proximal, medial, distal, and mean cross-sectional areas (CSA) of the elbow flexors. The volunteers completed 12 weeks of strength training. The training protocol consisted of 4 sets of 8-10 maximum repetitions of unilateral elbow flexion. The interval between sets was 120 s. The training frequency was 3 sessions per week. The magnetic resonance images verified the presence of significant and similar hypertrophy in the distal, medial, and proximal portions of the elbow flexor muscles. Muscle hypertrophy may be assessed using only the medial CSA. We should not expect different degrees of hypertrophy among the regions of the elbow flexor muscles. Muscle Nerve 54: 750-755, 2016. © 2016 Wiley Periodicals, Inc.

Exploring the limit of accuracy for density functionals based on the generalized gradient approximation: Local, global hybrid, and range-separated hybrid functionals with and without dispersion corrections

DOE PAGES

Mardirossian, Narbe; Head-Gordon, Martin

2014-03-25

The limit of accuracy for semi-empirical generalized gradient approximation (GGA) density functionals is explored in this paper by parameterizing a variety of local, global hybrid, and range-separated hybrid functionals. The training methodology employed differs from conventional approaches in 2 main ways: (1) Instead of uniformly truncating the exchange, same-spin correlation, and opposite-spin correlation functional inhomogeneity correction factors, all possible fits up to fourth order are considered, and (2) Instead of selecting the optimal functionals based solely on their training set performance, the fits are validated on an independent test set and ranked based on their overall performance on the trainingmore » and test sets. The 3 different methods of accounting for exchange are trained both with and without dispersion corrections (DFT-D2 and VV10), resulting in a total of 491 508 candidate functionals. For each of the 9 functional classes considered, the results illustrate the trade-off between improved training set performance and diminished transferability. Since all 491 508 functionals are uniformly trained and tested, this methodology allows the relative strengths of each type of functional to be consistently compared and contrasted. Finally, the range-separated hybrid GGA functional paired with the VV10 nonlocal correlation functional emerges as the most accurate form for the present training and test sets, which span thermochemical energy differences, reaction barriers, and intermolecular interactions involving lighter main group elements.« less

Training set optimization and classifier performance in a top-down diabetic retinopathy screening system

NASA Astrophysics Data System (ADS)

Wigdahl, J.; Agurto, C.; Murray, V.; Barriga, S.; Soliz, P.

2013-03-01

Diabetic retinopathy (DR) affects more than 4.4 million Americans age 40 and over. Automatic screening for DR has shown to be an efficient and cost-effective way to lower the burden on the healthcare system, by triaging diabetic patients and ensuring timely care for those presenting with DR. Several supervised algorithms have been developed to detect pathologies related to DR, but little work has been done in determining the size of the training set that optimizes an algorithm's performance. In this paper we analyze the effect of the training sample size on the performance of a top-down DR screening algorithm for different types of statistical classifiers. Results are based on partial least squares (PLS), support vector machines (SVM), k-nearest neighbor (kNN), and Naïve Bayes classifiers. Our dataset consisted of digital retinal images collected from a total of 745 cases (595 controls, 150 with DR). We varied the number of normal controls in the training set, while keeping the number of DR samples constant, and repeated the procedure 10 times using randomized training sets to avoid bias. Results show increasing performance in terms of area under the ROC curve (AUC) when the number of DR subjects in the training set increased, with similar trends for each of the classifiers. Of these, PLS and k-NN had the highest average AUC. Lower standard deviation and a flattening of the AUC curve gives evidence that there is a limit to the learning ability of the classifiers and an optimal number of cases to train on.

Acute Physiological Responses to Strongman Training Compared to Traditional Strength Training.

PubMed

Harris, Nigel K; Woulfe, Colm J; Wood, Matthew R; Dulson, Deborah K; Gluchowski, Ashley K; Keogh, Justin B

2016-05-01

Strongman training (ST) has become an increasingly popular modality, but data on physiological responses are limited. This study sought to determine physiological responses to an ST session compared to a traditional strength exercise training (RST) session. Ten healthy men (23.6 ± 27.5 years, 85.8 ± 10.3 kg) volunteered in a crossover design, where all participants performed an ST session, an RST session, and a resting session within 7 days apart. The ST consisted of sled drag, farmer's walk, 1 arm dumbbell clean and press, and tire flip at loads eliciting approximately 30 seconds of near maximal effort per set. The RST consisted of squat, deadlift, bench press, and power clean, progressing to 75% of 1 repetition maximum. Sessions were equated for approximate total set duration. Blood lactate and salivary testosterone were recorded immediately before and after training sessions. Heart rate, caloric expenditure, and substrate utilization were measured throughout the resting session, both training protocols and for 80 minutes after training sessions. Analyses were conducted to determine differences in physiological responses within and between protocols. No significant changes in testosterone occurred at any time point for either session. Lactate increased significantly immediately after both sessions. Heart rate, caloric expenditure, and substrate utilization were all elevated significantly during ST and RST. Heart rate and fat expenditure were significantly elevated compared to resting in both sessions' recovery periods; calorie and carbohydrate expenditures were not. Compared to RST, ST represents an equivalent physiological stimulus on key parameters indicative of potential training-induced adaptive responses. Such adaptations could conceivably include cardiovascular conditioning.

Rank Order Entropy: why one metric is not enough

PubMed Central

McLellan, Margaret R.; Ryan, M. Dominic; Breneman, Curt M.

2011-01-01

The use of Quantitative Structure-Activity Relationship models to address problems in drug discovery has a mixed history, generally resulting from the mis-application of QSAR models that were either poorly constructed or used outside of their domains of applicability. This situation has motivated the development of a variety of model performance metrics (r2, PRESS r2, F-tests, etc) designed to increase user confidence in the validity of QSAR predictions. In a typical workflow scenario, QSAR models are created and validated on training sets of molecules using metrics such as Leave-One-Out or many-fold cross-validation methods that attempt to assess their internal consistency. However, few current validation methods are designed to directly address the stability of QSAR predictions in response to changes in the information content of the training set. Since the main purpose of QSAR is to quickly and accurately estimate a property of interest for an untested set of molecules, it makes sense to have a means at hand to correctly set user expectations of model performance. In fact, the numerical value of a molecular prediction is often less important to the end user than knowing the rank order of that set of molecules according to their predicted endpoint values. Consequently, a means for characterizing the stability of predicted rank order is an important component of predictive QSAR. Unfortunately, none of the many validation metrics currently available directly measure the stability of rank order prediction, making the development of an additional metric that can quantify model stability a high priority. To address this need, this work examines the stabilities of QSAR rank order models created from representative data sets, descriptor sets, and modeling methods that were then assessed using Kendall Tau as a rank order metric, upon which the Shannon Entropy was evaluated as a means of quantifying rank-order stability. Random removal of data from the training set, also known as Data Truncation Analysis (DTA), was used as a means for systematically reducing the information content of each training set while examining both rank order performance and rank order stability in the face of training set data loss. The premise for DTA ROE model evaluation is that the response of a model to incremental loss of training information will be indicative of the quality and sufficiency of its training set, learning method, and descriptor types to cover a particular domain of applicability. This process is termed a “rank order entropy” evaluation, or ROE. By analogy with information theory, an unstable rank order model displays a high level of implicit entropy, while a QSAR rank order model which remains nearly unchanged during training set reductions would show low entropy. In this work, the ROE metric was applied to 71 data sets of different sizes, and was found to reveal more information about the behavior of the models than traditional metrics alone. Stable, or consistently performing models, did not necessarily predict rank order well. Models that performed well in rank order did not necessarily perform well in traditional metrics. In the end, it was shown that ROE metrics suggested that some QSAR models that are typically used should be discarded. ROE evaluation helps to discern which combinations of data set, descriptor set, and modeling methods lead to usable models in prioritization schemes, and provides confidence in the use of a particular model within a specific domain of applicability. PMID:21875058

"Functional" Inspiratory and Core Muscle Training Enhances Running Performance and Economy.

PubMed

Tong, Tomas K; McConnell, Alison K; Lin, Hua; Nie, Jinlei; Zhang, Haifeng; Wang, Jiayuan

2016-10-01

Tong, TK, McConnell, AK, Lin, H, Nie, J, Zhang, H, and Wang, J. "Functional" inspiratory and core muscle training enhances running performance and economy. J Strength Cond Res 30(10): 2942-2951, 2016-We compared the effects of two 6-week high-intensity interval training interventions. Under the control condition (CON), only interval training was undertaken, whereas under the intervention condition (ICT), interval training sessions were followed immediately by core training, which was combined with simultaneous inspiratory muscle training (IMT)-"functional" IMT. Sixteen recreational runners were allocated to either ICT or CON groups. Before the intervention phase, both groups undertook a 4-week program of "foundation" IMT to control for the known ergogenic effect of IMT (30 inspiratory efforts at 50% maximal static inspiratory pressure [P0] per set, 2 sets per day, 6 days per week). The subsequent 6-week interval running training phase consisted of 3-4 sessions per week. In addition, the ICT group undertook 4 inspiratory-loaded core exercises (10 repetitions per set, 2 sets per day, inspiratory load set at 50% post-IMT P0) immediately after each interval training session. The CON group received neither core training nor functional IMT. After the intervention phase, global inspiratory and core muscle functions increased in both groups (p ≤ 0.05), as evidenced by P0 and a sport-specific endurance plank test (SEPT) performance, respectively. Compared with CON, the ICT group showed larger improvements in SEPT, running economy at the speed of the onset of blood lactate accumulation, and 1-hour running performance (3.04% vs. 1.57%, p ≤ 0.05). The changes in these variables were interindividually correlated (r ≥ 0.57, n = 16, p ≤ 0.05). Such findings suggest that the addition of inspiratory-loaded core conditioning into a high-intensity interval training program augments the influence of the interval program on endurance running performance and that this may be underpinned by an improvement in running economy.

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 13: Laser Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 6: Welding, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 12: Instrumentation, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 5: Mold Making, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational speciality areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 3: Machining, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

The application of neural networks to the SSME startup transient

NASA Technical Reports Server (NTRS)

Meyer, Claudia M.; Maul, William A.

1991-01-01

Feedforward neural networks were used to model three parameters during the Space Shuttle Main Engine startup transient. The three parameters were the main combustion chamber pressure, a controlled parameter, the high pressure oxidizer turbine discharge temperature, a redlined parameter, and the high pressure fuel pump discharge pressure, a failure-indicating performance parameter. Network inputs consisted of time windows of data from engine measurements that correlated highly to the modeled parameter. A standard backpropagation algorithm was used to train the feedforward networks on two nominal firings. Each trained network was validated with four additional nominal firings. For all three parameters, the neural networks were able to accurately predict the data in the validation sets as well as the training set.

Quantifying natural delta variability using a multiple-point geostatistics prior uncertainty model

NASA Astrophysics Data System (ADS)

Scheidt, Céline; Fernandes, Anjali M.; Paola, Chris; Caers, Jef

2016-10-01

We address the question of quantifying uncertainty associated with autogenic pattern variability in a channelized transport system by means of a modern geostatistical method. This question has considerable relevance for practical subsurface applications as well, particularly those related to uncertainty quantification relying on Bayesian approaches. Specifically, we show how the autogenic variability in a laboratory experiment can be represented and reproduced by a multiple-point geostatistical prior uncertainty model. The latter geostatistical method requires selection of a limited set of training images from which a possibly infinite set of geostatistical model realizations, mimicking the training image patterns, can be generated. To that end, we investigate two methods to determine how many training images and what training images should be provided to reproduce natural autogenic variability. The first method relies on distance-based clustering of overhead snapshots of the experiment; the second method relies on a rate of change quantification by means of a computer vision algorithm termed the demon algorithm. We show quantitatively that with either training image selection method, we can statistically reproduce the natural variability of the delta formed in the experiment. In addition, we study the nature of the patterns represented in the set of training images as a representation of the "eigenpatterns" of the natural system. The eigenpattern in the training image sets display patterns consistent with previous physical interpretations of the fundamental modes of this type of delta system: a highly channelized, incisional mode; a poorly channelized, depositional mode; and an intermediate mode between the two.

Training artificial neural networks directly on the concordance index for censored data using genetic algorithms.

PubMed

Kalderstam, Jonas; Edén, Patrik; Bendahl, Pär-Ola; Strand, Carina; Fernö, Mårten; Ohlsson, Mattias

2013-06-01

The concordance index (c-index) is the standard way of evaluating the performance of prognostic models in the presence of censored data. Constructing prognostic models using artificial neural networks (ANNs) is commonly done by training on error functions which are modified versions of the c-index. Our objective was to demonstrate the capability of training directly on the c-index and to evaluate our approach compared to the Cox proportional hazards model. We constructed a prognostic model using an ensemble of ANNs which were trained using a genetic algorithm. The individual networks were trained on a non-linear artificial data set divided into a training and test set both of size 2000, where 50% of the data was censored. The ANNs were also trained on a data set consisting of 4042 patients treated for breast cancer spread over five different medical studies, 2/3 used for training and 1/3 used as a test set. A Cox model was also constructed on the same data in both cases. The two models' c-indices on the test sets were then compared. The ranking performance of the models is additionally presented visually using modified scatter plots. Cross validation on the cancer training set did not indicate any non-linear effects between the covariates. An ensemble of 30 ANNs with one hidden neuron was therefore used. The ANN model had almost the same c-index score as the Cox model (c-index=0.70 and 0.71, respectively) on the cancer test set. Both models identified similarly sized low risk groups with at most 10% false positives, 49 for the ANN model and 60 for the Cox model, but repeated bootstrap runs indicate that the difference was not significant. A significant difference could however be seen when applied on the non-linear synthetic data set. In that case the ANN ensemble managed to achieve a c-index score of 0.90 whereas the Cox model failed to distinguish itself from the random case (c-index=0.49). We have found empirical evidence that ensembles of ANN models can be optimized directly on the c-index. Comparison with a Cox model indicates that near identical performance is achieved on a real cancer data set while on a non-linear data set the ANN model is clearly superior. Copyright © 2013 Elsevier B.V. All rights reserved.

Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database

DOE Office of Scientific and Technical Information (OSTI.GOV)

Uehara, Takeki, E-mail: takeki.uehara@shionogi.co.jp; Toxicogenomics Informatics Project, National Institute of Biomedical Innovation, 7-6-8 Asagi, Ibaraki, Osaka 567-0085; Minowa, Yohsuke

2011-09-15

The present study was performed to develop a robust gene-based prediction model for early assessment of potential hepatocarcinogenicity of chemicals in rats by using our toxicogenomics database, TG-GATEs (Genomics-Assisted Toxicity Evaluation System developed by the Toxicogenomics Project in Japan). The positive training set consisted of high- or middle-dose groups that received 6 different non-genotoxic hepatocarcinogens during a 28-day period. The negative training set consisted of high- or middle-dose groups of 54 non-carcinogens. Support vector machine combined with wrapper-type gene selection algorithms was used for modeling. Consequently, our best classifier yielded prediction accuracies for hepatocarcinogenicity of 99% sensitivity and 97% specificitymore » in the training data set, and false positive prediction was almost completely eliminated. Pathway analysis of feature genes revealed that the mitogen-activated protein kinase p38- and phosphatidylinositol-3-kinase-centered interactome and the v-myc myelocytomatosis viral oncogene homolog-centered interactome were the 2 most significant networks. The usefulness and robustness of our predictor were further confirmed in an independent validation data set obtained from the public database. Interestingly, similar positive predictions were obtained in several genotoxic hepatocarcinogens as well as non-genotoxic hepatocarcinogens. These results indicate that the expression profiles of our newly selected candidate biomarker genes might be common characteristics in the early stage of carcinogenesis for both genotoxic and non-genotoxic carcinogens in the rat liver. Our toxicogenomic model might be useful for the prospective screening of hepatocarcinogenicity of compounds and prioritization of compounds for carcinogenicity testing. - Highlights: >We developed a toxicogenomic model to predict hepatocarcinogenicity of chemicals. >The optimized model consisting of 9 probes had 99% sensitivity and 97% specificity. >This model enables us to detect genotoxic as well as non-genotoxic hepatocarcinogens.« less

Do Pharmacological and Behavioral Interventions Differentially Affect Treatment Outcome for Children with Social Phobia?

ERIC Educational Resources Information Center

Scharfstein, Lindsay A.; Beidel, Deborah C.; Rendon Finnell, Laura; Distler, Aaron; Carter, Nathan T.

2011-01-01

In a randomized trial for children with social phobia (SP), Social Effectiveness Therapy for Children (SET-C; a treatment consisting of exposure and social skills training) and fluoxetine were more effective than pill placebo in reducing social distress and behavioral avoidance, but only SET-C demonstrated significantly improved overall social…

Consistent free energy landscapes and thermodynamic properties of small proteins based on a single all-atom force field employing an implicit solvation.

PubMed

Kim, Eunae; Jang, Soonmin; Pak, Youngshang

2007-10-14

We have attempted to improve the PARAM99 force field in conjunction with the generalized Born (GB) solvation model with a surface area correction for more consistent protein folding simulations. For this purpose, using an extended alphabeta training set of five well-studied molecules with various folds (alpha, beta, and betabetaalpha), a previously modified version of PARAM99/GBSA is further refined, such that all native states of the five training species correspond to their lowest free energy minimum states. The resulting modified force field (PARAM99MOD5/GBSA) clearly produces reasonably acceptable conformational free energy surfaces of the training set with correct identifications of their native states in the free energy minimum states. Moreover, due to its well-balanced nature, this new force field is expected to describe secondary structure propensities of diverse folds in a more consistent manner. Remarkably, temperature dependent behaviors simulated with the current force field are in good agreement with the experiment. This agreement is a significant improvement over the existing standard all-atom force fields. In addition, fundamentally important thermodynamic quantities, such as folding enthalpy (DeltaH) and entropy (DeltaS), agree reasonably well with the experimental data.

Automated video-based detection of nocturnal convulsive seizures in a residential care setting.

PubMed

Geertsema, Evelien E; Thijs, Roland D; Gutter, Therese; Vledder, Ben; Arends, Johan B; Leijten, Frans S; Visser, Gerhard H; Kalitzin, Stiliyan N

2018-06-01

People with epilepsy need assistance and are at risk of sudden death when having convulsive seizures (CS). Automated real-time seizure detection systems can help alert caregivers, but wearable sensors are not always tolerated. We determined algorithm settings and investigated detection performance of a video algorithm to detect CS in a residential care setting. The algorithm calculates power in the 2-6 Hz range relative to 0.5-12.5 Hz range in group velocity signals derived from video-sequence optical flow. A detection threshold was found using a training set consisting of video-electroencephalogaphy (EEG) recordings of 72 CS. A test set consisting of 24 full nights of 12 new subjects in residential care and additional recordings of 50 CS selected randomly was used to estimate performance. All data were analyzed retrospectively. The start and end of CS (generalized clonic and tonic-clonic seizures) and other seizures considered desirable to detect (long generalized tonic, hyperkinetic, and other major seizures) were annotated. The detection threshold was set to the value that obtained 97% sensitivity in the training set. Sensitivity, latency, and false detection rate (FDR) per night were calculated in the test set. A seizure was detected when the algorithm output exceeded the threshold continuously for 2 seconds. With the detection threshold determined in the training set, all CS were detected in the test set (100% sensitivity). Latency was ≤10 seconds in 78% of detections. Three/five hyperkinetic and 6/9 other major seizures were detected. Median FDR was 0.78 per night and no false detections occurred in 9/24 nights. Our algorithm could improve safety unobtrusively by automated real-time detection of CS in video registrations, with an acceptable latency and FDR. The algorithm can also detect some other motor seizures requiring assistance. © 2018 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

Observations of double layer-like and soliton-like structures in the ionosphere

NASA Technical Reports Server (NTRS)

Boehm, M. H.; Carlson, C. W.; Mcfadden, J.; Mozer, F. S.

1984-01-01

Two types of large electric field signatures, individual pulses and pulse trains, were observed on a sounding rocket launched into the afternoon auroral zone on January 21, 1982. The typical electric fields in the individual pulses were 50 mV/m or larger, aligned mostly parallel to B, and the corresponding potentials were at leat 100 mV (kT approximately 0.3 eV). A lower limit of 15 km/sec can be set on the velocity of these structures, indicating that they were not ion acoustic double layers. The pulse trains, each consisting of on the order of 100 pulses, were observed in close association with intense plasma frequency waves. This correlation is consistent with the interpretation of these trains as Langmuir solitons. The pulse trains correlate better with the intensity of the field-aligned currents than with the energetic electron flux.

Anomaly Detection Using an Ensemble of Feature Models

PubMed Central

Noto, Keith; Brodley, Carla; Slonim, Donna

2011-01-01

We present a new approach to semi-supervised anomaly detection. Given a set of training examples believed to come from the same distribution or class, the task is to learn a model that will be able to distinguish examples in the future that do not belong to the same class. Traditional approaches typically compare the position of a new data point to the set of “normal” training data points in a chosen representation of the feature space. For some data sets, the normal data may not have discernible positions in feature space, but do have consistent relationships among some features that fail to appear in the anomalous examples. Our approach learns to predict the values of training set features from the values of other features. After we have formed an ensemble of predictors, we apply this ensemble to new data points. To combine the contribution of each predictor in our ensemble, we have developed a novel, information-theoretic anomaly measure that our experimental results show selects against noisy and irrelevant features. Our results on 47 data sets show that for most data sets, this approach significantly improves performance over current state-of-the-art feature space distance and density-based approaches. PMID:22020249

Strength Gains by Motor Imagery with Different Ratios of Physical to Mental Practice

PubMed Central

Reiser, Mathias; Büsch, Dirk; Munzert, Jörn

2011-01-01

The purpose of this training study was to determine the magnitude of strength gains following a high-intensity resistance training (i.e., improvement of neuromuscular coordination) that can be achieved by imagery of the respective muscle contraction imagined maximal isometric contraction (IMC training). Prior to the experimental intervention, subjects completed a 4-week standardized strength training program. 3 groups with different combinations of real maximum voluntary contraction (MVC) and mental (IMC) strength training (M75, M50, M25; numbers indicate percentages of mental trials) were compared to a MVC-only training group (M0) and a control condition without strength training (CO). Training sessions (altogether 12) consisted of four sets of two maximal 5-s isometric contractions with 10 s rest between sets of either MVC or IMC training. Task-specific effects of IMC training were tested in four strength exercises commonly used in practical settings (bench pressing, leg pressing, triceps extension, and calf raising). Maximum isometric voluntary contraction force (MVC) was measured before and after the experimental training intervention and again 1 week after cessation of the program. IMC groups (M25, M50, M75) showed slightly smaller increases in MVC (3.0% to 4.2%) than M0 (5.1%), but significantly stronger improvements than CO (−0.2%). Compared to further strength gains in M0 after 1 week (9.4% altogether), IMC groups showed no “delayed” improvement, but the attained training effects remained stable. It is concluded that high-intensity strength training sessions can be partly replaced by IMC training sessions without any considerable reduction of strength gains. PMID:21897826

Improving machine learning reproducibility in genetic association studies with proportional instance cross validation (PICV).

PubMed

Piette, Elizabeth R; Moore, Jason H

2018-01-01

Machine learning methods and conventions are increasingly employed for the analysis of large, complex biomedical data sets, including genome-wide association studies (GWAS). Reproducibility of machine learning analyses of GWAS can be hampered by biological and statistical factors, particularly so for the investigation of non-additive genetic interactions. Application of traditional cross validation to a GWAS data set may result in poor consistency between the training and testing data set splits due to an imbalance of the interaction genotypes relative to the data as a whole. We propose a new cross validation method, proportional instance cross validation (PICV), that preserves the original distribution of an independent variable when splitting the data set into training and testing partitions. We apply PICV to simulated GWAS data with epistatic interactions of varying minor allele frequencies and prevalences and compare performance to that of a traditional cross validation procedure in which individuals are randomly allocated to training and testing partitions. Sensitivity and positive predictive value are significantly improved across all tested scenarios for PICV compared to traditional cross validation. We also apply PICV to GWAS data from a study of primary open-angle glaucoma to investigate a previously-reported interaction, which fails to significantly replicate; PICV however improves the consistency of testing and training results. Application of traditional machine learning procedures to biomedical data may require modifications to better suit intrinsic characteristics of the data, such as the potential for highly imbalanced genotype distributions in the case of epistasis detection. The reproducibility of genetic interaction findings can be improved by considering this variable imbalance in cross validation implementation, such as with PICV. This approach may be extended to problems in other domains in which imbalanced variable distributions are a concern.

Design of a Functional Training Prototype for Neonatal Resuscitation

PubMed Central

Rajaraman, Sivaramakrishnan; Ganesan, Sona; Jayapal, Kavitha; Kannan, Sadhani

2014-01-01

Birth Asphyxia is considered to be one of the leading causes of neonatal mortality around the world. Asphyxiated neonates require skilled resuscitation to survive the neonatal period. The project aims to train health professionals in a basic newborn care using a prototype with an ultimate objective to have one person at every delivery trained in neonatal resuscitation. This prototype will be a user-friendly device with which one can get trained in performing neonatal resuscitation in resource-limited settings. The prototype consists of a Force Sensing Resistor (FSR) that measures the pressure applied and is interfaced with Arduino® which controls the Liquid Crystal Display (LCD) and Light Emitting Diode (LED) indication for pressure and compression counts. With the increase in population and absence of proper medical care, the need for neonatal resuscitation program is not well addressed. The proposed work aims at offering a promising solution for training health care individuals on resuscitating newborn babies under low resource settings. PMID:27417489

Flexible workspace design and ergonomics training: impacts on the psychosocial work environment, musculoskeletal health, and work effectiveness among knowledge workers.

PubMed

Robertson, Michelle M; Huang, Yueng-Hsiang; O'Neill, Michael J; Schleifer, Lawrence M

2008-07-01

A macroergonomics intervention consisting of flexible workspace design and ergonomics training was conducted to examine the effects on psychosocial work environment, musculoskeletal health, and work effectiveness in a computer-based office setting. Knowledge workers were assigned to one of four conditions: flexible workspace (n=121), ergonomics training (n=92), flexible workspace+ergonomics training (n=31), and a no-intervention control (n=45). Outcome measures were collected 2 months prior to the intervention and 3 and 6 months post-intervention. Overall, the study results indicated positive, significant effects on the outcome variables for the two intervention groups compared to the control group, including work-related musculoskeletal discomfort, job control, environmental satisfaction, sense of community, ergonomic climate, communication and collaboration, and business process efficiency (time and costs). However, attrition of workers in the ergonomics training condition precluded an evaluation of the effects of this intervention. This study suggests that a macroergonomics intervention is effective among knowledge workers in office settings.

A pilot study of the efficacy of a computerized executive functioning remediation training with game elements for children with ADHD in an outpatient setting: outcome on parent- and teacher-rated executive functioning and ADHD behavior.

PubMed

van der Oord, S; Ponsioen, A J G B; Geurts, H M; Ten Brink, E L; Prins, P J M

2014-11-01

This pilot study tested the short- and long-term efficacy (9 weeks follow-up) of an executive functioning (EF) remediation training with game elements for children with ADHD in an outpatient clinical setting, using a randomized controlled wait-list design. Furthermore, in a subsample, that is, those treated with methylphenidate, additive effects of the EF training were assessed. A total of 40 children (aged 8-12 years) were randomized to the EF training or wait-list. The training consisted of a 25-session training of inhibition, cognitive flexibility, and working memory. Treatment outcome was assessed by parent- and teacher-rated EF, ADHD, oppositional deviant disorder, and conduct disorder symptoms. Children in the EF training showed significantly more improvement than those in the wait-list condition on parent-rated EF and ADHD behavior in the total sample and in the subsample treated with methylphenidate. Effects were maintained at follow-up. This pilot study shows promising evidence for the efficacy of an EF training with game elements. © 2012 SAGE Publications.

Sea ice classification using fast learning neural networks

NASA Technical Reports Server (NTRS)

Dawson, M. S.; Fung, A. K.; Manry, M. T.

1992-01-01

A first learning neural network approach to the classification of sea ice is presented. The fast learning (FL) neural network and a multilayer perceptron (MLP) trained with backpropagation learning (BP network) were tested on simulated data sets based on the known dominant scattering characteristics of the target class. Four classes were used in the data simulation: open water, thick lossy saline ice, thin saline ice, and multiyear ice. The BP network was unable to consistently converge to less than 25 percent error while the FL method yielded an average error of approximately 1 percent on the first iteration of training. The fast learning method presented can significantly reduce the CPU time necessary to train a neural network as well as consistently yield higher classification accuracy than BP networks.

Sensory stimulation augments the effects of massed practice training in persons with tetraplegia.

PubMed

Beekhuizen, Kristina S; Field-Fote, Edelle C

2008-04-01

To compare functional changes and cortical neuroplasticity associated with hand and upper extremity use after massed (repetitive task-oriented practice) training, somatosensory stimulation, massed practice training combined with somatosensory stimulation, or no intervention, in persons with chronic incomplete tetraplegia. Participants were randomly assigned to 1 of 4 groups: massed practice training combined with somatosensory peripheral nerve stimulation (MP+SS), somatosensory peripheral nerve stimulation only (SS), massed practice training only (MP), and no intervention (control). University medical school setting. Twenty-four subjects with chronic incomplete tetraplegia. Intervention sessions were 2 hours per session, 5 days a week for 3 weeks. Massed practice training consisted of repetitive practice of functional tasks requiring skilled hand and upper-extremity use. Somatosensory stimulation consisted of median nerve stimulation with intensity set below motor threshold. Pre- and post-testing assessed changes in functional hand use (Jebsen-Taylor Hand Function Test), functional upper-extremity use (Wolf Motor Function Test), pinch grip strength (key pinch force), sensory function (monofilament testing), and changes in cortical excitation (motor evoked potential threshold). The 3 groups showed significant improvements in hand function after training. The MP+SS and SS groups had significant improvements in upper-extremity function and pinch strength compared with the control group, but only the MP+SS group had a significant change in sensory scores compared with the control group. The MP+SS and MP groups had greater change in threshold measures of cortical excitability. People with chronic incomplete tetraplegia obtain functional benefits from massed practice of task-oriented skills. Somatosensory stimulation appears to be a valuable adjunct to training programs designed to improve hand and upper-extremity function in these subjects.

Adaptations to Speed Endurance Training in Highly Trained Soccer Players.

PubMed

Nyberg, Michael; Fiorenza, Matteo; Lund, Anders; Christensen, Magnus; Rømer, Tue; Piil, Peter; Hostrup, Morten; Christensen, Peter M; Holbek, Simon; Ravnholt, Thomas; Gunnarsson, Thomas P; Bangsbo, Jens

2016-07-01

The present study examined whether a period of additional speed endurance training would improve intense intermittent exercise performance in highly trained soccer players during the season and whether the training changed aerobic metabolism and the level of oxidative enzymes in type I and type II muscle fibers. During the last 9 wk of the season, 13 semiprofessional soccer players performed additional speed endurance training sessions consisting of two to three sets of 8-10 repetitions of 30-m sprints with 10 s of passive recovery (SET). Before and after SET, subjects completed a double-step exercise protocol that included transitions from standing to moderate-intensity running (~75% HRmax), followed by transitions from moderate- to high-intensity running (~90% HRmax) in which pulmonary oxygen uptake (V˙O2) was determined. In addition, the yo-yo intermittent recovery test level 1 was performed, and a muscle biopsy was obtained at rest. The yo-yo intermittent recovery test level 1 performance was 11.6% ± 6.4% (mean ± SD) better (2803 ± 330 vs 3127 ± 383 m, P < 0.05) after SET compared with before SET. In the transition from standing to moderate-intensity running, phase II pulmonary V˙O2 kinetics was 11.4% ± 16.5% faster (P < 0.05), and the running economy at this intensity was 2.3% ± 3.0% better (P < 0.05). These improvements were apparent despite the content of muscle proteins regulating oxidative metabolism (3-hydroxyacyl CoA dehydrogenase, COX IV, and OXPHOS), and capillarization was reduced (P < 0.05). The content of 3-hydroxyacyl CoA dehydrogenase and citrate synthase in type I and type II fibers did not change. In highly trained soccer players, additional speed endurance training is associated with an improved ability to perform repeated high-intensity work. To what extent the training-induced changes in V˙O2 kinetics and mechanical efficiency in type I fibers caused the improvement in performance warrants further investigation.

Creating Online Training for Procedures in Global Health with PEARLS (Procedural Education for Adaptation to Resource-Limited Settings).

PubMed

Bensman, Rachel S; Slusher, Tina M; Butteris, Sabrina M; Pitt, Michael B; On Behalf Of The Sugar Pearls Investigators; Becker, Amanda; Desai, Brinda; George, Alisha; Hagen, Scott; Kiragu, Andrew; Johannsen, Ron; Miller, Kathleen; Rule, Amy; Webber, Sarah

2017-11-01

The authors describe a multiinstitutional collaborative project to address a gap in global health training by creating a free online platform to share a curriculum for performing procedures in resource-limited settings. This curriculum called PEARLS (Procedural Education for Adaptation to Resource-Limited Settings) consists of peer-reviewed instructional and demonstration videos describing modifications for performing common pediatric procedures in resource-limited settings. Adaptations range from the creation of a low-cost spacer for inhaled medications to a suction chamber for continued evacuation of a chest tube. By describing the collaborative process, we provide a model for educators in other fields to collate and disseminate procedural modifications adapted for their own specialty and location, ideally expanding this crowd-sourced curriculum to reach a wide audience of trainees and providers in global health.

Local or global? How to choose the training set for principal component compression of hyperspectral satellite measurements: a hybrid approach

NASA Astrophysics Data System (ADS)

Hultberg, Tim; August, Thomas; Lenti, Flavia

2017-09-01

Principal Component (PC) compression is the method of choice to achieve band-width reduction for dissemination of hyper spectral (HS) satellite measurements and will become increasingly important with the advent of future HS missions (such as IASI-NG and MTG-IRS) with ever higher data-rates. It is a linear transformation defined by a truncated set of the leading eigenvectors of the covariance of the measurements as well as the mean of the measurements. We discuss the strategy for generation of the eigenvectors, based on the operational experience made with IASI. To compute the covariance and mean, a so-called training set of measurements is needed, which ideally should include all relevant spectral features. For the dissemination of IASI PC scores a global static training set consisting of a large sample of measured spectra covering all seasons and all regions is used. This training set was updated once after the start of the dissemination of IASI PC scores in April 2010 by adding spectra from the 2010 Russian wildfires, in which spectral features not captured by the previous training set were identified. An alternative approach, which has sometimes been proposed, is to compute the eigenvectors on the fly from a local training set, for example consisting of all measurements in the current processing granule. It might naively be thought that this local approach would improve the compression rate by reducing the number of PC scores needed to represent the measurements within each granule. This false belief is apparently confirmed, if the reconstruction scores (root mean square of the reconstruction residuals) is used as the sole criteria for choosing the number of PC scores to retain, which would overlook the fact that the decrease in reconstruction score (for the same number of PCs) is achieved only by the retention of an increased amount of random noise. We demonstrate that the local eigenvectors retain a higher amount of noise and a lower amount of atmospheric signal than global eigenvectors. Local eigenvectors do not increase the compression rate, but increase the amount of atmospheric loss and should be avoided. Only extremely rare situations, resulting in spectra with features which have not been observed previously, can lead to problems for the global approach. To cope with such situations we investigate a hybrid approach, which first apply the global eigenvectors and then apply local compression to the residuals in order to identify and disseminate in addition any directions in the local signal, which are orthogonal to the subspace spanned by the global eigenvectors.

Building an evidence-base for the training of evidence-based treatments in community settings: Use of an expert-informed approach.

PubMed

Scudder, Ashley; Herschell, Amy D

2015-08-01

In order to make EBTs available to a large number of children and families, developers and expert therapists have used their experience and expertise to train community-based therapists in EBTs. Understanding current training practices of treatment experts may be one method for establishing best practices for training community-based therapists prior to comprehensive empirical examinations of training practices. A qualitative study was conducted using surveys and phone interviews to identify the specific procedures used by treatment experts to train and implement an evidence-based treatment in community settings. Twenty-three doctoral-level, clinical psychologists were identified to participate because of their expertise in conducting and training Parent-Child Interaction Therapy. Semi-structured qualitative interviews were completed by phone, later transcribed verbatim, and analyzed using thematic coding. The de-identified data were coded by two independent qualitative data researchers and then compared for consistency of interpretation. The themes that emerged following the final coding were used to construct a training protocol to be empirically tested. The goal of this paper is to not only understand the current state of training practices for training therapists in a particular EBT, Parent-Child Interaction Therapy, but to illustrate the use of expert opinion as the best available evidence in preparation for empirical evaluation.

General practice--reflection on five years of multidisciplinary training at Medical Centre Gütersloh.

PubMed

van den Heuvel, H G J

2011-12-01

Medical Centre Gütersloh is a primary care setting which provides the full range of general practice care for British Forces Germany Health Service (BFG HS). The aim of this article is to evaluate the multidisciplinary training organised by the author there, to exchange information and to provide suggestions for improvement and development. Description of the training scheme and analysis of routinely collected management data. The training scheme is based on adult education principles with a focus on interactive learning. Over the period November 2005-July 2010 a total of 1201 members of staff from various disciplines participated in 86 documented training sessions. The majority of the attending staff considered the training to be relevant, interesting and well presented. A substantial proportion indicated that they would change their practice as a result of the training. These views remained stable over time. The majority of facilitators consisted of medical centre employees. This article provides an overview onfive years of multidisciplinary training in a general practice setting. Overall feedback from staff suggests that the training has been highly valued over those years. However, it is recognised that this evaluation has its limitations and suggestions are made regarding how these types of training schemes can be improved and developed further.

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 9: Tool and Die, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 8: Sheet Metal & Composites, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 4: Manufacturing Engineering Technology, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 14: Automated Equipment Technician (CIM), of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 10: Computer-Aided Drafting & Design, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 11: Computer-Aided Manufacturing & Advanced CNC, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 2: Career Development, General Education and Remediation, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Machine Tool Advanced Skills Technology (MAST). Common Ground: Toward a Standards-Based Training System for the U.S. Machine Tool and Metal Related Industries. Volume 7: Industrial Maintenance Technology, of a 15-Volume Set of Skill Standards and Curriculum Training Materials for the Precision Manufacturing Industry.

ERIC Educational Resources Information Center

Texas State Technical Coll., Waco.

This document is intended to help education and training institutions deliver the Machine Tool Advanced Skills Technology (MAST) curriculum to a variety of individuals and organizations. MAST consists of industry-specific skill standards and model curricula for 15 occupational specialty areas within the U.S. machine tool and metals-related…

Training US health care professionals on human trafficking: where do we go from here?

PubMed Central

Powell, Clydette; Dickins, Kirsten; Stoklosa, Hanni

2017-01-01

ABSTRACT Some 21 million adults and children are labor-trafficked or sex-trafficked through force, fraud, or coercion. In recognition of the interface between trafficking victims and the healthcare setting, over the last 10 years there has been a notable increase in training of health care professionals (HCPs) on human trafficking (HT) and its health implications. Many organizations have developed curricula and offered training in various clinical settings. However, methods and content of this education on trafficking vary widely, and there is little evaluation of the impact of the training. The goal of this study was to assess the gaps and strengths in HT education of HCPs in the US. This mixed-method study had two components. The first component consisted of structured interviews with experts in human trafficking HCP education. The second portion of the study involved an analysis of data from HCP calls to the National Human Trafficking Resource Center (NHTRC). The interviews captured trainer-specific data on types of HT training, duration and frequency, key content areas, presence of evaluation approaches and indicators, as well as an assessment of barriers and strengths in HT training for HCP. NHTRC call database analysis demonstrated increasing trends since 2008 in calls by HCPs. Overall findings revealed the need for standardization of HT training content to assure correct information, trauma-informed and patient-centered care, and consistent messaging for HCPs. Evaluation metrics for HT training need to be developed to demonstrate behavior change and impact on service delivery and patient-centered outcomes for HT victims, according to our proposed adapted Kirkpatrick’s Pyramid model. HT training and evaluation would benefit from an agency or institution at the national level to provide consistency and standardization of HT training content as well as to guide a process that would develop metrics for evaluation and the building of an evidence base. Abbreviations: AAP: American Academy of Pediatrics; ACF: Administration for Children and Families; CME: Continuing medical education; ED: Emergency department; HCP: Health care professional; HEAL: Health, Education, Advocacy, and Linkage; HHS: United States Department of Health and Human Services; HT: Human trafficking; IOM: United States Institute of Medicine; MH: Mental health; NHTRC: National Human Trafficking Resource Center; SOAR: Stop, Observe, Ask, and Respond to Health and Wellness Training PMID:28178913

Training US health care professionals on human trafficking: where do we go from here?

PubMed

Powell, Clydette; Dickins, Kirsten; Stoklosa, Hanni

2017-01-01

Some 21 million adults and children are labor-trafficked or sex-trafficked through force, fraud, or coercion. In recognition of the interface between trafficking victims and the healthcare setting, over the last 10 years there has been a notable increase in training of health care professionals (HCPs) on human trafficking (HT) and its health implications. Many organizations have developed curricula and offered training in various clinical settings. However, methods and content of this education on trafficking vary widely, and there is little evaluation of the impact of the training. The goal of this study was to assess the gaps and strengths in HT education of HCPs in the US. This mixed-method study had two components. The first component consisted of structured interviews with experts in human trafficking HCP education. The second portion of the study involved an analysis of data from HCP calls to the National Human Trafficking Resource Center (NHTRC). The interviews captured trainer-specific data on types of HT training, duration and frequency, key content areas, presence of evaluation approaches and indicators, as well as an assessment of barriers and strengths in HT training for HCP. NHTRC call database analysis demonstrated increasing trends since 2008 in calls by HCPs. Overall findings revealed the need for standardization of HT training content to assure correct information, trauma-informed and patient-centered care, and consistent messaging for HCPs. Evaluation metrics for HT training need to be developed to demonstrate behavior change and impact on service delivery and patient-centered outcomes for HT victims, according to our proposed adapted Kirkpatrick's Pyramid model. HT training and evaluation would benefit from an agency or institution at the national level to provide consistency and standardization of HT training content as well as to guide a process that would develop metrics for evaluation and the building of an evidence base. AAP: American Academy of Pediatrics; ACF: Administration for Children and Families; CME: Continuing medical education; ED: Emergency department; HCP: Health care professional; HEAL: Health, Education, Advocacy, and Linkage; HHS: United States Department of Health and Human Services; HT: Human trafficking; IOM: United States Institute of Medicine; MH: Mental health; NHTRC: National Human Trafficking Resource Center; SOAR: Stop, Observe, Ask, and Respond to Health and Wellness Training.

Automatic Train Operation Using Autonomic Prediction of Train Runs

NASA Astrophysics Data System (ADS)

Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo

In this paper, we present an automatic train control method adaptable to disturbed train traffic conditions. The proposed method presumes transmission of detected time of a home track clearance to trains approaching to the station by employing equipment of Digital ATC (Automatic Train Control). Using the information, each train controls its acceleration by the method that consists of two approaches. First, by setting a designated restricted speed, the train controls its running time to arrive at the next station in accordance with predicted delay. Second, the train predicts the time at which it will reach the current braking pattern generated by Digital ATC, along with the time when the braking pattern transits ahead. By comparing them, the train correctly chooses the coasting drive mode in advance to avoid deceleration due to the current braking pattern. We evaluated the effectiveness of the proposed method regarding driving conditions, energy consumption and reduction of delays by simulation.

Individualised training to address variability of radiologists' performance

NASA Astrophysics Data System (ADS)

Sun, Shanghua; Taylor, Paul; Wilkinson, Louise; Khoo, Lisanne

2008-03-01

Computer-based tools are increasingly used for training and the continuing professional development of radiologists. We propose an adaptive training system to support individualised learning in mammography, based on a set of real cases, which are annotated with educational content by experienced breast radiologists. The system has knowledge of the strengths and weakness of each radiologist's performance: each radiologist is assessed to compute a profile showing how they perform on different sets of cases, classified by type of abnormality, breast density, and perceptual difficulty. We also assess variability in cognitive aspects of image perception, classifying errors made by radiologists as errors of search, recognition or decision. This is a novel element in our approach. The profile is used to select cases to present to the radiologist. The intelligent and flexible presentation of these cases distinguishes our system from existing training tools. The training cases are organised and indexed by an ontology we have developed for breast radiologist training, which is consistent with the radiologists' profile. Hence, the training system is able to select appropriate cases to compose an individualised training path, addressing the variability of the radiologists' performance. A substantial part of the system, the ontology has been evaluated on a large number of cases, and the training system is under implementation for further evaluation.

Automating the training development process for mission flight operations

NASA Technical Reports Server (NTRS)

Scott, Carol J.

1994-01-01

Traditional methods of developing training do not effectively support the changing needs of operational users in a multimission environment. The Automated Training Development System (ATDS) provides advantages over conventional methods in quality, quantity, turnaround, database maintenance, and focus on individualized instruction. The Operations System Training Group at the JPL performed a six-month study to assess the potential of ATDS to automate curriculum development and to generate and maintain course materials. To begin the study, the group acquired readily available hardware and participated in a two-week training session to introduce the process. ATDS is a building activity that combines training's traditional information-gathering with a hierarchical method for interleaving the elements. The program can be described fairly simply. A comprehensive list of candidate tasks determines the content of the database; from that database, selected critical tasks dictate which competencies of skill and knowledge to include in course material for the target audience. The training developer adds pertinent planning information about each task to the database, then ATDS generates a tailored set of instructional material, based on the specific set of selection criteria. Course material consistently leads students to a prescribed level of competency.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (T{sub p}:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed amore » new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.« less

Developing a virtual reality application for training nuclear power plant operators: setting up a database containing dose rates in the refuelling plant.

PubMed

Ródenas, J; Zarza, I; Burgos, M C; Felipe, A; Sánchez-Mayoral, M L

2004-01-01

Operators in Nuclear Power Plants can receive high doses during refuelling operations. A training programme for simulating refuelling operations will be useful in reducing the doses received by workers as well as minimising operation time. With this goal in mind, a virtual reality application is developed within the framework of the CIPRES project. The application requires doses, both instantaneous and accumulated, to be displayed at all times during operator training. Therefore, it is necessary to set up a database containing dose rates at every point in the refuelling plant. This database is based on radiological protection surveillance data measured in the plant during refuelling operations. Some interpolation routines have been used to estimate doses through the refuelling plant. Different assumptions have been adopted in order to perform the interpolation and obtain consistent data. In this paper, the procedures developed to set up the dose database for the virtual reality application are presented and analysed.

Computing single step operators of logic programming in radial basis function neural networks

NASA Astrophysics Data System (ADS)

Hamadneh, Nawaf; Sathasivam, Saratha; Choon, Ong Hong

2014-07-01

Logic programming is the process that leads from an original formulation of a computing problem to executable programs. A normal logic program consists of a finite set of clauses. A valuation I of logic programming is a mapping from ground atoms to false or true. The single step operator of any logic programming is defined as a function (Tp:I→I). Logic programming is well-suited to building the artificial intelligence systems. In this study, we established a new technique to compute the single step operators of logic programming in the radial basis function neural networks. To do that, we proposed a new technique to generate the training data sets of single step operators. The training data sets are used to build the neural networks. We used the recurrent radial basis function neural networks to get to the steady state (the fixed point of the operators). To improve the performance of the neural networks, we used the particle swarm optimization algorithm to train the networks.

Quality and Diversity in VET [Vocational Education and Training] Research. Proceedings of the National Conference of the Australian Vocational Education and Training Research Association (AVETRA) (2nd, Melbourne, Australia, February 11-12, 1999).

ERIC Educational Resources Information Center

Australian Vocational Education and Training Research Association, Alexandria.

These proceedings consist of 43 presentations clustered into these key areas: position, strategy, contribution, and future issues; diversity of participation and contexts; issues in the workplace and learning settings; question of practitioners work; and questions of knowledge and methodology--all related to the themes of quality and diversity.…

Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules.

PubMed

Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

2018-02-05

This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules

NASA Astrophysics Data System (ADS)

Gong, Jing; Liu, Ji-Yu; Sun, Xi-Wen; Zheng, Bin; Nie, Sheng-Dong

2018-02-01

This study aims to develop a computer-aided diagnosis (CADx) scheme for classification between malignant and benign lung nodules, and also assess whether CADx performance changes in detecting nodules associated with early and advanced stage lung cancer. The study involves 243 biopsy-confirmed pulmonary nodules. Among them, 76 are benign, 81 are stage I and 86 are stage III malignant nodules. The cases are separated into three data sets involving: (1) all nodules, (2) benign and stage I malignant nodules, and (3) benign and stage III malignant nodules. A CADx scheme is applied to segment lung nodules depicted on computed tomography images and we initially computed 66 3D image features. Then, three machine learning models namely, a support vector machine, naïve Bayes classifier and linear discriminant analysis, are separately trained and tested by using three data sets and a leave-one-case-out cross-validation method embedded with a Relief-F feature selection algorithm. When separately using three data sets to train and test three classifiers, the average areas under receiver operating characteristic curves (AUC) are 0.94, 0.90 and 0.99, respectively. When using the classifiers trained using data sets with all nodules, average AUC values are 0.88 and 0.99 for detecting early and advanced stage nodules, respectively. AUC values computed from three classifiers trained using the same data set are consistent without statistically significant difference (p  >  0.05). This study demonstrates (1) the feasibility of applying a CADx scheme to accurately distinguish between benign and malignant lung nodules, and (2) a positive trend between CADx performance and cancer progression stage. Thus, in order to increase CADx performance in detecting subtle and early cancer, training data sets should include more diverse early stage cancer cases.

Increasing Lean Mass and Strength: A Comparison of High Frequency Strength Training to Lower Frequency Strength Training.

PubMed

Thomas, Michael H; Burns, Steve P

The purpose of this study was to determine the effect strength training frequency has on improvements in lean mass and strength. Participants were 7 women and 12 men, age ( χ̄ = 34.64 years ± 6.91 years), with strength training experience, training age ( χ̄ = 51.16 months ± 39.02 months). Participants were assigned to one of two groups to equal baseline group demographics. High frequency training group (HFT) trained each muscle group as the agonist, 3 times per week, exercising with 3 sets per muscle group per session (3 total body workouts). Low frequency training group (LFT) trained each muscle group as the agonist one time per week, completing all 9 sets during that one workout. LFT consisted of a routine split over three days: 1) pectoralis, deltoids, and triceps; 2) upper back and biceps; 3) quadriceps, hamstrings, calves, and abdominals. Following eight weeks of training, HFT increased lean mass by 1.06 kg ± 1.78 kg, (1.9%), and LFT increased lean mass by .99 kg ± 1.31 kg, (2.0%). HFT strength improvements on the chest press was 9.07 kg ± 6.33 kg, (11%), and hack squat 20.16 kg ± 11.59 kg, (21%). LFT strength improvements on chest press was 5.80kg ± 4.26 kg, (7.0%), and hack squat 21.83 kg ± 11.17 kg, (24 %). No mean differences between groups were significant. These results suggest that HFT and LFT of equal set totals result in similar improvements in lean mass and strength, following 8 weeks of strength training.

Active learning strategies for the deduplication of electronic patient data using classification trees.

PubMed

Sariyar, M; Borg, A; Pommerening, K

2012-10-01

Supervised record linkage methods often require a clerical review to gain informative training data. Active learning means to actively prompt the user to label data with special characteristics in order to minimise the review costs. We conducted an empirical evaluation to investigate whether a simple active learning strategy using binary comparison patterns is sufficient or if string metrics together with a more sophisticated algorithm are necessary to achieve high accuracies with a small training set. Based on medical registry data with different numbers of attributes, we used active learning to acquire training sets for classification trees, which were then used to classify the remaining data. Active learning for binary patterns means that every distinct comparison pattern represents a stratum from which one item is sampled. Active learning for patterns consisting of the Levenshtein string metric values uses an iterative process where the most informative and representative examples are added to the training set. In this context, we extended the active learning strategy by Sarawagi and Bhamidipaty (2002). On the original data set, active learning based on binary comparison patterns leads to the best results. When dropping four or six attributes, using string metrics leads to better results. In both cases, not more than 200 manually reviewed training examples are necessary. In record linkage applications where only forename, name and birthday are available as attributes, we suggest the sophisticated active learning strategy based on string metrics in order to achieve highly accurate results. We recommend the simple strategy if more attributes are available, as in our study. In both cases, active learning significantly reduces the amount of manual involvement in training data selection compared to usual record linkage settings. Copyright © 2012 Elsevier Inc. All rights reserved.

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies

PubMed Central

2010-01-01

Background All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. Results The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. Conclusions This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general. PMID:20144194

Using simple artificial intelligence methods for predicting amyloidogenesis in antibodies.

PubMed

David, Maria Pamela C; Concepcion, Gisela P; Padlan, Eduardo A

2010-02-08

All polypeptide backbones have the potential to form amyloid fibrils, which are associated with a number of degenerative disorders. However, the likelihood that amyloidosis would actually occur under physiological conditions depends largely on the amino acid composition of a protein. We explore using a naive Bayesian classifier and a weighted decision tree for predicting the amyloidogenicity of immunoglobulin sequences. The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the non-amyloidogenic prediction accuracy is 75.00%. This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.

The effect of low extremity plyometric training on back muscle power of high school throwing event athletes.

PubMed

Park, Gi Duck; Lee, Joong Chul; Lee, Juri

2014-01-01

[Purpose] The physical strength elements required for athletic throwing events include muscle strength, swiftness, agility, speed, flexibility, and physical balance. Although plyometric training and weight training are implemented as representative training methods for improving swiftness and agility, most studies of it have been conducted with players of other sports. [Subjects] The study subjects were 10 throwing event athletes attending K physical education high school. The subjects were randomly assigned to a control group of five subjects and an experimental group of five subjects. To analyze the body composition, an Inbody 3.0 instrument (Biospace, Korea) was used as experimental equipment to measure heights, weight, body fat percentages, and muscle masses and a Biodex system 4.0 (BIODEX, USA) was used to measure isokinetic muscle-joint and lumbar muscle strengths. The plyometric training consisted of 15 techniques out of the training methods introduced in the 'Power up plyometric training'. The plyometric program was implemented without any training load three times per week during daybreak exercises for the experimental group. The number of times and the number of sets were changed over time as follows: three sets of 10 times in the 1st -4th weeks, three sets of 15 times in the 5th-8th weeks, and five sets of 15 times in the 9th-12th weeks. [Results] According to the ANCOVA results of lumbar extensor muscle strength at 60°/sec, the overall reliability of the model was significant. According to the ANCOVA results of lumbar flexor muscle strength at 60°/sec, the overall reliability of the model was significant. [Conclusion] Plyometric training positively affected high school throwing event athletes. To summarize the study findings, the application of plyometric training with high intensity and loads improved the results of athletes who perform highly intensive exercises at normal times.

Expanded scope of training and education programs at the UFTR

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vernetson, W.G.; Whaley, P.M.

1985-01-01

Historically, the University of Florida Training Reactor (UFTR) has been used to train both hot and cold license reactor operator candidates in intensive two- and three-week training programs consisting of a correlated set of classroom lectures, hands-on reactor operations, and laboratory exercises. These training programs provide nuclear plant operating staff with fundamental operational experience in understanding, controlling, and evaluating subcritical multiplication, reactivity effects, reactivity manipulations, and reactor operations; a sufficient number of startups and shutdowns is also assured. The UDTR is also used in a nuclear engineering course entitled ''Principles of Nuclear Reactor Operations.'' The purpose of this paper ismore » to report the results of efforts to redirect and refine tractor operations educational and training programs at the UFTR.« less

Objective assessment in residency-based training for transoral robotic surgery.

PubMed

Curry, Martin; Malpani, Anand; Li, Ryan; Tantillo, Thomas; Jog, Amod; Blanco, Ray; Ha, Patrick K; Califano, Joseph; Kumar, Rajesh; Richmon, Jeremy

2012-10-01

To develop a robotic surgery training regimen integrating objective skill assessment for otolaryngology and head and neck surgery trainees consisting of training modules of increasing complexity leading up to procedure-specific training. In particular, we investigated applications of such a training approach for surgical extirpation of oropharyngeal tumors via a transoral approach using the da Vinci robotic system. Prospective blinded data collection and objective evaluation (Objective Structured Assessment of Technical Skills [OSATS]) of three distinct phases using the da Vinci robotic surgical system in an academic university medical engineering/computer science laboratory setting. Between September 2010 and July 2011, eight otolaryngology-head and neck surgery residents and four staff experts from an academic hospital participated in three distinct phases of robotic surgery training involving 1) robotic platform operational skills, 2) set up of the patient side system, and 3) a complete ex vivo surgical extirpation of an oropharyngeal tumor located in the base of tongue. Trainees performed multiple (four) approximately equally spaced training sessions in each stage of the training. In addition to trainees, baseline performance data were obtained for the experts. Each surgical stage was documented with motion and event data captured from the application programming interfaces of the da Vinci system, as well as separate video cameras as appropriate. All data were assessed using automated skill measures of task efficiency and correlated with structured assessment (OSATS and similar Likert scale) from three experts to assess expert and trainee differences and compute automated and expert assessed learning curves. Our data show that such training results in an improved didactic robotic knowledge base and improved clinical efficiency with respect to the set up and console manipulation. Experts (e.g., average OSATS, 25; standard deviation [SD], 3.1; module 1, suturing) and trainees (average OSATS, 15.9; SD, 3.9; week 1) are well separated at the beginning of the training, and the separation reduces significantly (expert average OSATS, 27.6; SD, 2.7; trainee average OSATS, 24.2; SD, 6.8; module 3) at the conclusion of the training. Learning curves in each of the three stages show diminishing differences between the experts and trainees, which is also consistent with expert assessment. Subjective assessment by experts verified the clinical utility of the module 3 surgical environment, and a survey of trainees consistently rated the curriculum as very useful in progression to human operating room assistance. Structured curricular robotic surgery training with objective assessment promises to reduce the overhead for mentors, allow detailed assessment of human-machine interface skills, and create customized training models for individualized training. This preliminary study verifies the utility of such training in improving human-machine operations skills (module 1), and operating room and surgical skills (modules 2 and 3). In contrast to current coarse measures of total operating time and subjective assessment of error for short mass training sessions, these methods may allow individual tasks to be removed from the trainee regimen when skill levels are within the standard deviation of the experts for these tasks, which can greatly enhance overall efficiency of the training regimen and allow time for additional and more complex training to be incorporated in the same time frame. Copyright © 2012 The American Laryngological, Rhinological, and Otological Society, Inc.

A Repeated Power Training Enhances Fatigue Resistance While Reducing Intraset Fluctuations.

PubMed

Gonzalo-Skok, Oliver; Tous-Fajardo, Julio; Moras, Gerard; Arjol-Serrano, José Luis; Mendez-Villanueva, Alberto

2018-04-04

Oliver, GS, Julio, TF, Moras, G, José Luis, AS, and Alberto, MV. A repeated power training enhances fatigue resistance while reducing intraset fluctuations. J Strength Cond Res XX(X): 000-000, 2018-The present study analyzed the effects of adding an upper-body repeated power ability (RPA) training to habitual strength training sessions. Twenty young elite male basketball players were randomly allocated into a control group (CON, n = 10) or repeated power group (RPG, n = 10) and evaluated by 1 repetition maximum (1RM), incremental load, and RPA tests in the bench press exercise before and after a 7-week period and a 4-week cessation period. Repeated power group performed 1-3 blocks of 5 sets of 5 repetitions using the load that maximized power output with 30 seconds and 3 minute of passive recovery between sets and blocks, respectively. Between-group analysis showed substantial greater improvements in RPG compared with CON in: best set (APB), last set (APL), mean power over 5 sets (APM), percentage of decrement, fluctuation decrease during APL and RPA index (APLpost/APBpre) during the RPA test (effect size [ES] = 0.64-1.86), and 1RM (ES = 0.48) and average power at 80% of 1RM (ES = 1.11) in the incremental load test. The improvements of APB and APM were almost perfectly correlated. In conclusion, RPA training represents an effective method to mainly improve fatigue resistance together with the novel finding of a better consistency in performance (measured as reduced intraset power fluctuations) at the end of a dynamic repeated effort.

Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.

2017-12-01

Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p  =  0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.

Teaching foster grandparents to train severely handicapped persons.

PubMed Central

Fabry, P L; Reid, D H

1978-01-01

Five foster grandparents were taught training skills for use in their daily interactions with severely handicapped persons in an institution. Following baseline, specific teaching procedures consisting of teacher instructions, prompts, modelling, and praise were implemented. The grandparents' frequency of training three skill areas increased as the specific teaching was implemented in multiple-baseline format. The total amount of training continued as teacher instructions, prompts, and modelling were terminated and praise continued, although the grandparents spent their training time emphasizing only two of the three skill areas. Teacher presence was gradually reduced over an 11-week period, with no decrease in grandparents' frequency of training. Four of the foster grandchildren, all profoundly retarded and multiply handicapped, demonstrated progress throughout the study. Results were discussed in light of the available contributions of foster grandparents in institutional settings and maintenance of staff training. PMID:148446

Cross-cultural training of general practitioner registrars: how does it happen?

PubMed

Watt, Kelly; Abbott, Penny; Reath, Jenny

2016-01-01

An equitable multicultural society requires general practitioners (GPs) to be proficient in providing health care to patients from diverse backgrounds. GPs are required to have a certain attitudes, knowledge and skills known as cultural competence. Given its importance to registrar training, the aim of this study was to explore ways in which GP registrars are currently developing cultural competence. This study employed a survey design for GP registrars in Western Sydney. Training approaches to cultural competence that are relevant to the Australian General Practice setting include exposure to diversity, attitudes, knowledge and skills development. The 43 GP registrar respondents in Western Sydney are exposed to a culturally diverse patient load during training. Registrars report a variety of teachings related to cross-cultural training, but there is little consistency, with the most common approach entailing listening to patients' personal stories. Exposure to cultural diversity appears to be an important way in which cultural competency is developed. However, guidance and facilitation of skills development throughout this exposure is required and currently may occur opportunistically rather than consistently.

Ranking the whole MEDLINE database according to a large training set using text indexing.

PubMed

Suomela, Brian P; Andrade, Miguel A

2005-03-24

The MEDLINE database contains over 12 million references to scientific literature, with about 3/4 of recent articles including an abstract of the publication. Retrieval of entries using queries with keywords is useful for human users that need to obtain small selections. However, particular analyses of the literature or database developments may need the complete ranking of all the references in the MEDLINE database as to their relevance to a topic of interest. This report describes a method that does this ranking using the differences in word content between MEDLINE entries related to a topic and the whole of MEDLINE, in a computational time appropriate for an article search query engine. We tested the capabilities of our system to retrieve MEDLINE references which are relevant to the subject of stem cells. We took advantage of the existing annotation of references with terms from the MeSH hierarchical vocabulary (Medical Subject Headings, developed at the National Library of Medicine). A training set of 81,416 references was constructed by selecting entries annotated with the MeSH term stem cells or some child in its sub tree. Frequencies of all nouns, verbs, and adjectives in the training set were computed and the ratios of word frequencies in the training set to those in the entire MEDLINE were used to score references. Self-consistency of the algorithm, benchmarked with a test set containing the training set and an equal number of references randomly selected from MEDLINE was better using nouns (79%) than adjectives (73%) or verbs (70%). The evaluation of the system with 6,923 references not used for training, containing 204 articles relevant to stem cells according to a human expert, indicated a recall of 65% for a precision of 65%. This strategy appears to be useful for predicting the relevance of MEDLINE references to a given concept. The method is simple and can be used with any user-defined training set. Choice of the part of speech of the words used for classification has important effects on performance. Lists of words, scripts, and additional information are available from the web address http://www.ogic.ca/projects/ks2004/.

The Effect of a Short-Term and Long-Term Whole-Body Vibration in Healthy Men upon the Postural Stability

PubMed Central

Piecha, Magdalena; Juras, Grzegorz; Król, Piotr; Sobota, Grzegorz; Polak, Anna; Bacik, Bogdan

2014-01-01

The study aimed to establish the short-term and long-term effects of whole-body vibration on postural stability. The sample consisted of 28 male subjects randomly allocated to four comparative groups, three of which exercised on a vibration platform with parameters set individually for the groups. The stabilographic signal was recorded before the test commenced, after a single session of whole-body vibration, immediately after the last set of exercises of the 4-week whole-body vibration training, and one week after the training ended. The subjects were exposed to vibrations 3 times a week for 4 weeks. Long-term vibration training significantly shortened the rambling and trembling paths in the frontal plane. The path lengths were significantly reduced in the frontal plane one week after the training end date. Most changes in the values of the center of pressure (COP) path lengths in the sagittal and frontal plane were statistically insignificant. We concluded that long-term vibration training improves the postural stability of young healthy individuals in the frontal plane. PMID:24520362

Use of Biotechnology Devices to Analyse Fatigue Process in Swimming Training.

PubMed

Clemente-Suárez, V J; Arroyo-Toledo, J J

2017-06-01

The aim of the present research was to analyze the acute psycho-physiological response during a high intensity interval training (HIIT) session of trained swimmers. We analyzed blood lactate concentration, heart rate, heart rate variability (HRV), arms isometric strength, rating of perceived exertion (RPE) and cortical arousal before and after a HIIT session in 14 trained swimmers (16.2 ± 2.6 years 169.1 ± 10.2 cm 61.3 ± 9.9 kg). HIIT session consisted in: 4 × 10 m tethered swimming resting 90 s between sets, 3 min rest, 16 × 25 m maximum speed swimming resting 30 s between sets. Blood lactate concentration, cortical arousal, and rating of perceived exertion significantly increased (p < 0.05) after HIIT. HRV parameters significantly decreased after HIIT, showing an increase in sympathetic nervous system modulation. Results obtained showed the high impact of HIIT sessions on the swimmer's organism, which may be the cause of adaptation in this low volume training sessions.

Effects of Combined Resistance Training and Plyometrics on Physical Performance in Young Soccer Players.

PubMed

Franco-Márquez, F; Rodríguez-Rosell, D; González-Suárez, J M; Pareja-Blanco, F; Mora-Custodio, R; Yañez-García, J M; González-Badillo, J J

2015-11-01

This study aimed to determine the effects of combined resistance training and plyometrics on physical performance in under-15 soccer players. One team (n=20) followed a 6-week resistance training program combined with plyometrics plus a soccer training program (STG), whereas another team (n=18) followed only the soccer training (CG). Strength training consisted of full squats with low load (45-60% 1RM) and low-volume (2-3 sets and 4-8 repetitions per set) combined with jumps and sprints twice a week. Sprint time in 10 and 20 m (T10, T20, T10-20), CMJ height, estimated one-repetition maximum (1RMest), average velocity attained against all loads common to pre- and post-tests (AV) and velocity developed against different absolute loads (MPV20, 30, 40 and 50) in full squat were selected as testing variables to evaluate the effects of the training program. STG experienced greater gains (P<0.05) in T20, CMJ, 1RMest, AV and MPV20, 30, 40 and 50 than CG. In addition, STG showed likely greater effects in T10 and T10-20 compared to CG. These results indicate that only 6 weeks of resistance training combined with plyometrics in addition to soccer training produce greater gains in physical performance than typical soccer training alone in young soccer players. © Georg Thieme Verlag KG Stuttgart · New York.

Training mildly handicapped peers to facilitate changes in the social interaction skills of autistic children.

PubMed Central

Shafer, M S; Egel, A L; Neef, N A

1984-01-01

We evaluated the effects of a peer-training strategy, consisting of direct prompting and modeling, on the occurrence and duration of interactions between autistic students and nonautistic peer-trainers. Data were obtained in both training and generalization settings. The results of a multiple-baseline design across students demonstrated that:the direct prompting procedure produced immediate and substantial increases in the occurrences and durations of positive social interactions between the peer-trainers and autistic students; these increases were maintained across time at levels above baseline during subsequent free-play probes; these findings were judged by teachers to be socially valid; untrained peers increased their interactions with the autistic students in three of the four groups; generalization of behavior change across settings occurred only after specific programming; and interactions between untrained peers and peer-trainers decreased following training. Variables that may account for the results and the implications of these findings for peer-mediated interventions are discussed. PMID:6526767

Employment training for disadvantaged or dependent populations.

PubMed

Stern, H

1982-01-01

The vocational rehabilitation process is viewed as having two dominant work-related components: the actual work-training experience and employability skills. The paper argues that both components are critical and must be integrated. The major role of the vocational rehabilitation agency is viewed as that of provider of employability (or job-seeking) skills programs. These programs consist of: (1) employability skills courses, (2) work performance demand standard setting, and (3) on-the-job rotational task schemes. Actual work skills can only be provided in the "real world" of work. Centralized work-training programs are viewed as creating inappropriate socialization and only moderately transferable skills.

Practical Qualitative Research Strategies: Training Interviewers and Coders.

PubMed

Goodell, L Suzanne; Stage, Virginia C; Cooke, Natalie K

2016-09-01

The increased emphasis on incorporating qualitative methodologies into nutrition education development and evaluation underscores the importance of using rigorous protocols to enhance the trustworthiness of the findings. A 5-phase protocol for training qualitative research assistants (data collectors and coders) was developed as an approach to increase the consistency of the data produced. This training provides exposure to the core principles of qualitative research and then asks the research assistant to apply those principles through practice in a setting structured on critical reflection. Copyright © 2016 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Acute effect of a complex training protocol of back squats on 30-m sprint times of elite male military athletes

PubMed Central

Ojeda, Álvaro Huerta; Ríos, Luis Chirosa; Barrilao, Rafael Guisado; Serrano, Pablo Cáceres

2016-01-01

[Purpose] The aim of this study was to determine the acute effect temporal of a complex training protocol on 30 meter sprint times. A secondary objective was to evaluate the fatigue indexes of military athletes. [Subjects and Methods] Seven military athletes were the subjects of this study. The variables measured were times in 30-meter sprint, and average power and peak power of squats. The intervention session with complex training consisted of 4 sets of 5 repetitions at 30% 1RM + 4 repetitions at 60% 1RM + 3 repetitions of 30 meters with 120-second rests. For the statistical analysis repeated measures of ANOVA was used, and for the post hoc analysis, student’s t-test was used. [Results] Times in 30 meter sprints showed a significant reduction between the control set and the four experimental sets, but the average power and peak power of squats did not show significant changes. [Conclusion] The results of the study show the acute positive effect of complex training, over time, in 30-meter sprint by military athletes. This effect is due to the post activation potentiation of the lower limbs’ muscles in the 30 meters sprint. PMID:27134353

Acute effect of a complex training protocol of back squats on 30-m sprint times of elite male military athletes.

PubMed

Ojeda, Álvaro Huerta; Ríos, Luis Chirosa; Barrilao, Rafael Guisado; Serrano, Pablo Cáceres

2016-03-01

[Purpose] The aim of this study was to determine the acute effect temporal of a complex training protocol on 30 meter sprint times. A secondary objective was to evaluate the fatigue indexes of military athletes. [Subjects and Methods] Seven military athletes were the subjects of this study. The variables measured were times in 30-meter sprint, and average power and peak power of squats. The intervention session with complex training consisted of 4 sets of 5 repetitions at 30% 1RM + 4 repetitions at 60% 1RM + 3 repetitions of 30 meters with 120-second rests. For the statistical analysis repeated measures of ANOVA was used, and for the post hoc analysis, student's t-test was used. [Results] Times in 30 meter sprints showed a significant reduction between the control set and the four experimental sets, but the average power and peak power of squats did not show significant changes. [Conclusion] The results of the study show the acute positive effect of complex training, over time, in 30-meter sprint by military athletes. This effect is due to the post activation potentiation of the lower limbs' muscles in the 30 meters sprint.

Rest Interval Required for Power Training With Power Load in the Bench Press Throw Exercise.

PubMed

Hernández Davó, Jose L; Solana, Rafael Sabido; Sarabia Marín, Jose M; Fernández Fernández, Jaime; Moya Ramón, Manuel

2016-05-01

This study aimed to test the influence of various rest interval (RI) durations used between sets on power output performance and physiological and perceptual variables during a strength training session using 40% of the 1 repetition maximum (1RM) in the bench press throw exercise. Thirty-one college students (18 males and 13 females) took part in the study. The experimental protocol consists of 5 sets of 8 repetitions of the bench press throw exercise with a load representing 40% of 1RM. Subjects performed the experimental protocol on 3 different occasions, differing by the RI between sets (1, 2, or 3 minutes). During the sessions, power data (mean power and peak power), physiological (lactate concentration [La]) and perceptual (rating of perceived exertion) variables were measured. In addition, delayed onset muscular soreness was reported 24 and 48 hours after the training session. One-way repeated-measures analysis of variance showed that 1-minute RI entailed higher power decreases and greater increases in values of physiological and perceptual variables compared with both 2- and 3-minute RIs. Nevertheless, no differences were found between 2- and 3-minute RIs. Therefore, this study showed that, when training with 40% of 1RM in the bench press throw exercise, a 2-minute RI between sets can be enough to avoid significant decreases in power output. Consequently, training sessions' duration could be reduced without causing excessive fatigue, allowing additional time to focus on other conditioning priorities.

Infrared imagery acquisition process supporting simulation and real image training

NASA Astrophysics Data System (ADS)

O'Connor, John

2012-05-01

The increasing use of infrared sensors requires development of advanced infrared training and simulation tools to meet current Warfighter needs. In order to prepare the force, a challenge exists for training and simulation images to be both realistic and consistent with each other to be effective and avoid negative training. The US Army Night Vision and Electronic Sensors Directorate has corrected this deficiency by developing and implementing infrared image collection methods that meet the needs of both real image trainers and real-time simulations. The author presents innovative methods for collection of high-fidelity digital infrared images and the associated equipment and environmental standards. The collected images are the foundation for US Army, and USMC Recognition of Combat Vehicles (ROC-V) real image combat ID training and also support simulations including the Night Vision Image Generator and Synthetic Environment Core. The characteristics, consistency, and quality of these images have contributed to the success of these and other programs. To date, this method has been employed to generate signature sets for over 350 vehicles. The needs of future physics-based simulations will also be met by this data. NVESD's ROC-V image database will support the development of training and simulation capabilities as Warfighter needs evolve.

The Effect of Low Extremity Plyometric Training on Back Muscle Power of High School Throwing Event Athletes

PubMed Central

Park, Gi Duck; Lee, Joong Chul; Lee, Juri

2014-01-01

[Purpose] The physical strength elements required for athletic throwing events include muscle strength, swiftness, agility, speed, flexibility, and physical balance. Although plyometric training and weight training are implemented as representative training methods for improving swiftness and agility, most studies of it have been conducted with players of other sports. [Subjects] The study subjects were 10 throwing event athletes attending K physical education high school. The subjects were randomly assigned to a control group of five subjects and an experimental group of five subjects. To analyze the body composition, an Inbody 3.0 instrument (Biospace, Korea) was used as experimental equipment to measure heights, weight, body fat percentages, and muscle masses and a Biodex system 4.0 (BIODEX, USA) was used to measure isokinetic muscle-joint and lumbar muscle strengths. The plyometric training consisted of 15 techniques out of the training methods introduced in the ‘Power up plyometric training’. The plyometric program was implemented without any training load three times per week during daybreak exercises for the experimental group. The number of times and the number of sets were changed over time as follows: three sets of 10 times in the 1st −4th weeks, three sets of 15 times in the 5th–8th weeks, and five sets of 15 times in the 9th−12th weeks. [Results] According to the ANCOVA results of lumbar extensor muscle strength at 60°/sec, the overall reliability of the model was significant. According to the ANCOVA results of lumbar flexor muscle strength at 60°/sec, the overall reliability of the model was significant. [Conclusion] Plyometric training positively affected high school throwing event athletes. To summarize the study findings, the application of plyometric training with high intensity and loads improved the results of athletes who perform highly intensive exercises at normal times. PMID:24567698

Manual patient transfers used most often by student and staff nurses are consistent with their perceptions of transfer training, and performance confidence.

PubMed

van Wyk, Paula M; Weir, Patricia L; Andrews, David M

2015-01-01

A disconnect in manual patient transfer (MPT) training practices for nurses, between what is taught and used in academic and clinical settings, could have implications for injury. This study aimed to determine: 1. what MPTs student and staff nurses use in clinical settings, and 2. if the MPTs used most often were also the ones they perceived that they received training for and had the most confidence performing. Survey responses from student nurses (n=163) (mid-sized university) and staff nurses (n=33) (local hospital) regarding 19 MPTs were analyzed to determine which transfers were perceived to be used most often, and which ones they had received training for and had the greatest confidence performing. The MPTs nurses perceived using most often were the same transfers they had the greatest confidence performing and for which they perceived receiving training. However, these MPTs were not taught at the university at the time of this investigation. Reducing the disconnect between manual patient transfer training obtained in the academic and clinical environments will hopefully reduce the risk of injury for nurses and improve the quality of care for patients.

Simulation Based Training Improves Airway Management for Helicopter EMS Teams

NASA Technical Reports Server (NTRS)

Dhindsa, Harinder S.; Reid, Renee; Murray, David; Lovelady, James; Powell, Katie; Sayles, Jeff; Stevenson, Christopher; Baker, Kathy; Solada, Brian; Carroll, Scott;

Cultural competency training of GP Registrars-exploring the views of GP Supervisors.

PubMed

Watt, Kelly; Abbott, Penny; Reath, Jenny

2015-10-06

An equitable multicultural society requires General Practitioners (GPs) to be proficient in providing health care to patients from diverse backgrounds. This requires a certain set of attitudes, knowledge and skills known as cultural competence. While training in cultural competence is an important part of the Australian GP Registrar training curriculum, it is unclear who provides this training apart from in Aboriginal and Torres Strait Islander training posts. The majority of Australian GP Registrar training takes place in a workplace setting facilitated by the GP Supervisor. In view of the central role of GP Supervisors, their views on culturally competent practice, and their role in its development in Registrars, are important to ascertain. We conducted 14 semi-structured interviews with GP Supervisors. These were audiotaped, transcribed verbatim and thematically analyzed using an iterative approach. The Supervisors interviewed frequently viewed cultural competence as adequately covered by using patient-centered approaches. The Supervisor role in promoting cultural competence of Registrars was affirmed, though training was noted to occur opportunistically and focused largely on patient-centered care rather than health disparities. Formal training for both Registrars and Supervisors may be beneficial not only to develop a deeper understanding of cultural competence and its relevance to practice but also to promote more consistency in training from Supervisors in the area, particularly with respect to self-reflection, non-conscious bias and utilizing appropriate cultural knowledge without stereotyping and assumption-making.

Dose-volume histogram prediction using density estimation.

PubMed

Skarpman Munter, Johanna; Sjölund, Jens

2015-09-07

Knowledge of what dose-volume histograms can be expected for a previously unseen patient could increase consistency and quality in radiotherapy treatment planning. We propose a machine learning method that uses previous treatment plans to predict such dose-volume histograms. The key to the approach is the framing of dose-volume histograms in a probabilistic setting.The training consists of estimating, from the patients in the training set, the joint probability distribution of some predictive features and the dose. The joint distribution immediately provides an estimate of the conditional probability of the dose given the values of the predictive features. The prediction consists of estimating, from the new patient, the distribution of the predictive features and marginalizing the conditional probability from the training over this. Integrating the resulting probability distribution for the dose yields an estimate of the dose-volume histogram.To illustrate how the proposed method relates to previously proposed methods, we use the signed distance to the target boundary as a single predictive feature. As a proof-of-concept, we predicted dose-volume histograms for the brainstems of 22 acoustic schwannoma patients treated with stereotactic radiosurgery, and for the lungs of 9 lung cancer patients treated with stereotactic body radiation therapy. Comparing with two previous attempts at dose-volume histogram prediction we find that, given the same input data, the predictions are similar.In summary, we propose a method for dose-volume histogram prediction that exploits the intrinsic probabilistic properties of dose-volume histograms. We argue that the proposed method makes up for some deficiencies in previously proposed methods, thereby potentially increasing ease of use, flexibility and ability to perform well with small amounts of training data.

Low-Active Male Adolescents: A Dose Response to High-Intensity Interval Training.

PubMed

Logan, Greig Robert Melrose; Harris, Nigel; Duncan, Scott; Plank, Lindsay D; Merien, Fabrice; Schofield, Grant

2016-03-01

High-intensity interval training (HIIT) is a potential alternative to traditionally recommended steady state exercise for providing health benefits in adolescents, yet its dose-response relationship in this cohort remains unclear, as does its translatability to real-world, nonclinical settings. The present study adopts a novel dose-response design to investigate the effects of undertaking 8 wk of HIIT on the cardiometabolic health of low-active male adolescents. Twenty-six male adolescents (age 16 ± 1 yr), identified as low active by nonparticipation in structured sport and physical education classes, were randomly assigned to one of five treatment groups. Corresponding with their group numbers (1-5), participants completed a number of HIIT "sets," which consisted of 4 repeated bouts of 20-s near-maximal exertion interspersed with 10-s passive recovery. Participants performed two HIIT sessions and one resistance training session each week for 8 wk. Baseline and follow-up health measures consisted of peak oxygen uptake (V˙O2peak) with an incremental ramp test to volitional exhaustion; body composition (including visceral fat mass, body fat, and lean tissue mass) with dual-energy x-ray absorptiometry; and lipid profile, glucose, insulin, and interleukin-6 from blood analysis. All health outcomes were analyzed as percentage changes, and data were modeled using a quadratic function to explore dose-response relationships. Significant improvements were observed for V˙O2peak (∼6%), body fat percentage (∼4%), visceral fat mass (∼10%), and waist circumference-to-height ratio (∼3%), but there was no clear effect of dose across groups. Low-active adolescent males performing a single HIIT set twice weekly, in addition to one resistance training session, gained meaningful improvements in fitness and body composition. Performing additional HIIT sets provided no additional improvements to those of the lowest dose in this study.

Integrated Resistance and Aerobic Training Maintains Cardiovascular and Skeletal Muscle Fitness During 14 Days of Bed Rest

NASA Technical Reports Server (NTRS)

Ploutz-Snyder, Lori; Goetchius, Elizabeth; Crowell, Brent; Hackney, Kyle; Wickwire, Jason; Ploutz-Snyder, Robert; Snyder, Scott

2012-01-01

Background: Known incompatibilities exist between resistance and aerobic training. Of particular importance are findings that concurrent resistance and aerobic training reduces the effectiveness of the resistance training and limits skeletal muscle adaptations (example: Dudley & Djamil, 1985). Numerous unloading studies have documented the effectiveness of resistance training alone for the maintenance of skeletal muscle size and strength. However the practical applications of those studies are limited because long ]duration crew members perform both aerobic and resistance exercise throughout missions/spaceflight. To date, such integrated training on the International Space Station (ISS) has not been fully effective in the maintenance of skeletal muscle function. Purpose: The purpose of this study was to evaluate the efficacy of high intensity concurrent resistance and aerobic training for the maintenance of cardiovascular fitness and skeletal muscle strength, power and endurance over 14 days of strict bed rest. Methods: 9 subjects (8 male and 1 female; 34.5 +/- 8.2 years) underwent 14 days of bed rest with concurrent training. Resistance and aerobic training were integrated as shown in table 1. Days that included 2 exercise sessions had a 4-8 hour rest between exercise bouts. The resistance training consisted of 3 sets of 12 repetitions of squat, heel raise, leg press and hamstring curl exercise. Aerobic exercise consisted of periodized interval training that included 30 sec, 2 min and 4 min intervals alternating by day with continuous aerobic exercise.

The Pursuit of Otolaryngology Subspecialty Fellowships.

PubMed

Wilson, Meghan N; Vila, Peter M; Cohen, David S; Carter, John M; Lawlor, Claire M; Davis, Kara S; Raol, Nikhila P

2016-06-01

To examine otolaryngology resident interest in subspecialty fellowship training and factors affecting interest over time and over the course of residency training Cross-sectional study of anonymous online survey data. Residents and fellows registered as members-in-training through the American Academy of Otolaryngology-Head and Neck Surgery. Data regarding fellowship interest and influencing factors, including demographics, were extracted from the Section for Residents and Fellows Annual Survey response database from 2008 to 2014. Over 6 years, there were 2422 resident and fellow responses to the survey. Senior residents showed a statistically significant decrease in fellowship interest compared with junior residents, with 79% of those in postgraduate year (PGY) 1, 73% in PGY-2 and PGY-3, and 64% in PGY-4 and PGY-5 planning to pursue subspecialty training (P < .0001). Educational debt, age, and intended practice setting significantly predicted interest in fellowship training. Sex was not predictive. The most important factors cited by residents in choosing a subspecialty were consistently type of surgical cases and nature of clinical problems. In this study, interest in pursuing fellowship training decreased with increased residency training. This decision is multifactorial in nature and also influenced by age, educational debt, and intended practice setting. © American Academy of Otolaryngology—Head and Neck Surgery Foundation 2016.

The development and implementation of the structured training programme for caregivers of inpatients after stroke (TRACS) intervention: the London Stroke Carers Training Course.

PubMed

Forster, Anne; Dickerson, Josie; Melbourn, Anne; Steadman, Jayne; Wittink, Margreet; Young, John; Kalra, Lalit; Farrin, Amanda

2015-03-01

To describe the content and delivery of the adapted London Stroke Carers Training Course intervention evaluated in the Training Caregivers after Stroke (TRACS) trial. The London Stroke Carers Training Course is a structured training programme for caregivers of inpatients who are likely to return home after their stroke. The course was delivered by members of the multidisciplinary team while the patient was in the stroke unit with one recommended 'follow through' session after discharge home. The intervention consists of 14 training components (six mandatory) that were identified as important knowledge/skills that caregivers would need to be able to care for the stroke patient after discharge home. Following national training days, the London Stroke Carers Training Course was disseminated to intervention sites by the cascade method of implementation. The intervention was adapted for implementation across a range of stroke units. Training days were well attended (median 2.5 and 2.0 attendees per centre for the first and second days, respectively) and the feedback positive, demonstrating 'face validity' for the intervention. However cascading of this training to other members of the multidisciplinary team was not consistent, with 7/18 centres recording no cascade training. The adapted London Stroke Carers Training Course provided a training programme that could be delivered in a standardised, structured way in a variety of stroke unit settings throughout the UK. The intervention was well received by stroke unit staff, however, the cascade method of implementation was not as effective as we would have wished. © The Author(s) 2014.

The Role of Therapist Training in the Implementation of Psychosocial Treatments: A Review and Critique with Recommendations

PubMed Central

Herschell, Amy D.; Kolko, David J.; Baumann, Barbara L.; Davis, Abigail C.

2010-01-01

Evidence-based treatments (EBT) are underutilized in community settings, where consumers are often seen for treatment. Underutilization of EBTs may be related to a lack of empirically informed and supported training strategies. The goals of this review are to understand the state of the literature for training therapists in psychotherapy skills and to offer recommendations to improve research in this area. Results of this review of 55 studies evaluating six training methods indicate that multi-component trainings have been studied most often and have most consistently demonstrated positive training outcomes relative to other training methods. Studies evaluating utility of reading, self-directed trainings, and workshops have documented that these methods do not routinely produce positive outcomes. Workshop follow-ups help to sustain outcomes. Little is known about the impact of train-the-trainer methods. Methodological flaws and factors that may influence training outcome and future directions are also reviewed. PMID:20304542

Effect of sprint training: training once daily versus twice every second day.

PubMed

Ijichi, Toshiaki; Hasegawa, Yuta; Morishima, Takuma; Kurihara, Toshiyuki; Hamaoka, Takafumi; Goto, Kazushige

2015-01-01

This study compared training adaptations between once daily (SINGLE) and twice every second day (REPEATED) sprint training, with same number of training sessions. Twenty physically active males (20.9 ± 1.3 yr) were assigned randomly to the SINGLE (n = 10) or REPEATED (n = 10) group. The SINGLE group trained once per day (5 days per week) for 4 weeks (20 sessions in total). The REPEATED group conducted two consecutive training sessions on the same day, separated by a rest period of 1 h (2-3 days per week) for 4 weeks (20 sessions in total). Each training session consisted of three consecutive 30-s maximal pedalling sets with a 10-min rest between sets. Before and after the training period, the power output during two bouts of 30-s maximal pedalling, exercise duration during submaximal pedalling and resting muscle phosphocreatine (PCr) levels were evaluated. Both groups showed significant increases in peak and mean power output during the two 30-s bouts of maximal pedalling after the training period (P < 0.05). The groups showed similar increases in VO2max after the training period (P < 0.05). The REPEATED group showed a significant increase in the onset of blood lactate accumulation (OBLA) after the training period (P < 0.05), whereas no change was observed in the SINGLE group. The time to exhaustion at 90% of VO2max and muscle PCr concentration at baseline did not change significantly in either group. Sprint training twice every second day improved OBLA during endurance exercise more than the same training once daily.

Exercise training during rehabilitation of patients with COPD: a current perspective.

PubMed

Spruit, Martijn A; Troosters, Thierry; Trappenburg, Jacob C A; Decramer, Marc; Gosselink, Rik

2004-03-01

Patients with chronic obstructive pulmonary disease (COPD) suffer frequently from physiologic and psychological impairments, such as dyspnea, peripheral muscle weakness, exercise intolerance, decreased health-related quality of life (HRQOL) and emotional distress. Rehabilitation programmes have shown to result in significant changes in perceived dyspnea and fatigue, utilisation of healthcare resources, exercise performance and HRQOL. Exercise training, which consists of whole-body exercise training and local resistance training, is the cornerstone of these programmes. Regrettably, the positive effects of respiratory rehabilitation deteriorate over time, especially after short programmes. Hence, attention should be given to the aftercare of these patients to prevent them to revert again to a sedentary lifestyle. On empirical basis three possibilities seem to be clinically feasible: (1) continuous outpatient exercise training; (2) exercise training in a home-based or community-based setting; or (3) exercise training sessions in a group of asthma and COPD patients.

Audiologists' communication behaviour during hearing device management appointments.

PubMed

Muñoz, Karen; Ong, Clarissa W; Borrie, Stephanie A; Nelson, Lauri H; Twohig, Michael P

2017-05-01

The aim of this exploratory study was to describe audiologist communication behaviours during appointments for hearing device monitoring and management before and after participation in counselling skills training. The study used a longitudinal design with three assessment points over 6 months. The sample included 10 audiologists and audiology graduate students interacting in a professional setting with their clients. Audiologists reported improvement in their counselling skills from pre-training to follow-up, which was consistent with objective findings that audiologist relative speaking time decreased from pre-training to post-training as well as from pre-training to follow-up. Observer-rated scores of participants' counselling skills; however, yielded no significant differences across time. Some improvement was noted in audiologists' counselling behaviour following a 1-day communication skills workshop and continued learning support. It is evident; however, that further training, such as increased training and performance feedback, is needed to maintain and enhance audiologist progress in the various aspects of counselling.

Formal and Informal Continuing Education Activities and Athletic Training Professional Practice

PubMed Central

Armstrong, Kirk J.; Weidner, Thomas G.

2010-01-01

Abstract Context: Continuing education (CE) is intended to promote professional growth and, ultimately, to enhance professional practice. Objective: To determine certified athletic trainers' participation in formal (ie, approved for CE credit) and informal (ie, not approved for CE credit) CE activities and the perceived effect these activities have on professional practice with regard to improving knowledge, clinical skills and abilities, attitudes toward patient care, and patient care itself. Design: Cross-sectional study. Setting: Athletic training practice settings. Patients or Other Participants: Of a geographic, stratified random sample of 1000 athletic trainers, 427 (42.7%) completed the survey. Main Outcome Measure(s): The Survey of Formal and Informal Athletic Training Continuing Education Activities was developed and administered electronically. The survey consisted of demographic characteristics and Likert-scale items regarding CE participation and perceived effect of CE on professional practice. Internal consistency of survey items was determined using the Cronbach α (α  =  0.945). Descriptive statistics were computed for all items. An analysis of variance and dependent t tests were calculated to determine differences among respondents' demographic characteristics and their participation in, and perceived effect of, CE activities. The α level was set at .05. Results: Respondents completed more informal CE activities than formal CE activities. Participation in informal CE activities included reading athletic training journals (75.4%), whereas formal CE activities included attending a Board of Certification–approved workshop, seminar, or professional conference not conducted by the National Athletic Trainers' Association or affiliates or committees (75.6%). Informal CE activities were perceived to improve clinical skills or abilities and attitudes toward patient care. Formal CE activities were perceived to enhance knowledge. Conclusions: More respondents completed informal CE activities than formal CE activities. Both formal and informal CE activities were perceived to enhance athletic training professional practice. Informal CE activities should be explored and considered for CE credit. PMID:20446842

An exploratory study of a text classification framework for Internet-based surveillance of emerging epidemics

PubMed Central

Torii, Manabu; Yin, Lanlan; Nguyen, Thang; Mazumdar, Chand T.; Liu, Hongfang; Hartley, David M.; Nelson, Noele P.

2014-01-01

Purpose Early detection of infectious disease outbreaks is crucial to protecting the public health of a society. Online news articles provide timely information on disease outbreaks worldwide. In this study, we investigated automated detection of articles relevant to disease outbreaks using machine learning classifiers. In a real-life setting, it is expensive to prepare a training data set for classifiers, which usually consists of manually labeled relevant and irrelevant articles. To mitigate this challenge, we examined the use of randomly sampled unlabeled articles as well as labeled relevant articles. Methods Naïve Bayes and Support Vector Machine (SVM) classifiers were trained on 149 relevant and 149 or more randomly sampled unlabeled articles. Diverse classifiers were trained by varying the number of sampled unlabeled articles and also the number of word features. The trained classifiers were applied to 15 thousand articles published over 15 days. Top-ranked articles from each classifier were pooled and the resulting set of 1337 articles was reviewed by an expert analyst to evaluate the classifiers. Results Daily averages of areas under ROC curves (AUCs) over the 15-day evaluation period were 0.841 and 0.836, respectively, for the naïve Bayes and SVM classifier. We referenced a database of disease outbreak reports to confirm that this evaluation data set resulted from the pooling method indeed covered incidents recorded in the database during the evaluation period. Conclusions The proposed text classification framework utilizing randomly sampled unlabeled articles can facilitate a cost-effective approach to training machine learning classifiers in a real-life Internet-based biosurveillance project. We plan to examine this framework further using larger data sets and using articles in non-English languages. PMID:21134784

The implementation of contour-based object orientation estimation algorithm in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Alpatov, Boris; Babayan, Pavel; Ershov, Maksim; Strotov, Valery

2016-10-01

This paper describes the implementation of the orientation estimation algorithm in FPGA-based vision system. An approach to estimate an orientation of objects lacking axial symmetry is proposed. Suggested algorithm is intended to estimate orientation of a specific known 3D object based on object 3D model. The proposed orientation estimation algorithm consists of two stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

Training set expansion: an approach to improving the reconstruction of biological networks from limited and uneven reliable interactions

PubMed Central

Yip, Kevin Y.; Gerstein, Mark

2009-01-01

Motivation: An important problem in systems biology is reconstructing complete networks of interactions between biological objects by extrapolating from a few known interactions as examples. While there are many computational techniques proposed for this network reconstruction task, their accuracy is consistently limited by the small number of high-confidence examples, and the uneven distribution of these examples across the potential interaction space, with some objects having many known interactions and others few. Results: To address this issue, we propose two computational methods based on the concept of training set expansion. They work particularly effectively in conjunction with kernel approaches, which are a popular class of approaches for fusing together many disparate types of features. Both our methods are based on semi-supervised learning and involve augmenting the limited number of gold-standard training instances with carefully chosen and highly confident auxiliary examples. The first method, prediction propagation, propagates highly confident predictions of one local model to another as the auxiliary examples, thus learning from information-rich regions of the training network to help predict the information-poor regions. The second method, kernel initialization, takes the most similar and most dissimilar objects of each object in a global kernel as the auxiliary examples. Using several sets of experimentally verified protein–protein interactions from yeast, we show that training set expansion gives a measurable performance gain over a number of representative, state-of-the-art network reconstruction methods, and it can correctly identify some interactions that are ranked low by other methods due to the lack of training examples of the involved proteins. Contact: mark.gerstein@yale.edu Availability: The datasets and additional materials can be found at http://networks.gersteinlab.org/tse. PMID:19015141

Phonological mismatch makes aided speech recognition in noise cognitively taxing.

PubMed

Rudner, Mary; Foo, Catharina; Rönnberg, Jerker; Lunner, Thomas

2007-12-01

The working memory framework for Ease of Language Understanding predicts that speech processing becomes more effortful, thus requiring more explicit cognitive resources, when there is mismatch between speech input and phonological representations in long-term memory. To test this prediction, we changed the compression release settings in the hearing instruments of experienced users and allowed them to train for 9 weeks with the new settings. After training, aided speech recognition in noise was tested with both the trained settings and orthogonal settings. We postulated that training would lead to acclimatization to the trained setting, which in turn would involve establishment of new phonological representations in long-term memory. Further, we postulated that after training, testing with orthogonal settings would give rise to phonological mismatch, associated with more explicit cognitive processing. Thirty-two participants (mean=70.3 years, SD=7.7) with bilateral sensorineural hearing loss (pure-tone average=46.0 dB HL, SD=6.5), bilaterally fitted for more than 1 year with digital, two-channel, nonlinear signal processing hearing instruments and chosen from the patient population at the Linköping University Hospital were randomly assigned to 9 weeks training with new, fast (40 ms) or slow (640 ms), compression release settings in both channels. Aided speech recognition in noise performance was tested according to a design with three within-group factors: test occasion (T1, T2), test setting (fast, slow), and type of noise (unmodulated, modulated) and one between-group factor: experience setting (fast, slow) for two types of speech materials-the highly constrained Hagerman sentences and the less-predictable Hearing in Noise Test (HINT). Complex cognitive capacity was measured using the reading span and letter monitoring tests. PREDICTION: We predicted that speech recognition in noise at T2 with mismatched experience and test settings would be associated with more explicit cognitive processing and thus stronger correlations with complex cognitive measures, as well as poorer performance if complex cognitive capacity was exceeded. Under mismatch conditions, stronger correlations were found between performance on speech recognition with the Hagerman sentences and reading span, along with poorer speech recognition for participants with low reading span scores. No consistent mismatch effect was found with HINT. The mismatch prediction generated by the working memory framework for Ease of Language Understanding is supported for speech recognition in noise with the highly constrained Hagerman sentences but not the less-predictable HINT.

Improving Academic Performance in a Bilingual Education Classroom.

ERIC Educational Resources Information Center

Golub, Lester S.; Sweeney, Gladys M.

The purpose of this study is twofold. First, it evaluates the effectiveness of token economy programs in increasing academic performance in a bilingual education classroom setting. Second, it attempts to train the teacher in the basic behavior modification principles and assist her/him in the delivery of appropriate and consistent reinforcement…

Processing Mode Causally Influences Emotional Reactivity

PubMed Central

Watkins, Ed; Moberly, Nicholas J.; Moulds, Michelle L.

2008-01-01

Three studies are reported showing that emotional responses to stress can be modified by systematic prior practice in adopting particular processing modes. Participants were induced to think about positive and negative scenarios in a mode either characteristic of or inconsistent with the abstract-evaluative mind-set observed in depressive rumination, via explicit instructions (Experiments 1 and 2) and via implicit induction of interpretative biases (Experiment 3), before being exposed to a failure experience. In all three studies, participants trained into the mode antithetical to depressive rumination demonstrated less emotional reactivity following failure than participants trained into the mode consistent with depressive rumination. These findings provide evidence consistent with the hypothesis that processing mode modifies emotional reactivity and support the processing-mode theory of rumination. PMID:18540752

Development and validation of a radiomics nomogram for progression-free survival prediction in stage IV EGFR-mutant non-small cell lung cancer

NASA Astrophysics Data System (ADS)

Song, Jiangdian; Zang, Yali; Li, Weimin; Zhong, Wenzhao; Shi, Jingyun; Dong, Di; Fang, Mengjie; Liu, Zaiyi; Tian, Jie

2017-03-01

Accurately predict the risk of disease progression and benefit of tyrosine kinase inhibitors (TKIs) therapy for stage IV non-small cell lung cancer (NSCLC) patients with activing epidermal growth factor receptor (EGFR) mutations by current staging methods are challenge. We postulated that integrating a classifier consisted of multiple computed tomography (CT) phenotypic features, and other clinicopathological risk factors into a single model could improve risk stratification and prediction of progression-free survival (PFS) of EGFR TKIs for these patients. Patients confirmed as stage IV EGFR-mutant NSCLC received EGFR TKIs with no resection; pretreatment contrast enhanced CT performed at approximately 2 weeks before the treatment was enrolled. A six-CT-phenotypic-feature-based classifier constructed by the LASSO Cox regression model, and three clinicopathological factors: pathologic N category, performance status (PS) score, and intrapulmonary metastasis status were used to construct a nomogram in a training set of 115 patients. The prognostic and predictive accuracy of this nomogram was then subjected to an external independent validation of 107 patients. PFS between the training and independent validation set is no statistical difference by Mann-Whitney U test (P = 0.2670). PFS of the patients could be predicted with good consistency compared with the actual survival. C-index of the proposed individualized nomogram in the training set (0·707, 95%CI: 0·643, 0·771) and the independent validation set (0·715, 95%CI: 0·650, 0·780) showed the potential of clinical prognosis to predict PFS of stage IV EGFR-mutant NSCLC from EGFR TKIs. The individualized nomogram might facilitate patient counselling and individualise management of patients with this disease.

Pilot Evaluation of a Communication Skills Training Program for Psychiatry Residents Using Standardized Patient Assessment.

PubMed

Ditton-Phare, Philippa; Sandhu, Harsimrat; Kelly, Brian; Kissane, David; Loughland, Carmel

2016-10-01

Mental health clinicians can experience difficulties communicating diagnostic information to patients and their families/carers, especially about distressing psychiatric disorders such as schizophrenia. There is evidence for the effectiveness of communication skills training (CST) for improving diagnostic discussions, particularly in specialties such as oncology, but only limited evidence exists about CST for psychiatry. This study evaluated a CST program specifically developed for psychiatry residents called ComPsych that focuses on conveying diagnostic and prognostic information about schizophrenia. The ComPsych program consists of an introductory lecture, module booklets for trainees, and exemplary skills videos, followed by small group role-plays with simulated patients (SPs) led by a trained facilitator. A standardized patient assessment (SPA) was digitally recorded pre- and post-training with a SP using a standardized scenario in a time-limited (15 min) period. Recorded SPAs were independently rated using a validated coding system (ComSkil) to identify frequency of skills used in five skills categories (agenda setting, checking, questioning, information organization, and empathic communication). Thirty trainees (15 males and 15 females; median age = 32) undertaking their vocational specialty training in psychiatry participated in ComPsych training and pre- and post-ComPsych SPAs. Skills increased post-training for agenda setting (d = -0.82), while questioning skills (d = 0.56) decreased. There were no significant differences in any other skills grouping, although checking, information organization, and empathic communication skills tended to increase post-training. A dose effect was observed for agenda setting, with trainees who attended more CST sessions outperforming those attending fewer. Findings support the generalization and translation of ComPsych CST to psychiatry.

Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

PubMed

Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

2018-04-17

The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

A new biodegradation prediction model specific to petroleum hydrocarbons.

PubMed

Howard, Philip; Meylan, William; Aronson, Dallas; Stiteler, William; Tunkel, Jay; Comber, Michael; Parkerton, Thomas F

2005-08-01

A new predictive model for determining quantitative primary biodegradation half-lives of individual petroleum hydrocarbons has been developed. This model uses a fragment-based approach similar to that of several other biodegradation models, such as those within the Biodegradation Probability Program (BIOWIN) estimation program. In the present study, a half-life in days is estimated using multiple linear regression against counts of 31 distinct molecular fragments. The model was developed using a data set consisting of 175 compounds with environmentally relevant experimental data that was divided into training and validation sets. The original fragments from the Ministry of International Trade and Industry BIOWIN model were used initially as structural descriptors and additional fragments were then added to better describe the ring systems found in petroleum hydrocarbons and to adjust for nonlinearity within the experimental data. The training and validation sets had r2 values of 0.91 and 0.81, respectively.

[Method of traditional Chinese medicine formula design based on 3D-database pharmacophore search and patent retrieval].

PubMed

He, Yu-su; Sun, Zhi-yi; Zhang, Yan-ling

2014-11-01

By using the pharmacophore model of mineralocorticoid receptor antagonists as a starting point, the experiment stud- ies the method of traditional Chinese medicine formula design for anti-hypertensive. Pharmacophore models were generated by 3D-QSAR pharmacophore (Hypogen) program of the DS3.5, based on the training set composed of 33 mineralocorticoid receptor antagonists. The best pharmacophore model consisted of two Hydrogen-bond acceptors, three Hydrophobic and four excluded volumes. Its correlation coefficient of training set and test set, N, and CAI value were 0.9534, 0.6748, 2.878, and 1.119. According to the database screening, 1700 active compounds from 86 source plant were obtained. Because of lacking of available anti-hypertensive medi cation strategy in traditional theory, this article takes advantage of patent retrieval in world traditional medicine patent database, in order to design drug formula. Finally, two formulae was obtained for antihypertensive.

Convolutional Neural Networks for Medical Image Analysis: Full Training or Fine Tuning?

PubMed

Tajbakhsh, Nima; Shin, Jae Y; Gurudu, Suryakanth R; Hurst, R Todd; Kendall, Christopher B; Gotway, Michael B; Jianming Liang

2016-05-01

Training a deep convolutional neural network (CNN) from scratch is difficult because it requires a large amount of labeled training data and a great deal of expertise to ensure proper convergence. A promising alternative is to fine-tune a CNN that has been pre-trained using, for instance, a large set of labeled natural images. However, the substantial differences between natural and medical images may advise against such knowledge transfer. In this paper, we seek to answer the following central question in the context of medical image analysis: Can the use of pre-trained deep CNNs with sufficient fine-tuning eliminate the need for training a deep CNN from scratch? To address this question, we considered four distinct medical imaging applications in three specialties (radiology, cardiology, and gastroenterology) involving classification, detection, and segmentation from three different imaging modalities, and investigated how the performance of deep CNNs trained from scratch compared with the pre-trained CNNs fine-tuned in a layer-wise manner. Our experiments consistently demonstrated that 1) the use of a pre-trained CNN with adequate fine-tuning outperformed or, in the worst case, performed as well as a CNN trained from scratch; 2) fine-tuned CNNs were more robust to the size of training sets than CNNs trained from scratch; 3) neither shallow tuning nor deep tuning was the optimal choice for a particular application; and 4) our layer-wise fine-tuning scheme could offer a practical way to reach the best performance for the application at hand based on the amount of available data.

Digital image classification with the help of artificial neural network by simple histogram.

PubMed

Dey, Pranab; Banerjee, Nirmalya; Kaur, Rajwant

2016-01-01

Visual image classification is a great challenge to the cytopathologist in routine day-to-day work. Artificial neural network (ANN) may be helpful in this matter. In this study, we have tried to classify digital images of malignant and benign cells in effusion cytology smear with the help of simple histogram data and ANN. A total of 404 digital images consisting of 168 benign cells and 236 malignant cells were selected for this study. The simple histogram data was extracted from these digital images and an ANN was constructed with the help of Neurointelligence software [Alyuda Neurointelligence 2.2 (577), Cupertino, California, USA]. The network architecture was 6-3-1. The images were classified as training set (281), validation set (63), and test set (60). The on-line backpropagation training algorithm was used for this study. A total of 10,000 iterations were done to train the ANN system with the speed of 609.81/s. After the adequate training of this ANN model, the system was able to identify all 34 malignant cell images and 24 out of 26 benign cells. The ANN model can be used for the identification of the individual malignant cells with the help of simple histogram data. This study will be helpful in the future to identify malignant cells in unknown situations.

Real-life efficacy and reliability of training a hearing aid.

PubMed

Keidser, Gitte; Alamudi, Karima

2013-09-01

Commercial trainable hearing aids (HA) (i.e., devices that for a period are adjusted by the user in different acoustic environments and that subsequently with changing environments automatically adapt to the user's preferred settings), are readily available; however, little information exists about the efficacy of training a HA. The purpose of this study was to investigate the efficacy and reliability of training a HA in everyday environments. The participants were 26 hearing-impaired volunteers with a median age of 79 years and an average pure-tone average of 53 dB HL. Test devices were commercial, multimemory, prototype devices that enabled training of the compression characteristics in four frequency bands and in six sound classes. Participants wore the National Acoustic Laboratories nonlinear fitting procedure version 2 prescription for 3 weeks and trained the devices from the prescribed response for 3 weeks, before comparing their trained response with the prescription for 2 weeks. The devices were reset to the prescription, and 19 participants repeated the training and comparison trials. During the comparison trial, participants made daily diary ratings of their satisfaction with the programs, and a structured interview was completed at the end of the comparison trial. The participants displayed different needs for changing the prescription, with more daily adjustments leading to training across more sound classes. Unreliable observations were obtained from 8 participants after each of the test and retest comparison trials. Of the 10 participants who made sufficient changes to the prescription during the first trial, 80% preferred their trained response. The 8 "low trainers" reported no preference, and also reported lower overall satisfaction with the device. Fewer adjustments were made during the repeat trial, resulting in less training. Significant correlations between trained variations were seen for 63% of 19 participants. Of the 10 participants who provided valid data after both comparison trials, those who trained the device consistently generally showed consistent preferences, and vice versa. For those who wanted a change to the prescription, training was mostly effective. Limited data on reliability showed reasonable consistency in training outcomes and preferences. Findings, in particular on reliability, should be verified in larger populations. A guideline on how to clinically manage training with clients is presented.

Neural network pattern recognition of thermal-signature spectra for chemical defense

NASA Astrophysics Data System (ADS)

Carrieri, Arthur H.; Lim, Pascal I.

1995-05-01

We treat infrared patterns of absorption or emission by nerve and blister agent compounds (and simulants of this chemical group) as features for the training of neural networks to detect the compounds' liquid layers on the ground or their vapor plumes during evaporation by external heating. Training of a four-layer network architecture is composed of a backward-error-propagation algorithm and a gradient-descent paradigm. We conduct testing by feed-forwarding preprocessed spectra through the network in a scaled format consistent with the structure of the training-data-set representation. The best-performance weight matrix (spectral filter) evolved from final network training and testing with software simulation trials is electronically transferred to a set of eight artificial intelligence integrated circuits (ICs') in specific modular form (splitting of weight matrices). This form makes full use of all input-output IC nodes. This neural network computer serves an important real-time detection function when it is integrated into pre-and postprocessing data-handling units of a tactical prototype thermoluminescence sensor now under development at the Edgewood Research, Development, and Engineering Center.

Acute physiological responses to different circuit training protocols.

PubMed

Monteiro, A G; Alveno, D A; Prado, M; Monteiro, G A; Ugrinowitsch, C; Aoki, M S; Piçarro, I C

2008-12-01

The purpose of present study was to compare the acute physiological responses to a circuit weight training with the responses to a combined circuit training (weight training and treadmill run). The sample consisted of 25 individuals at an average state of training, 10 men and 15 female, between 18 and 35 year old. There were selected 60 second sets of resistance exercises to the circuit weight training (CWT). Whereas in the combined circuit training (CCT), the subjects spent 30 seconds on the same resistance exercises and 30 seconds running on the treadmill. The rest intervals between the sets lasted 15 seconds. The analysis of variance (ANOVA) with 5% significance level was utilized to the statistical analysis of the results. Comparing circuit training protocols, it was noted that CCT elicits a higher relative and absolute VO2 and energy expenditure values than CWT for both genders (P<0.05). Regarding inter-gender comparison, males showed higher absolute and relative VO2 and absolute energy expenditure values for both CWT and CCT than females (P<0.05). Females showed a significant greater %VO2max value for both CWT and CCT. Due to the experimental conditions used to state both circuit training bouts (CWT and CCT), the VO2 rate found was higher than the values reported by previous studies which used heavier weight lift. CCT seems adequate to produce cardiovascular improvements and greater energy expenditure for both men and women, while CWT group classes are sufficient only for unfit women.

Chronic and acute inspiratory muscle loading augment the effect of a 6-week interval program on tolerance of high-intensity intermittent bouts of running.

PubMed

Tong, Tom K; Fu, Frank H; Eston, Roger; Chung, Pak-Kwong; Quach, Binh; Lu, Kui

2010-11-01

This study examined the hypothesis that chronic (training) and acute (warm-up) loaded ventilatory activities applied to the inspiratory muscles (IM) in an integrated manner would augment the training volume of an interval running program. This in turn would result in additional improvement in the maximum performance of the Yo-Yo intermittent recovery test in comparison with interval training alone. Eighteen male nonprofessional athletes were allocated to either an inspiratory muscle loading (IML) group or control group. Both groups participated in a 6-week interval running program consisting of 3-4 workouts (1-3 sets of various repetitions of selected distance [100-2,400 m] per workout) per week. For the IML group, 4-week IM training (30 inspiratory efforts at 50% maximal static inspiratory pressure [P0] per set, 2 sets·d-1, 6 d·wk-1) was applied before the interval program. Specific IM warm-up (2 sets of 30 inspiratory efforts at 40% P0) was performed before each workout of the program. For the control group, neither IML was applied. In comparison with the control group, the interval training volume as indicated by the repeatability of running bouts at high intensity was approximately 27% greater in the IML group. Greater increase in the maximum performance of the Yo-Yo test (control: 16.9 ± 5.5%; IML: 30.7 ± 4.7% baseline value) was also observed after training. The enhanced exercise performance was partly attributable to the greater reductions in the sensation of breathlessness and whole-body metabolic stress during the Yo-Yo test. These findings show that the combination of chronic and acute IML into a high-intensity interval running program is a beneficial training strategy for enhancing the tolerance to high-intensity intermittent bouts of running.

Potential metabolite markers of schizophrenia.

PubMed

Yang, J; Chen, T; Sun, L; Zhao, Z; Qi, X; Zhou, K; Cao, Y; Wang, X; Qiu, Y; Su, M; Zhao, A; Wang, P; Yang, P; Wu, J; Feng, G; He, L; Jia, W; Wan, C

2013-01-01

Schizophrenia is a severe mental disorder that affects 0.5-1% of the population worldwide. Current diagnostic methods are based on psychiatric interviews, which are subjective in nature. The lack of disease biomarkers to support objective laboratory tests has been a long-standing bottleneck in the clinical diagnosis and evaluation of schizophrenia. Here we report a global metabolic profiling study involving 112 schizophrenic patients and 110 healthy subjects, who were divided into a training set and a test set, designed to identify metabolite markers. A panel of serum markers consisting of glycerate, eicosenoic acid, β-hydroxybutyrate, pyruvate and cystine was identified as an effective diagnostic tool, achieving an area under the receiver operating characteristic curve (AUC) of 0.945 in the training samples (62 patients and 62 controls) and 0.895 in the test samples (50 patients and 48 controls). Furthermore, a composite panel by the addition of urine β-hydroxybutyrate to the serum panel achieved a more satisfactory accuracy, which reached an AUC of 1 in both the training set and the test set. Multiple fatty acids and ketone bodies were found significantly (P<0.01) elevated in both the serum and urine of patients, suggesting an upregulated fatty acid catabolism, presumably resulting from an insufficiency of glucose supply in the brains of schizophrenia patients.

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

PubMed

Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

2017-10-23

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

Principles Underpinning Graded Assessment in VET: A Critique of Prevailing Perceptions

ERIC Educational Resources Information Center

Gillis, Shelley; Griffin, Patrick

2005-01-01

To help achieve national consistency of assessment and reporting in the Australian Vocational Education and Training sector, there is a need to develop a set of national principles for graded performance assessment. This paper challenges a number of prevailing principles from both a theoretical and assessment perspective, namely that grades must…

Some Tests of Response Membership in Acquired Equivalence Classes

ERIC Educational Resources Information Center

Urcuioli, Peter J.; Lionello-DeNolf, Karen; Michalek, Sarah; Vasconcelos, Marco

2006-01-01

Pigeons were trained on many-to-one matching in which pairs of samples, each consisting of a visual stimulus and a distinctive pattern of center-key responding, occasioned the same reinforced comparison choice. Acquired equivalence between the visual and response samples then was evaluated by reinforcing new comparison choices to one set of…

Teacher Performance Assessment Instruments: Plans for Practice Rating.

ERIC Educational Resources Information Center

Capie, William; And Others

This manual consists of lesson plans developed to train data collectors in the use of the Teacher Performance Assessment Instruments (TPAI). Each set of plans was designed for one of three purposes. Lesson plans developed for the Teaching Plans and Materials Instrument (TPM) simulate a portfolio prepared by the teacher. One-day plans developed for…

Generalization of Posture Training to Computer Workstations in an Applied Setting

ERIC Educational Resources Information Center

Sigurdsson, Sigurdur O.; Ring, Brandon M.; Needham, Mick; Boscoe, James H.; Silverman, Kenneth

2011-01-01

Improving employees' posture may decrease the risk of musculoskeletal disorders. The current paper is a systematic replication and extension of Sigurdsson and Austin (2008), who found that an intervention consisting of information, real-time feedback, and self-monitoring improved participant posture at mock workstations. In the current study,…

Eyewitness Evidence: A Trainer's Manual for Law Enforcement. NIJ Special Report.

ERIC Educational Resources Information Center

Department of Justice, Washington, DC. National Inst. of Justice.

This training manual and guide (which consists of a set of 142 slides) were created by experienced law enforcement investigators, prosecutors, defense lawyers, and psychology researchers and are intended to be used by law enforcement trainers to teach law enforcement personnel how to collect accurate and reliable eyewitness evidence. The manual…

Distributed Group Design Process: Lessons Learned.

ERIC Educational Resources Information Center

Eseryel, Deniz; Ganesan, Radha

A typical Web-based training development team consists of a project manager, an instructional designer, a subject-matter expert, a graphic artist, and a Web programmer. The typical scenario involves team members working together in the same setting during the entire design and development process. What happens when the team is distributed, that is…

Lactate response to different volume patterns of power clean.

PubMed

Date, Anand S; Simonson, Shawn R; Ransdell, Lynda B; Gao, Yong

2013-03-01

The ability to metabolize or tolerate lactate and produce power simultaneously can be an important determinant of performance. Current training practices for improving lactate use include high-intensity aerobic activities or a combination of aerobic and resistance training. Excessive aerobic training may have undesired physiological adaptations (e.g., muscle loss, change in fiber types). The role of explosive power training in lactate production and use needs further clarification. We hypothesized that high-volume explosive power movements such as Olympic lifts can increase lactate production and overload lactate clearance. Hence, the purpose of this study was to assess lactate accumulation after the completion of 3 different volume patterns of power cleans. Ten male recreational athletes (age 24.22 ± 1.39 years) volunteered. Volume patterns consisted of 3 sets × 3 repetition maximum (3RM) (low volume [LV]), 3 sets × 6 reps at 80-85% of 3RM (midvolume [MV]), and 3 sets × 9 reps at 70-75% of 3RM (high volume [HV]). Rest period was identical at 2 minutes. Blood samples were collected immediately before and after each volume pattern. The HV resulted in the greatest lactate accumulation (7.43 ± 2.94 mmol·L) vs. (5.27 ± 2.48 and 4.03 ± 1.78 mmol·L in MV and LV, respectively). Mean relative increase in lactate was the highest in HV (356.34%). The findings indicate that lactate production in power cleans is largely associated with volume, determined by number of repetitions, load, and rest interval. High-volume explosive training may impose greater metabolic demands than low-volume explosive training and may improve ability to produce power in the presence of lactate. The role of explosive power training in overloading the lactate clearance mechanism should be examined further, especially for athletes of intermittent sport.

An exercise protocol designed to control energy expenditure for long-term space missions.

PubMed

Matsuo, Tomoaki; Ohkawara, Kazunori; Seino, Satoshi; Shimojo, Nobutake; Yamada, Shin; Ohshima, Hiroshi; Tanaka, Kiyoji; Mukai, Chiaki

2012-08-01

Astronauts experience weight loss during spaceflight. Future space missions require a more efficient exercise program not only to maintain work efficiency, but also to control increased energy expenditure (EE). When discussing issues concerning EE incurred through exercise, excess post-exercise energy expenditure (EPEE) must also be considered. The aim of this study was to compare the total EE, including EPEE, induced by two types of interval cycling protocols with the total EE of a traditional, continuous cycling protocol. There were 10 healthy men, ages 20 to 31 yr, who completed 3 exercise sessions: sprint interval training (SIT) consisting of 7 sets of 30-s cycling at 120% VO2max with a 15-s rest between each bout; high-intensity interval aerobic training (HIAT) consisting of 3 sets of 3-min cycling at 80-90% VO2max with a 2-min active rest at 50% VO2max; and continuous aerobic training (CAT) consisting of 40 min of cycling at 60-65% VO2max. During each session, resting metabolic rate, exercise EE, and a 180-min post-exercise EE were measured. The EPEEs during the SIT, HIAT, and CAT averaged 32 +/- 19, 21 +/- 16, and 13 +/- 13 kcal, and the total EE for an entire exercise/ rest session averaged 109 +/- 20, 182 +/- 17, and 363 +/- 45 kcal, respectively. While the EPEE after the CAT was significantly less than after the SIT, the total EE with the CAT was the greatest of the three. The SIT and HIAT would be potential protocols to control energy expenditure for long space missions.

Genome Properties and Prospects of Genomic Prediction of Hybrid Performance in a Breeding Program of Maize

PubMed Central

Technow, Frank; Schrag, Tobias A.; Schipprack, Wolfgang; Bauer, Eva; Simianer, Henner; Melchinger, Albrecht E.

2014-01-01

Maize (Zea mays L.) serves as model plant for heterosis research and is the crop where hybrid breeding was pioneered. We analyzed genomic and phenotypic data of 1254 hybrids of a typical maize hybrid breeding program based on the important Dent × Flint heterotic pattern. Our main objectives were to investigate genome properties of the parental lines (e.g., allele frequencies, linkage disequilibrium, and phases) and examine the prospects of genomic prediction of hybrid performance. We found high consistency of linkage phases and large differences in allele frequencies between the Dent and Flint heterotic groups in pericentromeric regions. These results can be explained by the Hill–Robertson effect and support the hypothesis of differential fixation of alleles due to pseudo-overdominance in these regions. In pericentromeric regions we also found indications for consistent marker–QTL linkage between heterotic groups. With prediction methods GBLUP and BayesB, the cross-validation prediction accuracy ranged from 0.75 to 0.92 for grain yield and from 0.59 to 0.95 for grain moisture. The prediction accuracy of untested hybrids was highest, if both parents were parents of other hybrids in the training set, and lowest, if none of them were involved in any training set hybrid. Optimizing the composition of the training set in terms of number of lines and hybrids per line could further increase prediction accuracy. We conclude that genomic prediction facilitates a paradigm shift in hybrid breeding by focusing on the performance of experimental hybrids rather than the performance of parental lines in testcrosses. PMID:24850820

Transfer of management training from alternative perspectives.

PubMed

Taylor, Paul J; Russ-Eft, Darlene F; Taylor, Hazel

2009-01-01

One hundred seven management training evaluations were meta-analyzed to compare effect sizes for the transfer of managerial training derived from different rating sources (self, superior, peer, and subordinate) and broken down by both study- and training-related variables. For studies as a whole, and interpersonal management skills training studies in particular, transfer effects based on trainees' self-ratings, and to a lesser extent ratings from their superiors, were largest and most varied across studies. In contrast, transfer effects based on peer ratings, and particularly subordinate ratings, were substantially smaller and more homogeneous. This pattern was consistent across different sources of studies, features of evaluation design, and within a subset of 14 studies that each included all 4 rating sources. Across most rating sources, transfer of training was greatest for studies conducted in nonmilitary settings, when raters were likely to have known whether the manager being rated had attended training, when criteria were targeted to training content, when training content was derived from an analysis of tasks and skill requirements, and when training included opportunities for practice. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Intelligent Predictor of Energy Expenditure with the Use of Patch-Type Sensor Module

PubMed Central

Li, Meina; Kwak, Keun-Chang; Kim, Youn-Tae

2012-01-01

This paper is concerned with an intelligent predictor of energy expenditure (EE) using a developed patch-type sensor module for wireless monitoring of heart rate (HR) and movement index (MI). For this purpose, an intelligent predictor is designed by an advanced linguistic model (LM) with interval prediction based on fuzzy granulation that can be realized by context-based fuzzy c-means (CFCM) clustering. The system components consist of a sensor board, the rubber case, and the communication module with built-in analysis algorithm. This sensor is patched onto the user's chest to obtain physiological data in indoor and outdoor environments. The prediction performance was demonstrated by root mean square error (RMSE). The prediction performance was obtained as the number of contexts and clusters increased from 2 to 6, respectively. Thirty participants were recruited from Chosun University to take part in this study. The data sets were recorded during normal walking, brisk walking, slow running, and jogging in an outdoor environment and treadmill running in an indoor environment, respectively. We randomly divided the data set into training (60%) and test data set (40%) in the normalized space during 10 iterations. The training data set is used for model construction, while the test set is used for model validation. The experimental results revealed that the prediction error on treadmill running simulation was improved by about 51% and 12% in comparison to conventional LM for training and checking data set, respectively. PMID:23202166

Spelling and Meaning of Compounds in the Early School Years through Classroom Games: An Intervention Study.

PubMed

Tsesmeli, Styliani N

2017-01-01

The study aimed to evaluate the intervention effects on spelling and meaning of compounds by Greek students via group board games in classroom settings. The sample consisted of 60 pupils, who were attending the first and second grade of two primary schools in Greece. Each grade-class was divided into an intervention ( N = 29 children) and a control group ( N = 31 children). Before intervention, groups were evaluated by standardized tests of reading words/pseudowords, spelling words, and vocabulary. Students were also assessed on compound knowledge by a word analogy task, a meaning task and a spelling task. The experimental design of the intervention included a pre-test, a training program, and a post-test. The pre- and post-assessments consisted of the spelling and the meaning tasks entailing equally morphologically transparent and opaque compounds. The training program was based on word families ( N = 10 word families, 56 trained items, 5 sessions) and aimed to offer instruction of morphological decomposition and meaning of words. The findings showed that training was effective in enhancing the spelling and most notably the meaning of compounds. A closer inspection of intervention data in terms of morphological transparency, revealed that training group of first graders improved significantly both on transparent and opaque compounds, while the degree of gains was larger on opaque items for the second graders. These findings are consistent with the experimental literature and particularly optimistic for the literacy enhancement of typically developing children in regular classrooms.

Spelling and Meaning of Compounds in the Early School Years through Classroom Games: An Intervention Study

PubMed Central

Tsesmeli, Styliani N.

2017-01-01

The study aimed to evaluate the intervention effects on spelling and meaning of compounds by Greek students via group board games in classroom settings. The sample consisted of 60 pupils, who were attending the first and second grade of two primary schools in Greece. Each grade-class was divided into an intervention (N = 29 children) and a control group (N = 31 children). Before intervention, groups were evaluated by standardized tests of reading words/pseudowords, spelling words, and vocabulary. Students were also assessed on compound knowledge by a word analogy task, a meaning task and a spelling task. The experimental design of the intervention included a pre-test, a training program, and a post-test. The pre- and post-assessments consisted of the spelling and the meaning tasks entailing equally morphologically transparent and opaque compounds. The training program was based on word families (N = 10 word families, 56 trained items, 5 sessions) and aimed to offer instruction of morphological decomposition and meaning of words. The findings showed that training was effective in enhancing the spelling and most notably the meaning of compounds. A closer inspection of intervention data in terms of morphological transparency, revealed that training group of first graders improved significantly both on transparent and opaque compounds, while the degree of gains was larger on opaque items for the second graders. These findings are consistent with the experimental literature and particularly optimistic for the literacy enhancement of typically developing children in regular classrooms. PMID:29238316

Advancing Continence in Typically Developing Children: Adapting the Procedures of Foxx and Azrin for Primary Care.

PubMed

Warzak, William J; Forcino, Stacy S; Sanberg, Sela Ann; Gross, Amy C

2016-01-01

To (1) identify and summarize procedures of Foxx and Azrin's classic toilet training protocol that continue to be used in training typically developing children and (2) adapt recent findings with the original Foxx and Azrin procedures to inform practical suggestions for the rapid toilet training of typically developing children in the primary care setting. Literature searches of PsychINFO and MEDLINE databases used the search terms "(toilet* OR potty* AND train*)." Selection criteria were only peer-reviewed experimental articles that evaluated intensive toilet training with typically developing children. Exclusion criteria were (1) nonpeer reviewed research, (2) studies addressing encopresis and/or enuresis, (3) studies excluding typically developing children, and (4) studies evaluating toilet training during infancy. In addition to the study of Foxx and Azrin, only 4 publications met the above criteria. Toilet training procedures from each article were reviewed to determine which toilet training methods were similar to components described by Foxx and Azrin. Common training elements include increasing the frequency of learning opportunities through fluid loading and having differential consequences for being dry versus being wet and for voiding in the toilet versus elsewhere. There is little research on intensive toilet training of typically developing children. Practice sits and positive reinforcement for voids in the toilet are commonplace, consistent with the Foxx and Azrin protocol, whereas positive practice as a corrective procedure for wetting accidents often is omitted. Fluid loading and differential consequences for being dry versus being wet and for voiding in the toilet also are suggested procedures, consistent with the Foxx and Azrin protocol.

Data presentation techniques for rotating machinery malfunction diagnosis

NASA Technical Reports Server (NTRS)

Spettel, T.

1985-01-01

Baseline steady state data is excellent for documentation of vibration signals at normal operating conditions. Assuming that a set of initial data was acquired with the machinery in a good state of repair, any future changes or deterioration in mechanical condition can be easily compared to the baseline information. Often this type of comparison will yield sufficient information for evaluation of the problem. However, many malfunctions require the analysis of transient data in order to identify the malfunction. Steady-state data formats consist of: Time Base Waveform, Orbit, Spectrum. Transient data formats consist of: Polar, Bode, Cascade. Our objective is to demonstrate the use of the above formats to diagnose a machine malfunction. A turbine-driven compressor train is chosen as an example. The machine train outline drawing is shown.

Combined Annual Report to Congress on Standardization of Equipment with NATO Members and Cooperative Research and Development Projects with Allied Countries

DTIC Science & Technology

1990-06-01

Contamination Marking Set This set is designed for marking areas contaminated with nuclear, biological and chemical (NBC) agents. It consists of a metal ...program, formerly the Heavy Forces Modernization (HFM) program. In March 1990, the Army Systems Acquisition Review Council (ASARC) reviewed the ASM...AUTOKO) prior to initial fielding of MSE in Europe this year, interoperability training was conducted at Grafenwoehr , Germany, from 30 January to 1

Balanced VS Imbalanced Training Data: Classifying Rapideye Data with Support Vector Machines

NASA Astrophysics Data System (ADS)

Ustuner, M.; Sanli, F. B.; Abdikan, S.

2016-06-01

The accuracy of supervised image classification is highly dependent upon several factors such as the design of training set (sample selection, composition, purity and size), resolution of input imagery and landscape heterogeneity. The design of training set is still a challenging issue since the sensitivity of classifier algorithm at learning stage is different for the same dataset. In this paper, the classification of RapidEye imagery with balanced and imbalanced training data for mapping the crop types was addressed. Classification with imbalanced training data may result in low accuracy in some scenarios. Support Vector Machines (SVM), Maximum Likelihood (ML) and Artificial Neural Network (ANN) classifications were implemented here to classify the data. For evaluating the influence of the balanced and imbalanced training data on image classification algorithms, three different training datasets were created. Two different balanced datasets which have 70 and 100 pixels for each class of interest and one imbalanced dataset in which each class has different number of pixels were used in classification stage. Results demonstrate that ML and NN classifications are affected by imbalanced training data in resulting a reduction in accuracy (from 90.94% to 85.94% for ML and from 91.56% to 88.44% for NN) while SVM is not affected significantly (from 94.38% to 94.69%) and slightly improved. Our results highlighted that SVM is proven to be a very robust, consistent and effective classifier as it can perform very well under balanced and imbalanced training data situations. Furthermore, the training stage should be precisely and carefully designed for the need of adopted classifier.

An algorithm for testing the efficient market hypothesis.

PubMed

Boboc, Ioana-Andreea; Dinică, Mihai-Cristian

2013-01-01

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH).

An Algorithm for Testing the Efficient Market Hypothesis

PubMed Central

Boboc, Ioana-Andreea; Dinică, Mihai-Cristian

2013-01-01

The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI) and Filter that gives buying and selling recommendations to investors. The algorithm optimizes the strategies by dynamically searching for parameters that improve profitability in the training period. The best sets of rules are then applied on the testing period. The results show inconsistency in finding a set of trading rules that performs well in both periods. Strategies that achieve very good returns in the training period show difficulty in returning positive results in the testing period, this being consistent with the efficient market hypothesis (EMH). PMID:24205148

Transfer to intermediate forms following concept discrimination by pigeons: chimeras and morphs.

PubMed Central

Ghosh, Natasha; Lea, Stephen E G; Noury, Malia

2004-01-01

Two experiments examined pigeons' generalization to intermediate forms following training of concept discriminations. In Experiment 1, the training stimuli were sets of images of dogs and cats, and the transfer stimuli were head/body chimeras, which humans tend to categorize more readily in terms of the head part rather than the body part. In Experiment 2, the training stimuli were sets of images of heads of dogs and cats, and the intermediate stimuli were computer-generated morphs. In both experiments, pigeons learned the concept discrimination quickly and generalized with some decrement to novel instances of the categories. In both experiments, transfer tests were carried out with intermediate forms generated from both familiar and novel exemplars of the training sets. In Experiment 1, the pigeons' transfer performance, unlike that of human infants exposed to similar stimuli, was best predicted by the body part of the stimulus when the chimeras were formed from familiar exemplars. Spatial frequency analysis of the stimuli showed that the body parts were richer in high spatial frequencies than the head parts, so these data are consistent with the hypothesis that categorization is more dependent on local stimulus features in pigeons than in humans. There was no corresponding trend when the chimeras were formed from novel exemplars. In Experiment 2, when morphs of training stimuli were used, response rates declined smoothly as the proportion of the morph contributed by the positive stimulus fell, although results with morphs of novel stimuli were again less orderly. PMID:15540501

Theory-Informed Research Training and Mentoring of Underrepresented Early-Career Faculty at Teaching-Intensive Institutions: The Obesity Health Disparities PRIDE Program.

PubMed

Beech, Bettina M; Bruce, Marino A; Thorpe, Roland J; Heitman, Elizabeth; Griffith, Derek M; Norris, Keith C

2018-01-01

Mentoring has been consistently identified as an important element for career advancement in many biomedical and health professional disciplines and has been found to be critical for success and promotion in academic settings. Early-career faculty from groups underrepresented in biomedical research, however, are less likely to have mentors, and in general, receive less mentoring than their majority-group peers, particularly among those employed in teaching-intensive institutions. This article describes Obesity Health Disparities (OHD) PRIDE, a theoretically and conceptually based research training and mentoring program designed for early-career faculty who trained or are employed at Historically Black Colleges and Universities (HBCUs).

Statistical learning in reading: variability in irrelevant letters helps children learn phonics skills.

PubMed

Apfelbaum, Keith S; Hazeltine, Eliot; McMurray, Bob

2013-07-01

Early reading abilities are widely considered to derive in part from statistical learning of regularities between letters and sounds. Although there is substantial evidence from laboratory work to support this, how it occurs in the classroom setting has not been extensively explored; there are few investigations of how statistics among letters and sounds influence how children actually learn to read or what principles of statistical learning may improve learning. We examined 2 conflicting principles that may apply to learning grapheme-phoneme-correspondence (GPC) regularities for vowels: (a) variability in irrelevant units may help children derive invariant relationships and (b) similarity between words may force children to use a deeper analysis of lexical structure. We trained 224 first-grade students on a small set of GPC regularities for vowels, embedded in words with either high or low consonant similarity, and tested their generalization to novel tasks and words. Variability offered a consistent benefit over similarity for trained and new words in both trained and new tasks.

Effect of the adapted Virtual Reality cognitive training program among Chinese older adults with chronic schizophrenia: a pilot study.

PubMed

Chan, Christopher L F; Ngai, Elena K Y; Leung, Paul K H; Wong, Stephen

2010-06-01

To examine the effect of the adapted virtual reality cognitive training program in older adults with chronic schizophrenia. Older adults with chronic schizophrenia were recruited from a long-stay care setting and were randomly assigned into intervention (n = 12) and control group (n = 15). The intervention group received 10-session of VR program that consisted of 2 VR activities using IREX. The control group attended the usual programs in the setting. After the 10-session intervention, older adults with chronic schizophrenia preformed significantly better than control in overall cognitive function (p .000), and in two cognitive subscales: repetition (p .001) and memory (p .040). These participants engaged in the VR activities volitionally. No problem of cybersickness was observed. The results of the current study indicate that engaging in the adapted virtual reality cognitive training program offers the potential for significant gains in cognitive function of the older adults with chronic schizophrenia.

Improving reflectance reconstruction from tristimulus values by adaptively combining colorimetric and reflectance similarities

NASA Astrophysics Data System (ADS)

Cao, Bin; Liao, Ningfang; Li, Yasheng; Cheng, Haobo

2017-05-01

The use of spectral reflectance as fundamental color information finds application in diverse fields related to imaging. Many approaches use training sets to train the algorithm used for color classification. In this context, we note that the modification of training sets obviously impacts the accuracy of reflectance reconstruction based on classical reflectance reconstruction methods. Different modifying criteria are not always consistent with each other, since they have different emphases; spectral reflectance similarity focuses on the deviation of reconstructed reflectance, whereas colorimetric similarity emphasizes human perception. We present a method to improve the accuracy of the reconstructed spectral reflectance by adaptively combining colorimetric and spectral reflectance similarities. The different exponential factors of the weighting coefficients were investigated. The spectral reflectance reconstructed by the proposed method exhibits considerable improvements in terms of the root-mean-square error and goodness-of-fit coefficient of the spectral reflectance errors as well as color differences under different illuminants. Our method is applicable to diverse areas such as textiles, printing, art, and other industries.

Development of the Human Factors Skills for Healthcare Instrument: a valid and reliable tool for assessing interprofessional learning across healthcare practice settings.

PubMed

Reedy, Gabriel B; Lavelle, Mary; Simpson, Thomas; Anderson, Janet E

2017-10-01

A central feature of clinical simulation training is human factors skills, providing staff with the social and cognitive skills to cope with demanding clinical situations. Although these skills are critical to safe patient care, assessing their learning is challenging. This study aimed to develop, pilot and evaluate a valid and reliable structured instrument to assess human factors skills, which can be used pre- and post-simulation training, and is relevant across a range of healthcare professions. Through consultation with a multi-professional expert group, we developed and piloted a 39-item survey with 272 healthcare professionals attending training courses across two large simulation centres in London, one specialising in acute care and one in mental health, both serving healthcare professionals working across acute and community settings. Following psychometric evaluation, the final 12-item instrument was evaluated with a second sample of 711 trainees. Exploratory factor analysis revealed a 12-item, one-factor solution with good internal consistency (α=0.92). The instrument had discriminant validity, with newly qualified trainees scoring significantly lower than experienced trainees ( t (98)=4.88, p<0.001) and was sensitive to change following training in acute and mental health settings, across professional groups (p<0.001). Confirmatory factor analysis revealed an adequate model fit (RMSEA=0.066). The Human Factors Skills for Healthcare Instrument provides a reliable and valid method of assessing trainees' human factors skills self-efficacy across acute and mental health settings. This instrument has the potential to improve the assessment and evaluation of human factors skills learning in both uniprofessional and interprofessional clinical simulation training.

A microsensor array for quantification of lubricant contaminants using a back propagation artificial neural network

NASA Astrophysics Data System (ADS)

Zhu, Xiaoliang; Du, Li; Liu, Bendong; Zhe, Jiang

2016-06-01

We present a method based on an electrochemical sensor array and a back propagation artificial neural network for detection and quantification of four properties of lubrication oil, namely water (0, 500 ppm, 1000 ppm), total acid number (TAN) (13.1, 13.7, 14.4, 15.6 mg KOH g-1), soot (0, 1%, 2%, 3%) and sulfur content (1.3%, 1.37%, 1.44%, 1.51%). The sensor array, consisting of four micromachined electrochemical sensors, detects the four properties with overlapping sensitivities. A total set of 36 oil samples containing mixtures of water, soot, and sulfuric acid with different concentrations were prepared for testing. The sensor array’s responses were then divided to three sets: training sets (80% data), validation sets (10%) and testing sets (10%). Several back propagation artificial neural network architectures were trained with the training and validation sets; one architecture with four input neurons, 50 and 5 neurons in the first and second hidden layer, and four neurons in the output layer was selected. The selected neural network was then tested using the four sets of testing data (10%). Test results demonstrated that the developed artificial neural network is able to quantitatively determine the four lubrication properties (water, TAN, soot, and sulfur content) with a maximum prediction error of 18.8%, 6.0%, 6.7%, and 5.4%, respectively, indicting a good match between the target and predicted values. With the developed network, the sensor array could be potentially used for online lubricant oil condition monitoring.

Seismogram offers insight into Oklahoma City bombing

NASA Astrophysics Data System (ADS)

Holzer, Thomas L.; Fletcher, Joe B.; Fuis, Gary S.; Ryberg, Trond; Brocher, Thomas M.; Dietel, Christopher M.

The terrorist bombing of the Alfred P. Murrah Federal Building in Oklahoma City on April 19, 1995, generated seismic waves that were recorded on two permanent seismographs about 7 and 26 km away from the bombing. The seismogram recorded at 26 km shows two low-frequency wave trains, discrete sets of oscillatory signals, that begin about 10 s apart. Public release of this record prompted speculation that each wave train was caused by a different energy source. On May 23, 1995, the U.S. Geological Survey monitored the demolition of the bomb-ravaged Federal Building with portable seismographs (Figure 1). Two wave trains were picked up again. The recordings indicate that the wave trains during both the bombing and demolition represent seismic waves traveling at different velocities. We conclude that the two wave trains recorded during the bombing are consistent with a single impulsive energy source.

The Structured Interview and Interviewer Training in the Admissions Process

PubMed Central

Cox, Wendy C.; White-Harris, Carla; Blalock, Susan J.

2007-01-01

Objectives To determine the extent to which the structured interview is used in the PharmD admissions process in US colleges and schools of pharmacy, and the prevalence and content of interviewer training. Methods A survey instrument consisting of 7 questions regarding interviews and interviewer training was sent to 92 colleges and schools of pharmacy in the United States that were accredited or seeking accreditation. Results Sixty survey instruments (65% response rate) were returned. The majority of the schools that responded (80%) used interviews as part of the PharmD admissions process. Of the schools that used an interview as part of the admissions process, 86% provided some type of interviewer training and 13% used a set of predefined questions in admissions interviews. Conclusions Most colleges and schools of pharmacy use some components of the structured interview in the PharmD admissions process; however, training for interviewers varies widely among colleges and schools of pharmacy. PMID:17998980

Portable detection system of vegetable oils based on laser induced fluorescence

NASA Astrophysics Data System (ADS)

Zhu, Li; Zhang, Yinchao; Chen, Siying; Chen, He; Guo, Pan; Mu, Taotao

2015-11-01

Food safety, especially edible oils, has attracted more and more attention recently. Many methods and instruments have emerged to detect the edible oils, which include oils classification and adulteration. It is well known than the adulteration is based on classification. Then, in this paper, a portable detection system, based on laser induced fluorescence, is proposed and designed to classify the various edible oils, including (olive, rapeseed, walnut, peanut, linseed, sunflower, corn oils). 532 nm laser modules are used in this equipment. Then, all the components are assembled into a module (100*100*25mm). A total of 700 sets of fluorescence data (100 sets of each type oil) are collected. In order to classify different edible oils, principle components analysis and support vector machine have been employed in the data analysis. The training set consisted of 560 sets of data (80 sets of each oil) and the test set consisted of 140 sets of data (20 sets of each oil). The recognition rate is up to 99%, which demonstrates the reliability of this potable system. With nonintrusive and no sample preparation characteristic, the potable system can be effectively applied for food detection.

Submaximal exercise training, more than dietary selenium supplementation, improves antioxidant status and ameliorates exercise-induced oxidative damage to skeletal muscle in young equine athletes.

PubMed

White, S H; Warren, L K

2017-02-01

Exercise is associated with increased production of reactive oxygen species (ROS) as metabolism is upregulated to fuel muscle activity. If antioxidant systems become overwhelmed, ROS can negatively affect health and performance. Adaptation to exercise through regular training has been shown to improve defense against oxidative insult. Given selenium's role as an antioxidant, we hypothesized that increased Se intake would further enhance skeletal muscle adaptations to training. Quarter Horse yearlings (18 ± 0.2 mo; 402 ± 10 kg) were randomly assigned to receive either 0.1 or 0.3 mg Se/kg DM and placed in either an untrained or a trained (30 min walk-trot-canter, 4 d/wk) group for 14 wk. Phase 1 (wk 1 to 8) consisted of 4 treatments: trained and fed 0.1 mg Se/kg DM through wk 14 (CON-TR; n = 10), trained and fed 0.3 mg Se/kg DM through wk 14 (HIGH-TR; n = 10), untrained and fed 0.1 mg Se/kg DM through wk 14 (CON-UN; n = 5), or untrained and fed 0.3 mg Se/kg DM through wk 14 (HIGH-UN; n = 5). During Phase 2 (wk 9 to 14), dietary Se level in half of the trained horses was reversed, resulting in 6 treatments: CON-TR (n = 5), trained and fed 0.1 mg/kg Se in Phase 1 and then switched to 0.3 mg/kg Se for Phase 2 (ADD-TR; n = 5), trained and fed 0.3 mg/kg Se in Phase 1 and then switched to 0.1 mg/kg Se for Phase 2 (DROP-TR; n = 5), HIGH-TR (n = 5), CON-UN (n = 5), or HIGH-UN (n = 5). All horses underwent a 120-min submaximal exercise test (SET) at the end of Phase 1 (SET 1) and 2 (SET 2). Blood samples and biopsies from the middle gluteal muscle were collected before and after each phase of the study and in response to each SET and analyzed for markers of oxidative damage and antioxidant enzyme activity. In both phases, serum Se was higher (P < 0.0001) when horses received a diet with 0.3 than 0.1 mg Se/kg DM. Throughout the 14-wk study, resting activities of muscle glutathione peroxidase (GPx; P = 0.004) and superoxide dismutase (SOD; P = 0.06) were greater in trained horses than in untrained horses. In response to SET 1, serum creatine kinase (CK) activity was lower in trained horses than in untrained horses (P < 0.0001), indicating less muscle damage, but plasma lipid hydroperoxides (LPO) and muscle GPx and SOD activities were unaffected by training or Se. In response to SET 2, trained horses had greater muscle SOD activity (P = 0.0002) and lower serum CK activity (P = 0.003) and showed a trend for lower plasma LPO (P = 0.09) and muscle malondialdehyde (P = 0.09) than untrained horses. Muscle GPx activity did not change in response to SET 2 and was unaffected by training or Se. Results indicate that exercise training lessens muscle damage and improves antioxidant defense following an acute bout of prolonged exercise and was not further enhanced by feeding Se above the NRC requirement.

Digital image classification with the help of artificial neural network by simple histogram

PubMed Central

Dey, Pranab; Banerjee, Nirmalya; Kaur, Rajwant

2016-01-01

Background: Visual image classification is a great challenge to the cytopathologist in routine day-to-day work. Artificial neural network (ANN) may be helpful in this matter. Aims and Objectives: In this study, we have tried to classify digital images of malignant and benign cells in effusion cytology smear with the help of simple histogram data and ANN. Materials and Methods: A total of 404 digital images consisting of 168 benign cells and 236 malignant cells were selected for this study. The simple histogram data was extracted from these digital images and an ANN was constructed with the help of Neurointelligence software [Alyuda Neurointelligence 2.2 (577), Cupertino, California, USA]. The network architecture was 6-3-1. The images were classified as training set (281), validation set (63), and test set (60). The on-line backpropagation training algorithm was used for this study. Result: A total of 10,000 iterations were done to train the ANN system with the speed of 609.81/s. After the adequate training of this ANN model, the system was able to identify all 34 malignant cell images and 24 out of 26 benign cells. Conclusion: The ANN model can be used for the identification of the individual malignant cells with the help of simple histogram data. This study will be helpful in the future to identify malignant cells in unknown situations. PMID:27279679

Effect of rest-pause vs. traditional bench press training on muscle strength, electromyography, and lifting volume in randomized trial protocols.

PubMed

Korak, J Adam; Paquette, Max R; Brooks, Justin; Fuller, Dana K; Coons, John M

2017-09-01

Rest-pause (4-s unloaded rest between repetitions) training effects on one repetition maximum (1 RM), lifting volume, and neural activation via electromyography (EMG) are currently vague in the literature and can benefit strength and conditioning professionals for resistance training programme design. Therefore, this study compared 1 RM, neural activation via (EMG), and volume differences between rest-pause vs. traditional resistance training. Trained males (N = 20) were randomly assigned to either a rest-pause or a traditional training group. Pre- and post-1 RM testing was recorded. Training sessions were completed twice a week for 4 weeks and consisted of four sets of bench press to volitional fatigue at 80% of pre-test 1 RM with a 2-min rest between sets. Total volume completed was recorded on each training day. Neural activation of the pectoralis major was measured on the first and last training days. A two-way repeated-measures ANOVA indicated both groups significantly increased their 1 RMs following the 4-week training protocol (p < .05). However, no significant differences were found in 1 RM and neural activation between the two groups (p > .05). An independent samples t test indicated that total volume lifted was significantly higher for the rest-pause group (56,778 vs. 38,315 lbs; p < .05) throughout the protocol and independently during weeks 2, 3, and 4. While strength and neural activation changes did not differ between groups, both increased 1 RMs and the rest-pause group achieved greater increases in volume than the traditional group. If volume is the focus of training, the rest-pause method should be utilized.

Effects of resistance and stretching training programmes on the viscoelastic properties of human tendon structures in vivo

PubMed Central

Kubo, Keitaro; Kanehisa, Hiroaki; Fukunaga, Tetsuo

2002-01-01

The present study examined whether resistance and stretching training programmes altered the viscoelastic properties of human tendon structures in vivo. Eight subjects completed 8 weeks (4 days per week) of resistance training which consisted of unilateral plantar flexion at 70 % of one repetition maximum with 10 repetitions per set (5 sets per day). They performed resistance training (RT) on one side and resistance training and static stretching training (RST; 10 min per day, 7 days per week) on the other side. Before and after training, the elongation of the tendon structures in the medial gastrocnemius muscle was directly measured using ultrasonography, while the subjects performed ramp isometric plantar flexion up to the voluntary maximum, followed by a ramp relaxation. The relationship between estimated muscle force (Fm) and tendon elongation (L) was fitted to a linear regression, the slope of which was defined as stiffness. The hysteresis was calculated as the ratio of the area within the Fm-L loop to the area beneath the load portion of the curve. The stiffness increased significantly by 18.8 ± 10.4 % for RT and 15.3 ± 9.3 % for RST. There was no significant difference in the relative increase of stiffness between RT and RST. The hysteresis, on the other hand, decreased 17 ± 20 % for RST, but was unchanged for RT. These results suggested that the resistance training increased the stiffness of tendon structures as well as muscle strength and size, and the stretching training affected the viscosity of tendon structures but not the elasticity. PMID:11773330

A Selection System and Catalog for Instructional Media and Devices.

ERIC Educational Resources Information Center

Boucher, Brian G.; And Others

A system is presented which facilitates the selection of training media and devices based on the requirements of specific learning objectives. The system consists of the use of a set of descriptive parameters which are common to both learning objectives and media. The system allows the essential intent of learning objectives to be analyzed in…

NeuroRecovery Network provides standardization of locomotor training for persons with incomplete spinal cord injury.

PubMed

Morrison, Sarah A; Forrest, Gail F; VanHiel, Leslie R; Davé, Michele; D'Urso, Denise

2012-09-01

To illustrate the continuity of care afforded by a standardized locomotor training program across a multisite network setting within the Christopher and Dana Reeve Foundation NeuroRecovery Network (NRN). Single patient case study. Two geographically different hospital-based outpatient facilities. This case highlights a 25-year-old man diagnosed with C4 motor incomplete spinal cord injury with American Spinal Injury Association Impairment Scale grade D. Standardized locomotor training program 5 sessions per week for 1.5 hours per session, for a total of 100 treatment sessions, with 40 sessions at 1 center and 60 at another. Ten-meter walk test and 6-minute walk test were assessed at admission and discharge across both facilities. For each of the 100 treatment sessions percent body weight support, average, and maximum treadmill speed were evaluated. Locomotor endurance, as measured by the 6-minute walk test, and overground gait speed showed consistent improvement from admission to discharge. Throughout training, the patient decreased the need for body weight support and was able to tolerate faster treadmill speeds. Data indicate that the patient continued to improve on both treatment parameters and walking function. Standardization across the NRN centers provided a mechanism for delivering consistent and reproducible locomotor training programs across 2 facilities without disrupting training or recovery progression. Copyright © 2012 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Effects of a Strength Training Session After an Exercise Inducing Muscle Damage on Recovery Kinetics.

PubMed

Abaïdia, Abd-Elbasset; Delecroix, Barthélémy; Leduc, Cédric; Lamblin, Julien; McCall, Alan; Baquet, Georges; Dupont, Grégory

2017-01-01

Abaïdia, A-E, Delecroix, B, Leduc, C, Lamblin, J, McCall, A, Baquet, G, and Dupont, G. Effects of a strength training session after an exercise inducing muscle damage on recovery kinetics. J Strength Cond Res 31(1): 115-125, 2017-The purpose of this study was to investigate the effects of an upper-limb strength training session the day after an exercise inducing muscle damage on recovery of performance. In a randomized crossover design, subjects performed the day after the exercise, on 2 separate occasions (passive vs. active recovery conditions) a single-leg exercise (dominant in one condition and nondominant in the other condition) consisting of 5 sets of 15 eccentric contractions of the knee flexors. Active recovery consisted of performing an upper-body strength training session the day after the exercise. Creatine kinase, hamstring strength, and muscle soreness were assessed immediately and 20, 24, and 48 hours after exercise-induced muscle damage. The upper-body strength session, after muscle-damaging exercise accelerated the recovery of slow concentric force (effect size = 0.65; 90% confidence interval = -0.06 to 1.32), but did not affect the recovery kinetics for the other outcomes. The addition of an upper-body strength training session the day after muscle-damaging activity does not negatively affect the recovery kinetics. Upper-body strength training may be programmed the day after a competition.

Cervical cancer screening and treatment training course in El Salvador: experience and lessons learned.

PubMed

Masch, Rachel; Ditzian, Lauren R; April, Ayana K; Maza, Mauricio; Peralta, Ethel; Cremer, Miriam L

2011-09-01

Visual inspection with acetic acid (VIA) is a simple, low-cost alternative to traditional Pap smears that could greatly benefit the amount of screening and treatment available in low-resource areas, such as rural El Salvador. The objective of this study was to train Salvadoran health providers in VIA and cryotherapy using a week-long competency course. Health providers participated in the VIA training course, which consisted of 1 half-day of didactics, followed by 4 and 1 half days of clinical training. Pretests and posttests were administered. A 1-day didactic refresher course was administered to assess the quality of services being provided. Sixty-eight nurses and physicians completed the training course. Each trainee screened approximately 120 women and performed, on average, seven cryotherapy treatments. The average trainee improved his or her score by 15% on the theoretical test and 16.7% on the image test. At the completion of the 1-day refresher, average test scores were the highest among all the courses. The final assessment was based on 41 providers. The course proved a successful tool for training healthcare providers in methods of cervical cancer screening and treatment. The course is replicable in other low-resource settings in different countries. It also provided trainees with the opportunity to adapt their clinical skills in their realistic work setting.

Evaluation of a Serum Lung Cancer Biomarker Panel.

PubMed

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results.

Evaluation of a Serum Lung Cancer Biomarker Panel

PubMed Central

Mazzone, Peter J; Wang, Xiao-Feng; Han, Xiaozhen; Choi, Humberto; Seeley, Meredith; Scherer, Richard; Doseeva, Victoria

2018-01-01

Background: A panel of 3 serum proteins and 1 autoantibody has been developed to assist with the detection of lung cancer. We aimed to validate the accuracy of the biomarker panel in an independent test set and explore the impact of adding a fourth serum protein to the panel, as well as the impact of combining molecular and clinical variables. Methods: The training set of serum samples was purchased from commercially available biorepositories. The testing set was from a biorepository at the Cleveland Clinic. All lung cancer and control subjects were >50 years old and had smoked a minimum of 20 pack-years. A panel of biomarkers including CEA (carcinoembryonic antigen), CYFRA21-1 (cytokeratin-19 fragment 21-1), CA125 (carbohydrate antigen 125), HGF (hepatocyte growth factor), and NY-ESO-1 (New York esophageal cancer-1 antibody) was measured using immunoassay techniques. The multiple of the median method, multivariate logistic regression, and random forest modeling was used to analyze the results. Results: The training set consisted of 604 patient samples (268 with lung cancer and 336 controls) and the testing set of 400 patient samples (155 with lung cancer and 245 controls). With a threshold established from the training set, the sensitivity and specificity of both the 4- and 5-biomarker panels on the testing set was 49% and 96%, respectively. Models built on the testing set using only clinical variables had an area under the receiver operating characteristic curve of 0.68, using the biomarker panel 0.81 and by combining clinical and biomarker variables 0.86. Conclusions: This study validates the accuracy of a panel of proteins and an autoantibody in a population relevant to lung cancer detection and suggests a benefit to combining clinical features with the biomarker results. PMID:29371783

Automatic threshold selection for multi-class open set recognition

NASA Astrophysics Data System (ADS)

Scherreik, Matthew; Rigling, Brian

2017-05-01

Multi-class open set recognition is the problem of supervised classification with additional unknown classes encountered after a model has been trained. An open set classifer often has two core components. The first component is a base classifier which estimates the most likely class of a given example. The second component consists of open set logic which estimates if the example is truly a member of the candidate class. Such a system is operated in a feed-forward fashion. That is, a candidate label is first estimated by the base classifier, and the true membership of the example to the candidate class is estimated afterward. Previous works have developed an iterative threshold selection algorithm for rejecting examples from classes which were not present at training time. In those studies, a Platt-calibrated SVM was used as the base classifier, and the thresholds were applied to class posterior probabilities for rejection. In this work, we investigate the effectiveness of other base classifiers when paired with the threshold selection algorithm and compare their performance with the original SVM solution.

[Formula: see text]Official Position of the American Academy of Clinical Neuropsychology (AACN): Guidelines for Practicum Training in Clinical Neuropsychology.

PubMed

Nelson, Aaron P; Roper, Brad L; Slomine, Beth S; Morrison, Chris; Greher, Michael R; Janusz, Jennifer; Larson, Jennifer C; Meadows, Mary-Ellen; Ready, Rebecca E; Rivera Mindt, Monica; Whiteside, Doug M; Willment, Kim; Wodushek, Thomas R

2015-01-01

Practical experience is central to the education and training of neuropsychologists, beginning in graduate school and extending through postdoctoral fellowship. However, historically, little attention has been given to the structure and requirements of practicum training in clinical neuropsychology. A working group of senior-level neuropsychologists, as well as a current postdoctoral fellow, all from a diverse range of settings (The AACN Practicum Guidelines Workgroup), was formed to propose guidelines for practicum training in clinical neuropsychology. The Workgroup reviewed relevant literature and sought input from professional organizations involved in education and training in neuropsychology. The proposed guidelines provide a definition of practicum training in clinical neuropsychology, detail entry and exit criteria across competencies relevant to practicum training in clinical neuropsychology, and discuss the relationship between doctoral training programs and practicum training sites. The proposed guidelines also provide a methodology for competency-based evaluation of clinical neuropsychology practicum trainees and outline characteristics and features that are integral to an effective training environment. Although the guidelines discussed below may not be implemented in their entirety across all clinical neuropsychology practicum training sites, they are consistent with the latest developments in competency-based education.

Building peace through participatory health training: a case from Cambodia.

PubMed

Ui, S; Leng, K; Aoyama, A

2007-01-01

This qualitative study examines the significance and effectiveness of participatory health training as a tool for peace building. It does so by analysing a case of training for 'health promoters' run by a Cambodian government health agency. The authors observed participants during the training and interviewed those involved in the courses. A developing capacity for coexistence and reconciliation between individuals who had been on opposite sides during the years of Khmer Rouge terror and continuous internal war was observed among both participants and trainers. Factors embodied in the training that facilitated favourable changes in self and in relations with others were identified as: (1) 'space for dialogue' was created by concrete common public health interests and urgent needs; (2) training took place 'live-in' style in a rural setting; (3) course contents and methods were consistent with peace education; (4) trainers had a conscious function as role models; and (5) there was continuity of effort and consequent accumulation of experience. To build peace, as well as conducting training directly on a technical topic, these essential factors need to be incorporated in the training programmes.

Effects of partial-body cryotherapy (- 110°C) on muscle recovery between high-intensity exercise bouts.

PubMed

Ferreira-Junior, J B; Bottaro, M; Vieira, C A; Soares, S R S; Vieira, A; Cleto, V A; Cadore, E L; Coelho, D B; Simoes, H G; Brown, L E

2014-12-01

The aim of this study was to evaluate the effects of a single partial-body cryotherapy bout between training sessions on strength recovery. 12 young men (23.9±5.9 years) were randomly exposed to 2 different conditions separated by 7 days: 1) Partial-body cryotherapy (subjects were exposed to 3 min of partial-body cryotherapy at - 110 °C between 2 high-intensity training sessions); 2) Control (subjects were not exposed to partial-body cryotherapy between 2 high-intensity training sessions). Subjects were exposed to partial-body cryotherapy after the first training session. The 2 knee extension high-intensity training sessions were separated by a 40-min rest interval. Knee extension training consisted of 6 sets of 10 repetitions at 60°.s(-1) for concentric actions and 6 sets of 10 at 180.s(-1) for eccentric actions. The decrease in eccentric peak torque and total work was significantly (p<0.05) less after partial-body cryotherapy (5.6 and 2%, respectively) when compared to control (16 and 11.6%, respectively). However, the decrease in concentric peak torque and total work was not different (p>0.05) between partial-body cryotherapy (9.4 and 6.5%, respectively) and control (7.5 and 5.2%, respectively). These results indicate that the use of partial-body cryotherapy between-training sessions can enhance eccentric muscle performance recovery. © Georg Thieme Verlag KG Stuttgart · New York.

Prediction of Partition Coefficients of Organic Compounds between SPME/PDMS and Aqueous Solution

PubMed Central

Chao, Keh-Ping; Lu, Yu-Ting; Yang, Hsiu-Wen

2014-01-01

Polydimethylsiloxane (PDMS) is commonly used as the coated polymer in the solid phase microextraction (SPME) technique. In this study, the partition coefficients of organic compounds between SPME/PDMS and the aqueous solution were compiled from the literature sources. The correlation analysis for partition coefficients was conducted to interpret the effect of their physicochemical properties and descriptors on the partitioning process. The PDMS-water partition coefficients were significantly correlated to the polarizability of organic compounds (r = 0.977, p < 0.05). An empirical model, consisting of the polarizability, the molecular connectivity index, and an indicator variable, was developed to appropriately predict the partition coefficients of 61 organic compounds for the training set. The predictive ability of the empirical model was demonstrated by using it on a test set of 26 chemicals not included in the training set. The empirical model, applying the straightforward calculated molecular descriptors, for estimating the PDMS-water partition coefficient will contribute to the practical applications of the SPME technique. PMID:24534804

A practical approach for writer-dependent symbol recognition using a writer-independent symbol recognizer.

PubMed

LaViola, Joseph J; Zeleznik, Robert C

2007-11-01

We present a practical technique for using a writer-independent recognition engine to improve the accuracy and speed while reducing the training requirements of a writer-dependent symbol recognizer. Our writer-dependent recognizer uses a set of binary classifiers based on the AdaBoost learning algorithm, one for each possible pairwise symbol comparison. Each classifier consists of a set of weak learners, one of which is based on a writer-independent handwriting recognizer. During online recognition, we also use the n-best list of the writer-independent recognizer to prune the set of possible symbols and thus reduce the number of required binary classifications. In this paper, we describe the geometric and statistical features used in our recognizer and our all-pairs classification algorithm. We also present the results of experiments that quantify the effect incorporating a writer-independent recognition engine into a writer-dependent recognizer has on accuracy, speed, and user training time.

Effect of sample size on multi-parametric prediction of tissue outcome in acute ischemic stroke using a random forest classifier

NASA Astrophysics Data System (ADS)

Forkert, Nils Daniel; Fiehler, Jens

2015-03-01

The tissue outcome prediction in acute ischemic stroke patients is highly relevant for clinical and research purposes. It has been shown that the combined analysis of diffusion and perfusion MRI datasets using high-level machine learning techniques leads to an improved prediction of final infarction compared to single perfusion parameter thresholding. However, most high-level classifiers require a previous training and, until now, it is ambiguous how many subjects are required for this, which is the focus of this work. 23 MRI datasets of acute stroke patients with known tissue outcome were used in this work. Relative values of diffusion and perfusion parameters as well as the binary tissue outcome were extracted on a voxel-by- voxel level for all patients and used for training of a random forest classifier. The number of patients used for training set definition was iteratively and randomly reduced from using all 22 other patients to only one other patient. Thus, 22 tissue outcome predictions were generated for each patient using the trained random forest classifiers and compared to the known tissue outcome using the Dice coefficient. Overall, a logarithmic relation between the number of patients used for training set definition and tissue outcome prediction accuracy was found. Quantitatively, a mean Dice coefficient of 0.45 was found for the prediction using the training set consisting of the voxel information from only one other patient, which increases to 0.53 if using all other patients (n=22). Based on extrapolation, 50-100 patients appear to be a reasonable tradeoff between tissue outcome prediction accuracy and effort required for data acquisition and preparation.

Protein Supplementation to Augment the Effects of High Intensity Resistance Training in Untrained Middle-Aged Males: The Randomized Controlled PUSH Trial.

PubMed

Wittke, Andreas; von Stengel, Simon; Hettchen, Michael; Fröhlich, Michael; Giessing, Jürgen; Lell, Michael; Scharf, Michael; Bebenek, Michael; Kohl, Matthias; Kemmler, Wolfgang

2017-01-01

High intensity (resistance exercise) training (HIT) defined as a "single set resistance exercise to muscular failure" is an efficient exercise method that allows people with low time budgets to realize an adequate training stimulus. Although there is an ongoing discussion, recent meta-analysis suggests the significant superiority of multiple set (MST) methods for body composition and strength parameters. The aim of this study is to determine whether additional protein supplementation may increase the effect of a HIT-protocol on body composition and strength to an equal MST-level. One hundred and twenty untrained males 30-50 years old were randomly allocated to three groups: (a) HIT, (b) HIT and protein supplementation (HIT&P), and (c) waiting-control (CG) and (after cross-over) high volume/high-intensity-training (HVHIT). HIT was defined as "single set to failure protocol" while HVHIT consistently applied two equal sets. Protein supplementation provided an overall intake of 1.5-1.7 g/kg/d/body mass. Primary study endpoint was lean body mass (LBM). LBM significantly improved in all exercise groups ( p ≤ 0.043); however only HIT&P and HVHIT differ significantly from control ( p ≤ 0.002). HIT diverges significantly from HIT&P ( p = 0.017) and nonsignificantly from HVHIT ( p = 0.059), while no differences were observed for HIT&P versus HVHIT ( p = 0.691). In conclusion, moderate to high protein supplementation significantly increases the effects of a HIT-protocol on LBM in middle-aged untrained males.

Repetition Performance And Blood Lactate Responses Adopting Different Recovery Periods Between Training Sessions In Trained Men.

PubMed

Miranda, Humberto; de Freitas Maia, Marianna; Paz, Gabriel Andrade; de Souza, João A A A; Simão, Roberto; de Araújo Farias, Déborah; Willardson, Jeffrey M

2017-02-08

The purpose of this study was to examine the effect of different recovery periods (24h, 48h, and 72h) between repeated resistance training (RT) sessions for the upper body muscles on repetition performance and blood lactate responses in trained men. Sixteen recreationally trained men (age: 26.1 ± 3.1 years; height: 179 ± 4.5 cm; body mass: 82.6 ± 4.0 kg, 4.5 ± 2.2 years of RT experience) participated in this study. Eight-repetition maximum (8-RM) loads were determined for the bench press (BP), 30° incline bench press (BP30), and 45° incline bench press (BP45) exercises. To assess the effects of different recovery periods between repeated training sessions, three protocols were performed in randomized order, including: 24 hours (P24); 48 hours (P48); and 72 hours (P72). Each RT session consisted of performing four repetition maximum sets of BP, BP30, and BP45 with 8-RM loads and 2-minute rest intervals between sets. Blood lactate levels were measured pre-session (PRE), immediately post-session (POST), 3 minutes post-session (P3), and 5 minutes post-session (P5). For the P24 protocol, significant decreases in repetition performance were found between sessions for the BP, BP30, and BP45 exercises, respectively. When considering session 2 only, the total work (repetition x sets) was significantly higher in P48 and P72 versus P24 for the BP30 and BP45 exercises. Blood lactate levels (i.e. POST, P3, and P5) significantly increased for session 2 under the P24 compared to the P48 and P72 protocols, respectively. Therefore, coaches and practitioners who need to accomplish a higher training volume for the upper body muscles should adopt recovery periods longer than 24 hours between sessions that train the same or similar muscle groups.

Defining and comparing learning actions in two simulation modalities: students training on a latex arm and each other's arms.

PubMed

Ravik, Monika; Havnes, Anton; Bjørk, Ida Torunn

2017-12-01

To explore, describe and compare learning actions that nursing students used during peripheral vein cannulation training on a latex arm or each other's arms in a clinical skills centre. Simulation-based training is thought to enhance learning and transfer of learning from simulation to the clinical setting and is commonly recommended in nursing education. What students actually are doing during simulation-based training is, however, less explored. The analysis of learning actions used during simulation-based training could contribute to development and improvement of simulation as a learning strategy in nursing education. A qualitative explorative and descriptive research design, involving content analysis of video recordings, was used. Video-supported observation of nine nursing students practicing vein cannulation was conducted in a clinical skills centre in late 2012. The students engaged in various learning actions. Students training on a latex arm used a considerably higher number of learning actions relative to those training on each other's arms. In both groups, students' learning actions consisted mainly of seeking and giving support. The teacher provided students training on each other's arms with detailed feedback regarding insertion of the cannula into the vein, while those training on a latex arm received sparse feedback from the teacher and fellow students. The teacher played an important role in facilitating nursing students' practical skill learning during simulation. The provision of support from both teachers and students should be emphasised to ensure that nursing students' learning needs are met. This study suggest that student nurses may be differently and inadequately prepared in peripheral vein cannulation in two simulation modalities used in the academic setting; training on a latex arm and on each other's arms. © 2017 John Wiley & Sons Ltd.

Combining virtual reality and multimedia techniques for effective maintenance training

NASA Astrophysics Data System (ADS)

McLin, David M.; Chung, James C.

1996-02-01

This paper describes a virtual reality (VR) system developed for use as part of an integrated, low-cost, stand-alone, multimedia trainer. The trainer is used to train National Guard personnel in maintenance and trouble-shooting tasks for the M1A1 Abrams tank, the M2A2 Bradley fighting vehicle and the TOW II missile system. The VR system features a modular, extensible, object-oriented design which consists of a training monitor component, a VR run time component, a model loader component, and a set of domain-specific object behaviors which mimic the behavior of objects encountered in the actual vehicles. The VR system is built from a combination of off-the-shelf commercial software and custom software developed at RTI.

Classification capacity of a modular neural network implementing neurally inspired architecture and training rules.

PubMed

Poirazi, Panayiota; Neocleous, Costas; Pattichis, Costantinos S; Schizas, Christos N

2004-05-01

A three-layer neural network (NN) with novel adaptive architecture has been developed. The hidden layer of the network consists of slabs of single neuron models, where neurons within a slab--but not between slabs--have the same type of activation function. The network activation functions in all three layers have adaptable parameters. The network was trained using a biologically inspired, guided-annealing learning rule on a variety of medical data. Good training/testing classification performance was obtained on all data sets tested. The performance achieved was comparable to that of SVM classifiers. It was shown that the adaptive network architecture, inspired from the modular organization often encountered in the mammalian cerebral cortex, can benefit classification performance.

Genome properties and prospects of genomic prediction of hybrid performance in a breeding program of maize.

PubMed

Technow, Frank; Schrag, Tobias A; Schipprack, Wolfgang; Bauer, Eva; Simianer, Henner; Melchinger, Albrecht E

2014-08-01

Maize (Zea mays L.) serves as model plant for heterosis research and is the crop where hybrid breeding was pioneered. We analyzed genomic and phenotypic data of 1254 hybrids of a typical maize hybrid breeding program based on the important Dent × Flint heterotic pattern. Our main objectives were to investigate genome properties of the parental lines (e.g., allele frequencies, linkage disequilibrium, and phases) and examine the prospects of genomic prediction of hybrid performance. We found high consistency of linkage phases and large differences in allele frequencies between the Dent and Flint heterotic groups in pericentromeric regions. These results can be explained by the Hill-Robertson effect and support the hypothesis of differential fixation of alleles due to pseudo-overdominance in these regions. In pericentromeric regions we also found indications for consistent marker-QTL linkage between heterotic groups. With prediction methods GBLUP and BayesB, the cross-validation prediction accuracy ranged from 0.75 to 0.92 for grain yield and from 0.59 to 0.95 for grain moisture. The prediction accuracy of untested hybrids was highest, if both parents were parents of other hybrids in the training set, and lowest, if none of them were involved in any training set hybrid. Optimizing the composition of the training set in terms of number of lines and hybrids per line could further increase prediction accuracy. We conclude that genomic prediction facilitates a paradigm shift in hybrid breeding by focusing on the performance of experimental hybrids rather than the performance of parental lines in test crosses. Copyright © 2014 by the Genetics Society of America.

Practice makes proficient: pigeons (Columba livia) learn efficient routes on full-circuit navigational traveling salesperson problems.

PubMed

Baron, Danielle M; Ramirez, Alejandro J; Bulitko, Vadim; Madan, Christopher R; Greiner, Ariel; Hurd, Peter L; Spetch, Marcia L

2015-01-01

Visiting multiple locations and returning to the start via the shortest route, referred to as the traveling salesman (or salesperson) problem (TSP), is a valuable skill for both humans and non-humans. In the current study, pigeons were trained with increasing set sizes of up to six goals, with each set size presented in three distinct configurations, until consistency in route selection emerged. After training at each set size, the pigeons were tested with two novel configurations. All pigeons acquired routes that were significantly more efficient (i.e., shorter in length) than expected by chance selection of the goals. On average, the pigeons also selected routes that were more efficient than expected based on a local nearest-neighbor strategy and were as efficient as the average route generated by a crossing-avoidance strategy. Analysis of the routes taken indicated that they conformed to both a nearest-neighbor and a crossing-avoidance strategy significantly more often than expected by chance. Both the time taken to visit all goals and the actual distance traveled decreased from the first to the last trials of training in each set size. On the first trial with novel configurations, average efficiency was higher than chance, but was not higher than expected from a nearest-neighbor or crossing-avoidance strategy. These results indicate that pigeons can learn to select efficient routes on a TSP problem.

Antepartum fetal heart rate feature extraction and classification using empirical mode decomposition and support vector machine

PubMed Central

2011-01-01

Background Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'. Methods The FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from these. All records were labelled as 'normal' or 'at risk' by two experienced obstetricians. A training set was formed by 60 records, the remaining 30 left as the testing set. The standard deviations of the EMD components are input as features to a support vector machine (SVM) to classify FHR samples. Results For the training set, a five-fold cross validation test resulted in an accuracy of 86% whereas the overall geometric mean of sensitivity and specificity was 94.8%. The Kappa value for the training set was .923. Application of the proposed method to the testing set (30 records) resulted in a geometric mean of 81.5%. The Kappa value for the testing set was .684. Conclusions Based on the overall performance of the system it can be stated that the proposed methodology is a promising new approach for the feature extraction and classification of FHR signals. PMID:21244712

The influence of variable range of motion training on neuromuscular performance and control of external loads.

PubMed

Clark, Ross A; Humphries, Brendan; Hohmann, Erik; Bryant, Adam L

2011-03-01

Resistance training programs that emphasize high force production in different regions of the range of motion (ROM) may provide performance benefits. This study examined whether variable ROM (VROM) training, which consists of partial ROM training with countermovements performed in a different phase of the ROM for each set, results in improved functional performance. Twenty-two athletes (age 22.7 ± 2.4 years, height 1.81 ± 0.07 m, and body mass 94.6 ± 14.5 kg) with extensive resistance training backgrounds performed either a VROM or full ROM control (CON) 5-week, concentric work-matched training program. The participants were assigned to a group based on stratified randomization incorporating their strength levels and performance gains in preceding training microcycles. Testing consisted of assessing the force-ROM relationship during isokinetic and isometric bench press and ballistic bench throws, with normalized electromyography amplitude assessed during the isometric tests. Repeated-measure analyses of variance revealed that the VROM intervention significantly (p < 0.05) increased both full ROM bench throw displacement (+15.5%) and half ROM bench throw peak force (+15.7%), in addition to isokinetic peak force in the terminal ROM (13.5% increase). No significant differences were observed in the CON group or between groups for any other outcome measures. Analysis of the force-ROM relationship revealed that that the VROM intervention enhanced performance at shorter muscle lengths. These findings suggest that VROM training improves terminal and midrange performance gains, resulting in the athlete possessing an improved ability to control external loading and produce dynamic force.

Reduction in training time of a deep learning model in detection of lesions in CT

NASA Astrophysics Data System (ADS)

Makkinejad, Nazanin; Tajbakhsh, Nima; Zarshenas, Amin; Khokhar, Ashfaq; Suzuki, Kenji

2018-02-01

Deep learning (DL) emerged as a powerful tool for object detection and classification in medical images. Building a well-performing DL model, however, requires a huge number of images for training, and it takes days to train a DL model even on a cutting edge high-performance computing platform. This study is aimed at developing a method for selecting a "small" number of representative samples from a large collection of training samples to train a DL model for the could be used to detect polyps in CT colonography (CTC), without compromising the classification performance. Our proposed method for representative sample selection (RSS) consists of a K-means clustering algorithm. For the performance evaluation, we applied the proposed method to select samples for the training of a massive training artificial neural network based DL model, to be used for the classification of polyps and non-polyps in CTC. Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model trained using the full training set. We compare the performance using area under the receiveroperating- characteristic curve (AUC).

Longitudinal Multiple Sclerosis Lesion Segmentation: Resource & Challenge

PubMed Central

Carass, Aaron; Roy, Snehashis; Jog, Amod; Cuzzocreo, Jennifer L.; Magrath, Elizabeth; Gherman, Adrian; Button, Julia; Nguyen, James; Prados, Ferran; Sudre, Carole H.; Cardoso, Manuel Jorge; Cawley, Niamh; Ciccarelli, Olga; Wheeler-Kingshott, Claudia A. M.; Ourselin, Sébastien; Catanese, Laurence; Deshpande, Hrishikesh; Maurel, Pierre; Commowick, Olivier; Barillot, Christian; Tomas-Fernandez, Xavier; Warfield, Simon K.; Vaidya, Suthirth; Chunduru, Abhijith; Muthuganapathy, Ramanathan; Krishnamurthi, Ganapathy; Jesson, Andrew; Arbel, Tal; Maier, Oskar; Handels, Heinz; Iheme, Leonardo O.; Unay, Devrim; Jain, Saurabh; Sima, Diana M.; Smeets, Dirk; Ghafoorian, Mohsen; Platel, Bram; Birenbaum, Ariel; Greenspan, Hayit; Bazin, Pierre-Louis; Calabresi, Peter A.; Crainiceanu, Ciprian M.; Ellingsen, Lotta M.; Reich, Daniel S.; Prince, Jerry L.; Pham, Dzung L.

2017-01-01

In conjunction with the ISBI 2015 conference, we organized a longitudinal lesion segmentation challenge providing training and test data to registered participants. The training data consisted of five subjects with a mean of 4.4 time-points, and test data of fourteen subjects with a mean of 4.4 time-points. All 82 data sets had the white matter lesions associated with multiple sclerosis delineated by two human expert raters. Eleven teams submitted results using state-of-the-art lesion segmentation algorithms to the challenge, with ten teams presenting their results at the conference. We present a quantitative evaluation comparing the consistency of the two raters as well as exploring the performance of the eleven submitted results in addition to three other lesion segmentation algorithms. The challenge presented three unique opportunities: 1) the sharing of a rich data set; 2) collaboration and comparison of the various avenues of research being pursued in the community; and 3) a review and refinement of the evaluation metrics currently in use. We report on the performance of the challenge participants, as well as the construction and evaluation of a consensus delineation. The image data and manual delineations will continue to be available for download, through an evaluation website1 as a resource for future researchers in the area. This data resource provides a platform to compare existing methods in a fair and consistent manner to each other and multiple manual raters. PMID:28087490

Interprofessional Emergency Training Leads to Changes in the Workplace.

PubMed

Eisenmann, Dorothea; Stroben, Fabian; Gerken, Jan D; Exadaktylos, Aristomenis K; Machner, Mareen; Hautz, Wolf E

2018-01-01

Preventable mistakes occur frequently and can lead to patient harm and death. The emergency department (ED) is notoriously prone to such errors, and evidence suggests that improving teamwork is a key aspect to reduce the rate of error in acute care settings. Only a few strategies are in place to train team skills and communication in interprofessional situations. Our goal was to conceptualize, implement, and evaluate a training module for students of three professions involved in emergency care. The objective was to sensitize participants to barriers for their team skills and communication across professional borders. We developed a longitudinal simulation-enhanced training format for interprofessional teams, consisting of final-year medical students, advanced trainees of emergency nursing and student paramedics. The training format consisted of several one-day training modules, which took place twice in 2016 and 2017. Each training module started with an introduction to share one's roles, professional self-concepts, common misconceptions, and communication barriers. Next, we conducted different simulated cases. Each case consisted of a prehospital section (for paramedics and medical students), a handover (everyone), and an ED section (medical students and emergency nurses). After each training module, we assessed participants' "Commitment to Change." In this questionnaire, students were anonymously asked to state up to three changes that they wished to implement as a result of the course, as well as the strength of their commitment to these changes. In total, 64 of 80 participants (80.0%) made at least one commitment to change after participating in the training modules. The total of 123 commitments was evenly distributed over four emerging categories: communication , behavior , knowledge and attitude . Roughly one third of behavior- and attitude-related commitments were directly related to interprofessional topics (e.g., "acknowledge other professions' work"), and these were equally distributed among professions. At the two-month follow-up, 32 participants (50%) provided written feedback on their original commitments: 57 of 62 (91.9%) commitments were at least partly realized at the follow-up, and only five (8.1%) commitments lacked realization entirely. A structured simulation-enhanced intervention was successful in promoting change to the practice of emergency care, while training teamwork and communication skills jointly.

Limited Effects of Set Shifting Training in Healthy Older Adults

PubMed Central

Grönholm-Nyman, Petra; Soveri, Anna; Rinne, Juha O.; Ek, Emilia; Nyholm, Alexandra; Stigsdotter Neely, Anna; Laine, Matti

2017-01-01

Our ability to flexibly shift between tasks or task sets declines in older age. As this decline may have adverse effects on everyday life of elderly people, it is of interest to study whether set shifting ability can be trained, and if training effects generalize to other cognitive tasks. Here, we report a randomized controlled trial where healthy older adults trained set shifting with three different set shifting tasks. The training group (n = 17) performed adaptive set shifting training for 5 weeks with three training sessions a week (45 min/session), while the active control group (n = 16) played three different computer games for the same period. Both groups underwent extensive pre- and post-testing and a 1-year follow-up. Compared to the controls, the training group showed significant improvements on the trained tasks. Evidence for near transfer in the training group was very limited, as it was seen only on overall accuracy on an untrained computerized set shifting task. No far transfer to other cognitive functions was observed. One year later, the training group was still better on the trained tasks but the single near transfer effect had vanished. The results suggest that computerized set shifting training in the elderly shows long-lasting effects on the trained tasks but very little benefit in terms of generalization. PMID:28386226

Comparative Effects of Different Balance-Training–Progression Styles on Postural Control and Ankle Force Production: A Randomized Controlled Trial

PubMed Central

Cuğ, Mutlu; Duncan, Ashley; Wikstrom, Erik

2016-01-01

Context:  Despite the effectiveness of balance training, the exact parameters needed to maximize the benefits of such programs remain unknown. One such factor is how individuals should progress to higher levels of task difficulty within a balance-training program. Yet no investigators have directly compared different balance-training–progression styles. Objective:  To compare an error-based progression (ie, advance when proficient at a task) with a repetition-based progression (ie, advance after a set amount of repetitions) style during a balance-training program in healthy individuals. Design:  Randomized controlled trial. Setting:  Research laboratory. Patients or Other Participants:  A total of 28 (16 women, 12 men) physically healthy young adults (age = 21.57 ± 3.95 years, height = 171.60 ± 11.03 cm, weight = 72.96 ± 16.18 kg, body mass index = 24.53 ± 3.7). Intervention(s):  All participants completed 12 supervised balance-training sessions over 4 weeks. Each session consisted of a combination of dynamic unstable-surface tasks that incorporated a BOSU ball and lasted about 30 minutes. Main Outcome Measure(s):  Static balance from an instrumented force plate, dynamic balance as measured via the Star Excursion Balance Test, and ankle force production in all 4 cardinal planes of motion as measured with a handheld dynamometer before and after the intervention. Results:  Selected static postural-control outcomes, dynamic postural control, and ankle force production in all planes of motion improved (P < .05). However, no differences between the progression styles were observed (P > .05) for any of the outcome measures. Conclusions:  A 4-week balance-training program consisting of dynamic unstable-surface exercises on a BOSU ball improved dynamic postural control and ankle force production in healthy young adults. These results suggest that an error-based balance-training program is comparable with but not superior to a repetition-based balance-training program in improving postural control and ankle force production in healthy young adults. PMID:26878257

Portable automatic text classification for adverse drug reaction detection via multi-corpus training.

PubMed

Sarker, Abeed; Gonzalez, Graciela

2015-02-01

Automatic detection of adverse drug reaction (ADR) mentions from text has recently received significant interest in pharmacovigilance research. Current research focuses on various sources of text-based information, including social media-where enormous amounts of user posted data is available, which have the potential for use in pharmacovigilance if collected and filtered accurately. The aims of this study are: (i) to explore natural language processing (NLP) approaches for generating useful features from text, and utilizing them in optimized machine learning algorithms for automatic classification of ADR assertive text segments; (ii) to present two data sets that we prepared for the task of ADR detection from user posted internet data; and (iii) to investigate if combining training data from distinct corpora can improve automatic classification accuracies. One of our three data sets contains annotated sentences from clinical reports, and the two other data sets, built in-house, consist of annotated posts from social media. Our text classification approach relies on generating a large set of features, representing semantic properties (e.g., sentiment, polarity, and topic), from short text nuggets. Importantly, using our expanded feature sets, we combine training data from different corpora in attempts to boost classification accuracies. Our feature-rich classification approach performs significantly better than previously published approaches with ADR class F-scores of 0.812 (previously reported best: 0.770), 0.538 and 0.678 for the three data sets. Combining training data from multiple compatible corpora further improves the ADR F-scores for the in-house data sets to 0.597 (improvement of 5.9 units) and 0.704 (improvement of 2.6 units) respectively. Our research results indicate that using advanced NLP techniques for generating information rich features from text can significantly improve classification accuracies over existing benchmarks. Our experiments illustrate the benefits of incorporating various semantic features such as topics, concepts, sentiments, and polarities. Finally, we show that integration of information from compatible corpora can significantly improve classification performance. This form of multi-corpus training may be particularly useful in cases where data sets are heavily imbalanced (e.g., social media data), and may reduce the time and costs associated with the annotation of data in the future. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Portable Automatic Text Classification for Adverse Drug Reaction Detection via Multi-corpus Training

PubMed Central

Gonzalez, Graciela

2014-01-01

Objective Automatic detection of Adverse Drug Reaction (ADR) mentions from text has recently received significant interest in pharmacovigilance research. Current research focuses on various sources of text-based information, including social media — where enormous amounts of user posted data is available, which have the potential for use in pharmacovigilance if collected and filtered accurately. The aims of this study are: (i) to explore natural language processing approaches for generating useful features from text, and utilizing them in optimized machine learning algorithms for automatic classification of ADR assertive text segments; (ii) to present two data sets that we prepared for the task of ADR detection from user posted internet data; and (iii) to investigate if combining training data from distinct corpora can improve automatic classification accuracies. Methods One of our three data sets contains annotated sentences from clinical reports, and the two other data sets, built in-house, consist of annotated posts from social media. Our text classification approach relies on generating a large set of features, representing semantic properties (e.g., sentiment, polarity, and topic), from short text nuggets. Importantly, using our expanded feature sets, we combine training data from different corpora in attempts to boost classification accuracies. Results Our feature-rich classification approach performs significantly better than previously published approaches with ADR class F-scores of 0.812 (previously reported best: 0.770), 0.538 and 0.678 for the three data sets. Combining training data from multiple compatible corpora further improves the ADR F-scores for the in-house data sets to 0.597 (improvement of 5.9 units) and 0.704 (improvement of 2.6 units) respectively. Conclusions Our research results indicate that using advanced NLP techniques for generating information rich features from text can significantly improve classification accuracies over existing benchmarks. Our experiments illustrate the benefits of incorporating various semantic features such as topics, concepts, sentiments, and polarities. Finally, we show that integration of information from compatible corpora can significantly improve classification performance. This form of multi-corpus training may be particularly useful in cases where data sets are heavily imbalanced (e.g., social media data), and may reduce the time and costs associated with the annotation of data in the future. PMID:25451103

Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data.

PubMed

Ribay, Kathryn; Kim, Marlene T; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

2016-03-01

Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR models, particularly for the activity cliffs that induce prediction errors. The results of this study indicate that the response profile of chemicals from public data provides useful information for modeling and evaluation purposes. The public big data resources should be considered along with chemical structure information when predicting new compounds, such as unknown ERα binding agents.

Efficient detection of wound-bed and peripheral skin with statistical colour models.

PubMed

Veredas, Francisco J; Mesa, Héctor; Morente, Laura

2015-04-01

A pressure ulcer is a clinical pathology of localised damage to the skin and underlying tissue caused by pressure, shear or friction. Reliable diagnosis supported by precise wound evaluation is crucial in order to success on treatment decisions. This paper presents a computer-vision approach to wound-area detection based on statistical colour models. Starting with a training set consisting of 113 real wound images, colour histogram models are created for four different tissue types. Back-projections of colour pixels on those histogram models are used, from a Bayesian perspective, to get an estimate of the posterior probability of a pixel to belong to any of those tissue classes. Performance measures obtained from contingency tables based on a gold standard of segmented images supplied by experts have been used for model selection. The resulting fitted model has been validated on a training set consisting of 322 wound images manually segmented and labelled by expert clinicians. The final fitted segmentation model shows robustness and gives high mean performance rates [(AUC: .9426 (SD .0563); accuracy: .8777 (SD .0799); F-score: 0.7389 (SD .1550); Cohen's kappa: .6585 (SD .1787)] when segmenting significant wound areas that include healing tissues.

Mobile technology intervention to improve care coordination between HIV and substance use treatment providers: development, training, and evaluation protocol.

PubMed

Claborn, Kasey; Becker, Sara; Ramsey, Susan; Rich, Josiah; Friedmann, Peter D

2017-03-14

People living with HIV (PLWH) with a substance use disorder (SUD) tend to receive inadequate medical care in part because of a siloed healthcare system in which HIV and substance use services are delivered separately. Ideal treatment requires an interdisciplinary, team-based coordinated care approach, but many structural and systemic barriers impede the integration of HIV and SUD services. The current protocol describes the development and preliminary evaluation of a care coordination intervention (CCI), consisting of a tablet-based mobile platform for HIV and SUD treatment providers, an interagency communication protocol, and a training protocol. We hypothesize that HIV and SUD treatment providers will find the CCI to be acceptable, and that after receipt of the CCI, providers will: exhibit higher retention in dual care among patients, report increased frequency and quality of communication, and report increased rates of relational coordination. A three phase approach is used to refine and evaluate the CCI. Phase 1 consists of in-depth qualitative interviews with 8 key stakeholders as well as clinical audits of participating HIV and SUD treatment agencies. Phase 2 contains functionality testing of the mobile platform with frontline HIV and SUD treatment providers, followed by refinement of the CCI. Phase 3 consists of a pre-, post-test trial with 30 SUD and 30 HIV treatment providers. Data will be collected at the provider, organization, and patient levels. Providers will complete assessments at baseline, immediately post-training, and at 1-, 3-, and 6-months post-training. Organizational data will be collected at baseline, 1-, 3-, and 6-months post training, while patient data will be collected at baseline and 6-months post training. This study will develop and evaluate a CCI consisting of a tablet-based mobile platform for treatment providers, an interagency communication protocol, and a training protocol as a means of improving the integration of care for PLWH who have a SUD. Results have the potential to advance the field by bridging gaps in a fragmented healthcare system, and improving treatment efficiency, work flow, and communication among interdisciplinary providers from different treatment settings. NCT02906215.

Evaluation on the Perception of the New Portable Set for Hajj Course (P.A.H.A.M) Based on Design Characteristics

NASA Astrophysics Data System (ADS)

Shahir Yahya, Mohd; Rahim, Abd Khalil Abd; Mohammad, Musli; Ibrahim, Mustaffa; Kadis, Ghazali

2017-08-01

This paper is about the perceptions of the pilgrims to the innovation of the portable training set for hajj course (P.A.H.A.M). The acronym P.A.H.A.M come from the Malay word “Praktikal Haji Mudahalih” as a tool in helping the hajj and umrah pilgrims to better understand the concept while doing the hajj and umrah practical. In Malaysia, one of the managing bodies of pilgrimage for Muslims in is Pilgrims Fund Board. It provides a series of courses every year to help in boosting the understanding of the pilgrims before leaving for the Holy Land. During the practical session, they will provide the replica model to help pilgrims to familiarise themselves with the actual situation in Mecca. However, the current replica model was built using an iron structure that is relatively heavy, not portable and embarks more cost of transportation and labour. Therefore, this paper discusses the perceptions of the pilgrims on the characteristics of Portable Training Set for Hajj Course (P.A.H.A.M) compared to the existing set in order to increase the understanding of pilgrims. A total of 53 samples of hajj and umrah pilgrims participated in this study consisted of the general public. From the data analysed using Statistical Software for Social Sciences (SPSS v19), the results of the survey showed that more than 90% of respondents agreed that this portable training set meets the characteristics such as easy to handle, more safety in crowd, portable, stability, light weight, suitable in-door and out-door activity, easy to clean, and more structured with average score 4.00 (agreed) and above. In conclusion, it is expected that this Portable Training Set for Hajj Course (P.A.H.A.M) can be used by Muslim’s communities in Malaysia particularly and Muslim countries in general to better understand the hajj and umrah activities before leaving to the Holy Land.

EDs find physical therapists are an underused asset for musculoskeletal injuries, patient education.

PubMed

2011-04-01

Some EDs are finding that the unique skill sets offered by physical therapists (PT) can be an asset to emergency care while also improving the patient experience. Experts say PTs are particularly valuable in the management of musculoskeletal pain and injuries, but they are also being used for wound care, gait training, and balance assessment. ED administrators say consistent, daily coverage is essential to making a PT program successful; otherwise, ED clinicians will neglect to use their services. PTs need to be comfortable with proactively marketing their skills to other ED clinicians who may not be used to having access to this resource. Experts say PT services in the ED can be reimbursed at a level that is consistent with reimbursement in other inpatient and outpatient settings.

Cognitive task analysis and innovation of training: the case of structured troubleshooting.

PubMed

Schaafstal, A; Schraagen, J M; van Berlo, M

2000-01-01

Troubleshooting is often a time-consuming and difficult activity. The question of how the training of novice technicians can be improved was the starting point of the research described in this article. A cognitive task analysis was carried out consisting of two preliminary observational studies on troubleshooting in naturalistic settings, combined with an interpretation of the data obtained in the context of the existing literature. On the basis of this cognitive task analysis, a new method for the training of troubleshooting was developed (structured troubleshooting), which combines a domain-independent strategy for troubleshooting with a context-dependent, multiple-level, functional decomposition of systems. This method has been systematically evaluated for its use in training. The results show that technicians trained in structured troubleshooting solve twice as many malfunctions, in less time, than those trained in the traditional way. Moreover, structured troubleshooting can be taught in less time than can traditional troubleshooting. Finally, technicians learn to troubleshoot in an explicit and uniform way. These advantages of structured troubleshooting ultimately lead to a reduction in training and troubleshooting costs.

Combined Aerobic/Strength Training and Energy Expenditure in Older Women

PubMed Central

Hunter, Gary R.; Bickel, C. Scott; Fisher, Gordon; Neumeier, William; McCarthy, John

2013-01-01

Purpose To examine the effects of three different frequencies of combined resistance and aerobic training on total energy expenditure (TEE) and activity related energy expenditure (AEE) in a group of older adults. Methods Seventy-two women, 60 – 74 years old, were randomly assigned to one of three groups: 1 day/week of aerobic and 1 day/week of resistance (1+1); 2 days/week of aerobic and 2 days/week resistance (2+2); or 3 days/week aerobic and 3 days/week resistance (3+3). Body composition (DXA), feeling of fatigue, depression, and vigor (questionnaire), strength (1RM), serum cytokines (ELISA), maximal oxygen uptake (progressive treadmill test), resting energy expenditure, and TEE were measured before and after 16 weeks of training. Aerobic training consisted of 40 minutes of aerobic exercise at 80% maximum heart rate and resistance training consisted of 2 sets of 10 repetitions for 10 different exercises at 80% of one repetition maximum. Results All groups increased fat free mass, strength and aerobic fitness and decreased fat mass. No changes were observed in cytokines or perceptions of fatigue/depression. No time by group interaction was found for any fitness/body composition variable. TEE and AEE increased with the 2+2 group but not with the other two groups. Non-exercise training AEE (NEAT) increased significantly in the 2+2 group (+200 kcal/day), group 1×1 showed a trend for an increase (+68 kcal/day) and group 3+3 decreased significantly (−150 kcal/day). Conclusion Results indicate that 3+3 training may inhibit NEAT by being too time consuming and does not induce superior training adaptations to 1+1 and 2+2 training. Key words: physical activity, older adults, total energy expenditure, maximum oxygen uptake. PMID:23774582

Classification

NASA Astrophysics Data System (ADS)

Oza, Nikunj

2012-03-01

A supervised learning task involves constructing a mapping from input data (normally described by several features) to the appropriate outputs. A set of training examples— examples with known output values—is used by a learning algorithm to generate a model. This model is intended to approximate the mapping between the inputs and outputs. This model can be used to generate predicted outputs for inputs that have not been seen before. Within supervised learning, one type of task is a classification learning task, in which each output is one or more classes to which the input belongs. For example, we may have data consisting of observations of sunspots. In a classification learning task, our goal may be to learn to classify sunspots into one of several types. Each example may correspond to one candidate sunspot with various measurements or just an image. A learning algorithm would use the supplied examples to generate a model that approximates the mapping between each supplied set of measurements and the type of sunspot. This model can then be used to classify previously unseen sunspots based on the candidate’s measurements. The generalization performance of a learned model (how closely the target outputs and the model’s predicted outputs agree for patterns that have not been presented to the learning algorithm) would provide an indication of how well the model has learned the desired mapping. More formally, a classification learning algorithm L takes a training set T as its input. The training set consists of |T| examples or instances. It is assumed that there is a probability distribution D from which all training examples are drawn independently—that is, all the training examples are independently and identically distributed (i.i.d.). The ith training example is of the form (x_i, y_i), where x_i is a vector of values of several features and y_i represents the class to be predicted.* In the sunspot classification example given above, each training example would represent one sunspot’s classification (y_i) and the corresponding set of measurements (x_i). The output of a supervised learning algorithm is a model h that approximates the unknown mapping from the inputs to the outputs. In our example, h would map from the sunspot measurements to the type of sunspot. We may have a test set S—a set of examples not used in training that we use to test how well the model h predicts the outputs on new examples. Just as with the examples in T, the examples in S are assumed to be independent and identically distributed (i.i.d.) draws from the distribution D. We measure the error of h on the test set as the proportion of test cases that h misclassifies: 1/|S| Sigma(x,y union S)[I(h(x)!= y)] where I(v) is the indicator function—it returns 1 if v is true and 0 otherwise. In our sunspot classification example, we would identify additional examples of sunspots that were not used in generating the model, and use these to determine how accurate the model is—the fraction of the test samples that the model classifies correctly. An example of a classification model is the decision tree shown in Figure 23.1. We will discuss the decision tree learning algorithm in more detail later—for now, we assume that, given a training set with examples of sunspots, this decision tree is derived. This can be used to classify previously unseen examples of sunpots. For example, if a new sunspot’s inputs indicate that its "Group Length" is in the range 10-15, then the decision tree would classify the sunspot as being of type “E,” whereas if the "Group Length" is "NULL," the "Magnetic Type" is "bipolar," and the "Penumbra" is "rudimentary," then it would be classified as type "C." In this chapter, we will add to the above description of classification problems. We will discuss decision trees and several other classification models. In particular, we will discuss the learning algorithms that generate these classification models, how to use them to classify new examples, and the strengths and weaknesses of these models. We will end with pointers to further reading on classification methods applied to astronomy data.

Effect of ultrasound training of physicians working in the prehospital setting.

PubMed

Krogh, Charlotte Loumann; Steinmetz, Jacob; Rudolph, Søren Steemann; Hesselfeldt, Rasmus; Lippert, Freddy K; Berlac, Peter A; Rasmussen, Lars S

2016-08-04

Advances in technology have made ultrasound (US) devices smaller and portable, hence accessible for prehospital care providers. This study aims to evaluate the effect of a four-hour, hands-on US training course for physicians working in the prehospital setting. The primary outcome measure was US performance assessed by the total score in a modified version of the Objective Structured Assessment of Ultrasound Skills scale (mOSAUS). Prehospital physicians participated in a four-hour US course consisting of both hands-on training and e-learning including a pre- and a post-learning test. Prior to the hands-on training a pre-training test was applied comprising of five videos in which the participants should identify pathology and a five-minute US examination of a healthy volunteer portraying to be a shocked patient after a blunt torso trauma. Following the pre-training test, the participants received a four-hour, hands-on US training course which was concluded with a post-training test. The US examinations and screen output from the US equipment were recorded for subsequent assessment. Two blinded raters assessed the videos using the mOSAUS. Forty participants completed the study. A significant improvement was identified in e-learning performance and US performance, (37.5 (SD: 10.0)) vs. (51.3 (SD: 5.9) p = < 0.0001), total US performance score (15.3 (IQR: 12.0-17.5) vs. 17.5 (IQR: 14.5-21.0), p = < 0.0001) and in each of the five assessment elements of the mOSAUS. In the prehospital physicians assessed, we found significant improvements in the ability to perform US examinations after completing a four-hour, hands-on US training course.

The usefulness of traditional birth attendants to women living with HIV in resource-poor settings: the case of Mfuwe, Zambia.

PubMed

Muzyamba, Choolwe; Groot, Wim; Tomini, Sonila M; Pavlova, Milena

2017-01-01

Although there is increased attention on the role of trained traditional birth attendants (TBAs) in maternal care, most of the research has mainly focused on providing evidence of the relevance of trained TBAs to women in general without a specific focus on women who are HIV positive, despite them being most vulnerable. Therefore, the aim of this study is to fill this gap by assessing the relevance of trained TBAs to women living with HIV in resource-poor settings by using Zambia as a case study. Our data collection consisted of two focus group discussions, one involving HIV-positive women utilizing trained TBAs and the other with women not utilizing TBAs. Additionally, in-depth interviews were conducted with trained TBAs and health workers. Thematic analysis was used to analyze the data. In general, women living with HIV positively characterized the services of TBAs. In the face of an inefficient health system, trained TBAs were seen to be useful in providing efficient, cheap and quality care, counseling, and referral and logistical support, including treatment adherence support. In Zambia, trained TBAs and professional care are not mutually exclusive but complementary. There is no doubt that HIV-positive women need professionals to handle complications and offer antiretroviral treatment to ensure prevention of mother to child transmission (PMTCT). However, additional "soft" services offered by trained TBAs are equally important in the promotion of maternal health care among HIV-positive women. Thus, it seems there is more to gain by systematically allowing trained TBAs to work alongside professionals in a well-coordinated and complementary manner.

Appropriate training and retention of community doctors in rural areas: a case study from Mali.

PubMed

Van Dormael, Monique; Dugas, Sylvie; Kone, Yacouba; Coulibaly, Seydou; Sy, Mansour; Marchal, Bruno; Desplats, Dominique

2008-11-18

While attraction of doctors to rural settings is increasing in Mali, there is concern for their retention. An orientation course for young practicing rural doctors was set up in 2003 by a professional association and a NGO. The underlying assumption was that rurally relevant training would strengthen doctors' competences and self-confidence, improve job satisfaction, and consequently contribute to retention. Programme evaluation distinguished trainees' opinions, competences and behaviour. Data were collected through participant observation, group discussions, satisfaction questionnaires, a monitoring tool of learning progress, and follow up visits. Retention was assessed for all 65 trainees between 2003 and 2007. The programme consisted of four classroom modules--clinical skills, community health, practice management and communication skills--and a practicum supervised by an experienced rural doctor. Out of the 65 trained doctors between 2003 and 2007, 55 were still engaged in rural practice end of 2007, suggesting high retention for the Malian context. Participants viewed the training as crucial to face technical and social problems related to rural practice. Discussing professional experience with senior rural doctors contributed to socialisation to novel professional roles. Mechanisms underlying training effects on retention include increased self confidence, self esteem as rural doctor, and sense of belonging to a professional group sharing a common professional identity. Retention can however not be attributed solely to the training intervention, as rural doctors benefit from other incentives and support mechanisms (follow up visits, continuing training, mentoring...) affecting job satisfaction. Training increasing self confidence and self esteem of rural practitioners may contribute to retention of skilled professionals in rural areas. While reorientations of curricula in training institutions are necessary, other types of professional support are needed. This experience suggests that professional associations dedicated to strengthening quality of care can contribute significantly to rural practitioners' morale.

Comparison of Random Forest and Support Vector Machine classifiers using UAV remote sensing imagery

NASA Astrophysics Data System (ADS)

Piragnolo, Marco; Masiero, Andrea; Pirotti, Francesco

2017-04-01

Since recent years surveying with unmanned aerial vehicles (UAV) is getting a great amount of attention due to decreasing costs, higher precision and flexibility of usage. UAVs have been applied for geomorphological investigations, forestry, precision agriculture, cultural heritage assessment and for archaeological purposes. It can be used for land use and land cover classification (LULC). In literature, there are two main types of approaches for classification of remote sensing imagery: pixel-based and object-based. On one hand, pixel-based approach mostly uses training areas to define classes and respective spectral signatures. On the other hand, object-based classification considers pixels, scale, spatial information and texture information for creating homogeneous objects. Machine learning methods have been applied successfully for classification, and their use is increasing due to the availability of faster computing capabilities. The methods learn and train the model from previous computation. Two machine learning methods which have given good results in previous investigations are Random Forest (RF) and Support Vector Machine (SVM). The goal of this work is to compare RF and SVM methods for classifying LULC using images collected with a fixed wing UAV. The processing chain regarding classification uses packages in R, an open source scripting language for data analysis, which provides all necessary algorithms. The imagery was acquired and processed in November 2015 with cameras providing information over the red, blue, green and near infrared wavelength reflectivity over a testing area in the campus of Agripolis, in Italy. Images were elaborated and ortho-rectified through Agisoft Photoscan. The ortho-rectified image is the full data set, and the test set is derived from partial sub-setting of the full data set. Different tests have been carried out, using a percentage from 2 % to 20 % of the total. Ten training sets and ten validation sets are obtained from each test set. The control dataset consist of an independent visual classification done by an expert over the whole area. The classes are (i) broadleaf, (ii) building, (iii) grass, (iv) headland access path, (v) road, (vi) sowed land, (vii) vegetable. The RF and SVM are applied to the test set. The performances of the methods are evaluated using the three following accuracy metrics: Kappa index, Classification accuracy and Classification Error. All three are calculated in three different ways: with K-fold cross validation, using the validation test set and using the full test set. The analysis indicates that SVM gets better results in terms of good scores using K-fold cross or validation test set. Using the full test set, RF achieves a better result in comparison to SVM. It also seems that SVM performs better with smaller training sets, whereas RF performs better as training sets get larger.

Effects of β-alanine supplementation during a 5-week strength training program: a randomized, controlled study.

PubMed

Maté-Muñoz, José Luis; Lougedo, Juan H; Garnacho-Castaño, Manuel V; Veiga-Herreros, Pablo; Lozano-Estevan, María Del Carmen; García-Fernández, Pablo; de Jesús, Fernando; Guodemar-Pérez, Jesús; San Juan, Alejandro F; Domínguez, Raúl

2018-01-01

β-Alanine (BA) is a non-essential amino acid that has been shown to enhance exercise performance. The purpose of this investigation was to determine if BA supplementation improved the adaptive response to five weeks of a resistance training program. Thirty healthy, strength-trained individuals were randomly assigned to the experimental groups placebo (PLA) or BA. Over 5 weeks of strength training, subjects in BA took 6.4 g/day of BA as 8 × 800 mg doses each at least 1.5 h apart. The training program consisted of 3 sessions per week in which three different leg exercises were conducted as a circuit (back squat, barbell step ups and loaded jumping lunges). The program started with 3 sets of 40 s of work per exercise and rest periods between sets of 120 s in the first week. This training volume was then gradually built up to 5 sets of 20 s work/60 s rest in the fifth week. The work load during the program was set by one of the authors according to the individual's perceived effort the previous week. The variables measured were average velocity, peak velocity, average power, peak power, and load in kg in a back squat, incremental load, one-repetition maximum (1RM) test. In addition, during the rest period, jump ability (jump height and power) was assessed on a force platform. To compare data, a general linear model with repeated measures two-way analysis of variance was used. Significantly greater training improvements were observed in the BA group versus PLA group ( p  = 0.045) in the variables average power at 1RM (BA: 42.65%, 95% CI, 432.33, 522.52 VS. PLA: 21.07%, 95% CI, 384.77, 482.19) and average power at maximum power output ( p  = 0.037) (BA: 20.17%, 95% CI, 637.82, 751.90 VS. PLA; 10.74%, 95% CI, 628.31, 751.53). The pre- to post training average power gain produced at 1RM in BA could be explained by a greater maximal strength gain, or load lifted at 1RM ( p  = 0.014) (24 kg, 95% CI, 19.45, 28.41 VS. 16 kg, 95% CI, 10.58, 20.25) and in the number of sets executed ( p  = 0.025) in the incremental load test (BA: 2.79 sets, 95% CI, 2.08, 3.49 VS. PLA: 1.58 sets, 95% CI, 0.82, 2.34). β-Alanine supplementation was effective at increasing power output when lifting loads equivalent to the individual's maximal strength or when working at maximum power output. The improvement observed at 1RM was explained by a greater load lifted, or strength gain, in response to training in the participants who took this supplement.

Enhanced Medical Rehabilitation: Effectiveness of a clinical training model.

PubMed

Bland, Marghuretta D; Birkenmeier, Rebecca L; Barco, Peggy; Lenard, Emily; Lang, Catherine E; Lenze, Eric J

2016-10-14

Patient engagement in medical rehabilitation can be greatly influenced by their provider during therapy sessions. We developed Enhanced Medical Rehabilitation (EMR), a set of provider skills grounded in theories of behavior change. EMR utilizes 18 motivational techniques focused on providing frequent feedback to patients on their effort and progress and linking these to patient goals. To examine the effectiveness of a clinical training protocol for clinicians to do EMR, as measured by clinician adherence. A physical therapist, physical therapist assistant, occupational therapist, and certified occupational therapist assistant were trained in EMR. Training consisted of five formal training sessions and individual and group coaching. Adherence to EMR techniques was measured during two phases: Pre-Training and Maintenance, with an a priori target of 90% adherence by clinicians to each EMR technique. With training and coaching, clinician adherence per therapeutic activity significantly improved in 13 out of 18 items (p < 0.05). The target of 90% adherence was not achieved for many items. Our training and coaching program successfully trained clinicians to promote patient engagement during therapeutic service delivery, although not typically to 90% or greater adherence. Ongoing coaching efforts were necessary to increase adherence.

Effects of Goal Setting on Performance and Job Satisfaction

ERIC Educational Resources Information Center

Ivancevich, John M.

1976-01-01

Studied the effect of goal-setting training on the performance and job satisfaction of sales personnel. One group was trained in participative goal setting; one group was trained in assigned goal setting; and one group received no training. Both trained groups showed temporary improvements in performance and job satisfaction. For availability see…

A ferrofluid-based neural network: design of an analogue associative memory

NASA Astrophysics Data System (ADS)

Palm, R.; Korenivski, V.

2009-02-01

We analyse an associative memory based on a ferrofluid, consisting of a system of magnetic nano-particles suspended in a carrier fluid of variable viscosity subject to patterns of magnetic fields from an array of input and output magnetic pads. The association relies on forming patterns in the ferrofluid during a training phase, in which the magnetic dipoles are free to move and rotate to minimize the total energy of the system. Once equilibrated in energy for a given input-output magnetic field pattern pair, the particles are fully or partially immobilized by cooling the carrier liquid. Thus produced particle distributions control the memory states, which are read out magnetically using spin-valve sensors incorporated into the output pads. The actual memory consists of spin distributions that are dynamic in nature, realized only in response to the input patterns that the system has been trained for. Two training algorithms for storing multiple patterns are investigated. Using Monte Carlo simulations of the physical system, we demonstrate that the device is capable of storing and recalling two sets of images, each with an accuracy approaching 100%.

Neural Network and Letter Recognition.

NASA Astrophysics Data System (ADS)

Lee, Hue Yeon

Neural net architectures and learning algorithms that recognize hand written 36 alphanumeric characters are studied. The thin line input patterns written in 32 x 32 binary array are used. The system is comprised of two major components, viz. a preprocessing unit and a Recognition unit. The preprocessing unit in turn consists of three layers of neurons; the U-layer, the V-layer, and the C -layer. The functions of the U-layer is to extract local features by template matching. The correlation between the detected local features are considered. Through correlating neurons in a plane with their neighboring neurons, the V-layer would thicken the on-cells or lines that are groups of on-cells of the previous layer. These two correlations would yield some deformation tolerance and some of the rotational tolerance of the system. The C-layer then compresses data through the 'Gabor' transform. Pattern dependent choice of center and wavelengths of 'Gabor' filters is the cause of shift and scale tolerance of the system. Three different learning schemes had been investigated in the recognition unit, namely; the error back propagation learning with hidden units, a simple perceptron learning, and a competitive learning. Their performances were analyzed and compared. Since sometimes the network fails to distinguish between two letters that are inherently similar, additional ambiguity resolving neural nets are introduced on top of the above main neural net. The two dimensional Fourier transform is used as the preprocessing and the perceptron is used as the recognition unit of the ambiguity resolver. One hundred different person's handwriting sets are collected. Some of these are used as the training sets and the remainders are used as the test sets. The correct recognition rate of the system increases with the number of training sets and eventually saturates at a certain value. Similar recognition rates are obtained for the above three different learning algorithms. The minimum error rate, 4.9% is achieved for alphanumeric sets when 50 sets are trained. With the ambiguity resolver, it is reduced to 2.5%. In case that only numeral sets are trained and tested, 2.0% error rate is achieved. When only alphabet sets are considered, the error rate is reduced to 1.1%.

Evaluation of a parallel implementation of the learning portion of the backward error propagation neural network: experiments in artifact identification.

PubMed Central

Sittig, D. F.; Orr, J. A.

1991-01-01

Various methods have been proposed in an attempt to solve problems in artifact and/or alarm identification including expert systems, statistical signal processing techniques, and artificial neural networks (ANN). ANNs consist of a large number of simple processing units connected by weighted links. To develop truly robust ANNs, investigators are required to train their networks on huge training data sets, requiring enormous computing power. We implemented a parallel version of the backward error propagation neural network training algorithm in the widely portable parallel programming language C-Linda. A maximum speedup of 4.06 was obtained with six processors. This speedup represents a reduction in total run-time from approximately 6.4 hours to 1.5 hours. We conclude that use of the master-worker model of parallel computation is an excellent method for obtaining speedups in the backward error propagation neural network training algorithm. PMID:1807607

Systematic review of back schools, brief education, and fear-avoidance training for chronic low back pain.

PubMed

Brox, J I; Storheim, K; Grotle, M; Tveito, T H; Indahl, A; Eriksen, H R

2008-01-01

Seven previous systematic reviews (SRs) have evaluated back schools, and one has evaluated brief education, with the latest SR including studies until November 2004. The effectiveness of fear-avoidance training has not been assessed. To assess the effectiveness of back schools, brief education, and fear-avoidance training for chronic low back pain (CLBP). A SR. We searched the MEDLINE database of randomized controlled trials (RCT) until August 2006 for relevant trials reported in English. Assessment of effectiveness was based on pain, disability, and sick leave. RCTs that reported back schools, or brief education as the main intervention, were included. For fear-avoidance training, evaluation of domain-specific outcome was required. Two reviewers independently reviewed the studies. Eight RCTs including 1,002 patients evaluated back schools, three studies were of high quality. We found conflicting evidence for back schools compared with waiting list, placebo, usual care, and exercises, and a cognitive behavioral back school. Twelve trials including 3,583 patients evaluated brief education. Seven trials, six of high quality, evaluated brief education in the clinical setting. We found strong evidence of effectiveness on sick leave and short-term disability compared with usual care. We found conflicting or limited evidence for back book or Internet discussion (five trials, two of high quality) compared with waiting list, no intervention, massage, yoga, or exercises. Three RCTs of high quality, including 364 patients, evaluated fear-avoidance training. We found moderate evidence that there is no difference between rehabilitation including fear-avoidance training and spinal fusion. Consistent recommendations are given for brief education in the clinical setting, and fear-avoidance training should be considered as an alternative to spinal fusion, and back schools may be considered in the occupational setting. The discordance between reviews can be attributed differences in inclusion criteria and application of evidence rules.

Constellation Training Facility Support

NASA Technical Reports Server (NTRS)

Flores, Jose M.

2008-01-01

The National Aeronautics and Space Administration is developing the next set of vehicles that will take men back to the moon under the Constellation Program. The Constellation Training Facility (CxTF) is a project in development that will be used to train astronauts, instructors, and flight controllers on the operation of Constellation Program vehicles. It will also be used for procedure verification and validation of flight software and console tools. The CxTF will have simulations for the Crew Exploration Vehicle (CEV), Crew Module (CM), CEV Service Module (SM), Launch Abort System (LAS), Spacecraft Adapter (SA), Crew Launch Vehicle (CLV), Pressurized Cargo Variant CM, Pressurized Cargo Variant SM, Cargo Launch Vehicle, Earth Departure Stage (EDS), and the Lunar Surface Access Module (LSAM). The Facility will consist of part-task and full-task trainers, each with a specific set of mission training capabilities. Part task trainers will be used for focused training on a single vehicle system or set of related systems. Full task trainers will be used for training on complete vehicles and all of its subsystems. Support was provided in both software development and project planning areas of the CxTF project. Simulation software was developed for the hydraulic system of the Thrust Vector Control (TVC) of the ARES I launch vehicle. The TVC system is in charge of the actuation of the nozzle gimbals for navigation control of the upper stage of the ARES I rocket. Also, software was developed using C standards to send and receive data to and from hand controllers to be used in CxTF cockpit simulations. The hand controllers provided movement in all six rotational and translational axes. Under Project Planning & Control, support was provided to the development and maintenance of integrated schedules for both the Constellation Training Facility and Missions Operations Facilities Division. These schedules maintain communication between projects in different levels. The CxTF support provided is one that requires continuous maintenance since the project is still on initial development phases.

Crisis Management Simulation: Establishing a Dual Neurosurgery and Anesthesia Training Experience.

PubMed

Ciporen, Jeremy; Gillham, Haley; Noles, Michele; Dillman, Dawn; Baskerville, Mark; Haley, Caleb; Spight, Donn; Turner, Ryan C; Lucke-Wold, Brandon P

2018-01-01

Simulation training has been shown to be an effective teaching tool. Learner management of an intraoperative crisis such as a major cerebrovascular bleed requires effective teamwork, communication, and implementation of key skill sets at appropriate time points. This study establishes a first of a kind simulation experience in a neurosurgery/anesthesia resident (learners) team working together to manage an intraoperative crisis. Using a cadaveric cavernous carotid injury perfusion model, 7 neurosurgery and 6 anesthesia learners, were trained on appropriate vascular injury management using an endonasal endoscopic technique. Learners were evaluated on communication skills, crisis management algorithms, and implementation of appropriate skill sets at the right time. A preanatomic and postanatomic examination and postsimulation survey was administered to neurosurgery learners. Anesthesia learners provided posttraining evaluation through a tailored realism and teaching survey. Neurosurgery learners' anatomic examination score improved from presimulation (33.89%) to postsimulation (86.11%). No significant difference between learner specialties was observed for situation awareness, decision making, communications and teamwork, or leadership evaluations. Learners reported the simulation realistic, beneficial, and highly instructive. Realistic, first of kind, clinical simulation scenarios were presented to a neurosurgery/anesthesia resident team who worked together to manage an intraoperative crisis. Learners were effectively trained on crisis management, the importance of communication, and how to develop algorithms for future implementation in difficult scenarios. Learners were highly satisfied with the simulation training experience and requested that it be integrated more consistently into their residency training programs.

Does training improve diagnostic accuracy and inter-rater agreement in applying the Berlin radiographic definition of acute respiratory distress syndrome? A multicenter prospective study.

PubMed

Peng, Jin-Min; Qian, Chuan-Yun; Yu, Xiang-You; Zhao, Ming-Yan; Li, Shu-Sheng; Ma, Xiao-Chun; Kang, Yan; Zhou, Fa-Chun; He, Zhen-Yang; Qin, Tie-He; Yin, Yong-Jie; Jiang, Li; Hu, Zhen-Jie; Sun, Ren-Hua; Lin, Jian-Dong; Li, Tong; Wu, Da-Wei; An, You-Zhong; Ai, Yu-Hang; Zhou, Li-Hua; Cao, Xiang-Yuan; Zhang, Xi-Jing; Sun, Rong-Qing; Chen, Er-Zhen; Du, Bin

2017-01-20

Poor inter-rater reliability in chest radiograph interpretation has been reported in the context of acute respiratory distress syndrome (ARDS), although not for the Berlin definition of ARDS. We sought to examine the effect of training material on the accuracy and consistency of intensivists' chest radiograph interpretations for ARDS diagnosis. We conducted a rater agreement study in which 286 intensivists (residents 41.3%, junior attending physicians 35.3%, and senior attending physician 23.4%) independently reviewed the same 12 chest radiographs developed by the ARDS Definition Task Force ("the panel") before and after training. Radiographic diagnoses by the panel were classified into the consistent (n = 4), equivocal (n = 4), and inconsistent (n = 4) categories and were used as a reference. The 1.5-hour training course attended by all 286 intensivists included introduction of the diagnostic rationale, and a subsequent in-depth discussion to reach consensus for all 12 radiographs. Overall diagnostic accuracy, which was defined as the percentage of chest radiographs that were interpreted correctly, improved but remained poor after training (42.0 ± 14.8% before training vs. 55.3 ± 23.4% after training, p < 0.001). Diagnostic sensitivity and specificity improved after training for all diagnostic categories (p < 0.001), with the exception of specificity for the equivocal category (p = 0.883). Diagnostic accuracy was higher for the consistent category than for the inconsistent and equivocal categories (p < 0.001). Comparisons of pre-training and post-training results revealed that inter-rater agreement was poor and did not improve after training, as assessed by overall agreement (0.450 ± 0.406 vs. 0.461 ± 0.575, p = 0.792), Fleiss's kappa (0.133 ± 0.575 vs. 0.178 ± 0.710, p = 0.405), and intraclass correlation coefficient (ICC; 0.219 vs. 0.276, p = 0.470). The radiographic diagnostic accuracy and inter-rater agreement were poor when the Berlin radiographic definition was used, and were not significantly improved by the training set of chest radiographs developed by the ARDS Definition Task Force. The study was registered at ClinicalTrials.gov (registration number NCT01704066 ) on 6 October 2012.

Relevant, irredundant feature selection and noisy example elimination.

PubMed

Lashkia, George V; Anthony, Laurence

2004-04-01

In many real-world situations, the method for computing the desired output from a set of inputs is unknown. One strategy for solving these types of problems is to learn the input-output functionality from examples in a training set. However, in many situations it is difficult to know what information is relevant to the task at hand. Subsequently, researchers have investigated ways to deal with the so-called problem of consistency of attributes, i.e., attributes that can distinguish examples from different classes. In this paper, we first prove that the notion of relevance of attributes is directly related to the consistency of attributes, and show how relevant, irredundant attributes can be selected. We then compare different relevant attribute selection algorithms, and show the superiority of algorithms that select irredundant attributes over those that select relevant attributes. We also show that searching for an "optimal" subset of attributes, which is considered to be the main purpose of attribute selection, is not the best way to improve the accuracy of classifiers. Employing sets of relevant, irredundant attributes improves classification accuracy in many more cases. Finally, we propose a new method for selecting relevant examples, which is based on filtering the so-called pattern frequency domain. By identifying examples that are nontypical in the determination of relevant, irredundant attributes, irrelevant examples can be eliminated prior to the learning process. Empirical results using artificial and real databases show the effectiveness of the proposed method in selecting relevant examples leading to improved performance even on greatly reduced training sets.

Evaluation of skill-based training program on rational drug treatment for medical interns

PubMed Central

Venkatesan, Murugan; Dongre, Amol R; Ganapathy, Kalaiselvan

2017-01-01

Context: A module-based training program for medical interns using World Health Organization guide for good prescription along with the individual feedback on their prescription was developed and implemented. Objective: The objective of the study was to obtain the medical interns’ reactions to newly developed skill-based training program on rational treatment. Study Setting: This study was conducted at the Department of Community Medicine. Participants: A total of 96 medical interns were included in the study. Study Design: A cross-sectional study consisting of retro-prefeedback and open-ended questions about self-assessment of perceived skill on rational treatment. Analysis: Collected data were entered in Epi Info (3.5.4) and analyzed. Results: After training, there was a significant increase in self-perceived posttest scores of setting up the therapeutic objective for the treatment (2.9–4.9), ability to select the correct drug (2.8–5.1), ability to select right dose, schedule, and duration of drugs (2.5–4.9). and overall prescription skill (2.9–4.9). There is a significant decrease in self-perceived scores in the skill of practicing polypharmacy (4.1–2.5). Conclusions: Overall, the training program was taken well and interns perceived their skill on rational treatment was improved as shown by the feedback. PMID:29564272

Effects of weight training on cognitive functions in elderly with Alzheimer's disease

PubMed Central

Vital, Thays Martins; Hernández, Salma S. Soleman; Pedroso, Renata Valle; Teixeira, Camila Vieira Ligo; Garuffi, Marcelo; Stein, Angelica Miki; Costa, José Luiz Riani; Stella, Florindo

2012-01-01

Deterioration in cognitive functions is characteristic in Alzheimer's disease (AD) and may be associated with decline in daily living activities with consequent reduced quality of life. Objective To analyze weight training effects on cognitive functions in elderly with AD. Subjects 34 elderly with AD were allocated into two groups: Training Group (TG) and Social Gathering Group (SGG). Methods Global cognitive status was determined using the Mini-Mental State Exam. Specific cognitive functions were measured using the Brief Cognitive Battery, Clock Drawing Test and Verbal Fluency Test. The protocols were performed three times a week, one hour per session. The weight training protocol consisted of three sets of 20 repetitions, with two minutes of rest between sets and exercises. The activities proposed for the SGG were not systematized and aimed at promoting social interaction among patients. The statistical analyses were performed with the U Mann Whitney and Wilcoxon tests for group comparisons. All analyses were considered statistically significant at a p-value of 0.05. Results There were no significant differences associated to the effects of the practice of weight training on cognition in AD patients. Conclusion In this study, no improvement in cognitive functions was evident in elderly with AD who followed a low intensity resistance exercise protocol. Thus, future studies could evaluate the effect of more intense exercise programs. PMID:29213805

Quantum adiabatic machine learning

NASA Astrophysics Data System (ADS)

Pudenz, Kristen L.; Lidar, Daniel A.

2013-05-01

We develop an approach to machine learning and anomaly detection via quantum adiabatic evolution. This approach consists of two quantum phases, with some amount of classical preprocessing to set up the quantum problems. In the training phase we identify an optimal set of weak classifiers, to form a single strong classifier. In the testing phase we adiabatically evolve one or more strong classifiers on a superposition of inputs in order to find certain anomalous elements in the classification space. Both the training and testing phases are executed via quantum adiabatic evolution. All quantum processing is strictly limited to two-qubit interactions so as to ensure physical feasibility. We apply and illustrate this approach in detail to the problem of software verification and validation, with a specific example of the learning phase applied to a problem of interest in flight control systems. Beyond this example, the algorithm can be used to attack a broad class of anomaly detection problems.

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

Comparative Effects of In-Season Full-Back Squat, Resisted Sprint Training, and Plyometric Training on Explosive Performance in U-19 Elite Soccer Players.

PubMed

de Hoyo, Moises; Gonzalo-Skok, Oliver; Sañudo, Borja; Carrascal, Claudio; Plaza-Armas, Jose R; Camacho-Candil, Fernando; Otero-Esquina, Carlos

2016-02-01

The aim of this study was to analyze the effects of 3 different low/moderate load strength training methods (full-back squat [SQ], resisted sprint with sled towing [RS], and plyometric and specific drills training [PLYO]) on sprinting, jumping, and change of direction (COD) abilities in soccer players. Thirty-two young elite male Spanish soccer players participated in the study. Subjects performed 2 specific strength training sessions per week, in addition to their normal training sessions for 8 weeks. The full-back squat protocol consisted of 2-3 sets × 4-8 repetitions at 40-60% 1 repetition maximum (∼ 1.28-0.98 m · s(-1)). The resisted sprint training was compounded by 6-10 sets × 20-m loaded sprints (12.6% of body mass). The plyometric and specific drills training was based on 1-3 sets × 2-3 repetitions of 8 plyometric and speed/agility exercises. Testing sessions included a countermovement jump (CMJ), a 20-m sprint (10-m split time), a 50-m (30-m split time) sprint, and COD test (i.e., Zig-Zag test). Substantial improvements (likely to almost certainly) in CMJ (effect size [ES]: 0.50-0.57) and 30-50 m (ES: 0.45-0.84) were found in every group in comparison to pretest results. Moreover, players in PLYO and SQ groups also showed substantial enhancements (likely to very likely) in 0-50 m (ES: 0.46-0.60). In addition, 10-20 m was also improved (very likely) in the SQ group (ES: 0.61). Between-group analyses showed that improvements in 10-20 m (ES: 0.57) and 30-50 m (ES: 0.40) were likely greater in the SQ group than in the RS group. Also, 10-20 m (ES: 0.49) was substantially better in the SQ group than in the PLYO group. In conclusion, the present strength training methods used in this study seem to be effective to improve jumping and sprinting abilities, but COD might need other stimulus to achieve positive effects.

Do informal musical activities shape auditory skill development in preschool-age children?

PubMed

Putkinen, Vesa; Saarikivi, Katri; Tervaniemi, Mari

2013-08-29

The influence of formal musical training on auditory cognition has been well established. For the majority of children, however, musical experience does not primarily consist of adult-guided training on a musical instrument. Instead, young children mostly engage in everyday musical activities such as singing and musical play. Here, we review recent electrophysiological and behavioral studies carried out in our laboratory and elsewhere which have begun to map how developing auditory skills are shaped by such informal musical activities both at home and in playschool-type settings. Although more research is still needed, the evidence emerging from these studies suggests that, in addition to formal musical training, informal musical activities can also influence the maturation of auditory discrimination and attention in preschool-aged children.

Do informal musical activities shape auditory skill development in preschool-age children?

PubMed Central

Putkinen, Vesa; Saarikivi, Katri; Tervaniemi, Mari

2013-01-01

The influence of formal musical training on auditory cognition has been well established. For the majority of children, however, musical experience does not primarily consist of adult-guided training on a musical instrument. Instead, young children mostly engage in everyday musical activities such as singing and musical play. Here, we review recent electrophysiological and behavioral studies carried out in our laboratory and elsewhere which have begun to map how developing auditory skills are shaped by such informal musical activities both at home and in playschool-type settings. Although more research is still needed, the evidence emerging from these studies suggests that, in addition to formal musical training, informal musical activities can also influence the maturation of auditory discrimination and attention in preschool-aged children. PMID:24009597

The effectiveness and cost-effectiveness of parent training/education programmes for the treatment of conduct disorder, including oppositional defiant disorder, in children.

PubMed

Dretzke, J; Frew, E; Davenport, C; Barlow, J; Stewart-Brown, S; Sandercock, J; Bayliss, S; Raftery, J; Hyde, C; Taylor, R

2005-12-01

To assess the clinical and cost-effectiveness of parent training programmes for the treatment of children with conduct disorder (CD) up to the age of 18 years. Electronic databases. For the effectiveness review, relevant studies were identified and evaluated. A quantitative synthesis of behavioural outcomes across trials was also undertaken using two approaches: vote counting and meta-analysis. The economic analysis consisted of reviewing previous economic/cost evaluations of parent training/education programmes and the economic information within sponsor's submissions; carrying out a detailed exploration of costs of parent training/education programmes; and a de novo modelling assessment of the cost-effectiveness of parent training/education programmes. The potential budget impact to the health service of implementing such programmes was also considered. Many of the 37 randomised controlled trials that met the review inclusion and exclusion criteria were assessed as being of poor methodological quality. Studies were clinically heterogeneous in terms of the population, type of parent training/education programme and content, setting, delivery, length and child behaviour outcomes used. Both vote counting and meta-analysis revealed a consistent trend across all studies towards short-term effectiveness (up to 4 months) of parent training/education programmes (compared with control) as measured by a change in child behaviour. Pooled estimates showed a statistically significant improvement on the Eyberg Child Behaviour Inventory frequency and intensity scales, the Dyadic Parent-Child Interaction Coding System and the Child Behaviour Checklist. No studies reported a statistically significant result favouring control over parent training/education programmes. There were few statistically significant differences between different parent training/education programmes, although there was a trend towards more intensive interventions (e.g. longer contact hours, additional child involvement) being more effective. The cost of treating CD is high, with costs incurred by many agencies. A recent study suggested that by age 28, costs for individuals with CD were around 10 times higher than for those with no problems, with a mean cost of 70,019 pounds sterling. Criminality incurs the greatest cost, followed by educational provision, foster and residential care and state benefits. Only a small proportion of these costs fall on health services. Using a 'bottom-up' costing approach, the costs per family of providing parent training/education programmes range from 629 pounds sterling to 3839 pounds sterling depending on the type and style of delivery. Using the conservative assumption that there are no cost savings from treatment, a total lifetime quality of life gain of 0.1 would give a cost per quality-adjusted life-year of between 38,393 pounds sterling and 6288 pounds sterling depending on the type of programme delivery and setting. Parent training/education programmes appear to be an effective and potentially cost-effective therapy for children with CD. However, the relative effectiveness and cost-effectiveness of different models (such as therapy intensity and setting) require further investigation. Further research is required on the impact of parent training/education programmes on the quality of life of children with CD and their parents/carers, as well as on longer term child outcomes.

Fourier spatial frequency analysis for image classification: training the training set

NASA Astrophysics Data System (ADS)

Johnson, Timothy H.; Lhamo, Yigah; Shi, Lingyan; Alfano, Robert R.; Russell, Stewart

2016-04-01

The Directional Fourier Spatial Frequencies (DFSF) of a 2D image can identify similarity in spatial patterns within groups of related images. A Support Vector Machine (SVM) can then be used to classify images if the inter-image variance of the FSF in the training set is bounded. However, if variation in FSF increases with training set size, accuracy may decrease as the size of the training set increases. This calls for a method to identify a set of training images from among the originals that can form a vector basis for the entire class. Applying the Cauchy product method we extract the DFSF spectrum from radiographs of osteoporotic bone, and use it as a matched filter set to eliminate noise and image specific frequencies, and demonstrate that selection of a subset of superclassifiers from within a set of training images improves SVM accuracy. Central to this challenge is that the size of the search space can become computationally prohibitive for all but the smallest training sets. We are investigating methods to reduce the search space to identify an optimal subset of basis training images.

Court-Mandated Counseling for Men Who Batter: A Three-Day Workshop for Mental Health Professionals. Participant's Manual.

ERIC Educational Resources Information Center

Ganley, Anne L.

The purpose of this manual is to provide a written tool for those participating in a 3-day workshop designed to train mental health professionals from diverse settings and communities to counsel court-mandated batterers. The manual consists of: (1) an outline of the workshop; (2) an introduction; (3) six chapters/sections; (4) notes; and (5) three…

The Use of Autonomic Modulation Device to Control Training Performance after High-Intensity Interval Training Program.

PubMed

Clemente-Suárez, Vicente Javier; Arroyo-Toledo, Juan Jaime

2018-01-25

The aim of the present research was to analyze the autonomic response in a group of trained swimmers before and after conducting a 4-week period of high-intensity interval training (HIT). Heart rate variability was analyzed in 14 swimmers (16.2 ± 2.6 years, 169.1 ± 10.2 cm and 61.3 ± 9.9 kg) in basal condition and during a HIT session before and after completing a training period. The HIT session that was evaluated consisted of: 16 × 25 m maximum speed, resting 30 s between sets. Participants combined aerobic training with tethered swimming and HIT sessions three times per week in a period of 4 weeks. Results showed a significantly decrease (p < 0.05) of the standard deviation of the NN intervals (SDNN), the standard deviation of differences between adjacent NN intervals (SDSD), the number of successive difference of intervals which differ by more than 50 ms (NN50), after the training period. Results showed a higher parasympathetic activation besides improvements in autonomic adaptation after HIT training period.

Ensemble Methods for Classification of Physical Activities from Wrist Accelerometry.

PubMed

Chowdhury, Alok Kumar; Tjondronegoro, Dian; Chandran, Vinod; Trost, Stewart G

2017-09-01

To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbor, support vector machine, and neural network). The study used three independent data sets that included wrist-worn accelerometer data. For each data set, a four-step classification framework consisting of data preprocessing, feature extraction, normalization and feature selection, and classifier training and testing was implemented. For the custom ensemble, decisions from the single classifiers were aggregated using three decision fusion methods: weighted majority vote, naïve Bayes combination, and behavior knowledge space combination. Classifiers were cross-validated using leave-one subject out cross-validation and compared on the basis of average F1 scores. In all three data sets, ensemble learning methods consistently outperformed the individual classifiers. Among the conventional ensemble methods, random forest models provided consistently high activity recognition; however, the custom ensemble model using weighted majority voting demonstrated the highest classification accuracy in two of the three data sets. Combining multiple individual classifiers using conventional or custom ensemble learning methods can improve activity recognition accuracy from wrist-worn accelerometer data.

The nature of expertise in fingerprint examiners.

PubMed

Busey, Thomas A; Parada, Francisco J

2010-04-01

Latent print examinations involve a complex set of psychological and cognitive processes. This article summarizes existing work that has addressed how training and experience creates changes in latent print examiners. Experience appears to improve overall accuracy, increase visual working memory, and lead to configural processing of upright fingerprints. Experts also demonstrate a narrower visual filter and, as a group, tend to show greater consistency when viewing ink prints. These findings address recent criticisms of latent print evidence, but many open questions still exist. Cognitive scientists are well positioned to conduct studies that will improve the training and practices of latent print examiners, and suggestions for becoming involved in fingerprint research are provided.

The effects of spaced retrieval training in improving hyperphagia of people living with dementia in residential settings.

PubMed

Hsu, Chia-Ning; Lin, Li-Chan; Wu, Shiao-Chi

2017-10-01

To investigate the effectiveness of spaced retrieval for improving hyperphagia in patients with dementia in residential care settings. Although 10-30% of patients with dementia have hyperphagia, most studies have focused on eating difficulties. Only a few studies have focused on hyperphagia. Various memory problems cause hyperphagia in patients with dementia. Spaced retrieval, a cognitive technique for information learning, can be used as a training method to improve memory loss. Recent studies showed that patients who received the training successfully memorised information learned in the training and correctly applied it to their daily lives. Single-blind experiments were performed. The 97 subjects with dementia were recruited from seven institutions. All research participants were stratified into three groups according to cognitive impairment severity and Hyperphagic Behavior Scale scores and then randomly assigned to the experimental and control groups. The experimental group received a six-week one-by-one spaced retrieval training for hyperphagia behaviour. The control group received routine care. After the intervention, the frequency and severity of hyperphagia in the patients with dementia, and food intake were significantly lower in the experimental group than in the control group. However, body mass index did not significantly differ. Our results suggest that the spaced retrieval training could decrease the frequency and severity of hyperphagia in patients with dementia. The content of this training programme is consistent with the normal manner of eating in daily life and is easy for patients to understand and perform. Therefore, it can be applied in residents' daily lives. This study confirms the efficacy of the spaced retrieval training protocol for hyperphagia in patients with dementia. In future studies, the follow-up duration can be increased to determine the long-term effectiveness of the intervention. © 2016 John Wiley & Sons Ltd.

Protein contact prediction using patterns of correlation.

PubMed

Hamilton, Nicholas; Burrage, Kevin; Ragan, Mark A; Huber, Thomas

2004-09-01

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two "windows" of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. Copyright 2004 Wiley-Liss, Inc.

Rational-emotive behavior therapy and the formation of stimulus equivalence classes.

PubMed

Plaud, J J; Gaither, G A; Weller, L A; Bigwood, S J; Barth, J; von Duvillard, S P

1998-08-01

Stimulus equivalence is a behavioral approach to analyzing the "meaning" of stimulus sets and has an implication for clinical psychology. The formation of three-member (A --> B --> C) stimulus equivalence classes was used to investigate the effects of three different sets of sample and comparison stimuli on emergent behavior. The three stimulus sets were composed of Rational-Emotive Behavior Therapy (REBT)-related words, non-REBT emotionally charged words, and a third category of neutral words composed of flower labels. Sixty-two women and men participated in a modified matching-to-sample experiment. Using a mixed cross-over design, and controlling for serial order effects, participants received conditional training and emergent relationship training in the three stimulus set conditions. Results revealed a significant interaction between the formation of stimulus equivalence classes and stimulus meaning, indicating consistently biased responding in favor of reaching criterion responding more slowly for REBT-related and non-REBT emotionally charged words. Results were examined in the context of an analysis of the importance of stimulus meaning on behavior and the relation of stimulus meaning to behavioral and cognitive theories, with special appraisal given to the influence of fear-related discriminative stimuli on behavior.

Web based scoring is useful for validation and harmonisation of scoring criteria within RENEB.

PubMed

Romm, Horst; Ainsbury, Elizabeth A; Barquinero, Joan Francesc; Barrios, Leonardo; Beinke, Christina; Cucu, Alexandra; Domene, Mercedes Moreno; Filippi, Silvia; Monteiro Gil, Octávia; Gregoire, Eric; Hadjidekova, Valeria; Hatzi, Vasia; Lindholm, Carita; M Kacher, Radhia; Montoro, Alegria; Moquet, Jayne; Noditi, Mihaela; Oestreicher, Ursula; Palitti, Fabrizio; Pantelias, Gabriel; Prieto, María Jesús; Popescu, Irina; Rothkamm, Kai; Sebastià, Natividad; Sommer, Sylwester; Terzoudi, Georgia; Testa, Antonella; Wojcik, Andrzej

2017-01-01

To establish a training data set of digital images and to investigate the scoring criteria and dose assessment of the dicentric assay within the European network of biodosimetry (RENEB), a web based scoring inter-comparison was undertaken by 17 RENEB partners. Two sets of 50 high resolution images were uploaded onto the RENEB website. One set included metaphases after a moderate exposure (1.3 Gy) and the other set consisted of metaphases after a high dose exposure (3.5 Gy). The laboratories used their own calibration curves for estimating doses based on observed aberration frequencies. The dose estimations and 95% confidence limits were compared to the actual doses and the corresponding z-values were satisfactory for the majority; only the dose estimations from two laboratories were too low or too high. The coefficients of variation were 17.6% for the moderate and 11.2% for the high dose. Metaphases with controversial results could be identified for training purposes. Overall, the web based scoring of the two galleries by the 17 laboratories produced very good results. Application of web based scoring for the dicentric assay may therefore be a relevant strategy for an operational biodosimetry assistance network.

Suggested set-up and layout of instruments and equipment for advanced operative laparoscopy.

PubMed

Winer, W K; Lyons, T L

1995-02-01

Crucial elements that ensure the organization and smoothness of a laparoscopic procedure are clear communication among well-trained endoscopy team members, properly maintained equipment, and a sensible layout of the instruments. The team consists of the surgeon, surgical assistant, circulator, scrub nurse, laser nurse, and anesthesiologist. To promote continuity and interaction and to ensure a systematic, pleasant pace for laparoscopic procedures, the team should establish a specific routine, as well as set-up and layout of tables, equipment, and instruments. Key ingredients for advanced operative laparoscopy to be performed with optimum efficiency and effectiveness are the best organization and placement of the equipment, instrumentation, and team in a particular setting in the operating room.

Intensive training program for ultrasound diagnosis of adnexal masses: protocol and preliminary results.

PubMed

Alcázar, J L; Díaz, L; Flórez, P; Guerriero, S; Jurado, M

2013-08-01

To assess the feasibility of a specific training program for ultrasound diagnosis of adnexal masses. A 2-month intensive training program was developed. The program protocol consisted of a 1-day intensive theoretical course focused on clinical and sonographic issues related to adnexal masses and ovarian cancer, followed by a 4-week real-time ultrasound training program in a tertiary center (25-30 adnexal masses evaluated per month) and a final 4-week period for offline assessment of three-dimensional (3D) volumes from adnexal masses. In this final period, each trainee evaluated five sets of 100 3D volumes. 3D volumes contained gray-scale and power Doppler information, and the trainee was provided with clinical data for each case (patient age, menopausal status and reported symptoms). 3D volumes were obtained from surgically removed masses that had undergone histological diagnosis or from masses that had been followed up until resolution. After assessment of each set, the trainee's diagnostic performance was calculated (sensitivity and specificity) and each incorrectly classified mass was evaluated with the trainer. The objective was to achieve a sensitivity of > 95% and a specificity of > 90%. Learning curve cumulative summation (LC-CUSUM) graphs were plotted to assess the learning curve for the trainees. One trainer and two trainees with little experience in gynecological ultrasound (one gynecologist and one radiologist) participated in this study. LC-CUSUM graphs showed that competence was achieved after 170 or 185 examinations. The objectives for diagnostic performance were achieved after assessment of the second set of 3D volumes (200 cases) for each trainee. The proposed training program appears to be feasible. High diagnostic performance can be achieved after analysis of 200 cases and maintained thereafter. Copyright © 2013 ISUOG. Published by John Wiley & Sons Ltd.

A new dose of maximal-intensity interval training in hypoxia to improve body composition and hemoglobin and hematocrit levels: a pilot study.

PubMed

Camacho-Cardenosa, Marta; Camacho-Cardenosa, Alba; Martínez Guardado, Ismael; Marcos-Serrano, Marta; Timon, Rafael; Olcina, Guillermo

2017-01-01

This pilot study had the aim to determine the effects of a new dose of maximal-intensity interval training in hypoxia in active adults. Twenty-four university student volunteers were randomly assigned to three groups: hypoxia group, normoxia group or control group. The eight training sessions consisted of 2 sets of 5 repeated sprints of 10 seconds with a recovery of 20 seconds between sprints and a recovery period of 10 minutes between sets. Body composition was measured following standard procedures. A blood sample was taken for an immediate hematocrit (HCT) and hemoglobin (Hb) concentration assessment. An all-out 3-ute test was performed to evaluate ventilation parameters and power. HCT and Hb were significantly higher for the hypoxia group in Post- and Det- (P=0.01; P=0.03). Fat mass percentage was significantly lower for the hypoxia group in both assessments (P=0.05; P=0.05). The hypoxia group underwent a significant increase in mean power after the recovery period. A new dose of 8 sessions of maximal-intensity interval training in hypoxia is enough to decrease the percentage of fat mass and to improve HCT and Hb parameters and mean muscle power in healthy and active adults.

A summative, Objective, Structured, Clinical Examination in ENT used to assess postgraduate doctors after one year of ENT training, as part of the Diploma of Otorhinolaryngology, Head and Neck Surgery.

PubMed

Drake-Lee, A B; Skinner, D; Hawthorne, M; Clarke, R

2009-10-01

'High stakes' postgraduate medical examinations should conform to current educational standards. In the UK and Ireland, national assessments in surgery are devised and managed through the examination structure of the Royal Colleges of Surgeons. Their efforts are not reported in the medical education literature. In the current paper, we aim to clarify this process. To replace the clinical section of the Diploma of Otorhinolaryngology with an Objective, Structured, Clinical Examination, and to set the level of the assessment at one year of postgraduate training in the specialty. After 'blueprinting' against the whole curriculum, an Objective, Structured, Clinical Examination comprising 25 stations was divided into six clinical stations and 19 other stations exploring written case histories, instruments, test results, written communication skills and interpretation skills. The pass mark was set using a modified borderline method and other methods, and statistical analysis of the results was performed. The results of nine examinations between May 2004 and May 2008 are presented. The pass mark varied between 68 and 82 per cent. Internal consistency was good, with a Cronbach's alpha value of 0.99 for all examinations and split-half statistics varying from 0.96 to 0.99. Different standard settings gave similar pass marks. We have developed a summative, Objective, Structured, Clinical Examination for doctors training in otorhinolaryngology, reported herein. The objectives and standards of setting a high quality assessment were met.

Learning Outcome Measurement in Nurse Participants After Disaster Training.

PubMed

Farra, Sharon L; Smith, Sherrill; Bashaw, Marie A

2016-10-01

The National Disaster Health Consortium is an interprofessional disaster training program. Using the Hierarchical Learning Framework of Competency Sets in Disaster Medicine and Public Health, this program educates nurses and other professionals to provide competent care and leadership within the interprofessional team. This study examined outcomes of this training. Training consisted of a combination of online and on-site training. Learning outcomes were measured by using the Emergency Preparedness Information Questionnaire (EPIQ) pre/post training and participant performance during live functional exercises with the use of rubrics based on Homeland Security Exercise and Evaluation principles. A total of 64 participants completed the EPIQ before and after training. The mean EPIQ pre-training score of 154 and mean post-training score of 81 (reverse-scored) was found to be statistically significant by paired t-test (P<0.001). Performance was evaluated in the areas of triage, re-triage, surge response, and sheltering. Greater than 90% of the exercise criteria were either met or partially met. Participants successfully achieved overall objectives in all scenarios. Disaster response requires nurses and other providers to function in interprofessional teams. Educational projects, like the National Disaster Health Consortium program, offer the potential to address the need for a standardized, interprofessional disaster training curriculum to promote positive outcomes. (Disaster Med Public Health Preparedness. 2016;page 1 of 6).

Stress training improves performance during a stressful flight.

PubMed

McClernon, Christopher K; McCauley, Michael E; O'Connor, Paul E; Warm, Joel S

2011-06-01

This study investigated whether stress training introduced during the acquisition of simulator-based flight skills enhances pilot performance during subsequent stressful flight operations in an actual aircraft. Despite knowledge that preconditions to aircraft accidents can be strongly influenced by pilot stress, little is known about the effectiveness of stress training and how it transfers to operational flight settings. For this study, 30 participants with no flying experience were assigned at random to a stress-trained treatment group or a control group. Stress training consisted of systematic pairing of skill acquisition in a flight simulator with stress coping mechanisms in the presence of a cold pressor. Control participants received identical flight skill acquisition training but without stress training. Participants then performed a stressful flying task in a Piper Archer aircraft. Stress-trained research participants flew the aircraft more smoothly, as recorded by aircraft telemetry data, and generally better, as recorded by flight instructor evaluations, than did control participants. Introducing stress coping mechanisms during flight training improved performance in a stressful flying task. The results of this study indicate that stress training during the acquisition of flight skills may serve to enhance pilot performance in stressful operational flight and, therefore, might mitigate the contribution of pilot stress to aircraft mishaps.

Case Study: Does training of private networks of Family Planning clinicians in urban Pakistan affect service utilization?

PubMed Central

2010-01-01

Background To determine whether training of providers participating in franchise clinic networks is associated with increased Family Planning service use among low-income urban families in Pakistan. Methods The study uses 2001 survey data consisting of interviews with 1113 clinical and non-clinical providers working in public and private hospitals/clinics. Data analysis excludes non-clinical providers reducing sample size to 822. Variables for the analysis are divided into client volume, and training in family planning. Regression models are used to compute the association between training and service use in franchise versus private non-franchise clinics. Results In franchise clinic networks, staff are 6.5 times more likely to receive family planning training (P = 0.00) relative to private non-franchises. Service use was significantly associated with training (P = 0.00), franchise affiliation (P = 0.01), providers' years of family planning experience (P = 0.02) and the number of trained staff working at government owned clinics (P = 0.00). In this setting, nurses are significantly less likely to receive training compared to doctors (P = 0.00). Conclusions These findings suggest that franchises recruit and train various cadres of health workers and training maybe associated with increased service use through improvement in quality of services. PMID:21062460

Case Study: Does training of private networks of Family Planning clinicians in urban Pakistan affect service utilization?

PubMed

Qureshi, Asma M

2010-11-09

To determine whether training of providers participating in franchise clinic networks is associated with increased Family Planning service use among low-income urban families in Pakistan. The study uses 2001 survey data consisting of interviews with 1113 clinical and non-clinical providers working in public and private hospitals/clinics. Data analysis excludes non-clinical providers reducing sample size to 822. Variables for the analysis are divided into client volume, and training in family planning. Regression models are used to compute the association between training and service use in franchise versus private non-franchise clinics. In franchise clinic networks, staff are 6.5 times more likely to receive family planning training (P = 0.00) relative to private non-franchises. Service use was significantly associated with training (P = 0.00), franchise affiliation (P = 0.01), providers' years of family planning experience (P = 0.02) and the number of trained staff working at government owned clinics (P = 0.00). In this setting, nurses are significantly less likely to receive training compared to doctors (P = 0.00). These findings suggest that franchises recruit and train various cadres of health workers and training maybe associated with increased service use through improvement in quality of services.

Folk Dance Pattern Recognition Over Depth Images Acquired via Kinect Sensor

NASA Astrophysics Data System (ADS)

Protopapadakis, E.; Grammatikopoulou, A.; Doulamis, A.; Grammalidis, N.

2017-02-01

The possibility of accurate recognition of folk dance patterns is investigated in this paper. System inputs are raw skeleton data, provided by a low cost sensor. In particular, data were obtained by monitoring three professional dancers, using a Kinect II sensor. A set of six traditional Greek dances (without their variations) consists the investigated data. A two-step process was adopted. At first, the most descriptive skeleton data were selected using a combination of density based and sparse modelling algorithms. Then, the representative data served as training set for a variety of classifiers.

An implementation strategy to improve the guideline adherence of insurance physicians: an experiment in a controlled setting

PubMed Central

2011-01-01

Background The aim of this study was to investigate the efficacy of a newly developed implementation strategy for the insurance medicine guidelines for depression in the Netherlands. We hypothesized that an educational intervention would increase the insurance physicians' (IPs) guideline adherence in a controlled setting. Methods Forty IPs were allocated in a randomised controlled trial (RCT) to an intervention group (IG) (n = 21) and a control group (CG) (n = 19). The IG received tailored training in applying the guidelines for depression, while the CG received an alternative programme. Baseline (T0) and follow-up (T1) measurements were conducted before and after the intervention within a period of two weeks. The intervention consisted of a workshop in which the evidence-based theory of the guidelines was translated for use in practice, with the help of various tools. The IPs had to write a case-report on the basis of video cases, two before and two after the training. Specially trained and blinded test IPs judged the case reports independently on the basis of six performance indicators. Primary outcome measure in the controlled setting of the trial was guideline adherence measured by six performance indicators on a scale of one to seven. Secondary outcome measure was knowledge of the guidelines for depression. Analyses were performed using Linear Mixed Models, and ANCOVA. Results We found significantly higher scores in the IG than in the CG at T1 for both outcomes. The interaction effect (standard error; p-value) of group crossed with time was 0.97 (0.19; p < 0.0005) for guideline adherence in the controlled setting. The group effect at T1 for the knowledge test was 0.86 (0.40; p = 0.038). Conclusions The newly developed implementation strategy for the insurance medicine guidelines for depression improved the guideline adherence of the trained IPs in disability assessments of clients with depression when performed in a controlled setting. Furthermore, the trained IPs showed gains in knowledge of the guidelines for depression. Trial registration Netherlands' Trial Register NTR1863. PMID:22188876

DMT-TAFM: a data mining tool for technical analysis of futures market

NASA Astrophysics Data System (ADS)

Stepanov, Vladimir; Sathaye, Archana

2002-03-01

Technical analysis of financial markets describes many patterns of market behavior. For practical use, all these descriptions need to be adjusted for each particular trading session. In this paper, we develop a data mining tool for technical analysis of the futures markets (DMT-TAFM), which dynamically generates rules based on the notion of the price pattern similarity. The tool consists of three main components. The first component provides visualization of data series on a chart with different ranges, scales, and chart sizes and types. The second component constructs pattern descriptions using sets of polynomials. The third component specifies the training set for mining, defines the similarity notion, and searches for a set of similar patterns. DMT-TAFM is useful to prepare the data, and then reveal and systemize statistical information about similar patterns found in any type of historical price series. We performed experiments with our tool on three decades of trading data fro hundred types of futures. Our results for this data set shows that, we can prove or disprove many well-known patterns based on real data, as well as reveal new ones, and use the set of relatively consistent patterns found during data mining for developing better futures trading strategies.

MABAL: a Novel Deep-Learning Architecture for Machine-Assisted Bone Age Labeling.

PubMed

Mutasa, Simukayi; Chang, Peter D; Ruzal-Shapiro, Carrie; Ayyala, Rama

2018-02-05

Bone age assessment (BAA) is a commonly performed diagnostic study in pediatric radiology to assess skeletal maturity. The most commonly utilized method for assessment of BAA is the Greulich and Pyle method (Pediatr Radiol 46.9:1269-1274, 2016; Arch Dis Child 81.2:172-173, 1999) atlas. The evaluation of BAA can be a tedious and time-consuming process for the radiologist. As such, several computer-assisted detection/diagnosis (CAD) methods have been proposed for automation of BAA. Classical CAD tools have traditionally relied on hard-coded algorithmic features for BAA which suffer from a variety of drawbacks. Recently, the advent and proliferation of convolutional neural networks (CNNs) has shown promise in a variety of medical imaging applications. There have been at least two published applications of using deep learning for evaluation of bone age (Med Image Anal 36:41-51, 2017; JDI 1-5, 2017). However, current implementations are limited by a combination of both architecture design and relatively small datasets. The purpose of this study is to demonstrate the benefits of a customized neural network algorithm carefully calibrated to the evaluation of bone age utilizing a relatively large institutional dataset. In doing so, this study will aim to show that advanced architectures can be successfully trained from scratch in the medical imaging domain and can generate results that outperform any existing proposed algorithm. The training data consisted of 10,289 images of different skeletal age examinations, 8909 from the hospital Picture Archiving and Communication System at our institution and 1383 from the public Digital Hand Atlas Database. The data was separated into four cohorts, one each for male and female children above the age of 8, and one each for male and female children below the age of 10. The testing set consisted of 20 radiographs of each 1-year-age cohort from 0 to 1 years to 14-15+ years, half male and half female. The testing set included left-hand radiographs done for bone age assessment, trauma evaluation without significant findings, and skeletal surveys. A 14 hidden layer-customized neural network was designed for this study. The network included several state of the art techniques including residual-style connections, inception layers, and spatial transformer layers. Data augmentation was applied to the network inputs to prevent overfitting. A linear regression output was utilized. Mean square error was used as the network loss function and mean absolute error (MAE) was utilized as the primary performance metric. MAE accuracies on the validation and test sets for young females were 0.654 and 0.561 respectively. For older females, validation and test accuracies were 0.662 and 0.497 respectively. For young males, validation and test accuracies were 0.649 and 0.585 respectively. Finally, for older males, validation and test set accuracies were 0.581 and 0.501 respectively. The female cohorts were trained for 900 epochs each and the male cohorts were trained for 600 epochs. An eightfold cross-validation set was employed for hyperparameter tuning. Test error was obtained after training on a full data set with the selected hyperparameters. Using our proposed customized neural network architecture on our large available data, we achieved an aggregate validation and test set mean absolute errors of 0.637 and 0.536 respectively. To date, this is the best published performance on utilizing deep learning for bone age assessment. Our results support our initial hypothesis that customized, purpose-built neural networks provide improved performance over networks derived from pre-trained imaging data sets. We build on that initial work by showing that the addition of state-of-the-art techniques such as residual connections and inception architecture further improves prediction accuracy. This is important because the current assumption for use of residual and/or inception architectures is that a large pre-trained network is required for successful implementation given the relatively small datasets in medical imaging. Instead we show that a small, customized architecture incorporating advanced CNN strategies can indeed be trained from scratch, yielding significant improvements in algorithm accuracy. It should be noted that for all four cohorts, testing error outperformed validation error. One reason for this is that our ground truth for our test set was obtained by averaging two pediatric radiologist reads compared to our training data for which only a single read was used. This suggests that despite relatively noisy training data, the algorithm could successfully model the variation between observers and generate estimates that are close to the expected ground truth.

Deep 3D Convolutional Encoder Networks With Shortcuts for Multiscale Feature Integration Applied to Multiple Sclerosis Lesion Segmentation.

PubMed

Brosch, Tom; Tang, Lisa Y W; Youngjin Yoo; Li, David K B; Traboulsee, Anthony; Tam, Roger

2016-05-01

We propose a novel segmentation approach based on deep 3D convolutional encoder networks with shortcut connections and apply it to the segmentation of multiple sclerosis (MS) lesions in magnetic resonance images. Our model is a neural network that consists of two interconnected pathways, a convolutional pathway, which learns increasingly more abstract and higher-level image features, and a deconvolutional pathway, which predicts the final segmentation at the voxel level. The joint training of the feature extraction and prediction pathways allows for the automatic learning of features at different scales that are optimized for accuracy for any given combination of image types and segmentation task. In addition, shortcut connections between the two pathways allow high- and low-level features to be integrated, which enables the segmentation of lesions across a wide range of sizes. We have evaluated our method on two publicly available data sets (MICCAI 2008 and ISBI 2015 challenges) with the results showing that our method performs comparably to the top-ranked state-of-the-art methods, even when only relatively small data sets are available for training. In addition, we have compared our method with five freely available and widely used MS lesion segmentation methods (EMS, LST-LPA, LST-LGA, Lesion-TOADS, and SLS) on a large data set from an MS clinical trial. The results show that our method consistently outperforms these other methods across a wide range of lesion sizes.

TU-C-12A-12: Differentiating Bone Lesions and Degenerative Joint Disease in NaF PET/CT Scans Using Machine Learning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perk, T; Bradshaw, T; Muzahir, S

2014-06-15

Purpose: [F-18]NaF PET can be used to image bone metastases; however, tracer uptake in degenerative joint disease (DJD) often appears similar to metastases. This study aims to develop and compare different machine learning algorithms to automatically identify regions of [F-18]NaF scans that correspond to DJD. Methods: 10 metastatic prostate cancer patients received whole body [F-18]NaF PET/CT scans prior to treatment. Image segmentation resulted in 852 ROIs, 69 of which were identified by a nuclear medicine physician as DJD. For all ROIs, various PET and CT textural features were computed. ROIs were divided into training and testing sets used to trainmore » eight different machine learning classifiers. Classifiers were evaluated based on receiver operating characteristics area under the curve (AUC), sensitivity, specificity, and positive predictive value (PPV). We also assessed the added value of including CT features in addition to PET features for training classifiers. Results: The training set consisted of 37 DJD ROIs with 475 non-DJD ROIs, and the testing set consisted of 32 DJD ROIs with 308 non-DJD ROIs. Of all classifiers, generalized linear models (GLM), decision forests (DF), and support vector machines (SVM) had the best performance. AUCs of GLM (0.929), DF (0.921), and SVM (0.889) were significantly higher than the other models (p<0.001). GLM and DF, overall, had the best sensitivity, specificity, and PPV, and gave a significantly better performance (p<0.01) than all other models. PET/CT GLM classifiers had higher AUC than just PET or just CT. GLMs built using PET/CT information had superior or comparable sensitivities, specificities and PPVs to just PET or just CT. Conclusion: Machine learning algorithms trained with PET/CT features were able to identify some cases of DJD. GLM outperformed the other classification algorithms. Using PET and CT information together was shown to be superior to using PET or CT features alone. Research supported by the Prostate Cancer Foundation.« less

Training set extension for SVM ensemble in P300-speller with familiar face paradigm.

PubMed

Li, Qi; Shi, Kaiyang; Gao, Ning; Li, Jian; Bai, Ou

2018-03-27

P300-spellers are brain-computer interface (BCI)-based character input systems. Support vector machine (SVM) ensembles are trained with large-scale training sets and used as classifiers in these systems. However, the required large-scale training data necessitate a prolonged collection time for each subject, which results in data collected toward the end of the period being contaminated by the subject's fatigue. This study aimed to develop a method for acquiring more training data based on a collected small training set. A new method was developed in which two corresponding training datasets in two sequences are superposed and averaged to extend the training set. The proposed method was tested offline on a P300-speller with the familiar face paradigm. The SVM ensemble with extended training set achieved 85% classification accuracy for the averaged results of four sequences, and 100% for 11 sequences in the P300-speller. In contrast, the conventional SVM ensemble with non-extended training set achieved only 65% accuracy for four sequences, and 92% for 11 sequences. The SVM ensemble with extended training set achieves higher classification accuracies than the conventional SVM ensemble, which verifies that the proposed method effectively improves the classification performance of BCI P300-spellers, thus enhancing their practicality.

An Assessment of Worldview-2 Imagery for the Classification Of a Mixed Deciduous Forest

NASA Astrophysics Data System (ADS)

Carter, Nahid

Remote sensing provides a variety of methods for classifying forest communities and can be a valuable tool for the impact assessment of invasive species. The emerald ash borer (Agrilus planipennis) infestation of ash trees (Fraxinus) in the United States has resulted in the mortality of large stands of ash throughout the Northeast. This study assessed the suitability of multi-temporal Worldview-2 multispectral satellite imagery for classifying a mixed deciduous forest in Upstate New York. Training sites were collected using a Global Positioning System (GPS) receiver, with each training site consisting of a single tree of a corresponding class. Six classes were collected; Ash, Maple, Oak, Beech, Evergreen, and Other. Three different classifications were investigated on four data sets. A six class classification (6C), a two class classification consisting of ash and all other classes combined (2C), and a merging of the ash and maple classes for a five class classification (5C). The four data sets included Worldview-2 multispectral data collection from June 2010 (J-WV2) and September 2010 (S-WV2), a layer stacked data set using J-WV2 and S-WV2 (LS-WV2), and a reduced data set (RD-WV2). RD-WV2 was created using a statistical analysis of the processed and unprocessed imagery. Statistical analysis was used to reduce the dimensionality of the data and identify key bands to create a fourth data set (RD-WV2). Overall accuracy varied considerably depending upon the classification type, but results indicated that ash was confused with maple in a majority of the classifications. Ash was most accurately identified using the 2C classification and RD-WV2 data set (81.48%). A combination of the ash and maple classes yielded an accuracy of 89.41%. Future work should focus on separating the ash and maple classifiers by using data sources such as hyperspectral imagery, LiDAR, or extensive forest surveys.

Suicide Prevention Training: Policies for Health Care Professionals Across the United States as of October 2017.

PubMed

Graves, Janessa M; Mackelprang, Jessica L; Van Natta, Sara E; Holliday, Carrie

2018-06-01

To identify and compare state policies for suicide prevention training among health care professionals across the United States and benchmark state plan updates against national recommendations set by the surgeon general and the National Action Alliance for Suicide Prevention in 2012. We searched state legislation databases to identify policies, which we described and characterized by date of adoption, target audience, and duration and frequency of the training. We used descriptive statistics to summarize state-by-state variation in suicide education policies. In the United States, as of October 9, 2017, 10 (20%) states had passed legislation mandating health care professionals complete suicide prevention training, and 7 (14%) had policies encouraging training. The content and scope of policies varied substantially. Most states (n = 43) had a state suicide prevention plan that had been revised since 2012, but 7 lacked an updated plan. Considerable variation in suicide prevention training for health care professionals exists across the United States. There is a need for consistent polices in suicide prevention training across the nation to better equip health care providers to address the needs of patients who may be at risk for suicide.

An evaluation of training for lay providers in the use of Motivational Interviewing to promote academic achievement among urban youth

PubMed Central

Simon, Patricia; Ward, Nadia L.

2015-01-01

This study examined training outcomes for lay service providers who participated in a Motivational Interviewing (MI) training program designed to help increase intrinsic motivation and academic achievement among urban low-income and minority youth. Seventeen lay academic advisors received 16 hours of training in MI. Two, two-hour booster sessions plus five, two- hour weekly group supervision sessions were conducted with lay advisors over a period of seven months. One-hundred percent of lay advisors (n =17) participated in all training, booster sessions and assessments. Seventy-one percent of lay advisors (n=12) completed all group supervision sessions and submitted tapes for review. MI training was associated with increased knowledge of MI principles among lay service providers; increased proficiency in responding to simulated clients in an MI consistent style; increased use of MI adherent behaviors in sessions with real clients and maintenance of high motivation to use MI from pretest to posttest. Although lay advisors increased their knowledge of MI, further training is required for advisors to increase competence in delivering MI. Overall, Implications for using MI in the context of school-based settings is discussed. PMID:26356248

An evaluation of training for lay providers in the use of Motivational Interviewing to promote academic achievement among urban youth.

PubMed

Simon, Patricia; Ward, Nadia L

This study examined training outcomes for lay service providers who participated in a Motivational Interviewing (MI) training program designed to help increase intrinsic motivation and academic achievement among urban low-income and minority youth. Seventeen lay academic advisors received 16 hours of training in MI. Two, two-hour booster sessions plus five, two- hour weekly group supervision sessions were conducted with lay advisors over a period of seven months. One-hundred percent of lay advisors (n =17) participated in all training, booster sessions and assessments. Seventy-one percent of lay advisors (n=12) completed all group supervision sessions and submitted tapes for review. MI training was associated with increased knowledge of MI principles among lay service providers; increased proficiency in responding to simulated clients in an MI consistent style; increased use of MI adherent behaviors in sessions with real clients and maintenance of high motivation to use MI from pretest to posttest. Although lay advisors increased their knowledge of MI, further training is required for advisors to increase competence in delivering MI. Overall, Implications for using MI in the context of school-based settings is discussed.

Neural-network Kohn-Sham exchange-correlation potential and its out-of-training transferability

NASA Astrophysics Data System (ADS)

Nagai, Ryo; Akashi, Ryosuke; Sasaki, Shu; Tsuneyuki, Shinji

2018-06-01

We incorporate in the Kohn-Sham self-consistent equation a trained neural-network projection from the charge density distribution to the Hartree-exchange-correlation potential n → VHxc for a possible numerical approach to the exact Kohn-Sham scheme. The potential trained through a newly developed scheme enables us to evaluate the total energy without explicitly treating the formula of the exchange-correlation energy. With a case study of a simple model, we show that the well-trained neural-network VHxc achieves accuracy for the charge density and total energy out of the model parameter range used for the training, indicating that the property of the elusive ideal functional form of VHxc can approximately be encapsulated by the machine-learning construction. We also exemplify a factor that crucially limits the transferability—the boundary in the model parameter space where the number of the one-particle bound states changes—and see that this is cured by setting the training parameter range across that boundary. The training scheme and insights from the model study apply to more general systems, opening a novel path to numerically efficient Kohn-Sham potential.

The effect of open kinetic chain knee extensor resistance training at different training loads on anterior knee laxity in the uninjured.

PubMed

Barcellona, Massimo G; Morrissey, Matthew C

2016-04-01

The commonly used open kinetic chain knee extensor (OKCKE) exercise loads the sagittal restraints to knee anterior tibial translation. To investigate the effect of different loads of OKCKE resistance training on anterior knee laxity (AKL) in the uninjured knee. non-clinical trial. Randomization into one of three supervised training groups occurred with training 3 times per week for 12 weeks. Subjects in the LOW and HIGH groups performed OKCKE resistance training at loads of 2 sets of 20 repetition maximum (RM) and 20 sets of 2RM, respectively. Subjects in the isokinetic training group (ISOK) performed isokinetic OKCKE resistance training using 2 sets of 20 maximal efforts. AKL was measured using the KT2000 arthrometer with concurrent measurement of lateral hamstrings muscle activity at baseline, 6 weeks and 12 weeks. Twenty six subjects participated (LOW n = 9, HIGH n = 10, ISOK n = 7). The main finding from this study is that a 12-week OKCKE resistance training programme at loads of 20 sets of 2RM, leads to an increase in manual maximal AKL. OKCKE resistance training at high loads (20 sets of 2RM) increases AKL while low load OKCKE resistance training (2 sets of 20RM) and isokinetic OKCKE resistance training at 2 sets of 20RM does not. Copyright © 2015 Elsevier Ltd. All rights reserved.

Segmentation and Recognition of Continuous Human Activity

DTIC Science & Technology

2001-01-01

This paper presents a methodology for automatic segmentation and recognition of continuous human activity . We segment a continuous human activity into...commencement or termination. We use single action sequences for the training data set. The test sequences, on the other hand, are continuous sequences of human ... activity that consist of three or more actions in succession. The system has been tested on continuous activity sequences containing actions such as

Interprofessional Emergency Training Leads to Changes in the Workplace

PubMed Central

Eisenmann, Dorothea; Stroben, Fabian; Gerken, Jan D.; Exadaktylos, Aristomenis K.; Machner, Mareen; Hautz, Wolf E.

2018-01-01

Introduction Preventable mistakes occur frequently and can lead to patient harm and death. The emergency department (ED) is notoriously prone to such errors, and evidence suggests that improving teamwork is a key aspect to reduce the rate of error in acute care settings. Only a few strategies are in place to train team skills and communication in interprofessional situations. Our goal was to conceptualize, implement, and evaluate a training module for students of three professions involved in emergency care. The objective was to sensitize participants to barriers for their team skills and communication across professional borders. Methods We developed a longitudinal simulation-enhanced training format for interprofessional teams, consisting of final-year medical students, advanced trainees of emergency nursing and student paramedics. The training format consisted of several one-day training modules, which took place twice in 2016 and 2017. Each training module started with an introduction to share one’s roles, professional self-concepts, common misconceptions, and communication barriers. Next, we conducted different simulated cases. Each case consisted of a prehospital section (for paramedics and medical students), a handover (everyone), and an ED section (medical students and emergency nurses). After each training module, we assessed participants’ “Commitment to Change.” In this questionnaire, students were anonymously asked to state up to three changes that they wished to implement as a result of the course, as well as the strength of their commitment to these changes. Results In total, 64 of 80 participants (80.0%) made at least one commitment to change after participating in the training modules. The total of 123 commitments was evenly distributed over four emerging categories: communication, behavior, knowledge and attitude. Roughly one third of behavior- and attitude-related commitments were directly related to interprofessional topics (e.g., “acknowledge other professions’ work”), and these were equally distributed among professions. At the two-month follow-up, 32 participants (50%) provided written feedback on their original commitments: 57 of 62 (91.9%) commitments were at least partly realized at the follow-up, and only five (8.1%) commitments lacked realization entirely. Conclusion A structured simulation-enhanced intervention was successful in promoting change to the practice of emergency care, while training teamwork and communication skills jointly. PMID:29383079

Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation.

PubMed

Grossi, Giuliano; Lanzarotti, Raffaella; Lin, Jianyi

2017-01-01

In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error. Finding the best fitting dictionary remains a very difficult task, leaving the question still open. A well-established heuristic method for tackling this problem is an iterative alternating scheme, adopted for instance in the well-known K-SVD algorithm. Essentially, it consists in repeating two stages; the former promotes sparse coding of the training set and the latter adapts the dictionary to reduce the error. In this paper we present R-SVD, a new method that, while maintaining the alternating scheme, adopts the Orthogonal Procrustes analysis to update the dictionary atoms suitably arranged into groups. Comparative experiments on synthetic data prove the effectiveness of R-SVD with respect to well known dictionary learning algorithms such as K-SVD, ILS-DLA and the online method OSDL. Moreover, experiments on natural data such as ECG compression, EEG sparse representation, and image modeling confirm R-SVD's robustness and wide applicability.

Emotion-independent face recognition

NASA Astrophysics Data System (ADS)

De Silva, Liyanage C.; Esther, Kho G. P.

2000-12-01

Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

Longitudinal attentional engagement rescues mice from age-related cognitive declines and cognitive inflexibility

PubMed Central

Matzel, Louis D.; Light, Kenneth R.; Wass, Christopher; Colas-Zelin, Danielle; Denman-Brice, Alexander; Waddel, Adam C.; Kolata, Stefan

2011-01-01

Learning, attentional, and perseverative deficits are characteristic of cognitive aging. In this study, genetically diverse CD-1 mice underwent longitudinal training in a task asserted to tax working memory capacity and its dependence on selective attention. Beginning at 3 mo of age, animals were trained for 12 d to perform in a dual radial-arm maze task that required the mice to remember and operate on two sets of overlapping guidance (spatial) cues. As previously reported, this training resulted in an immediate (at 4 mo of age) improvement in the animals' aggregate performance across a battery of five learning tasks. Subsequently, these animals received an additional 3 d of working memory training at 3-wk intervals for 15 mo (totaling 66 training sessions), and at 18 mo of age were assessed on a selective attention task, a second set of learning tasks, and variations of those tasks that required the animals to modify the previously learned response. Both attentional and learning abilities (on passive avoidance, active avoidance, and reinforced alternation tasks) were impaired in aged animals that had not received working memory training. Likewise, these aged animals exhibited consistent deficits when required to modify a previously instantiated learned response (in reinforced alternation, active avoidance, and spatial water maze). In contrast, these attentional, learning, and perseverative deficits were attenuated in aged animals that had undergone lifelong working memory exercise. These results suggest that general impairments of learning, attention, and cognitive flexibility may be mitigated by a cognitive exercise regimen that requires chronic attentional engagement. PMID:21521768

Longitudinal attentional engagement rescues mice from age-related cognitive declines and cognitive inflexibility.

PubMed

Matzel, Louis D; Light, Kenneth R; Wass, Christopher; Colas-Zelin, Danielle; Denman-Brice, Alexander; Waddel, Adam C; Kolata, Stefan

2011-01-01

Learning, attentional, and perseverative deficits are characteristic of cognitive aging. In this study, genetically diverse CD-1 mice underwent longitudinal training in a task asserted to tax working memory capacity and its dependence on selective attention. Beginning at 3 mo of age, animals were trained for 12 d to perform in a dual radial-arm maze task that required the mice to remember and operate on two sets of overlapping guidance (spatial) cues. As previously reported, this training resulted in an immediate (at 4 mo of age) improvement in the animals' aggregate performance across a battery of five learning tasks. Subsequently, these animals received an additional 3 d of working memory training at 3-wk intervals for 15 mo (totaling 66 training sessions), and at 18 mo of age were assessed on a selective attention task, a second set of learning tasks, and variations of those tasks that required the animals to modify the previously learned response. Both attentional and learning abilities (on passive avoidance, active avoidance, and reinforced alternation tasks) were impaired in aged animals that had not received working memory training. Likewise, these aged animals exhibited consistent deficits when required to modify a previously instantiated learned response (in reinforced alternation, active avoidance, and spatial water maze). In contrast, these attentional, learning, and perseverative deficits were attenuated in aged animals that had undergone lifelong working memory exercise. These results suggest that general impairments of learning, attention, and cognitive flexibility may be mitigated by a cognitive exercise regimen that requires chronic attentional engagement.

Take-Home Training in Laparoscopy.

PubMed

Thinggaard, Ebbe

2017-04-01

When laparoscopy was first introduced, skills were primarily taught using the apprenticeship model. A limitation of this method when compared to open surgery, was that it requires more time to practise and more frequent learning opportunities in clinical practice. The unique set of skills required in laparoscopy highlighted the need for new training methods that reduce the need for supervision and do not put the patient at risk. Simulation training was developed to meet this need. The overall purpose of this thesis was to explore simulation-based laparoscopic training at home. The thesis consists of five papers: a review, a validation study, a study of methodology, a randomised controlled trial and a mixed-methods study. Our aims were to review the current knowledge on training off-site, to develop and explore validity for a training and assessment system, to investigate the effect of take-home training in a simulation-based laparoscopic training programme, and to explore the use of take-home training. The first paper in this thesis is a scoping review. The aim of the review was to explore the current knowledge on off-site laparoscopic skills training. We found that off-site training was feasible but that changes were required in order for it to become an effective method of training. Furthermore, the select-ed instructional design varied and training programmes were designed using a variety of educational theories. Based on our findings, we recommended that courses and training curricula should follow established education theories such as proficiency-based learning and deliberate practice. Principles of directed self-regulated learning could be used to improve off-site laparoscopic training programmes. In the second study, we set out to develop and explore validity evidence of the TABLT test. The TABLT test was developed for basic laparoscopic skills training in a cross-specialty curriculum. We found validity evidence to support the TABLT test as a summative test in a basic laparoscopic training programme. We also established a credible pass/fail level using the contrasting groups method. We concluded that the TABTL test could be used to assess novice laparoscopic trainees across different specialties and help trainees acquire basic laparoscopic competencies prior to supervised surgery. In the third study, we aimed to explore the consequences of the choice of standard setting method and whether there is a difference in terms of how high a score experienced and novice laparoscopic surgeons expect that novices should achieve during training. We used three different standard setting methods and found that pass/fail levels vary depending on the choice of standard setting method. We also asked experienced and novice laparoscopic surgeons how high a score they expected a novice laparoscopic surgeon should achieve on a test during training. We found a significant difference, with experienced surgeons setting a lower pass/fail level. We concluded that an established standard setting method supported by evidence should be used when setting a pass/fail level. In the first and second papers of this thesis, we found that off-site training is feasible and explored validity for the TABLT test. We used this knowledge in the fourth study to design a randomised controlled trial. The aim of the trial was to investigate the effect of take-home training in a simulation-based laparoscopic course. We hypothesised that training at home could help trainees plan their training according to their own schedule and thereby increase the effect of training. We found that participants had a distributed training pattern; they trained more frequently and in shorter sessions. We also found that participants were able to rate their own performance during unsupervised training and that selfrating was reliable. The fifth and final study of the thesis was a mixed-methods study that aimed to explore the use of take-home training. To meet this aim, we recruited participants from the intervention arm in our randomised controlled trial. All participants had access to the simulation centre and were given a port-able trainer to train on at home. Participants were asked to use a logbook during training. At the end of the course, they were invited to take part in focus group interviews and individual interviews. Based on data from logbooks, a descriptive statistical analysis was conducted and data from interviews were analysed using a content analysis. We found that participants took an individualised approach to training when training at home. They structured their training according to their needs and external requirements. We concluded that mandatory training requirements and testing help determine when and how much participants train. We also found that self-rating can guide unsupervised training by giving clear goals to be reached during training. From the papers included in the thesis, we found that the literature describes training at home as a feasible method of acquiring laparoscopic skills. Nonetheless, changes to current training programmes are needed in order to make this method effective. We then developed and explored validity evidence for the TABLT test. We also established a reasonable pass/fail level and went on to explore the immediate consequences of the pass/fail level. Using our knowledge from the review, we conducted a randomised controlled trial and a mixed-method study. Based on these studies we found that training at home allows for distributed learning, that self-rating guides unsupervised training, and that mandatory training requirements and testing strongly influence training patterns. Access to training, guidance during training, and mandatory training requirements will make take-home training not just feasible but also effective. Articles published in the Danish Medical Journal are “open access”. This means that the articles are distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits any non-commercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Neural Network and Response Surface Methodology for Rocket Engine Component Optimization

NASA Technical Reports Server (NTRS)

Vaidyanathan, Rajkumar; Papita, Nilay; Shyy, Wei; Tucker, P. Kevin; Griffin, Lisa W.; Haftka, Raphael; Fitz-Coy, Norman; McConnaughey, Helen (Technical Monitor)

2000-01-01

The goal of this work is to compare the performance of response surface methodology (RSM) and two types of neural networks (NN) to aid preliminary design of two rocket engine components. A data set of 45 training points and 20 test points obtained from a semi-empirical model based on three design variables is used for a shear coaxial injector element. Data for supersonic turbine design is based on six design variables, 76 training, data and 18 test data obtained from simplified aerodynamic analysis. Several RS and NN are first constructed using the training data. The test data are then employed to select the best RS or NN. Quadratic and cubic response surfaces. radial basis neural network (RBNN) and back-propagation neural network (BPNN) are compared. Two-layered RBNN are generated using two different training algorithms, namely solverbe and solverb. A two layered BPNN is generated with Tan-Sigmoid transfer function. Various issues related to the training of the neural networks are addressed including number of neurons, error goals, spread constants and the accuracy of different models in representing the design space. A search for the optimum design is carried out using a standard gradient-based optimization algorithm over the response surfaces represented by the polynomials and trained neural networks. Usually a cubic polynominal performs better than the quadratic polynomial but exceptions have been noticed. Among the NN choices, the RBNN designed using solverb yields more consistent performance for both engine components considered. The training of RBNN is easier as it requires linear regression. This coupled with the consistency in performance promise the possibility of it being used as an optimization strategy for engineering design problems.

Development of low-volume, high-intensity, aerobic-type interval training for elderly Japanese men: a feasibility study.

PubMed

Osuka, Yosuke; Matsubara, Muneaki; Hamasaki, Ai; Hiramatsu, Yuji; Ohshima, Hiroshi; Tanaka, Kiyoji

2017-01-01

The purposes of this study were to identify 1) the feasibility of a novel exercise protocol (elderly Japanese male version of high-intensity interval aerobic training: EJ-HIAT) and 2) its preliminary data (%V̇O 2peak , rating of perceived exertion) in comparison with traditional moderate-intensity continuous aerobic training (MICT). Twenty-one sedentary elderly men, aged 60-69 years, performed two exercise protocols: EJ-HIAT, consisting of 3 sets of 2-3-min cycling at 75-85%V̇O 2peak with 1-2-min active rests at 50%V̇O 2peak between sets, and MICT, consisting of 40-min cycling at 65%V̇O 2peak . The completion rate, defined as the rate of participants who 1) did not demand withdrawal, 2) were not interrupted by the tester, and 3) did not change the workload during either exercise protocol, of EJ-HIAT was similar to that of MICT (EJ-HIAT: 100%, MICT: 95.2%). Maximal perceived exertion ratings assessed by Borg scale were also similar between EJ-HIAT and MICT. However, objectively measured maximal intensity assessed by %V̇O 2peak was higher for EJ-HIAT than for MICT (EJ-HIAT: 86.0 ± 5.6%, MICT: 67.1 ± 6.4%). These results suggested that EJ-HIAT has good feasibility and perceived exertion similar to MICT despite having higher objectively measured intensity than MICT. An intervention aimed as identifying the effects of EJ-HIAT on exercise tolerance should be performed in the future. UMIN000021185 (February 26, 2016).

Identifying and reducing error in cluster-expansion approximations of protein energies.

PubMed

Hahn, Seungsoo; Ashenberg, Orr; Grigoryan, Gevorg; Keating, Amy E

2010-12-01

Protein design involves searching a vast space for sequences that are compatible with a defined structure. This can pose significant computational challenges. Cluster expansion is a technique that can accelerate the evaluation of protein energies by generating a simple functional relationship between sequence and energy. The method consists of several steps. First, for a given protein structure, a training set of sequences with known energies is generated. Next, this training set is used to expand energy as a function of clusters consisting of single residues, residue pairs, and higher order terms, if required. The accuracy of the sequence-based expansion is monitored and improved using cross-validation testing and iterative inclusion of additional clusters. As a trade-off for evaluation speed, the cluster-expansion approximation causes prediction errors, which can be reduced by including more training sequences, including higher order terms in the expansion, and/or reducing the sequence space described by the cluster expansion. This article analyzes the sources of error and introduces a method whereby accuracy can be improved by judiciously reducing the described sequence space. The method is applied to describe the sequence-stability relationship for several protein structures: coiled-coil dimers and trimers, a PDZ domain, and T4 lysozyme as examples with computationally derived energies, and SH3 domains in amphiphysin-1 and endophilin-1 as examples where the expanded pseudo-energies are obtained from experiments. Our open-source software package Cluster Expansion Version 1.0 allows users to expand their own energy function of interest and thereby apply cluster expansion to custom problems in protein design. © 2010 Wiley Periodicals, Inc.

Channel characterization using multiple-point geostatistics, neural network, and modern analogy: A case study from a carbonate reservoir, southwest Iran

NASA Astrophysics Data System (ADS)

Hashemi, Seyyedhossein; Javaherian, Abdolrahim; Ataee-pour, Majid; Tahmasebi, Pejman; Khoshdel, Hossein

2014-12-01

In facies modeling, the ideal objective is to integrate different sources of data to generate a model that has the highest consistency to reality with respect to geological shapes and their facies architectures. Multiple-point (geo)statistics (MPS) is a tool that gives the opportunity of reaching this goal via defining a training image (TI). A facies modeling workflow was conducted on a carbonate reservoir located southwest Iran. Through a sequence stratigraphic correlation among the wells, it was revealed that the interval under a modeling process was deposited in a tidal flat environment. Bahamas tidal flat environment which is one of the most well studied modern carbonate tidal flats was considered to be the source of required information for modeling a TI. In parallel, a neural network probability cube was generated based on a set of attributes derived from 3D seismic cube to be applied into the MPS algorithm as a soft conditioning data. Moreover, extracted channel bodies and drilled well log facies came to the modeling as hard data. Combination of these constraints resulted to a facies model which was greatly consistent to the geological scenarios. This study showed how analogy of modern occurrences can be set as the foundation for generating a training image. Channel morphology and facies types currently being deposited, which are crucial for modeling a training image, was inferred from modern occurrences. However, there were some practical considerations concerning the MPS algorithm used for facies simulation. The main limitation was the huge amount of RAM and CPU-time needed to perform simulations.

Varying performance in mammographic interpretation across two countries: Do results indicate reader or population variances?

NASA Astrophysics Data System (ADS)

Soh, BaoLin P.; Lee, Warwick B.; Wong, Jill; Sim, Llewellyn; Hillis, Stephen L.; Tapia, Kriscia A.; Brennan, Patrick C.

2016-03-01

Aim: To compare the performance of Australian and Singapore breast readers interpreting a single test-set that consisted of mammographic examinations collected from the Australian population. Background: In the teleradiology era, breast readers are interpreting mammographic examinations from different populations. The question arises whether two groups of readers with similar training backgrounds, demonstrate the same level of performance when presented with a population familiar only to one of the groups. Methods: Fifty-three Australian and 15 Singaporean breast radiologists participated in this study. All radiologists were trained in mammogram interpretation and had a median of 9 and 15 years of experience in reading mammograms respectively. Each reader interpreted the same BREAST test-set consisting of sixty de-identified mammographic examinations arising from an Australian population. Performance parameters including JAFROC, ROC, case sensitivity as well as specificity were compared between Australian and Singaporean readers using a Mann Whitney U test. Results: A significant difference (P=0.036) was demonstrated between the JAFROC scores of the Australian and Singaporean breast radiologists. No other significant differences were observed. Conclusion: JAFROC scores for Australian radiologists were higher than those obtained by the Singaporean counterparts. Whilst it is tempting to suggest this is down to reader expertise, this may be a simplistic explanation considering the very similar training and audit backgrounds of the two populations of radiologists. The influence of reading images that are different from those that radiologists normally encounter cannot be ruled out and requires further investigation, particularly in the light of increasing international outsourcing of radiologic reporting.

[Peripheral venous catheter use in the emergency department: reducing adverse events in patients and biosafety problems for staff].

PubMed

Tomás Vecina, Santiago; Mozota Duarte, Julián; Ortega Marcos, Miguel; Gracia Ruiz Navarro, María; Borillo, Vicente; San Juan Gago, Leticia; Roqueta Egea, Fermin; Chanovas Borrás, Manuel

2016-01-01

To test a strategy to reduce the rate of adverse events in patients and safety problems for emergency department staff who insert peripheral venous catheters (PVCs). The strategy consisted of training, implementing a protocol, and introducing safety-engineered PVCs. Prospective, multicenter, observational, preauthorization study in patients requiring PVC placement in an emergency department. The study had 2 phases. The first consisted of training, implementing a protocol for using conventional PVCs, and monitoring practice. The second phase introduced safety-engineered PVC sets. The number of adverse events in patients and threats to safety for staff were compared between the 2 phases. A total of 520 patients were included, 180 in the first phase and 340 in the second. We detected breaches in aseptic technique, failure to maintain a sterile field, and improper management of safety equipment and devices. Some practices improved significantly during the second phase. Eighty-six adverse events occurred in the first phase and 52 (15.4%) in the second; the between-phase difference was not statistically significant. The incidence of postinfusion phlebitis was 50% lower in the second phase. Seven splash injuries and 1 accidental puncture occurred with conventional PVCs in the first phase; 2 splash injuries occurred with the safety-engineered PVCs in the second phase (36% decrease, P = .04). Differences were particularly noticeable for short-term PVC placements (P = .02). Combining training, a protocol, and the use of safety-engineered PVC sets offers an effective strategy for improving patient and staff safety.

Effect of training level and blood flow restriction on thermal parameters: Preliminary study

NASA Astrophysics Data System (ADS)

Sampaio, Lucas; Bezerra, Ewertton; Paladino, Kayo; dos Santos, João Otacílio Libardoni; Priego Quesada, Jose I.; Rossato, Mateus

2016-11-01

Training with blood flow restriction could lead to an effect on skin temperature. Additionally, this effect could be higher in people with lower physical fitness level due to their lower capacity of heat loss. The aim of this preliminary study was therefore to evaluate the effects of training experience on the acute and chronic thermal skin responses after performing exercise with and without blood flow restriction. The study included ten men, of these, five were trained. All subjects performed tests and re-tests for maximum strength (1 repetition maximum) through unilateral leg extensions (right thigh at 45 ± 6.7 kg and left thigh at 45.5 ± 8.1 kg, p > 0.05). The protocol consisted of four sets to concentric failure, with one-minute rest intervals between sets at an intensity corresponding to 40% of 1 RM. There were 7-day intervals between experimental sessions (150 mmHg versus unrestricted flow restriction). The thermal images were made before the protocol (pre), immediately after the end of the series (post), and 24 h afterward (post 24 h). When comparing temperature variation (Δ exercise and Δ 24 h) between groups, it was observed that the trained participants showed a greater drop in temperature 24 h after exercise with 150 mmHg restriction (confidence interval: 95% of Δ 24 h [-0.2 to -0.9 °C]) compared to untrained subjects (p = 0.006 and ES > 1.5, confidence interval: 95% Δ 24 h [-0.1 to 0.6 °C].) In conclusion, this preliminary study showed that training experience interferes with the chronic cutaneous thermal temperature of the anterior thigh when strength training associated with blood flow restriction 150 mmHg was performed.

Improvement of Repeated-Sprint Ability and Horizontal-Jumping Performance in Elite Young Basketball Players With Low-Volume Repeated-Maximal-Power Training.

PubMed

Gonzalo-Skok, Oliver; Tous-Fajardo, Julio; Arjol-Serrano, José Luis; Suarez-Arrones, Luis; Casajús, José Antonio; Mendez-Villanueva, Alberto

2016-05-01

To examine the effects of a low-volume repeated-power-ability (RPA) training program on repeated-sprint and change-of- direction (COD) ability and functional jumping performance. Twenty-two male elite young basketball players (age 16.2 ± 1.2 y, height 190.0 ± 10.0 cm, body mass 82.9 ± 10.1 kg) were randomly assigned either to an RPA-training group (n = 11) or a control group (n = 11). RPA training consisted of leg-press exercise, twice a week for 6 wk, of 1 or 2 blocks of 5 sets × 5 repetitions with 20 s of passive recovery between sets and 3 min between blocks with the load that maximized power output. Before and after training, performance was assessed by a repeated-sprint-ability (RSA) test, a repeated-COD-ability test, a hop for distance, and a drop jump followed by tests of a double unilateral hop with the right and left legs. Within-group and between-groups differences showed substantial improvements in slowest (RSAs) and mean time (RSAm) on RSA; best, slowest and mean time on repeated-COD ability; and unilateral right and left hop in the RPA group in comparison with control. While best time on RSA showed no improvement in any group, there was a large relationship (r = .68, 90% CI .43;.84) between the relative decrement in RSAm and RSAs, suggesting better sprint maintenance with RPA training. The relative improvements in best and mean repeated-COD ability were very largely correlated (r = .89, 90% CI .77;.94). Six weeks of lowvolume (4-14 min/wk) RPA training improved several physical-fitness tests in basketball players.

Computer-enhanced laparoscopic training system (CELTS): bridging the gap.

PubMed

Stylopoulos, N; Cotin, S; Maithel, S K; Ottensmeye, M; Jackson, P G; Bardsley, R S; Neumann, P F; Rattner, D W; Dawson, S L

2004-05-01

There is a large and growing gap between the need for better surgical training methodologies and the systems currently available for such training. In an effort to bridge this gap and overcome the disadvantages of the training simulators now in use, we developed the Computer-Enhanced Laparoscopic Training System (CELTS). CELTS is a computer-based system capable of tracking the motion of laparoscopic instruments and providing feedback about performance in real time. CELTS consists of a mechanical interface, a customizable set of tasks, and an Internet-based software interface. The special cognitive and psychomotor skills a laparoscopic surgeon should master were explicitly defined and transformed into quantitative metrics based on kinematics analysis theory. A single global standardized and task-independent scoring system utilizing a z-score statistic was developed. Validation exercises were performed. The scoring system clearly revealed a gap between experts and trainees, irrespective of the task performed; none of the trainees obtained a score above the threshold that distinguishes the two groups. Moreover, CELTS provided educational feedback by identifying the key factors that contributed to the overall score. Among the defined metrics, depth perception, smoothness of motion, instrument orientation, and the outcome of the task are major indicators of performance and key parameters that distinguish experts from trainees. Time and path length alone, which are the most commonly used metrics in currently available systems, are not considered good indicators of performance. CELTS is a novel and standardized skills trainer that combines the advantages of computer simulation with the features of the traditional and popular training boxes. CELTS can easily be used with a wide array of tasks and ensures comparability across different training conditions. This report further shows that a set of appropriate and clinically relevant performance metrics can be defined and a standardized scoring system can be designed.

Improvement of Predictive Ability by Uniform Coverage of the Target Genetic Space

PubMed Central

Bustos-Korts, Daniela; Malosetti, Marcos; Chapman, Scott; Biddulph, Ben; van Eeuwijk, Fred

2016-01-01

Genome-enabled prediction provides breeders with the means to increase the number of genotypes that can be evaluated for selection. One of the major challenges in genome-enabled prediction is how to construct a training set of genotypes from a calibration set that represents the target population of genotypes, where the calibration set is composed of a training and validation set. A random sampling protocol of genotypes from the calibration set will lead to low quality coverage of the total genetic space by the training set when the calibration set contains population structure. As a consequence, predictive ability will be affected negatively, because some parts of the genotypic diversity in the target population will be under-represented in the training set, whereas other parts will be over-represented. Therefore, we propose a training set construction method that uniformly samples the genetic space spanned by the target population of genotypes, thereby increasing predictive ability. To evaluate our method, we constructed training sets alongside with the identification of corresponding genomic prediction models for four genotype panels that differed in the amount of population structure they contained (maize Flint, maize Dent, wheat, and rice). Training sets were constructed using uniform sampling, stratified-uniform sampling, stratified sampling and random sampling. We compared these methods with a method that maximizes the generalized coefficient of determination (CD). Several training set sizes were considered. We investigated four genomic prediction models: multi-locus QTL models, GBLUP models, combinations of QTL and GBLUPs, and Reproducing Kernel Hilbert Space (RKHS) models. For the maize and wheat panels, construction of the training set under uniform sampling led to a larger predictive ability than under stratified and random sampling. The results of our methods were similar to those of the CD method. For the rice panel, all training set construction methods led to similar predictive ability, a reflection of the very strong population structure in this panel. PMID:27672112

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma

PubMed Central

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

Background There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Methods Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. Results The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. Conclusions TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC. PMID:27798689

Clinical Significance of Tissue Factor Pathway Inhibitor 2, a Serum Biomarker Candidate for Ovarian Clear Cell Carcinoma.

PubMed

Arakawa, Noriaki; Kobayashi, Hiroshi; Yonemoto, Naohiro; Masuishi, Yusuke; Ino, Yoko; Shigetomi, Hiroshi; Furukawa, Naoto; Ohtake, Norihisa; Miyagi, Yohei; Hirahara, Fumiki; Hirano, Hisashi; Miyagi, Etsuko

2016-01-01

There is currently no reliable serum biomarker for ovarian clear cell carcinoma (CCC), a highly lethal histological subtype of epithelial ovarian cancer (EOC). Previously, using a proteome-based approach, we identified tissue factor pathway inhibitor 2 (TFPI2) as a candidate serum biomarker for CCC. In this study, we sought to evaluate the clinical diagnostic performance of TFPI2 in preoperative prediction of CCC. Serum TFPI2 levels were measured in serum samples from a retrospective training set consisting of patients with benign and borderline ovarian tumors, EOC subtypes, and uterine diseases. Via receiver operating characteristic (ROC) analyses, we compared the diagnostic performance of TFPI2 with that of CA125 in discrimination of patients with ovarian CCC from other patient groups. The observed diagnostic performances were examined in a prospective validation set. The 268-patient training set included 29 patients with ovarian CCC. Unlike CA125, which was also elevated in patients with endometriosis and several EOC subtypes, serum TFPI2 levels were specifically elevated only in ovarian CCC patients, consistent with the mRNA expression pattern in tumor tissues. The area under the ROC curve (AUC) of serum TFPI2 was obviously higher than that of CA125 for discrimination of CCC from other ovarian diseases (AUC = 0.891 versus 0.595). Applying a cut-off value of 280 pg/mL, TFPI2 could distinguish early-stage (FIGO I and II) CCC from endometriosis with 72.2% sensitivity, 93.3% specificity, and 88.8% accuracy. Similar results were confirmed in an independent 156-patient prospective validation set. TFPI2 is a useful serum biomarker for preoperative clinical diagnosis of CCC.

Model for Team Training Using the Advanced Trauma Operative Management Course: Pilot Study Analysis.

PubMed

Perkins, R Serene; Lehner, Kathryn A; Armstrong, Randy; Gardiner, Stuart K; Karmy-Jones, Riyad C; Izenberg, Seth D; Long, William B; Wackym, P Ashley

2015-01-01

Education and training of surgeons has traditionally focused on the development of individual knowledge, technical skills, and decision making. Team training with the surgeon's operating room staff has not been prioritized in existing educational paradigms, particularly in trauma surgery. We aimed to determine whether a pilot curriculum for surgical technicians and nurses, based on the American College of Surgeons' Advanced Trauma Operative Management (ATOM) course, would improve staff knowledge if conducted in a team-training environment. Between December 2012 and December 2014, 22 surgical technicians and nurses participated in a curriculum complementary to the ATOM course, consisting of 8 individual 8-hour training sessions designed by and conducted at our institution. Didactic and practical sessions included educational content, hands-on instruction, and alternating role play during 5 system-specific injury scenarios in a simulated operating room environment. A pre- and postcourse examination was administered to participants to assess for improvements in team members' didactic knowledge. Course participants displayed a significant improvement in didactic knowledge after working in a team setting with trauma surgeons during the ATOM course, with a 9-point improvement on the postcourse examination (83%-92%, p = 0.0008). Most participants (90.5%) completing postcourse surveys reported being "highly satisfied" with course content and quality after working in our simulated team-training setting. Team training is critical to improving the knowledge base of surgical technicians and nurses in the trauma operative setting. Improved communication, efficiency, appropriate equipment use, and staff awareness are the desired outcomes when shifting the paradigm from individual to surgical team training so that improved patient outcomes, decreased risk, and cost savings can be achieved. Determine whether a pilot curriculum for surgical technicians and nurses, based on the American College of Surgeons' ATOM course, improves staff knowledge if conducted in a team-training environment. Surgical technicians and nurses participated in a curriculum complementary to the ATOM course. In all, 8 individual 8-hour training sessions were conducted at our institution and contained both didactic and practical content, as well as alternating role play during 5 system-specific injury scenarios. A pre- and postcourse examination was administered to assess for improvements in didactic knowledge. The course was conducted in a simulated team-training setting at the Legacy Institute for Surgical Education and Innovation (Portland, OR), an American College of Surgeons Accredited Educational Institute. In all, 22 surgical technicians and operating room nurses participated in 8 separate ATOM(s) courses and had at least 1 year of surgical scrubbing experience in general surgery with little or no exposure to Level I trauma surgical care. Of these participants, 16 completed the postcourse examination. Participants displayed a significant improvement in didactic knowledge (83%-92%, p = 0.0008) after the ATOM(s) course. Of the 14 participants who completed postcourse surveys, 90.5% were "highly satisfied" with the course content and quality. Team training is critical to improving the knowledge base of surgical technicians and nurses in the trauma operative setting and may contribute to improved patient outcomes, decreased risk, and hospital cost savings. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

[Generalization of money-handling though training in equivalence relationships].

PubMed

Vives-Montero, Carmen; Valero-Aguayo, Luis; Ascanio, Lourdes

2011-02-01

This research used a matching-to-sample procedure and equivalence learning process with language and verbal tasks. In the study, an application of the equivalence relationship of money was used with several kinds of euro coins presented. The sample consisted of 16 children (8 in the experimental group and 8 in the control group) aged 5 years. The prerequisite behaviors, the identification of coins and the practical use of different euro coins, were assessed in the pre and post phases for both groups. The children in the experimental group performed an equivalence task using the matching-to-sample procedure. This consisted of a stimulus sample and four matching stimuli, using a series of euro coins with equivalent value in each set. The children in the control group did not undergo this training process. The results showed a large variability in the children's data of the equivalence tests. The experimental group showed the greatest pre and post changes in the statistically significant data. They also showed a greater generalization in the identification of money and in the use of euro coins than the control group. The implications for educational training and the characteristics of the procedure used here for coin equivalence are discussed.

Asymmetry of Peak Thicknesses between the Superior and Inferior Retinal Nerve Fiber Layers for Early Glaucoma Detection: A Simple Screening Method.

PubMed

Bae, Hyoung Won; Lee, Sang Yeop; Kim, Sangah; Park, Chan Keum; Lee, Kwanghyun; Kim, Chan Yun; Seong, Gong Je

2018-01-01

To assess whether the asymmetry in the peripapillary retinal nerve fiber layer (pRNFL) thickness between superior and inferior hemispheres on optical coherence tomography (OCT) is useful for early detection of glaucoma. The patient population consisted of Training set (a total of 60 subjects with early glaucoma and 59 normal subjects) and Validation set (30 subjects with early glaucoma and 30 normal subjects). Two kinds of ratios were employed to measure the asymmetry between the superior and inferior pRNFL thickness using OCT. One was the ratio of the superior to inferior peak thicknesses (peak pRNFL thickness ratio; PTR), and the other was the ratio of the superior to inferior average thickness (average pRNFL thickness ratio; ATR). The diagnostic abilities of the PTR and ATR were compared to the color code classification in OCT. Using the optimal cut-off values of the PTR and ATR obtained from the Training set, the two ratios were independently validated for diagnostic capability. For the Training set, the sensitivities/specificities of the PTR, ATR, quadrants color code classification, and clock-hour color code classification were 81.7%/93.2%, 71.7%/74.6%, 75.0%/93.2%, and 75.0%/79.7%, respectively. The PTR showed a better diagnostic performance for early glaucoma detection than the ATR and the clock-hour color code classification in terms of areas under the receiver operating characteristic curves (AUCs) (0.898, 0.765, and 0.773, respectively). For the Validation set, the PTR also showed the best sensitivity and AUC. The PTR is a simple method with considerable diagnostic ability for early glaucoma detection. It can, therefore, be widely used as a new screening method for early glaucoma. © Copyright: Yonsei University College of Medicine 2018

Eccentric-Overload Training in Team-Sport Functional Performance: Constant Bilateral Vertical Versus Variable Unilateral Multidirectional Movements.

PubMed

Gonzalo-Skok, Oliver; Tous-Fajardo, Julio; Valero-Campo, Carlos; Berzosa, César; Bataller, Ana Vanessa; Arjol-Serrano, José Luis; Moras, Gerard; Mendez-Villanueva, Alberto

2017-08-01

To analyze the effects of 2 different eccentric-overload training (EOT) programs, using a rotational conical pulley, on functional performance in team-sport players. A traditional movement paradigm (ie, squat) including several sets of 1 bilateral and vertical movement was compared with a novel paradigm including a different exercise in each set of unilateral and multi-directional movements. Forty-eight amateur or semiprofessional team-sport players were randomly assigned to an EOT program including either the same bilateral vertical (CBV, n = 24) movement (squat) or different unilateral multidirectional (VUMD, n = 24) movements. Training programs consisted of 6 sets of 1 exercise (CBV) or 1 set of 6 exercises (VUMD) × 6-10 repetitions with 3 min of passive recovery between sets and exercises, biweekly for 8 wk. Functional-performance assessment included several change-of-direction (COD) tests, a 25-m linear-sprint test, unilateral multidirectional jumping tests (ie, lateral, horizontal, and vertical), and a bilateral vertical-jump test. Within-group analysis showed substantial improvements in all tests in both groups, with VUMD showing more robust adaptations in pooled COD tests and lateral/horizontal jumping, whereas the opposite occurred in CBV respecting linear sprinting and vertical jumping. Between-groups analyses showed substantially better results in lateral jumps (ES = 0.21), left-leg horizontal jump (ES = 0.35), and 10-m COD with right leg (ES = 0.42) in VUMD than in CBV. In contrast, left-leg countermovement jump (ES = 0.26) was possibly better in CBV than in VUMD. Eight weeks of EOT induced substantial improvements in functional-performance tests, although the force-vector application may play a key role to develop different and specific functional adaptations.

Predicting binding poses and affinities for protein - ligand complexes in the 2015 D3R Grand Challenge using a physical model with a statistical parameter estimation

NASA Astrophysics Data System (ADS)

Grudinin, Sergei; Kadukova, Maria; Eisenbarth, Andreas; Marillet, Simon; Cazals, Frédéric

2016-09-01

The 2015 D3R Grand Challenge provided an opportunity to test our new model for the binding free energy of small molecules, as well as to assess our protocol to predict binding poses for protein-ligand complexes. Our pose predictions were ranked 3-9 for the HSP90 dataset, depending on the assessment metric. For the MAP4K dataset the ranks are very dispersed and equal to 2-35, depending on the assessment metric, which does not provide any insight into the accuracy of the method. The main success of our pose prediction protocol was the re-scoring stage using the recently developed Convex-PL potential. We make a thorough analysis of our docking predictions made with AutoDock Vina and discuss the effect of the choice of rigid receptor templates, the number of flexible residues in the binding pocket, the binding pocket size, and the benefits of re-scoring. However, the main challenge was to predict experimentally determined binding affinities for two blind test sets. Our affinity prediction model consisted of two terms, a pairwise-additive enthalpy, and a non pairwise-additive entropy. We trained the free parameters of the model with a regularized regression using affinity and structural data from the PDBBind database. Our model performed very well on the training set, however, failed on the two test sets. We explain the drawback and pitfalls of our model, in particular in terms of relative coverage of the test set by the training set and missed dynamical properties from crystal structures, and discuss different routes to improve it.

Global Characterization and Monitoring of Forest Cover Using Landsat Data: Opportunities and Challenges

NASA Technical Reports Server (NTRS)

Townshend, John R.; Masek, Jeffrey G.; Huang, ChengQuan; Vermote, Eric F.; Gao, Feng; Channan, Saurabh; Sexton, Joseph O.; Feng, Min; Narasimhan, Ramghuram; Kim, Dohyung;

Training and generalization of affective behavior displayed by youth with autism.

PubMed Central

Gena, A; Krantz, P J; McClannahan, L E; Poulson, C L

1996-01-01

The purpose of this study was to teach contextually appropriate affective behavior to 4 youths with autism. Treatment consisted of modeling, prompting, and reinforcement introduced in a multiple baseline design across response categories of affective behavior. During treatment, verbal praise and tokens were delivered contingent on appropriate affective responding during training trials. Modeling and verbal prompting were used as correction procedures. Each youth received treatment in either three or four response categories. Treatment systematically increased responding within the response categories for all 4 participants, with effects being specific to the affective response categories under treatment. Treatment effects occurred across untrained scenarios, therapists, time, and settings, suggesting that generalization had occurred. PMID:8926222

Preferences for and Barriers to Formal and Informal Athletic Training Continuing Education Activities

PubMed Central

Armstrong, Kirk J.; Weidner, Thomas G.

2011-01-01

Context: Our previous research determined the frequency of participation and perceived effect of formal and informal continuing education (CE) activities. However, actual preferences for and barriers to CE must be characterized. Objective: To determine the types of formal and informal CE activities preferred by athletic trainers (ATs) and barriers to their participation in these activities. Design: Cross-sectional study. Setting: Athletic training practice settings. Patients or Other Participants: Of a geographically stratified random sample of 1000 ATs, 427 ATs (42.7%) completed the survey. Main Outcome Measure(s): As part of a larger study, the Survey of Formal and Informal Athletic Training Continuing Education Activities (FIATCEA) was developed and administered electronically. The FIATCEA consists of demographic characteristics and Likert scale items (1 = strongly disagree, 5 = strongly agree) about preferred CE activities and barriers to these activities. Internal consistency of survey items, as determined by Cronbach α, was 0.638 for preferred CE activities and 0.860 for barriers to these activities. Descriptive statistics were computed for all items. Differences between respondent demographic characteristics and preferred CE activities and barriers to these activities were determined via analysis of variance and dependent t tests. The α level was set at .05. Results: Hands-on clinical workshops and professional networking were the preferred formal and informal CE activities, respectively. The most frequently reported barriers to formal CE were the cost of attending and travel distance, whereas the most frequently reported barriers to informal CE were personal and job-specific factors. Differences were noted between both the cost of CE and travel distance to CE and all other barriers to CE participation (F1,411 = 233.54, P < .001). Conclusions: Overall, ATs preferred formal CE activities. The same barriers (eg, cost, travel distance) to formal CE appeared to be universal to all ATs. Informal CE was highly valued by ATs because it could be individualized. PMID:22488195

A comparative study of two hazard handling training methods for novice drivers.

PubMed

Wang, Y B; Zhang, W; Salvendy, G

2010-10-01

The effectiveness of two hazard perception training methods, simulation-based error training (SET) and video-based guided error training (VGET), for novice drivers' hazard handling performance was tested, compared, and analyzed. Thirty-two novice drivers participated in the hazard perception training. Half of the participants were trained using SET by making errors and/or experiencing accidents while driving with a desktop simulator. The other half were trained using VGET by watching prerecorded video clips of errors and accidents that were made by other people. The two groups had exposure to equal numbers of errors for each training scenario. All the participants were tested and evaluated for hazard handling on a full cockpit driving simulator one week after training. Hazard handling performance and hazard response were measured in this transfer test. Both hazard handling performance scores and hazard response distances were significantly better for the SET group than the VGET group. Furthermore, the SET group had more metacognitive activities and intrinsic motivation. SET also seemed more effective in changing participants' confidence, but the result did not reach the significance level. SET exhibited a higher training effectiveness of hazard response and handling than VGET in the simulated transfer test. The superiority of SET might benefit from the higher levels of metacognition and intrinsic motivation during training, which was observed in the experiment. Future research should be conducted to assess whether the advantages of error training are still effective under real road conditions.

Cerebrospinal Fluid Peptides as Potential Parkinson Disease Biomarkers: A Staged Pipeline for Discovery and Validation*

PubMed Central

Shi, Min; Movius, James; Dator, Romel; Aro, Patrick; Zhao, Yanchun; Pan, Catherine; Lin, Xiangmin; Bammler, Theo K.; Stewart, Tessandra; Zabetian, Cyrus P.; Peskind, Elaine R.; Hu, Shu-Ching; Quinn, Joseph F.; Galasko, Douglas R.; Zhang, Jing

2015-01-01

Finding robust biomarkers for Parkinson disease (PD) is currently hampered by inherent technical limitations associated with imaging or antibody-based protein assays. To circumvent the challenges, we adapted a staged pipeline, starting from our previous proteomic profiling followed by high-throughput targeted mass spectrometry (MS), to identify peptides in human cerebrospinal fluid (CSF) for PD diagnosis and disease severity correlation. In this multicenter study consisting of training and validation sets, a total of 178 subjects were randomly selected from a retrospective cohort, matching age and sex between PD patients, healthy controls, and neurological controls with Alzheimer disease (AD). From ∼14,000 unique peptides displaying differences between PD and healthy control in proteomic investigations, 126 peptides were selected based on relevance and observability in CSF using bioinformatic analysis and MS screening, and then quantified by highly accurate and sensitive selected reaction monitoring (SRM) in the CSF of 30 PD patients versus 30 healthy controls (training set), followed by diagnostic (receiver operating characteristics) and disease severity correlation analyses. The most promising candidates were further tested in an independent cohort of 40 PD patients, 38 AD patients, and 40 healthy controls (validation set). A panel of five peptides (derived from SPP1, LRP1, CSF1R, EPHA4, and TIMP1) was identified to provide an area under curve (AUC) of 0.873 (sensitivity = 76.7%, specificity = 80.0%) for PD versus healthy controls in the training set. The performance was essentially confirmed in the validation set (AUC = 0.853, sensitivity = 82.5%, specificity = 82.5%). Additionally, this panel could also differentiate the PD and AD groups (AUC = 0.990, sensitivity = 95.0%, specificity = 97.4%). Furthermore, a combination of two peptides belonging to proteins TIMP1 and APLP1 significantly correlated with disease severity as determined by the Unified Parkinson's Disease Rating Scale motor scores in both the training (r = 0.381, p = 0.038)j and the validation (r = 0.339, p = 0.032) sets. The novel panel of CSF peptides, if validated in independent cohorts, could be used to assist in clinical diagnosis of PD and has the potential to help monitoring or predicting disease progression. PMID:25556233

Effects of quadriceps strength after static and dynamic whole-body vibration exercise.

PubMed

Bush, Jill A; Blog, Gabriel L; Kang, Jie; Faigenbaum, Avery D; Ratamess, Nicholas A

2015-05-01

Numerous studies have shown performance benefits including whole-body vibration (WBV) as a training modality or an acute exercise protocol when used as a component of the resistance training program. Some studies have indicated that performing dynamic exercises as compared with static position exercises while exposed to WBV might be beneficial; however, evidence is lacking. Thus, the purpose of this study was to determine if an acute bout of dynamic versus static squats performed during WBV results in increase in quadriceps force production by means of dynamic isokinetic knee extension and flexion exercise. Nonresistance-trained healthy young men and women (N = 21) of 18-25 years participated in 4 protocols with 2-week rest in-between. Protocol 1 consisted of 5 sets of 10 dynamic squats without vibration; Protocol 2: 5 sets of 30-second static squats without vibration; Protocol 3: 5 sets of 10 dynamic squats with 30-Hz WBV for a total of 2.5 minutes; and Protocol 4: 5 sets of 30-second static squats with 30-Hz WBV for a total of 2.5 minutes. Prestrength tests (1 set of 4 repetitions at 100° · s(-1) for the knee extension exercise) was performed within 5 minutes of starting each protocol, and poststrength testing was performed within 1 minute of completing each protocol. Strength outcomes were analyzed by repeated measures analysis of variance with a significance level set at p ≤ 0.05. A significant decrease in strength was observed after dynamic and static squats without WBV (p = 0.002); an increase in strength after dynamic squats with WBV (p = 0.003); and a decrease in strength after static squats with WBV (p = 0.003). The inclusion of WBV to dynamic resistance exercise can be an added modality to increase strength. Whole-body vibration can have varied effects in altering muscle strength in untrained individuals according to the type of resistance training performed. As a dynamic squat with WBV seems to immediately potentiate neuromuscular functioning, the combination of dynamic exercises and WBV could be used as a potential warm-up procedure before resistance exercise.

Set Shifting Training with Categorization Tasks

PubMed Central

Soveri, Anna; Waris, Otto; Laine, Matti

2013-01-01

The very few cognitive training studies targeting an important executive function, set shifting, have reported performance improvements that also generalized to untrained tasks. The present randomized controlled trial extends set shifting training research by comparing previously used cued training with uncued training. A computerized adaptation of the Wisconsin Card Sorting Test was utilized as the training task in a pretest-posttest experimental design involving three groups of university students. One group received uncued training (n = 14), another received cued training (n = 14) and the control group (n = 14) only participated in pre- and posttests. The uncued training group showed posttraining performance increases on their training task, but neither training group showed statistically significant transfer effects. Nevertheless, comparison of effect sizes for transfer effects indicated that our results did not differ significantly from the previous studies. Our results suggest that the cognitive effects of computerized set shifting training are mostly task-specific, and would preclude any robust generalization effects with this training. PMID:24324717

Sex and Employment-Setting Differences in Work-Family Conflict in Athletic Training.

PubMed

Mazerolle, Stephanie M; Eason, Christianne M; Pitney, William A; Mueller, Megan N

2015-09-01

Work-family conflict (WFC) has received much attention in athletic training, yet several factors related to this phenomenon have not been examined, specifically a practitioner's sex, occupational setting, willingness to leave the profession, and willingness to use work-leave benefits. To examine how sex and occupational differences in athletic training affect WFC and to examine willingness to leave the profession and use work-leave benefits. Cross-sectional study. Multiple occupational settings, including clinic/outreach, education, collegiate, industrial, professional sports, secondary school, and sales. A total of 246 athletic trainers (ATs) (men = 110, women = 136) participated. Of these, 61.4% (n = 151) were between 20 and 39 years old. Participants responded to a previously validated and reliable WFC instrument. We created and validated a 3-item instrument that assessed willingness to use work-leave benefits, which demonstrated good internal consistency (Cronbach α = 0.88), as well as a single question about willingness to leave the profession. The mean (± SD) WFC score was 16.88 ± 4.4 (range = 5 [least amount of conflict] to 25 [highest amount of conflict]). Men scored 17.01 ± 4.5, and women scored 16.76 ± 4.36, indicating above-average WFC. We observed no difference between men and women based on conflict scores (t244 = 0.492, P = .95) or their willingness to leave the profession (t244 = -1.27, P = .21). We noted differences among ATs in different practice settings (F8,245 = 5.015, P <.001); those in collegiate and secondary school settings had higher reported WFC scores. A negative relationship existed between WFC score and comfort using work-leave benefits (2-tailed r = -0.533, P < .001). Comfort with using work-leave benefits was different among practice settings (F8,245 = 3.01, P = .003). The ATs employed in traditional practice settings reported higher levels of WFC. Male and female ATs had comparable experiences of WFC and willingness to leave the profession.

Convolutional networks for vehicle track segmentation

NASA Astrophysics Data System (ADS)

Quach, Tu-Thach

2017-10-01

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple and fast models to label track pixels. These models, however, are unable to capture natural track features, such as continuity and parallelism. More powerful but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3×3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate in low power and have limited training data. As a result, we aim for small and efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our six-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.

Putting the MeaT into TeaM Training: Development, Delivery, and Evaluation of a Surgical Team-Training Workshop.

PubMed

Seymour, Neal E; Paige, John T; Arora, Sonal; Fernandez, Gladys L; Aggarwal, Rajesh; Tsuda, Shawn T; Powers, Kinga A; Langlois, Gerard; Stefanidis, Dimitrios

2016-01-01

Despite importance to patient care, team training is infrequently used in surgical education. To address this, a workshop was developed by the Association for Surgical Education Simulation Committee to teach team training using high-fidelity patient simulators and the American College of Surgeons-Association of Program Directors in Surgery team-training curriculum. Workshops were conducted at 3 national meetings. Participants completed preworkshop and postworkshop questionnaires to define experience, confidence in using simulation, intention to implement, as well as workshop content quality. The course consisted of (A) a didactic review of Preparation, Implementation, and Debriefing and (B) facilitated small group simulation sessions followed by debriefings. Of 78 participants, 51 completed the workshops. Overall, 65% indicated that residents at their institutions used patient simulation, but only 33% used the American College of Surgeons-the Association of Program Directors in Surgery team-training modules. The workshop increased confidence to implement simulation team training (3.4 ± 1.3 vs 4.5 ± 0.9). Quality and importance were rated highly (5.4 ± 00.6, highest score = 6). Preparation for simulation-based team training is possible in this workshop setting, although the effect on actual implementation remains to be determined. Copyright © 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Comparative Effects of Different Balance-Training-Progression Styles on Postural Control and Ankle Force Production: A Randomized Controlled Trial.

PubMed

Cuğ, Mutlu; Duncan, Ashley; Wikstrom, Erik

2016-02-01

Despite the effectiveness of balance training, the exact parameters needed to maximize the benefits of such programs remain unknown. One such factor is how individuals should progress to higher levels of task difficulty within a balance-training program. Yet no investigators have directly compared different balance-training-progression styles. To compare an error-based progression (ie, advance when proficient at a task) with a repetition-based progression (ie, advance after a set amount of repetitions) style during a balance-training program in healthy individuals. Randomized controlled trial. Research laboratory. A total of 28 (16 women, 12 men) physically healthy young adults (age = 21.57 ± 3.95 years, height = 171.60 ± 11.03 cm, weight = 72.96 ± 16.18 kg, body mass index = 24.53 ± 3.7). All participants completed 12 supervised balance-training sessions over 4 weeks. Each session consisted of a combination of dynamic unstable-surface tasks that incorporated a BOSU ball and lasted about 30 minutes. Static balance from an instrumented force plate, dynamic balance as measured via the Star Excursion Balance Test, and ankle force production in all 4 cardinal planes of motion as measured with a handheld dynamometer before and after the intervention. Selected static postural-control outcomes, dynamic postural control, and ankle force production in all planes of motion improved (P < .05). However, no differences between the progression styles were observed (P > .05) for any of the outcome measures. A 4-week balance-training program consisting of dynamic unstable-surface exercises on a BOSU ball improved dynamic postural control and ankle force production in healthy young adults. These results suggest that an error-based balance-training program is comparable with but not superior to a repetition-based balance-training program in improving postural control and ankle force production in healthy young adults.

Underwater target classification using wavelet packets and neural networks.

PubMed

Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J

2000-01-01

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery.

PubMed

Sigdel, Madhav; Dinç, İmren; Dinç, Semih; Sigdel, Madhu S; Pusey, Marc L; Aygün, Ramazan S

2014-03-01

In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training. Secondly, we analyze the performance of Yet Another Two Stage Idea (YATSI) semi-supervised learning using NB, SMO, multilayer perceptron (MLP), J48 and random forest (RF) classifiers. These results are compared with the basic supervised learning using the same training sets. We perform our experiments on a dataset consisting of 2250 protein crystallization images for different proportions of training and test data. Our results indicate that NB and SMO using both self-training and YATSI semi-supervised approaches improve accuracies with respect to supervised learning. On the other hand, MLP, J48 and RF perform better using basic supervised learning. Overall, random forest classifier yields the best accuracy with supervised learning for our dataset.

Application of an Artificial Neural Network to the Prediction of OH Radical Reaction Rate Constants for Evaluating Global Warming Potential.

PubMed

Allison, Thomas C

2016-03-03

Rate constants for reactions of chemical compounds with hydroxyl radical are a key quantity used in evaluating the global warming potential of a substance. Experimental determination of these rate constants is essential, but it can also be difficult and time-consuming to produce. High-level quantum chemistry predictions of the rate constant can suffer from the same issues. Therefore, it is valuable to devise estimation schemes that can give reasonable results on a variety of chemical compounds. In this article, the construction and training of an artificial neural network (ANN) for the prediction of rate constants at 298 K for reactions of hydroxyl radical with a diverse set of molecules is described. Input to the ANN consists of counts of the chemical bonds and bends present in the target molecule. The ANN is trained using 792 (•)OH reaction rate constants taken from the NIST Chemical Kinetics Database. The mean unsigned percent error (MUPE) for the training set is 12%, and the MUPE of the testing set is 51%. It is shown that the present methodology yields rate constants of reasonable accuracy for a diverse set of inputs. The results are compared to high-quality literature values and to another estimation scheme. This ANN methodology is expected to be of use in a wide range of applications for which (•)OH reaction rate constants are required. The model uses only information that can be gathered from a 2D representation of the molecule, making the present approach particularly appealing, especially for screening applications.

Invitation choice structure has no impact on attendance in a female business training program in Kenya.

PubMed

Diwan, Faizan; Makana, Grace; McKenzie, David; Paruzzolo, Silvia

2014-01-01

Business training programs are a common form of support to small businesses, but organizations providing this training often struggle to get business owners to attend. We evaluate the role of invitation choice structure in determining agreement to participate and actual attendance. A field experiment randomly assigned female small business owners in Kenya (N = 1172) to one of three invitation types: a standard opt-in invitation; an active choice invitation where business owners had to explicitly say yes or no to the invitation; and an enhanced active choice invitation which highlighted the costs of saying no. We find no statistically significant effect of these alternative choice structures on willingness to participate in training, attending at least one day, and completing the course. The 95 percent confidence interval for the active treatment effect on attendance is [-1.9%, +9.5%], while for the enhanced active choice treatment it is [-4.1%, +7.7%]. The effect sizes consistent with our data are smaller than impacts measured in health and retirement savings studies in the United States. We examine several potential explanations for the lack of effect in a developing country setting. We find evidence consistent with two potential reasons being limited decision-making power amongst some women, and lower levels of cognition making the enhanced active choice wording less effective.

Invitation Choice Structure Has No Impact on Attendance in a Female Business Training Program in Kenya

PubMed Central

Diwan, Faizan; Makana, Grace; McKenzie, David; Paruzzolo, Silvia

2014-01-01

Business training programs are a common form of support to small businesses, but organizations providing this training often struggle to get business owners to attend. We evaluate the role of invitation choice structure in determining agreement to participate and actual attendance. A field experiment randomly assigned female small business owners in Kenya (N = 1172) to one of three invitation types: a standard opt-in invitation; an active choice invitation where business owners had to explicitly say yes or no to the invitation; and an enhanced active choice invitation which highlighted the costs of saying no. We find no statistically significant effect of these alternative choice structures on willingness to participate in training, attending at least one day, and completing the course. The 95 percent confidence interval for the active treatment effect on attendance is [−1.9%, +9.5%], while for the enhanced active choice treatment it is [−4.1%, +7.7%]. The effect sizes consistent with our data are smaller than impacts measured in health and retirement savings studies in the United States. We examine several potential explanations for the lack of effect in a developing country setting. We find evidence consistent with two potential reasons being limited decision-making power amongst some women, and lower levels of cognition making the enhanced active choice wording less effective. PMID:25299647

Computer-assisted instruction in programming: AID

NASA Technical Reports Server (NTRS)

Friend, J.; Atkinson, R. C.

1971-01-01

Lessons for training students on how to program and operate computers to and AID language are given. The course consists of a set of 50 lessons, plus summaries, reviews, tests, and extra credit problems. No prior knowledge is needed for the course, the only requirement being a strong background in algebra. A student manual, which includes instruction for operating the instructional program and a glossary of terms used in the course, is included in the appendices.

Observations of Distribution Company Decisive Action Operations at the NTC

DTIC Science & Technology

2016-02-26

company consists of a headquarters section and three platoons that have unique skill sets that enable it to execute tactical dis- tribution operations...November–December 2015 Army Sustainment54 TR AI NI NG & ED UC AT IO N Serving as a distribution company observer-coach/trainer (OC/T) for brigade...support battalions (BSBs) at the National Training Center (NTC) at Fort Irwin, Cali- fornia, gave me a clear perspective of company -level

Specific physical trainability in elite young soccer players: efficiency over 6 weeks’ in-season training

PubMed Central

Rouissi, M; Haddad, M; Chtara, H; Chaalali, A; Owen, A; Chamari, K

2017-01-01

The aim of the present study was to compare the effects of 3 training protocols (plyometric [PLYO], agility [AG], or repeated shuttle sprints [RS]) on physical performance in the same population of young soccer players. Forty-two youth-level male players (13.6±0.3-years; 1.65±0.07 m; 54.1±6.5 kg; body fat: 12.8±2.6%) participated in a short-term (6-week) randomized parallel fully controlled training study (pre-to-post measurements): PLYO group, n=10; AG group, n=10; RS group, n=12; and control group [CON] n=10. PLYO training = 9 lower limb exercises (2-3 sets of 8-12 repetitions). The AG group performed planned AG drills and direction changes. RS training consisted of 2-4 sets of 5-6x 20 to 30 m shuttle sprints (20 seconds recovery in between). Progressive overload principles were incorporated into the programme by increasing the number of foot contacts and varying the complexity of the exercises. Pre/post-training tests were: bilateral standing horizontal jump, and unilateral horizontal jumps, sprint (30 m with 10 m lap time), agility (20 m zigzag), and repeated sprint ability (RSA) (i.e. 6x30 m shuttle sprints: 2x15 m with 180° turns). Significant main effects for time (i.e. training application) and group (training type) were detected. Improvements in horizontal jumping were higher (p<0.01: ES=large) in PLYO. The RS group improved significantly more (p<0.01; ES=large) than other groups: 30 m sprint, RSAbest and RSAmean performances. Significantly greater increases in 20 m zigzag performance were observed following AG and RS training (4.0 and 3.8%, respectively) compared with PLYO (2.0%) and CON training (0.8%). No significant differences were reported in the RSAdec between groups. Elite young male soccer players’ physical performances can be significantly and specifically improved either using PLYO or AG or RSA training over short-term in-season training. PMID:28566807

Specific physical trainability in elite young soccer players: efficiency over 6 weeks' in-season training.

PubMed

Chtara, M; Rouissi, M; Haddad, M; Chtara, H; Chaalali, A; Owen, A; Chamari, K

2017-06-01

The aim of the present study was to compare the effects of 3 training protocols (plyometric [PLYO], agility [AG], or repeated shuttle sprints [RS]) on physical performance in the same population of young soccer players. Forty-two youth-level male players (13.6±0.3-years; 1.65±0.07 m; 54.1±6.5 kg; body fat: 12.8±2.6%) participated in a short-term (6-week) randomized parallel fully controlled training study (pre-to-post measurements): PLYO group, n=10; AG group, n=10; RS group, n=12; and control group [CON] n=10. PLYO training = 9 lower limb exercises (2-3 sets of 8-12 repetitions). The AG group performed planned AG drills and direction changes. RS training consisted of 2-4 sets of 5-6x 20 to 30 m shuttle sprints (20 seconds recovery in between). Progressive overload principles were incorporated into the programme by increasing the number of foot contacts and varying the complexity of the exercises. Pre/post-training tests were: bilateral standing horizontal jump, and unilateral horizontal jumps, sprint (30 m with 10 m lap time), agility (20 m zigzag), and repeated sprint ability (RSA) (i.e. 6x30 m shuttle sprints: 2x15 m with 180° turns). Significant main effects for time (i.e. training application) and group (training type) were detected. Improvements in horizontal jumping were higher (p<0.01: ES=large) in PLYO. The RS group improved significantly more (p<0.01; ES=large) than other groups: 30 m sprint, RSA best and RSA mean performances. Significantly greater increases in 20 m zigzag performance were observed following AG and RS training (4.0 and 3.8%, respectively) compared with PLYO (2.0%) and CON training (0.8%). No significant differences were reported in the RSA dec between groups. Elite young male soccer players' physical performances can be significantly and specifically improved either using PLYO or AG or RSA training over short-term in-season training.

An automatic panoramic image reconstruction scheme from dental computed tomography images

PubMed Central

Papakosta, Thekla K; Savva, Antonis D; Economopoulos, Theodore L; Gröhndal, H G

2017-01-01

Objectives: Panoramic images of the jaws are extensively used for dental examinations and/or surgical planning because they provide a general overview of the patient's maxillary and mandibular regions. Panoramic images are two-dimensional projections of three-dimensional (3D) objects. Therefore, it should be possible to reconstruct them from 3D radiographic representations of the jaws, produced by CBCT scanning, obviating the need for additional exposure to X-rays, should there be a need of panoramic views. The aim of this article is to present an automated method for reconstructing panoramic dental images from CBCT data. Methods: The proposed methodology consists of a series of sequential processing stages for detecting a fitting dental arch which is used for projecting the 3D information of the CBCT data to the two-dimensional plane of the panoramic image. The detection is based on a template polynomial which is constructed from a training data set. Results: A total of 42 CBCT data sets of real clinical pre-operative and post-operative representations from 21 patients were used. Eight data sets were used for training the system and the rest for testing. Conclusions: The proposed methodology was successfully applied to CBCT data sets, producing corresponding panoramic images, suitable for examining pre-operatively and post-operatively the patients' maxillary and mandibular regions. PMID:28112548

Some strategies to address the challenges of collecting observational data in a busy clinical environment.

PubMed

Jackson, Debra; McDonald, Glenda; Luck, Lauretta; Waine, Melissa; Wilkes, Lesley

2016-01-01

Studies drawing on observational methods can provide vital data to enhance healthcare. However, collecting observational data in clinical settings is replete with challenges, particularly where multiple data-collecting observers are used. Observers collecting data require shared understanding and training to ensure data quality, and particularly, to confirm accurate and consistent identification, discrimination and recording of data. The aim of this paper is to describe strategies for preparing and supporting multiple researchers tasked with collecting observational data in a busy, and often unpredictable, hospital environment. We hope our insights might assist future researchers undertaking research in similar settings.

Psychometric properties of the Postgraduate Hospital Educational Environment Measure in an Iranian hospital setting.

PubMed

Shokoohi, Shahrzad; Emami, Amir Hossein; Mohammadi, Aeen; Ahmadi, Soleiman; Mojtahedzadeh, Rita

2014-01-01

Background Students' perceptions of the educational environment are an important construct in assessing and enhancing the quality of medical training programs. Reliable and valid measurement, however, can be problematic - especially as instruments developed and tested in one culture are translated for use in another. Materials and method This study sought to explore the psychometric properties of the Postgraduate Hospital Educational Environment Measure (PHEEM) for use in an Iranian hospital training setting. We translated the instrument into Persian and ensured its content validity by back translation and expert review prior to administering it to 127 residents of Urmia University of Medical Science. Results Overall internal consistency of the translated measure was good (a=0.94). Principal components analysis revealed five factors accounting for 52.8% of the variance. Conclusion The Persian version of the PHEEM appears to be a reliable and potentially valid instrument for use in Iranian medical schools and may find favor in evaluating the educational environments of residency programs nationwide.

Psychometric properties of the postgraduate hospital educational environment measure in an Iranian hospital setting.

PubMed

Shokoohi, Shahrzad; Hossein Emami, Amir; Mohammadi, Aeen; Ahmadi, Soleiman; Mojtahedzadeh, Rita

2014-01-01

Students' perceptions of the educational environment are an important construct in assessing and enhancing the quality of medical training programs. Reliable and valid measurement, however, can be problematic - especially as instruments developed and tested in one culture are translated for use in another. This study sought to explore the psychometric properties of the Postgraduate Hospital Educational Environment Measure (PHEEM) for use in an Iranian hospital training setting. We translated the instrument into Persian and ensured its content validity by back translation and expert review prior to administering it to 127 residents of Urmia University of Medical Science. Overall internal consistency of the translated measure was good (a=0.94). Principal components analysis revealed five factors accounting for 52.8% of the variance. The Persian version of the PHEEM appears to be a reliable and potentially valid instrument for use in Iranian medical schools and may find favor in evaluating the educational environments of residency programs nationwide.

Chile: Acceptability of a Training Program for Depression Management in Primary Care.

PubMed

Marín, Rigoberto; Martínez, Pablo; Cornejo, Juan P; Díaz, Berta; Peralta, José; Tala, Álvaro; Rojas, Graciela

2016-01-01

In Chile, there are inconsistencies in the management of depression in primary care settings, and the National Depression Program, currently in effect, was implemented without a standardized training program. The objective of this study is to evaluate the acceptability of a training program on the management of depression for primary care health teams. The study was a randomized controlled trial, and two primary centers from the Metropolitan Region of Santiago were randomly selected to carry out the intervention training program. Pre-post surveys were applied, to evaluate expectations and satisfaction with the intervention, respectively. Descriptive and content analysis was carried out. The sample consisted of 41 health professionals, 56.1% of who reported that their expectations for the intervention were met. All of the training activities were evaluated with scores higher than 6.4 (on a 1-7 scale). The trainers, the methodology, and the learning environment were considered strengths and facilitators of the program, while the limited duration of the training, the logistical problems faced during part of the program, and the lack of educational material were viewed as weaknesses. The intervention was well accepted by primary health care teams. However, the clinical impact in patients still has to be evaluated.

The Pediatric Obesity Initiative: development, implementation, and evaluation.

PubMed

Sample, Denise A; Carroll, Heather L; Barksdale, Debra J; Jessup, Ann

2013-09-01

Pediatric obesity rates have nearly tripled over the past three decades contributing to increased morbidity and mortality in the United States and around the world. Pediatric obesity is most prevalent in developed countries and affects all races, ethnicities, cultures, and age groups. To combat this epidemic locally, a team of dedicated providers developed a comprehensive evidenced-based toolkit and training program for clinical practices providing primary care services to children in a North Carolina county. The toolkit and training program were developed using the most current treatment guidelines for pediatric obesity and included resources developed by Healthy Carolinians. One unique feature of the training was a demonstration of motivational interviewing with additional resources included in the toolkit. Staff and providers in three pediatric practices and the local Health Department received the training. In a 3 months follow-up survey after the training, the providers indicated that the toolkit and training program were useful but that they still did not consistently use the guidelines or tools. Ensuring the use of available guidelines and resources by providers remains a challenge. Further study is needed on how to improve implementation of guidelines in primary care settings. ©2013 The Author(s) ©2013 American Association of Nurse Practitioners.

Training Attentional Control in Infancy

PubMed Central

Wass, Sam; Porayska-Pomsta, Kaska; Johnson, Mark H.

2011-01-01

Summary Several recent studies have reported that cognitive training in adults does not lead to generalized performance improvements [1, 2], whereas many studies with younger participants (children 4 years and older) have reported distal transfer [3, 4]. This is consistent with convergent evidence [5–8] for greater neural and behavioral plasticity earlier in development. We used gaze-contingent paradigms to train 11-month-old infants on a battery of attentional control tasks. Relative to an active control group, and following only a relatively short training period, posttraining assessments revealed improvements in cognitive control and sustained attention, reduced saccadic reaction times, and reduced latencies to disengage visual attention. Trend changes were also observed in spontaneous looking behavior during free play, but no change was found in working memory. The amount of training correlated with the degree of improvement on some measures. These findings are to our knowledge the first demonstration of distal transfer following attentional control training in infancy. Given the longitudinal relationships identified between early attentional control and learning in academic settings [9, 10], and the causal role that impaired control of attention may play in disrupting learning in several disorders [11–14], the current results open a number of avenues for future work. PMID:21889346

Single- vs. Multiple-Set Strength Training in Women.

ERIC Educational Resources Information Center

Schlumberger, Andreas; Stec, Justyna; Schmidtbleicher, Dietmar

2001-01-01

Compared the effects of single- and multiple-set strength training in women with basic experience in resistance training. Both training groups had significant strength improvements in leg extension. In the seated bench press, only the three-set group showed a significant increase in maximal strength. There were higher strength gains overall in the…

Optimizing support vector machine learning for semi-arid vegetation mapping by using clustering analysis

NASA Astrophysics Data System (ADS)

Su, Lihong

In remote sensing communities, support vector machine (SVM) learning has recently received increasing attention. SVM learning usually requires large memory and enormous amounts of computation time on large training sets. According to SVM algorithms, the SVM classification decision function is fully determined by support vectors, which compose a subset of the training sets. In this regard, a solution to optimize SVM learning is to efficiently reduce training sets. In this paper, a data reduction method based on agglomerative hierarchical clustering is proposed to obtain smaller training sets for SVM learning. Using a multiple angle remote sensing dataset of a semi-arid region, the effectiveness of the proposed method is evaluated by classification experiments with a series of reduced training sets. The experiments show that there is no loss of SVM accuracy when the original training set is reduced to 34% using the proposed approach. Maximum likelihood classification (MLC) also is applied on the reduced training sets. The results show that MLC can also maintain the classification accuracy. This implies that the most informative data instances can be retained by this approach.

DESCRIPTIVE ANALYSIS OF DIVALENT SALTS

PubMed Central

YANG, HEIDI HAI-LING; LAWLESS, HARRY T.

2005-01-01

Many divalent salts (e.g., calcium, iron, zinc), have important nutritional value and are used to fortify food or as dietary supplements. Sensory characterization of some divalent salts in aqueous solutions by untrained judges has been reported in the psychophysical literature, but formal sensory evaluation by trained panels is lacking. To provide this information, a trained descriptive panel evaluated the sensory characteristics of 10 divalent salts including ferrous sulfate, chloride and gluconate; calcium chloride, lactate and glycerophosphate; zinc sulfate and chloride; and magnesium sulfate and chloride. Among the compounds tested, iron compounds were highest in metallic taste; zinc compounds had higher astringency and a glutamate-like sensation; and bitterness was pronounced for magnesium and calcium salts. Bitterness was affected by the anion in ferrous and calcium salts. Results from the trained panelists were largely consistent with the psychophysical literature using untrained judges, but provided a more comprehensive set of oral sensory attributes. PMID:16614749

Promoting self-exploration and function through an individualized power mobility training program.

PubMed

Kenyon, Lisa K; Farris, John; Brockway, Kaelee; Hannum, Nanette; Proctor, Kevin

2015-01-01

This case report describes the development and implementation of an intervention program that used a Power Wheelchair Trainer (Trainer) to enable an individual with severe impairments to participate in power mobility training. The participant was an 18 year-old female with spastic quadriplegic cerebral palsy, Gross Motor Function Classification Level V. The examination included the Power Mobility Screen and the Caregiver Priorities & Child Health Index of Life with Disabilities (CPCHILD). Switches on the participant's headrest provided control of the Trainer. Intervention consisted of power mobility training in an engaging environment that was set-up to focus on specific power mobility skills. Scores on the Power Mobility Screen and the CPCHILD were higher after intervention. The outcomes of this case report appear to support the use of the Trainer, which allowed the participant to practice power mobility skills and participate in self-exploration of her environment.

[Film as a resource for training in pediatrics].

PubMed

Martínez Barellas, Maria Rosa; Icart Isern, Maria Teresa

2012-11-01

This paper deals with the use of commercial cinema in teaching aimed at students and nursing professionals and related professions. It consists of two parts: the first deals with the use of cinema in the health sciences with emphasis on the training of specialists in pediatrics. We present Pompe disease that is the subject of the film Extraordinary Measures (T. Vaughan, 2010). The second sets out a number of guidelines that can guide in the preparation and conduct of a class or session with the film above. These guidelines provide guidance for other films on de health issues. The specific objective of this first part is to present the commercial cinema as a useful resource to train students in values, attitudes and social skills, using the theme and content of the films viewed. It also shows how to incorporate film as educational methodology in the curriculum project.

Comparison of three methods for long-term monitoring of boreal lake area using Landsat TM and ETM+ imagery

USGS Publications Warehouse

Roach, Jennifer K.; Griffith, Brad; Verbyla, David

2012-01-01

Programs to monitor lake area change are becoming increasingly important in high latitude regions, and their development often requires evaluating tradeoffs among different approaches in terms of accuracy of measurement, consistency across multiple users over long time periods, and efficiency. We compared three supervised methods for lake classification from Landsat imagery (density slicing, classification trees, and feature extraction). The accuracy of lake area and number estimates was evaluated relative to high-resolution aerial photography acquired within two days of satellite overpasses. The shortwave infrared band 5 was better at separating surface water from nonwater when used alone than when combined with other spectral bands. The simplest of the three methods, density slicing, performed best overall. The classification tree method resulted in the most omission errors (approx. 2x), feature extraction resulted in the most commission errors (approx. 4x), and density slicing had the least directional bias (approx. half of the lakes with overestimated area and half of the lakes with underestimated area). Feature extraction was the least consistent across training sets (i.e., large standard error among different training sets). Density slicing was the best of the three at classifying small lakes as evidenced by its lower optimal minimum lake size criterion of 5850 m2 compared with the other methods (8550 m2). Contrary to conventional wisdom, the use of additional spectral bands and a more sophisticated method not only required additional processing effort but also had a cost in terms of the accuracy and consistency of lake classifications.

Texture classification of normal tissues in computed tomography using Gabor filters

NASA Astrophysics Data System (ADS)

Dettori, Lucia; Bashir, Alia; Hasemann, Julie

2007-03-01

The research presented in this article is aimed at developing an automated imaging system for classification of normal tissues in medical images obtained from Computed Tomography (CT) scans. Texture features based on a bank of Gabor filters are used to classify the following tissues of interests: liver, spleen, kidney, aorta, trabecular bone, lung, muscle, IP fat, and SQ fat. The approach consists of three steps: convolution of the regions of interest with a bank of 32 Gabor filters (4 frequencies and 8 orientations), extraction of two Gabor texture features per filter (mean and standard deviation), and creation of a Classification and Regression Tree-based classifier that automatically identifies the various tissues. The data set used consists of approximately 1000 DIACOM images from normal chest and abdominal CT scans of five patients. The regions of interest were labeled by expert radiologists. Optimal trees were generated using two techniques: 10-fold cross-validation and splitting of the data set into a training and a testing set. In both cases, perfect classification rules were obtained provided enough images were available for training (~65%). All performance measures (sensitivity, specificity, precision, and accuracy) for all regions of interest were at 100%. This significantly improves previous results that used Wavelet, Ridgelet, and Curvelet texture features, yielding accuracy values in the 85%-98% range The Gabor filters' ability to isolate features at different frequencies and orientations allows for a multi-resolution analysis of texture essential when dealing with, at times, very subtle differences in the texture of tissues in CT scans.

Thinking Outside of Outpatient: Underutilized Settings for Psychotherapy Education.

PubMed

Blumenshine, Philip; Lenet, Alison E; Havel, Lauren K; Arbuckle, Melissa R; Cabaniss, Deborah L

2017-02-01

Although psychiatry residents are expected to achieve competency in conducting psychotherapy during their training, it is unclear how psychotherapy teaching is integrated across diverse clinical settings. Between January and March 2015, 177 psychiatry residency training directors were sent a survey asking about psychotherapy training practices in their programs, as well as perceived barriers to psychotherapy teaching. Eighty-two training directors (44%) completed the survey. While 95% indicated that psychotherapy was a formal learning objective for outpatient clinic rotations, fifty percent or fewer noted psychotherapy was a learning objective in other settings. Most program directors would like to see psychotherapy training included (particularly supportive psychotherapy and cognitive behavioral therapy) on inpatient (82%) and consultation-liaison settings (57%). The most common barriers identified to teaching psychotherapy in these settings were time and perceived inadequate staff training and interest. Non-outpatient rotations appear to be an underutilized setting for psychotherapy teaching.

The Utrecht questionnaire (U-CEP) measuring knowledge on clinical epidemiology proved to be valid.

PubMed

Kortekaas, Marlous F; Bartelink, Marie-Louise E L; de Groot, Esther; Korving, Helen; de Wit, Niek J; Grobbee, Diederick E; Hoes, Arno W

2017-02-01

Knowledge on clinical epidemiology is crucial to practice evidence-based medicine. We describe the development and validation of the Utrecht questionnaire on knowledge on Clinical epidemiology for Evidence-based Practice (U-CEP); an assessment tool to be used in the training of clinicians. The U-CEP was developed in two formats: two sets of 25 questions and a combined set of 50. The validation was performed among postgraduate general practice (GP) trainees, hospital trainees, GP supervisors, and experts. Internal consistency, internal reliability (item-total correlation), item discrimination index, item difficulty, content validity, construct validity, responsiveness, test-retest reliability, and feasibility were assessed. The questionnaire was externally validated. Internal consistency was good with a Cronbach alpha of 0.8. The median item-total correlation and mean item discrimination index were satisfactory. Both sets were perceived as relevant to clinical practice. Construct validity was good. Both sets were responsive but failed on test-retest reliability. One set took 24 minutes and the other 33 minutes to complete, on average. External GP trainees had comparable results. The U-CEP is a valid questionnaire to assess knowledge on clinical epidemiology, which is a prerequisite for practicing evidence-based medicine in daily clinical practice. Copyright © 2016 Elsevier Inc. All rights reserved.

Working memory training in children: Effectiveness depends on temperament.

PubMed

Studer-Luethi, Barbara; Bauer, Catherine; Perrig, Walter J

2016-02-01

Studies revealing transfer effects of working memory (WM) training on non-trained cognitive performance of children hold promising implications for scholastic learning. However, the results of existing training studies are not consistent and provoke debates about the potential and limitations of cognitive enhancement. To examine the influence of individual differences on training outcomes is a promising approach for finding causes for such inconsistencies. In this study, we implemented WM training in an elementary school setting. The aim was to investigate near and far transfer effects on cognitive abilities and academic achievement and to examine the moderating effects of a dispositional and a regulative temperament factor, neuroticism and effortful control. Ninety-nine second-graders were randomly assigned to 20 sessions of computer-based adaptive WM training, computer-based reading training, or a no-contact control group. For the WM training group, our analyses reveal near transfer on a visual WM task, far transfer on a vocabulary task as a proxy for crystallized intelligence, and increased academic achievement in reading and math by trend. Considering individual differences in temperament, we found that effortful control predicts larger training mean and gain scores and that there is a moderation effect of both temperament factors on post-training improvement: WM training condition predicted higher post-training gains compared to both control conditions only in children with high effortful control or low neuroticism. Our results suggest that a short but intensive WM training program can enhance cognitive abilities in children, but that sufficient self-regulative abilities and emotional stability are necessary for WM training to be effective.

The Effect of Rest Interval Length on Repetition Consistency and Perceived Exertion During Near Maximal Loaded Bench Press Sets.

PubMed

Scudese, Estevão; Willardson, Jeffrey M; Simão, Roberto; Senna, Gilmar; de Salles, Belmiro F; Miranda, Humberto

2015-11-01

The purpose of this study was to compare different rest intervals between sets on repetition consistency and ratings of perceived exertion (RPE) during consecutive bench press sets with an absolute 3RM (3 repetition maximum) load. Sixteen trained men (23.75 ± 4.21 years; 74.63 ± 5.36 kg; 175 ± 4.64 cm; bench press relative strength: 1.44 ± 0.19 kg/kg of body mass) attended 4 randomly ordered sessions during which 5 consecutive sets of the bench press were performed with an absolute 3RM load and 1, 2, 3, or 5 minutes of rest interval between sets. The results indicated that significantly greater bench press repetitions were completed with 2, 3, and 5 minutes vs. 1-minute rest between sets (p ≤ 0.05); no significant differences were noted between the 2, 3, and 5 minutes rest conditions. For the 1-minute rest condition, performance reductions (relative to the first set) were observed commencing with the second set; whereas for the other conditions (2, 3, and 5 minutes rest), performance reductions were not evident until the third and fourth sets. The RPE values before each of the successive sets were significantly greater, commencing with the second set for the 1-minute vs. the 3 and 5 minutes rest conditions. Significant increases were also evident in RPE immediately after each set between the 1 and 5 minutes rest conditions from the second through fifth sets. These findings indicate that when utilizing an absolute 3RM load for the bench press, practitioners may prescribe a time-efficient minimum of 2 minutes rest between sets without significant impairments in repetition performance. However, lower perceived exertion levels may necessitate prescription of a minimum of 3 minutes rest between sets.

Establishing Fire Safety Skills Using Behavioral Skills Training

ERIC Educational Resources Information Center

Houvouras, Andrew J., IV; Harvey, Mark T.

2014-01-01

The use of behavioral skills training (BST) to educate 3 adolescent boys on the risks of lighters and fire setting was evaluated using in situ assessment in a school setting. Two participants had a history of fire setting. After training, all participants adhered to established rules: (a) avoid a deactivated lighter, (b) leave the training area,…

A practical model for the train-set utilization: The case of Beijing-Tianjin passenger dedicated line in China

PubMed Central

Li, Xiaomeng; Yang, Zhuo

2017-01-01

As a sustainable transportation mode, high-speed railway (HSR) has become an efficient way to meet the huge travel demand. However, due to the high acquisition and maintenance cost, it is impossible to build enough infrastructure and purchase enough train-sets. Great efforts are required to improve the transport capability of HSR. The utilization efficiency of train-sets (carrying tools of HSR) is one of the most important factors of the transport capacity of HSR. In order to enhance the utilization efficiency of the train-sets, this paper proposed a train-set circulation optimization model to minimize the total connection time. An innovative two-stage approach which contains segments generation and segments combination was designed to solve this model. In order to verify the feasibility of the proposed approach, an experiment was carried out in the Beijing-Tianjin passenger dedicated line, to fulfill a 174 trips train diagram. The model results showed that compared with the traditional Ant Colony Algorithm (ACA), the utilization efficiency of train-sets can be increased from 43.4% (ACA) to 46.9% (Two-Stage), and 1 train-set can be saved up to fulfill the same transportation tasks. The approach proposed in the study is faster and more stable than the traditional ones, by using which, the HSR staff can draw up the train-sets circulation plan more quickly and the utilization efficiency of the HSR system is also improved. PMID:28489933

The implementation of aerial object recognition algorithm based on contour descriptor in FPGA-based on-board vision system

NASA Astrophysics Data System (ADS)

Babayan, Pavel; Smirnov, Sergey; Strotov, Valery

2017-10-01

This paper describes the aerial object recognition algorithm for on-board and stationary vision system. Suggested algorithm is intended to recognize the objects of a specific kind using the set of the reference objects defined by 3D models. The proposed algorithm based on the outer contour descriptor building. The algorithm consists of two stages: learning and recognition. Learning stage is devoted to the exploring of reference objects. Using 3D models we can build the database containing training images by rendering the 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. Gathered training image set is used for calculating descriptors, which will be used in the recognition stage of the algorithm. The recognition stage is focusing on estimating the similarity of the captured object and the reference objects by matching an observed image descriptor and the reference object descriptors. The experimental research was performed using a set of the models of the aircraft of the different types (airplanes, helicopters, UAVs). The proposed orientation estimation algorithm showed good accuracy in all case studies. The real-time performance of the algorithm in FPGA-based vision system was demonstrated.

The development and pilot-testing of a training curriculum in adolescent medicine and health.

PubMed

Michaud, Pierre-André; Stronski, Susanne; Fonseca, Helena; Macfarlane, Aidan

2004-07-01

To select and propose a set of knowledge, attitudes, and skills essential for the care of adolescents; to encourage the development of adolescent health multidisciplinary networks; and to set up training programs in as many European countries as possible. The curriculum was developed by 16 physicians from 11 European countries with various professional specializations. In line with modern guidelines in medical education, it is a modular, flexible instrument which covers the main teaching areas in the field, such as basic skills (i.e. setting, rights and confidentiality, gender and cultural issues) as well as specific themes (i.e. sexual and reproductive health, eating disorders, chronic conditions). It consists of 17 thematic modules, each containing detailed objectives, learning approaches, examples, and evaluation methods. Two international one-week summer schools were used to assess the feasibility and appropriateness of the curriculum. The overall evaluation was good, with most of the items surpassing three on a four-point Likert scale. However, it pointed to several aspects (process and content) which will need to be refined in the future, such as an increase in interactive sessions (role playing), and a better mix of clinical and public health issues.

A survey-based cross-sectional study of doctors’ expectations and experiences of non-technical skills for Out of Hours work

PubMed Central

Brown, Michael; Shaw, Dominick; Sharples, Sarah; Jeune, Ivan Le; Blakey, John

2015-01-01

Objectives The skill set required for junior doctors to work efficiently and safely Out of Hours (OoH) in hospitals has not been established. This is despite the OoH period representing 75% of the year and it being the time of highest mortality. We set out to explore the expectations of medical students and experiences of junior doctors of the non-technical skills needed to work OoH. Design Survey-based cross-sectional study informed by focus groups. Setting Online survey with participants from five large teaching hospitals across the UK. Participants 300 Medical Students and Doctors Outcome measure Participants ranked the importance of non-technical skills, as identified by literature review and focus groups, needed for OoH care. Results The focus groups revealed a total of eight non-technical skills deemed to be important. In the survey ‘Task Prioritisation’ (mean rank 1.617) was consistently identified as the most important non-technical skill. Stage of training affected the ranking of skills, with significant differences for ‘Communication with Senior Doctors’, ‘Dealing with Clinical Isolation’, ‘Task Prioritisation’ and ‘Communication with Patients’. Importantly, there was a significant discrepancy between the medical student expectations and experiences of doctors undertaking work. Conclusions Our findings suggest that medical staff particularly value task prioritisation skills; however, these are not routinely taught in medical schools. The discrepancy between expectations of students and experience of doctors reinforces the idea that there is a gap in training. Doctors of different grades place different importance on specific non-technical skills with implications for postgraduate training. There is a pressing need for medical schools and deaneries to review non-technical training to include more than communication skills. PMID:25687899

Toward automated biochemotype annotation for large compound libraries.

PubMed

Chen, Xian; Liang, Yizeng; Xu, Jun

2006-08-01

Combinatorial chemistry allows scientists to probe large synthetically accessible chemical space. However, identifying the sub-space which is selectively associated with an interested biological target, is crucial to drug discovery and life sciences. This paper describes a process to automatically annotate biochemotypes of compounds in a library and thus to identify bioactivity related chemotypes (biochemotypes) from a large library of compounds. The process consists of two steps: (1) predicting all possible bioactivities for each compound in a library, and (2) deriving possible biochemotypes based on predictions. The Prediction of Activity Spectra for Substances program (PASS) was used in the first step. In second step, structural similarity and scaffold-hopping technologies are employed. These technologies are used to derive biochemotypes from bioactivity predictions and the corresponding annotated biochemotypes from MDL Drug Data Report (MDDR) database. About a one million (982,889) commercially available compound library (CACL) has been tested using this process. This paper demonstrates the feasibility of automatically annotating biochemotypes for large libraries of compounds. Nevertheless, some issues need to be considered in order to improve the process. First, the prediction accuracy of PASS program has no significant correlation with the number of compounds in a training set. Larger training sets do not necessarily increase the maximal error of prediction (MEP), nor do they increase the hit structural diversity. Smaller training sets do not necessarily decrease MEP, nor do they decrease the hit structural diversity. Second, the success of systematic bioactivity prediction relies on modeling, training data, and the definition of bioactivities (biochemotype ontology). Unfortunately, the biochemotype ontology was not well developed in the PASS program. Consequently, "ill-defined" bioactivities can reduce the quality of predictions. This paper suggests the ways in which the systematic bioactivities prediction program should be improved.

Analysing the 21 cm signal from the epoch of reionization with artificial neural networks

NASA Astrophysics Data System (ADS)

Shimabukuro, Hayato; Semelin, Benoit

2017-07-01

The 21 cm signal from the epoch of reionization should be observed within the next decade. While a simple statistical detection is expected with Square Kilometre Array (SKA) pathfinders, the SKA will hopefully produce a full 3D mapping of the signal. To extract from the observed data constraints on the parameters describing the underlying astrophysical processes, inversion methods must be developed. For example, the Markov Chain Monte Carlo method has been successfully applied. Here, we test another possible inversion method: artificial neural networks (ANNs). We produce a training set that consists of 70 individual samples. Each sample is made of the 21 cm power spectrum at different redshifts produced with the 21cmFast code plus the value of three parameters used in the seminumerical simulations that describe astrophysical processes. Using this set, we train the network to minimize the error between the parameter values it produces as an output and the true values. We explore the impact of the architecture of the network on the quality of the training. Then we test the trained network on the new set of 54 test samples with different values of the parameters. We find that the quality of the parameter reconstruction depends on the sensitivity of the power spectrum to the different parameters at a given redshift, that including thermal noise and sample variance decreases the quality of the reconstruction and that using the power spectrum at several redshifts as an input to the ANN improves the quality of the reconstruction. We conclude that ANNs are a viable inversion method whose main strength is that they require a sparse exploration of the parameter space and thus should be usable with full numerical simulations.

Performance goals on simulators boost resident motivation and skills laboratory attendance.

PubMed

Stefanidis, Dimitrios; Acker, Christina E; Greene, Frederick L

2010-01-01

To assess the impact of setting simulator training goals on resident motivation and skills laboratory attendance. Residents followed a proficiency-based laparoscopic curriculum on the 5 Fundamentals of Laparoscopic Surgery and 9 virtual reality tasks. Training goals consisted of the average expert performance on each task + 2 SD (mandatory) and best expert performance (optional). Residents rated the impact of the training goals on their motivation on a 20-point visual analog scale. Performance and attendance data were analyzed and correlated (Spearman's). Data are reported as medians (range). General Surgery residency program at a regional referral Academic Medical Center. General surgery residents (n = 15). During the first 5 months of the curriculum, weekly attendance rate was 51% (range, 8-96). After 153 (range, 21-412) repetitions, resident speed improved by 97% (range, 18-230), errors improved by 17% (range, 0-24), and motion efficiency by 59% (range, 26-114) compared with their baseline. Nine (60%) residents achieved proficiency in 7 (range, 3-14) and the best goals in 3.5 (range, 1-9) tasks; the other 6 residents had attendance rates <30%. Residents rated the impact of setting performance goals on their motivation as 15 (range, 1-18) and setting a best goal as 13 (range, 1-18). Motivation ratings correlated positively with attendance rates, number of repetitions, performance improvement, and achievement of proficiency and best goals (r = 0.59-0.75; p < 0.05) but negatively with postgraduate year (PGY) (-0.67; p = 0.02). Setting training goals on simulators are associated with improved resident motivation to participate in a simulator curriculum. While more stringent goals may potentiate this effect, they have a limited impact on senior residents. Further research is needed to investigate ways to improve skills laboratory attendance. Copyright 2010 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

A Data-Driven Approach to Assess Coastal Vulnerability: Machine Learning from Hurricane Sandy

NASA Astrophysics Data System (ADS)

Foti, R.; Miller, S. M.; Montalto, F. A.

2015-12-01

As climate changes and population living along the coastlines continues to increase, an understanding of coastal risk and vulnerability to extreme events becomes increasingly important. With as many as 700,000 people living less than 3 m above the high tide line, New York City (NYC) represents one of the most threatened among major world cities. Recent events, most notably Hurricane Sandy, have put a tremendous pressure on the mosaic of economic, environmental, and social activities occurring in NYC at the interface between land and water. Using information on property damages collected by the Civil Air Patrol (CAP) after Hurricane Sandy, we developed a machine-learning based model able to identify the primary factors determining the occurrence and the severity of damages and intended to both assess and predict coastal vulnerability. The available dataset consists of categorical classifications of damages, ranging from 0 (not damaged) to 5 (damaged and flooded), and available for a sample of buildings in the NYC area. A set of algorithms, such as Logistic Regression, Gradient Boosting and Random Forest, were trained on 75% of the available dataset and tested on the remaining 25%, both training and test sets being picked at random. A combination of factors, including elevation, distance from shore, surge depth, soil type and proximity to key topographic features, such as wetlands and parks, were used as predictors. Trained algorithms were able to achieve over 85% prediction accuracy on both the training set and, most notably, the test set, with as few as six predictors, allowing a realistic depiction of the field of damage. Given their accuracy and robustness, we believe that these algorithms can be successfully applied to provide fields of coastal vulnerability for future extreme events, as well as to assess the consequences of changes, whether intended (e.g. land use change) or contingent (e.g. sea level rise), in the physical layout of NYC.

Changes in circulating angiogenic factors after an acute training bout before and after resistance training with or without whole-body-vibration training

NASA Astrophysics Data System (ADS)

Beijer, Åsa; Degens, Hans; May, Francisca; Bloch, Wilhelm; Rittweger, Joern; Rosenberger, Andre

2012-07-01

Both Resistance Exercise and Whole-Body-Vibration training are currently considered as countermeasures against microgravity-induced physiological deconditioning. Here we investigated the effects of whole-body vibration superimposed upon resistance exercise. Within this context, the present study focuses on changes in circulating angiogenic factors as indicators of skeletal muscle adaption. Methods: Twenty-six healthy male subjects (25.2 ± 4.2 yr) were included in this two-group parallel-designed study and randomly assigned to one of the training interventions: either resistance exercise (RE) or resistance vibration exercise (RVE). Participants trained 2-3 times per week for 6 weeks (completing 16 training sessions), where one session took 9 ± 1 min. Participants trained with weights on a guided barbell. The individual training load was set at 80% of their 1-Repetition-Maximum. Each training session consisted of three sets with 8 squats and 12 heel raises, following an incremental training design with regards to weight (RE and RVE) and vibration frequency (RVE only). The vibration frequency was increased from 20 Hz in the first week till 40 Hz during the last two weeks with 5-Hz weekly increments. At the first and 16 ^{th} training session, six blood samples (pre training and 2 min, 5 min, 15 min, 35 min and 75 min post training) were taken. Circulating levels of vascular endothelial growth factor (VEGF), Endostatin and Matrix Metalloproteinases -2 and -9 (MMPs) were determined in serum using Enzyme-linked Immunosorbent Assays. Results: MMP-2 levels increased by 7.0% (SE = 2.7%, P < 0.001) within two minutes after the exercise bout and then decreased to 5.7% below baseline (SE = 2.4%, P < 0.001) between 15 and 75 minutes post exercise. This response was comparable before and after the training programs (P = 0.70) and also between the two intervention groups (P = 0.42). Preliminary analyses indicate that a similar pattern applies to circulating MMP-9, VEGF and Endostatin levels. Conclusion: The present findings suggest 1) that resistance exercise, both with and without superimposed vibration, leads to a transient rise in circulating angiogenic factors, 2) which is not altered after a period of resistance exercise with or without vibration.

Tailoring a training based on the Mental Health Gap Action Programme (mhGAP) Intervention Guide (IG) to Tunisia: process and relevant adaptations.

PubMed

Spagnolo, Jessica; Champagne, François; Leduc, Nicole; Melki, Wahid; Guesmi, Imen; Bram, Nesrine; Guisset, Ann-Lise; Piat, Myra; Laporta, Marc; Charfi, Fatma

2018-01-01

In order to make mental health services more accessible, the Tunisian Ministry of Health, in collaboration with the School of Public Health at the University of Montreal, the World Health Organization office in Tunisia and the Montreal World Health Organization-Pan American Health Organization Collaborating Center for Research and Training in Mental Health, implemented a training programme based on the Mental Health Gap Action Programme (mhGAP) Intervention Guide (IG) (version 1.0) , developed by the World Health Organization. This article describes the phase prior to the implementation of the training, which was offered to general practitioners working in primary care settings in the Greater Tunis area of Tunisia. The phase prior to implementation consisted of adapting the standard mhGAP-IG (version 1.0) to the local primary healthcare context. This adaptation process, an essential step before piloting the training, involved discussions with stakeholder groups, as well as field observations. Through the adaptation process, we were able to make changes to the standard training format and material. In addition, the process helped uncover systemic barriers to effective mental health care. Targeting these barriers in addition to implementing a training programme may help reduce the mental health treatment gap, and promote implementation that is successful and sustainable.

Pilot study of a robotic protocol to treat shoulder subluxation in patients with chronic stroke

PubMed Central

2013-01-01

Background Shoulder subluxation is a frequent complication of motor impairment after stroke, leading to soft tissue damage, stretching of the joint capsule, rotator cuff injury, and in some cases pain, thus limiting use of the affected extremity beyond weakness. In this pilot study, we determined whether robotic treatment of chronic shoulder subluxation can lead to functional improvement and whether any improvement was robust. Methods 18 patients with chronic stroke (3.9 ± 2.9 years from acute stroke), completed 6 weeks of robotic training using the linear shoulder robot. Training was performed 3 times per week on alternate days. Each session consisted of 3 sets of 320 repetitions of the affected arm, and the robotic protocol alternated between training vertical arm movements, shoulder flexion and extension, in an anti-gravity plane, and training horizontal arm movements, scapular protraction and retraction, in a gravity eliminated plane. Results Training with the linear robot improved shoulder stability, motor power, and resulted in improved functional outcomes that were robust 3 months after training. Conclusion In this uncontrolled pilot study, the robotic protocol effectively treated shoulder subluxation in chronic stroke patients. Treatment of subluxation can lead to improved functional use of the affected arm, likely by increasing motor power in the trained muscles. PMID:23914834

Pilot study of a robotic protocol to treat shoulder subluxation in patients with chronic stroke.

PubMed

Dohle, Carolin I; Rykman, Avrielle; Chang, Johanna; Volpe, Bruce T

2013-08-05

Shoulder subluxation is a frequent complication of motor impairment after stroke, leading to soft tissue damage, stretching of the joint capsule, rotator cuff injury, and in some cases pain, thus limiting use of the affected extremity beyond weakness. In this pilot study, we determined whether robotic treatment of chronic shoulder subluxation can lead to functional improvement and whether any improvement was robust. 18 patients with chronic stroke (3.9 ± 2.9 years from acute stroke), completed 6 weeks of robotic training using the linear shoulder robot. Training was performed 3 times per week on alternate days. Each session consisted of 3 sets of 320 repetitions of the affected arm, and the robotic protocol alternated between training vertical arm movements, shoulder flexion and extension, in an anti-gravity plane, and training horizontal arm movements, scapular protraction and retraction, in a gravity eliminated plane. Training with the linear robot improved shoulder stability, motor power, and resulted in improved functional outcomes that were robust 3 months after training. In this uncontrolled pilot study, the robotic protocol effectively treated shoulder subluxation in chronic stroke patients. Treatment of subluxation can lead to improved functional use of the affected arm, likely by increasing motor power in the trained muscles.

A novel perceptual discrimination training task: Reducing fear overgeneralization in the context of fear learning.

PubMed

Ginat-Frolich, Rivkah; Klein, Zohar; Katz, Omer; Shechner, Tomer

2017-06-01

Generalization is an adaptive learning mechanism, but it can be maladaptive when it occurs in excess. A novel perceptual discrimination training task was therefore designed to moderate fear overgeneralization. We hypothesized that improvement in basic perceptual discrimination would translate into lower fear overgeneralization in affective cues. Seventy adults completed a fear-conditioning task prior to being allocated into training or placebo groups. Predesignated geometric shape pairs were constructed for the training task. A target shape from each pair was presented. Thereafter, participants in the training group were shown both shapes and asked to identify the image that differed from the target. Placebo task participants only indicated the location of each shape on the screen. All participants then viewed new geometric pairs and indicated whether they were identical or different. Finally, participants completed a fear generalization test consisting of perceptual morphs ranging from the CS + to the CS-. Fear-conditioning was observed through physiological and behavioural measures. Furthermore, the training group performed better than the placebo group on the assessment task and exhibited decreased fear generalization in response to threat/safety cues. The findings offer evidence for the effectiveness of the novel discrimination training task, setting the stage for future research with clinical populations. Copyright © 2017 Elsevier Ltd. All rights reserved.

The implementation and evaluation of a communication skills training program for oncology nurses.

PubMed

Banerjee, Smita C; Manna, Ruth; Coyle, Nessa; Penn, Stacey; Gallegos, Tess E; Zaider, Talia; Krueger, Carol A; Bialer, Philip A; Bylund, Carma L; Parker, Patricia A

2017-09-01

Many nurses express difficulty in communicating with their patients, especially in oncology settings where there are numerous challenges and high-stake decisions during the course of diagnosis and treatment. Providing specific training in communication skills is one way to enhance the communication between nurses and their patients. We developed and implemented a communication skills training program for nurses, consisting of three teaching modules: responding empathically to patients; discussing death, dying, and end-of-life goals of care; and responding to challenging interactions with families. Training included didactic and experiential small group role plays. This paper presents results on program evaluation, self-efficacy, and behavioral demonstration of learned communication skills. Three hundred forty-two inpatient oncology nurses participated in a 1-day communication skills training program and completed course evaluations, self-reports, and pre- and post-standardized patient assessments. Participants rated the training favorably, and they reported significant gains in self-efficacy in their ability to communicate with patients in various contexts. Participants also demonstrated significant improvement in several empathic skills, as well as in clarifying skill. Our work demonstrates that implementation of a nurse communication skills training program at a major cancer center is feasible and acceptable and has a significant impact on participants' self-efficacy and uptake of communication skills.

Supplemental Oxygen During High-Intensity Exercise Training in Nonhypoxemic Chronic Obstructive Pulmonary Disease.

PubMed

Neunhäuserer, Daniel; Steidle-Kloc, Eva; Weiss, Gertraud; Kaiser, Bernhard; Niederseer, David; Hartl, Sylvia; Tschentscher, Marcus; Egger, Andreas; Schönfelder, Martin; Lamprecht, Bernd; Studnicka, Michael; Niebauer, Josef

2016-11-01

Physical exercise training is an evidence-based treatment in chronic obstructive pulmonary disease, and patients' peak work rate is associated with reduced chronic obstructive pulmonary disease mortality. We assessed whether supplemental oxygen during exercise training in nonhypoxemic patients with chronic obstructive pulmonary disease might lead to superior training outcomes, including improved peak work rate. This was a randomized, double-blind, controlled, crossover trial. Twenty-nine patients with chronic obstructive pulmonary disease (aged 63.5 ± 5.9 years; forced expiratory volume in 1 second percent predicted, 46.4 ± 8.6) completed 2 consecutive 6-week periods of endurance and strength training with progressive intensity, which was performed 3 times per week with supplemental oxygen or compressed medical air (flow via nasal cannula: 10 L/min). Each session of electrocardiography-controlled interval cycling lasted 31 minutes and consisted of a warm-up, 7 cycles of 1-minute intervals at 70% to 80% of peak work rate alternating with 2 minutes of active recovery, and final cooldown. Thereafter, patients completed 8 strength-training exercises of 1 set each with 8 to 15 repetitions to failure. Change in peak work rate was the primary study end point. The increase in peak work rate was more than twice as high when patients exercised with supplemental oxygen compared with medical air (0.16 ± 0.02 W/kg vs 0.07 ± 0.02 W/kg; P < .001), which was consistent with all other secondary study end points related to exercise capacity. The impact of oxygen on peak work rate was 39.1% of the overall training effect, whereas it had no influence on strength gain (P > .1 for all exercises). We report that supplemental oxygen in nonhypoxemic chronic obstructive pulmonary disease doubled the effect of endurance training but had no effect on strength gain. Copyright © 2016 Elsevier Inc. All rights reserved.

Balance Training Versus Balance Training With STARS in Patients With Chronic Ankle Instability: A Randomized Controlled Trial.

PubMed

Burcal, Christopher J; Trier, Alejandra Y; Wikstrom, Erik A

2017-09-01

Both balance training and selected interventions meant to target sensory structures (STARS) have been shown to be effective at restoring deficits associated with chronic ankle instability (CAI). Clinicians often use multiple treatment modalities in patients with CAI. However, evidence for combined intervention effectiveness in CAI patients remains limited. To determine if augmenting a balance-training protocol with STARS (BTS) results in greater improvements than balance training (BT) alone in those with CAI. Randomized-controlled trial. Research laboratory. 24 CAI participants (age 21.3 ± 2.0 y; height 169.8 ± 12.9 cm; mass 72.5 ± 22.2 kg) were randomized into 2 groups: BT and BTS. Participants completed a 4-week progression-based balance-training protocol consisting of 3 20-min sessions per week. The experimental group also received a 5-min set of STARS treatments consisting of calf stretching, plantar massage, ankle joint mobilizations, and ankle joint traction before each balance-training session. Outcomes included self-assessed disability, Star Excursion Balance Test reach distance, and time-to-boundary calculated from static balance trials. All outcomes were assessed before, and 24-hours and 1-week after protocol completion. Self-assessed disability was also captured 1-month after the intervention. No significant group differences were identified (P > .10). Both groups demonstrated improvements in all outcome categories after the interventions (P < .10), many of which were retained at 1-week posttest (P < .10). Although 90% CIs include zero, effect sizes favor BTS. Similarly, only the BTS group exceeded the minimal detectable change for time-to-boundary outcomes. While statistically no more effective, exceeding minimal detectable change scores and favorable effect sizes suggest that a 4-week progressive BTS program may be more effective at improving self-assessed disability and postural control in CAI patients than balance training in isolation.

Health Literacy Training for Public Health Nurses in Fukushima: A Multi-site Program Evaluation.

PubMed

Goto, Aya; Lai, Alden Yuanhong; Rudd, Rima E

2015-09-01

Public health nurses (PHNs) are community residents' access points to health information and services in Japan. After the Fukushima nuclear accident, they were challenged to communicate radiation-related health information to best meet community needs. We previously developed and evaluated the outcome of a single-site health literacy training program to augment PHNs' ability to improve community residents' access to written health information. This paper presents an evaluation of an identical training program using data combined from multiple sites, and further included proximal and distal evaluations to document the impact of health literacy training in a post-disaster setting. A total of 64 participants, primarily experienced PHNs, attended one of three multi-session health literacy workshops conducted in multiple sites across Fukushima. Quantitative and qualitative data on PHNs' training satisfaction, self-evaluation of achievements regarding training goals, and application of learned skills were collected and analyzed. Each workshop consisted of two 2-hour sessions introducing health literacy and assessment tools and developing skills to improve written materials, followed by a one-month follow-up assessment on PHNs' application of the gained skills in the field. Post-training evaluations on the appropriateness and usefulness of the workshop were highly positive. At the end of the one-month follow-up, 45% of participants had gained confidence in assessing and revising written materials and had applied the skills they had gained to develop and communicate health information in various settings and modes. This increase in confidence was associated with further application of the learned skills at the municipal level. However, participants reported difficulties in explaining risks, and the need to learn more about plain language to be able to paraphrase professional terms. This paper highlighs the positive outcomes of health literacy training among PHNs. Practical strategies to reinforce their skills to use plain language and communicate the epidemiological concept of risk are also recommended.

Correcting Evaluation Bias of Relational Classifiers with Network Cross Validation

DTIC Science & Technology

2010-01-01

classi- fication algorithms: simple random resampling (RRS), equal-instance random resampling (ERS), and network cross-validation ( NCV ). The first two... NCV procedure that eliminates overlap between test sets altogether. The procedure samples for k disjoint test sets that will be used for evaluation...propLabeled ∗ S) nodes from train Pool in f erenceSet =network − trainSet F = F ∪ < trainSet, test Set, in f erenceSet > end for output: F NCV addresses

Management strategies of iron accumulation in a captive population of black rhinoceroses (Diceros bicornis minor).

PubMed

Mylniczenko, Natalie D; Sullivan, Kathleen E; Corcoran, Michelle E; Fleming, Gregory J; Valdes, Eduardo V

2012-09-01

During routine health screens for black rhinoceroses (Diceros bicornis minor) in a captive setting, serum iron and ferritin were analyzed as well as total iron binding capacity and total iron saturation. Trends for ferritin and percent iron saturation showed steady increases since 2003 in four of four animals (three males; one female) with two animals (one male; one female) consistently showing higher elevations over conspecifics. The historical diet had been comprised of a commercial or in-house complete pelleted feed; several species of fresh browse, Bermuda grass, alfalfa and timothy hays, as well as enrichment and training items (apples, carrots, sweet potatoes, and a small amount of leafy greens and vegetables). In 2009, one of the three male rhinoceroses showed a threefold increase in ferritin and concurrently exhibited clinical signs of lethargy, decreased appetite, and disinterest in training. The lone female showed a twofold increase; she also became reproductively acyclic in the prior year. The male was immobilized for examination and phlebotomy. During the same time period, a new version of the complete pelleted feed, with a reduced amount of iron, was introduced. Subsequent to the diet change, the male's ferritin levels have consistently declined, and the female started cycling again. Even with these corrective steps to reduce iron levels, levels of iron saturation remained high, and ferritin levels were still above 1,500 ng/ml. Therapeutic phlebotomy was instituted via a rigorous training program that allowed phlebotomies over a 30-min time frame. This was possible because of a long-term training program for the animals, consistent training personnel, routine collection of samples on a monthly basis, and general comfort level of the animals in the restraint chute. The results of this integrated approach showed some significant improvements and an overall positive impact on the animals.

Quantitative modeling of peptide binding to TAP using support vector machine.

PubMed

Diez-Rivero, Carmen M; Chenlo, Bernardo; Zuluaga, Pilar; Reche, Pedro A

2010-01-01

The transport of peptides to the endoplasmic reticulum by the transporter associated with antigen processing (TAP) is a necessary step towards determining CD8 T cell epitopes. In this work, we have studied the predictive performance of support vector machine models trained on single residue positions and residue combinations drawn from a large dataset consisting of 613 nonamer peptides of known affinity to TAP. Predictive performance of these TAP affinity models was evaluated under 10-fold cross-validation experiments and measured using Pearson's correlation coefficients (R(p)). Our results show that every peptide position (P1-P9) contributes to TAP binding (minimum R(p) of 0.26 +/- 0.11 was achieved by a model trained on the P6 residue), although the largest contributions to binding correspond to the C-terminal end (R(p) = 0.68 +/- 0.06) and the P1 (R(p) = 0.51 +/- 0.09) and P2 (0.57 +/- 0.08) residues of the peptide. Training the models on additional peptide residues generally improved their predictive performance and a maximum correlation (R(p) = 0.89 +/- 0.03) was achieved by a model trained on the full-length sequences or a residue selection consisting of the first 5 N- and last 3 C-terminal residues of the peptides included in the training set. A system for predicting the binding affinity of peptides to TAP using the methods described here is readily available for free public use at http://imed.med.ucm.es/Tools/tapreg/. (c) 2009 Wiley-Liss, Inc.

Multiclass Reduced-Set Support Vector Machines

NASA Technical Reports Server (NTRS)

Tang, Benyang; Mazzoni, Dominic

2006-01-01

There are well-established methods for reducing the number of support vectors in a trained binary support vector machine, often with minimal impact on accuracy. We show how reduced-set methods can be applied to multiclass SVMs made up of several binary SVMs, with significantly better results than reducing each binary SVM independently. Our approach is based on Burges' approach that constructs each reduced-set vector as the pre-image of a vector in kernel space, but we extend this by recomputing the SVM weights and bias optimally using the original SVM objective function. This leads to greater accuracy for a binary reduced-set SVM, and also allows vectors to be 'shared' between multiple binary SVMs for greater multiclass accuracy with fewer reduced-set vectors. We also propose computing pre-images using differential evolution, which we have found to be more robust than gradient descent alone. We show experimental results on a variety of problems and find that this new approach is consistently better than previous multiclass reduced-set methods, sometimes with a dramatic difference.

A selection of giant radio sources from NVSS

DOE PAGES

Proctor, D. D.

2016-06-01

Results of the application of pattern-recognition techniques to the problem of identifying giant radio sources (GRSs) from the data in the NVSS catalog are presented, and issues affecting the process are explored. Decision-tree pattern-recognition software was applied to training-set source pairs developed from known NVSS large-angular-size radio galaxies. The full training set consisted of 51,195 source pairs, 48 of which were known GRSs for which each lobe was primarily represented by a single catalog component. The source pairs had a maximum separation ofmore » $$20^{\\prime} $$ and a minimum component area of 1.87 square arcmin at the 1.4 mJy level. The importance of comparing the resulting probability distributions of the training and application sets for cases of unknown class ratio is demonstrated. The probability of correctly ranking a randomly selected (GRS, non-GRS) pair from the best of the tested classifiers was determined to be 97.8 ± 1.5%. The best classifiers were applied to the over 870,000 candidate pairs from the entire catalog. Images of higher-ranked sources were visually screened, and a table of over 1600 candidates, including morphological annotation, is presented. These systems include doubles and triples, wide-angle tail and narrow-angle tail, S- or Z-shaped systems, and core-jets and resolved cores. In conclusion, while some resolved-lobe systems are recovered with this technique, generally it is expected that such systems would require a different approach.« less

Objective structured assessment of nontechnical skills: Reliability of a global rating scale for the in-training assessment in the operating room.

PubMed

Dedy, Nicolas J; Szasz, Peter; Louridas, Marisa; Bonrath, Esther M; Husslein, Heinrich; Grantcharov, Teodor P

2015-06-01

Nontechnical skills are critical for patient safety in the operating room (OR). As a result, regulatory bodies for accreditation and certification have mandated the integration of these competencies into postgraduate education. A generally accepted approach to the in-training assessment of nontechnical skills, however, is lacking. The goal of the present study was to develop an evidence-based and reliable tool for the in-training assessment of residents' nontechnical performance in the OR. The Objective Structured Assessment of Nontechnical Skills tool was designed as a 5-point global rating scale with descriptive anchors for each item, based on existing evidence-based frameworks of nontechnical skills, as well as resident training requirements. The tool was piloted on scripted videos and refined in an iterative process. The final version was used to rate residents' performance in recorded OR crisis simulations and during live observations in the OR. A total of 37 simulations and 10 live procedures were rated. Interrater agreement was good for total mean scores, both in simulation and in the real OR, with intraclass correlation coefficients >0.90 in all settings for average and single measures. Internal consistency of the scale was high (Cronbach's alpha = 0.80). The Objective Structured Assessment of Nontechnical Skills global rating scale was developed as an evidence-based tool for the in-training assessment of residents' nontechnical performance in the OR. Unique descriptive anchors allow for a criterion-referenced assessment of performance. Good reliability was demonstrated in different settings, supporting applications in research and education. Copyright © 2015 Elsevier Inc. All rights reserved.

Errorless Learning for Training Individuals With Schizophrenia at a Community Mental Health Setting Providing Work Experience

PubMed Central

Kern, Robert S.; Liberman, Robert P.; Becker, Deborah R.; Drake, Robert E.; Sugar, Catherine A.; Green, Michael F.

2009-01-01

The effects of errorless learning (EL) on work performance, tenure, and personal well-being were compared with conventional job training in a community mental health fellowship club offering 12-week time-limited work experience. Participants were 40 clinically stable schizophrenia and schizoaffective disorder outpatients randomly assigned to EL vs conventional instruction (CI) at a thrift-type clothing store. EL participants received training on how to perform their assigned job tasks based on principles of EL, such as error reduction and automation of task performance. CI participants received training common to other community-based entry-level jobs that included verbal instruction, a visual demonstration, independent practice, and corrective feedback. Participants were scheduled to work 2 hours per week for 12 weeks. For both groups, job training occurred during the first 2 weeks at the worksite. Work performance (assessed using the Work Behavior Inventory, WBI) and personal well-being (self-esteem, job satisfaction, and work stress) were assessed at weeks 2, 4, and 12. Job tenure was defined as the number of weeks on the job or total number of hours worked prior to quitting or study end. The EL group performed better than the CI group on the Work Quality Scale from the WBI, and the group differences were relatively consistent over time. Results from the survival analyses of job tenure revealed a non-significant trend favoring EL. There were no group differences on self-esteem, job satisfaction, or work stress. The findings provide modest support for the extensions of EL to community settings for enhancing work performance. PMID:18326529

How do doctors in training react to seizures?

PubMed

Seneviratne, Udaya; Ma, Henry; Phan, Thanh G

2016-01-01

There are scant data on how doctors approach seizures in the acute setting. We sought to study (a) exposure to seizure disorders as well as relevant training and (b) reactions to seizures in the acute setting, among medical residents undergoing physician training. The exposure to and training on seizure disorders were assessed using a structured questionnaire first. Then, they were tested with 20 videos consisting of 10 epileptic seizures (ESs) and 10 psychogenic nonepileptic seizures (PNESs). After each video, we asked three questions to test (a) the diagnosis and the practice of administration of benzodiazepines to terminate the seizure, (b) the estimation of seizure duration, and (c) the practice of intubation. The accuracy of diagnosis was measured by the area under the summary receiver operating characteristics curve (AUC). The difference between true seizure duration and estimated duration was evaluated using paired-sample t-test. A total of 48 trainees participated in the study. The majority witnessed seizures in movies (37, 77.1%) and television (35, 72.9%). Only 12 (25%) received bedside teaching on seizure disorders. Their diagnostic accuracy of seizures was very poor (AUC=0.54). Participants significantly underestimated the duration of seizures. Thirty-five doctors made an illogical decision to intubate but not to terminate the seizure with intravenous benzodiazepine. The diagnostic accuracy of seizures is poor among trainees, and their estimates of seizure duration are unreliable. Our study highlights potential pitfalls in the acute management of seizures and the need for more training on seizure disorders. Crown Copyright © 2015. Published by Elsevier Inc. All rights reserved.

Errorless learning for training individuals with schizophrenia at a community mental health setting providing work experience.

PubMed

Kern, Robert S; Liberman, Robert P; Becker, Deborah R; Drake, Robert E; Sugar, Catherine A; Green, Michael F

2009-07-01

The effects of errorless learning (EL) on work performance, tenure, and personal well-being were compared with conventional job training in a community mental health fellowship club offering 12-week time-limited work experience. Participants were 40 clinically stable schizophrenia and schizoaffective disorder outpatients randomly assigned to EL vs conventional instruction (CI) at a thrift-type clothing store. EL participants received training on how to perform their assigned job tasks based on principles of EL, such as error reduction and automation of task performance. CI participants received training common to other community-based entry-level jobs that included verbal instruction, a visual demonstration, independent practice, and corrective feedback. Participants were scheduled to work 2 hours per week for 12 weeks. For both groups, job training occurred during the first 2 weeks at the worksite. Work performance (assessed using the Work Behavior Inventory, WBI) and personal well-being (self-esteem, job satisfaction, and work stress) were assessed at weeks 2, 4, and 12. Job tenure was defined as the number of weeks on the job or total number of hours worked prior to quitting or study end. The EL group performed better than the CI group on the Work Quality Scale from the WBI, and the group differences were relatively consistent over time. Results from the survival analyses of job tenure revealed a non-significant trend favoring EL. There were no group differences on self-esteem, job satisfaction, or work stress. The findings provide modest support for the extensions of EL to community settings for enhancing work performance.

Employee to employer communication skills: balancing cancer treatment and employment.

PubMed

Brown, Richard F; Owens, Myra; Bradley, Cathy

2013-02-01

Cancer patients face difficulties in accessing legally mandated benefits and accommodations when they return to the workplace. Poor employer-employee communication inflates these difficulties. Although proven methods to facilitate physician-patient communication exist, these have not been applied to the workplace. Thus, we aimed to assess the feasibility and utility of applying these methods to educate patients about their workplace rights and provide them with communication skills training to aid their conversations with their employers. A DVD was produced to educate patients and facilitate workplace communication. Participants consisted of 28 solid tumor cancer patients (14 women and 14 men) who completed primary cancer treatment in the past 12 months and were employed at the time of diagnosis. Participants watched a communication skills training DVD and completed a telephone interview. The interview elicited information about workplace experiences and evaluation of the DVD training program. The physician-patient communication skills training model utilized was successfully translated to the employer-employee setting. All but one participant found the DVD useful and easy to understand and indicated a high degree of confidence in using the communication skills to help them ask for workplace accommodations. All participants agreed that it would help newly diagnosed patients in discussions with their employers. Our data provides promising preliminary evidence that patient communication skills training can be applied to the workplace setting and is a welcomed aid to newly diagnosed cancer patients in their discussions with employers regarding the impact of treatment on their work performance and needs for accommodations. Copyright © 2011 John Wiley & Sons, Ltd.

The Effects of a Duathlon Simulation on Ventilatory Threshold and Running Economy

PubMed Central

Berry, Nathaniel T.; Wideman, Laurie; Shields, Edgar W.; Battaglini, Claudio L.

2016-01-01

Multisport events continue to grow in popularity among recreational, amateur, and professional athletes around the world. This study aimed to determine the compounding effects of the initial run and cycling legs of an International Triathlon Union (ITU) Duathlon simulation on maximal oxygen uptake (VO2max), ventilatory threshold (VT) and running economy (RE) within a thermoneutral, laboratory controlled setting. Seven highly trained multisport athletes completed three trials; Trial-1 consisted of a speed only VO2max treadmill protocol (SOVO2max) to determine VO2max, VT, and RE during a single-bout run; Trial-2 consisted of a 10 km run at 98% of VT followed by an incremental VO2max test on the cycle ergometer; Trial-3 consisted of a 10 km run and 30 km cycling bout at 98% of VT followed by a speed only treadmill test to determine the compounding effects of the initial legs of a duathlon on VO2max, VT, and RE. A repeated measures ANOVA was performed to determine differences between variables across trials. No difference in VO2max, VT (%VO2max), maximal HR, or maximal RPE was observed across trials. Oxygen consumption at VT was significantly lower during Trial-3 compared to Trial-1 (p = 0.01). This decrease was coupled with a significant reduction in running speed at VT (p = 0.015). A significant interaction between trial and running speed indicate that RE was significantly altered during Trial-3 compared to Trial-1 (p < 0.001). The first two legs of a laboratory based duathlon simulation negatively impact VT and RE. Our findings may provide a useful method to evaluate multisport athletes since a single-bout incremental treadmill test fails to reveal important alterations in physiological thresholds. Key points Decrease in relative oxygen uptake at VT (ml·kg-1·min-1) during the final leg of a duathlon simulation, compared to a single-bout maximal run. We observed a decrease in running speed at VT during the final leg of a duathlon simulation; resulting in an increase of more than 2 minutes to complete a 5 km run. During our study, highly trained athletes were unable to complete the final 5 km run at the same intensity that they completed the initial 10 km run (in a laboratory setting). A better understanding, and determination, of training loads during multisport training may help to better periodize training programs; additional research is required. PMID:27274661

Advanced Simulation in Undergraduate Pilot Training: Visual Display Development

DTIC Science & Technology

1975-12-01

properties of each member were calculated manually and were inserted by means of punched cards, thus it was relatively easy (but time consuming ) to...investigations leading to the decision to employ an all-glass approach which consisted of a two-part glass funnel produced by Corning Glass Wo ks... consuming . After complete sets of materials were selected they had to be cemented into a final assembly. This had to be done in two operations because of the

Orthogonal Procrustes Analysis for Dictionary Learning in Sparse Linear Representation

PubMed Central

Grossi, Giuliano; Lin, Jianyi

2017-01-01

In the sparse representation model, the design of overcomplete dictionaries plays a key role for the effectiveness and applicability in different domains. Recent research has produced several dictionary learning approaches, being proven that dictionaries learnt by data examples significantly outperform structured ones, e.g. wavelet transforms. In this context, learning consists in adapting the dictionary atoms to a set of training signals in order to promote a sparse representation that minimizes the reconstruction error. Finding the best fitting dictionary remains a very difficult task, leaving the question still open. A well-established heuristic method for tackling this problem is an iterative alternating scheme, adopted for instance in the well-known K-SVD algorithm. Essentially, it consists in repeating two stages; the former promotes sparse coding of the training set and the latter adapts the dictionary to reduce the error. In this paper we present R-SVD, a new method that, while maintaining the alternating scheme, adopts the Orthogonal Procrustes analysis to update the dictionary atoms suitably arranged into groups. Comparative experiments on synthetic data prove the effectiveness of R-SVD with respect to well known dictionary learning algorithms such as K-SVD, ILS-DLA and the online method OSDL. Moreover, experiments on natural data such as ECG compression, EEG sparse representation, and image modeling confirm R-SVD’s robustness and wide applicability. PMID:28103283

Smartphone-Based System for Learning and Inferring Hearing Aid Settings.

PubMed

Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J

2016-10-01

Previous research has shown that hearing aid wearers can successfully self-train their instruments' gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the "untrained system," that is, the manufacturer's algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The "trained system" first learned each individual's preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. An experimental within-participants study. Participants used a prototype hearing system-comprising two hearing aids, Android smartphone, and body-worn gateway device-for ∼6 weeks. Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Participants were fitted and instructed to perform daily comparisons of settings ("listening evaluations") through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase, HALIC recorded individual listening preferences along with sensor data from the smartphone-including environmental sound classification, sound level, and location-to build trained models. In the subsequent two-week-long validation phase, participants performed blinded listening evaluations comparing settings predicted by the trained system ("trained settings") to those suggested by the hearing aids' untrained system ("untrained settings"). We analyzed data collected on the smartphone and hearing aids during the study. We also obtained audiometric and demographic information. Overall, the 15 participants with valid data significantly preferred trained settings to untrained settings (paired-samples t test). Seven participants had a significant preference for trained settings, while one had a significant preference for untrained settings (binomial test). The remaining seven participants had nonsignificant preferences. Pooling data across participants, the proportion of times that each setting was chosen in a given environmental sound class was on average very similar. However, breaking down the data by participant revealed strong and idiosyncratic individual preferences. Fourteen participants reported positive feelings of clarity, competence, and mastery when training via HALIC. The obtained data, as well as subjective participant feedback, indicate that smartphones could become viable tools to train hearing aids. Individuals who are tech savvy and have milder HL seem well suited to take advantages of the benefits offered by training with a smartphone. American Academy of Audiology

How well does multiple OCR error correction generalize?

NASA Astrophysics Data System (ADS)

Lund, William B.; Ringger, Eric K.; Walker, Daniel D.

2013-12-01

As the digitization of historical documents, such as newspapers, becomes more common, the need of the archive patron for accurate digital text from those documents increases. Building on our earlier work, the contributions of this paper are: 1. in demonstrating the applicability of novel methods for correcting optical character recognition (OCR) on disparate data sets, including a new synthetic training set, 2. enhancing the correction algorithm with novel features, and 3. assessing the data requirements of the correction learning method. First, we correct errors using conditional random fields (CRF) trained on synthetic training data sets in order to demonstrate the applicability of the methodology to unrelated test sets. Second, we show the strength of lexical features from the training sets on two unrelated test sets, yielding a relative reduction in word error rate on the test sets of 6.52%. New features capture the recurrence of hypothesis tokens and yield an additional relative reduction in WER of 2.30%. Further, we show that only 2.0% of the full training corpus of over 500,000 feature cases is needed to achieve correction results comparable to those using the entire training corpus, effectively reducing both the complexity of the training process and the learned correction model.

Myoeletric indices of fatigue adopting different rest intervals during leg press sets.

PubMed

Miranda, Humberto; Maia, Marianna; de Oliveira, Carlos G; Farias, Déborah; da Silva, Jurandir B; Lima, Vicente P; Willardson, Jeffrey M; Paz, Gabriel A

2018-01-01

The purpose of this study was to examine the acute effect of different rest intervals between multiple sets of the 45° angled leg press exercise (LP45) on surface electromyographic (SEMG) spectral and amplitude indices of fatigue. Fifteen recreationally trained females performed three protocols in a randomized crossover design; each consisting of four sets of 10 repetitions with 1 (P1), 3 (P3), or 5 (P5) minute rest intervals between sets. Each set was performed with 70% of the LP45 ten-repetition maximum load. The SEMG data for biceps femoris (BF), vastus lateralis (VL), vastus medialis (VM), and rectus femoris (RF) muscles was then evaluated. The SEMG amplitude change in the time coefficient (CRMS) and spectral fatigue index (Cf5) indicated higher levels of fatigue for all muscles evaluated during the P3 protocol versus the P1 and P5 protocols (p ≤ 0.05), respectively. The RF and VL muscles showed greater fatigue levels by the second and third sets; whereas, greater fatigue was shown in the VM and BF muscles by the fourth set (p ≤ 0.05). A three-minute rest interval between sets might represent a neuromuscular window between a fatigue stated and fully recovered state in the context of neural activation. Moreover, a three minute rest interval between sets might allow for consistent recruitment of high threshold motor units over multiple sets, and thus promote a more effective stimulus for strength gains. Copyright © 2017 Elsevier Ltd. All rights reserved.

Strengthening close to community provision of maternal health services in fragile settings: an exploration of the changing roles of TBAs in Sierra Leone and Somaliland.

PubMed

Orya, Evelyn; Adaji, Sunday; Pyone, Thidar; Wurie, Haja; van den Broek, Nynke; Theobald, Sally

2017-07-05

Efforts to take forward universal health coverage require innovative approaches in fragile settings, which experience particularly acute human resource shortages and poor health indicators. For maternal and newborn health, it is important to innovate with new partnerships and roles for Traditional Birth Attendants (TBAs) to promote maternal health. We explore perspectives on programmes in Somaliland and Sierra Leone which link TBAs to health centres as part of a pathway to maternal health care. Our study aims to understand the perceptions of communities, stakeholder and TBAs themselves who have been trained in new roles to generate insights on strategies to engage with TBAs and to promote skilled birth attendance in fragile affected settings. A qualitative study was carried out in two chiefdoms in Bombali district in Sierra Leone and the Maroodi Jeex region of Somaliland. Purposively sampled participants consisted of key players from the Ministries of Health, programme implementers, trained TBAs and women who benefitted from the services of trained TBAs. Data was collected through key informants and in-depth interviews and focus group discussions. Data was transcribed, translated and analyzed using the framework approach. For the purposes of this paper, a comparative analysis was undertaken reviewing similarities and differences across the two different contexts. Analysis of multiple viewpoints reveal that with appropriate training and support it is possible to change TBAs practices so they support pregnant women in new ways (support and referral rather than delivery). Participants perceived that trained TBAs can utilize their embedded and trusted community relationships to interact effectively with their communities, help overcome barriers to acceptability, utilization and contribute to effective demand for maternal and newborn services and ultimately enhance utilization of skilled birth attendants. Trained TBAs appreciated cordial relationship at the health centres and feeling as part of the health system. Key challenges that emerged included the distance women needed to travel to reach health centers, appropriate remuneration of trained TBAs and strategies to sustain their work. Our findings highlight the possible gains of the new roles and approaches for trained TBAs through further integrating them into the formal health system. Their potential is arguably critically important in promoting universal health coverage in fragile and conflict affected states (FCAS) where human resources are additionally constrained and maternal and newborn health care needs particularly acute.

Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design.

PubMed

Xu, G; Hughes-Oliver, J M; Brooks, J D; Yeatts, J L; Baynes, R E

2013-01-01

Quantitative structure-activity relationship (QSAR) models are being used increasingly in skin permeation studies. The main idea of QSAR modelling is to quantify the relationship between biological activities and chemical properties, and thus to predict the activity of chemical solutes. As a key step, the selection of a representative and structurally diverse training set is critical to the prediction power of a QSAR model. Early QSAR models selected training sets in a subjective way and solutes in the training set were relatively homogenous. More recently, statistical methods such as D-optimal design or space-filling design have been applied but such methods are not always ideal. This paper describes a comprehensive procedure to select training sets from a large candidate set of 4534 solutes. A newly proposed 'Baynes' rule', which is a modification of Lipinski's 'rule of five', was used to screen out solutes that were not qualified for the study. U-optimality was used as the selection criterion. A principal component analysis showed that the selected training set was representative of the chemical space. Gas chromatograph amenability was verified. A model built using the training set was shown to have greater predictive power than a model built using a previous dataset [1].

Final Report - Facilitating Wind Energy: Addressing Challenges around Visual Impacts, Noise, Credible Data, and Local Benefits through Creative Stakeholder Engagement

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harvey, Kate; Field, Patrick; Fierman, Elizabeth

The project team consisting of the Consensus Building Institute, Inc., Raab Associates, Ltd., and the MIT-Harvard Program on Negotiation created a model and set of tools for building the capacity of state officials to effectively collaborate with diverse stakeholders in advancing wind development policy formation, wind facility siting, and transmission policy and siting. The model was used to enhance the ability of state officials to advance wind development in their states. Training was delivered in Cambridge, MA, in Spring 2011. The training and associated materials, including a Wind Energy Workbook, website, and simulations, is available for ongoing and widespread disseminationmore » throughout the US.« less

Music acquisition: effects of enculturation and formal training on development.

PubMed

Hannon, Erin E; Trainor, Laurel J

2007-11-01

Musical structure is complex, consisting of a small set of elements that combine to form hierarchical levels of pitch and temporal structure according to grammatical rules. As with language, different systems use different elements and rules for combination. Drawing on recent findings, we propose that music acquisition begins with basic features, such as peripheral frequency-coding mechanisms and multisensory timing connections, and proceeds through enculturation, whereby everyday exposure to a particular music system creates, in a systematic order of acquisition, culture-specific brain structures and representations. Finally, we propose that formal musical training invokes domain-specific processes that affect salience of musical input and the amount of cortical tissue devoted to its processing, as well as domain-general processes of attention and executive functioning.

LVQ and backpropagation neural networks applied to NASA SSME data

NASA Technical Reports Server (NTRS)

Doniere, Timothy F.; Dhawan, Atam P.

1993-01-01

Feedfoward neural networks with backpropagation learning have been used as function approximators for modeling the space shuttle main engine (SSME) sensor signals. The modeling of these sensor signals is aimed at the development of a sensor fault detection system that can be used during ground test firings. The generalization capability of a neural network based function approximator depends on the training vectors which in this application may be derived from a number of SSME ground test-firings. This yields a large number of training vectors. Large training sets can cause the time required to train the network to be very large. Also, the network may not be able to generalize for large training sets. To reduce the size of the training sets, the SSME test-firing data is reduced using the learning vector quantization (LVQ) based technique. Different compression ratios were used to obtain compressed data in training the neural network model. The performance of the neural model trained using reduced sets of training patterns is presented and compared with the performance of the model trained using complete data. The LVQ can also be used as a function approximator. The performance of the LVQ as a function approximator using reduced training sets is presented and compared with the performance of the backpropagation network.

Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.

PubMed

Nath, Abhigyan; Subbiah, Karthikeyan

2015-12-01

Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance than that of individual base classifiers. The performance of the learned models trained on Kmeans preprocessed training set is far better than the randomly generated training sets. The proposed method achieved a sensitivity of 90.6%, specificity of 91.4% and accuracy of 91.0% on the first test set and sensitivity of 92.9%, specificity of 96.2% and accuracy of 94.7% on the second blind test set. These results have established that diversifying training set improves the performance of predictive models through superior generalization ability and balancing the training set improves prediction accuracy. For smaller data sets, unsupervised Kmeans based sampling can be an effective technique to increase generalization than that of the usual random splitting method. Copyright © 2015 Elsevier Ltd. All rights reserved.

The UXO Classification Demonstration at San Luis Obispo, CA

DTIC Science & Technology

2010-09-01

Set ................................45  2.17.2  Active Learning Training and Test Set ..........................................47  2.17.3  Extended...optimized algorithm by applying it to only the unlabeled data in the test set. 2.17.2 Active Learning Training and Test Set SIG also used active ... learning [12]. Active learning , an alternative approach for constructing a training set, is used in conjunction with either supervised or semi

Does rational selection of training and test sets improve the outcome of QSAR modeling?

PubMed

Martin, Todd M; Harten, Paul; Young, Douglas M; Muratov, Eugene N; Golbraikh, Alexander; Zhu, Hao; Tropsha, Alexander

2012-10-22

Prior to using a quantitative structure activity relationship (QSAR) model for external predictions, its predictive power should be established and validated. In the absence of a true external data set, the best way to validate the predictive ability of a model is to perform its statistical external validation. In statistical external validation, the overall data set is divided into training and test sets. Commonly, this splitting is performed using random division. Rational splitting methods can divide data sets into training and test sets in an intelligent fashion. The purpose of this study was to determine whether rational division methods lead to more predictive models compared to random division. A special data splitting procedure was used to facilitate the comparison between random and rational division methods. For each toxicity end point, the overall data set was divided into a modeling set (80% of the overall set) and an external evaluation set (20% of the overall set) using random division. The modeling set was then subdivided into a training set (80% of the modeling set) and a test set (20% of the modeling set) using rational division methods and by using random division. The Kennard-Stone, minimal test set dissimilarity, and sphere exclusion algorithms were used as the rational division methods. The hierarchical clustering, random forest, and k-nearest neighbor (kNN) methods were used to develop QSAR models based on the training sets. For kNN QSAR, multiple training and test sets were generated, and multiple QSAR models were built. The results of this study indicate that models based on rational division methods generate better statistical results for the test sets than models based on random division, but the predictive power of both types of models are comparable.

Teaching Health Center Graduate Medical Education Locations Predominantly Located in Federally Designated Underserved Areas.

PubMed

Barclift, Songhai C; Brown, Elizabeth J; Finnegan, Sean C; Cohen, Elena R; Klink, Kathleen

2016-05-01

Background The Teaching Health Center Graduate Medical Education (THCGME) program is an Affordable Care Act funding initiative designed to expand primary care residency training in community-based ambulatory settings. Statute suggests, but does not require, training in underserved settings. Residents who train in underserved settings are more likely to go on to practice in similar settings, and graduates more often than not practice near where they have trained. Objective The objective of this study was to describe and quantify federally designated clinical continuity training sites of the THCGME program. Methods Geographic locations of the training sites were collected and characterized as Health Professional Shortage Area, Medically Underserved Area, Population, or rural areas, and were compared with the distribution of Centers for Medicare and Medicaid Services (CMS)-funded training positions. Results More than half of the teaching health centers (57%) are located in states that are in the 4 quintiles with the lowest CMS-funded resident-to-population ratio. Of the 109 training sites identified, more than 70% are located in federally designated high-need areas. Conclusions The THCGME program is a model that funds residency training in community-based ambulatory settings. Statute suggests, but does not explicitly require, that training take place in underserved settings. Because the majority of the 109 clinical training sites of the 60 funded programs in 2014-2015 are located in federally designated underserved locations, the THCGME program deserves further study as a model to improve primary care distribution into high-need communities.

Development of automatic body condition scoring using a low-cost 3-dimensional Kinect camera.

PubMed

Spoliansky, Roii; Edan, Yael; Parmet, Yisrael; Halachmi, Ilan

2016-09-01

Body condition scoring (BCS) is a farm-management tool for estimating dairy cows' energy reserves. Today, BCS is performed manually by experts. This paper presents a 3-dimensional algorithm that provides a topographical understanding of the cow's body to estimate BCS. An automatic BCS system consisting of a Kinect camera (Microsoft Corp., Redmond, WA) triggered by a passive infrared motion detector was designed and implemented. Image processing and regression algorithms were developed and included the following steps: (1) image restoration, the removal of noise; (2) object recognition and separation, identification and separation of the cows; (3) movie and image selection, selection of movies and frames that include the relevant data; (4) image rotation, alignment of the cow parallel to the x-axis; and (5) image cropping and normalization, removal of irrelevant data, setting the image size to 150×200 pixels, and normalizing image values. All steps were performed automatically, including image selection and classification. Fourteen individual features per cow, derived from the cows' topography, were automatically extracted from the movies and from the farm's herd-management records. These features appear to be measurable in a commercial farm. Manual BCS was performed by a trained expert and compared with the output of the training set. A regression model was developed, correlating the features with the manual BCS references. Data were acquired for 4 d, resulting in a database of 422 movies of 101 cows. Movies containing cows' back ends were automatically selected (389 movies). The data were divided into a training set of 81 cows and a test set of 20 cows; both sets included the identical full range of BCS classes. Accuracy tests gave a mean absolute error of 0.26, median absolute error of 0.19, and coefficient of determination of 0.75, with 100% correct classification within 1 step and 91% correct classification within a half step for BCS classes. Results indicated good repeatability, with all standard deviations under 0.33. The algorithm is independent of the background and requires 10 cows for training with approximately 30 movies of 4 s each. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Evidence-based nursing-sensitive indicators for patients hospitalized with depression in Thailand.

PubMed

Thapinta, Darawan; Anders, Robert L; Mahatnirunkul, Suwat; Srikosai, Soontaree

2010-12-01

The aim of this study was to develop and validate nursing-sensitive indicators for patients hospitalized with depression in Thailand. The initial draft, consisting of 12 categories with 37 subcategories, was then evaluated by experts in the US and Thailand. Hospital records were then utilized to evaluate the feasibility and efficacy of the indicators. The finalized instrument consisted of 11 categories with 43 items with a validity of .98 and internal consistency of .88. This is the first set of indicators developed to evaluate nursing-sensitivity for patients hospitalized with a diagnosis of depression in Thailand. Having nursing indicators for depressed patients provides nurses with concrete tools to evaluate their work with depressed patients, allowing these staff to assess their work in a very specific, methodical, and consistent manner. When problems are discovered, both the staff and administration can work to address these issues through training, procedural changes, and departmental shifts.

Sex and Employment-Setting Differences in Work-Family Conflict in Athletic Training

PubMed Central

Mazerolle, Stephanie M.; Eason, Christianne M.; Pitney, William A.; Mueller, Megan N.

2015-01-01

Context  Work-family conflict (WFC) has received much attention in athletic training, yet several factors related to this phenomenon have not been examined, specifically a practitioner's sex, occupational setting, willingness to leave the profession, and willingness to use work-leave benefits. Objective  To examine how sex and occupational differences in athletic training affect WFC and to examine willingness to leave the profession and use work-leave benefits. Design  Cross-sectional study. Setting  Multiple occupational settings, including clinic/outreach, education, collegiate, industrial, professional sports, secondary school, and sales. Patients or Other Participants  A total of 246 athletic trainers (ATs) (men = 110, women = 136) participated. Of these, 61.4% (n = 151) were between 20 and 39 years old. Main Outcome Measures(s)  Participants responded to a previously validated and reliable WFC instrument. We created and validated a 3-item instrument that assessed willingness to use work-leave benefits, which demonstrated good internal consistency (Cronbach α = 0.88), as well as a single question about willingness to leave the profession. Results  The mean (± SD) WFC score was 16.88 ± 4.4 (range = 5 [least amount of conflict] to 25 [highest amount of conflict]). Men scored 17.01 ± 4.5, and women scored 16.76 ± 4.36, indicating above-average WFC. We observed no difference between men and women based on conflict scores (t244 = 0.492, P = .95) or their willingness to leave the profession (t244 = −1.27, P = .21). We noted differences among ATs in different practice settings (F8,245 = 5.015, P <.001); those in collegiate and secondary school settings had higher reported WFC scores. A negative relationship existed between WFC score and comfort using work-leave benefits (2-tailed r = −0.533, P < .001). Comfort with using work-leave benefits was different among practice settings (F8,245 = 3.01, P = .003). Conclusions  The ATs employed in traditional practice settings reported higher levels of WFC. Male and female ATs had comparable experiences of WFC and willingness to leave the profession. PMID:26381472

Home-based bimanual training based on motor learning principles in children with unilateral cerebral palsy and their parents (the COAD-study): rationale and protocols.

PubMed

Schnackers, Marlous; Beckers, Laura; Janssen-Potten, Yvonne; Aarts, Pauline; Rameckers, Eugène; van der Burg, Jan; de Groot, Imelda; Smeets, Rob; Geurts, Sander; Steenbergen, Bert

2018-04-18

Home-based training is considered an important intervention in rehabilitation of children with unilateral cerebral palsy. Despite consensus on the value of home-based upper limb training, no evidence-based best practice exists. Promoting compliance of children to adhere to an intensive program while keeping parental stress levels low is an important challenge when designing home-based training programs. Incorporating implicit motor learning principles emerges to be a promising method to resolve this challenge. Here we describe two protocols for home-based bimanual training programs, one based on implicit motor learning principles and one based on explicit motor learning principles, for children with unilateral spastic cerebral palsy aged 2 through 7 years. Children receive goal-oriented, task-specific bimanual training in their home environment from their parents for 3.5 h/week for 12 weeks according to an individualized program. Parents will be intensively coached by a multidisciplinary team, consisting of a pediatric therapist and remedial educationalist. Both programs consist of a preparation phase (goal setting, introductory meetings with coaching professionals, design of individualized program, instruction of parents, home visit) and home-based training phase (training, video-recordings, registrations, and telecoaching and home visits by the coaching team). The programs contrast with respect to the teaching strategy, i.e. how the parents support their child during training. In both programs parents provide their child with instructions and feedback that focus on the activity (i.e. task-oriented) or the result of the activity (i.e. result-oriented). However, in the explicit program parents are in addition instructed to give exact instructions and feedback on the motor performance of the bimanual activities, whereas in the implicit program the use of both hands and the appropriate motor performance of the activity are elicited via manipulation of the organization of the activities. With the protocols described here, we aim to take a next step in the development of much needed evidence-based home-based training programs for children with unilateral cerebral palsy.

Neuroendocrine Responses and Body Composition Changes Following Resistance Training Under Normobaric Hypoxia

PubMed Central

Chycki, Jakub; Gołaś, Artur; Zając, Adam; Fidos-Czuba, Olga; Młynarz, Adrian; Smółka, Wojciech

2016-01-01

Abstract The aim of the present study was to evaluate the effects of a 6 week resistance training protocol under hypoxic conditions (FiO2 = 12.9%, 4000 m) on muscle hypertrophy. The project included 12 resistance trained male subjects, randomly divided into two experimental groups. Group 1 (n = 6; age 21 ± 2.4 years; body height [BH] 178.8 ± 7.3 cm; body mass [BM] 80.6 ± 12.3 kg) and group 2 (n = 6; age 22 ± 1.5 years; BH 177.8 ± 3.7cm; BM 81.1 ± 7.5 kg). Each group performed resistance exercises alternately under normoxic and hypoxic conditions (4000 m) for 6 weeks. All subjects followed a training protocol that comprised two training sessions per week at an exercise intensity of 70% of 1RM; each training session consisted of eight sets of 10 repetitions of the bench press and barbell squat, with 3 min rest periods. The results indicated that strength training in normobaric hypoxia caused a significant increase in BM (p < 0.01) and fat free mass (FFM) (p < 0.05) in both groups. Additionally, a significant increase (p < 0.05) was observed in IGF-1 concentrations at rest after 6 weeks of hypoxic resistance training in both groups. The results of this study allow to conclude that resistance training (6 weeks) under normobaric hypoxic conditions induces greater muscle hypertrophy compared to training in normoxic conditions. PMID:28149414

Assessing the need for communication training for specialists in poison information.

PubMed

Planalp, Sally; Crouch, Barbara; Rothwell, Erin; Ellington, Lee

2009-07-01

Effective communication has been shown to be essential to physician-patient communication and may be even more critical for poison control center (PCC) calls because of the absence of visual cues, the need for quick and accurate information exchange, and possible suboptimal conditions such as call surges. Professionals who answer poison control calls typically receive extensive training in toxicology but very little formal training in communication. An instrument was developed to assess the perceived need for communication training for specialists in poison information (SPIs) with input from focus groups and a panel of experts. Requests to respond to an online questionnaire were made to PCCs throughout the United States and Canada. The 537 respondents were 70% SPIs or poison information providers (PIPs), primarily educated in nursing or pharmacy, working across the United States and Canada, and employed by their current centers an average of 10 years. SPIs rated communication skills as extremely important to securing positive outcomes for PCC calls even though they reported that their own training was not strongly focused on communication and existing training in communication was perceived as only moderately useful. Ratings of the usefulness of 21 specific training units were consistently high, especially for new SPIs but also for experienced SPIs. Directors rated the usefulness of training for experienced SPIs higher for 5 of the 21 challenges compared to the ratings of SPIs. Findings support the need for communication training for SPIs and provide an empirical basis for setting priorities in developing training units.

Plyometric Training Effects on Athletic Performance in Youth Soccer Athletes: A Systematic Review.

PubMed

Bedoya, Abigail A; Miltenberger, Matthew R; Lopez, Rebecca M

2015-08-01

The purpose of this systematic review was to critically analyze the literature to determine the effectiveness of plyometric training on athletic performance in youth soccer athletes. A total of 7 studies were included in this review after meeting the following criteria: (a) used plyometric training programs to assess athletic performance, (b) subjects were soccer athletes aged preadolescent up to 17 years, and (c) were published from 2000 to January 2014. Study methods were assessed using the PEDro scale with scores ranging from 4 to 6. Results showed similarities and differences in methodologies and procedures among the included studies. Athletic performance consisting of kicking distance, speed, jumping ability, and agility significantly improved because of plyometric training interventions. The current evidence suggests that plyometric training should be completed 2 days per week for 8-10 weeks during soccer practice with a 72-hour rest period between plyometric training days. The initial number of foot contacts should be 50-60 per session and increase to no more than 80-120 foot contacts per session for this age group to prevent overuse injuries. A total of 3-4 plyometric training exercises should be performed 2-4 sets for 6-15 repetitions per training session. The evidence and the literature suggest that plyometric training for this age group should only be implemented using recommended safety guidelines such as those published by the Canadian Society for Exercise Physiology and the National Strength and Conditioning Association and under appropriate supervision by trained personnel.

Randomized controlled trial of strength training in post-polio patients.

PubMed

Chan, K Ming; Amirjani, Nasim; Sumrain, Mae; Clarke, Anita; Strohschein, Fay J

2003-03-01

Many post-polio patients develop new muscle weakness decades after the initial illness. However, its mechanism and treatment are controversial. The purpose of this study was to test the hypotheses that: (1) after strength training, post-polio patients show strength improvement comparable to that seen in the healthy elderly; (2) such training does not have a deleterious effect on motor unit (MU) survival; and (3) part of the strength improvement is due to an increase in voluntary motor drive. After baseline measures including maximum voluntary contraction force, voluntary activation index, motor unit number estimate, and the tetanic tension of the thumb muscles had been determined, 10 post-polio patients with hand involvement were randomized to either the training or control group. The progressive resistance training program consisted of three sets of eight isometric contractions, three times weekly for 12 weeks. Seven healthy elderly were also randomized and trained in a similar manner. Changes in the baseline parameters were monitored once every 4 weeks throughout the training period. The trained post-polio patients showed a significant improvement in their strength (P < 0.05). The magnitude of gain was greater than that seen in the healthy elderly (mean +/- SE, 41 +/- 16% vs. 29 +/- 8%). The training did not adversely affect MU survival and the improvement was largely attributable to an increase in voluntary motor drive. We therefore conclude that moderate intensity strength training is safe and effective in post-polio patients.

Musical training generalises across modalities and reveals efficient and adaptive mechanisms for reproducing temporal intervals.

PubMed

Aagten-Murphy, David; Cappagli, Giulia; Burr, David

2014-03-01

Expert musicians are able to time their actions accurately and consistently during a musical performance. We investigated how musical expertise influences the ability to reproduce auditory intervals and how this generalises across different techniques and sensory modalities. We first compared various reproduction strategies and interval length, to examine the effects in general and to optimise experimental conditions for testing the effect of music, and found that the effects were robust and consistent across different paradigms. Focussing on a 'ready-set-go' paradigm subjects reproduced time intervals drawn from distributions varying in total length (176, 352 or 704 ms) or in the number of discrete intervals within the total length (3, 5, 11 or 21 discrete intervals). Overall, Musicians performed more veridical than Non-Musicians, and all subjects reproduced auditory-defined intervals more accurately than visually-defined intervals. However, Non-Musicians, particularly with visual stimuli, consistently exhibited a substantial and systematic regression towards the mean interval. When subjects judged intervals from distributions of longer total length they tended to regress more towards the mean, while the ability to discriminate between discrete intervals within the distribution had little influence on subject error. These results are consistent with a Bayesian model that minimizes reproduction errors by incorporating a central tendency prior weighted by the subject's own temporal precision relative to the current distribution of intervals. Finally a strong correlation was observed between all durations of formal musical training and total reproduction errors in both modalities (accounting for 30% of the variance). Taken together these results demonstrate that formal musical training improves temporal reproduction, and that this improvement transfers from audition to vision. They further demonstrate the flexibility of sensorimotor mechanisms in adapting to different task conditions to minimise temporal estimation errors. © 2013.

The Immune System as a Model for Pattern Recognition and Classification

PubMed Central

Carter, Jerome H.

2000-01-01

Objective: To design a pattern recognition engine based on concepts derived from mammalian immune systems. Design: A supervised learning system (Immunos-81) was created using software abstractions of T cells, B cells, antibodies, and their interactions. Artificial T cells control the creation of B-cell populations (clones), which compete for recognition of “unknowns.” The B-cell clone with the “simple highest avidity” (SHA) or “relative highest avidity” (RHA) is considered to have successfully classified the unknown. Measurement: Two standard machine learning data sets, consisting of eight nominal and six continuous variables, were used to test the recognition capabilities of Immunos-81. The first set (Cleveland), consisting of 303 cases of patients with suspected coronary artery disease, was used to perform a ten-way cross-validation. After completing the validation runs, the Cleveland data set was used as a training set prior to presentation of the second data set, consisting of 200 unknown cases. Results: For cross-validation runs, correct recognition using SHA ranged from a high of 96 percent to a low of 63.2 percent. The average correct classification for all runs was 83.2 percent. Using the RHA metric, 11.2 percent were labeled “too close to determine” and no further attempt was made to classify them. Of the remaining cases, 85.5 percent were correctly classified. When the second data set was presented, correct classification occurred in 73.5 percent of cases when SHA was used and in 80.3 percent of cases when RHA was used. Conclusions: The immune system offers a viable paradigm for the design of pattern recognition systems. Additional research is required to fully exploit the nuances of immune computation. PMID:10641961

Long-Term Performance of Readers Trained in Grading Crohn Disease Activity Using MRI.

PubMed

Puylaert, Carl A J; Tielbeek, Jeroen A W; Bipat, Shandra; Boellaard, Thierry N; Nio, C Yung; Stoker, Jaap

2016-12-01

We aim to evaluate the long-term performance of readers who had participated in previous magnetic resonance imaging (MRI) reader training in grading Crohn disease activity. Fourteen readers (8 women; 12 radiologists, 2 residents; mean age 40; range 31-59), who had participated in a previous MRI reader training, participated in a follow-up evaluation after a mean interval of 29 months (range 25-34 months). Follow-up evaluation comprised 25 MRI cases of suspected or known Crohn disease patients with direct feedback; cases were identical to the evaluation set used in the initial reader training (of which readers were unaware). Grading accuracy, overstaging, and understaging were compared between training and follow-up using a consensus score by two experienced abdominal radiologists as the reference standard. In the follow-up evaluation, overall grading accuracy was 73% (95% confidence interval [CI]: 62%-81%), which was comparable to reader training grading accuracy (72%, 95% CI: 61%-80%) (P = .66). Overstaging decreased significantly from 19% (95% CI: 12%-27%) to 13% (95% CI: 8%-21%) between training and follow-up (P = .03), whereas understaging increased significantly from 9% (95% CI: 4%-21%) to 14% (95% CI: 7%-26%) (P < .01). Readers have consistent long-term accuracy for grading Crohn disease activity after case-based reader training with direct feedback. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Information dissemination and training: two key issues for consolidating and strengthening the results of health telematic projects.

PubMed

Arcarese, T; Boi, S; Gagliardi, R

2000-01-01

The concepts expressed in this paper concerns the activities to be developed within HEALTHLINE, a European project under the Telematics Application programme. HEALTHLINE is an umbrella project which takes initiatives and provides links to other international projects on health telematics. The projects involved are NIVEMES and RISE; they represent the starting point from which a common approach will be developed. The experience gained from these projects has highlighted two emerging requirements: information dissemination and training. To fulfil the needs of information, an Internet corner will be set up; it will allow citizens and health professionals to find and exchange information as well as to discuss themes concerning health care. Due to the most advanced technologies recently introduced, the Health care sector has had to modify its traditional ways of working to aid professionals in exploiting new training techniques and Health Care provision methods. HEALTHLINE will focus on training and on the development of the use of new tools and services. Furthermore, the project will exploit the training methodologies based on multimedia technology for developing training-on-the-job modules. The entire system, in its final stage, will consist of a network for co-operating training and information dissemination; European sites in the project will share information, training material and provide education and information on tele-health, medical and health-care issues to health care providers, beneficiaries and the general public.

Effects of 4 Weeks of Explosive-type Strength Training for the Plantar Flexors on the Rate of Torque Development and Postural Stability in Elderly Individuals.

PubMed

Kobayashi, Y; Ueyasu, Y; Yamashita, Y; Akagi, R

2016-06-01

This study aimed to investigate the effect of a 4-week explosive-type strength training program for the plantar flexors on the rate of torque development and postural stability. The participants were 56 elderly men and women divided into training (17 men and 15 women) and control (14 men and 10 women) groups. The participants in the training group underwent explosive-type strength training of the plantar flexors 2 days per week for 4 weeks. Training consisted of 3 sets of 10 repetitions of explosive plantar flexion lasting less than 1 s. The following parameters were determined: muscle volume of the plantar flexors estimated by the muscle thickness and lower leg length, maximal voluntary contraction torque and rate of torque development of plantar flexion, and one-leg standing ability. The training increased the maximal voluntary contraction torque and rate of torque development, but corresponding increases in muscle volume and one-leg standing ability were not found. These results suggest that, for elderly individuals, the 4-week explosive-type strength training of the plantar flexors is effective for increasing the maximal voluntary contraction torque and rate of torque development of plantar flexion but is not effective for improving postural stability. © Georg Thieme Verlag KG Stuttgart · New York.

Neural Network for Nanoscience Scanning Electron Microscope Image Recognition.

PubMed

Modarres, Mohammad Hadi; Aversa, Rossella; Cozzini, Stefano; Ciancio, Regina; Leto, Angelo; Brandino, Giuseppe Piero

2017-10-16

In this paper we applied transfer learning techniques for image recognition, automatic categorization, and labeling of nanoscience images obtained by scanning electron microscope (SEM). Roughly 20,000 SEM images were manually classified into 10 categories to form a labeled training set, which can be used as a reference set for future applications of deep learning enhanced algorithms in the nanoscience domain. The categories chosen spanned the range of 0-Dimensional (0D) objects such as particles, 1D nanowires and fibres, 2D films and coated surfaces, and 3D patterned surfaces such as pillars. The training set was used to retrain on the SEM dataset and to compare many convolutional neural network models (Inception-v3, Inception-v4, ResNet). We obtained compatible results by performing a feature extraction of the different models on the same dataset. We performed additional analysis of the classifier on a second test set to further investigate the results both on particular cases and from a statistical point of view. Our algorithm was able to successfully classify around 90% of a test dataset consisting of SEM images, while reduced accuracy was found in the case of images at the boundary between two categories or containing elements of multiple categories. In these cases, the image classification did not identify a predominant category with a high score. We used the statistical outcomes from testing to deploy a semi-automatic workflow able to classify and label images generated by the SEM. Finally, a separate training was performed to determine the volume fraction of coherently aligned nanowires in SEM images. The results were compared with what was obtained using the Local Gradient Orientation method. This example demonstrates the versatility and the potential of transfer learning to address specific tasks of interest in nanoscience applications.

Resistance exercise training and the orthostatic response

NASA Technical Reports Server (NTRS)

McCarthy, J. P.; Bamman, M. M.; Yelle, J. M.; LeBlanc, A. D.; Rowe, R. M.; Greenisen, M. C.; Lee, S. M.; Spector, E. R.; Fortney, S. M.

1997-01-01

Resistance exercise has been suggested to increase blood volume, increase the sensitivity of the carotid baroreceptor cardiac reflex response (BARO), and decrease leg compliance, all factors that are expected to improve orthostatic tolerance. To further test these hypotheses, cardiovascular responses to standing and to pre-syncopal limited lower body negative pressure (LBNP) were measured in two groups of sedentary men before and after a 12-week period of either exercise (n = 10) or no exercise (control, n = 9). Resistance exercise training consisted of nine isotonic exercises, four sets of each, 3 days per week, stressing all major muscle groups. After exercise training, leg muscle volumes increased (P < 0.05) by 4-14%, lean body mass increased (P = 0.00) by 2.0 (0.5) kg, leg compliance and BARO were not significantly altered, and the maximal LBNP tolerated without pre-syncope was not significantly different. Supine resting heart rate was reduced (P = 0.03) without attenuating the heart rate or blood pressure responses during the stand test or LBNP. Also, blood volume (125I and 51Cr) and red cell mass were increased (P < 0.02) by 2.8% and 3.9%, respectively. These findings indicate that intense resistance exercise increases blood volume but does not consistently improve orthostatic tolerance.

Morphological hippocampal markers for automated detection of Alzheimer's disease and mild cognitive impairment converters in magnetic resonance images.

PubMed

Ferrarini, Luca; Frisoni, Giovanni B; Pievani, Michela; Reiber, Johan H C; Ganzola, Rossana; Milles, Julien

2009-01-01

In this study, we investigated the use of hippocampal shape-based markers for automatic detection of Alzheimer's disease (AD) and mild cognitive impairment converters (MCI-c). Three-dimensional T1-weighted magnetic resonance images of 50 AD subjects, 50 age-matched controls, 15 MCI-c, and 15 MCI-non-converters (MCI-nc) were taken. Manual delineations of both hippocampi were obtained from normalized images. Fully automatic shape modeling was used to generate comparable meshes for both structures. Repeated permutation tests, run over a randomly sub-sampled training set (25 controls and 25 ADs), highlighted shape-based markers, mostly located in the CA1 sector, which consistently discriminated ADs and controls. Support vector machines (SVMs) were trained, using markers from either one or both hippocampi, to automatically classify control and AD subjects. Leave-1-out cross-validations over the remaining 25 ADs and 25 controls resulted in an optimal accuracy of 90% (sensitivity 92%), for markers in the left hippocampus. The same morphological markers were used to train SVMs for MCI-c versus MCI-nc classification: markers in the right hippocampus reached an accuracy (and sensitivity) of 80%. Due to the pattern recognition framework, our results statistically represent the expected performances of clinical set-ups, and compare favorably to analyses based on hippocampal volumes.

Automatic Classification of Time-variable X-Ray Sources

NASA Astrophysics Data System (ADS)

Lo, Kitty K.; Farrell, Sean; Murphy, Tara; Gaensler, B. M.

2014-05-01

To maximize the discovery potential of future synoptic surveys, especially in the field of transient science, it will be necessary to use automatic classification to identify some of the astronomical sources. The data mining technique of supervised classification is suitable for this problem. Here, we present a supervised learning method to automatically classify variable X-ray sources in the Second XMM-Newton Serendipitous Source Catalog (2XMMi-DR2). Random Forest is our classifier of choice since it is one of the most accurate learning algorithms available. Our training set consists of 873 variable sources and their features are derived from time series, spectra, and other multi-wavelength contextual information. The 10 fold cross validation accuracy of the training data is ~97% on a 7 class data set. We applied the trained classification model to 411 unknown variable 2XMM sources to produce a probabilistically classified catalog. Using the classification margin and the Random Forest derived outlier measure, we identified 12 anomalous sources, of which 2XMM J180658.7-500250 appears to be the most unusual source in the sample. Its X-ray spectra is suggestive of a ultraluminous X-ray source but its variability makes it highly unusual. Machine-learned classification and anomaly detection will facilitate scientific discoveries in the era of all-sky surveys.

Designing Multi-target Compound Libraries with Gaussian Process Models.

PubMed

Bieler, Michael; Reutlinger, Michael; Rodrigues, Tiago; Schneider, Petra; Kriegl, Jan M; Schneider, Gisbert

2016-05-01

We present the application of machine learning models to selecting G protein-coupled receptor (GPCR)-focused compound libraries. The library design process was realized by ant colony optimization. A proprietary Boehringer-Ingelheim reference set consisting of 3519 compounds tested in dose-response assays at 11 GPCR targets served as training data for machine learning and activity prediction. We compared the usability of the proprietary data with a public data set from ChEMBL. Gaussian process models were trained to prioritize compounds from a virtual combinatorial library. We obtained meaningful models for three of the targets (5-HT2c , MCH, A1), which were experimentally confirmed for 12 of 15 selected and synthesized or purchased compounds. Overall, the models trained on the public data predicted the observed assay results more accurately. The results of this study motivate the use of Gaussian process regression on public data for virtual screening and target-focused compound library design. © 2016 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

STACCATO: a novel solution to supernova photometric classification with biased training sets

NASA Astrophysics Data System (ADS)

Revsbech, E. A.; Trotta, R.; van Dyk, D. A.

2018-01-01

We present a new solution to the problem of classifying Type Ia supernovae from their light curves alone given a spectroscopically confirmed but biased training set, circumventing the need to obtain an observationally expensive unbiased training set. We use Gaussian processes (GPs) to model the supernovae's (SN's) light curves, and demonstrate that the choice of covariance function has only a small influence on the GPs ability to accurately classify SNe. We extend and improve the approach of Richards et al. - a diffusion map combined with a random forest classifier - to deal specifically with the case of biased training sets. We propose a novel method called Synthetically Augmented Light Curve Classification (STACCATO) that synthetically augments a biased training set by generating additional training data from the fitted GPs. Key to the success of the method is the partitioning of the observations into subgroups based on their propensity score of being included in the training set. Using simulated light curve data, we show that STACCATO increases performance, as measured by the area under the Receiver Operating Characteristic curve (AUC), from 0.93 to 0.96, close to the AUC of 0.977 obtained using the 'gold standard' of an unbiased training set and significantly improving on the previous best result of 0.88. STACCATO also increases the true positive rate for SNIa classification by up to a factor of 50 for high-redshift/low-brightness SNe.

Exploring Summer Medical Care Within the National Collegiate Athletic Association Division I Setting: A Perspective From the Athletic Trainer

PubMed Central

Mazerolle, Stephanie M.; Eason, Christianne M.; Goodman, Ashley

2016-01-01

Context:  Over the last few decades, the National Collegiate Athletics Association (NCAA) has made changes related to the increase in sanctioned team activities during summer athletics. These changes may affect how athletic training services are provided. Objective:  To investigate the methods by which athletic training departments of NCAA institutions manage expectations regarding athletic training services during the summer. Design:  Mixed-methods qualitative and quantitative study. Setting:  The NCAA Division I. Patients or Other Participants:  Twenty-two athletic trainers (13 men, 9 women) participated. All were employed full time within the NCAA Division I setting. Participants were 35 ± 8 years of age (range, 26−52 years), with 12 ± 7 years (range, 3−29 years) of athletic training experience. Data Collection and Analysis:  All participants completed a series of questions online that consisted of closed- (demographic and Likert-scale 5-point) and open-ended items that addressed the research questions. Descriptive statistics, frequency distributions, and phenomenologic analyses were completed with the data. Peer review and multiple-analyst triangulation established credibility. Results:  Summer athletic training services included 3 primary mechanisms: individual medical care, shared medical care, or a combination of the 2. Participants reported working 40 ± 10 hours during the summer. Likert-item analysis showed that participants were moderately satisfied with their summer medical care structure (3.3 ± 1.0) and with the flexibility of summer schedules (3.0 ± 1.2). Yet the qualitative analysis revealed that perceptions of summer medical care were more positive for shared-care participants than for individual- or combination-care participants. The perceived effect on the athletic trainer included increased workload and expectations and a negative influence on work-life balance, particularly in terms of decreased schedule flexibility and opportunities for rejuvenation. For many, the summer season mimicked the hours, workload, and expectations of the nontraditional season. Conclusions:  The NCAA rule changes and medical care expectations affected the summer workload of athletic trainers, but job sharing seemed to help them manage conflict associated with providing summer athletic training services. PMID:26881869

The Training of Morphological Decomposition in Word Processing and Its Effects on Literacy Skills.

PubMed

Bar-Kochva, Irit; Hasselhorn, Marcus

2017-01-01

This study set out to examine the effects of a morpheme-based training on reading and spelling in fifth and sixth graders ( N = 47), who present poor literacy skills and speak German as a second language. A computerized training, consisting of a visual lexical decision task (comprising 2,880 items, presented in 12 sessions), was designed to encourage fast morphological analysis in word processing. The children were divided between two groups: the one underwent a morpheme-based training, in which word-stems of inflections and derivations were presented for a limited duration, while their pre- and suffixes remained on screen until response. Another group received a control training consisting of the same task, except that the duration of presentation of a non-morphological unit was restricted. In a Word Disruption Task, participants read words under three conditions: morphological separation (with symbols separating between the words' morphemes), non-morphological separation (with symbols separating between non-morphological units of words), and no-separation (with symbols presented at the beginning and end of each word). The group receiving the morpheme-based program improved more than the control group in terms of word reading fluency in the morphological condition. The former group also presented similar word reading fluency after training in the morphological condition and in the no-separation condition, thereby suggesting that the morpheme-based training contributed to the integration of morphological decomposition into the process of word recognition. At the same time, both groups similarly improved in other measures of word reading fluency. With regard to spelling, the morpheme-based training group showed a larger improvement than the control group in spelling of trained items, and a unique improvement in spelling of untrained items (untrained word-stems integrated into trained pre- and suffixes). The results further suggest some contribution of the morpheme-based training to performance in a standardized spelling task. The morpheme-based training did not, however, show any unique effect on comprehension. These results suggest that the morpheme-based training is effective in enhancing some basic literacy skill in the population examined, i.e., morphological analysis in word processing and the access to orthographic representations in spelling, with no specific effects on reading fluency and comprehension.

The Training of Morphological Decomposition in Word Processing and Its Effects on Literacy Skills

PubMed Central

Bar-Kochva, Irit; Hasselhorn, Marcus

2017-01-01

This study set out to examine the effects of a morpheme-based training on reading and spelling in fifth and sixth graders (N = 47), who present poor literacy skills and speak German as a second language. A computerized training, consisting of a visual lexical decision task (comprising 2,880 items, presented in 12 sessions), was designed to encourage fast morphological analysis in word processing. The children were divided between two groups: the one underwent a morpheme-based training, in which word-stems of inflections and derivations were presented for a limited duration, while their pre- and suffixes remained on screen until response. Another group received a control training consisting of the same task, except that the duration of presentation of a non-morphological unit was restricted. In a Word Disruption Task, participants read words under three conditions: morphological separation (with symbols separating between the words’ morphemes), non-morphological separation (with symbols separating between non-morphological units of words), and no-separation (with symbols presented at the beginning and end of each word). The group receiving the morpheme-based program improved more than the control group in terms of word reading fluency in the morphological condition. The former group also presented similar word reading fluency after training in the morphological condition and in the no-separation condition, thereby suggesting that the morpheme-based training contributed to the integration of morphological decomposition into the process of word recognition. At the same time, both groups similarly improved in other measures of word reading fluency. With regard to spelling, the morpheme-based training group showed a larger improvement than the control group in spelling of trained items, and a unique improvement in spelling of untrained items (untrained word-stems integrated into trained pre- and suffixes). The results further suggest some contribution of the morpheme-based training to performance in a standardized spelling task. The morpheme-based training did not, however, show any unique effect on comprehension. These results suggest that the morpheme-based training is effective in enhancing some basic literacy skill in the population examined, i.e., morphological analysis in word processing and the access to orthographic representations in spelling, with no specific effects on reading fluency and comprehension. PMID:29163245

Neural Network Burst Pressure Prediction in Graphite/Epoxy Pressure Vessels from Acoustic Emission Amplitude Data

NASA Technical Reports Server (NTRS)

Hill, Eric v. K.; Walker, James L., II; Rowell, Ginger H.

1995-01-01

Acoustic emission (AE) data were taken during hydroproof for three sets of ASTM standard 5.75 inch diameter filament wound graphite/epoxy bottles. All three sets of bottles had the same design and were wound from the same graphite fiber; the only difference was in the epoxies used. Two of the epoxies had similar mechanical properties, and because the acoustic properties of materials are a function of their stiffnesses, it was thought that the AE data from the two sets might also be similar; however, this was not the case. Therefore, the three resin types were categorized using dummy variables, which allowed the prediction of burst pressures all three sets of bottles using a single neural network. Three bottles from each set were used to train the network. The resin category, the AE amplitude distribution data taken up to 25 % of the expected burst pressure, and the actual burst pressures were used as inputs. Architecturally, the network consisted of a forty-three neuron input layer (a single categorical variable defining the resin type plus forty-two continuous variables for the AE amplitude frequencies), a fifteen neuron hidden layer for mapping, and a single output neuron for burst pressure prediction. The network trained on all three bottle sets was able to predict burst pressures in the remaining bottles with a worst case error of + 6.59%, slightly greater than the desired goal of + 5%. This larger than desired error was due to poor resolution in the amplitude data for the third bottle set. When the third set of bottles was eliminated from consideration, only four hidden layer neurons were necessary to generate a worst case prediction error of - 3.43%, well within the desired goal.

Biomedical image segmentation using geometric deformable models and metaheuristics.

PubMed

Mesejo, Pablo; Valsecchi, Andrea; Marrakchi-Kacem, Linda; Cagnoni, Stefano; Damas, Sergio

2015-07-01

This paper describes a hybrid level set approach for medical image segmentation. This new geometric deformable model combines region- and edge-based information with the prior shape knowledge introduced using deformable registration. Our proposal consists of two phases: training and test. The former implies the learning of the level set parameters by means of a Genetic Algorithm, while the latter is the proper segmentation, where another metaheuristic, in this case Scatter Search, derives the shape prior. In an experimental comparison, this approach has shown a better performance than a number of state-of-the-art methods when segmenting anatomical structures from different biomedical image modalities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of hydraulic resistance circuit training on physical fitness components of potential relevance to +Gz tolerance.

PubMed

Jacobs, I; Bell, D G; Pope, J; Lee, W

1987-08-01

Recent studies carried out in the United States and Sweden have demonstrated that strength training can improve +Gz acceleration tolerance. Based on these findings, the Canadian Forces have introduced a training program for aircrew of high performance aircraft. This report describes the changes in physical fitness components considered relevant to +Gz tolerance after 12 weeks of training with this program. Prior to beginning training, 45 military personnel were tested, but only 20 completed a minimum of 24 training sessions. The following variables were measured in these 20 subjects before and after training: maximal strength of several large muscle groups during isokinetic contractions, maximal aerobic power and an endurance fitness index, maximal anaerobic power, anthropometric characteristics, and maximal expiratory pressure generated during exhalation. Training involved hydraulic resistance circuit training 2-4 times/week. The circuit consisted of 3 consecutive sets at each of 8 stations using Hydra-Gym equipment. The exercise:rest ratio was 20:40 s for the initial 4 training weeks and was then changed to 30:50. After training the changes in anthropometric measurements suggested that lean body mass was increased. Small, but significant, increases were also measured in muscle strength during bench press, biceps curls, squats, knee extension, and knee flexion. Neither maximal anaerobic power (i.e. muscular endurance) nor maximal expiratory pressure were changed after the training. Indices of endurance fitness were also increased in the present study. The relatively small increases in strength are probably due to the design of the exercise:rest ratio which resulted in improved strength and aerobic fitness.(ABSTRACT TRUNCATED AT 250 WORDS)

Investigating the different mechanisms of genotoxic and non-genotoxic carcinogens by a gene set analysis.

PubMed

Lee, Won Jun; Kim, Sang Cheol; Lee, Seul Ji; Lee, Jeongmi; Park, Jeong Hill; Yu, Kyung-Sang; Lim, Johan; Kwon, Sung Won

2014-01-01

Based on the process of carcinogenesis, carcinogens are classified as either genotoxic or non-genotoxic. In contrast to non-genotoxic carcinogens, many genotoxic carcinogens have been reported to cause tumor in carcinogenic bioassays in animals. Thus evaluating the genotoxicity potential of chemicals is important to discriminate genotoxic from non-genotoxic carcinogens for health care and pharmaceutical industry safety. Additionally, investigating the difference between the mechanisms of genotoxic and non-genotoxic carcinogens could provide the foundation for a mechanism-based classification for unknown compounds. In this study, we investigated the gene expression of HepG2 cells treated with genotoxic or non-genotoxic carcinogens and compared their mechanisms of action. To enhance our understanding of the differences in the mechanisms of genotoxic and non-genotoxic carcinogens, we implemented a gene set analysis using 12 compounds for the training set (12, 24, 48 h) and validated significant gene sets using 22 compounds for the test set (24, 48 h). For a direct biological translation, we conducted a gene set analysis using Globaltest and selected significant gene sets. To validate the results, training and test compounds were predicted by the significant gene sets using a prediction analysis for microarrays (PAM). Finally, we obtained 6 gene sets, including sets enriched for genes involved in the adherens junction, bladder cancer, p53 signaling pathway, pathways in cancer, peroxisome and RNA degradation. Among the 6 gene sets, the bladder cancer and p53 signaling pathway sets were significant at 12, 24 and 48 h. We also found that the DDB2, RRM2B and GADD45A, genes related to the repair and damage prevention of DNA, were consistently up-regulated for genotoxic carcinogens. Our results suggest that a gene set analysis could provide a robust tool in the investigation of the different mechanisms of genotoxic and non-genotoxic carcinogens and construct a more detailed understanding of the perturbation of significant pathways.

Investigating the Different Mechanisms of Genotoxic and Non-Genotoxic Carcinogens by a Gene Set Analysis

PubMed Central

Lee, Won Jun; Kim, Sang Cheol; Lee, Seul Ji; Lee, Jeongmi; Park, Jeong Hill; Yu, Kyung-Sang; Lim, Johan; Kwon, Sung Won

2014-01-01

Based on the process of carcinogenesis, carcinogens are classified as either genotoxic or non-genotoxic. In contrast to non-genotoxic carcinogens, many genotoxic carcinogens have been reported to cause tumor in carcinogenic bioassays in animals. Thus evaluating the genotoxicity potential of chemicals is important to discriminate genotoxic from non-genotoxic carcinogens for health care and pharmaceutical industry safety. Additionally, investigating the difference between the mechanisms of genotoxic and non-genotoxic carcinogens could provide the foundation for a mechanism-based classification for unknown compounds. In this study, we investigated the gene expression of HepG2 cells treated with genotoxic or non-genotoxic carcinogens and compared their mechanisms of action. To enhance our understanding of the differences in the mechanisms of genotoxic and non-genotoxic carcinogens, we implemented a gene set analysis using 12 compounds for the training set (12, 24, 48 h) and validated significant gene sets using 22 compounds for the test set (24, 48 h). For a direct biological translation, we conducted a gene set analysis using Globaltest and selected significant gene sets. To validate the results, training and test compounds were predicted by the significant gene sets using a prediction analysis for microarrays (PAM). Finally, we obtained 6 gene sets, including sets enriched for genes involved in the adherens junction, bladder cancer, p53 signaling pathway, pathways in cancer, peroxisome and RNA degradation. Among the 6 gene sets, the bladder cancer and p53 signaling pathway sets were significant at 12, 24 and 48 h. We also found that the DDB2, RRM2B and GADD45A, genes related to the repair and damage prevention of DNA, were consistently up-regulated for genotoxic carcinogens. Our results suggest that a gene set analysis could provide a robust tool in the investigation of the different mechanisms of genotoxic and non-genotoxic carcinogens and construct a more detailed understanding of the perturbation of significant pathways. PMID:24497971

Perceptual control models of pursuit manual tracking demonstrate individual specificity and parameter consistency.

PubMed

Parker, Maximilian G; Tyson, Sarah F; Weightman, Andrew P; Abbott, Bruce; Emsley, Richard; Mansell, Warren

2017-11-01

Computational models that simulate individuals' movements in pursuit-tracking tasks have been used to elucidate mechanisms of human motor control. Whilst there is evidence that individuals demonstrate idiosyncratic control-tracking strategies, it remains unclear whether models can be sensitive to these idiosyncrasies. Perceptual control theory (PCT) provides a unique model architecture with an internally set reference value parameter, and can be optimized to fit an individual's tracking behavior. The current study investigated whether PCT models could show temporal stability and individual specificity over time. Twenty adults completed three blocks of 15 1-min, pursuit-tracking trials. Two blocks (training and post-training) were completed in one session and the third was completed after 1 week (follow-up). The target moved in a one-dimensional, pseudorandom pattern. PCT models were optimized to the training data using a least-mean-squares algorithm, and validated with data from post-training and follow-up. We found significant inter-individual variability (partial η 2 : .464-.697) and intra-individual consistency (Cronbach's α: .880-.976) in parameter estimates. Polynomial regression revealed that all model parameters, including the reference value parameter, contribute to simulation accuracy. Participants' tracking performances were significantly more accurately simulated by models developed from their own tracking data than by models developed from other participants' data. We conclude that PCT models can be optimized to simulate the performance of an individual and that the test-retest reliability of individual models is a necessary criterion for evaluating computational models of human performance.

49 CFR 232.213 - Extended haul trains.

Code of Federal Regulations, 2010 CFR

2010-10-01

..., DEPARTMENT OF TRANSPORTATION BRAKE SYSTEM SAFETY STANDARDS FOR FREIGHT AND OTHER NON-PASSENGER TRAINS AND... extended haul trains will originate and a description of the trains that will be operated as extended haul.... (5) The train shall have no more than one pick-up and one set-out en route, except for the set-out of...

Choice, numeracy, and physicians-in-training performance: the case of Medicare Part D.

PubMed

Hanoch, Yaniv; Miron-Shatz, Talya; Cole, Helen; Himmelstein, Mary; Federman, Alex D

2010-07-01

In this study, we examined the effect of choice-set size and numeracy levels on a physician-in-training's ability to choose appropriate Medicare drug plans. Medical students and internal medicine residents (N = 100) were randomly assigned to 1 of 3 surveys, differing only in the number of plans to be evaluated (3, 10, and 20). After reviewing information about stand-alone Medicare prescription drug plans, participants answered questions about what plan they would advise 2 hypothetical patients to choose on the basis of a brief summary of the relevant concerns of each patient. Participants also completed an 11-item numeracy scale. Ability to answer correctly questions about hypothetical Medicare Part D insurance plans and numeracy levels. Consistent with our hypotheses, increases in choice sets correlated significantly with fewer correct answers, and higher numeracy levels were associated with more correct answers. Hence, our data further highlight the role of numeracy in financial- and health-related decision making, and also raise concerns about physicians' ability to help patients choose the optimal Part D plan. Our data indicate that even physicians-in-training perform more poorly when choice size is larger, thus raising concerns about the capacity of physicians-in-training to successfully navigate Medicare Part D and help their patients pick the best drug plan. Our results also illustrate the importance of numeracy in evaluating insurance-related information and the need for enhancing numeracy skills among medical students and physicians. PsycINFO Database Record (c) 2010 APA, all rights reserved

A Gold Standards Approach to Training Instructors to Evaluate Crew Performance

NASA Technical Reports Server (NTRS)

Baker, David P.; Dismukes, R. Key

2003-01-01

The Advanced Qualification Program requires that airlines evaluate crew performance in Line Oriented Simulation. For this evaluation to be meaningful, instructors must observe relevant crew behaviors and evaluate those behaviors consistently and accurately against standards established by the airline. The airline industry has largely settled on an approach in which instructors evaluate crew performance on a series of event sets, using standardized grade sheets on which behaviors specific to event set are listed. Typically, new instructors are given a class in which they learn to use the grade sheets and practice evaluating crew performance observed on videotapes. These classes emphasize reliability, providing detailed instruction and practice in scoring so that all instructors within a given class will give similar scores to similar performance. This approach has value but also has important limitations; (1) ratings within one class of new instructors may differ from those of other classes; (2) ratings may not be driven primarily by the specific behaviors on which the company wanted the crews to be scored; and (3) ratings may not be calibrated to company standards for level of performance skill required. In this paper we provide a method to extend the existing method of training instructors to address these three limitations. We call this method the "gold standards" approach because it uses ratings from the company's most experienced instructors as the basis for training rater accuracy. This approach ties the training to the specific behaviors on which the experienced instructors based their ratings.

Key role of staff competencies for patient and donor safety in a bone marrow transplantation unit: design and implementation of an accredited training and self-assessment program.

PubMed

Lamanna, C; Baroni, M; Bisin, S; Gianassi, S; Bambi, F; Caselli, D; Aricò, M

2010-01-01

Human resources represent at the moment the most critical factor in an hospital setting characterized by a high rate of staff turnover. It is important to ensure a consistent level of expertise and knowledge of professionals who work in health care facilities to provide quality services and simultaneously support the implementation of strategies for patient safety. Unfortunately, the development of effective interventions for training newly added staff and self-evaluation of skills possessed by trained staff are closely related to understanding critical aspects of the organization. At the new Center for Bone Marrow Transplantation and Blood Transfusion Service in Meyer Hospital, during the last year, a group of professional nurses and technicians completed a specific plan to train new staff and, at the same time, a program of self-assessment of skills for experienced staff. The main purpose of this project was to promote skills development by newly added as well as experienced staff, to identify areas of weaknesses, and to correct them with training (organized by the hospital, departmental, or individual) designed to improve performance. Copyright 2010 Elsevier Inc. All rights reserved.

Evaluation of Semi-supervised Learning for Classification of Protein Crystallization Imagery

PubMed Central

Sigdel, Madhav; Dinç, İmren; Dinç, Semih; Sigdel, Madhu S.; Pusey, Marc L.; Aygün, Ramazan S.

2015-01-01

In this paper, we investigate the performance of two wrapper methods for semi-supervised learning algorithms for classification of protein crystallization images with limited labeled images. Firstly, we evaluate the performance of semi-supervised approach using self-training with naïve Bayesian (NB) and sequential minimum optimization (SMO) as the base classifiers. The confidence values returned by these classifiers are used to select high confident predictions to be used for self-training. Secondly, we analyze the performance of Yet Another Two Stage Idea (YATSI) semi-supervised learning using NB, SMO, multilayer perceptron (MLP), J48 and random forest (RF) classifiers. These results are compared with the basic supervised learning using the same training sets. We perform our experiments on a dataset consisting of 2250 protein crystallization images for different proportions of training and test data. Our results indicate that NB and SMO using both self-training and YATSI semi-supervised approaches improve accuracies with respect to supervised learning. On the other hand, MLP, J48 and RF perform better using basic supervised learning. Overall, random forest classifier yields the best accuracy with supervised learning for our dataset. PMID:25914518

Programmatic assessment of a university-based implant training program using patient-reported outcomes.

PubMed

Al-Sabbagh, Mohanad; Jenkins, Diane W; de Leeuw, Reny; Nihill, Patricia; Robinson, Fonda G; Thomas, Mark V

2014-11-01

The University of Kentucky College of Dentistry (UKCD) established an implant training program that provides training in the use of a single implant system, evidence-based diagnostic and treatment protocols (standardized work practices), and a total quality management system (Implant Quality Assurance Program). The aim of this study was to assess the programmatic effectiveness of the UKCD implant training program by reporting the success and survival of implants placed, using patient-reported outcomes and comparing them to previously established benchmarks. A total of 415 patients (963 implants) were interviewed, approximately 50 percent of all qualified patients. The implant survival rate was 97 percent, and 88 percent of the implants were considered successful (as determined by patient-centric criteria). These outcomes were consistent with the program's previously established benchmarks of 90 percent. These results suggest that work standardization (in the form of specific treatment protocols) and the use of a formal, incremental learning system can result in positive patient outcomes. Clinical outcomes should be monitored in academic dental settings as part of clinical process improvement, and these outcomes can provide a means of assessing the effectiveness of the training program.

Evaluation of SLAR and thematic mapper MSS data for forest cover mapping using computer-aided analysis techniques

NASA Technical Reports Server (NTRS)

Hoffer, R. M. (Principal Investigator); Knowlton, D. J.; Dean, M. E.

1981-01-01

A set of training statistics for the 30 meter resolution simulated thematic mapper MSS data was generated based on land use/land cover classes. In addition to this supervised data set, a nonsupervised multicluster block of training statistics is being defined in order to compare the classification results and evaluate the effect of the different training selection methods on classification performance. Two test data sets, defined using a stratified sampling procedure incorporating a grid system with dimensions of 50 lines by 50 columns, and another set based on an analyst supervised set of test fields were used to evaluate the classifications of the TMS data. The supervised training data set generated training statistics, and a per point Gaussian maximum likelihood classification of the 1979 TMS data was obtained. The August 1980 MSS data was radiometrically adjusted. The SAR data was redigitized and the SAR imagery was qualitatively analyzed.

Child health in low-resource settings: pathways through UK paediatric training.

PubMed

Goenka, Anu; Magnus, Dan; Rehman, Tanya; Williams, Bhanu; Long, Andrew; Allen, Steve J

2013-11-01

UK doctors training in paediatrics benefit from experience of child health in low-resource settings. Institutions in low-resource settings reciprocally benefit from hosting UK trainees. A wide variety of opportunities exist for trainees working in low-resource settings including clinical work, research and the development of transferable skills in management, education and training. This article explores a range of pathways for UK trainees to develop experience in low-resource settings. It is important for trainees to start planning a robust rationale early for global child health activities via established pathways, in the interests of their own professional development as well as UK service provision. In the future, run-through paediatric training may include core elements of global child health, as well as designated 'tracks' for those wishing to develop their career in global child health further. Hands-on experience in low-resource settings is a critical component of these training initiatives.

Machine Tool Technology. Automatic Screw Machine Troubleshooting & Set-Up Training Outlines [and] Basic Operator's Skills Set List.

ERIC Educational Resources Information Center

Anoka-Hennepin Technical Coll., Minneapolis, MN.

This set of two training outlines and one basic skills set list are designed for a machine tool technology program developed during a project to retrain defense industry workers at risk of job loss or dislocation because of conversion of the defense industry. The first troubleshooting training outline lists the categories of problems that develop…

Convolutional networks for vehicle track segmentation

DOE PAGES

Quach, Tu-Thach

2017-08-19

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Virtual Reality Job Interview Training for Individuals with Psychiatric Disabilities

PubMed Central

Smith, Matthew J.; Ginger, Emily J.; Wright, Michael; Wright, Katherine; Humm, Laura Boteler; Olsen, Dale; Bell, Morris D.; Fleming, Michael F.

2014-01-01

Services are available to help support existing employment for individual with psychiatric disabilities; however, there is a gap in services targeting job interview skills that can help obtain employment. We assessed the feasibility and efficacy of Virtual Reality Job Interview Training (VR-JIT) in a randomized controlled trial. Participants were randomized to VR-JIT (n=25) or treatment as usual (TAU) (n=12) groups. VR-JIT consisted of 10 hours of simulated job interviews with a virtual character and didactic online training. Participants attended 95% of lab-based training sessions and found VR-JIT easy-to-use and felt prepared for future interviews. The VR-JIT group improved their job interview role-play performance (p<0.05) and self-confidence (p<0.05) between baseline and follow-up as compared to the TAU group. VR-JIT performance scores increased over time (R-Squared=0.65). VR-JIT demonstrated initial feasibility and efficacy at improving job interview skills and self-confidence. Future research may help clarify whether this intervention is efficacious in community-based settings. PMID:25099298

Convolutional networks for vehicle track segmentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Quach, Tu-Thach

Existing methods to detect vehicle tracks in coherent change detection images, a product of combining two synthetic aperture radar images taken at different times of the same scene, rely on simple, fast models to label track pixels. These models, however, are unable to capture natural track features such as continuity and parallelism. More powerful, but computationally expensive models can be used in offline settings. We present an approach that uses dilated convolutional networks consisting of a series of 3-by-3 convolutions to segment vehicle tracks. The design of our networks considers the fact that remote sensing applications tend to operate inmore » low power and have limited training data. As a result, we aim for small, efficient networks that can be trained end-to-end to learn natural track features entirely from limited training data. We demonstrate that our 6-layer network, trained on just 90 images, is computationally efficient and improves the F-score on a standard dataset to 0.992, up from 0.959 obtained by the current state-of-the-art method.« less

Virtual reality job interview training for individuals with psychiatric disabilities.

PubMed

Smith, Matthew J; Ginger, Emily J; Wright, Michael; Wright, Katherine; Boteler Humm, Laura; Olsen, Dale; Bell, Morris D; Fleming, Michael F

2014-09-01

Services are available to help support existing employment for individuals with psychiatric disabilities; however, there is a gap in services targeting job interview skills that can help obtain employment. We assessed the feasibility and efficacy of Virtual Reality Job Interview Training (VR-JIT) in a randomized controlled trial. Participants were randomized to VR-JIT (n = 25) or treatment-as-usual (TAU) (n = 12) groups. VR-JIT consisted of 10 hours of simulated job interviews with a virtual character and didactic online training. The participants attended 95% of laboratory-based training sessions and found VR-JIT easy to use and felt prepared for future interviews. The VR-JIT group improved their job interview role-play performance (p ≤ 0.05) and self-confidence (p ≤ 0.05) between baseline and follow-up as compared with the TAU group. VR-JIT performance scores increased over time (R = 0.65). VR-JIT demonstrated initial feasibility and efficacy at improving job interview skills and self-confidence. Future research may help clarify whether this intervention is efficacious in community-based settings.

Scalable Nearest Neighbor Algorithms for High Dimensional Data.

PubMed

Muja, Marius; Lowe, David G

2014-11-01

For many computer vision and machine learning problems, large training sets are key for good performance. However, the most computationally expensive part of many computer vision and machine learning algorithms consists of finding nearest neighbor matches to high dimensional vectors that represent the training data. We propose new algorithms for approximate nearest neighbor matching and evaluate and compare them with previous algorithms. For matching high dimensional features, we find two algorithms to be the most efficient: the randomized k-d forest and a new algorithm proposed in this paper, the priority search k-means tree. We also propose a new algorithm for matching binary features by searching multiple hierarchical clustering trees and show it outperforms methods typically used in the literature. We show that the optimal nearest neighbor algorithm and its parameters depend on the data set characteristics and describe an automated configuration procedure for finding the best algorithm to search a particular data set. In order to scale to very large data sets that would otherwise not fit in the memory of a single machine, we propose a distributed nearest neighbor matching framework that can be used with any of the algorithms described in the paper. All this research has been released as an open source library called fast library for approximate nearest neighbors (FLANN), which has been incorporated into OpenCV and is now one of the most popular libraries for nearest neighbor matching.

Random Access Memories: A New Paradigm for Target Detection in High Resolution Aerial Remote Sensing Images.

PubMed

Zou, Zhengxia; Shi, Zhenwei

2018-03-01

We propose a new paradigm for target detection in high resolution aerial remote sensing images under small target priors. Previous remote sensing target detection methods frame the detection as learning of detection model + inference of class-label and bounding-box coordinates. Instead, we formulate it from a Bayesian view that at inference stage, the detection model is adaptively updated to maximize its posterior that is determined by both training and observation. We call this paradigm "random access memories (RAM)." In this paradigm, "Memories" can be interpreted as any model distribution learned from training data and "random access" means accessing memories and randomly adjusting the model at detection phase to obtain better adaptivity to any unseen distribution of test data. By leveraging some latest detection techniques e.g., deep Convolutional Neural Networks and multi-scale anchors, experimental results on a public remote sensing target detection data set show our method outperforms several other state of the art methods. We also introduce a new data set "LEarning, VIsion and Remote sensing laboratory (LEVIR)", which is one order of magnitude larger than other data sets of this field. LEVIR consists of a large set of Google Earth images, with over 22 k images and 10 k independently labeled targets. RAM gives noticeable upgrade of accuracy (an mean average precision improvement of 1% ~ 4%) of our baseline detectors with acceptable computational overhead.

Chile: Acceptability of a Training Program for Depression Management in Primary Care

PubMed Central

Marín, Rigoberto; Martínez, Pablo; Cornejo, Juan P.; Díaz, Berta; Peralta, José; Tala, Álvaro; Rojas, Graciela

2016-01-01

Background: In Chile, there are inconsistencies in the management of depression in primary care settings, and the National Depression Program, currently in effect, was implemented without a standardized training program. The objective of this study is to evaluate the acceptability of a training program on the management of depression for primary care health teams. Methods: The study was a randomized controlled trial, and two primary centers from the Metropolitan Region of Santiago were randomly selected to carry out the intervention training program. Pre-post surveys were applied, to evaluate expectations and satisfaction with the intervention, respectively. Descriptive and content analysis was carried out. Result: The sample consisted of 41 health professionals, 56.1% of who reported that their expectations for the intervention were met. All of the training activities were evaluated with scores higher than 6.4 (on a 1–7 scale). The trainers, the methodology, and the learning environment were considered strengths and facilitators of the program, while the limited duration of the training, the logistical problems faced during part of the program, and the lack of educational material were viewed as weaknesses. Conclusion: The intervention was well accepted by primary health care teams. However, the clinical impact in patients still has to be evaluated. PMID:27375531

Nonhomogeneous transfer reveals specificity in speech motor learning.

PubMed

Rochet-Capellan, Amélie; Richer, Lara; Ostry, David J

2012-03-01

Does motor learning generalize to new situations that are not experienced during training, or is motor learning essentially specific to the training situation? In the present experiments, we use speech production as a model to investigate generalization in motor learning. We tested for generalization from training to transfer utterances by varying the acoustical similarity between these two sets of utterances. During the training phase of the experiment, subjects received auditory feedback that was altered in real time as they repeated a single consonant-vowel-consonant utterance. Different groups of subjects were trained with different consonant-vowel-consonant utterances, which differed from a subsequent transfer utterance in terms of the initial consonant or vowel. During the adaptation phase of the experiment, we observed that subjects in all groups progressively changed their speech output to compensate for the perturbation (altered auditory feedback). After learning, we tested for generalization by having all subjects produce the same single transfer utterance while receiving unaltered auditory feedback. We observed limited transfer of learning, which depended on the acoustical similarity between the training and the transfer utterances. The gradients of generalization observed here are comparable to those observed in limb movement. The present findings are consistent with the conclusion that speech learning remains specific to individual instances of learning.

Nonhomogeneous transfer reveals specificity in speech motor learning

PubMed Central

Rochet-Capellan, Amélie; Richer, Lara

2012-01-01

Does motor learning generalize to new situations that are not experienced during training, or is motor learning essentially specific to the training situation? In the present experiments, we use speech production as a model to investigate generalization in motor learning. We tested for generalization from training to transfer utterances by varying the acoustical similarity between these two sets of utterances. During the training phase of the experiment, subjects received auditory feedback that was altered in real time as they repeated a single consonant-vowel-consonant utterance. Different groups of subjects were trained with different consonant-vowel-consonant utterances, which differed from a subsequent transfer utterance in terms of the initial consonant or vowel. During the adaptation phase of the experiment, we observed that subjects in all groups progressively changed their speech output to compensate for the perturbation (altered auditory feedback). After learning, we tested for generalization by having all subjects produce the same single transfer utterance while receiving unaltered auditory feedback. We observed limited transfer of learning, which depended on the acoustical similarity between the training and the transfer utterances. The gradients of generalization observed here are comparable to those observed in limb movement. The present findings are consistent with the conclusion that speech learning remains specific to individual instances of learning. PMID:22190628

Smartphone-Based System for Learning and Inferring Hearing Aid Settings

PubMed Central

Aldaz, Gabriel; Puria, Sunil; Leifer, Larry J.

2017-01-01

Background Previous research has shown that hearing aid wearers can successfully self-train their instruments’ gain-frequency response and compression parameters in everyday situations. Combining hearing aids with a smartphone introduces additional computing power, memory, and a graphical user interface that may enable greater setting personalization. To explore the benefits of self-training with a smartphone-based hearing system, a parameter space was chosen with four possible combinations of microphone mode (omnidirectional and directional) and noise reduction state (active and off). The baseline for comparison was the “untrained system,” that is, the manufacturer’s algorithm for automatically selecting microphone mode and noise reduction state based on acoustic environment. The “trained system” first learned each individual’s preferences, self-entered via a smartphone in real-world situations, to build a trained model. The system then predicted the optimal setting (among available choices) using an inference engine, which considered the trained model and current context (e.g., sound environment, location, and time). Purpose To develop a smartphone-based prototype hearing system that can be trained to learn preferred user settings. Determine whether user study participants showed a preference for trained over untrained system settings. Research Design An experimental within-participants study. Participants used a prototype hearing system—comprising two hearing aids, Android smartphone, and body-worn gateway device—for ~6 weeks. Study Sample Sixteen adults with mild-to-moderate sensorineural hearing loss (HL) (ten males, six females; mean age = 55.5 yr). Fifteen had ≥6 mo of experience wearing hearing aids, and 14 had previous experience using smartphones. Intervention Participants were fitted and instructed to perform daily comparisons of settings (“listening evaluations”) through a smartphone-based software application called Hearing Aid Learning and Inference Controller (HALIC). In the four-week-long training phase, HALIC recorded individual listening preferences along with sensor data from the smartphone—including environmental sound classification, sound level, and location—to build trained models. In the subsequent two-week-long validation phase, participants performed blinded listening evaluations comparing settings predicted by the trained system (“trained settings”) to those suggested by the hearing aids’ untrained system (“untrained settings”). Data Collection and Analysis We analyzed data collected on the smartphone and hearing aids during the study. We also obtained audiometric and demographic information. Results Overall, the 15 participants with valid data significantly preferred trained settings to untrained settings (paired-samples t test). Seven participants had a significant preference for trained settings, while one had a significant preference for untrained settings (binomial test). The remaining seven participants had nonsignificant preferences. Pooling data across participants, the proportion of times that each setting was chosen in a given environmental sound class was on average very similar. However, breaking down the data by participant revealed strong and idiosyncratic individual preferences. Fourteen participants reported positive feelings of clarity, competence, and mastery when training via HALIC. Conclusions The obtained data, as well as subjective participant feedback, indicate that smartphones could become viable tools to train hearing aids. Individuals who are tech savvy and have milder HL seem well suited to take advantages of the benefits offered by training with a smartphone. PMID:27718350

At-home resistance tubing strength training increases shoulder strength in the trained and untrained limb.

PubMed

Magnus, C R A; Boychuk, K; Kim, S Y; Farthing, J P

2014-06-01

The purpose was to determine if an at-home resistance tubing strength training program on one shoulder (that is commonly used in rehabilitation settings) would produce increases in strength in the trained and untrained shoulders via cross-education. Twenty-three participants were randomized to TRAIN (strength-trained one shoulder; n = 13) or CONTROL (no intervention; n = 10). Strength training was completed at home using resistance tubing and consisted of maximal shoulder external rotation, internal rotation, scaption, retraction, and flexion 3 days/week for 4 weeks. Strength was measured via handheld dynamometry and muscle size measured via ultrasound. For external rotation strength, the trained (10.9 ± 10.9%) and untrained (12.7 ± 9.6%) arm of TRAIN was significantly different than CONTROL (1.6 ± 13.2%; -2.7 ± 12.3%; pooled across arm; P < 0.05). For internal rotation strength, the trained (14.8 ± 11.3%) and untrained (14.6 ± 10.1%) arm of TRAIN was significantly different than CONTROL (6.4 ± 11.2%; 5.1 ± 8.8%; pooled across arm; P < 0.05). There were no significant differences for scaption strength (P = 0.056). TRAIN significantly increased muscle size in the training arm of the supraspinatus (1.90 ± 0.32 to 1.99 ± 0.31 cm), and the anterior deltoid (1.08 ± 0.37 to 1.21 ± 0.39 cm; P < 0.05). This study suggests that an at-home resistance tubing training program on one limb can produce increases in strength in both limbs, and has implications for rehabilitation after unilateral shoulder injuries. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

"Geo-statistics methods and neural networks in geophysical applications: A case study"

NASA Astrophysics Data System (ADS)

Rodriguez Sandoval, R.; Urrutia Fucugauchi, J.; Ramirez Cruz, L. C.

2008-12-01

The study is focus in the Ebano-Panuco basin of northeastern Mexico, which is being explored for hydrocarbon reservoirs. These reservoirs are in limestones and there is interest in determining porosity and permeability in the carbonate sequences. The porosity maps presented in this study are estimated from application of multiattribute and neural networks techniques, which combine geophysics logs and 3-D seismic data by means of statistical relationships. The multiattribute analysis is a process to predict a volume of any underground petrophysical measurement from well-log and seismic data. The data consist of a series of target logs from wells which tie a 3-D seismic volume. The target logs are neutron porosity logs. From the 3-D seismic volume a series of sample attributes is calculated. The objective of this study is to derive a set of attributes and the target log values. The selected set is determined by a process of forward stepwise regression. The analysis can be linear or nonlinear. In the linear mode the method consists of a series of weights derived by least-square minimization. In the nonlinear mode, a neural network is trained using the select attributes as inputs. In this case we used a probabilistic neural network PNN. The method is applied to a real data set from PEMEX. For better reservoir characterization the porosity distribution was estimated using both techniques. The case shown a continues improvement in the prediction of the porosity from the multiattribute to the neural network analysis. The improvement is in the training and the validation, which are important indicators of the reliability of the results. The neural network showed an improvement in resolution over the multiattribute analysis. The final maps provide more realistic results of the porosity distribution.

Probabilistic pharmacokinetic models of decompression sickness in humans, part 1: Coupled perfusion-limited compartments.

PubMed

Murphy, F Gregory; Hada, Ethan A; Doolette, David J; Howle, Laurens E

2017-07-01

Decompression sickness (DCS) is a disease caused by gas bubbles forming in body tissues following a reduction in ambient pressure, such as occurs in scuba diving. Probabilistic models for quantifying the risk of DCS are typically composed of a collection of independent, perfusion-limited theoretical tissue compartments which describe gas content or bubble volume within these compartments. It has been previously shown that 'pharmacokinetic' gas content models, with compartments coupled in series, show promise as predictors of the incidence of DCS. The mechanism of coupling can be through perfusion or diffusion. This work examines the application of five novel pharmacokinetic structures with compartments coupled by perfusion to the prediction of the probability and time of onset of DCS in humans. We optimize these models against a training set of human dive trial data consisting of 4335 exposures with 223 DCS cases. Further, we examine the extrapolation quality of the models on an additional set of human dive trial data consisting of 3140 exposures with 147 DCS cases. We find that pharmacokinetic models describe the incidence of DCS for single air bounce dives better than a single-compartment, perfusion-limited model. We further find the U.S. Navy LEM-NMRI98 is a better predictor of DCS risk for the entire training set than any of our pharmacokinetic models. However, one of the pharmacokinetic models we consider, the CS2T3 model, is a better predictor of DCS risk for single air bounce dives and oxygen decompression dives. Additionally, we find that LEM-NMRI98 outperforms CS2T3 on the extrapolation data. Copyright © 2017 Elsevier Ltd. All rights reserved.

Issues in the Development and Evaluation of Cross-Cultural Training in a Business Setting.

ERIC Educational Resources Information Center

Broadbooks, Wendy J.

Issues in the development and evaluation of cross-cultural training in a business setting were investigated. Cross-cultural training and cross-cultural evaluation were defined as training and evaluation of training that involve the interaction of participants from two or more different countries. Two evaluations of a management development-type…

Bridging the Gap: Supporting Translational Research Careers Through an Integrated Research Track Within Residency Training

PubMed Central

Arbuckle, Melissa R.; Gordon, Joshua A.; Pincus, Harold A.; Oquendo, Maria A.

2013-01-01

In the setting of traditional residency training programs, physician–scientists are often limited in their ability to pursue research training goals while meeting clinical training requirements. This creates a gap in research training at a critical developmental stage. In response, Columbia University Medical Center’s Department of Psychiatry, in partnership with the New York State Psychiatric Institute, has created a formal Research Track Program (RTP) for psychiatry residents so that interested individuals can maintain their attention on research training during formative residency years. Clinical and research training are integrated through core clinical rotations on research units. With protected research time and clear developmental milestones for each year of training, the RTP allows research track residents to meet both clinical and research training goals while maintaining a healthy work–life balance. In coordination with existing postdoctoral research fellowship programs, research track residents can effectively jump-start fellowship training with advanced course work and consistent, continuous mentorship bridging residency and fellowship years. A key element of the program is its provision of core training in research literacy and extensive research opportunities for all residents, stimulating research interest across the whole residency program. Supported by the National Institutes of Health and a private foundation, this RTP capitalizes on a unique academic–private partnership to address many of the challenges facing physician–scientists. By integrating clinical and research exposures and offering protected research time, careful mentoring, and financial resources, the program aims to further the development of those most poised to establish careers in translational research. PMID:23619070

Exercise Training and Energy Expenditure following Weight Loss

PubMed Central

Hunter, Gary R.; Fisher, Gordon; Neumeier, William H.; Carter, Stephen J.; Plaisance, Eric P.

2015-01-01

Purpose Determine the effects of aerobic or resistance training on activity related energy expenditure (AEE, kcal/d) and physical activity index (ARTE) following weight loss. It was hypothesized that weight loss without exercise training would be accompanied by a decrease in AEE, ARTE, and non-training physical activity energy expenditure (NEAT) and that exercise training would prevent decreases in free living energy expenditure. Methods 140 pre-menopausal women underwent an average of 25 pound weight loss during an 800 kcal/day diet of furnished food. One group aerobically trained 3 times/wk (40 min/d), another resistance trained 3 times/wk (10 exercises/2 sets x10 repetitions) and the third group did not exercise. DXA was used to measure body composition, indirect calorimetry to measure resting (REE) and walking energy expenditure, and doubly labeled water to measure total energy expenditure (TEE). AEE, ARTE, and non-training physical activity energy expenditure (NEAT) were calculated. Results TEE, REE, and NEAT all decreased following weight loss for the no exercise group, but not for the aerobic and resistance trainers. Only REE decreased in the two exercise groups. The resistance trainers increased ARTE. Heart rate and oxygen uptake while walking on the flat and up a grade were consistently related to TEE, AEE, NEAT, and ARTE. Conclusion Exercise training prevents a decrease in energy expenditure, including free living energy expenditure separate from the exercise training, following weight loss. Resistance training increased physical activity, while ease and economy in walking associates with increased TEE, AEE, NEAT, and ARTE. PMID:25606816

Preparations for a train-to-train impact test of crash-energy management passenger rail equipment

DOT National Transportation Integrated Search

2005-03-16

Preparations are ongoing for a full-scale train-to-train : impact test of crash-energy management (CEM) equipment, : during which a cab car-led passenger consist, initially moving : at 30 mph, will impact a standing locomotive-led consist. The : coll...

An algebraic method for constructing stable and consistent autoregressive filters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harlim, John, E-mail: jharlim@psu.edu; Department of Meteorology, the Pennsylvania State University, University Park, PA 16802; Hong, Hoon, E-mail: hong@ncsu.edu

2015-02-15

In this paper, we introduce an algebraic method to construct stable and consistent univariate autoregressive (AR) models of low order for filtering and predicting nonlinear turbulent signals with memory depth. By stable, we refer to the classical stability condition for the AR model. By consistent, we refer to the classical consistency constraints of Adams–Bashforth methods of order-two. One attractive feature of this algebraic method is that the model parameters can be obtained without directly knowing any training data set as opposed to many standard, regression-based parameterization methods. It takes only long-time average statistics as inputs. The proposed method provides amore » discretization time step interval which guarantees the existence of stable and consistent AR model and simultaneously produces the parameters for the AR models. In our numerical examples with two chaotic time series with different characteristics of decaying time scales, we find that the proposed AR models produce significantly more accurate short-term predictive skill and comparable filtering skill relative to the linear regression-based AR models. These encouraging results are robust across wide ranges of discretization times, observation times, and observation noise variances. Finally, we also find that the proposed model produces an improved short-time prediction relative to the linear regression-based AR-models in forecasting a data set that characterizes the variability of the Madden–Julian Oscillation, a dominant tropical atmospheric wave pattern.« less

Fall hazard control observed on residential construction sites.

PubMed

Kaskutas, Vicki; Dale, Ann Marie; Nolan, James; Patterson, Dennis; Lipscomb, Hester J; Evanoff, Bradley

2009-06-01

Falls are a leading cause of mortality and morbidity in the construction industry. This study measured fall hazards at residential construction sites. Trained carpenters administered the St. Louis Audit of Fall Risks and interviewed carpenters. The prevalence of fall prevention practices meeting safety criteria was counted and correlations explored. We identified a high prevalence of fall hazards at the 197 residential sites audited. Roof sheathing met safety criteria most consistently (81%) and truss setting least consistently (28%). Use of personal fall arrest and monitoring of unguarded floor openings were rare. Safer performance on several scales was correlated. Construction sites of large-sized contractors were generally safer than smaller contractors. Apprentice carpenters were less familiar with their employers' fall prevention plan than experienced workers. Safety could be improved with consistent use of recognized fall prevention practices at residential construction sites.

Effects of different duration isometric contractions on tendon elasticity in human quadriceps muscles

PubMed Central

Kubo, Keitaro; Kanehisa, Hiroaki; Fukunaga, Tetsuo

2001-01-01

The present study aimed to investigate the influence of isometric training protocols with long- and short-duration contractions on the elasticity of human tendon structures in vivo. The elasticity was assessed through in vivo determination of the elongation (L) of the tendons and aponeuroses using ultrasonography, while the subjects performed ramp isometric exercise up to maximum voluntary contraction (MVC).Eight young males completed 12 weeks (4 days per week) of a unilateral isometric training programme on knee extensors, which consisted of two different combinations of contraction and relaxation times at 70 % MVC: one leg was trained using a short-duration protocol (3 sets of 50 repetitions of contraction for 1 s and relaxation for 2 s), and the other leg was trained using a long-duration protocol (4 sets of a combination of contraction for 20 s and relaxation for 1 min). The training volume per session, expressed as the integrated torque, was the same for the two protocols.Both protocols resulted in a significant increase in MVC: 31.8 ± 17.2 % for the short-duration protocol and 33.9 ± 14.4 % for the long-duration protocol. Moreover, the training produced significant increases in the muscle volume of the constituents of the quadriceps femoris, with similar relative gains for the two protocols: 7.4 ± 3.9 % for the short-duration protocol and 7.6 ± 4.3 % for the long-duration protocol.The short-duration protocol produced no significant change in L values at any of the force production levels. For the long-duration protocol, however, the L values above 550 N were significantly shorter after training. Analysis revealed that the group × test time interaction effect on tendon stiffness was significant. Stiffness increased significantly for the long-duration protocol, but not for the short-duration protocol.The present study demonstrates a greater increase in stiffness of human tendon structures following isometric training using longer duration contractions compared to shorter contractions. This suggests that the changes in the elasticity of the tendon structures after resistance training may be affected by the duration of muscle contraction. PMID:11600697

Structural similarity based kriging for quantitative structure activity and property relationship modeling.

PubMed

Teixeira, Ana L; Falcao, Andre O

2014-07-28

Structurally similar molecules tend to have similar properties, i.e. closer molecules in the molecular space are more likely to yield similar property values while distant molecules are more likely to yield different values. Based on this principle, we propose the use of a new method that takes into account the high dimensionality of the molecular space, predicting chemical, physical, or biological properties based on the most similar compounds with measured properties. This methodology uses ordinary kriging coupled with three different molecular similarity approaches (based on molecular descriptors, fingerprints, and atom matching) which creates an interpolation map over the molecular space that is capable of predicting properties/activities for diverse chemical data sets. The proposed method was tested in two data sets of diverse chemical compounds collected from the literature and preprocessed. One of the data sets contained dihydrofolate reductase inhibition activity data, and the second molecules for which aqueous solubility was known. The overall predictive results using kriging for both data sets comply with the results obtained in the literature using typical QSPR/QSAR approaches. However, the procedure did not involve any type of descriptor selection or even minimal information about each problem, suggesting that this approach is directly applicable to a large spectrum of problems in QSAR/QSPR. Furthermore, the predictive results improve significantly with the similarity threshold between the training and testing compounds, allowing the definition of a confidence threshold of similarity and error estimation for each case inferred. The use of kriging for interpolation over the molecular metric space is independent of the training data set size, and no reparametrizations are necessary when more compounds are added or removed from the set, and increasing the size of the database will consequentially improve the quality of the estimations. Finally it is shown that this model can be used for checking the consistency of measured data and for guiding an extension of the training set by determining the regions of the molecular space for which new experimental measurements could be used to maximize the model's predictive performance.

Optimization of genomic selection training populations with a genetic algorithm

USDA-ARS?s Scientific Manuscript database

In this article, we derive a computationally efficient statistic to measure the reliability of estimates of genetic breeding values for a fixed set of genotypes based on a given training set of genotypes and phenotypes. We adopt a genetic algorithm scheme to find a training set of certain size from ...

Assessment of tautomer distribution using the condensed reaction graph approach

NASA Astrophysics Data System (ADS)

Gimadiev, T. R.; Madzhidov, T. I.; Nugmanov, R. I.; Baskin, I. I.; Antipin, I. S.; Varnek, A.

2018-03-01

We report the first direct QSPR modeling of equilibrium constants of tautomeric transformations (logK T ) in different solvents and at different temperatures, which do not require intermediate assessment of acidity (basicity) constants for all tautomeric forms. The key step of the modeling consisted in the merging of two tautomers in one sole molecular graph ("condensed reaction graph") which enables to compute molecular descriptors characterizing entire equilibrium. The support vector regression method was used to build the models. The training set consisted of 785 transformations belonging to 11 types of tautomeric reactions with equilibrium constants measured in different solvents and at different temperatures. The models obtained perform well both in cross-validation (Q2 = 0.81 RMSE = 0.7 logK T units) and on two external test sets. Benchmarking studies demonstrate that our models outperform results obtained with DFT B3LYP/6-311 ++ G(d,p) and ChemAxon Tautomerizer applicable only in water at room temperature.

Effects of strongman training on salivary testosterone levels in a sample of trained men.

PubMed

Ghigiarelli, Jamie J; Sell, Katie M; Raddock, Jessica M; Taveras, Kurt

2013-03-01

Strongman exercises consist of multi-joint movements that incorporate large muscle mass groups and impose a substantial amount of neuromuscular stress. The purpose of this study was to examine salivary testosterone responses from 2 novel strongman training (ST) protocols in comparison with an established hypertrophic (H) protocol reported to acutely elevate testosterone levels. Sixteen men (24 ± 4.4 years, 181.2 ± 6.8 cm, and 95.3 ± 20.3 kg) volunteered to participate in this study. Subjects completed 3 protocols designed to ensure equal total volume (sets and repetitions), rest period, and intensity between the groups. Exercise sets were performed to failure. Exercise selection and intensity (3 sets × 10 repetitions at 75% 1 repetition maximum) were chosen as they reflected commonly prescribed resistance exercise protocols recognized to elicit a large acute hormonal response. In each of the protocols, subjects were required to perform 3 sets to muscle failure of 5 different exercises (tire flip, chain drag, farmers walk, keg carry, and atlas stone lift) with a 2-minute rest interval between sets and a 3-minute rest interval between exercises. Saliva samples were collected pre-exercise (PRE), immediate postexercise (PST), and 30 minutes postexercise (30PST). Delta scores indicated a significant difference between PRE and PST testosterone level within each group (p ≤ 0.05), with no significant difference between the groups. Testosterone levels spiked 136% (225.23 ± 148.01 pg·ml(-1)) for the H group, 74% (132.04 ± 98.09 pg·ml(-1)) for the ST group, and 54% (122.10 ± 140.67 pg·ml) for the mixed strongman/hypertrophy (XST) group. A significant difference for testosterone level occurred over time (PST to 30PST) for the H group p ≤ 0.05. In conclusion, ST elicits an acute endocrine response similar to a recognized H protocol when equated for duration and exercise intensity.

Training a whole-book LSTM-based recognizer with an optimal training set

NASA Astrophysics Data System (ADS)

Soheili, Mohammad Reza; Yousefi, Mohammad Reza; Kabir, Ehsanollah; Stricker, Didier

2018-04-01

Despite the recent progress in OCR technologies, whole-book recognition, is still a challenging task, in particular in case of old and historical books, that the unknown font faces or low quality of paper and print contributes to the challenge. Therefore, pre-trained recognizers and generic methods do not usually perform up to required standards, and usually the performance degrades for larger scale recognition tasks, such as of a book. Such reportedly low error-rate methods turn out to require a great deal of manual correction. Generally, such methodologies do not make effective use of concepts such redundancy in whole-book recognition. In this work, we propose to train Long Short Term Memory (LSTM) networks on a minimal training set obtained from the book to be recognized. We show that clustering all the sub-words in the book, and using the sub-word cluster centers as the training set for the LSTM network, we can train models that outperform any identical network that is trained with randomly selected pages of the book. In our experiments, we also show that although the sub-word cluster centers are equivalent to about 8 pages of text for a 101- page book, a LSTM network trained on such a set performs competitively compared to an identical network that is trained on a set of 60 randomly selected pages of the book.

Rehabilitation (exercise and strength training) and osteoarthritis: A critical narrative review.

PubMed

Nguyen, Christelle; Lefèvre-Colau, Marie-Martine; Poiraudeau, Serge; Rannou, François

2016-06-01

Rehabilitation is widely recommended in national and international guidelines for managing osteoarthritis (OA) in primary care settings. According to the 2014 OA Research Society International (OARSI) recommendations, rehabilitation is even considered the core treatment of OA and is recommended for all patients. Rehabilitation for OA widely includes land- and water-based exercise, strength training, weight management, self-management and education, biomechanical interventions, and physically active lifestyle. We performed a critical narrative review of the efficacy and safety of rehabilitation for managing OA and discuss evidence-based international recommendations. The process of article selection was unsystematic. Articles were selected based on authors' expertise, self-knowledge, and reflective practice. For the purpose of the review, we focused on land- and water-based exercise and strength training for knee, hip and hand OA. Other aspects of rehabilitation in OA are treated elsewhere in this special issue. Exercise therapy is widely recommended for managing knee, hip and hand OA. However, the level of evidence varies according to OA location. Overall, consistent evidence suggests that exercise therapy and specific strengthening exercise or strength training for the lower limb reduce pain and improve physical function in knee OA. Evidence for other OA sites are less consistent. Therefore, because of the lack of specific studies, recommendations for hip and hand OA are mainly derived from studies of knee OA. In addition, no recommendations have been established regarding the exercise regimen. The efficacy and safety of exercise therapy and strength training need to be further evaluated in randomized controlled trials of patients with hip and hand OA. The optimal delivery of exercise programs also has to be more clearly defined. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

The effects of varying resistance-training loads on intermediate- and high-velocity-specific adaptations.

PubMed

Jones, K; Bishop, P; Hunter, G; Fleisig, G

2001-08-01

The purpose of this study was to compare changes in velocity-specific adaptations in moderately resistance-trained athletes who trained with either low or high resistances. The study used tests of sport-specific skills across an intermediate- to high-velocity spectrum. Thirty NCAA Division I baseball players were randomly assigned to either a low-resistance (40-60% 1 repetition maximum [1RM]) training group or a high-resistance (70-90% 1RM) training group. Both of the training groups intended to maximallv accelerate each repetition during the concentric phase (IMCA). The 10 weeks of training consisted of 4 training sessions a week using basic core exercises. Peak force, velocity, and power were evaluated during set angle and depth jumps as well as weighted jumps using 30 and 50% 1RM. Squat 1RMs were also tested. Although no interactions for any of the jump tests were found, trends supported the hypothesis of velocity-specific training. Percentage gains suggest that the combined use of heavier training loads (70-90% 1RM) and IMCA tend to increase peak force in the lower-body leg and hip extensors. Trends also show that the combined use of lighter training loads (40-60% 1RM) and IMCA tend to increase peak power and peak velocity in the lower-body leg and hip extensors. The high-resistance group improved squats more than the low-resistance group (p < 0.05; +22.7 vs. + 16.1 kg). The results of this study support the use of a combination of heavier training loads and IMCA to increase 1RM strength in the lower bodies of resistance-trained athletes.

Physiological Responses to On-Court vs Running Interval Training in Competitive Tennis Players

PubMed Central

Fernandez-Fernandez, Jaime; Sanz-Rivas, David; Sanchez-Muñoz, Cristobal; de la Aleja Tellez, Jose Gonzalez; Buchheit, Martin; Mendez-Villanueva, Alberto

2011-01-01

The aim of this study was to compare heart rate (HR), blood lactate (LA) and rate of perceived exertion (RPE) responses to a tennis-specific interval training (i.e., on-court) session with that of a matched-on-time running interval training (i.e., off-court). Eight well-trained, male (n = 4) and female (n = 4) tennis players (mean ± SD; age: 16.4 ± 1.8 years) underwent an incremental test where peak treadmill speed, maximum HR (HRmax) and maximum oxygen uptake (VO2max) were determined. The two interval training protocols (i.e., off- court and on-court) consisted of 4 sets of 120 s of work, interspersed with 90 s rest. Percentage of HRmax (95.9 ± 2.4 vs. 96.1 ± 2.2%; p = 0.79), LA (6.9 ± 2.5 vs. 6.2 ± 2.4 mmol·L-1; p = 0.14) and RPE (16.7 ± 2.1 vs. 16.3 ± 1.8; p = 0.50) responses were similar for off-court and on-court, respectively. The two interval training protocols used in the present study have equivalent physiological responses. Longitudinal studies are still warranted but tennis-specific interval training sessions could represent a time-efficient alternative to off-court (running) interval training for the optimization of the specific cardiorespiratory fitness in tennis players. Key points On-court interval training protocol can be used as an alternative to running interval training Technical/tactical training should be performed under conditions that replicate the physical and technical demands of a competitive match During the competitive season tennis on-court training might be preferred to off-court training PMID:24150630

Development and assessment of users' satisfaction with the systemic lupus erythematosus disease activity index 2000 responder index-50 website.

PubMed

Touma, Zahi; Gladman, Dafna D; MacKinnon, Anne; Carette, Simon; Abu-Shakra, Mahmoud; Askanase, Anca; Nived, Ola; Hanly, John G; Landolt-Marticorena, Carolina; Tam, Lai-Shan; Toloza, Sergio; Nikpour, Mandana; Riddell, Claire; Steiman, Amanda; Eder, Lihi; Haddad, Amir; Barber, Claire; Urowitz, Murray B

2013-01-01

To describe the development of the Systemic Lupus Erythematosus Disease Activity Index 2000 Responder Index-50 (S2K RI-50) Website (www.s2k-ri-50.com) and to assess satisfaction with its training and examination modules among rheumatologists and rheumatology fellows. The development of the Website occurred in 3 phases. The first was a deployment phase that consisted of preparing the site map along with its content. The content included the S2K RI-50 training manual, the tests and corresponding question bank, and the online adaptive training module, along with the extensive site testing. The second phase included the participation of rheumatologists and trainees who completed the Website modules. The third was a quality assurance phase in which an online survey was developed to determine the satisfaction level of its users. Further modifications were implemented per participants' recommendations. The site has been online since it was registered in September 2010. Fourteen rheumatologists and rheumatology trainees from different centers reviewed and completed the material contained in the Website. The survey revealed acceptance among rheumatologists for the Website's content, design, and presentation. The Website was rated as user-friendly and useful in familiarizing investigators with the S2K RI-50. After completion of the training and examination modules, participants reported a suitable level of preparation to implement the S2K RI-50 in clinical trials and research settings in a timely manner. The Website includes training and examination modules that familiarize rheumatologists with the S2K RI-50 and assesses their competence to use the index. This prepares them for the use of the S2K RI-50 in clinical trials and research settings.

Predicting hydrofacies and hydraulic conductivity from direct-push data using a data-driven relevance vector machine approach: Motivations, algorithms, and application

NASA Astrophysics Data System (ADS)

Paradis, Daniel; Lefebvre, René; Gloaguen, Erwan; Rivera, Alfonso

2015-01-01

The spatial heterogeneity of hydraulic conductivity (K) exerts a major control on groundwater flow and solute transport. The heterogeneous spatial distribution of K can be imaged using indirect geophysical data as long as reliable relations exist to link geophysical data to K. This paper presents a nonparametric learning machine approach to predict aquifer K from cone penetrometer tests (CPT) coupled with a soil moisture and resistivity probe (SMR) using relevance vector machines (RVMs). The learning machine approach is demonstrated with an application to a heterogeneous unconsolidated littoral aquifer in a 12 km2 subwatershed, where relations between K and multiparameters CPT/SMR soundings appear complex. Our approach involved fuzzy clustering to define hydrofacies (HF) on the basis of CPT/SMR and K data prior to the training of RVMs for HFs recognition and K prediction on the basis of CPT/SMR data alone. The learning machine was built from a colocated training data set representative of the study area that includes K data from slug tests and CPT/SMR data up-scaled at a common vertical resolution of 15 cm with K data. After training, the predictive capabilities of the learning machine were assessed through cross validation with data withheld from the training data set and with K data from flowmeter tests not used during the training process. Results show that HF and K predictions from the learning machine are consistent with hydraulic tests. The combined use of CPT/SMR data and RVM-based learning machine proved to be powerful and efficient for the characterization of high-resolution K heterogeneity for unconsolidated aquifers.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

PubMed Central

Hartwell, Matthew J.; Özbek, Umut; Holler, Ernst; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J.; Ayuk, Francis; Efebera, Yvonne A.; Hexner, Elizabeth O.; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Chen, Yi-Bin; Devine, Steven; Jagasia, Madan; Kitko, Carrie L.; Litzow, Mark R.; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Yanik, Gregory A.; Levine, John E.; Ferrara, James L.M.

2017-01-01

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set (n = 309) and validation set (n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group (P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation. PMID:28194439

The effectiveness of three sets of school-based instructional materials and community training on the acquisition and generalization of community laundry skills by students with severe handicaps.

PubMed

Morrow, S A; Bates, P E

1987-01-01

This study examined the effectiveness of three sets of school-based instructional materials and community training on acquisition and generalization of a community laundry skill by nine students with severe handicaps. School-based instruction involved artificial materials (pictures), simulated materials (cardboard replica of a community washing machine), and natural materials (modified home model washing machine). Generalization assessments were conducted at two different community laundromats, on two machines represented fully by the school-based instructional materials and two machines not represented fully by these materials. After three phases of school-based instruction, the students were provided ten community training trials in one laundromat setting and a final assessment was conducted in both the trained and untrained community settings. A multiple probe design across students was used to evaluate the effectiveness of the three types of school instruction and community training. After systematic training, most of the students increased their laundry performance with all three sets of school-based materials; however, generalization of these acquired skills was limited in the two community settings. Direct training in one of the community settings resulted in more efficient acquisition of the laundry skills and enhanced generalization to the untrained laundromat setting for most of the students. Results of this study are discussed in regard to the issue of school versus community-based instruction and recommendations are made for future research in this area.

The Effects of Transfer in Teaching Vocabulary to School Children: An Analysis of the Dependencies between Lists of Trained and Non-Trained Words

ERIC Educational Resources Information Center

Frost, Jørgen; Ottem, Ernst; Hagtvet, Bente E.; Snow, Catherine E.

2016-01-01

In the present study, 81 Norwegian students were taught the meaning of words by the Word Generation (WG) method and 51 Norwegian students were taught by an approach inspired by the Thinking Schools (TS) concept. Two sets of words were used: a set of words to be trained and a set of non-trained control words. The two teaching methods yielded no…

Preventing a Relapse or Setting Goals? Elucidating the Impact of Post-Training Transfer Interventions on Training Transfer Performance

ERIC Educational Resources Information Center

Rahyuda, Agoes Ganesha; Soltani, Ebrahim; Syed, Jawad

2018-01-01

Based on a review of the literature on post-training transfer interventions, this paper offers a conceptual model that elucidates potential mechanisms through which two types of post-training transfer intervention (relapse prevention and proximal plus distal goal setting) influence the transfer of training. We explain how the application of…

Including crystal structure attributes in machine learning models of formation energies via Voronoi tessellations

NASA Astrophysics Data System (ADS)

Ward, Logan; Liu, Ruoqian; Krishna, Amar; Hegde, Vinay I.; Agrawal, Ankit; Choudhary, Alok; Wolverton, Chris

2017-07-01

While high-throughput density functional theory (DFT) has become a prevalent tool for materials discovery, it is limited by the relatively large computational cost. In this paper, we explore using DFT data from high-throughput calculations to create faster, surrogate models with machine learning (ML) that can be used to guide new searches. Our method works by using decision tree models to map DFT-calculated formation enthalpies to a set of attributes consisting of two distinct types: (i) composition-dependent attributes of elemental properties (as have been used in previous ML models of DFT formation energies), combined with (ii) attributes derived from the Voronoi tessellation of the compound's crystal structure. The ML models created using this method have half the cross-validation error and similar training and evaluation speeds to models created with the Coulomb matrix and partial radial distribution function methods. For a dataset of 435 000 formation energies taken from the Open Quantum Materials Database (OQMD), our model achieves a mean absolute error of 80 meV/atom in cross validation, which is lower than the approximate error between DFT-computed and experimentally measured formation enthalpies and below 15% of the mean absolute deviation of the training set. We also demonstrate that our method can accurately estimate the formation energy of materials outside of the training set and be used to identify materials with especially large formation enthalpies. We propose that our models can be used to accelerate the discovery of new materials by identifying the most promising materials to study with DFT at little additional computational cost.

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

Automatic Lung-RADS™ classification with a natural language processing system.

PubMed

Beyer, Sebastian E; McKee, Brady J; Regis, Shawn M; McKee, Andrea B; Flacke, Sebastian; El Saadawi, Gilan; Wald, Christoph

2017-09-01

Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines ® . All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used.

Automatic Lung-RADS™ classification with a natural language processing system

PubMed Central

Beyer, Sebastian E.; Regis, Shawn M.; McKee, Andrea B.; Flacke, Sebastian; El Saadawi, Gilan; Wald, Christoph

2017-01-01

Background Our aim was to train a natural language processing (NLP) algorithm to capture imaging characteristics of lung nodules reported in a structured CT report and suggest the applicable Lung-RADS™ (LR) category. Methods Our study included structured, clinical reports of consecutive CT lung screening (CTLS) exams performed from 08/2014 to 08/2015 at an ACR accredited Lung Cancer Screening Center. All patients screened were at high-risk for lung cancer according to the NCCN Guidelines®. All exams were interpreted by one of three radiologists credentialed to read CTLS exams using LR using a standard reporting template. Training and test sets consisted of consecutive exams. Lung screening exams were divided into two groups: three training sets (500, 120, and 383 reports each) and one final evaluation set (498 reports). NLP algorithm results were compared with the gold standard of LR category assigned by the radiologist. Results The sensitivity/specificity of the NLP algorithm to correctly assign LR categories for suspicious nodules (LR 4) and positive nodules (LR 3/4) were 74.1%/98.6% and 75.0%/98.8% respectively. The majority of mismatches occurred in cases where pulmonary findings were present not currently addressed by LR. Misclassifications also resulted from the failure to identify exams as follow-up and the failure to completely characterize part-solid nodules. In a sub-group analysis among structured reports with standardized language, the sensitivity and specificity to detect LR 4 nodules were 87.0% and 99.5%, respectively. Conclusions An NLP system can accurately suggest the appropriate LR category from CTLS exam findings when standardized reporting is used. PMID:29221286

Collaborative Supervised Learning for Sensor Networks

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Rebbapragada, Umaa; Lane, Terran

2011-01-01

Collaboration methods for distributed machine-learning algorithms involve the specification of communication protocols for the learners, which can query other learners and/or broadcast their findings preemptively. Each learner incorporates information from its neighbors into its own training set, and they are thereby able to bootstrap each other to higher performance. Each learner resides at a different node in the sensor network and makes observations (collects data) independently of the other learners. After being seeded with an initial labeled training set, each learner proceeds to learn in an iterative fashion. New data is collected and classified. The learner can then either broadcast its most confident classifications for use by other learners, or can query neighbors for their classifications of its least confident items. As such, collaborative learning combines elements of both passive (broadcast) and active (query) learning. It also uses ideas from ensemble learning to combine the multiple responses to a given query into a single useful label. This approach has been evaluated against current non-collaborative alternatives, including training a single classifier and deploying it at all nodes with no further learning possible, and permitting learners to learn from their own most confident judgments, absent interaction with their neighbors. On several data sets, it has been consistently found that active collaboration is the best strategy for a distributed learner network. The main advantages include the ability for learning to take place autonomously by collaboration rather than by requiring intervention from an oracle (usually human), and also the ability to learn in a distributed environment, permitting decisions to be made in situ and to yield faster response time.

Comparison of molecular breeding values based on within- and across-breed training in beef cattle.

PubMed

Kachman, Stephen D; Spangler, Matthew L; Bennett, Gary L; Hanford, Kathryn J; Kuehn, Larry A; Snelling, Warren M; Thallman, R Mark; Saatchi, Mahdi; Garrick, Dorian J; Schnabel, Robert D; Taylor, Jeremy F; Pollak, E John

2013-08-16

Although the efficacy of genomic predictors based on within-breed training looks promising, it is necessary to develop and evaluate across-breed predictors for the technology to be fully applied in the beef industry. The efficacies of genomic predictors trained in one breed and utilized to predict genetic merit in differing breeds based on simulation studies have been reported, as have the efficacies of predictors trained using data from multiple breeds to predict the genetic merit of purebreds. However, comparable studies using beef cattle field data have not been reported. Molecular breeding values for weaning and yearling weight were derived and evaluated using a database containing BovineSNP50 genotypes for 7294 animals from 13 breeds in the training set and 2277 animals from seven breeds (Angus, Red Angus, Hereford, Charolais, Gelbvieh, Limousin, and Simmental) in the evaluation set. Six single-breed and four across-breed genomic predictors were trained using pooled data from purebred animals. Molecular breeding values were evaluated using field data, including genotypes for 2227 animals and phenotypic records of animals born in 2008 or later. Accuracies of molecular breeding values were estimated based on the genetic correlation between the molecular breeding value and trait phenotype. With one exception, the estimated genetic correlations of within-breed molecular breeding values with trait phenotype were greater than 0.28 when evaluated in the breed used for training. Most estimated genetic correlations for the across-breed trained molecular breeding values were moderate (> 0.30). When molecular breeding values were evaluated in breeds that were not in the training set, estimated genetic correlations clustered around zero. Even for closely related breeds, within- or across-breed trained molecular breeding values have limited prediction accuracy for breeds that were not in the training set. For breeds in the training set, across- and within-breed trained molecular breeding values had similar accuracies. The benefit of adding data from other breeds to a within-breed training population is the ability to produce molecular breeding values that are more robust across breeds and these can be utilized until enough training data has been accumulated to allow for a within-breed training set.

Evidence-based Practices Addressed in Community-based Children’s Mental Health Clinical Supervision

PubMed Central

Accurso, Erin C.; Taylor, Robin M.; Garland, Ann F.

2013-01-01

Context Clinical supervision is the principal method of training for psychotherapeutic practice, however there is virtually no research on supervision practice in community settings. Of particular interest is the role supervision might play in facilitating implementation of evidence-based (EB) care in routine care settings. Objective This study examines the format and functions of clinical supervision sessions in routine care, as well as the extent to which supervision addresses psychotherapeutic practice elements common to EB care for children with disruptive behavior problems, who represent the majority of patients served in publicly-funded routine care settings. Methods Supervisors (n=7) and supervisees (n=12) from four publicly-funded community-based child mental health clinics reported on 130 supervision sessions. Results Supervision sessions were primarily individual in-person meetings lasting one hour. The most common functions included case conceptualization and therapy interventions. Coverage of practice elements common to EB treatments was brief. Discussion Despite the fact that most children presenting to public mental health services are referred for disruptive behavior problems, supervision sessions are infrequently focused on practice elements consistent with EB treatments for this population. Supervision is a promising avenue through which training in EB practices could be supported to improve the quality of care for children in community-based “usual care” clinics. PMID:24761163

Starlings uphold principles of economic rationality for delay and probability of reward.

PubMed

Monteiro, Tiago; Vasconcelos, Marco; Kacelnik, Alex

2013-04-07

Rationality principles are the bedrock of normative theories of decision-making in biology and microeconomics, but whereas in microeconomics, consistent choice underlies the notion of utility; in biology, the assumption of consistent selective pressures justifies modelling decision mechanisms as if they were designed to maximize fitness. In either case, violations of consistency contradict expectations and attract theoretical interest. Reported violations of rationality in non-humans include intransitivity (i.e. circular preferences) and lack of independence of irrelevant alternatives (changes in relative preference between options when embedded in different choice sets), but the extent to which these observations truly represent breaches of rationality is debatable. We tested both principles with starlings (Sturnus vulgaris), training subjects either with five options differing in food delay (exp. 1) or with six options differing in reward probability (exp. 2), before letting them choose repeatedly one option out of several binary and trinary sets of options. The starlings conformed to economic rationality on both tests, showing strong stochastic transitivity and no violation of the independence principle. These results endorse the rational choice and optimality approaches used in behavioural ecology, and highlight the need for functional and mechanistic enquiring when apparent violations of such principles are observed.

Starlings uphold principles of economic rationality for delay and probability of reward

PubMed Central

Monteiro, Tiago; Vasconcelos, Marco; Kacelnik, Alex

2013-01-01

Rationality principles are the bedrock of normative theories of decision-making in biology and microeconomics, but whereas in microeconomics, consistent choice underlies the notion of utility; in biology, the assumption of consistent selective pressures justifies modelling decision mechanisms as if they were designed to maximize fitness. In either case, violations of consistency contradict expectations and attract theoretical interest. Reported violations of rationality in non-humans include intransitivity (i.e. circular preferences) and lack of independence of irrelevant alternatives (changes in relative preference between options when embedded in different choice sets), but the extent to which these observations truly represent breaches of rationality is debatable. We tested both principles with starlings (Sturnus vulgaris), training subjects either with five options differing in food delay (exp. 1) or with six options differing in reward probability (exp. 2), before letting them choose repeatedly one option out of several binary and trinary sets of options. The starlings conformed to economic rationality on both tests, showing strong stochastic transitivity and no violation of the independence principle. These results endorse the rational choice and optimality approaches used in behavioural ecology, and highlight the need for functional and mechanistic enquiring when apparent violations of such principles are observed. PMID:23390098

Generalization of cross-modal stimulus equivalence classes: operant processes as components in human category formation.

PubMed Central

Lane, S D; Clow, J K; Innis, A; Critchfield, T S

1998-01-01

This study employed a stimulus-class rating procedure to explore whether stimulus equivalence and stimulus generalization can combine to promote the formation of open-ended categories incorporating cross-modal stimuli. A pretest of simple auditory discrimination indicated that subjects (college students) could discriminate among a range of tones used in the main study. Before beginning the main study, 10 subjects learned to use a rating procedure for categorizing sets of stimuli as class consistent or class inconsistent. After completing conditional discrimination training with new stimuli (shapes and tones), the subjects demonstrated the formation of cross-modal equivalence classes. Subsequently, the class-inclusion rating procedure was reinstituted, this time with cross-modal sets of stimuli drawn from the equivalence classes. On some occasions, the tones of the equivalence classes were replaced by novel tones. The probability that these novel sets would be rated as class consistent was generally a function of the auditory distance between the novel tone and the tone that was explicitly included in the equivalence class. These data extend prior work on generalization of equivalence classes, and support the role of operant processes in human category formation. PMID:9821680

Effects of Non-Symbolic Approximate Number Practice on Symbolic Numerical Abilities in Pakistani Children.

PubMed

Khanum, Saeeda; Hanif, Rubina; Spelke, Elizabeth S; Berteletti, Ilaria; Hyde, Daniel C

2016-01-01

Current theories of numerical cognition posit that uniquely human symbolic number abilities connect to an early developing cognitive system for representing approximate numerical magnitudes, the approximate number system (ANS). In support of this proposal, recent laboratory-based training experiments with U.S. children show enhanced performance on symbolic addition after brief practice comparing or adding arrays of dots without counting: tasks that engage the ANS. Here we explore the nature and generality of this effect through two brief training experiments. In Experiment 1, elementary school children in Pakistan practiced either a non-symbolic numerical addition task or a line-length addition task with no numerical content, and then were tested on symbolic addition. After training, children in the numerical training group completed the symbolic addition test faster than children in the line length training group, suggesting a causal role of brief, non-symbolic numerical training on exact, symbolic addition. These findings replicate and extend the core findings of a recent U.S. laboratory-based study to non-Western children tested in a school setting, attesting to the robustness and generalizability of the observed training effects. Experiment 2 tested whether ANS training would also enhance the consistency of performance on a symbolic number line task. Over several analyses of the data there was some evidence that approximate number training enhanced symbolic number line placements relative to control conditions. Together, the findings suggest that engagement of the ANS through brief training procedures enhances children's immediate attention to number and engagement with symbolic number tasks.

A systematic review of training programmes for recruiters to randomised controlled trials.

PubMed

Townsend, Daisy; Mills, Nicola; Savović, Jelena; Donovan, Jenny L

2015-09-28

Recruitment to randomised controlled trials (RCTs) is often difficult. Clinician related factors have been implicated as important reasons for low rates of recruitment. Clinicians (doctors and other health professionals) can experience discomfort with some underlying principles of RCTs and experience difficulties in conveying them positively to potential trial participants. Recruiter training has been suggested to address identified problems but a synthesis of this research is lacking. The aim of our study was to systematically review the available evidence on training interventions for recruiters to randomised trials. Studies that evaluated training programmes for trial recruiters were included. Those that provided only general communication training not linked to RCT recruitment were excluded. Data extraction and quality assessment were completed by two reviewers independently, with a third author where necessary. Seventeen studies of 9615 potentially eligible titles and abstracts were included in the review: three randomised controlled studies, two non-randomised controlled studies, nine uncontrolled pre-test/post-test studies, two qualitative studies, and a post-training questionnaire survey. Most studies were of moderate or weak quality. Training programmes were mostly set within cancer trials, and usually consisted of workshops with a mix of health professionals over one or two consecutive days covering generic and trial specific issues. Recruiter training programmes were well received and some increased recruiters' self-confidence in communicating key RCT concepts to patients. There was, however, little evidence that this training increased actual recruitment rates or patient understanding, satisfaction, or levels of informed consent. There is a need to develop recruiter training programmes that can lead to improved recruitment and informed consent in randomised trials.

Effects of Non-Symbolic Approximate Number Practice on Symbolic Numerical Abilities in Pakistani Children

PubMed Central

Khanum, Saeeda; Hanif, Rubina; Spelke, Elizabeth S.; Berteletti, Ilaria; Hyde, Daniel C.

2016-01-01

Current theories of numerical cognition posit that uniquely human symbolic number abilities connect to an early developing cognitive system for representing approximate numerical magnitudes, the approximate number system (ANS). In support of this proposal, recent laboratory-based training experiments with U.S. children show enhanced performance on symbolic addition after brief practice comparing or adding arrays of dots without counting: tasks that engage the ANS. Here we explore the nature and generality of this effect through two brief training experiments. In Experiment 1, elementary school children in Pakistan practiced either a non-symbolic numerical addition task or a line-length addition task with no numerical content, and then were tested on symbolic addition. After training, children in the numerical training group completed the symbolic addition test faster than children in the line length training group, suggesting a causal role of brief, non-symbolic numerical training on exact, symbolic addition. These findings replicate and extend the core findings of a recent U.S. laboratory-based study to non-Western children tested in a school setting, attesting to the robustness and generalizability of the observed training effects. Experiment 2 tested whether ANS training would also enhance the consistency of performance on a symbolic number line task. Over several analyses of the data there was some evidence that approximate number training enhanced symbolic number line placements relative to control conditions. Together, the findings suggest that engagement of the ANS through brief training procedures enhances children's immediate attention to number and engagement with symbolic number tasks. PMID:27764117

Use of Combined A-Train Observations to Validate GEOS Model Simulated Dust Distributions During NAMMA

NASA Technical Reports Server (NTRS)

Nowottnick, E.

2007-01-01

During August 2006, the NASA African Multidisciplinary Analyses Mission (NAMMA) field experiment was conducted to characterize the structure of African Easterly Waves and their evolution into tropical storms. Mineral dust aerosols affect tropical storm development, although their exact role remains to be understood. To better understand the role of dust on tropical cyclogenesis, we have implemented a dust source, transport, and optical model in the NASA Goddard Earth Observing System (GEOS) atmospheric general circulation model and data assimilation system. Our dust source scheme is more physically based scheme than previous incarnations of the model, and we introduce improved dust optical and microphysical processes through inclusion of a detailed microphysical scheme. Here we use A-Train observations from MODIS, OMI, and CALIPSO with NAMMA DC-8 flight data to evaluate the simulated dust distributions and microphysical properties. Our goal is to synthesize the multi-spectral observations from the A-Train sensors to arrive at a consistent set of optical properties for the dust aerosols suitable for direct forcing calculations.

Abstract numerical discrimination learning in rats.

PubMed

Taniuchi, Tohru; Sugihara, Junko; Wakashima, Mariko; Kamijo, Makiko

2016-06-01

In this study, we examined rats' discrimination learning of the numerical ordering positions of objects. In Experiments 1 and 2, five out of seven rats successfully learned to respond to the third of six identical objects in a row and showed reliable transfer of this discrimination to novel stimuli after being trained with three different training stimuli. In Experiment 3, the three rats from Experiment 2 continued to be trained to respond to the third object in an object array, which included an odd object that needed to be excluded when identifying the target third object. All three rats acquired this selective-counting task of specific stimuli, and two rats showed reliable transfer of this selective-counting performance to test sets of novel stimuli. In Experiment 4, the three rats from Experiment 3 quickly learned to respond to the third stimulus in object rows consisting of either six identical or six different objects. These results offer strong evidence for abstract numerical discrimination learning in rats.

Effects of cultural characteristics on building an emotion classifier through facial expression analysis

NASA Astrophysics Data System (ADS)

da Silva, Flávio Altinier Maximiano; Pedrini, Helio

2015-03-01

Facial expressions are an important demonstration of humanity's humors and emotions. Algorithms capable of recognizing facial expressions and associating them with emotions were developed and employed to compare the expressions that different cultural groups use to show their emotions. Static pictures of predominantly occidental and oriental subjects from public datasets were used to train machine learning algorithms, whereas local binary patterns, histogram of oriented gradients (HOGs), and Gabor filters were employed to describe the facial expressions for six different basic emotions. The most consistent combination, formed by the association of HOG filter and support vector machines, was then used to classify the other cultural group: there was a strong drop in accuracy, meaning that the subtle differences of facial expressions of each culture affected the classifier performance. Finally, a classifier was trained with images from both occidental and oriental subjects and its accuracy was higher on multicultural data, evidencing the need of a multicultural training set to build an efficient classifier.

Learn from every mistake! Hierarchical information combination in astronomy

NASA Astrophysics Data System (ADS)

Süveges, Maria; Fotopoulou, Sotiria; Coupon, Jean; Paltani, Stéphane; Eyer, Laurent; Rimoldini, Lorenzo

2017-06-01

Throughout the processing and analysis of survey data, a ubiquitous issue nowadays is that we are spoilt for choice when we need to select a methodology for some of its steps. The alternative methods usually fail and excel in different data regions, and have various advantages and drawbacks, so a combination that unites the strengths of all while suppressing the weaknesses is desirable. We propose to use a two-level hierarchy of learners. Its first level consists of training and applying the possible base methods on the first part of a known set. At the second level, we feed the output probability distributions from all base methods to a second learner trained on the remaining known objects. Using classification of variable stars and photometric redshift estimation as examples, we show that the hierarchical combination is capable of achieving general improvement over averaging-type combination methods, correcting systematics present in all base methods, is easy to train and apply, and thus, it is a promising tool in the astronomical ``Big Data'' era.

Detection and Genotyping of Human Papillomavirus in Self-Obtained Cervicovaginal Samples by Using the FTA Cartridge: New Possibilities for Cervical Cancer Screening ▿

PubMed Central

Lenselink, Charlotte H.; de Bie, Roosmarie P.; van Hamont, Dennis; Bakkers, Judith M. J. E.; Quint, Wim G. V.; Massuger, Leon F. A. G.; Bekkers, Ruud L. M.; Melchers, Willem J. G.

2009-01-01

This study assesses human papillomavirus (HPV) detection and genotyping in self-sampled genital smears applied to an indicating FTA elute cartridge (FTA cartridge). The study group consisted of 96 women, divided into two sample sets. All samples were analyzed by the HPV SPF10-Line Blot 25. Set 1 consisted of 45 women attending the gynecologist; all obtained a self-sampled cervicovaginal smear, which was applied to an FTA cartridge. HPV results were compared to a cervical smear (liquid based) taken by a trained physician. Set 2 consisted of 51 women who obtained a self-sampled cervicovaginal smear at home, which was applied to an FTA cartridge and to a liquid-based medium. DNA was obtained from the FTA cartridges by simple elution as well as extraction. Of all self-obtained samples of set 1, 62.2% tested HPV positive. The overall agreement between self- and physician-obtained samples was 93.3%, in favor of the self-obtained samples. In sample set 2, 25.5% tested HPV positive. The overall agreement for high-risk HPV presence between the FTA cartridge and liquid-based medium and between DNA elution and extraction was 100%. This study shows that HPV detection and genotyping in self-obtained cervicovaginal samples applied to an FTA cartridge is highly reliable. It shows a high level of overall agreement with HPV detection and genotyping in physician-obtained cervical smears and liquid-based self-samples. DNA can be obtained by simple elution and is therefore easy, cheap, and fast. Furthermore, the FTA cartridge is a convenient medium for collection and safe transport at ambient temperatures. Therefore, this method may contribute to a new way of cervical cancer screening. PMID:19553570

Detection and genotyping of human papillomavirus in self-obtained cervicovaginal samples by using the FTA cartridge: new possibilities for cervical cancer screening.

PubMed

Lenselink, Charlotte H; de Bie, Roosmarie P; van Hamont, Dennis; Bakkers, Judith M J E; Quint, Wim G V; Massuger, Leon F A G; Bekkers, Ruud L M; Melchers, Willem J G

2009-08-01

This study assesses human papillomavirus (HPV) detection and genotyping in self-sampled genital smears applied to an indicating FTA elute cartridge (FTA cartridge). The study group consisted of 96 women, divided into two sample sets. All samples were analyzed by the HPV SPF(10)-Line Blot 25. Set 1 consisted of 45 women attending the gynecologist; all obtained a self-sampled cervicovaginal smear, which was applied to an FTA cartridge. HPV results were compared to a cervical smear (liquid based) taken by a trained physician. Set 2 consisted of 51 women who obtained a self-sampled cervicovaginal smear at home, which was applied to an FTA cartridge and to a liquid-based medium. DNA was obtained from the FTA cartridges by simple elution as well as extraction. Of all self-obtained samples of set 1, 62.2% tested HPV positive. The overall agreement between self- and physician-obtained samples was 93.3%, in favor of the self-obtained samples. In sample set 2, 25.5% tested HPV positive. The overall agreement for high-risk HPV presence between the FTA cartridge and liquid-based medium and between DNA elution and extraction was 100%. This study shows that HPV detection and genotyping in self-obtained cervicovaginal samples applied to an FTA cartridge is highly reliable. It shows a high level of overall agreement with HPV detection and genotyping in physician-obtained cervical smears and liquid-based self-samples. DNA can be obtained by simple elution and is therefore easy, cheap, and fast. Furthermore, the FTA cartridge is a convenient medium for collection and safe transport at ambient temperatures. Therefore, this method may contribute to a new way of cervical cancer screening.

Muscle hypertrophy and fast fiber type conversions in heavy resistance-trained women.

PubMed

Staron, R S; Malicky, E S; Leonardi, M J; Falkel, J E; Hagerman, F C; Dudley, G A

1990-01-01

Twenty-four women completed a 20-week heavy-resistance weight training program for the lower extremity. Workouts were twice a week and consisted of warm-up exercises followed by three sets each of full squats, vertical leg presses, leg extensions, and leg curls. All exercises were performed to failure using 6-8 RM (repetition maximum). Weight training caused a significant increase in maximal isotonic strength (1 RM) for each exercise. After training, there was a decrease in body fat percentage (p less than 0.05), and an increase in lean body mass (p less than 0.05) with no overall change in thigh girth. Biopsies were obtained before and after training from the superficial portion of the vastus lateralis muscle. Sections were prepared for histological and histochemical examination. Six fiber types (I, IC, IIC, IIA, IIAB, and IIB) were distinguished following routine myofibrillar adenosine triphosphatase histochemistry. Areas were determined for fiber types I, IIA, and IIAB + IIB. The heavy-resistance training resulted in significant hypertrophy of all three groups: I (15%), IIA (45%), and IIAB + IIB (57%). These data are similar to those in men and suggest considerable hypertrophy of all major fiber types is also possible in women if exercise intensity and duration are sufficient. In addition, the training resulted in a significant decrease in the percentage of IIB with a concomitant increase in IIA fibers, suggesting that strength training may lead to fiber conversions.

Effects of off-axis elliptical training on reducing pain and improving knee function in individuals with patellofemoral pain

PubMed Central

Tsai, Liang-Ching; Lee, Song Joo; Yang, Aaron J.; Ren, Yupeng; Press, Joel M.; Zhang, Li-Qun

2014-01-01

Objective To examine whether an off-axis elliptical training program reduces pain and improves knee function in individuals with patellofemoral pain (PFP). Design Controlled laboratory study, pre-test-post-test. Setting University rehabilitation center. Participants Twelve adult subjects with PFP. Interventions Subjects with PFP completed an exercise program consisting of 18 sessions of lower extremity off-axis training using a custom-made elliptical trainer that allows frontal-plane sliding and transverse-plane pivoting of the footplates. Main Outcome Measures Changes in knee pain and function post-training and 6 weeks following training were evaluated using the Knee Injury and Osteoarthritis Outcome Score (KOOS) and International Knee Documentation Committee (IKDC) scores. Lower extremity off-axis control was assessed by pivoting and sliding instability, calculated as the root mean square (RMS) of the footplate pivoting angle and sliding distance during elliptical exercise. Subjects’ single-leg hop distance and proprioception in detecting lower extremity pivoting motion were also evaluated. Results Subjects reported significantly greater KOOS and IKDC scores (increased by 12–18 points) and hop distance (increased by 0.2 m) following training. A significant decrease in the pivoting and sliding RMS was also observed following training. Additionally, subjects with PFP demonstrated improved pivoting proprioception when tested under a minimum-weight-bearing position. Conclusions An off-axis elliptical training program was effective in enhancing lower extremity neuromuscular control on the frontal and transverse planes, reducing pain and improving knee function in persons with PFP. PMID:25591131

Team Training and Retention of Skills Acquired Above Real Time Training on a Flight Simulator

NASA Technical Reports Server (NTRS)

Ali, Syed Friasat; Guckenberger, Dutch; Crane, Peter; Rossi, Marcia; Williams, Mayard; Williams, Jason; Archer, Matt

2000-01-01

Above Real-Time Training (ARTT) is the training acquired on a real time simulator when it is modified to present events at a faster pace than normal. The experiments related to training of pilots performed by NASA engineers (Kolf in 1973, Hoey in 1976) and others (Guckenberger, Crane and their associates in the nineties) have shown that in comparison with the real time training (RTT), ARTT provides the following benefits: increased rate of skill acquisition, reduced simulator and aircraft training time, and more effective training for emergency procedures. Two sets of experiments have been performed; they are reported in professional conferences and the respective papers are included in this report. The retention of effects of ARTT has been studied in the first set of experiments and the use of ARTT as top-off training has been examined in the second set of experiments. In ARTT, the pace of events was 1.5 times the pace in RTT. In both sets of experiments, university students were trained to perform an aerial gunnery task. The training unit was equipped with a joystick and a throttle. The student acted as a nose gunner in a hypothetical two place attack aircraft. The flight simulation software was installed on a Universal Distributed Interactive Simulator platform supplied by ECC International of Orlando, Florida. In the first set of experiments, two training programs RTT or ART7 were used. Students were then tested in real time on more demanding scenarios: either immediately after training or two days later. The effects of ARTT did not decrease over a two day retention interval and ARTT was more time efficient than real time training. Therefore, equal test performance could be achieved with less clock-time spent in the simulator. In the second set of experiments three training programs RTT or ARTT or RARTT, were used. In RTT, students received 36 minutes of real time training. In ARTT, students received 36 minutes of above real time training. In RARTT, students received 18 minutes of real time training and 18 minutes of above real time training as top-off training. Students were then tested in real time on more demanding scenarios. The use of ARTT as top-off training after RTT offered better training than RTT alone or ARTT alone. It is, however, suggested that a similar experiment be conducted on a relatively more complex task with a larger sample of participants. Within the proposed duration of the research effort, the setting up of experiments and trial runs on using ARTT for team training were also scheduled but they could not be accomplished due to extra ordinary challenges faced in developing the required software configuration. Team training is, however, scheduled in a future study sponsored by NASA at Tuskegee University.

Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery

NASA Astrophysics Data System (ADS)

Ma, Lei; Cheng, Liang; Li, Manchun; Liu, Yongxue; Ma, Xiaoxue

2015-04-01

Unmanned Aerial Vehicle (UAV) has been used increasingly for natural resource applications in recent years due to their greater availability and the miniaturization of sensors. In addition, Geographic Object-Based Image Analysis (GEOBIA) has received more attention as a novel paradigm for remote sensing earth observation data. However, GEOBIA generates some new problems compared with pixel-based methods. In this study, we developed a strategy for the semi-automatic optimization of object-based classification, which involves an area-based accuracy assessment that analyzes the relationship between scale and the training set size. We found that the Overall Accuracy (OA) increased as the training set ratio (proportion of the segmented objects used for training) increased when the Segmentation Scale Parameter (SSP) was fixed. The OA increased more slowly as the training set ratio became larger and a similar rule was obtained according to the pixel-based image analysis. The OA decreased as the SSP increased when the training set ratio was fixed. Consequently, the SSP should not be too large during classification using a small training set ratio. By contrast, a large training set ratio is required if classification is performed using a high SSP. In addition, we suggest that the optimal SSP for each class has a high positive correlation with the mean area obtained by manual interpretation, which can be summarized by a linear correlation equation. We expect that these results will be applicable to UAV imagery classification to determine the optimal SSP for each class.

Trip optimization system and method for a train

DOEpatents

Kumar, Ajith Kuttannair; Shaffer, Glenn Robert; Houpt, Paul Kenneth; Movsichoff, Bernardo Adrian; Chan, David So Keung

2017-08-15

A system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives, the system including a locator element to determine a location of the train, a track characterization element to provide information about a track, a sensor for measuring an operating condition of the locomotive consist, a processor operable to receive information from the locator element, the track characterizing element, and the sensor, and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train.

Systematic review of skills transfer after surgical simulation-based training.

PubMed

Dawe, S R; Pena, G N; Windsor, J A; Broeders, J A J L; Cregan, P C; Hewett, P J; Maddern, G J

2014-08-01

Simulation-based training assumes that skills are directly transferable to the patient-based setting, but few studies have correlated simulated performance with surgical performance. A systematic search strategy was undertaken to find studies published since the last systematic review, published in 2007. Inclusion of articles was determined using a predetermined protocol, independent assessment by two reviewers and a final consensus decision. Studies that reported on the use of surgical simulation-based training and assessed the transferability of the acquired skills to a patient-based setting were included. Twenty-seven randomized clinical trials and seven non-randomized comparative studies were included. Fourteen studies investigated laparoscopic procedures, 13 endoscopic procedures and seven other procedures. These studies provided strong evidence that participants who reached proficiency in simulation-based training performed better in the patient-based setting than their counterparts who did not have simulation-based training. Simulation-based training was equally as effective as patient-based training for colonoscopy, laparoscopic camera navigation and endoscopic sinus surgery in the patient-based setting. These studies strengthen the evidence that simulation-based training, as part of a structured programme and incorporating predetermined proficiency levels, results in skills transfer to the operative setting. © 2014 BJS Society Ltd. Published by John Wiley & Sons Ltd.

Differences in Physiological Responses to Interval Training in Cyclists With and Without Interval Training Experience

PubMed Central

Hebisz, Rafal; Borkowski, Jacek; Zatoń, Marek

2016-01-01

Abstract The aim of this study was to determine differences in glycolytic metabolite concentrations and work output in response to an all-out interval training session in 23 cyclists with at least 2 years of interval training experience (E) and those inexperienced (IE) in this form of training. The intervention involved subsequent sets of maximal intensity exercise on a cycle ergometer. Each set comprised four 30 s repetitions interspersed with 90 s recovery periods; sets were repeated when blood pH returned to 7.3. Measurements of post-exercise hydrogen (H+) and lactate ion (LA-) concentrations and work output were taken. The experienced cyclists performed significantly more sets of maximal efforts than the inexperienced athletes (5.8 ± 1.2 vs. 4.3 ± 0.9 sets, respectively). Work output decreased in each subsequent set in the IE group and only in the last set in the E group. Distribution of power output changed only in the E group; power decreased in the initial repetitions of set only to increase in the final repetitions. H+ concentration decreased in the third, penultimate, and last sets in the E group and in each subsequent set in the IE group. LA- decreased in the last set in both groups. In conclusion, the experienced cyclists were able to repeatedly induce elevated levels of lactic acidosis. Power output distribution changed with decreased acid–base imbalance. In this way, this group could compensate for a decreased anaerobic metabolism. The above factors allowed cyclists experienced in interval training to perform more sets of maximal exercise without a decrease in power output compared with inexperienced cyclists. PMID:28149346

An accelerated training method for back propagation networks

NASA Technical Reports Server (NTRS)

Shelton, Robert O. (Inventor)

1993-01-01

The principal objective is to provide a training procedure for a feed forward, back propagation neural network which greatly accelerates the training process. A set of orthogonal singular vectors are determined from the input matrix such that the standard deviations of the projections of the input vectors along these singular vectors, as a set, are substantially maximized, thus providing an optimal means of presenting the input data. Novelty exists in the method of extracting from the set of input data, a set of features which can serve to represent the input data in a simplified manner, thus greatly reducing the time/expense to training the system.

Impact of a structured ICU training programme in resource-limited settings in Asia.

PubMed

Haniffa, Rashan; Lubell, Yoel; Cooper, Ben S; Mohanty, Sanjib; Alam, Shamsul; Karki, Arjun; Pattnaik, Rajya; Maswood, Ahmed; Haque, R; Pangeni, Raju; Schultz, Marcus J; Dondorp, Arjen M

2017-01-01

To assess the impact on ICU performance of a modular training program in three resource-limited general adult ICUs in India, Bangladesh, and Nepal. A modular ICU training programme was evaluated using performance indicators from June 2009 to June 2012 using an interrupted time series design with an 8 to 15 month pre-intervention and 18 to 24 month post-intervention period. ICU physicians and nurses trained in Europe and the USA provided training for ICU doctors and nurses. The training program consisted of six modules on basic intensive care practices of 2-3 weeks each over 20 months. The performance indicators consisting of ICU mortality, time to ICU discharge, rate at which patients were discharged alive from the ICU, discontinuation of mechanical ventilation or vasoactive drugs and duration of antibiotic use were extracted. Stepwise changes and changes in trends associated with the intervention were analysed. Pre-Training ICU mortality in Rourkela (India), and Patan (Nepal) Chittagong (Bangladesh), was 28%, 41% and 62%, respectively, compared to 30%, 18% and 51% post-intervention. The intervention was associated with a stepwise reduction in cumulative incidence of in-ICU mortality in Chittagong (adjusted subdistribution hazard ratio [aSHR] (95% CI): 0.62 (0.40, 0.97), p = 0.03) and Patan (aSHR 0.16 (0.06, 0.41), p<0.001), but not in Rourkela (aSHR: 1.17 (0.75, 1.82), p = 0.49). The intervention was associated with earlier discontinuation of vasoactive drugs at Rourkela (adjusted hazard ratio for weekly change [aHR] 1.08 (1.03, 1.14), earlier discontinuation of mechanical ventilation in Chittagong (aHR 2.97 (1.24, 7.14), p = 0.02), and earlier ICU discharge in Patan (aHR 1.87 (1.02, 3.43), p = 0.04). This structured training program was associated with a decrease in ICU mortality in two of three sites and improvement of other performance indicators. A larger cluster randomised study assessing process outcomes and longer-term indicators is warranted.

High-intensity body weight training is comparable to combined training in changes in muscle mass, physical performance, inflammatory markers and metabolic health in postmenopausal women at high risk for type 2 diabetes mellitus: A randomized controlled clinical trial.

PubMed

Martins, Fernanda Maria; de Paula Souza, Aletéia; Nunes, Paulo Ricardo Prado; Michelin, Márcia Antoniazi; Murta, Eddie Fernando Candido; Resende, Elisabete Aparecida Mantovani Rodrigues; de Oliveira, Erick Prado; Orsatti, Fábio Lera

2018-07-01

This study compared the effects of 12 weeks of high-intensity interval body weight training (HIBWT) with combined training (COMT; aerobic and resistance exercises on body composition, a 6-minute walk test (6MWT; physical performance), insulin resistance (IR) and inflammatory markers in postmenopausal women (PW) at high risk of type 2 diabetes mellitus (TDM2). In this randomized controlled clinical study, 16 PW at high risk of TDM2 were randomly allocated into two groups: HIBWT (n = 8) and COMT (n = 8). The HIBWT group performed a training protocol (length time ~28 min) consisting of ten sets of 60 s of high intensity exercise interspersed by a recovery period of 60 s of low intensity exercise. The COMT group performed a training protocol (length time ~60 min) consisting of a 30 min walk of moderate intensity following by five resistance exercises. All training sessions were performed in the university gym facility three days a week (no consecutive days) for 12 weeks. All outcomes (body composition, muscle function, and IR and inflammatory markers) were assessed at the baseline and at the end of the study. Both groups increased (P < 0.05) muscle mass index (MMI), 6MWT, and interleukin 1 receptor antagonist and decreased fasting glucose, glycated hemoglobin , Insulin, HOMA-IR, and monocyte chemoattractant protein-1 (trend, P = 0.056). HIBWT effects were indistinguishable (P > 0.05) from the effects of COMT. There was a significant (P < 0.05) interaction of time by the group in muscle strength, indicating that only the COMT increased the muscle strength. This study suggests that changes in HOMA, IL-1ra, 6MWT, and MMI with HITBW are similar when compared to COMT in PW at high risk of TDM2. The patients were part of a 12-week training study (ClinicalTrials.gov Identifier: NCT03200639). Copyright © 2018 Elsevier Inc. All rights reserved.

A feedback inclusive neuromuscular training program alters frontal plane kinematics.

PubMed

Greska, Eric K; Cortes, Nelson; Van Lunen, Bonnie L; Oñate, James A

2012-06-01

Anterior cruciate ligament (ACL) neuromuscular training programs have demonstrated beneficial effects in reducing ACL injuries, yet further evaluation of their effects on biomechanical measures across a sports team season is required to elucidate the specific factors that are modifiable. The purpose of this study was to evaluate the effects of a 10-week off-season neuromuscular training program on lower extremity kinematics. Twelve Division I female soccer players (age: 19.2 ± 0.8 years, height: 1.67 ± 0.1 m, weight: 60.2 ± 6.5 kg) performed unanticipated dynamic trials of a running stop-jump task pretraining and posttraining. Data collection was performed using an 8-camera Vicon system (Los Angeles, CA, USA) and 2 Bertec (Columbus, OH, USA) force plates. The 10-week training program consisted of resistance training 2 times per week and field training, consisting of plyometric, agility, and speed drills, 2 times per week. Repeated measures analyses of variance (ANOVAs) were used to assess the differences between pretraining and posttraining kinetics and kinematics of the hip, knee, and ankle at initial contact (IC), peak knee flexion (PKF), and peak stance. Repeated measures ANOVAs were also used to assess isometric strength differences pretraining and posttraining. The alpha level was set at 0.05 a priori. The training program demonstrated significant increases in left hip extension, left and right hip flexion, and right hip adduction isometric strength. At IC, knee abduction angle moved from an abducted to an adducted position (-1.48 ± 3.65° to 1.46 ± 3.86°, p = 0.007), and hip abduction angle increased (-6.05 ± 4.63° to -10.34 ± 6.83°, p = 0.007). Hip abduction angle at PKF increased (-2.23 ± 3.40° to 6.01 ± 3.82°, p = 0.002). The maximum knee extension moment achieved at peak stance increased from pretraining to posttraining (2.02 ± 0.32 to 2.38 ± 0.75 N·m·kg⁻¹, p = 0.027). The neuromuscular training program demonstrated a potential positive effect in altering mechanics that influence the risk of incurring an ACL injury.

Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-02-01

We propose a cross-domain, multi-task transfer learning framework to transfer knowledge learned from non-medical images by a deep convolutional neural network (DCNN) to medical image recognition task while improving the generalization by multi-task learning of auxiliary tasks. A first stage cross-domain transfer learning was initiated from ImageNet trained DCNN to mammography trained DCNN. 19,632 regions-of-interest (ROI) from 2,454 mass lesions were collected from two imaging modalities: digitized-screen film mammography (SFM) and full-field digital mammography (DM), and split into training and test sets. In the multi-task transfer learning, the DCNN learned the mass classification task simultaneously from the training set of SFM and DM. The best transfer network for mammography was selected from three transfer networks with different number of convolutional layers frozen. The performance of single-task and multitask transfer learning on an independent SFM test set in terms of the area under the receiver operating characteristic curve (AUC) was 0.78+/-0.02 and 0.82+/-0.02, respectively. In the second stage cross-domain transfer learning, a set of 12,680 ROIs from 317 mass lesions on DBT were split into validation and independent test sets. We first studied the data requirements for the first stage mammography trained DCNN by varying the mammography training data from 1% to 100% and evaluated its learning on the DBT validation set in inference mode. We found that the entire available mammography set provided the best generalization. The DBT validation set was then used to train only the last four fully connected layers, resulting in an AUC of 0.90+/-0.04 on the independent DBT test set.

An Exemplar-Based Multi-View Domain Generalization Framework for Visual Recognition.

PubMed

Niu, Li; Li, Wen; Xu, Dong; Cai, Jianfei

2018-02-01

In this paper, we propose a new exemplar-based multi-view domain generalization (EMVDG) framework for visual recognition by learning robust classifier that are able to generalize well to arbitrary target domain based on the training samples with multiple types of features (i.e., multi-view features). In this framework, we aim to address two issues simultaneously. First, the distribution of training samples (i.e., the source domain) is often considerably different from that of testing samples (i.e., the target domain), so the performance of the classifiers learnt on the source domain may drop significantly on the target domain. Moreover, the testing data are often unseen during the training procedure. Second, when the training data are associated with multi-view features, the recognition performance can be further improved by exploiting the relation among multiple types of features. To address the first issue, considering that it has been shown that fusing multiple SVM classifiers can enhance the domain generalization ability, we build our EMVDG framework upon exemplar SVMs (ESVMs), in which a set of ESVM classifiers are learnt with each one trained based on one positive training sample and all the negative training samples. When the source domain contains multiple latent domains, the learnt ESVM classifiers are expected to be grouped into multiple clusters. To address the second issue, we propose two approaches under the EMVDG framework based on the consensus principle and the complementary principle, respectively. Specifically, we propose an EMVDG_CO method by adding a co-regularizer to enforce the cluster structures of ESVM classifiers on different views to be consistent based on the consensus principle. Inspired by multiple kernel learning, we also propose another EMVDG_MK method by fusing the ESVM classifiers from different views based on the complementary principle. In addition, we further extend our EMVDG framework to exemplar-based multi-view domain adaptation (EMVDA) framework when the unlabeled target domain data are available during the training procedure. The effectiveness of our EMVDG and EMVDA frameworks for visual recognition is clearly demonstrated by comprehensive experiments on three benchmark data sets.

Computerized multiple image analysis on mammograms: performance improvement of nipple identification for registration of multiple views using texture convergence analyses

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Sahiner, Berkman; Hadjiiski, Lubomir M.; Paramagul, Chintana

2004-05-01

Automated registration of multiple mammograms for CAD depends on accurate nipple identification. We developed two new image analysis techniques based on geometric and texture convergence analyses to improve the performance of our previously developed nipple identification method. A gradient-based algorithm is used to automatically track the breast boundary. The nipple search region along the boundary is then defined by geometric convergence analysis of the breast shape. Three nipple candidates are identified by detecting the changes along the gray level profiles inside and outside the boundary and the changes in the boundary direction. A texture orientation-field analysis method is developed to estimate the fourth nipple candidate based on the convergence of the tissue texture pattern towards the nipple. The final nipple location is determined from the four nipple candidates by a confidence analysis. Our training and test data sets consisted of 419 and 368 randomly selected mammograms, respectively. The nipple location identified on each image by an experienced radiologist was used as the ground truth. For 118 of the training and 70 of the test images, the radiologist could not positively identify the nipple, but provided an estimate of its location. These were referred to as invisible nipple images. In the training data set, 89.37% (269/301) of the visible nipples and 81.36% (96/118) of the invisible nipples could be detected within 1 cm of the truth. In the test data set, 92.28% (275/298) of the visible nipples and 67.14% (47/70) of the invisible nipples were identified within 1 cm of the truth. In comparison, our previous nipple identification method without using the two convergence analysis techniques detected 82.39% (248/301), 77.12% (91/118), 89.93% (268/298) and 54.29% (38/70) of the nipples within 1 cm of the truth for the visible and invisible nipples in the training and test sets, respectively. The results indicate that the nipple on mammograms can be detected accurately. This will be an important step towards automatic multiple image analysis for CAD techniques.

Decision Tree Repository and Rule Set Based Mingjiang River Estuarine Wetlands Classifaction

NASA Astrophysics Data System (ADS)

Zhang, W.; Li, X.; Xiao, W.

2018-05-01

The increasing urbanization and industrialization have led to wetland losses in estuarine area of Mingjiang River over past three decades. There has been increasing attention given to produce wetland inventories using remote sensing and GIS technology. Due to inconsistency training site and training sample, traditionally pixel-based image classification methods can't achieve a comparable result within different organizations. Meanwhile, object-oriented image classification technique shows grate potential to solve this problem and Landsat moderate resolution remote sensing images are widely used to fulfill this requirement. Firstly, the standardized atmospheric correct, spectrally high fidelity texture feature enhancement was conducted before implementing the object-oriented wetland classification method in eCognition. Secondly, we performed the multi-scale segmentation procedure, taking the scale, hue, shape, compactness and smoothness of the image into account to get the appropriate parameters, using the top and down region merge algorithm from single pixel level, the optimal texture segmentation scale for different types of features is confirmed. Then, the segmented object is used as the classification unit to calculate the spectral information such as Mean value, Maximum value, Minimum value, Brightness value and the Normalized value. The Area, length, Tightness and the Shape rule of the image object Spatial features and texture features such as Mean, Variance and Entropy of image objects are used as classification features of training samples. Based on the reference images and the sampling points of on-the-spot investigation, typical training samples are selected uniformly and randomly for each type of ground objects. The spectral, texture and spatial characteristics of each type of feature in each feature layer corresponding to the range of values are used to create the decision tree repository. Finally, with the help of high resolution reference images, the random sampling method is used to conduct the field investigation, achieve an overall accuracy of 90.31 %, and the Kappa coefficient is 0.88. The classification method based on decision tree threshold values and rule set developed by the repository, outperforms the results obtained from the traditional methodology. Our decision tree repository and rule set based object-oriented classification technique was an effective method for producing comparable and consistency wetlands data set.